Items where Division is "Europe University of Atlantic > Research > Articles and books" and Year is [pin missing: value2]

2025

Article Subjects > Social Sciences Europe University of Atlantic > Research > Articles and books Abierto Español Esta obra, ambientada en la Revolución francesa, pertenece a la compilación Bunte Steine und Erzählungen (Piedras de colores y narraciones, traducido al español) del austriaco Adalbert Stifter. En ella, se plantea el tema moral de la doble naturaleza divina y salvaje que inevitablemente existe en cada uno de nosotros, independientemente de que se encuentre aún dormida, y a la que tenemos que resistirnos continuamente. metadata Quijano-Peña, Paula mail paula.quijano@uneatlantico.es (2025) Adalbert STIFTER, «Firme esperanza». Hermēneus. Revista de traducción e interpretación (26). pp. 631-637. ISSN 2530-609X

Article Subjects > Biomedicine Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production Abierto Inglés Disposal of antibiotics and antimicrobial-resistant enteric bacteria (ARB) into water from various sources is responsible for maintaining ARB in the environment. Relative prevalence and circulation of ARB may vary across water sources. We hypothesized that these ARBs with different resistance genes are distributed in various freshwater sources and are related to each other. We screened 155 enteric bacterial isolates from eight different water sources in Dhaka. The prevalence of ARB and MDR enteric bacteria in water was significantly associated (p value < 0.05) with the sources. The genotypic analysis of blaTEM, qnrB, tetA, mcr-1, and sul-1 revealed higher similarity of the isolates from freshwater with previously reported isolates from clinical samples. Water sources with direct exposure to antibiotics had a significantly higher frequency of genotypic and phenotypic resistance. This study calls for continuous monitoring of water sources and strengthening the treatment of antibiotic and ARB-containing effluents in Bangladesh. metadata Sharif, Nadim and Opu, Rubayet Rayhan and Saha, Tama and Khan, Afsana and Alzahrani, Fuad M. and Alsuwat, Meshari A. and Rivas Suárez, Roger Sarín and García Villena, Eduardo and Alzahrani, Khalid J. and Dey, Shuvra Kanti mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, eduardo.garcia@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2025) Antimicrobial resistant enteric bacteria are widely distributed among environmental water sources in Dhaka, Bangladesh. npj Clean Water, 8 (1). ISSN 2059-7037

Article Subjects > Biomedicine
Subjects > Nutrition Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Fasting–feeding timing is a crucial pattern implicated in the regulation of daily circadian rhythms. The interplay between sleep and meal timing underscores the importance of maintaining circadian alignment in order to avoid creating a metabolic environment conducive to carcinogenesis following the molecular and systemic disruption of metabolic performance and immune function. The chronicity of such a condition may support the initiation and progression of cancer through a variety of mechanisms, including increased oxidative stress, immune suppression, and the activation of proliferative signaling pathways. This review aims to summarize current evidence from human studies and provide an overview of the potential mechanisms underscoring the role of chrononutrition (including time-restricted eating) on cancer risk. Current evidence shows that the morning chronotype, suggesting an alignment between physiological circadian rhythms and eating timing, is associated with a lower risk of cancer. Also, early time-restricted eating and prolonged nighttime fasting were also associated with a lower risk of cancer. The current evidence suggests that the chronotype influences cancer risk through cell cycle regulation, the modulation of metabolic pathways and inflammation, and gut microbiota fluctuations. In conclusion, although there are no clear guidelines on this matter, emerging evidence supports the hypothesis that the role of time-related eating (i.e., time/calorie-restricted feeding and intermittent/periodic fasting) could potentially lead to a reduced risk of cancer. metadata Godos, Justyna and Currenti, Walter and Ferri, Raffaele and Lanza, Giuseppe and Caraci, Filippo and Frias-Toral, Evelyn and Guglielmetti, Monica and Ferraris, Cinzia and Lipari, Vivian and Carvajal Altamiranda, Stefanía and Galvano, Fabio and Castellano, Sabrina and Grosso, Giuseppe mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, vivian.lipari@uneatlantico.es, stefania.carvajal@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2025) Chronotype and Cancer: Emerging Relation Between Chrononutrition and Oncology from Human Studies. Nutrients, 17 (3). p. 529. ISSN 2072-6643

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés In the rapidly advanced and evolving information technology industry, adequate client engagement plays a critical role as it is very important to understand the client’s concerns, and requirements, have the records, authorizations, and go-ahead of previously agreed requirements, and provide the feasible solution accordingly. Previously multiple solutions have been proposed to enhance the efficiency of client engagement, but they lack traceability, trust, transparency, and conflict in agreements of previous contracts. Due to the lack of these shortcomings, the client requirement is getting delayed which is causing client escalations, integrity issues, project failure, and penalties. In this study, we proposed the UniferCollab framework to overcome the issues of collaboration between various teams, transparency, the record of client authorizations, and the go-ahead on previous developments by implementing blockchain technology. We store the data on the permissible network in the proposed approach. It allows us to compile all the requirements and information shared by clients on permissible blockchain to secure a large amount of data which enhances the traceability of all the requirements. All the authorizations from the client generate push notifications for any changes in their current system executed through smart contracts. It removes the ambiguity between various development teams if the client has only shared the requirement with one team. The data is stored in the decentralized network from where information is gathered which resolves the traceability, transparency, and trust issues. Lastly, evaluations involved a total of 800 hypertext transfer protocol (HTTP) requests tested using Postman with blockchain block sizes ranging from 0.568 KB to 550 KB and an average size increase of 280 KB was observed as new blocks were added. The longest chain in the network was observed during 800 repetitions of blockchain operations. Latency analysis revealed that delays in processing HTTP requests were influenced by decentralized node processing, local machine response times, and internet bandwidth through various experiments. Results show that the proposed framework resolves all client engagement issues in implementation between all stakeholders which enhances trust, and transparency improves client experience and helps us manage disputes effectively. metadata Farooq, Muhammad Shoaib and Irshad, Khurram and Riaz, Danish and Abdel Samee, Nagwan and Bautista Thompson, Ernesto and Gavilanes Aray, Daniel and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, ernesto.bautista@unini.edu.mx, daniel.gavilanes@uneatlantico.es, UNSPECIFIED (2025) Client engagement solution for post implementation issues in software industry using blockchain. Scientific Reports, 15 (1). ISSN 2045-2322

Article Subjects > Biomedicine Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Background Co-infection of dengue and COVID-19 has increased the health burden worldwide. We found a significant knowledge gap in epidemiology and risk factors of co-infection in Bangladesh. Methods This study included 2458 participants from Dhaka city from December 1, 2021, to November 30, 2023. We performed Kruskal-Walli’s test and χ2 test. Multivariable logistic regression was also performed. Results Co-infection of dengue and COVID-19 was found among 31% of the participants. Co-prevalence of dengue and COVID-19 was found in higher frequency in Jatrabari (14%), and Motijhil (11%). Severe (65%, p-value 0.001) and very severe (78%, p-value 0.005) symptoms were prevalent among the participants aged >50 years. Long-term illness was prevalent among the participants with co-infection (35%, 95% CI 33%- 36%) and COVID-19 (28%, 95% CI 26%- 30%). Co-infected participants had a higher frequency of heart damage (31.6%, p-value 0.005), brain fog (22%, p-value 0.03), and kidney damage (49.3%, p-value 0.001). Fever (100%) was the most prevalent symptom followed by weakness (89.6%), chills (82.4%), fatigue (81.4%), headache (80.6%), feeling thirsty (76.3%), myalgia (75%), pressure in the chest (69.1%), and shortness of breath (68.3%), respectively. Area of residence (OR 2.26, 95% CI 1.96-2.49, p-value 0.01), number of family members (OR 1.45, 95% CI 1.08-1.87, p-value <0.001), and population density (OR 2.43, 95% CI 2.15-3.01, p-value 0.001) were associated with higher odds of co-infection. We found that coinfected participants had a 4 times higher risk of developing severe health conditions (OR 4.22, 95% CI 4.11-4.67, p-value 0.02). Conclusions This is one of the early epidemiologic studies of co-infection of dengue and COVID-19 in Bangladesh. metadata Sharif, Nadim and Opu, Rubayet Rayhan and Khan, Afsana and Saha, Tama and Masud, Abdullah Ibna and Naim, Jannatin and Velázquez Martínez, Zaily Leticia and Osorio García, Carlos Manuel and Alsuwat, Meshari A and Alzahrani, Fuad M and Alzahrani, Khalid J and De la Torre Díez, Isabel and Dey, Shuvra Kanti mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, zaily.velazquez@unini.edu.mx, carlos.osorio@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2025) Clinical epidemiology of dengue and COVID-19 co-infection among the residents in Dhaka, Bangladesh, 2021-2023: A cross-sectional study. Open Forum Infectious Diseases. ISSN 2328-8957

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Efficient image retrieval from a variety of datasets is crucial in today's digital world. Visual properties are represented using primitive image signatures in Content Based Image Retrieval (CBIR). Feature vectors are employed to classify images into predefined categories. This research presents a unique feature identification technique based on suppression to locate interest points by computing productive sum of pixel derivatives by computing the differentials for corner scores. Scale space interpolation is applied to define interest points by combining color features from spatially ordered L2 normalized coefficients with shape and object information. Object based feature vectors are formed using high variance coefficients to reduce the complexity and are converted into bag-of-visual-words (BoVW) for effective retrieval and ranking. The presented method encompass feature vectors for information synthesis and improves the discriminating strength of the retrieval system by extracting deep image features including primitive, spatial, and overlayed using multilayer fusion of Convolutional Neural Networks(CNNs). Extensive experimentation is performed on standard image datasets benchmarks, including ALOT, Cifar-10, Corel-10k, Tropical Fruits, and Zubud. These datasets cover wide range of categories including shape, color, texture, spatial, and complicated objects. Experimental results demonstrate considerable improvements in precision and recall rates, average retrieval precision and recall, and mean average precision and recall rates across various image semantic groups within versatile datasets. The integration of traditional feature extraction methods fusion with multilevel CNN advances image sensing and retrieval systems, promising more accurate and efficient image retrieval solutions. metadata Chaki, Jyotismita and Shabir, Aiza and Ahmed, Khawaja Tehseen and Mahmood, Arif and Garay, Helena and Prado González, Luis Eduardo and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, helena.garay@uneatlantico.es, uis.prado@uneatlantico.es, UNSPECIFIED (2025) Deep image features sensing with multilevel fusion for complex convolution neural networks & cross domain benchmarks. PLOS ONE, 20 (3). e0317863. ISSN 1932-6203

Article Subjects > Teaching Europe University of Atlantic > Research > Articles and books Abierto Español Este artículo aborda la necesidad de capacitar a docentes en el enfoque AICLE (Aprendizaje Integrado de Contenidos y Lenguas Extranjeras) y presenta los resultados de un seminario realizado en inglés en la Università degli Studi di Palermo, Italia. A pesar de las dificultades lingüísticas enfrentadas por los estudiantes, el taller introdujo el concepto de AICLE, su historia, características y beneficios mediante el uso de vídeos y actividades prácticas. Los hallazgos indicaron que algunos estudiantes no habían cursado asignaturas con AICLE debido a que finalizaron sus estudios antes de 2013. Las materias enseñadas con AICLE incluían ciencias naturales, economía, historia y artes. Aunque algunos estudiantes no conocían previamente el enfoque AICLE, valoraron positivamente el seminario, considerándolo útil para sus futuras carreras en escuelas plurilingües. Las conclusiones resaltan la necesidad de extender la formación para abordar aspectos esenciales como el andamiaje y las estrategias de evaluación adaptadas. metadata Sánchez-Bejerano, Lucía mail lucia.sanchez@uneatlantico.es (2025) Desarrollando Competencias Docentes en AICLE: Experiencias y Desafíos en la Università degli Studi di Palermo. Revista de Innovación y Buenas Prácticas Docentes, 14 (1). pp. 94-101.

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés The agricultural industry is experiencing revolutionary changes through the latest advances in artificial intelligence and deep learning-based technologies. These powerful tools are being used for a variety of tasks including crop yield estimation, crop maturity assessment, and disease detection. The cotton crop is an essential source of revenue for many countries highlighting the need to protect it from deadly diseases that can drastically reduce yields. Early and accurate disease detection is quite crucial for preventing economic losses in the agricultural sector. Thanks to deep learning algorithms, researchers have developed innovative disease detection approaches that can help safeguard the cotton crop and promote economic growth. This study presents dissimilar state-of-the-art deep learning models for disease recognition including VGG16, DenseNet, EfficientNet, InceptionV3, MobileNet, NasNet, and ResNet models. For this purpose, real cotton disease data is collected from fields and preprocessed using different well-known techniques before using as input to deep learning models. Experimental analysis reveals that the ResNet152 model outperforms all other deep learning models, making it a practical and efficient approach for cotton disease recognition. By harnessing the power of deep learning and artificial intelligence, we can help protect the cotton crop and ensure a prosperous future for the agricultural sector. metadata Faisal, Hafiz Muhammad and Aqib, Muhammad and Rehman, Saif Ur and Mahmood, Khalid and Aparicio Obregón, Silvia and Calderón Iglesias, Rubén and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, silvia.aparicio@uneatlantico.es, ruben.calderon@uneatlantico.es, UNSPECIFIED (2025) Detection of cotton crops diseases using customized deep learning model. Scientific Reports, 15 (1). ISSN 2045-2322

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Background/Objectives: Sleep is a fundamental physiological function that plays a crucial role in maintaining health and well-being. The aim of this study was to assess dietary and lifestyle factors associated with adequate sleep duration in children and adolescents living in five Mediterranean countries. Methods: Parents of children and adolescents taking part in an initial survey for the DELICIOUS project were examined to assess their children’s dietary and eating habits (i.e., meal routines), as well as other lifestyle behaviors (i.e., physical activity levels, screen time, etc.) potentially associated with adequate sleep duration (defined as 8–10 h according to the National Sleep Foundation). The youth healthy eating index (Y-HEI) was used to assess the diet quality of children and adolescents. Multivariate logistic regression analyses were performed to calculate the odds ratios (ORs) and 95% confidence intervals (CIs), indicating the level of association between variables. Results: A total of 2011 individuals participated in the survey. The adolescents and children of younger parents reported being more likely to have inadequate sleep duration. Among eating behaviors, having breakfast (OR = 2.23, 95% CI: 1.62, 3.08) and eating at school (OR = 1.33, 95% CI: 1.01, 1.74) were associated with adequate sleep duration. In contrast, children eating alone, screen time, and eating outside of the home were less likely to have adequate sleep duration, although these findings were only significant in the unadjusted model. After adjusting for covariates, a better diet quality (OR = 1.63, 95% CI: 1.24, 2.16), including higher intake of fruits, meat, fish, and whole grains, was associated with adequate sleep duration. Conclusions: Adequate sleep duration seems to be highly influenced by factors related to individual lifestyles, family and school eating behaviors, as well as diet quality. metadata Godos, Justyna and Rosi, Alice and Scazzina, Francesca and Touriz Bonifaz, Maria Antonieta and Giampieri, Francesca and Abdelkarim, Osama and Ammar, Achraf and Aly, Mohamed and Frias-Toral, Evelyn and Pons, Juancho and Vázquez-Araújo, Laura and Alemany Iturriaga, Josep and Monasta, Lorenzo and Mata, Ana and Chacón, Adrián and Busó, Pablo and Grosso, Giuseppe mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, francesca.giampieri@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, josep.alemany@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2025) Diet, Eating Habits, and Lifestyle Factors Associated with Adequate Sleep Duration in Children and Adolescents Living in 5 Mediterranean Countries: The DELICIOUS Project. Nutrients, 17 (7). p. 1242. ISSN 2072-6643

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production Abierto Inglés Garlic is a horticultural product highly valued for its culinary and medicinal attributes. The aim of this study was to evaluate the composition of a garlic hydrophilic extract as well as the influence on redox biology, Alzheimer's Disease (AD) markers and aging, using Caenorhabditis elegans as experimental model. The extract was rich in sulfur compounds, highlighting the presence of other compounds like phenolics, and the antioxidant property was corroborated. Regarding AD markers, the acetylcholinesterase inhibitory capacity was demonstrated in vitro. Although the extract did not modify the amyloid β-induced paralysis degree, it was able to improve, in a dose-dependent manner, some locomotive parameters affected by the hyperphosphorylated tau protein in C. elegans. It could be related to the effect found on GFP-transgenic stains, mainly regarding to the increase in the gene expression of HSP-16.2. Moreover, an initial investigation into the aging process revealed that the extract successfully inhibited the accumulation of intracellular and mitochondrial reactive oxygen species in aged worms. These results provide valuable insights into the multifaceted impact of garlic extract, particularly in the context of aging and neurodegenerative processes. This study lays a foundation for further research avenues exploring the intricate molecular mechanisms underlying garlic effects and its translation into potential therapeutic interventions for age-related neurodegenerative conditions. metadata Navarro‐Hortal, María D. and Romero‐Marquez, Jose M. and Ansary, Johura and Montalbán‐Hernández, Cristina and Varela‐López, Alfonso and Giampieri, Francesca and Xiao, Jianbo and Calderón Iglesias, Rubén and Battino, Maurizio and Sánchez‐González, Cristina and Forbes‐Hernández, Tamara Y. and Quiles, José L. mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, francesca.giampieri@uneatlantico.es, UNSPECIFIED, ruben.calderon@uneatlantico.es, maurizio.battino@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, jose.quiles@uneatlantico.es (2025) Effects of a Garlic Hydrophilic Extract Rich in Sulfur Compounds on Redox Biology and Alzheimer's Disease Markers in Caenorhabditis Elegans. eFood, 6 (2). ISSN 2666-3066

Article Subjects > Physical Education and Sport Europe University of Atlantic > Research > Articles and books Cerrado Inglés Background The aging process leads to negative changes in various bodily systems, including the neuromuscular system. Strength training, is considered the best strategy to counteract these neuromuscular changes, preventing sarcopenia and frailty in older adults. Objective To compare the effects of strength training with elastic resistance and free weights on the muscle strength of knee extensors and flexors and functional performance in the older adults. Methods This was a randomised clinical study. Thirty-one participants of both sexes were allocated randomly into two groups: Training Group Free Weight (TGFW, n = 15) and Training Group with Elastic Resistance (TGER, n = 16). Two individuals were excluded and so, twenty-nine individuals were evaluated before and after eight weeks training protocol, which was performed three times a week. The determination of the training load was obtained using a protocol of 10 repetitions maximum. Results No significant differences were found in either the intra- or the inter-group comparisons, on functional performance and peak muscle strength. In the intra-groups (pre- and post-strength training), it was observed that both groups significantly increased the training load (10 RM) for the extensors (TGFW p = 0.0002; TGER p = 0.0001) and the knee flexors (TGFW p = 0.006; TGER p = 0.0001). Conclusion Both training protocols similarly were effective in increasing the training load observed by the 10 RM test of the extension and flexion movements of the knee. metadata Ferreira, Rafaela Zanin and Souza Gomes, Antonio Felipe and Ferreira Baldim, Marco Antonio and Alves, Ricardo Silva and Carvalho, Leonardo César and Simão, Adriano Prado mail UNSPECIFIED (2025) Effects of strength training with free weights and elastic resistance in older adults: A randomised clinical study. Journal of Bodywork and Movement Therapies, 41. pp. 48-55. ISSN 13608592

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés The process of image formulation uses semantic analysis to extract influential vectors from image components. The proposed approach integrates DenseNet with ResNet-50, VGG-19, and GoogLeNet using an innovative bonding process that establishes algorithmic channeling between these models. The goal targets compact efficient image feature vectors that process data in parallel regardless of input color or grayscale consistency and work across different datasets and semantic categories. Image patching techniques with corner straddling and isolated responses help detect peaks and junctions while addressing anisotropic noise through curvature-based computations and auto-correlation calculations. An integrated channeled algorithm processes the refined features by uniting local-global features with primitive-parameterized features and regioned feature vectors. Using K-nearest neighbor indexing methods analyze and retrieve images from the harmonized signature collection effectively. Extensive experimentation is performed on the state-of-the-art datasets including Caltech-101, Cifar-10, Caltech-256, Cifar-100, Corel-10000, 17-Flowers, COIL-100, FTVL Tropical Fruits, Corel-1000, and Zubud. This contribution finally endorses its standing at the peak of deep and complex image sensing analysis. A state-of-the-art deep image sensing analysis method delivers optimal channeling accuracy together with robust dataset harmonization performance. metadata Kanwal, Khadija and Ahmad, Khawaja Tehseen and Shabir, Aiza and Jing, Li and Garay, Helena and Prado González, Luis Eduardo and Karamti, Hanen and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, helena.garay@uneatlantico.es, uis.prado@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2025) Efficient CNN architecture with image sensing and algorithmic channeling for dataset harmonization. Scientific Reports, 15 (1). ISSN 2045-2322

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Cerrado Inglés The health benefits of mulberry fruit are closely associated with its phenolic compounds. However, the effects of enzymatic treatments on the digestion patterns of these compounds in mulberry juice remain largely unknown. This study investigated the impact of pectinase (PE), pectin lyase (PL), and cellulase (CE) on the release of phenolic compounds in whole mulberry juice. The digestion patterns were further evaluated using an in vitro simulated digestion model. The results revealed that PE significantly increased chlorogenic acid content by 77.8 %, PL enhanced cyanidin-3-O-glucoside by 20.5 %, and CE boosted quercetin by 44.5 %. Following in vitro digestion, the phenolic compound levels decreased differently depending on the treatment, while cyanidin-3-O-rutinoside content increased across all groups. In conclusion, the selected enzymes effectively promoted the release of phenolic compounds in mulberry juice. However, during gastrointestinal digestion, the degradation of phenolic compounds surpassed their enhanced release, with effects varying based on the compound's structure. metadata Luo, Peihuan and Ai, Jian and Wang, Qiongyao and Lou, Yihang and Liao, Zhiwei and Giampieri, Francesca and Battino, Maurizio and Sieniawska, Elwira and Bai, Weibin and Tian, Lingmin mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, francesca.giampieri@uneatlantico.es, maurizio.battino@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2025) Enzymatic treatment shapes in vitro digestion pattern of phenolic compounds in mulberry juice. Food Chemistry, 469. p. 142555. ISSN 03088146

Article Subjects > Physical Education and Sport Europe University of Atlantic > Research > Articles and books Abierto Español El balonmano es un deporte de cooperación-oposición, mediado por una sucesión de lanzamientos, agarres, desplazamientos y acciones breves e intensas. Este deporte requiere la ejecución de diversas acciones motrices y técnicas-tácticas que implican componentes específicos de fuerza. El objetivo de esta revisión sistemática es valorar la eficacia del entrenamiento de fuerza mediante el uso de bandas elásticas en jugadores jóvenes de balonmano. Siguiendo las directrices PRISMA, se realizaron búsquedas en las bases de datos Pubmed, Dialnet y Google Scholar. Se seleccionaron 5 estudios que analizaban los efectos del entrenamiento de fuerza mediante el uso de bandas elásticas en jugadores de balonmano de entre 13 y 26 años. Los resultados obtenidos en esta revisión presentan mejoras significativas en la fuerza, potencia y velocidad de lanzamiento, así como en acciones motrices específicas del balonmano. En conclusión, el entrenamiento de fuerza con bandas elásticas en jugadores jóvenes de balonmano tiene impactos positivos en el aumento de la capacidad de fuerza, fuerza explosiva, fuerza resistencia y potencia de la musculatura. Del mismo modo, ayuda a mejorar aspectos cruciales del rendimiento deportivo, incluyendo la velocidad de lanzamiento, desplazamiento y las acciones específicas del juego como saltos y cambios de dirección y ritmo. metadata Montes Salas, Carlos and Santiago, Marta Victoria and Pulgar, Susana and Heres, Miguel mail UNSPECIFIED, UNSPECIFIED, susana.pulgar@uneatlantico.es, UNSPECIFIED (2025) Evaluación de los efectos del entrenamiento de fuerza con bandas elásticas en jugadores jóvenes de balonmano. Revisión sistemática. E-balonmano com Journal Sports Science, 21 (1). pp. 131-142. ISSN 1885-7019

Article Subjects > Physical Education and Sport Europe University of Atlantic > Research > Articles and books Abierto Inglés The aim of this study was to compare the external load of each session along competitive microcycles on an elite futsal team, considering the positions and relationships of the players. The external load of 10 elite players from a First Division team in the Spanish Futsal League (age 27.5 ± 7 years, height 1.73 ± 0.05 m, weight 70.1 ± 3.8 kg) were recorded across 30 microcycles. The players’ external loads were monitored using OLIVER devices. To analyse the external load, Levene’s test was conducted to assess the homogeneity of variances, followed by one-way analysis of variance (ANOVA) to identify differences in dependent variables across the different microcycle days and player positions. Regarding external load during the microcycle, the day with the lowest external load was MD-1, and the days with the highest external load were MD-3 and MD-4. In addition, considering playing positions, pivots exhibited the lowest loads throughout the microcycle, whereas wingers and defenders exhibited the highest loads, depending on the variables analysed. By providing reference values from elite contexts, this study offers practical insights for S&C coaches to optimize microcycles. Furthermore, it contributes to workload management strategies within sport science and public health frameworks, promoting sustainable performance and athlete wellness in futsal. metadata Gadea-Uribarri, Héctor and Mainer-Pardos, Elena and Bores Arce, Ainhoa and Albalad-Aiguabella, Rafael and López-García, Sergio and Lago-Fuentes, Carlos mail UNSPECIFIED, UNSPECIFIED, ainhoa.bores@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, carlos.lago@uneatlantico.es (2025) External Load Variability in Elite Futsal: Positional Demands and Microcycle Structuring for Player Well-Being and Performance. Sports, 13 (1). p. 7. ISSN 2075-4663

Article Subjects > Biomedicine
Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Abierto Inglés Background: Flavonoids are naturally occurring dietary phytochemicals with significant antioxidant effects aside from several health benefits. People often consume them in combination with other food components. Compiling data establishes a link between bioactive flavonoids and prevention of several diseases in animal models, including cardiovascular diseases, diabetes, gut dysbiosis, and metabolic dysfunction-associated steatotic liver disease (MASLD). However, numerous clinical studies have demonstrated the ineffectiveness of flavonoids contradicting rodent models, thereby challenging the validity of using flavonoids as dietary supplements. Aim of Review: This review provides a clinical perspective to emphasize the effective roles of dietary flavonoids as well as to summarize their specific mechanisms in animals briefly. metadata Li, Xiaopeng and Xie, Enjun and Sun, Shumin and Shen, Jie and Ding, Yujin and Wang, Jiaqi and Peng, Xiaoyu and Zheng, Ruting and Farag, Mohamed A. and Xiao, Jianbo mail UNSPECIFIED (2025) Flavonoids for gastrointestinal tract local and associated systemic effects: A review of clinical trials and future perspectives. Journal of Advanced Research. ISSN 20901232

Article Subjects > Biomedicine
Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Background Deep learning models assist ophthalmologists in early detection of diseases from retinal images and timely treatment. Aim Owing to robust and accurate results from deep learning models, we aim to use convolutional neural network (CNN) to provide a non-invasive method for early detection of eye diseases. Methodology We used a hybridized CNN with deep learning (DL) based on two separate CNN blocks, to identify multiple Optic Disc Cupping, Diabetic Retinopathy, Media Haze, and Healthy images. We used the RFMiD dataset, which contains various categories of fundus images representing different eye diseases. Data augmenting, resizing, coping, and one-hot encoding are used among other preprocessing techniques to improve the performance of the proposed model. Color fundus images have been analyzed by CNNs to extract relevant features. Two CCN models that extract deep features are trained in parallel. To obtain more noticeable features, the gathered features are further fused utilizing the Canonical Correlation Analysis fusion approach. To assess the effectiveness, we employed eight classification algorithms: Gradient boosting, support vector machines, voting ensemble, medium KNN, Naive Bayes, COARSE- KNN, random forest, and fine KNN. Results With the greatest accuracy of 93.39%, the ensemble learning performed better than the other algorithms. Conclusion The accuracy rates suggest that the deep learning model has learned to distinguish between different eye disease categories and healthy images effectively. It contributes to the field of eye disease detection through the analysis of color fundus images by providing a reliable and efficient diagnostic system. metadata Ejaz, Sara and Zia, Hafiz U and Majeed, Fiaz and Shafique, Umair and Carvajal-Altamiranda, Stefanía and Lipari, Vivian and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, stefania.carvajal@uneatlantico.es, vivian.lipari@uneatlantico.es, UNSPECIFIED (2025) Fundus image classification using feature concatenation for early diagnosis of retinal disease. DIGITAL HEALTH, 11. ISSN 2055-2076

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés In the rapidly evolving landscape of artificial intelligence (AI) and the Internet of Things (IoT), the significance of device diagnostics and prognostics is paramount for guaranteeing the dependable operation and upkeep of intricate systems. The capacity to precisely diagnose and preemptively predict potential failures holds the potential to considerably amplify maintenance efficiency, diminish downtime, and optimize resource allocation. The wealth of information offered by telemetry data gathered from IoT devices presents an opportunity for diagnostics and prognostics applications. However, extracting valuable insights and making well-timed decisions from this extensive data reservoir remains a formidable challenge. This study proposes a novel AI-driven framework that integrates forward chaining and backward chaining algorithms to analyze telemetry data from IoT devices. The proposed methodology utilizes rule-based inference to detect real-time anomalies and predict potential future failures, providing a dual-layered approach for diagnostics and prognostics. The results show that the diagnostics engine using forward chaining detects real-time issues like “High Temperature” and “Low Pressure,” while the prognostics engine with backward chaining predicts potential future occurrences of these issues, enabling proactive prevention measures. The experimental results demonstrate that adopting this approach could offer valuable assistance to authorities and stakeholders. Accurate early diagnosis and prediction of potential failures have the capability to greatly improve maintenance efficiency, minimize downtime, and optimize cost. metadata Farooq, Muhammad Shoaib and Mir, Rizwan Pervez and Alvi, Atif and Tutusaus, Kilian and García Villena, Eduardo and Alrowais, Fadwa and Karamti, Hanen and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, kilian.tutusaus@uneatlantico.es, eduardo.garcia@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2025) Harnessing AI forward and backward chaining with telemetry data for enhanced diagnostics and prognostics of smart devices. Scientific Reports, 15 (1). ISSN 2045-2322

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Faced with anomalies in medical images, Deep learning is facing major challenges in detecting, diagnosing, and classifying the various pathologies that can be treated via medical imaging. The main challenges encountered are mainly due to the imbalance and variability of the data, as well as its complexity. The detection and classification of skin diseases is one such challenge that researchers are trying to overcome, as these anomalies present great variability in terms of appearance, texture, color, and localization, which sometimes makes them difficult to identify accurately and quickly, particularly by doctors, or by the various Deep Learning techniques on offer. In this study, an innovative and robust hybrid architecture is unveiled, underscoring the symbiotic potential of wavelet decomposition in conjunction with EfficientNet models. This approach integrates wavelet transformations with an EfficientNet backbone and incorporates advanced data augmentation, loss function, and optimization strategies. The model tested on the publicly accessible HAM10000 and ISIC2017 datasets has achieved an accuracy rate of 94.7%, and 92.2% respectively. metadata Aboulmira, Amina and Hrimech, Hamid and Lachgar, Mohamed and Hanine, Mohamed and Osorio García, Carlos Manuel and Méndez Mezquita, Gerardo and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, carlos.osorio@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2025) Hybrid Model with Wavelet Decomposition and EfficientNet for Accurate Skin Cancer Classification. Journal of Cancer, 16 (2). pp. 506-520. ISSN 1837-9664

Article Subjects > Physical Education and Sport Europe University of Atlantic > Research > Articles and books Abierto Español La actividad física practicada de forma regular antes de los primeros 36 meses de vida es un aspecto crucial a la hora de establecer las bases de las destrezas motoras necesarias en los niños, beneficiando de esta forma, su desarrollo físico, social y cognitivo. El objetivo de este estudio consistió en comprobar si la práctica de actividad física orientada durante la primera infancia presentaba beneficios en el desarrollo psicomotor en una muestra de niños con edades comprendidas entre los 0-3 años pertenecientes a la Comunidad de Cantabria. La muestra estuvo compuesta por dos escuelas infantiles que previamente promovían el movimiento libre: el grupo intervención, compuesto por alumnos del Centro Infantil Chiquitín (n=23) dónde se llevó a cabo un programa de actividad física orientada destinado a la mejora del desarrollo motor y el grupo control, compuesto por alumnos del Centro Infantil La Cucaña (n=14) a quiénes se instó a que mantuviesen las mismas actividades que hasta el momento. Ambos grupos realizaron un pre-post utilizando un test ad hoc, basado en los hitos evolutivos del Test de Denver. Los resultados demuestran mejoras en ambos grupos fruto del proceso de maduración biológica y fisiológica de los niños, aunque solamente fueron significativas (p < .001) en el grupo intervención en comparación con el grupo control. Se concluye que la práctica de actividad física orientada desde temprana edad puede tener un impacto positivo en el desarrollo motor de los niños, siendo determinante éste para la prevención de enfermedades crónicas y un buen estado de salud general. metadata Clemente Zubieta, Marina and Heres, Miguel and Pulgar, Susana mail UNSPECIFIED, miguel.heres@uneatlantico.es, susana.pulgar@uneatlantico.es (2025) Impacto de la actividad física orientada en el desarrollo psicomotor durante la primera infancia. Sportis. Scientific Journal of School Sport, Physical Education and Psychomotricity, 11 (2). pp. 1-21. ISSN 2386-8333

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Teaching > Teaching Materials
University of La Romana > Research > Scientific Production Abierto Inglés The agriculture field is the basis of a country’s change and financial system. Crops are the main source of revenue for the people. One of the farmer’s most challenging problems is choosing the right crops for their land. This critical decision has a direct impact on productivity and profit. Wrong crop selection not only reduces yields but also causes food shortages, creating more problems for farmers. The best crop depends on many parameters such as illustration humidity, N, K, P, pH, rainfall, and temperature of the soil. Getting advice from experts is not an easy task. This requires intelligent models in crop recommendations that use machine-learning models to suggest suitable crops for soil and other environmental conditions. Temperature, humidity, and pH are important data for growing crops in agriculture. In this study, we gather and preprocess relevant data. To recommend the most suitable crop, we propose a novel ensemble learning approach called RFXG based on random forest (RF) and extreme gradient boosting (XGB) to suggest the best crop out of the twenty-two major crops. To measure the capability of the proposed approach, various machine learning models are utilized including extra tree classifier, multilayer perceptron, RF, decision trees, logistic regression, and XGB classifiers. To get the best performance, optimization of hyperparameter, and K-fold cross-validation procedures are performed. Experimental outcomes show that the proposed RFXG technique achieves a recommendation accuracy is 98%. Specifically, the proposed solution provides immediate recommendations to help farmers make timely decisions. metadata Afzal, Hadeeqa and Amjad, Madiha and Raza, Ali and Munir, Kashif and Gracia Villar, Santos and Dzul López, Luis Alonso and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, santos.gracia@uneatlantico.es, luis.dzul@uneatlantico.es, UNSPECIFIED (2025) Incorporating soil information with machine learning for crop recommendation to improve agricultural output. Scientific Reports, 15 (1). ISSN 2045-2322

Article Subjects > Biomedicine
Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Cerrado Inglés Quercetin, a dietary flavonol enriched in food, regulates immune-related models through epigenetic modifications. However, few studies have explored the transmission of regulatory effects across generations to the progeny. Here, we selected Escherichia coli, a conditional pathogen capable of causing gastrointestinal infections or various localized tissue and organ infections under specific conditions, as the pathogenic strain to infect mice. We provide evidence that quercetin can not only induce responsiveness changes against systemic E. coli infection in directly exposed organisms, but also in subsequent generations through the transgenerational inheritance of epigenetic traits. Both parental male mice and their progeny exhibited cellular and phenotypic changes associated with metabolic alterations. Surprisingly, the male and female progeny of mice treated with quercetin (200 mg/kg) for six weeks negatively enhanced the survival rate under systemic E. coli (1 × 108 CFU/mL) infection, concurrent with an increase in bacterial loads in the liver and spleen. Serum TNF-α and IL-1β levels significantly increased post-infection in the progeny. Our results provide the first evidence of the inheritance of immunity driven by quercetin in mammals and the attenuation of protection against bacterial infection. metadata Zheng, Xuanyu and Huang, Wenqi and Farag, Mohamed A. and Xiao, Jianbo and Li, Chunlin mail UNSPECIFIED (2025) Intergenerational inheritance of quercetin-induced abnormal immunity in mice. Critical Reviews in Food Science and Nutrition. pp. 1-12. ISSN 1040-8398

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Background/Objectives: With the increasing life expectancy and, as a result, the aging of the global population, there has been a rise in the prevalence of chronic conditions, which can significantly impact individuals’ health-related quality of life, a multidimensional concept that comprises an individual’s physical, mental, and social wellbeing. While a balanced, nutrient-dense diet, such as Mediterranean diet, is widely recognized for its role in chronic disease prevention, particularly in reducing the risk of cardiovascular diseases and certain cancers, its potential benefits extend beyond these well-known effects, showing promise in improving physical and mental wellbeing, and promoting health-related quality of life. Methods: A systematic search of the scientific literature in electronic databases (Pubmed/Medline) was performed to identify potentially eligible studies reporting on the relation between adherence to the Mediterranean diet and health-related quality of life, published up to December 2024. Results: A total of 28 studies were included in this systematic review, comprising 13 studies conducted among the general population and 15 studies involving various types of patients. Overall, most studies showed a significant association between adherence to the Mediterranean diet and HRQoL, with the most significant results retrieved for physical domains of quality of life, suggesting that diet seems to play a relevant role in both the general population and people affected by chronic conditions with an inflammatory basis. Conclusions: Adherence to the Mediterranean diet provides significant benefits in preventing and managing various chronic diseases commonly associated with aging populations. Furthermore, it enhances the overall health and quality of life of aging individuals, ultimately supporting more effective and less invasive treatment approaches for chronic diseases. metadata Godos, Justyna and Guglielmetti, Monica and Ferraris, Cinzia and Frias-Toral, Evelyn and Dominguez Azpíroz, Irma and Lipari, Vivian and Di Mauro, Andrea and Furnari, Fabrizio and Castellano, Sabrina and Galvano, Fabio and Iacoviello, Licia and Bonaccio, Marialaura and Grosso, Giuseppe mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, irma.dominguez@unini.edu.mx, vivian.lipari@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2025) Mediterranean Diet and Quality of Life in Adults: A Systematic Review. Nutrients, 17 (3). p. 577. ISSN 2072-6643

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés This study emphasizes a multi-pronged approach to improving the energy efficiency of Multi-Effect Evaporator (MEE) in the paper industry. By incorporating traditional Energy-Saving Schemes (ESSs) and innovative renewable energy sources, the study demonstrates significant potential for reducing energy consumption and environmental impact, making it a decisive pathway for industrial sustainability. Key ESS strategies include Thermo-Vapor Compressors, Feed Preheaters, and Steam- and Feed-Split, which are employed to enhance Steam Economy (SE) to evaluate MEE efficiency. This integration results in a 67.93% enhancement in SE, reducing energy consumption significantly. Further, SE enhancement is achieved by integrating flash tanks that capture and reuse excess heat, which boosts SE by an additional 5.89%, leading to a total improvement of 73% without additional energy consumption. A significant innovation in the study is the integration of Linear Fresnel Reflectors (LFRs) based solar collectors and turbine-based wind energy sources to power the MEE and reduce reliance on conventional energy. This hybrid system decreases energy dependence by 62% for the base MEE and 34% for the hybrid MEE. The results are validated by comparing them with existing studies, confirming the effectiveness of the proposed method and offering significant energy and environment savings. metadata Pati, Smitarani and Navin, Nandan Kumar and Verma, Om Prakash and Singh, Dwesh Kumar and Sharma, Tarun Kumar and Agarwal, Saurabh and Gracia Villar, Santos and Dzul López, Luis Alonso and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, santos.gracia@uneatlantico.es, luis.dzul@uneatlantico.es, UNSPECIFIED (2025) Metaheuristic-based optimal energy assessment of hybrid multi-effect evaporator with synergy of solar and wind energy sources. Heliyon, 11 (2). e41653. ISSN 24058440

Article Subjects > Biomedicine
Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Abierto Inglés Background The gut-brain axis is a complex communication network that connects the gastrointestinal system with the central nervous system, significantly influencing various health outcomes, such as mental health, cognitive function, metabolic regulation, and immune responses. While traditional research models, particularly animal studies, have provided valuable insights, they often overlook the intricate and human-specific interactions within this axis. Consequently, translating findings from these models into clinical applications has been challenging. However, recent advancements in human-based Novel Approach Methodologies (NAMs), like organoids, organs-on-chip, and omic sciences, present innovative tools for investigating the gut-brain axis with improved accuracy and relevance to human physiology. These methodologies facilitate a deeper understanding of the molecular and cellular mechanisms by which nutritional interventions affect not only mental health but also a wider range of gut-brain-related health outcomes. Scope and approach: Scope and approach: This paper explores how NAMs are revolutionizing gut-brain axis research by providing more accurate models that replicate human physiology, thereby replacing less effective traditional approaches. Key findings and conclusion By using these advanced methods, researchers can produce detailed data that better mirror human responses to dietary components, resulting in more effective and personalized strategies for managing and enhancing gut-brain health. Future research should concentrate on utilizing NAMs to deepen our understanding of the gut-brain axis in nutritional science, which will ultimately lead to more targeted and effective health interventions for various conditions. metadata Cassotta, Manuela and Armas Diaz, Yasmany and Qi, Zexiu and Yang, Bei and Grosso, Giuseppe and Quiles, José L. and Battino, Maurizio and Godos, Justyna and Giampieri, Francesca mail manucassotta@gmail.com, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, maurizio.battino@uneatlantico.es, UNSPECIFIED, francesca.giampieri@uneatlantico.es (2025) Modernizing gut-brain axis research in nutritional Science: The role of human-centered New Approach Methodologies. Trends in Food Science & Technology, 159. p. 104980. ISSN 09242244

Article Subjects > Engineering
Subjects > Nutrition Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Maize is a staple crop worldwide, essential for food security, livestock feed, and industrial uses. Its health directly impacts agricultural productivity and economic stability. Effective detection of maize crop health is crucial for preventing disease spread and ensuring high yields. This study presents VG-GNBNet, an innovative transfer learning model that accurately detects healthy and infected maize crops through a two-step feature extraction process. The proposed model begins by leveraging the visual geometry group (VGG-16) network to extract initial pixel-based spatial features from the crop images. These features are then further refined using the Gaussian Naive Bayes (GNB) model and feature decomposition-based matrix factorization mechanism, which generates more informative features for classification purposes. This study incorporates machine learning models to ensure a comprehensive evaluation. By comparing VG-GNBNet's performance against these models, we validate its robustness and accuracy. Integrating deep learning and machine learning techniques allows VG-GNBNet to capitalize on the strengths of both approaches, leading to superior performance. Extensive experiments demonstrate that the proposed VG-GNBNet+GNB model significantly outperforms other models, achieving an impressive accuracy score of 99.85%. This high accuracy highlights the model's potential for practical application in the agricultural sector, where the precise detection of crop health is crucial for effective disease management and yield optimization. metadata Tanveer, Muhammad Usama and Munir, Kashif and Raza, Ali and Abualigah, Laith and Garay, Helena and Prado González, Luis Eduardo and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, helena.garay@uneatlantico.es, uis.prado@uneatlantico.es, UNSPECIFIED (2025) Novel Transfer Learning Approach for Detecting Infected and Healthy Maize Crop Using Leaf Images. Food Science & Nutrition, 13 (1). ISSN 2048-7177

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Wheat is one of the world’s most widely cultivated cereal crops and is a primary food source for a significant portion of the population. Wheat goes through several distinct developmental phases, and accurately identifying these stages is essential for precision farming. Determining wheat growth stages accurately is crucial for increasing the efficiency of agricultural yield in wheat farming. Preliminary research identified obstacles in distinguishing between these stages, negatively impacting crop yields. To address this, this study introduces an innovative approach, MobDenNet, based on data collection and real-time wheat crop stage recognition. The data collection utilized a diverse image dataset covering seven growth phases ‘Crown Root’, ‘Tillering’, ‘Mid Vegetative’, ‘Booting’, ‘Heading’, ‘Anthesis’, and ‘Milking’, comprising 4496 images. The collected image dataset underwent rigorous preprocessing and advanced data augmentation to refine and minimize biases. This study employed deep and transfer learning models, including MobileNetV2, DenseNet-121, NASNet-Large, InceptionV3, and a convolutional neural network (CNN) for performance comparison. Experimental evaluations demonstrated that the transfer model MobileNetV2 achieved 95% accuracy, DenseNet-121 achieved 94% accuracy, NASNet-Large achieved 76% accuracy, InceptionV3 achieved 74% accuracy, and the CNN achieved 68% accuracy. The proposed novel hybrid approach, MobDenNet, that synergistically merges the architectures of MobileNetV2 and DenseNet-121 neural networks, yields highly accurate results with precision, recall, and an F1 score of 99%. We validated the robustness of the proposed approach using the k-fold cross-validation. The proposed research ensures the detection of growth stages with great promise for boosting agricultural productivity and management practices, empowering farmers to optimize resource distribution and make informed decisions. metadata Naseer, Aisha and Amjad, Madiha and Raza, Ali and Munir, Kashif and Smerat, Aseel and Fabian Gongora, Henry and Uc Ríos, Carlos Eduardo and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, henry.gongora@uneatlantico.es, carlos.uc@unini.edu.mx, UNSPECIFIED (2025) Novel hybrid transfer neural network for wheat crop growth stages recognition using field images. Scientific Reports, 15 (1). ISSN 2045-2322

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Hand-drawn mathematical geometric shapes are geometric figures, such as circles, triangles, squares, and polygons, sketched manually using pen and paper or digital tools. These shapes are fundamental in mathematics education and geometric problem-solving, serving as intuitive visual aids for understanding complex concepts and theories. Recognizing hand-drawn shapes accurately enables more efficient digitization of handwritten notes, enhances educational tools, and improves user interaction with mathematical software. This research proposes an innovative machine learning algorithm for the automatic classification of mathematical geometric shapes to identify and interpret these shapes from handwritten input, facilitating seamless integration with digital systems. We utilized a benchmark dataset of mathematical shapes based on a total of 20,000 images with eight classes circle, kite, parallelogram, square, rectangle, rhombus, trapezoid, and triangle. We introduced a novel machine-learning algorithm CnN-RFc that uses convolution neural networks (CNN) for spatial feature extraction and the random forest classifier for probabilistic feature extraction from image data. Experimental results illustrate that using the CnN-RFc method, the Light Gradient Boosting Machine (LGBM) algorithm surpasses state-of-the-art approaches with high accuracy scores of 98% for hand-drawn shape classification. Applications of the proposed mathematical geometric shape classification algorithm span various domains, including education, where it enhances interactive learning platforms and provides instant feedback to students. metadata Alam, Aneeza and Raza, Ali and Thalji, Nisrean and Abualigah, Laith and Garay, Helena and Alemany Iturriaga, Josep and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, helena.garay@uneatlantico.es, josep.alemany@uneatlantico.es, UNSPECIFIED (2025) Novel transfer learning approach for hand drawn mathematical geometric shapes classification. PeerJ Computer Science, 11. e2652. ISSN 2376-5992

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés A bone fracture is a medical condition characterized by a partial or complete break in the continuity of the bone. Fractures are primarily caused by injuries and accidents, affecting millions of people worldwide. The healing process for a fracture can take anywhere from one month to one year, leading to significant economic and psychological challenges for patients. The detection of bone fractures is crucial, and radiographic images are often relied on for accurate assessment. An efficient neural network method is essential for the early detection and timely treatment of fractures. In this study, we propose a novel transfer learning-based approach called MobLG-Net for feature engineering purposes. Initially, the spatial features are extracted from bone X-ray images using a transfer model, MobileNet, and then input into a tree-based light gradient boosting machine (LGBM) model for the generation of class probability features. Several machine learning (ML) techniques are applied to the subsets of newly generated transfer features to compare the results. K-nearest neighbor (KNN), LGBM, logistic regression (LR), and random forest (RF) are implemented using the novel features with optimized hyperparameters. The LGBM and LR models trained on proposed MobLG-Net (MobileNet-LGBM) based features outperformed others, achieving an accuracy of 99% in predicting bone fractures. A cross-validation mechanism is used to evaluate the performance of each model. The proposed study can improve the detection of bone fractures using X-ray images. metadata Alam, Aneeza and Al-Shamayleh, Ahmad Sami and Thalji, Nisrean and Raza, Ali and Morales Barajas, Edgar Aníbal and Bautista Thompson, Ernesto and de la Torre Diez, Isabel and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, ernesto.bautista@unini.edu.mx, UNSPECIFIED, UNSPECIFIED (2025) Novel transfer learning based bone fracture detection using radiographic images. BMC Medical Imaging, 25 (1). ISSN 1471-2342

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés A bone fracture is a medical condition characterized by a partial or complete break in the continuity of the bone. Fractures are primarily caused by injuries and accidents, affecting millions of people worldwide. The healing process for a fracture can take anywhere from one month to one year, leading to significant economic and psychological challenges for patients. The detection of bone fractures is crucial, and radiographic images are often relied on for accurate assessment. An efficient neural network method is essential for the early detection and timely treatment of fractures. In this study, we propose a novel transfer learning-based approach called MobLG-Net for feature engineering purposes. Initially, the spatial features are extracted from bone X-ray images using a transfer model, MobileNet, and then input into a tree-based light gradient boosting machine (LGBM) model for the generation of class probability features. Several machine learning (ML) techniques are applied to the subsets of newly generated transfer features to compare the results. K-nearest neighbor (KNN), LGBM, logistic regression (LR), and random forest (RF) are implemented using the novel features with optimized hyperparameters. The LGBM and LR models trained on proposed MobLG-Net (MobileNet-LGBM) based features outperformed others, achieving an accuracy of 99% in predicting bone fractures. A cross-validation mechanism is used to evaluate the performance of each model. The proposed study can improve the detection of bone fractures using X-ray images. metadata Alam, Aneeza and Al-Shamayleh, Ahmad Sami and Thalji, Nisrean and Raza, Ali and Morales Barajas, Edgar Aníbal and Bautista Thompson, Ernesto and de la Torre Diez, Isabel and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, ernesto.bautista@unini.edu.mx, UNSPECIFIED, UNSPECIFIED (2025) Novel transfer learning based bone fracture detection using radiographic images. BMC Medical Imaging, 25 (1). ISSN 1471-2342

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Background: Nut consumption has been considered a potential protective factor against cognitive decline. The aim of this study was to test whether higher total and specific nut intake was associated with better cognitive status in a sample of older Italian adults. Methods: A cross-sectional analysis on 883 older adults (>50 y) was conducted. A 110-item food frequency questionnaire was used to collect information on the consumption of various types of nuts. The Short Portable Mental Status Questionnaire was used to assess cognitive status. Multivariate logistic regression analyses were performed to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for the association between nut intake and cognitive status after adjusting for potential confounding factors. Results: The median intake of total nuts was 11.7 g/day and served as a cut-off to categorize low and high consumers (mean intake 4.3 g/day vs. 39.7 g/day, respectively). Higher total nut intake was significantly associated with a lower prevalence of impaired cognitive status among older individuals (OR = 0.35, CI 95%: 0.15, 0.84) after adjusting for potential confounding factors. Notably, this association remained significant after additional adjustment for adherence to the Mediterranean dietary pattern as an indicator of diet quality, (OR = 0.32, CI 95%: 0.13, 0.77). No significant associations were found between cognitive status and specific types of nuts. Conclusions: Habitual nut intake is associated with better cognitive status in older adults. metadata Godos, Justyna and Giampieri, Francesca and Frias-Toral, Evelyn and Zambrano-Villacres, Raynier and Rojas Vistorte, Angel Olider and Yélamos Torres, Vanessa and Battino, Maurizio and Galvano, Fabio and Castellano, Sabrina and Grosso, Giuseppe mail UNSPECIFIED, francesca.giampieri@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, angel.rojas@uneatlantico.es, vanessa.yelamos@funiber.org, maurizio.battino@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2025) Nut Consumption Is Associated with Cognitive Status in Southern Italian Adults. Nutrients, 17 (3). p. 521. ISSN 2072-6643

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Ensuring safe and independent mobility for visually impaired individuals requires efficient obstacle detection systems. This study introduces an innovative smart knee glove, integrating machine learning technologies for real-time obstacle detection and alerting. The system is equipped with ultrasonic sensor, PIR sensor and a buzzer, with data processing managed by an Arduino Uno microcontroller. To enhance detection accuracy, multiple machine learning algorithms including Decision Tree (DT), Support Vector Machine (SVM), K-Nearest Neighbour (KNN), Random Forest (RF) and Gaussian Naïve Bayes (GNB) are utilized. A novel Voting Classifier ensemble method is proposed, effectively combining the strengths of these classifiers to maximize performance. Rigorous cross-fold validation ensures robust evaluation under varying conditions. Experimental results demonstrates that the system achieves an impressive 98.34% detection accuracy within a 4-meter range, with high precision, recall and F1 scores. These findings underscore the system’s reliability and potential to empower visually impaired users with safer, more autonomous navigation, marking a significant advancement in obstacle detection technologies. metadata Ikram, Sunnia and Bajwa, Imran Sarwar and Ikram, Amna and Díez, Isabel de la Torre and Uc Ríos, Carlos Eduardo and Kuc Castilla, Ángel Gabriel mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, carlos.uc@unini.edu.mx, UNSPECIFIED (2025) Obstacle Detection and Warning System for Visually Impaired Using IoT Sensors. IEEE Access, 13. pp. 35309-35321. ISSN 2169-3536

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production Abierto Inglés Alzheimer's disease (AD) involves β-amyloid plaques and tau hyperphosphorylation, driven by oxidative stress and neuroinflammation. Cyclooxygenase-2 (COX-2) and acetylcholinesterase (AChE) activities exacerbate AD pathology. Olive leaf (OL) extracts, rich in bioactive compounds, offer potential therapeutic benefits. This study aimed to assess the anti-inflammatory, anti-cholinergic, and antioxidant effects of three OL extracts (low, mid, and high bioactive content) in vitro and their protective effects against AD-related proteinopathies in Caenorhabditis elegans models. OL extracts were characterized for phenolic composition, AChE and COX-2 inhibition, as well as antioxidant capacity. Their effects on intracellular and mitochondrial reactive oxygen species (ROS) were tested in C. elegans models expressing human Aβ and tau proteins. Gene expression analyses examined transcription factors (DAF-16, skinhead [SKN]-1) and their targets (superoxide dismutase [SOD]-2, SOD-3, GST-4, and heat shock protein [HSP]-16.2). High-OL extract demonstrated superior AChE and COX-2 inhibition and antioxidant capacity. Low- and high-OL extracts reduced Aβ aggregation, ROS levels, and proteotoxicity via SKN-1/NRF-2 and DAF-16/FOXO pathways, whereas mid-OL showed moderate effects through proteostasis modulation. In tau models, low- and high-OL extracts mitigated mitochondrial ROS levels via SOD-2 but had limited effects on intracellular ROS levels. High-OL extract also increased GST-4 levels, whereas low and mid extracts enhanced GST-4 levels. OL extracts protect against AD-related proteinopathies by modulating oxidative stress, inflammation, and proteostasis. High-OL extract showed the most promise for nutraceutical development due to its robust phenolic profile and activation of key antioxidant pathways. Further research is needed to confirm long-term efficacy. metadata Romero‐Marquez, Jose M. and Navarro‐Hortal, María D. and Varela‐López, Alfonso and Calderón Iglesias, Rubén and Puentes, Juan G. and Giampieri, Francesca and Battino, Maurizio and Sánchez‐González, Cristina and Xiao, Jianbo and García‐Ruiz, Roberto and Sánchez, Sebastián and Forbes‐Hernández, Tamara Y. and Quiles, José L. mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, ruben.calderon@uneatlantico.es, UNSPECIFIED, francesca.giampieri@uneatlantico.es, maurizio.battino@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, jose.quiles@uneatlantico.es (2025) Olive Leaf Extracts With High, Medium, or Low Bioactive Compounds Content Differentially Modulate Alzheimer's Disease via Redox Biology. Food Frontiers. ISSN 2643-8429

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Abierto Inglés The One Health approach emphasizes the interconnectedness of human, animal, and environmental health, recognizing that the health of each is interdependent and influenced by shared ecosystems. Nutrition research plays a critical role in improving health outcomes across these domains, with implications for sustainability and food security. Organ-on-chip (OoC) technologies have emerged as innovative tools replicating key organ functions, supporting disease modeling, drug discovery, and personalized medicine. They also hold promise as alternatives to traditional animal models. This systematic review examines the potential of OoC technologies within the One Health framework and nutrition research, focusing on (1) their ability to replicate human and animal organ functions, (2) applications in food safety and ecotoxicology, and (3) their use in studying food components’ health effects. Challenges and future directions for adoption are also discussed. Although fully replicating the complexity of in vivo physiology remains a challenge, OoCs offer a promising platform to simulate organ functions and interactions. These systems hold significant potential for advancing food safety assessments, studying food impacts on health, and addressing sustainability in food systems. Challenges such as standardization, scalability, accessibility, and biases toward traditional models remain. Despite these hurdles, current advancements underscore the versatility and promise of OoCs, positioning them as valuable tools for driving innovation in nutrition research, food and feed safety, and ecotoxicology. With continued progress, OoCs are poised to make significant contributions to the goals of the One Health framework. metadata Cassotta, Manuela and Elexpuru Zabaleta, Maria and Sumalla Cano, Sandra and Diaz, Yasmany Armas and Giampieri, Francesca and Xiaobo, Zou and Zhang, Di and Grosso, Giuseppe and Battino, Maurizio mail manucassotta@gmail.com, maria.elexpuru@uneatlantico.es, sandra.sumalla@uneatlantico.es, UNSPECIFIED, francesca.giampieri@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, maurizio.battino@uneatlantico.es (2025) Organ‐on‐Chip: The Future of Nutrition Research in a One Health World. Food Frontiers. ISSN 2643-8429

Article Subjects > Psychology Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production Abierto Español La parentalidad positiva se presenta como un nuevo reto para la sociedad actual en la que profesionales de la salud mental y profesionales del ámbito psicoeducativo proporcionan a las familias programas parentales, para fortalecer el funcionamiento familiar y empoderar a los progenitores con relación a la crianza de sus hijos. El presente trabajo busca describir un conjunto de publicaciones científicas para tratar de buscar correlaciones significativas entre la parentalidad positiva y la prevención del fututo de la población infanto-juvenil con relación a su salud mental, a partir del fortalecimiento del funcionamiento familiar y la reducción del impacto de las experiencias adversas durante la infancia y la adolescencia. Se realizó una revisión sistemática exploratoria del tema con un cribado de los parámetros “Positive parenting AND Mental disorders AND Prevention” a través de artículos de investigación publicados en revistas arbitradas y con revisión en cuatro bases de datos —Redalyc, la Biblioteca Virtual de Salud (BVS), PubMed y SciencieDirect—, de las que se examinaron 229, 31, 20 y 48 artículos, respectivamente. Los artículos fueron seleccionados basándose en criterios predefinidos y haciendo uso de limitadores. Finalmente, se seleccionaron un total de 61 artículos que fueron analizados y categorizados en los apartados correspondientes planteados. metadata Morán del Castillo, Marta and Martín Ayala, Juan Luis mail marta.moran@master.uneatlantico.es, juan.martin@uneatlantico.es (2025) Parentalidad Positiva y Prevención de la Población infanto-juvenil con relación a su Salud Mental: una Revisión Actualizada. Psykhe (Santiago) (Online).

Article Subjects > Biomedicine Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés The aim of the present work was to determine the correlation between the State-Trait Anxiety Inventory (STAI) score and pupillary diameter and whether this correlation exists to develop a predictive model of anxiety with the pupillary diameter of students exposed to high-fidelity clinical simulation. This was a randomized, blinded, simulation-based clinical trial. The study was conducted at the Advanced Clinical Simulation Center, Faculty of Medicine, Valladolid University (Spain), from February 1 to April 15, 2023, and involved volunteer sixth-year undergraduate medical students. The STAI score, vital signs (oxygen saturation, perfusion index, blood pressure, heart rate, and temperature), and pupillary response were assessed. The primary outcomes were the delta (pre/postsimulation) of the state STAI and the delta of the pupillary diameter. Sixty-one sixth-year students fulfilled the inclusion criteria. There was no difference regarding the clinical scenario. There was a statistically significant correlation between the state STAI score and pupillary diameter. The predictive model had an AUC of 0.876, with the delta diameter of the pupillary being the only statistically significant variable for anxiety prediction. Our results showed that both the pupillary response and the STAI score allowed the identification of students with disabling anxiety. These results could pave the way for appropriate protocol development that allows for personalized tutoring of students with elevated anxiety levels. metadata Martín-Rodríguez, Francisco and Martín-Sánchez, Rafael and del Pozo Vegas, Carlos and Lopez-Izquierdo, Raúl and Martín-Conty, José Luis and Silva Alvarado, Eduardo René and Gracia Villar, Santos and Dzul López, Luis Alonso and Aparicio Obregón, Silvia and Calderón Iglesias, Rubén and Sanz-García, Ancor and Castro Villamor, Miguel Ángel mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, eduardo.silva@funiber.org, santos.gracia@uneatlantico.es, luis.dzul@uneatlantico.es, silvia.aparicio@uneatlantico.es, ruben.calderon@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2025) Pupilometer efficacy in monitoring anxiety in undergraduate medical students during high-fidelity clinical simulation. Scientific Reports, 15 (1). ISSN 2045-2322

Article Subjects > Biomedicine
Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Abierto Inglés Background/Objectives: Bioactive compounds possess the ability to maintain health and improve diseases by regulating inflammation and cell death processes. Pyroptosis is programmed cell death related to inflammation and exerts a critical role in the development and progression of different types of diseases. This narrative review aims to investigate and discuss the effects of dietary bioactive compounds on pyroptosis in different common human pathologies, such as inflammatory disease, bacterial infection, injury disease, cancer, diabetes and heart disease, etc. Method: Studies published in the major databases until December 2024 in English were considered, for a total of 50 papers. Results: The current evidence demonstrated that the bioactive compounds are able to regulate the pyroptosis process by modulating different inflammasome sensors (NLRP1, NLRP3, and AIM2), caspase family proteins (caspase-1, caspase-3, and caspase-11), and gasdermins (GSDMD and GSDME) in many pathological conditions related to inflammation, including cancer and cardiovascular diseases. Conclusions: Bioactive compounds have powerful potential to be the candidate drug for pyroptosis modulation in inflammatory diseases, even if more clinical studies are needed to confirm the effects and establish efficient doses for humans. metadata Yang, Bei and Qi, Zexiu and Armas Diaz, Yasmany and Cassotta, Manuela and Grosso, Giuseppe and Cianciosi, Danila and Zhang, Di and Zou, Xiaobo and Quiles, José L. and Battino, Maurizio and Giampieri, Francesca mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, manucassotta@gmail.com, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, jose.quiles@uneatlantico.es, maurizio.battino@uneatlantico.es, francesca.giampieri@uneatlantico.es (2025) Pyroptosis: A Novel Therapeutic Target for Bioactive Compounds in Human Disease Treatment? A Narrative Review. Nutrients, 17 (3). p. 461. ISSN 2072-6643

Article Subjects > Physical Education and Sport Europe University of Atlantic > Research > Articles and books Abierto Inglés (1) Background: Physical education at school is not able to meet the need for physical activity and sport (PA and S) established by international organizations, making it necessary to implement its practice outside school hours. This study aimed to find out the reasons for practicing, abandoning, and never having practiced PA and S outside school hours among students of Primary Education (PE) and Secondary Education (SE) in Cantabria (Spain). (2) Overall, 1038 students participated (349 from PE and 689 from SE), consisting of 512 boys and 526 girls between 10 and 17 years old (M = 12.92; SD = 1.92). They completed an ad hoc questionnaire with 21 questions about reasons for practicing (12 items), abandoning (3 items), and never having practiced PA and S (6 items) between the months of May and June 2024. (3) Results: As for active students, boys argue that they do so because of the influence of friends (p = 0.024), search for excitement (p = 0.002), liking PA and S (p = 0.022), and entertainment (p = 0.001). In PE, compared to SE, the most important factors are excitement (p < 0.001), health (p = 0.005), and liking PA and S (p = 0.022). Students who abandon PA and S do so because of the competitive environment (p = 0.001), with boys predominating. SE students highlight reluctance and laziness (p < 0.001) and the loss of liking PA and S (p = 0.013). Students who have never practiced PA and S do so because they do not find any sport motivating (p = 0.047) and because of reluctance and laziness (p = 0.018), especially among girls. In SE, the differences appear due to reluctance and laziness (p = 0.009) and because friends do not practice PA and S (p = 0.049). (4) Conclusions: Boys prioritize emotional and competency aspects, while girls focus on social aspects and happiness. PE students tend to participate in sports for fun and to improve their skills, while SE students tend to show reluctance and laziness and a loss of interest in PA and S. metadata Barcala Furelos, Martín and González-Gutiérrez, Iván and Rodríguez-Negro, Josune and Mecías-Calvo, Marcos and Navarro-Patón, Rubén mail martin.barcala@uneatlantico.es, ivan.gutierrez@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2025) Reasons for the Practice, Abandonment, and Non-Practice of Extracurricular Physical Activity and Sport Among Primary and Secondary School Students in Cantabria: What Can We Do About It? Sports, 13 (2). p. 44. ISSN 2075-4663

Article Subjects > Physical Education and Sport Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Background: Scientific research should be carried out to prevent sports injuries. For this purpose, new assessment technologies must be used to analyze and identify the risk factors for injury. The main objective of this systematic review was to compile, synthesize and integrate international research published in different scientific databases on Countermovement Jump (CMJ), Functional Movement Screen (FMS) and Tensiomyography (TMG) tests and technologies for the assessment of injury risk in sport. This way, this review determines the current state of the knowledge about this topic and allows a better understanding of the existing problems, making easier the development of future lines of research. Methodology: A structured search was carried out following the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines and the PICOS model until November 30, 2024, in the MEDLINE/PubMed, Web of Science (WOS), ScienceDirect, Cochrane Library, SciELO, EMBASE, SPORTDiscus and Scopus databases. The risk of bias was assessed and the PEDro scale was used to analyze methodological quality. Results: A total of 510 articles were obtained in the initial search. After inclusion and exclusion criteria, the final sample was 40 articles. These studies maintained a high standard of quality. This revealed the effects of the CMJ, FMS and TMG methods for sports injury assessment, indicating the sample population, sport modality, assessment methods, type of research design, study variables, main findings and intervention effects. Conclusions: The CMJ vertical jump allows us to evaluate the power capacity of the lower extremities, both unilaterally and bilaterally, detect neuromuscular asymmetries and evaluate fatigue. Likewise, FMS could be used to assess an athlete's basic movement patterns, mobility and postural stability. Finally, TMG is a non-invasive method to assess the contractile properties of superficial muscles, monitor the effects of training, detect muscle asymmetries, symmetries, provide information on muscle tone and evaluate fatigue. Therefore, they should be considered as assessment tests and technologies to individualize training programs and identify injury risk factors. metadata Velarde-Sotres, Álvaro and Bores-Cerezal, Antonio and Alemany Iturriaga, Josep and Calleja-González, Julio mail alvaro.velarde@uneatlantico.es, antonio.bores@uneatlantico.es, josep.alemany@uneatlantico.es, UNSPECIFIED (2025) Tensiomyography, functional movement screen and counter movement jump for the assessment of injury risk in sport: a systematic review of original studies of diagnostic tests. Frontiers in Sports and Active Living, 7. ISSN 2624-9367

Article Subjects > Psychology Europe University of Atlantic > Research > Articles and books Abierto Inglés There is still much resistance, myths, beliefs, and misconceptions regarding the seeking of mental health services for diagnosis and treatment. The objective was to validate an instrument to determine why Peruvian workers would not seek mental health professionals. In an instrumental study, literature was searched, and mental health professionals were asked about the most common reasons for not attending consultations. An expert panel undertook exploratory and confirmatory factor analyses (CFA), which were applied to a large population. Descriptive and instrumental statistics were used for the data. The 20 experts gave excellent ratings to the initial questions. In the pilot (250 people), it was confirmed that all questions had saturations >0.40. The item modification technique was also performed, eliminating six questions. With the CFA in 1312 respondents, it was seen that the goodness-of-fit indices were not adequate for three questions, then the index modification technique was used, achieving a satisfactory factorial structure model (χ2 = 61.497; df = 9; p < 0.001; RMR = 0.015; TLI = 0.984; CFI = 0.990, and RMSEA = 0.067). A scale of six questions was validated to measure the most important reasons why Peruvian workers do not want to attend mental health consultations. metadata Mejia, Christian R. and Paucar, Medally C. and Mamani-Benito, Oscar and Requena, Tatiana and Castillo-Vilela, Nino and Alvarez-Risco, Aldo and Armada, Jose and Ramos-Quispe, Teresa and Palomino-Vargas, Victor and Davies, Neal M. and Del-Aguila-Arcentales, Shyla and Yáñez, Jaime A. mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, jaime.yanez@unini.edu.mx (2025) Understanding the reasons to avoid seeking mental health professionals: Validation of the MITOS-MENTAL questionnaire in Peru population. Acta Psychologica, 254. p. 104858. ISSN 00016918

Article Subjects > Biomedicine
Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Objectives: Mechanical ventilator plays a vital role in saving millions of lives. Patients with COVID-19 symptoms need a ventilator to survive during the pandemic. Studies have reported that the mortality rates rise from 50% to 97% in those requiring mechanical ventilation during COVID-19. The pumping of air into the patient’s lungs using a ventilator requires a particular air pressure. High or low ventilator pressure can result in a patient’s life loss as high air pressure in the ventilator causes the patient lung damage while lower pressure provides insufficient oxygen. Consequently, precise prediction of ventilator pressure is a task of great significance in this regard. The primary aim of this study is to predict the airway pressure in the ventilator respiratory circuit during the breath. Methods: A novel hybrid ventilator pressure predictor (H-VPP) approach is proposed. The ventilator exploratory data analysis reveals that the high values of lung attributes R and C during initial time step values are the prominent causes of high ventilator pressure. Results: Experiments using the proposed approach indicate H-VPP achieves a 0.78 R2, mean absolute error of 0.028, and mean squared error of 0.003. These results are better than other machine learning and deep learning models employed in this study. Conclusion: Extensive experimentation indicates the superior performance of the proposed approach for ventilator pressure prediction with high accuracy. Furthermore, performance comparison with state-of-the-art studies corroborates the superior performance of the proposed approach. metadata Raza, Ali and Rustam, Furqan and Siddiqui, Hafeez Ur Rehman and Soriano Flores, Emmanuel and Vidal Mazón, Juan Luis and de la Torre Díez, Isabel and Ripoll, María Asunción Vicente and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, emmanuel.soriano@uneatlantico.es, juanluis.vidal@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2025) Ventilator pressure prediction employing voting regressor with time series data of patient breaths. Health Informatics Journal, 31 (1). ISSN 1460-4582

Article Subjects > Biomedicine Europe University of Atlantic > Research > Articles and books Abierto Inglés Background/Objectives: As probiotics gain prominence in the prevention and treatment of intestinal diseases, their protective effects against pathogens and influence on host health have drawn significant attention. This study investigates the genomic characteristics and functional potential of Pediococcus acidilactici XJ-24 (XJ-24) in the prevention of Listeria monocytogenes (LM) infection in mice. Methods/Results: Whole-genome analysis confirmed the safety and probiotic properties of XJ-24, including acid and bile salt tolerance, antimicrobial activity, and safety. In vivo, C57BL/6 mice challenges indicated that XJ-24 significantly reduced LM colonization, suppressed pro-inflammatory cytokines (IL-1β, IL-6, TNF-α, IFN-γ), alleviated colon and spleen tissue damage, and maintained intestinal barrier integrity by upregulating tight junction proteins (Occludin, Claudin-1, ZO-1). Moreover, XJ-24 modulated gut microbiota composition by increasing beneficial taxa while reducing harmful bacteria. Correlation analysis highlighted a positive association between Lachnospiraceae and tight junction proteins. Conclusions: These findings demonstrate the potential of XJ-24 as a functional probiotic for preventing LM infection and provide a basis for further clinical exploration. metadata Hu, Weizhong and Zhou, Shuxin and Ibrahim, Amel and Li, Guannan and Awad, Sameh and Ramos-Vivas, José and Kan, Jianquan and Du, Muying mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, jose.ramos@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2025) Whole Genome Analysis of Pediococcus acidilactici XJ-24 and Its Role in Preventing Listeria monocytogenes ATCC® 19115TM Infection in C57BL/6 Mice. Antibiotics, 14 (3). p. 323. ISSN 2079-6382

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books Abierto Inglés Steganography is used to hide sensitive types of data including images, audio, text, and videos in an invisible way so that no one can detect it. Image-based steganography is a technique that uses images as a cover media for hiding and transmitting sensitive information over the internet. However, image-based steganography is a challenging task due to transparency, security, computational efficiency, tamper protection, payload, etc. Recently, different image steganography methods have been proposed but most of them have reliability issues. Therefore, to solve this issue, we propose an efficient technique based on the Least Significant Bit (LSB). The LSB substitution method minimizes the error rate in the embedding process and is used to achieve greater reliability. Our proposed image-based steganography algorithm incorporates LSB substitution with Magic Matrix, Multi-Level Encryption Algorithm (MLEA), Secret Key (SK), and transposition, flipping. We performed several experiments and the results show that our proposed technique is efficient and achieves efficient results. We tested a total of 165 different RGB images of various dimensions and sizes of hidden information, using various Quality Assessment Metrics (QAMs); A name of few are; Normalized Cross Correlation (NCC), Image Fidelity (IF), Peak Signal Noise Ratio (PSNR), Root Mean Square Error (RMSE), Quality Index (QI), Correlation Coefficient (CC), Structural Similarity Index (SSIM), Mean Square Error (MSE), Entropy, Contrast, and Homogeneity, Image Histogram (IH). We also conducted a comparative analysis with some existing methods as well as security analysis which showed better results. The achieved result demonstrates significant improvements over the current state-of-the-art methods. metadata Rahman, Shahid and uddin, Jamal and Hussain, Hameed and Shah, Sabir and Salam, Abdu and Amin, Farhan and de la Torre Díez, Isabel and Ramírez-Vargas, Debora L. and Martínez Espinosa, Julio César mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, debora.ramirez@unini.edu.mx, ulio.martinez@unini.edu.mx (2025) A novel and efficient digital image steganography technique using least significant bit substitution. Scientific Reports, 15 (1). ISSN 2045-2322

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books Cerrado Inglés Background Endometriosis is one of the causes of female infertility, with some studies estimating its prevalence at around 10 % of reproductive-age women worldwide and between 30 and 50 % in symptomatic women. However, its diagnosis is complex and often delayed, highlighting the need for more accessible and accurate diagnostic methods. The difficulty lies in its diverse etiology and the variability of symptoms among those affected. Methods This study proposes a predictive model based on supervised machine learning for the early identification of endometriosis, providing support for decision-making by healthcare professionals. For this purpose, an anonymised dataset of 5,143 female patients diagnosed with endometriosis at the private fertility clinic Inebir was used. The model integrates clinical records and genetic analysis through supervised machine learning algorithms, focusing on clinical variables and pathogenic and potentially pathogenic genetic variants. Results The developed predictive model achieves high accuracy in identifying the presence of endometriosis, highlighting the importance of combining clinical and genetic data in diagnosis. The integration of this data into the DELFOS platform, a clinical decision support system, demonstrates the utility of machine learning in improving the diagnosis of endometriosis. Conclusions The findings underscore the potential of clinical and genetic factors in the early diagnosis of endometriosis using supervised machine learning algorithms. This study contributes to the classification of clinical variables that influence endometriosis, offering a valuable tool for clinicians in making therapeutic and management decisions for their female patients. metadata Enamorado-Díaz, Elena and Morales-Trujillo, Leticia and García-García, Julián-Alberto and Marcos Rodríguez, Ana Teresa and Navarro-Pando, José Manuel and Escalona-Cuaresma, María-José mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, anateresa.marcos@uneatlantico.es, jose.navarro@uneatlantico.es, UNSPECIFIED (2025) A novel machine learning-based proposal for early prediction of endometriosis disease. Expert Systems with Applications, 271. p. 126621. ISSN 09574174

2024

Article Subjects > Biomedicine
Subjects > Physical Education and Sport Europe University of Atlantic > Research > Articles and books Cerrado Inglés INTRODUCTION: Patients with metastatic breast cancer (mBC) often experience cancer- and treatment-related side effects that can impair daily life activities and health-related quality of life (HRQoL). Interventions are needed that improve HRQoL by alleviating fatigue and other side effects during palliative BC cancer treatment. Recent evidence-based international guidelines (ASCO, ACSM) recommend exercise for patients with BC during adjuvant treatment for reducing side effects. However, evidence of the effectiveness of exercise in patients with mBC is scarce. The PREFERABLE-EFFECT study (NCT04120298) was designed to assess the effects of a 9-month supervised exercise program in patients with mBC on fatigue, HRQoL, and other cancer- and treatment-related side effects. METHODS: PREFERABLE-EFFECT is a multinational, randomized controlled trial including patients with mBC from five European countries (Germany, Poland, Spain, Sweden, The Netherlands) and Australia. Participants were randomly assigned to usual care or an individualized, structured exercise program consisting of aerobic, resistance, and balance training. The first six months included twice weekly supervised exercise sessions of one hour. In the last three months, one supervised session was replaced by an unsupervised session, supplemented by an exercise App. All participants received general exercise advice (physical activity ≥ 30 min/day) and an activity tracker. Our primary outcomes, physical fatigue (subscale of the EORTC QLQ-FA12) and HRQoL (summary score of the EORTC QLQ-C30), were assessed at baseline, 3, 6, and 9 months. Among other physical fitness outcomes, maximal short exercise capacity was assessed with the Steep Ramp Test. The intervention effects (intention-to-treat) were determined by comparing the change from baseline to 3, 6 (i.e., primary endpoint) and 9 months between groups using separate mixed models for repeated measures, adjusted for baseline values of the outcome variable and stratification factors (mBC line of treatment (1st/2nd vs. 3rd or higher) and study center). A significant improvement of either or both primary outcomes (applying the Bonferroni-Holm method) was considered as successful. RESULTS: Between 2019-2022, we included 357 patients with mBC, with 178 patients randomized to the exercise intervention and 179 to usual care. Patients were, on average, 55.4 years of age (SD=11.1), most patients received 1st or 2nd line of treatment at study enrollment (74.8%) and had bone metastases (73.9%). At 6 months (primary endpoint), participation in the exercise intervention resulted in statistically significant positive effects on both primary outcomes, compared to usual care: physical fatigue was lower (mean difference: -5.3, 95% CI -10.0; -0.6, p=0.027, effect size (ES)=0.22) and HRQoL was better (+4.8, 95% CI 2.2; 7.4, p=0.0003, ES=0.33). Beneficial effects were also found at 3 months (physical fatigue: -3.4, -7.8; 1.0, ES=0.14 and QoL: 3.9, 1.5; 6.3, ES=0.27) and 9 months (physical fatigue: -5.6, -10.9; -0.4, ES=0.24 and QoL: +4.3, 1.4; 7.3, ES=0.31). Further, at the primary endpoint, we found positive exercise effects on physical fitness (+24.3 Watts, 15.5; 33.1, ES=0.42) and numerous QLQ-C30 scales, including social functioning (+5.5, 0.2; 10.8, ES=0.20), pain (-7.1, -12.1; -1.9, ES=0.28) and dyspnea (-7.6, -12.2; -3.0, ES=0.28). Two SAEs occurred (one wrist fracture and one sacral stress fracture), neither related to bone metastases. CONCLUSION: This large multinational study demonstrated significant beneficial effects of a supervised exercise intervention offered during palliative treatment on mBC patients’ fatigue, HRQoL, and other clinically relevant outcomes. Based on these findings, we recommend supervised resistance and aerobic exercise as part of supportive care regimens during palliative treatment of mBC. metadata May, Anne and Hiensch, Anouk and Depenbusch, Johanna and Schmidt, Martina and Monninkhof, Evelyn and Peláez, Mireia and Clauss, Dorothea and Zimmer, Philipp and Belloso, Jon and Trevaskis, Mark and Rundqvist, Helene and Wiskemann, Joachim and Muller, Jana and Fremd, Carlo and Altena, Renske and Kufel-Grabowska, Joanna and Bijlsma, Rhode and van Leeuwen-Snoeks, Lobke and Bokkel-Huinink, Daan ten and Sonke, Gabe and Mann, Bruce and Francis, Prudence and Richardson, Gary and Álvarez, Isabel and Malter, Wolfram and Van der Wall, Elsken and Aaronson, Neil and Senkus, Elżbieta and Urriticoechea, Ander and Zopf, Eva and Bloch, Wilhelm and Stuiver, Martijn and Wengström, Yvonne and Steindorf, Karen mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, mireia.pelaez@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2024) Abstract GS02-10: Effects of a structured and individualized exercise program on fatigue and health-related quality of life in patients with metastatic breast cancer: the multinational randomized controlled PREFERABLE-EFFECT study. Cancer Research, 84 (9_Supp). GS02-10. ISSN 1538-7445

Article Subjects > Physical Education and Sport Europe University of Atlantic > Research > Articles and books Cerrado Inglés The purpose of this study was to analyze the association and predictive capacity between the acute:chronic workload ratio (ACWR) and non-contact injuries in a semiprofessional football team. Seventeen football or soccer players from a Spanish Third Division football team participated voluntarily in this study. A prospective longitudinal study was developed during the 2020/2021 season. Twenty-four weeks were analyzed from October to March, including a regenerative microcycle due to the absence of competition during Christmas. Rate of perceived exertion (RPE) and session-rate of perceived exertion (sRPE) were registered for every training and game session. Afterward, acute and chronic workloads were calculated, and ACWR was subsequently derived from them. Furthermore, non-contact injuries were registered during the period mentioned. The main findings were that there is a poor correlation between the ACWR and non-contact injuries (r=0.069 (p<0.05)), and the use of the ACWR by itself is insufficient to predict the occurrence of non-contact injuries in a semiprofessional football team. Consequently, the ACWR is not an useful predictive tool for injuries in semiprofessional football teams. metadata Seco-Serna, Roberto and Lago-Fuentes, Carlos and Barcala Furelos, Martín mail UNSPECIFIED, carlos.lago@uneatlantico.es, martin.barcala@uneatlantico.es (2024) The Acute: Chronic Workload Ratio and Injury Risk in Semiprofessional Football Players. International Journal of Sports Medicine. ISSN 0172-4622

Article Subjects > Physical Education and Sport
Subjects > Psychology Europe University of Atlantic > Research > Articles and books Abierto Inglés (1) Background: Sport goals, although widely recognised as crucial for motivation and performance in sport, are multifaceted and can be difficult to measure directly. The present research aims to validate the 3 × 2 achievement goals questionnaire of Mascret in Spanish in a population of athletes. (2) Method: By using a latent factor approach, it is possible to identify the underlying dimensions of these goals and to better understand how they are structured. For this purpose, this questionnaire has been translated and compared with the life satisfaction scale. An exploration of the multifaceted nature of sport goals has been carried out using structural equation modelling. A total of 580 athletes (463 males and 216 females, M = 21.5, SD = 2.36) from different sport disciplines and from 12 autonomous communities in Spain participated in the research. (3) Results: The results show that the questionnaire presents a high scale reliability and that all items contribute significantly to the internal consistency of the scale. (4) Conclusions: The adaptation of this scale to the Spanish population of athletes can be a valid and useful tool to measure and understand motivation and goals in the sport context. metadata García-Romero, Cristina and Roldan-Aguilar, Elkin Eduardo and Hurtado-Castaño, Carlos Alberto and Rodríguez-Negro, Josune and Ramos-Álvarez, Oliver mail UNSPECIFIED (2024) Adaptation and Validation of the 3 × 2 Achievement Goals Questionnaire in a Population of Athletes. Behavioral Sciences, 14 (4). p. 350. ISSN 2076-328X

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Extracting knowledge from hybrid data, comprising both categorical and numerical data, poses significant challenges due to the inherent difficulty in preserving information and practical meanings during the conversion process. To address this challenge, hybrid data processing methods, combining complementary rough sets, have emerged as a promising approach for handling uncertainty. However, selecting an appropriate model and effectively utilizing it in data mining requires a thorough qualitative and quantitative comparison of existing hybrid data processing models. This research aims to contribute to the analysis of hybrid data processing models based on neighborhood rough sets by investigating the inherent relationships among these models. We propose a generic neighborhood rough set-based hybrid model specifically designed for processing hybrid data, thereby enhancing the efficacy of the data mining process without resorting to discretization and avoiding information loss or practical meaning degradation in datasets. The proposed scheme dynamically adapts the threshold value for the neighborhood approximation space according to the characteristics of the given datasets, ensuring optimal performance without sacrificing accuracy. To evaluate the effectiveness of the proposed scheme, we develop a testbed tailored for Parkinson’s patients, a domain where hybrid data processing is particularly relevant. The experimental results demonstrate that the proposed scheme consistently outperforms existing schemes in adaptively handling both numerical and categorical data, achieving an impressive accuracy of 95% on the Parkinson’s dataset. Overall, this research contributes to advancing hybrid data processing techniques by providing a robust and adaptive solution that addresses the challenges associated with handling hybrid data, particularly in the context of Parkinson’s disease analysis. metadata Raza, Imran and Jamal, Muhammad Hasan and Qureshi, Rizwan and Shahid, Abdul Karim and Rojas Vistorte, Angel Olider and Samad, Md Abdus and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, angel.rojas@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2024) Adaptive neighborhood rough set model for hybrid data processing: a case study on Parkinson’s disease behavioral analysis. Scientific Reports, 14 (1). ISSN 2045-2322

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés The provision of Wireless Fidelity (Wi-Fi) service in an indoor environment is a crucial task and the decay in signal strength issues arises especially in indoor environments. The Line-of-Sight (LOS) is a path for signal propagation that commonly impedes innumerable indoor objects damage signals and also causes signal fading. In addition, the Signal decay (signal penetration), signal reflection, and long transmission distance between transceivers are the key concerns. The signals lose their power due to the existence of obstacles (path of signals) and hence destroy received signal strength (RSS) between different communicating nodes and ultimately cause loss of the packet. Thus, to solve this issue, herein we propose an advanced model to maximize the LOS in communicating nodes using a modern indoor environment. Our proposal comprised various components for instance signal enhancers, repeaters, reflectors,. these components are connected. The signal attenuation and calculation model comprises of power algorithm and hence it can quickly and efficiently find the walls and corridors as obstacles in an indoor environment. We compared our proposed model with state of the art model using Received Signal Strength (RSS) and Packet Delivery Ratio (PDR) (different scenario) and found that our proposed model is efficient. Our proposed model achieved high network throughput as compared to the state-of-the-art models. metadata Khan, Muhammad Nasir and Waqas, Muhammad and Abbas, Qamar and Qureshi, Ahsan and Amin, Farhan and de la Torre Díez, Isabel and Uc Ríos, Carlos Eduardo and Fabian Gongora, Henry mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, carlos.uc@unini.edu.mx, henry.gongora@uneatlantico.es (2024) Advanced Line-of-Sight (LOS) model for communicating devices in modern indoor environment. PLOS ONE, 19 (7). e0305039. ISSN 1932-6203

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Cerrado Inglés The correct analysis of medical images requires the medical knowledge and expertise of radiologists to understand, clarify, and explain complex patterns and diagnose diseases. After analyzing, radiologists write detailed and well-structured reports that contribute to the precise and timely diagnosis of patients. However, manually writing reports is often expensive and time-consuming, and it is difficult for radiologists to analyze medical images, particularly images with multiple views and perceptions. It is challenging to accurately diagnose diseases, and many methods are proposed to help radiologists, both traditional and deep learning-based. Automatic report generation is widely used to tackle this issue as it streamlines the process and lessens the burden of manual labeling of images. This paper introduces a systematic literature review with a focus on analyses and evaluating existing research on medical report generation. This SLR follows a proper protocol for the planning, reviewing, and reporting of the results. This review recognizes that the most commonly used deep learning models are encoder-decoder frameworks (45 articles), which provide an accuracy of around 92–95%. Transformers-based models (20 articles) are the second most established method and achieve an accuracy of around 91%. The remaining articles explored in this SLR are attention mechanisms (10), RNN-LSTM (10), Large language models (LLM-10), and graph-based methods (4) with promising results. However, these methods also face certain limitations such as overfitting, risk of bias, and high data dependency that impact their performance. The review not only highlights the strengths and challenges of these methods but also suggests ways to handle them in the future to increase the accuracy and timely generation of medical reports. The goal of this review is to direct radiologists toward methods that lessen their workload and provide precise medical diagnoses. metadata Rehman, Marwareed and Shafi, Imran and Ahmad, Jamil and Osorio García, Carlos Manuel and Pascual Barrera, Alina Eugenia and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, carlos.osorio@uneatlantico.es, alina.pascual@unini.edu.mx, UNSPECIFIED (2024) Advancement in medical report generation: current practices, challenges, and future directions. Medical & Biological Engineering & Computing. ISSN 0140-0118

Article Subjects > Biomedicine
Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Abierto Inglés Aging is a physiological process characterized by a progressive deterioration of all the biological functions and a marked reduction in stress resistance, thus resulting in an increased susceptibility to several pathologies metadata Cassotta, Manuela and Quiles, José L. and Giampieri, Francesca and Battino, Maurizio mail manucassotta@gmail.com, jose.quiles@uneatlantico.es, francesca.giampieri@uneatlantico.es, maurizio.battino@uneatlantico.es (2024) Aging, age-related diseases, oxidative stress and plant polyphenols: Is this a true relationship? Mediterranean Journal of Nutrition and Metabolism, 17 (3). pp. 255-259. ISSN 1973798X

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Universidad Internacional do Cuanza > Research > Scientific Production Cerrado Inglés This article seeks to anticipate AirBnB prices using advanced regression approaches. Extensive data analysis was done on different databases spanning diverse variables such as location, property type, facility, and user level. The database is constructed utilizing robust approaches such as feature augmentation, outlier reduction, and value loss. A number of complex regression models, such as linear regression, decision tree, random forest, gradient regression, are generated on the pre-developed database. The model is improved through hyperparameter adjustment to increase prediction accuracy. A cross-validation approach was employed to examine the performance and resilience of the model. In addition, a feature significance study was undertaken to discover the most significant elements impacting Airbnb prices. The experimental findings suggest that the improved regression approach delivers greater prediction accuracy than the standard model. The results of this study add to Airbnb’s pricing system and can promote improved decision-making for hosts and visitors searching for competitive pricing. metadata Sar, Ayan and Choudhury, Tanupriya and Bajaj, Tridha and Kotecha, Ketan and Garat de Marin, Mirtha Silvana mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, silvana.marin@uneatlantico.es (2024) Airbnb Price Prediction Using Advanced Regression Techniques and Deployment Using Streamlit. Lecture Notes in Networks and Systems, 894. pp. 685-698. ISSN 2367-3370

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Public concern regarding health systems has experienced a rapid surge during the last two years due to the COVID-19 outbreak. Accordingly, medical professionals and health-related institutions reach out to patients and seek feedback to analyze, monitor, and uplift medical services. Such views and perceptions are often shared on social media platforms like Facebook, Instagram, Twitter, etc. Twitter is the most popular and commonly used by the researcher as an online platform for instant access to real-time news, opinions, and discussion. Its trending hashtags (#) and viral content make it an ideal hub for monitoring public opinion on a variety of topics. The tweets are extracted using three hashtags #healthcare, #healthcare services, and #medical facilities. Also, location and tweet sentiment analysis are considered in this study. Several recent studies deployed Twitter datasets using ML and DL models, but the results show lower accuracy. In addition, the studies did not perform extensive comparative analysis and lack validation. This study addresses two research questions: first, what are the sentiments of people toward medical services worldwide? and second, how effective are the machine learning and deep learning approaches for the classification of sentiment on healthcare tweets? Experiments are performed using several well-known machine learning models including support vector machine, logistic regression, Gaussian naive Bayes, extra tree classifier, k nearest neighbor, random forest, decision tree, and AdaBoost. In addition, this study proposes a transfer learning-based LSTM-ETC model that effectively predicts the customer’s satisfaction level from the healthcare dataset. Results indicate that despite the best performance by the ETC model with an 0.88 accuracy score, the proposed model outperforms with a 0.95 accuracy score. Predominantly, the people are happy about the provided medical services as the ratio of the positive sentiments is substantially higher than the negative sentiments. The sentiments, either positive or negative, play a crucial role in making important decisions through customer feedback and enhancing quality. metadata Usman, Muhammad and Mujahid, Muhammad and Rustam, Furqan and Soriano Flores, Emmanuel and Vidal Mazón, Juan Luis and Díez, Isabel de la Torre and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, emmanuel.soriano@uneatlantico.es, juanluis.vidal@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2024) Analyzing patients satisfaction level for medical services using twitter data. PeerJ Computer Science, 10. e1697. ISSN 2376-5992

Article Subjects > Physical Education and Sport Europe University of Atlantic > Research > Articles and books Abierto Inglés PURPOSE: Muscle asymmetries can be associated with increased risk of injury. Using countermovement jump (CMJ) to analyze muscular asymmetries in the lower limbs of soccer players, according to the stage of the season. metadata Velarde-Sotres, Álvaro and Mjaanes, Jeffrey and Vistorte, Angel Olider Rojas and Calleja-González, Julio mail alvaro.velarde@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2024) Assessment Of Lower Limb Asymmetries In Soccer Players According To The Stage Of The Season. Medicine & Science in Sports & Exercise, 56 (10S). pp. 589-590. ISSN 0195-9131

Article Subjects > Teaching Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production Abierto Inglés It is recommended to implement the teaching of Basic Life Support (BLS) in schools; however, studies on the best training method are limited and have been a priority in recent years. The objective of this study was to analyze the attitudes and practical skills learned during BLS training using a gamified proposal. A comparative study was carried out, consisting of Compulsory Secondary Education students [control group (CG; classical teaching) and experimental group (EG; gamified proposal)]. The instruments used were the CPR and AED action sequence observation sheet, data from the Laerdal Resusci Anne manikin and AED and Attitude Questionnaire towards Basic Life Support and the Use of the Automated External Defibrillator. Sixty-eight students (33 girls) with a mean age of 13.91 ± 0.70 years were recruited. Results were significantly better in the EG (n = 37) [i.e., breathing control (p = 0.037); call to emergency services (p = 0.049); mean compression depth (p = 0.001); self-confidence (p = 0.006); intention to perform BLS and AED (p = 0.002)]; and significantly better in the CG (n = 31) [Total percentage of CPR (p < 0.001); percentage of correct compression (p < 0.001); time to apply effective shock with AED (p < 0.001); demotivation (p = 0.005). We can conclude that the group that was trained with the training method through the gamified proposal presents better intentions and attitudes to act in the event of cardiac arrest than those of the classic method. This training method allows for similar results in terms of CPR and AED skills to classical teaching, so it should be taken into account as a method for teaching BLS to secondary education students. metadata Rodríguez-García, Adrián and Ruiz-García, Giovanna and Navarro-Patón, Rubén and Mecías-Calvo, Marcos mail adrian.rodriguez@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, marcos.mecias@uneatlantico.es (2024) Attitudes and Skills in Basic Life Support after Two Types of Training: Traditional vs. Gamification, of Compulsory Secondary Education Students: A Simulation Study. Pediatric Reports, 16 (3). pp. 631-643. ISSN 2036-7503

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés The wheat crop that fulfills 35% of human food demand is facing several problems due to a lack of transparency, security, reliability, and traceability in the existing agriculture supply chain. Many systems have been developed for the agriculture supply chain to overcome such issues, however, monopolistic centralized control is the biggest hurdle to realizing the use of such systems. It has eventually gained consumers’ trust in branded products and rejected other products due to the lack of traceable supply chain information. This study proposes a blockchain-based framework for supply chain traceability which provides trustable, transparent, secure, and reliable services for the wheat crop. A crypto token called wheat coin (WC) has been introduced to keep track of transactions among the stakeholders of the wheat supply chain. Moreover, an initial coin offering (ICO) of WC, crypto wallets, and an economic model are proposed. Furthermore, a smart contract-based transaction system has been devised for the transparency of wheat crop transactions and conversion of WC to fiat and vice versa. We have developed the interplanetary file system (IPFS) to improve data availability, security, and transparency which stores encrypted private data of farmers, businesses, and merchants. Lastly, the results of the experiments show that the proposed framework shows better performance as compared to previous crop supply chain solutions in terms of latency to add-blocks, per-minute transactions, average gas charge for the transaction, and transaction verification time. Performance analysis with Bitcoin and Ethereum shows the superior performance of the proposed system. metadata Alam, Shadab and Farooq, Muhammad Shoaib and Ansari, Zain Khalid and Alvi, Atif and Rustam, Furqan and Díez, Isabel De La Torre and Vidal Mazón, Juan Luis and Rodríguez Velasco, Carmen Lilí and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, juanluis.vidal@uneatlantico.es, carmen.rodriguez@uneatlantico.es, UNSPECIFIED (2024) Blockchain based transparent and reliable framework for wheat crop supply chain. PLOS ONE, 19 (1). e0295036. ISSN 1932-6203

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Cerrado Inglés Induced resistance is considered as a sustainable strategy to control postharvest decay of fruits, while light emitting diodes (LEDs) as a green physical technology are of more and more interest in postharvest fruit preservation field. In this study, we evaluated for the first time the resistance inducing ability of LED irradiation with different light wavelengths and photoperiods for cherry tomatoes (Solanum lycopersicum L. ‘Qianxi’). Results indicated the exposure to 40 W m-2 of four light wavelengths for 3 d decreased B. cinerea lesion diameter on harvested cherry tomatoes, notably the best effect in blue light (470 nm). Meanwhile, the mechanism of blue light-induced disease resistance is the enhancement of defense-enzyme activity and the expression of defense-related genes. Moreover, results revealed that blue light enhanced vitamin C content and the firmness of the fruit exocarp, suggesting the potential usage of blue light in the postharvest preservation of cherry tomatoes. metadata Sun, Jiayi and Tan, Xinhui and Liu, Bingjie and Battino, Maurizio and Meng, Xianghong and Zhang, Fang mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, maurizio.battino@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2024) Blue light inhibits gray mold infection by inducing disease resistance in cherry tomato. Postharvest Biology and Technology, 215. p. 113006. ISSN 09255214

Article Subjects > Psychology Europe University of Atlantic > Research > Articles and books Cerrado Inglés Objective Eating disorders (ED) have recently been studied from a network approach, conceptualising them as a complex system of interconnected variables, while highlighting the role of non-ED symptoms and personality dimensions. This study aims to explore the connections between personality and ED symptoms, identify central nodes, and compare the EDs network to a healthy control network. Methods We employed network analysis to examine the personality-ED symptom connections in 329 individuals with an ED diagnosis and 192 healthy controls. We estimated a regularised partial correlation network and the indices of centrality and bridge centrality to identify the most influential nodes for each group. Network differences between groups were also examined. Results Low Self-Directedness and high Harm avoidance emerged as central bridge nodes, displaying the strongest relationship with ED symptoms. Both networks differed in their global connectivity and structure, although no differences were found in bridge centrality and centrality indices. Conclusions These findings shed light on the role of personality dimensions, such as Self-Directedness and Harm Avoidance in the maintenance of ED psychopathology, supporting the transdiagnostic conceptualisation of ED. This study advances a deeper understanding of the complex interplay between personality dimensions and ED symptoms, offering potential directions for clinical interventions. metadata Ruiz‐Gutiérrez, Jose and Miras‐Aguilar, María del Mar and Rodríguez‐Pérez, Noelia and Ventura, Ludovica and González Gómez, Jana and del Barrio, Andrés Gómez and González‐Blanch, César mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, cesar.gonzalezblanch@uneatlantico.es (2024) Bridging personality dimensions and eating symptoms: A transdiagnostic network approach. European Eating Disorders Review. ISSN 1072-4133

Article Subjects > Physical Education and Sport Europe University of Atlantic > Research > Articles and books Abierto Inglés This study aimed to explore the effect of the menstrual cycle (MC) phases (i.e., early follicular phase [EFP], late follicular phase [LFP], and mid-luteal phase [MLP]) on the repetitions performed to momentary failure in back squat and bench press exercises, as well as to determine subsequent fatigue (i.e., change in countermovement jump [CMJ], perceived effort, and muscle soreness). Twelve physically active eumenorrheic women performed a back squat and bench press set to momentary failure at 80% of the one-repetition maximum during the EFP, LFP, and MLP. The results revealed that subjects were able to perform 2.2 [0.2 to 4.2] more repetitions in the LFP with respect to the EFP for the back squat exercise (p = 0.009), but no significant differences were observed for the bench press (p = 0.354). The EFP displayed a larger CMJ height drop (−0.86 [−1.71 to −0.01] cm) with respect to the LFP (0.01 [−0.57 to 0.58] cm) and the MLP (−0.36 [−1.15 to 0.43] cm). Neither the perceived effort of each set to failure nor the resulting muscle soreness differed between MC phases. Therefore, practitioners should be aware that the MC could condition the repetitions available to momentary failure and the resulting allostatic load. metadata Osmani, Florent and Terán Fernández, Danel and Alonso Pérez, Sergio and Ruiz-Alias, Santiago A. and García-Pinillos, Felipe and Lago-Fuentes, Carlos mail florent.osmani@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, carlos.lago@uneatlantico.es (2024) Can Women Maintain Their Strength Performance Along the Menstrual Cycle? Applied Sciences, 14 (21). p. 9818. ISSN 2076-3417

Article Subjects > Physical Education and Sport Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production Abierto Inglés The aim of the present study was to understand the effect of a multicomponent physical exercise program on the functional physical fitness of older people with overweight or obesity in Chile, and whether these effects were similar in women and men. For this purpose, a quasi-experimental study was designed with a control group to evaluate the functional physical fitness through the Senior Fitness Test battery for older people [SFT; aerobic endurance (AE), lower body strength (LBS), upper body strength (UBS), upper body flexibility (UBF), lower body flexibility (LBF), dynamic balance (DB), and hand pressure strength right (HPSR) and left (HPSL)]. Seventy older people with overweight or obesity aged between 60 and 86 years participated (M = 73.15; SD = 5.94), and were randomized into a control group (CG, n = 35) and an experimental group (EG, n = 35). The results after the intervention between the CG and EG indicated that there were statistically significant differences in the AE (p = 0.036), in the LBS (p = 0.031), and in the LBF (p = 0.017), which did not exist before the intervention (p > 0.050), except in the HPSR (0.029). Regarding the results of the EG (pre vs. post-intervention), statistically significant differences were found in all of the variables studied: AE (p < 0.001), LBS (p < 0.001), UBS (p < 0.001), LBF (p = 0.017), UBF (p < 0.001), DB (p = 0.002), HPSR (p < 0.001), and HPSL (p = 0.012) in both men and women. These improvements did not exist in any of the CG variables (p > 0.05). Based on the results obtained, we can say that a multicomponent physical exercise program applied for 6 months in older people with overweight or obesity produces improvements in functional physical fitness regardless of sex, except in lower body flexibility and left-hand dynamometry. metadata Pleticosic-Ramírez, Yazmina and Velarde-Sotres, Álvaro and Mecías-Calvo, Marcos and Navarro-Patón, Rubén mail yazmina.pleticosic@doctorado.unini.edu.mx, alvaro.velarde@uneatlantico.es, marcos.mecias@uneatlantico.es, UNSPECIFIED (2024) Can the Functional Physical Fitness of Older People with Overweight or Obesity Be Improved through a Multicomponent Physical Exercise Program? A Chilean Population Study. Applied Sciences, 14 (15). p. 6502. ISSN 2076-3417

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Background: Cardiovascular diseases (CVDs) encompass a variety of conditions that affect the heart and blood vessels. Carotenoids, a group of fat-soluble organic pigments synthesized by plants, fungi, algae, and some bacteria, may have a beneficial effect in reducing cardiovascular disease (CVD) risk. This study aims to examine and synthesize current research on the relationship between carotenoids and CVDs. Methods: A systematic review was conducted using MEDLINE and the Cochrane Library to identify relevant studies on the efficacy of carotenoid supplementation for CVD prevention. Interventional analytical studies (randomized and non-randomized clinical trials) published in English from January 2011 to February 2024 were included. Results: A total of 38 studies were included in the qualitative analysis. Of these, 17 epidemiological studies assessed the relationship between carotenoids and CVDs, 9 examined the effect of carotenoid supplementation, and 12 evaluated dietary interventions. Conclusions: Elevated serum carotenoid levels are associated with reduced CVD risk factors and inflammatory markers. Increasing the consumption of carotenoid-rich foods appears to be more effective than supplementation, though the specific effects of individual carotenoids on CVD risk remain uncertain. metadata Sumalla Cano, Sandra and Eguren García, Imanol and Lasarte García, Álvaro and Prola, Thomas and Martínez Díaz, Raquel and Elío Pascual, Iñaki mail sandra.sumalla@uneatlantico.es, imanol.eguren@uneatlantico.es, UNSPECIFIED, thomas.prola@uneatlantico.es, raquel.martinez@uneatlantico.es, inaki.elio@uneatlantico.es (2024) Carotenoids Intake and Cardiovascular Prevention: A Systematic Review. Nutrients, 16 (22). p. 3859. ISSN 2072-6643

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Abierto Inglés The olive oil sector is a fundamental food in the Mediterranean diet. It has been demonstrated that the consumption of extra virgin olive oil (EVOO) with a high content of phenolic compounds is beneficial in the prevention and/or treatment of many diseases. The main objective of this work was to study the relationship between the content of phenolic compounds and the in vitro neuroprotective and anti-inflammatory activity of EVOOs from two PDOs in the province of Granada. To this purpose, the amounts of phenolic compounds were determined by liquid chromatography coupled to mass spectrometry (HPLC–MS) and the inhibitory activity of acetylcholinesterase (AChE) and cyclooxygenase-2 (COX-2) enzymes by spectrophotometric and fluorimetric assays. The main families identified were phenolic alcohols, secoiridoids, lignans, flavonoids, and phenolic acids. The EVOO samples with the highest total concentration of compounds and the highest inhibitory activity belonged to the Picual and Manzanillo varieties. Statistical analysis showed a positive correlation between identified compounds and AChE and COX-2 inhibitory activity, except for lignans. These results confirm EVOO’s compounds possess neuroprotective potential. metadata López-Bascón, María Asunción and Moscoso-Ruiz, Inmaculada and Quirantes-Piné, Rosa and del Pino-García, Raquel and López-Gámez, Gloria and Justicia-Rueda, Andrea and Verardo, Vito and Quiles, José L. mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, jose.quiles@uneatlantico.es (2024) Characterization of Phenolic Compounds in Extra Virgin Olive Oil from Granada (Spain) and Evaluation of Its Neuroprotective Action. International Journal of Molecular Sciences, 25 (9). p. 4878. ISSN 1422-0067

Article Subjects > Biomedicine Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Emergency medical services (EMSs) face critical situations that require patient risk classification based on analytical and vital signs. We aimed to establish clustering-derived phenotypes based on prehospital analytical and vital signs that allow risk stratification. This was a prospective, multicenter, EMS-delivered, ambulance-based cohort study considering six advanced life support units, 38 basic life support units, and four tertiary hospitals in Spain. Adults with unselected acute diseases managed by the EMS and evacuated with discharge priority to emergency departments were considered between January 1, 2020, and June 30, 2023. Prehospital point-of-care testing and on-scene vital signs were used for the unsupervised machine learning method (clustering) to determine the phenotypes. Then phenotypes were compared with the primary outcome (cumulative mortality (all-cause) at 2, 7, and 30 days). A total of 7909 patients were included. The median (IQR) age was 64 (51–80) years, 41% were women, and 26% were living in rural areas. Three clusters were identified: alpha 16.2% (1281 patients), beta 28.8% (2279), and gamma 55% (4349). The mortality rates for alpha, beta and gamma at 2 days were 18.6%, 4.1%, and 0.8%, respectively; at 7 days, were 24.7%, 6.2%, and 1.7%; and at 30 days, were 33%, 10.2%, and 3.2%, respectively. Based on standard vital signs and blood test biomarkers in the prehospital scenario, three clusters were identified: alpha (high-risk), beta and gamma (medium- and low-risk, respectively). This permits the EMS system to quickly identify patients who are potentially compromised and to proactively implement the necessary interventions. metadata López-Izquierdo, Raúl and del Pozo Vegas, Carlos and Sanz-García, Ancor and Mayo Íscar, Agustín and Castro Villamor, Miguel A. and Silva Alvarado, Eduardo René and Gracia Villar, Santos and Dzul López, Luis Alonso and Aparicio Obregón, Silvia and Calderón Iglesias, Rubén and Soriano, Joan B. and Martín-Rodríguez, Francisco mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, eduardo.silva@funiber.org, santos.gracia@uneatlantico.es, luis.dzul@uneatlantico.es, silvia.aparicio@uneatlantico.es, ruben.calderon@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2024) Clinical phenotypes and short-term outcomes based on prehospital point-of-care testing and on-scene vital signs. npj Digital Medicine, 7 (1). ISSN 2398-6352

Article Subjects > Biomedicine Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Emergency medical services (EMSs) face critical situations that require patient risk classification based on analytical and vital signs. We aimed to establish clustering-derived phenotypes based on prehospital analytical and vital signs that allow risk stratification. This was a prospective, multicenter, EMS-delivered, ambulance-based cohort study considering six advanced life support units, 38 basic life support units, and four tertiary hospitals in Spain. Adults with unselected acute diseases managed by the EMS and evacuated with discharge priority to emergency departments were considered between January 1, 2020, and June 30, 2023. Prehospital point-of-care testing and on-scene vital signs were used for the unsupervised machine learning method (clustering) to determine the phenotypes. Then phenotypes were compared with the primary outcome (cumulative mortality (all-cause) at 2, 7, and 30 days). A total of 7909 patients were included. The median (IQR) age was 64 (51–80) years, 41% were women, and 26% were living in rural areas. Three clusters were identified: alpha 16.2% (1281 patients), beta 28.8% (2279), and gamma 55% (4349). The mortality rates for alpha, beta and gamma at 2 days were 18.6%, 4.1%, and 0.8%, respectively; at 7 days, were 24.7%, 6.2%, and 1.7%; and at 30 days, were 33%, 10.2%, and 3.2%, respectively. Based on standard vital signs and blood test biomarkers in the prehospital scenario, three clusters were identified: alpha (high-risk), beta and gamma (medium- and low-risk, respectively). This permits the EMS system to quickly identify patients who are potentially compromised and to proactively implement the necessary interventions. metadata López-Izquierdo, Raúl and del Pozo Vegas, Carlos and Sanz-García, Ancor and Mayo Íscar, Agustín and Castro Villamor, Miguel A. and Silva Alvarado, Eduardo René and Gracia Villar, Santos and Dzul López, Luis Alonso and Aparicio Obregón, Silvia and Calderón Iglesias, Rubén and Soriano, Joan B. and Martín-Rodríguez, Francisco mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, eduardo.silva@funiber.org, santos.gracia@uneatlantico.es, luis.dzul@uneatlantico.es, silvia.aparicio@uneatlantico.es, ruben.calderon@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2024) Clinical phenotypes and short-term outcomes based on prehospital point-of-care testing and on-scene vital signs. npj Digital Medicine, 7 (1). ISSN 2398-6352

Article Subjects > Biomedicine
Subjects > Social Sciences
Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Aim: The development of predictive models for patients treated by emergency medical services (EMS) is on the rise in the emergency field. However, how these models evolve over time has not been studied. The objective of the present work is to compare the characteristics of patients who present mortality in the short, medium and long term, and to derive and validate a predictive model for each mortality time. Methods: A prospective multicenter study was conducted, which included adult patients with unselected acute illness who were treated by EMS. The primary outcome was noncumulative mortality from all causes by time windows including 30-day mortality, 31- to 180-day mortality, and 181- to 365-day mortality. Prehospital predictors included demographic variables, standard vital signs, prehospital laboratory tests, and comorbidities. Results: A total of 4830 patients were enrolled. The noncumulative mortalities at 30, 180, and 365 days were 10.8%, 6.6%, and 3.5%, respectively. The best predictive value was shown for 30-day mortality (AUC = 0.930; 95% CI: 0.919–0.940), followed by 180-day (AUC = 0.852; 95% CI: 0.832–0.871) and 365-day (AUC = 0.806; 95% CI: 0.778–0.833) mortality. Discussion: Rapid characterization of patients at risk of short-, medium-, or long-term mortality could help EMS to improve the treatment of patients suffering from acute illnesses. metadata Enriquez de Salamanca Gambara, Rodrigo and Sanz-García, Ancor and del Pozo Vegas, Carlos and López-Izquierdo, Raúl and Sánchez Soberón, Irene and Delgado Benito, Juan F. and Martínez Díaz, Raquel and Mazas Pérez-Oleaga, Cristina and Martínez López, Nohora Milena and Dominguez Azpíroz, Irma and Martín-Rodríguez, Francisco mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, raquel.martinez@uneatlantico.es, cristina.mazas@uneatlantico.es, nohora.martinez@uneatlantico.es, irma.dominguez@unini.edu.mx, UNSPECIFIED (2024) A Comparison of the Clinical Characteristics of Short-, Mid-, and Long-Term Mortality in Patients Attended by the Emergency Medical Services: An Observational Study. Diagnostics, 14 (12). p. 1292. ISSN 2075-4418

Article Subjects > Physical Education and Sport Europe University of Atlantic > Research > Articles and books Abierto Inglés Purpose: The purpose of this study was to analyze the concordance of a new Inertial Measurement Unit (IMU) device called OLIVER in different specific training tasks and real futsal game.Methods: 10 elite futsal players competing in First National Division performed most of the typical futsal training tasks (game possession in 22×20m, 2vs2 in 20×20m, 3vs3, 4vs4 in 28×20m and 4vs4 in 40×20m). Players wore two tracking devices (OLIVER and WIMU Pro). Data were recorded with specific software systems to compare the concordance of data. After recording data, descriptive analysis was developed for each training task, as well as a one-way ANOVA to evaluate the concordance of OLIVER and WIMU devices.Results: The results reported good agreement for most variables, such as total distance, distance covered in different partials, as well as meters of accelerations and decelerations at different intensities and maximum speed (P> .05). However, the distance covered in high-speed running 12.1-18 km/h (m) and the number of runs above 12 km/h reported statistical differences between OLIVER and WIMU (P< .05) in some of the training tasks.Conclusion: The OLIVER system and WIMU system shows a high level of concordance in main variables of external load in different training tasks. OLIVER system is a valid and useful device to monitor external load in indoor sports, both small-sided games and real games metadata Gadea Uribarri, Héctor and Lago-Fuentes, Carlos and Bores Arce, Ainhoa and López-García, Sergio and Ibañez, Enrique and Serrano, Carlos and Mainer-Pardos, Elena mail UNSPECIFIED, carlos.lago@uneatlantico.es, ainhoa.bores@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2024) Concordance of a new IMU in different small-sided games and real game tasks in indoor sports. Acta kinesiologica (N3 202). pp. 53-60. ISSN 1840-2976

Article Subjects > Biomedicine Europe University of Atlantic > Research > Articles and books Cerrado Inglés Background: Celiac disease (CD) is a multifactorial, immune-mediated enteropathic disorder that may occur at any age with heterogeneous clinical presentation. In the last years, unusual manifestations have become very frequent, and currently, it is not so uncommon to diagnose CD in subjects with overweight or obesity, especially in adults; however, little is known in the pediatric population. This systematic review aims to evaluate the literature regarding the association between CD and overweight/obesity in school-age children. Methods: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed. An electronic database search of articles published in the last 20 years in English was carried out in Web of Sciences, PubMed, and Medline. The quality of the included studies was assessed by using the STrengthening the Reporting of OBservational studies in Epidemiology statement. Results: Of the 1396 articles identified, 9 articles, investigating overweight/obesity in children/adolescents affected by CD or screening CD in children/adolescents with overweight/obesity, met the inclusion criteria. Overall, the results showed that the prevalence of overweight or obesity in school-age children (6–17 years) affected by CD ranged between 3.5% and 20%, highlighting that the coexistence of CD with overweight/obesity in children is not uncommon as previously thought. Conclusion: Although CD has been historically correlated with being underweight due to malabsorption, it should be evaluated also in children with overweight and obesity, especially those who have a familiar predisposition to other autoimmune diseases and/or manifest unusual symptoms of CD. metadata De Giuseppe, Rachele and Bergomas, Francesca and Loperfido, Federica and Giampieri, Francesca and Preatoni, Giorgia and Calcaterra, Valeria and Cena, Hellas mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, francesca.giampieri@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2024) Could Celiac Disease and Overweight/Obesity Coexist in School-Aged Children and Adolescents? A Systematic Review. Childhood Obesity, 20 (1). pp. 48-67. ISSN 2153-2168

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production Abierto Inglés Objectives: We sought to examine the correlation between the recommended consumption of at least two servings (400 g) of vegetables per day and the prevalence of metabolic syndrome (MetS) in an elderly population. Methods: This observational, cross-sectional, and descriptive study was conducted with 264 non-institutionalized people aged 65 to 79 years old. We adhered to the recommended guidelines for vegetable intake from the MEDAS-14 questionnaire, which has been validated for elderly populations at high cardiovascular risk. Diagnoses of MetS were made based on the criteria set forth by the International Diabetes Federation (IDF). Results: Among 264 individuals, who had a mean age of 71.9 (SD: 4.2) and comprised 39% men, the prevalence of MetS was 40.2%. A total of 17% of the participants adhered to the recommended vegetable consumption. Consuming the recommended amount of vegetables was correlated with a 19% reduction in the prevalence of MetS, to 24.4% from 43.4% among those with low vegetable consumption (p < 0.05). A main finding was that inadequate vegetable consumption was significantly associated with a higher prevalence of MetS (OR: 2.21; 95% CI: 1.06–4.63; p = 0.035), considering potential influences by nutritional (consumption of fruit and nuts) and socio-demographic (sex, age, and level of education) covariates. Conclusions: A beneficial inverse correlation was identified between the recommended vegetable intake and the prevalence of MetS. In contrast, inadequate vegetable consumption was revealed as an independent variable associated with the prevalence of MetS. Considering the very low adherence to the recommended vegetable intake we observed, encouraging increased vegetable consumption among older individuals, who have a high prevalence of MetS, is advisable. metadata Cubas-Basterrechea, Gloria and Elío Pascual, Iñaki and González Antón, Carolina and Muñoz Cacho, Pedro mail UNSPECIFIED, inaki.elio@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2024) Daily Intake of Two or More Servings of Vegetables Is Associated with a Lower Prevalence of Metabolic Syndrome in Older People. Nutrients, 16 (23). p. 4101. ISSN 2072-6643

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés The perception and recognition of objects around us empower environmental interaction. Harnessing the brain’s signals to achieve this objective has consistently posed difficulties. Researchers are exploring whether the poor accuracy in this field is a result of the design of the temporal stimulation (block versus rapid event) or the inherent complexity of electroencephalogram (EEG) signals. Decoding perceptive signal responses in subjects has become increasingly complex due to high noise levels and the complex nature of brain activities. EEG signals have high temporal resolution and are non-stationary signals, i.e., their mean and variance vary overtime. This study aims to develop a deep learning model for the decoding of subjects’ responses to rapid-event visual stimuli and highlights the major factors that contribute to low accuracy in the EEG visual classification task.The proposed multi-class, multi-channel model integrates feature fusion to handle complex, non-stationary signals. This model is applied to the largest publicly available EEG dataset for visual classification consisting of 40 object classes, with 1000 images in each class. Contemporary state-of-the-art studies in this area investigating a large number of object classes have achieved a maximum accuracy of 17.6%. In contrast, our approach, which integrates Multi-Class, Multi-Channel Feature Fusion (MCCFF), achieves a classification accuracy of 33.17% for 40 classes. These results demonstrate the potential of EEG signals in advancing EEG visual classification and offering potential for future applications in visual machine models. metadata Rehman, Madiha and Anwer, Humaira and Garay, Helena and Alemany Iturriaga, Josep and Díez, Isabel De la Torre and Siddiqui, Hafeez ur Rehman and Ullah, Saleem mail UNSPECIFIED, UNSPECIFIED, helena.garay@uneatlantico.es, josep.alemany@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2024) Decoding Brain Signals from Rapid-Event EEG for Visual Analysis Using Deep Learning. Sensors, 24 (21). p. 6965. ISSN 1424-8220

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Generative intelligence relies heavily on the integration of vision and language. Much of the research has focused on image captioning, which involves describing images with meaningful sentences. Typically, when generating sentences that describe the visual content, a language model and a vision encoder are commonly employed. Because of the incorporation of object areas, properties, multi-modal connections, attentive techniques, and early fusion approaches like bidirectional encoder representations from transformers (BERT), these components have experienced substantial advancements over the years. This research offers a reference to the body of literature, identifies emerging trends in an area that blends computer vision as well as natural language processing in order to maximize their complementary effects, and identifies the most significant technological improvements in architectures employed for image captioning. It also discusses various problem variants and open challenges. This comparison allows for an objective assessment of different techniques, architectures, and training strategies by identifying the most significant technical innovations, and offers valuable insights into the current landscape of image captioning research. metadata Jamil, Azhar and Rehman, Saif Ur and Mahmood, Khalid and Gracia Villar, Mónica and Prola, Thomas and Diez, Isabel De La Torre and Samad, Md Abdus and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, monica.gracia@uneatlantico.es, thomas.prola@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2024) Deep Learning Approaches for Image Captioning: Opportunities, Challenges and Future Potential. IEEE Access. p. 1. ISSN 2169-3536

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés The classification of bird species is of significant importance in the field of ornithology, as it plays an important role in assessing and monitoring environmental dynamics, including habitat modifications, migratory behaviors, levels of pollution, and disease occurrences. Traditional methods of bird classification, such as visual identification, were time-intensive and required a high level of expertise. However, audio-based bird species classification is a promising approach that can be used to automate bird species identification. This study aims to establish an audio-based bird species classification system for 264 Eastern African bird species employing modified deep transfer learning. In particular, the pre-trained EfficientNet technique was utilized for the investigation. The study adapts the fine-tune model to learn the pertinent patterns from mel spectrogram images specific to this bird species classification task. The fine-tuned EfficientNet model combined with a type of Recurrent Neural Networks (RNNs) namely Gated Recurrent Unit (GRU) and Long short-term memory (LSTM). RNNs are employed to capture the temporal dependencies in audio signals, thereby enhancing bird species classification accuracy. The dataset utilized in this work contains nearly 17,000 bird sound recordings across a diverse range of species. The experiment was conducted with several combinations of EfficientNet and RNNs, and EfficientNet-B7 with GRU surpasses other experimental models with an accuracy of 84.03% and a macro-average precision score of 0.8342. metadata Shaikh, Asadullah and Baowaly, Mrinal Kanti and Sarkar, Bisnu Chandra and Walid, Md. Abul Ala and Ahamad, Md. Martuza and Singh, Bikash Chandra and Silva Alvarado, Eduardo René and Ashraf, Imran and Samad, Md. Abdus mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, eduardo.silva@funiber.org, UNSPECIFIED, UNSPECIFIED (2024) Deep transfer learning-based bird species classification using mel spectrogram images. PLOS ONE, 19 (8). e0305708. ISSN 1932-6203

Article Subjects > Engineering
Subjects > Psychology Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Predicting depression intensity from microblogs and social media posts has numerous benefits and applications, including predicting early psychological disorders and stress in individuals or the general public. A major challenge in predicting depression using social media posts is that the existing studies do not focus on predicting the intensity of depression in social media texts but rather only perform the binary classification of depression and moreover noisy data makes it difficult to predict the true depression in the social media text. This study intends to begin by collecting relevant Tweets and generating a corpus of 210000 public tweets using Twitter public application programming interfaces (APIs). A strategy is devised to filter out only depression-related tweets by creating a list of relevant hashtags to reduce noise in the corpus. Furthermore, an algorithm is developed to annotate the data into three depression classes: ‘Mild,’ ‘Moderate,’ and ‘Severe,’ based on International Classification of Diseases-10 (ICD-10) depression diagnostic criteria. Different baseline classifiers are applied to the annotated dataset to get a preliminary idea of classification performance on the corpus. Further FastText-based model is applied and fine-tuned with different preprocessing techniques and hyperparameter tuning to produce the tuned model, which significantly increases the depression classification performance to an 84% F1 score and 90% accuracy compared to baselines. Finally, a FastText-based weighted soft voting ensemble (WSVE) is proposed to boost the model’s performance by combining several other classifiers and assigning weights to individual models according to their individual performances. The proposed WSVE outperformed all baselines as well as FastText alone, with an F1 of 89%, 5% higher than FastText alone, and an accuracy of 93%, 3% higher than FastText alone. The proposed model better captures the contextual features of the relatively small sample class and aids in the detection of early depression intensity prediction from tweets with impactful performances. metadata Rizwan, Muhammad and Mushtaq, Muhammad Faheem and Rafiq, Maryam and Mehmood, Arif and Diez, Isabel de la Torre and Gracia Villar, Mónica and Garay, Helena and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, monica.gracia@uneatlantico.es, helena.garay@uneatlantico.es, UNSPECIFIED (2024) Depression Intensity Classification from Tweets Using FastText Based Weighted Soft Voting Ensemble. Computers, Materials & Continua, 78 (2). pp. 2047-2066. ISSN 1546-2226

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés With the outbreak of the COVID-19 pandemic, social isolation and quarantine have become commonplace across the world. IoT health monitoring solutions eliminate the need for regular doctor visits and interactions among patients and medical personnel. Many patients in wards or intensive care units require continuous monitoring of their health. Continuous patient monitoring is a hectic practice in hospitals with limited staff; in a pandemic situation like COVID-19, it becomes much more difficult practice when hospitals are working at full capacity and there is still a risk of medical workers being infected. In this study, we propose an Internet of Things (IoT)-based patient health monitoring system that collects real-time data on important health indicators such as pulse rate, blood oxygen saturation, and body temperature but can be expanded to include more parameters. Our system is comprised of a hardware component that collects and transmits data from sensors to a cloud-based storage system, where it can be accessed and analyzed by healthcare specialists. The ESP-32 microcontroller interfaces with the multiple sensors and wirelessly transmits the collected data to the cloud storage system. A pulse oximeter is utilized in our system to measure blood oxygen saturation and body temperature, as well as a heart rate monitor to measure pulse rate. A web-based interface is also implemented, allowing healthcare practitioners to access and visualize the collected data in real-time, making remote patient monitoring easier. Overall, our IoT-based patient health monitoring system represents a significant advancement in remote patient monitoring, allowing healthcare practitioners to access real-time data on important health metrics and detect potential health issues before they escalate. metadata Islam, Md. Milon and Shafi, Imran and Din, Sadia and Farooq, Siddique and Díez, Isabel de la Torre and Breñosa, Jose and Martínez Espinosa, Julio César and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, josemanuel.brenosa@uneatlantico.es, ulio.martinez@unini.edu.mx, UNSPECIFIED (2024) Design and development of patient health tracking, monitoring and big data storage using Internet of Things and real time cloud computing. PLOS ONE, 19 (3). e0298582. ISSN 1932-6203

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés Retinitis pigmentosa (RP) is a group of genetic retinal disorders characterized by progressive vision loss, culminating in blindness. Identifying pigment signs (PS) linked with RP is crucial for monitoring and possibly slowing the disease’s degenerative course. However, the segmentation and detection of PS are challenging due to the difficulty of distinguishing between PS and blood vessels and the variability in size, shape, and color of PS. Recently, advances in deep learning techniques have shown impressive results in medical image analysis, especially in ophthalmology. This study presents an approach for classifying pigment marks in color fundus images of RP using a modified squeeze-and-excitation ResNet (SE-ResNet) architecture. This variant synergizes the efficiency of residual skip connections with the robust attention mechanism of the SE block to amplify feature representation. The SE-ResNet model was fine-tuned to determine the optimal layer configuration that balances performance metrics and computational costs. We trained the proposed model on the RIPS dataset, which comprises images from patients diagnosed at various RP stages. Experimental results confirm the efficacy of the proposed model in classifying different types of pigment signs associated with RP. The model yielded performance metrics, such as accuracy, sensitivity, specificity, and f-measure of 99.16%, 97.70%, 96.93%, 90.47%, 99.37%, 97.80%, 97.44%, and 90.60% on the testing set, based on GT1 & GT2 respectively. Given its performance, this model is an excellent candidate for integration into computer-aided diagnostic systems for RP, aiming to enhance patient care and vision-related healthcare services. metadata Rashid, Rubina and Aslam, Waqar and Mehmood, Arif and Ramírez-Vargas, Debora L. and Diez, Isabel De La Torre and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, debora.ramirez@unini.edu.mx, UNSPECIFIED, UNSPECIFIED (2024) A Detectability Analysis of Retinitis Pigmetosa Using Novel SE-ResNet Based Deep Learning Model and Color Fundus Images. IEEE Access, 12. pp. 28297-28309. ISSN 2169-3536

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Cerrado Inglés Federated learning is a distributed machine-learning technique that enables multiple devices to learn a shared model while keeping their local data private. The approach poses security challenges, such as model integrity, that must be addressed to ensure the reliability of the learned models. In this context, software-defined networking (SDN) can play a crucial role in improving the security of federated learning systems; indeed, it can provide centralized control and management of network resources, enforcement of security policies, and detection and mitigation of network-level threats. The integration of SDN with federated learning can help achieve a secure and efficient distributed learning environment. In this paper, an architecture is proposed to detect attacks on Federated Learning using SDN; furthermore, the machine learning model is deployed on a number of devices for training. The simulation results are carried out using the N-BaIoT dataset and training models such as Random Forest achieves 99.6%, Decision Tree achieves 99.8%, and K-Nearest Neighbor achieves 99.3% with 20 features. metadata Babbar, Himanshi and Rani, Shalli and Singh, Aman and Gianini, Gabriele mail UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es, UNSPECIFIED (2024) Detecting Cyberattacks to Federated Learning on Software-Defined Networks. Communications in Computer and Information Science, 2022. pp. 120-132. ISSN 1865-0929

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Requirements specifications written in natural language enable us to understand a program’s intended functionality, which we can then translate into operational software. At varying stages of requirement specification, multiple ambiguities emerge. Ambiguities may appear at several levels including the syntactic, semantic, domain, lexical, and pragmatic levels. The primary objective of this study is to identify requirements’ pragmatic ambiguity. Pragmatic ambiguity occurs when the same set of circumstances can be interpreted in multiple ways. It requires consideration of the context statement of the requirements. Prior research has developed methods for obtaining concepts based on individual nodes, so there is room for improvement in the requirements interpretation procedure. This research aims to develop a more effective model for identifying pragmatic ambiguity in requirement definition. To better interpret requirements, we introduced the Concept Maximum Matching (CMM) technique, which extracts concepts based on edges. The CMM technique significantly improves precision because it permits a more accurate interpretation of requirements based on the relative weight of their edges. Obtaining an F-measure score of 0.754 as opposed to 0.563 in existing models, the evaluation results demonstrate that CMM is a substantial improvement over the previous method. metadata Aslam, Khadija and Iqbal, Faiza and Altaf, Ayesha and Hussain, Naveed and Gracia Villar, Mónica and Soriano Flores, Emmanuel and Diez, Isabel De La Torre and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, monica.gracia@uneatlantico.es, emmanuel.soriano@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2024) Detecting Pragmatic Ambiguity in Requirement Specification Using Novel Concept Maximum Matching Approach Based on Graph Network. IEEE Access. p. 1. ISSN 2169-3536

Article Subjects > Biomedicine
Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Non-Insulin-Dependent Diabetes Mellitus (NIDDM) is a chronic health condition caused by high blood sugar levels, and if not treated early, it can lead to serious complications i.e. blindness. Human Activity Recognition (HAR) offers potential for early NIDDM diagnosis, emerging as a key application for HAR technology. This research introduces DiabSense, a state-of-the-art smartphone-dependent system for early staging of NIDDM. DiabSense incorporates HAR and Diabetic Retinopathy (DR) upon leveraging the power of two different Graph Neural Networks (GNN). HAR uses a comprehensive array of 23 human activities resembling Diabetes symptoms, and DR is a prevalent complication of NIDDM. Graph Attention Network (GAT) in HAR achieved 98.32% accuracy on sensor data, while Graph Convolutional Network (GCN) in the Aptos 2019 dataset scored 84.48%, surpassing other state-of-the-art models. The trained GCN analyzed retinal images of four experimental human subjects for DR report generation, and GAT generated their average duration of daily activities over 30 days. The daily activities in non-diabetic periods of diabetic patients were measured and compared with the daily activities of the experimental subjects, which helped generate risk factors. Fusing risk factors with DR conditions enabled early diagnosis recommendations for the experimental subjects despite the absence of any apparent symptoms. The comparison of DiabSense system outcome with clinical diagnosis reports in the experimental subjects was conducted using the A1C test. The test results confirmed the accurate assessment of early diagnosis requirements for experimental subjects by the system. Overall, DiabSense exhibits significant potential for ensuring early NIDDM treatment, improving millions of lives worldwide. metadata Alam, Md Nuho Ul and Hasnine, Ibrahim and Bahadur, Erfanul Hoque and Masum, Abdul Kadar Muhammad and Briones Urbano, Mercedes and Masías Vergara, Manuel and Uddin, Jia and Ashraf, Imran and Samad, Md. Abdus mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, mercedes.briones@uneatlantico.es, manuel.masias@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2024) DiabSense: early diagnosis of non-insulin-dependent diabetes mellitus using smartphone-based human activity recognition and diabetic retinopathy analysis with Graph Neural Network. Journal of Big Data, 11 (1). ISSN 2196-1115

Article Subjects > Biomedicine
Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Objective Epileptic seizures are neurological events that pose significant risks of physical injuries characterized by sudden, abnormal bursts of electrical activity in the brain, often leading to loss of consciousness and uncontrolled movements. Early seizure detection is essential for timely treatments and better patient outcomes. To address this critical issue, there is a need for an advanced artificial intelligence approach for the early detection of epileptic seizure disorder. Methods This study primarily focuses on designing a novel ensemble approach to perform early detection of epileptic seizure disease with high performance. A novel ensemble approach consisting of a fast, independent component analysis random forest (FIR) and prediction probability is proposed, which uses electroencephalography (EEG) data to investigate the efficacy of the proposed approach for early detection of epileptic seizures. The FIR model extracts independent components and class prediction probability features, creating a new feature set. The proposed model combined integrated component analysis (ICA) with predicting probability to enhance seizure recognition accuracy scores. Extensive experimental evaluations demonstrate that FIR assists machine learning models to obtain superior results compared to original features. Results The research gap is addressed using combined features to improve the performance of epileptic seizure detection compared to a single feature set. In particular, the ensemble model FIR with support vector machine (FIR + SVM) outperforms other methods, achieving an accuracy of 98.4% for epileptic seizure detection. Conclusions The proposed FIR has the potential for early diagnosis of epileptic seizures and can significantly help the medical industry with enhanced detection and timely interventions. metadata Khalid, Madiha and Raza, Ali and Akhtar, Adnan and Rustam, Furqan and Brito Ballester, Julién and Rodríguez Velasco, Carmen Lilí and Díez, Isabel de la Torre and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, julien.brito@uneatlantico.es, carmen.rodriguez@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2024) Diagnosing epileptic seizures using combined features from independent components and prediction probability from EEG data. DIGITAL HEALTH, 10. ISSN 2055-2076

Article Subjects > Biomedicine Europe University of Atlantic > Research > Articles and books Abierto Inglés Background Plasma biomarkers of Alzheimer’s disease (AD), especially p-tau217, are promising tools to identify subjects with amyloid deposition in the brain, determined either by cerebrospinal fluid (CSF) or positron emission tomography. However, it is essential to measure them in an accurate and fully automated way in order to apply them in clinical practice. Objectives To evaluate the diagnostic performance of the fully-automated Lumipulse plasma p-tau217 assay in preclinical AD. Design Cross-sectional analyses from a prospective cohort. Setting A population-based study. Participants Volunteers over 55 years without cognitive impairment or contraindications for complementary tests. Measurements Plasma p-tau217 was measured with the fully-automated Lumipulse assay, as well as CSF Aβ40, Aβ42, p-taul81, and t-tau levels. We correlated plasma p-tau217 with CSF Aβ40, Aβ42 and p-tau181, and assessed the differences in plasma p-tau217 according to CSF amyloid status (A−/+), AD status (AD+ being those subjects A+T+ and AD- the rest) and ATN group. We performed ROC curves and measured the areas under the curve (AUC) using CSF amyloid as result, and both p-tau217 and ApoE4 status as predictor. Results We screened 209 cognitively unimpaired volunteers with a mean age 64 years (60–69) and 30.2% of ApoE4 carriers. Plasma p-tau217 correlated significantly with CSF Aβ42/Aβ40 (Rho=−0.51; p-value<0.001) and p-tau181 (r=0.59; p-value<0.001). Its levels were significantly higher in A+ subjects (0.26 pg/ml) compared with A- (0.12 pg/ml; p-value<0.001); and along ATN groups. It predicts CSF amyloid pathology with an AUC of 0.85. Conclusions Plasma p-tau217 measured using the Lumipulse platform shows promise as an accurate biomarker of preclinical AD pathology. metadata Martínez-Dubarbie, F. and Guerra-Ruiz, A. and López-García, S. and Lage, C. and Fernández-Matarrubia, M. and Infante, J. and Pozueta-Cantudo, A. and García-Martínez, M. and Corrales Pardo, Andrea and Bravo, M. and López-Hoyos, M. and Irure-Ventura, J. and Valeriano-Lorenzo, E. and García-Unzueta, M.T. and Sánchez-Juan, P. and Rodríguez-Rodríguez, E. mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, andrea.corrales@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2024) Diagnostic Accuracy of Plasma p-tau217 for Detecting Pathological Cerebrospinal Fluid Changes in Cognitively Unimpaired Subjects Using the Lumipulse Platform. The Journal of Prevention of Alzheimer's Disease, 11 (6). pp. 1581-1591. ISSN 22745807

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Cerrado Inglés Background: Arterial stiffness and atherosclerosis are known risk factors for cardiovascular morbidity and mortality. Vegetarian diets have been associated with cardiovascular benefits, including improvements in metabolic parameters. However, the impact of a vegetarian diet on cardiovascular parameters, specifically arterial stiffness and atherosclerosis, in healthy individuals remains unclear. Thus, this study aims to analyze differences in arterial stiffness and atherosclerosis between vegetarian and omnivorous diets in healthy subjects. Methods: A systematic review and meta-analysis were conducted following established guidelines. PubMed, Scopus, Web of Science, and Cochrane Library databases were searched for studies examining the association between vegetarian and omnivorous diets with arterial stiffness and atherosclerosis. Cross-sectional studies reporting carotid to femoral pulse wave velocity (cf-PWv) as a measure of arterial stiffness and carotid intima media thickness (c-IMT) as a measure of atherosclerosis were included. Data were synthesized using random effects models, and sensitivity analyses, meta-regressions, and assessment of publication bias were performed. Results: Ten studies were included in the systematic review, and seven studies were included in the meta-analysis. The pooled analysis demonstrated that individuals following a vegetarian diet had differences in the levels of arterial stiffness (cf-PWv) compared to those following an omnivorous diet (MD: −0.43 m s−1; 95% CI: −0.63, −0.23). Similarly, atherosclerosis (c-IMT) was found to be different in individuals adhering to a vegetarian dietary pattern (MD = −29.86 mm; 95% CI: −58.41, −1.32). Conclusions: Our findings suggest that a vegetarian diet is associated with improved arterial stiffness and reduced atherosclerosis in healthy individuals. These results support the inclusion of a well-balanced vegetarian dietary pattern in the prevention and management of cardiovascular diseases. However, further research is needed to explore the effects of a vegetarian diet on arterial health in diverse populations and to assess long-term cardiovascular outcomes. metadata Saz-Lara, Alicia and Battino, Maurizio and del Saz Lara, Andrea and Cavero-Redondo, Iván and Dávalos, Alberto and López de Las Hazas, María-Carmen and Visioli, Francesco and Lucerón-Lucas-Torres, Maribel and Giampieri, Francesca mail UNSPECIFIED, maurizio.battino@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, francesca.giampieri@uneatlantico.es (2024) Differences in carotid to femoral pulse wave velocity and carotid intima media thickness between vegetarian and omnivorous diets in healthy subjects: a systematic review and meta-analysis. Food & Function, 15 (3). pp. 1135-1143. ISSN 2042-6496

Article Subjects > Biomedicine Europe University of Atlantic > Research > Articles and books Abierto Inglés The microbiota is in symbiosis with the human body as a holobiont. Infertility conditions affect the female reproductive tract (FRT) and its resident microbiota. However, a disturbance in homeostasis could influence the FRT and other distal body sites, such as the gastrointestinal tract (GIT). We included 21 patients with endometriosis and other infertility-associated diseases with clinical profiles and biological samples from the FRT (endometrium, endometrial fluid, and vagina), and GIT samples (oral and feces). We performed a 16S rRNA analysis of site-specific microbial communities and estimated diversity metrics. The study found body site-specific microbial patterns in the FRT–GIT. In both study groups, Lactobacillus was the most shared Amplicon Sequence Variant (ASV), a precise identifier of microbial sequences, between endometrial and vagina samples. However, shared Gardnerella and Enterobacteriaceae ASVs were linked to other conditions but not endometriosis. Remarkably, Haemophilus was a specific GIT-shared taxon in endometriosis cases. In conclusion, infertility influences distinctly the FRT and GIT microbiomes, with endometriosis showing unique microbial characteristics. We proposed the concept of ‘female holobiont’ as a community that comprises the host and microbes that must maintain overall homeostasis across all body sites to ensure a woman’s health. Insights into these microbial patterns not only advance our understanding of the pathophysiology of infertility but also open new avenues for developing microbe-based therapeutic interventions aimed at restoring microbial balance, thereby enhancing fertility prospects. metadata Marcos, Ana T. and Rus, Maria J. and Areal-Quecuty, Victoria and Simon-Soro, Aurea and Navarro-Pando, José Manuel mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, jose.navarro@uneatlantico.es (2024) Distinct Gastrointestinal and Reproductive Microbial Patterns in Female Holobiont of Infertility. Microorganisms, 12 (5). p. 989. ISSN 2076-2607

Article Subjects > Social Sciences Europe University of Atlantic > Research > Articles and books Cerrado Inglés Technological firms invest in R&D looking for innovative solutions but assuming high costs and great (technological) uncertainty regarding final results and returns. Additionally, they face other problems related to R&D management. This empirical study tries to determine which of the factors favour or constrain the decision of these firms to engage in R&D. The analysis uses financial data of 14,619 ICT listed companies of 22 countries from 2003 to 2018. Additionally, macroeconomic data specific for the countries and the sector were used. For the analysis of dynamic panel data, a System-GMM method is used. Among the findings, we highlight that cash flow, contrary to the known theoretical models and empirical evidences, negatively impacts on R&D investment. Debt is neither the right source for R&D funding, as the effect is also negative. This suggests that ICT companies are forced to manage their R&D activities differently, relying more on other funding sources, taking advantage of growth opportunities and benefiting from a favourable macroeconomic environment in terms of growth and increased business sector spending on R&D. These results are similar in both sub-sectors and in all countries, both bank- and market based. The exception is firms with few growth opportunities and little debt. metadata Alexeeva-Alexeev, Inna and Mazas Pérez-Oleag, Cristina mail inna.alexeeva@uneatlantico.es, cristina.mazas@uneatlantico.es (2024) Do ICT firms manage R&D differently? Firm-level and macroeconomic effects on corporate R&D investment: Empirical evidence from a multi-countries context. Technological Forecasting and Social Change, 198. p. 122970. ISSN 00401625

Book Section Subjects > Engineering
Subjects > Teaching
Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Cerrado Inglés The E-Dieting Lab project addresses the critical need for improved practical education in dietetics, responding to the growing obesity crisis and its associated health and economic impacts. This innovative approach combines digital tools, virtual patients, and a service-learning model to enhance the training of dietetics students. The project aims to bridge the gap between theoretical knowledge and real-world practice by creating simulated professional experiences based on the Nutrition Care Process (NCP). By incorporating realistic patient scenarios and virtual interactions, students develop crucial interpersonal skills and patient follow-up abilities. The initiative also promotes community engagement, allowing students to apply their knowledge in meaningful, socially beneficial ways. Preliminary results and impressions from participants will be analysed to assess the effectiveness of this novel educational approach in improving dietetics training and preparing future professionals for the challenges of modern healthcare. metadata Elío Pascual, Iñaki and Prola, Thomas and Sumalla Cano, Sandra and Tutusaus, Kilian mail inaki.elio@uneatlantico.es, thomas.prola@uneatlantico.es, sandra.sumalla@uneatlantico.es, kilian.tutusaus@uneatlantico.es (2024) E+DIETing_LAB Digital Lab for Education in Dietetics Combining Experiential Learning and Community Service. In: Technological Approaches to Medical and Pharmaceutical Education. IGI Global Scientific Publishing. ISBN 9798337311272

Article Subjects > Biomedicine
Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Cerrado Inglés Brain–computer interface (BCI) technology holds promise for individuals with profound motor impairments, offering the potential for communication and control. Motor imagery (MI)-based BCI systems are particularly relevant in this context. Despite their potential, achieving accurate and robust classification of MI tasks using electroencephalography (EEG) data remains a significant challenge. In this paper, we employed the Minimum Redundancy Maximum Relevance (MRMR) algorithm to optimize channel selection. Furthermore, we introduced a hybrid optimization approach that combines the War Strategy Optimization (WSO) and Chimp Optimization Algorithm (ChOA). This hybridization significantly enhances the classification model’s overall performance and adaptability. A two-tier deep learning architecture is proposed for classification, consisting of a Convolutional Neural Network (CNN) and a modified Deep Neural Network (M-DNN). The CNN focuses on capturing temporal correlations within EEG data, while the M-DNN is designed to extract high-level spatial characteristics from selected EEG channels. Integrating optimal channel selection, hybrid optimization, and the two-tier deep learning methodology in our BCI framework presents an enhanced approach for precise and effective BCI control. Our model got 95.06% accuracy with high precision. This advancement has the potential to significantly impact neurorehabilitation and assistive technology applications, facilitating improved communication and control for individuals with motor impairments metadata Kumari, Annu and Edla, Damodar Reddy and Reddy, R. Ravinder and Jannu, Srikanth and Vidyarthi, Ankit and Alkhayyat, Ahmed and Garat de Marin, Mirtha Silvana mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, silvana.marin@uneatlantico.es (2024) EEG-based motor imagery channel selection and classification using hybrid optimization and two-tier deep learning. Journal of Neuroscience Methods, 409. p. 110215. ISSN 01650270

Article Subjects > Biomedicine
Subjects > Nutrition Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production Abierto Inglés In order to promote the sustainable development of aquaculture, it is of great importance to better understand fish diseases caused by classic and emerging bacterial pathogens. Strains of classic fish pathogens such as Aeromonas, Vibrio, Photobacterium, Edwardsiella, Yersinia, Flavobacterium, or Piscirickettsia. metadata Ramos-Vivas, José and Acosta, Félix mail jose.ramos@uneatlantico.es, UNSPECIFIED (2024) Editorial: Host-bacteria interactions in fish pathogens. Frontiers in Cellular and Infection Microbiology, 14. ISSN 2235-2988

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production Cerrado Inglés In this study, the phytochemical profile of fifty olive leaves (OL) extracts from Spain, Italy, Greece, Portugal, and Morocco was characterized and their anti-cholinergic, anti-inflammatory, and antioxidant activities were evaluated. Luteolin-7-O-glucoside, isoharmnentin, and apigenin were involved in the acetylcholinesterase (AChE) inhibitory activity, while oleuropein and hydroxytyrosol showed noteworthy potential. Secoiridoids contributed to the cyclooxygenase-2 inhibitory activity and antioxidant capacity. Compounds such as oleuropein, ligstroside and luteolin-7-O-glucoside, may exert an important role in the ferric reducing antioxidant capacity. It should be also highlighted the role of hydroxytyrosol, hydroxycoumarins, and verbascoside concerning the antioxidant activity. This research provides valuable insights and confirms that specific compounds within OL extracts contribute to distinct anti-cholinergic, anti-inflammatory, and anti-oxidative effects. metadata Romero-Márquez, Jose M. and Navarro-Hortal, María D. and Forbes-Hernández, Tamara Y. and Varela-López, Alfonso and Puentes, Juan G. and Sánchez-González, Cristina and Sumalla Cano, Sandra and Battino, Maurizio and García-Ruiz, Roberto and Sánchez, Sebastián and Quiles, José L. mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, sandra.sumalla@uneatlantico.es, maurizio.battino@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, jose.quiles@uneatlantico.es (2024) Effect of olive leaf phytochemicals on the anti-acetylcholinesterase, anti-cyclooxygenase-2 and ferric reducing antioxidant capacity. Food Chemistry, 444. p. 138516. ISSN 03088146

Article Subjects > Physical Education and Sport Europe University of Atlantic > Research > Articles and books Abierto Inglés Objectives: The aim of this study was to evaluate the incidence and associated factors of urinary incontinence in women who participate in weightlifting sports. Material and method: The final sample included 22 female athletes aged 18–27. Participants were divided into a control group (n = 6) and two intervention groups based on training frequency: IG1 (≥4 days/week, n = 8) and IG2 (<4 days/week, n = 8). The intervention, based on Kegel exercises performed five times weekly for six weeks. UI impact was assessed pre and post intervention using the ICIQ-LUTSqol questionnaire. Results: A high prevalence of urinary incontinence (UI) was reported (63.6%), especially during sports activity. In the intervention groups, no statistically significant differences were observed in ICIQ-LUTSqol scores between groups (P = 0.65) or over time (P = 0.47), nor in the group-by-time interaction (P = 0.15). However, a non-significant trend suggested a reduction in ICIQ-LUTSqol scores in IG2 post-intervention. However, a non significant trend suggested a reduction in ICIQ-LUTSqol scores in IG2 post-intervention, although eta 2 was low. Conclusions: The six-week Kegel intervention had limited impact on UI symptoms among these young female athletes, suggesting that longer interventions and consideration of additional factors may be necessary to achieve significant UI reduction in this population. metadata Pulgar, Susana and Battyán Padró, Lya and del Pueyo, Elena and Olmedillas, Hugo mail susana.pulgar@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2024) Effectiveness of a Kegel protocol on urinary incontinence in female weightlifters. Archivos de Medicina del Deporte, 41 (6). pp. 303-309. ISSN 02128799

Article Subjects > Teaching Europe University of Atlantic > Research > Articles and books Abierto Inglés Background: Research has shown that 20% of Czech teachers suffer with burnout symptoms and 65% are at risk of burning out, which suggests that it is essential to continue addressing the issue of stress in Czech teachers. The main objective of this study was to evaluate a self-compassion and mindfulness-based professional development program for primary school teachers in the Czech Republic. Methods: Five schools were recruited, two as intervention schools (n of teachers = 47) and three as controls (n of teachers = 57). Teachers completed questionnaires at three time points: pre-test in September 2018, post-test in November 2018, and a follow-up in April 2019. Results: The results at post-test indicated that teachers in the intervention group scored significantly higher (p < 0.05) in self-efficacy and self-compassion, and significantly lower in depression, anxiety and emotional exhaustion, compared to the controls. The intervention teachers were marginally lower (p < 0.10) in perceived stress and marginally higher in subjective well-being, compared to the controls. At follow-up, teachers’ subjective well-being in the control group significantly worsened compared to the baseline. However, the intervention group did not show significant changes over time, which suggests a “protective effect” on the intervention group against worsening during the school year. Conclusions: The study suggests that providing teachers with self-compassion and mindfulness practices can lead to beneficial effects on several outcome variables. Further studies need to investigate if these benefits can be sustained and if they affect teachers’ physical health, their relationships with students, and the students’ outcomes. metadata Dvořáková, Kamila and García Valladares, Laura and Butzer, Bethany and Lange, Calvin and Greenberg, Mark mail UNSPECIFIED, laura.garcia@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2024) Effectiveness of a Mindfulness-Based Professional Development Program for Primary School Teachers in the Czech Republic: A Quasi-Experimental Study. International Journal of Environmental Research and Public Health, 21 (12). p. 1669. ISSN 1660-4601

Article Subjects > Physical Education and Sport Europe University of Atlantic > Research > Articles and books Abierto Inglés Futsal is a high intensity team sport with intermittent actions of short duration, so it is necessary to include different training strategies to improve explosive actions. There is a gap in the scientific literature regarding training programs that improve the performance of young futsal players. The aim of this study was to determine the effects of different strength and velocity training programs on lower body physical performance in youth futsal players. Forty-two youth futsal players were divided into control group (CG, n = 14) and a strength intervention group (SG, n = 14), which included a weekly session for 8 weeks of eccentric strength training, plyometrics and core strengthening, and a velocity intervention group (VG, n = 14), which included a weekly session during 8 weeks of training with linear speed exercises and with change of direction, accelerations with resistance bands and core strengthening. SG significantly improved horizontal jump (HJ) (p:0.02), V-CUT (p:0.91) and change of direction deficit (CODD) (p:0.01). VG showed significant improvements in HJ (p:0.01), in 25 m sprint (p:0.01), in total repeated sprint ability time (p:0.01), in V-CUT (p:0.01) and in CODD (p:0.01). SG showed significant intergroup differences (p:0.01) in COD variables with respect to CG and VG. In conclusion, SG and VG showed significant improvements in lower body performance variables in youth futsal players. In addition, the SG has substantial changes in COD compared to the other two groups, so it has a greater effect. metadata Villanueva-Guerrero, Oscar and Lozano, Demetrio and Roso-Moliner, Alberto and Nobari, Hadi and Lago-Fuentes, Carlos and Mainer-Pardos, Elena mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, carlos.lago@uneatlantico.es, UNSPECIFIED (2024) Effects of different strength and velocity training programs on physical performance in youth futsal players. Heliyon, 10 (10). e30747. ISSN 24058440

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Cerrado Inglés The aim of this study was to investigate the effects of enzymatic treatments (pectinase, pectin lyase, and cellulase) on the in vitro digestion and fermentation characteristics of whole mulberry fruit juice. The analysis focused on changes in carbohydrate properties within the black mulberry fruit matrix during simulated digestion and fermentation. Human fecal microbiota were collected and introduced to the fruit matrix to monitor the fate of both soluble and insoluble polysaccharides during fermentation. The results revealed that enzymatic treatments enhanced the solubilization of carbohydrates from mulberry fruits, with pectinase showing the most significant effect. Throughout the process of in vitro digestion, there was a gradual increase in the percentage of solubilized carbohydrates from the mulberry juice substrate. The digested suspensions underwent dialysis to remove degradation fragments, and a lower quantity of carbohydrate in the enzyme-treated groups compared to the control. Polysaccharide populations with varying molecular weights (Mw) were obtained from the soluble fractions of mulberry residues for subsequent fermentation. An increase in Mw of soluble polysaccharides was detected by HPSEC during fermentation in certain cases. The gut microbiota demonstrated the ability to convert specific insoluble fractions into soluble components, which were subsequently subjected to microbial utilization. Enzymatic treatments during mulberry juice preparation can potentially positively impact health by influencing gut microbiota and short-chain fatty acid (SCFA) modulations. Enzymes could serve as valuable tools for producing functional fruit and vegetable juices, with the need to specify processing conditions for specific raw materials remaining a subject of further investigation. metadata Luo, Peihuan and Ai, Jian and Wang, Yuxin and Wang, Songen and Schols, Henk A. and Smidt, Hauke and Battino, Maurizio and Bai, Weibin and Tian, Lingmin mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, maurizio.battino@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2024) Effects of enzymatic treatment on the in vitro digestion and fermentation patterns of mulberry fruit juice: A focus on carbohydrates. Food Hydrocolloids, 146. p. 109223. ISSN 0268005X

Article Subjects > Biomedicine
Subjects > Engineering
Subjects > Nutrition Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Background and objectives: As microbes are developing resistance to antibiotics, natural, botanical drugs or traditional herbal medicine are presently being studied with an eye of great curiosity and hope. Hence, complementary and alternative treatments for uncomplicated pelvic inflammatory disease (uPID) are explored for their efficacy. Therefore, this study determined the therapeutic efficacy and safety of Sesamum indicum Linn seeds with Rosa damascena Mill Oil in uPID with standard control. Additionally, we analyzed the data with machine learning. Materials and methods: We included 60 participants in a double-blind, double-dummy, randomized standard-controlled study. Participants in the Sesame and Rose oil group (SR group) (n = 30) received 14 days course of black sesame powder (5 gm) mixed with rose oil (10 mL) per vaginum at bedtime once daily plus placebo capsules orally. The standard group (SC), received doxycycline 100 mg twice and metronidazole 400 mg thrice orally plus placebo per vaginum for the same duration. The primary outcome was a clinical cure at post-intervention for visual analogue scale (VAS) for lower abdominal pain (LAP), and McCormack pain scale (McPS) for abdominal-pelvic tenderness. The secondary outcome included white blood cells (WBC) cells in the vaginal wet mount test, safety profile, and health-related quality of life assessed by SF-12. In addition, we used AdaBoost (AB), Naïve Bayes (NB), and Decision Tree (DT) classifiers in this study to analyze the experimental data. Results: The clinical cure for LAP and McPS in the SR vs SC group was 82.85% vs 81.48% and 83.85% vs 81.60% on Day 15 respectively. On Day 15, pus cells less than 10 in the SR vs SC group were 86.6% vs 76.6% respectively. No adverse effects were reported in both groups. The improvement in total SF-12 score on Day 30 for the SR vs SC group was 82.79% vs 80.04% respectively. In addition, our Naive Bayes classifier based on the leave-one-out model achieved the maximum accuracy (68.30%) for the classification of both groups of uPID. Conclusion: We concluded that the SR group is cost-effective, safer, and efficacious for curing uPID. Proposed alternative treatment (test drug) could be a substitute of standard drug used for Female genital tract infections. metadata Sumbul, X. and Sultana, Arshiya and Heyat, Md Belal Bin and Rahman, Khaleequr and Akhtar, Faijan and Parveen, Saba and Briones Urbano, Mercedes and Lipari, Vivian and De la Torre Díez, Isabel and Khan, Azmat Ali and Malik, Abdul mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, mercedes.briones@uneatlantico.es, vivian.lipari@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2024) Efficacy and classification of Sesamum indicum linn seeds with Rosa damascena mill oil in uncomplicated pelvic inflammatory disease using machine learning. Frontiers in Chemistry, 12. ISSN 2296-2646

Article Subjects > Biomedicine Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Objective: This study aims to determine the efficacy of the Acacia arabica (Lam.) Willd. and Cinnamomum camphora (L.) J. Presl. vaginal suppository in addressing heavy menstrual bleeding (HMB) and their impact on participants' health-related quality of life (HRQoL) analyzed using machine learning algorithms. Method: A total of 62 participants were enrolled in a double-dummy, single-center study. They were randomly assigned to either the suppository group (SG), receiving a formulation prepared with Acacia arabica gum (Gond Babul) and camphor from Cinnamomum camphora (Kafoor) through two vaginal suppositories (each weighing 3,500 mg) for 7 days at bedtime along with oral placebo capsules, or the tranexamic group (TG), receiving oral tranexamic acid (500 mg) twice a day for 5 days and two placebo vaginal suppositories during menstruation at bedtime for three consecutive menstrual cycles. The primary outcome was the pictorial blood loss assessment chart (PBLAC) for HMB, and secondary outcomes included hemoglobin level and SF-36 HRQoL questionnaire scores. Additionally, machine learning algorithms such as k-nearest neighbor (KNN), AdaBoost (AB), naive Bayes (NB), and random forest (RF) classifiers were employed for analysis. Results: In the SG and TG, the mean PBLAC score decreased from 635.322 ± 504.23 to 67.70 ± 22.37 and 512.93 ± 283.57 to 97.96 ± 39.25, respectively, at post-intervention (TF3), demonstrating a statistically significant difference (p < 0.001). A higher percentage of participants in the SG achieved normal menstrual blood loss compared to the TG (93.5% vs 74.2%). The SG showed a considerable improvement in total SF-36 scores (73.56%) compared to the TG (65.65%), with a statistically significant difference (p < 0.001). Additionally, no serious adverse events were reported in either group. Notably, machine learning algorithms, particularly AB and KNN, demonstrated the highest accuracy within cross-validation models for both primary and secondary outcomes. Conclusion: The A. arabica and C. camphora vaginal suppository is effective, cost-effective, and safe in controlling HMB. This botanical vaginal suppository provides a novel and innovative alternative to traditional interventions, demonstrating promise as an effective management approach for HMB. metadata Fazmiya, Mohamed Joonus Aynul and Sultana, Arshiya and Heyat, Md Belal Bin and Parveen, Saba and Rahman, Khaleequr and Akhtar, Faijan and Khan, Azmat Ali and Alanazi, Amer M. and Ahmed, Zaheer and Díez, Isabel de la Torre and Brito Ballester, Julién and Saripalli, Tirumala Santhosh Kumar mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, julien.brito@uneatlantico.es, UNSPECIFIED (2024) Efficacy of a vaginal suppository formulation prepared with Acacia arabica (Lam.) Willd. gum and Cinnamomum camphora (L.) J. Presl. in heavy menstrual bleeding analyzed using a machine learning technique. Frontiers in Pharmacology, 15. ISSN 1663-9812

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Malaria is an extremely malignant disease and is caused by the bites of infected female mosquitoes. This disease is not only infectious among humans, but among animals as well. Malaria causes mild symptoms like fever, headache, sweating and vomiting, and muscle discomfort; severe symptoms include coma, seizures, and kidney failure. The timely identification of malaria parasites is a challenging and chaotic endeavor for health staff. An expert technician examines the schematic blood smears of infected red blood cells through a microscope. The conventional methods for identifying malaria are not efficient. Machine learning approaches are effective for simple classification challenges but not for complex tasks. Furthermore, machine learning involves rigorous feature engineering to train the model and detect patterns in the features. On the other hand, deep learning works well with complex tasks and automatically extracts low and high-level features from the images to detect disease. In this paper, EfficientNet, a deep learning-based approach for detecting Malaria, is proposed that uses red blood cell images. Experiments are carried out and performance comparison is made with pre-trained deep learning models. In addition, k-fold cross-validation is also used to substantiate the results of the proposed approach. Experiments show that the proposed approach is 97.57% accurate in detecting Malaria from red blood cell images and can be beneficial practically for medical healthcare staff. metadata Mujahid, Muhammad and Rustam, Furqan and Shafique, Rahman and Caro Montero, Elizabeth and Silva Alvarado, Eduardo René and de la Torre Diez, Isabel and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, elizabeth.caro@uneatlantico.es, eduardo.silva@funiber.org, UNSPECIFIED, UNSPECIFIED (2024) Efficient deep learning-based approach for malaria detection using red blood cell smears. Scientific Reports, 14 (1). ISSN 2045-2322

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books Abierto Inglés Background Cancer remains one of the leading causes of mortality globally, with conventional chemotherapy often resulting in severe side effects and limited effectiveness. Recent advancements in bioinformatics and machine learning, particularly deep learning, offer promising new avenues for cancer treatment through the prediction and identification of anticancer peptides. Objective This study aimed to develop and evaluate a deep learning model utilizing a two-dimensional convolutional neural network (2D CNN) to enhance the prediction accuracy of anticancer peptides, addressing the complexities and limitations of current prediction methods. Methods A diverse dataset of peptide sequences with annotated anticancer activity labels was compiled from various public databases and experimental studies. The sequences were preprocessed and encoded using one-hot encoding and additional physicochemical properties. The 2D CNN model was trained and optimized using this dataset, with performance evaluated through metrics such as accuracy, precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC-ROC). Results The proposed 2D CNN model achieved superior performance compared to existing methods, with an accuracy of 0.87, precision of 0.85, recall of 0.89, F1-score of 0.87, and an AUC-ROC value of 0.91. These results indicate the model’s effectiveness in accurately predicting anticancer peptides and capturing intricate spatial patterns within peptide sequences. Conclusion The findings demonstrate the potential of deep learning, specifically 2D CNNs, in advancing the prediction of anticancer peptides. The proposed model significantly improves prediction accuracy, offering a valuable tool for identifying effective peptide candidates for cancer treatment. metadata Salam, Abdu and Ullah, Faizan and Amin, Farhan and Ahmad Khan, Izaz and Garcia Villena, Eduardo and Kuc Castilla, Ángel Gabriel and de la Torre, Isabel mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, angel.kuc@uneatlantico.es, UNSPECIFIED (2024) Efficient prediction of anticancer peptides through deep learning. PeerJ Computer Science, 10. e2171. ISSN 2376-5992

Article Subjects > Social Sciences Europe University of Atlantic > Research > Articles and books Abierto Español El presente trabajo preparado para su publicación en el Anuario Janus, del Observatorio de Relaciones Exteriores (OBSERVARE) de la Universidad Autónoma de Lisboa (UAL), extracta y actualiza diversos elementos de la obra del autor ̈titulada Iberofonía y Paniberismo. Definición y articulación del Mundo Ibérico (Última Línea, 2018). metadata Durántez Prados, Frigdiano Álvaro mail durantez@uneatlantico.es (2024) El espacio multinacional de países de lenguas española y portuguesa: La iberofonía. JANUS ANUARIO (22). pp. 168-173. ISSN 2183-4814

Article Subjects > Biomedicine
Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Diabetes is a persistent health condition led by insufficient use or inappropriate use of insulin in the body. If left undetected, it can lead to further complications involving organ damage such as heart, lungs, and eyes. Timely detection of diabetes helps obtain the right medication, diet, and exercise plan to lead a healthy life. ML approach has been utilized to obtain rapid and reliable diabetes detection, however, existing approaches suffer from the use of limited datasets, lack of generalizability, and lower accuracy. This study proposes a novel feature extraction approach to overcome these limitations by using an ensemble of convolutional neural network (CNN) and long short-term memory (LSTM) models. Multiple datasets are combined to make a larger dataset for experiments and multiple features are utilized for investigating the efficacy of the proposed approach. Features from the extra tree classifier, CNN, and LSTM are also considered for comparison. Experimental results reveal the superb performance of CNN-LSTM-based features with random forest model obtaining a 0.99 accuracy score. This performance is further validated by comparison with existing approaches and k-fold cross-validation which shows the proposed approach provides robust results. metadata Rustam, Furqan and Al-Shamayleh, Ahmad Sami and Shafique, Rahman and Aparicio Obregón, Silvia and Calderón Iglesias, Rubén and Gonzalez, J. Pablo Miramontes and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, silvia.aparicio@uneatlantico.es, ruben.calderon@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2024) Enhanced detection of diabetes mellitus using novel ensemble feature engineering approach and machine learning model. Scientific Reports, 14 (1). ISSN 2045-2322

Article Subjects > Biomedicine
Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Thyroid illness encompasses a range of disorders affecting the thyroid gland, leading to either hyperthyroidism or hypothyroidism, which can significantly impact metabolism and overall health. Hypothyroidism can cause a slowdown in bodily processes, leading to symptoms such as fatigue, weight gain, depression, and cold sensitivity. Hyperthyroidism can lead to increased metabolism, causing symptoms like rapid weight loss, anxiety, irritability, and heart palpitations. Prompt diagnosis and appropriate treatment are crucial in managing thyroid disorders and improving patients’ quality of life. Thyroid illness affects millions worldwide and can significantly impact their quality of life if left untreated. This research aims to propose an effective artificial intelligence-based approach for the early diagnosis of thyroid illness. An open-access thyroid disease dataset based on 3,772 male and female patient observations is used for this research experiment. This study uses the nominal continuous synthetic minority oversampling technique (SMOTE-NC) for data balancing and a fine-tuned light gradient booster machine (LGBM) technique to diagnose thyroid illness and handle class imbalance problems. The proposed SNL (SMOTE-NC-LGBM) approach outperformed the state-of-the-art approach with high-accuracy performance scores of 0.96. We have also applied advanced machine learning and deep learning methods for comparison to evaluate performance. Hyperparameter optimizations are also conducted to enhance thyroid diagnosis performance. In addition, we have applied the explainable Artificial Intelligence (XAI) mechanism based on Shapley Additive exPlanations (SHAP) to enhance the transparency and interpretability of the proposed method by analyzing the decision-making processes. The proposed research revolutionizes the diagnosis of thyroid disorders efficiently and helps specialties overcome thyroid disorders early. metadata Raza, Ali and Eid, Fatma and Caro Montero, Elisabeth and Delgado Noya, Irene and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, elizabeth.caro@uneatlantico.es, irene.delgado@uneatlantico.es, UNSPECIFIED (2024) Enhanced interpretable thyroid disease diagnosis by leveraging synthetic oversampling and machine learning models. BMC Medical Informatics and Decision Making, 24 (1). ISSN 1472-6947

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Humans can carry various diseases, some of which are poorly understood and lack comprehensive solutions. Such a disease can exists in human eye that can affect one or both eyes is diabetic retinopathy (DR) which can impair function, vision, and eventually result in permanent blindness. It is one of those complex complexities. Therefore, early detection of DR can significantly reduce the risk of vision impairment by appropriate treatment and necessary precautions. The primary aim of this study is to leverage cutting-edge models trained on diverse image datasets and propose a CNN model that demonstrates comparable performance. Specifically, we employ transfer learning models such as DenseNet121, Xception, Resnet50, VGG16, VGG19, and InceptionV3, and machine learning models such as SVM, and neural network models like (RNN) for binary and multi-class classification. It has been shown that the proposed approach of multi-label classification with softmax functions and categorical cross-entropy works more effectively, yielding perfect accuracy, precision, and recall values. In particular, Xception achieved an impressive 82% accuracy among all the transfer learning models, setting a new benchmark for the dataset used. However, our proposed CNN model shows superior performance, achieving an accuracy of 95.27% on this dataset, surpassing the state-of-the-art Xception model. Moreover, for single-label (binary classifications), our proposed model achieved perfect accuracy as well. Through exploration of these advances, our objective is to provide a comprehensive overview of the leading methods for the early detection of DR. The aim is to discuss the challenges associated with these methods and highlight potential enhancements. In essence, this paper provides a high-level perspective on the integration of deep learning techniques and machine learning models, coupled with explainable artificial intelligence (XAI) and gradient-weighted class activation mapping (Grad-CAM). We prese... metadata Ahnaf Alavee, Kazi and Hasan, Mehedi and Hasnayen Zillanee, Abu and Mostakim, Moin and Uddin, Jia and Silva Alvarado, Eduardo René and de la Torre Diez, Isabel and Ashraf, Imran and Abdus Samad, Md mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, eduardo.silva@funiber.org, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2024) Enhancing Early Detection of Diabetic Retinopathy Through the Integration of Deep Learning Models and Explainable Artificial Intelligence. IEEE Access, 12. pp. 73950-73969. ISSN 2169-3536

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Efficient traffic management has become a major concern within the framework of smart city projects. However, the increasing complexity of data exchanges and the growing importance of big data makes this task more challenging. Vehicular ad hoc networks (VANETs) face various challenges, including the management of massive data generated by different entities in their environment. In this context, a proposal is put forth for a real-time anomaly detection system with parallel data processing, thereby speeding up data processing. This approach accurately computes vehicle density for each section at any given time, enabling precise traffic management and the provision of information to vehicles regarding traffic density and the safest route to their destination. Furthermore, a machine learning-based prediction system has been developed to mitigate congestion problems and reduce accident risks. Simulations demonstrate that the proposed solution effectively addresses transportation issues while maintaining low latency and high precision. metadata Driss Laanaoui, My and Lachgar, Mohamed and Mohamed, Hanine and Hamid, Hrimech and Gracia Villar, Santos and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, santos.gracia@uneatlantico.es, UNSPECIFIED (2024) Enhancing Urban Traffic Management Through Real-Time Anomaly Detection and Load Balancing. IEEE Access, 12. pp. 63683-63700. ISSN 2169-3536

Article Subjects > Biomedicine Europe University of Atlantic > Research > Articles and books Cerrado Inglés Uterine leiomyomas are the most common benign, monoclonal, gynaecological tumors in a woman’s uterus, while leiomyosarcoma is a rare but aggressive condition caused by the malignant transformation of the myometrium. To overcome the common obstacles related to the methods usually used to study these pathologies, we aimed to devise three-dimensional models of myometrium, uterine leiomyoma and leiomyosarcoma cell lines, using two different types of biocompatible scaffolds. Specifically, we exploited the agarose gel matrix in common 6-well plates and the alginate matrix using Bioprinting INKREDIBLE + (CELLINK), a pneumatic extruded base equipped with a system with double printheads, and a UV printer LED curing system. Both methods allowed the development of 3D spheroids of all three cell types, that were also suitable for morphological investigations. We showed that all cell types embedded in both agarose and alginate formed spheroids in their growth medium. The spheroids successfully proliferated and self-organized into complex structures, developing a sustainable system that emulated the condition of the tissues through the accumulation of extracellular matrix. These models could be useful for a better understanding of pathophysiology, etiopathogenesis, and testing new methods or molecules from a preventive and therapeutic point of view. metadata Pellegrino, Pamela and Greco, Stefania and Duménigo Gonzàlez, Abel and Giampieri, Francesca and Giannubilo, Stefano Raffaele and Delli Carpini, Giovanni and Capocasa, Franco and Mezzetti, Bruno and Battino, Maurizio and Ciavattini, Andrea and Ciarmela, Pasquapina mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, francesca.giampieri@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, maurizio.battino@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2024) Establishment of 3D Cultures of Myometrium, Leiomyoma, and Leiomyosarcoma Cells: Advantages and Disadvantages of Two Different Models. Reproductive Sciences. ISSN 1933-7191

Article Subjects > Biomedicine Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Background: The 2023 dengue outbreak has proven that dengue is not only an endemic disease but also an emerging health threat in Bangladesh. Integrated studies on the epidemiology, clinical characteristics, seasonality, and genotype of dengue are limited. This study was conducted to determine recent trends in the molecular epidemiology, clinical features, and seasonality of dengue outbreaks. Methods: We analyzed data from 41 original studies, extracting epidemiological information from all 41 articles, clinical symptoms from 30 articles, and genotypic diversity from 11 articles. The study adhered to the standards of the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) Statement and Cochrane Collaboration guidelines. Conclusion: This study provides integrated insights into the molecular epidemiology, clinical features, seasonality, and transmission of dengue in Bangladesh and highlights research gaps for future studies. metadata Sharif, Nadim and Opu, Rubayet Rayhan and Saha, Tama and Masud, Abdullah Ibna and Naim, Jannatin and Alsharif, Khalaf F. and Alzahrani, Khalid J. and Silva Alvarado, Eduardo René and Delgado Noya, Irene and De la Torre Díez, Isabel and Dey, Shuvra Kanti mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, eduardo.silva@funiber.org, irene.delgado@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2024) Evolving epidemiology, clinical features, and genotyping of dengue outbreaks in Bangladesh, 2000–2024: a systematic review. Frontiers in Microbiology, 15. ISSN 1664-302X

Article Subjects > Physical Education and Sport Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés OBJECTIVE: This study aimed to analyze the body composition and somatotype of professional soccer players, investigating variations across categories and playing positions. METHODS: An observational, cross-sectional, and analytical study was conducted with 51 male professional soccer players in the U-19 and U-20 categories. Data about sex, age, height, and weight were collected between March and May 2023. Body composition analysis utilized the ISAK protocol for the restricted profile, while somatotype categorization employed the Heath and Carter formula. Statistical analysis was performed using IBM SPSS Statistics V.26, which involved the application of Mann-Whitney and Kruskal-Wallis tests to discern differences in body composition variables and proportionality based on categories and playing positions. The Dunn test further identified specific positions exhibiting significant differences. RESULTS: The study encompassed 51 players, highlighting meaningful differences in body composition. The average body mass in kg was 75.8 (±6.9) for U-20 players and 70.5 (±6.1) for U-19 players. The somatotype values were 2.6-4.6-2.3 for U-20 players and 2.5-4.3-2.8 for U-19 players, with a predominance of muscle mass in all categories, characterizing them as balanced mesomorphs. CONCLUSIONS: Body composition and somatotype findings underscore distinctions in body mass across categories and playing positions, with notably higher body mass and muscle mass predominance in elevated categories. However, the prevailing skeletal muscle development establishes a significant semblance with the recognized somatotype standard for soccer. metadata Zambrano-Villacres, Raynier and Frias-Toral, Evelyn and Maldonado-Ponce, Emily and Poveda-Loor, Carlos and Leal, Paola and Velarde-Sotres, Álvaro and Leonardi, Alice and Trovato, Bruno and Roggio, Federico and Castorina, Alessandro and Wenxin, Xu and Musumeci, Giuseppe mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, alvaro.velarde@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2024) Exploring body composition and somatotype profiles among youth professional soccer players. Mediterranean Journal of Nutrition and Metabolism, 17 (3). pp. 241-254. ISSN 1973798X

Article Subjects > Psychology Europe University of Atlantic > Research > Articles and books Cerrado Inglés Purpose The study aimed to explore the role of parenthood at first episode of psychosis (FEP) on recovery, with a focus on potential sex differences. Methods Sociodemographic, clinical, and neurocognitive information was considered on 610 FEP patients form the PAFIP cohort (Spain). Baseline and three-year follow-up comparisons were carried out. Chi-square tests and ANCOVA analysis were performed controlling for the effect of age and years of education. Results Men comprised 57.54% of the sample, with only 5.41% having offspring when compared to 36.29% of women. Parenthood was related to shorter duration of untreated illness (DUI) in women with children (12.08 months mothers vs. 27.61 months no mothers), showing mothers better premorbid adjustment as well. Childless men presented the worst premorbid adjustment and the highest cannabis and tobacco consumption rates. Mothers presented better global cognitive function, particularly in attention, motor dexterity and executive function at three-year follow-up. Conclusions Diminished parental rates among FEP men could be suggested as a consequence of a younger age of illness onset. Sex roles in caregiving may explain the potential role of parenthood on premorbid phase, with a better and heathier profile, and a more favorable long-term outcome in women. These characteristics may be relevant when adjusting treatment specific needs in men and women with and without offspring. metadata Díaz-Pons, Alexandre and Soler-Andrés, Marina and Ortiz-García de la Foz, Víctor and Murillo-García, Nancy and Yorca-Ruiz, Angel and Magdaleno Herrero, Rebeca and Castaño-Castaño, Sergio and González-Rodríguez, Alexandre and Setién-Suero, Esther and Ayesa-Arriola, Rosa mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, esther.setien@uneatlantico.es, UNSPECIFIED (2024) Exploring parenthood in first episode of psychosis: the potential role of the offspring in the outcome of women. Archives of Women's Mental Health. ISSN 1434-1816

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés With the rapid growth of Internet of Things (IoT) systems, ensuring robust security measures has become paramount. Microservices Architecture (MSA) has emerged as a promising approach for enhancing IoT systems security, yet its adoption in this context lacks comprehensive analysis. This systematic review addresses this research gap by examining the incorporation of MSA in IoT systems from 2010 to 2024. From an initial pool of 4388 studies, selected articles underwent thorough quality assessment with weighted critical appraisal questions and a defined inclusion threshold. This study represents the first comprehensive systematic review to investigate the potential of microservices in IoT, with a particular focus on security aspects. The review explores the merits of MSA, highlighting twelve benefits, eight key challenges, and eight security risks. Additionally, the eight best practices for implementing MSA in IoT systems are extracted. The findings underscore MSA’s utility in fortifying IoT security while also acknowledging complexities and potential vulnerabilities. Moreover, the study calls attention to the importance of incorporating complementary technologies including blockchain and machine learning to address identified gaps effectively. Finally, we propose a taxonomic classification for Microservice-based IoT security patterns, facilitating the categorization and organization of security measures in this context. Such a review can help researchers and practitioners identify existing gaps, highlight potential research directions, and provide guidelines for designing secure and efficient microservice-based IoT systems. metadata El Akhdar, Abir and Baidada, Chafik and Kartit, Ali and Hanine, Mohamed and Osorio García, Carlos Manuel and García Lara, Roberto and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, carlos.osorio@uneatlantico.es, roberto.garcia@unini.edu.mx, UNSPECIFIED (2024) Exploring the Potential of Microservices in Internet of Things: A Systematic Review of Security and Prospects. Sensors, 24 (20). p. 6771. ISSN 1424-8220

Article Subjects > Physical Education and Sport Europe University of Atlantic > Research > Articles and books Abierto Inglés The purpose of this study was to assess the external load demands in futsal, considering both home and away matches and their outcomes, in order to plan microcycles throughout the season based on the external load of each match. The external load of 10 players from a First Division team in the Spanish Futsal League was recorded throughout 15 official matches in the first half of the league championship. The players’ external load was monitored using OLIVER devices. To analyse the influence of the match outcome and location on the external load, a univariate general linear model (GLM) analysis was conducted with Bonferroni post hoc. There are no differences between the variables neither comparing results nor location factors, except for accelerations of 2 to 3 m/s2 (m) per minute and the number of accelerations of 2 to 3 m/s2 per minute, reporting higher value winnings at home than away (p < 0.05). The location and results are not factors that influence on external load in futsal matches, except the number and distance performed in accelerations and distance covered at a low to medium speed. These findings are important for planning microcycles and providing the appropriate dosage to each player to achieve optimal performance in matches. metadata Gadea-Uribarri, Héctor and Lago-Fuentes, Carlos and Bores Arce, Ainhoa and Villavicencio Álvarez, Víctor Emilio and López-García, Sergio and Calero-Morales, Santiago and Mainer-Pardos, Elena mail UNSPECIFIED, carlos.lago@uneatlantico.es, ainhoa.bores@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2024) External Load Evaluation in Elite Futsal: Influence of Match Results and Game Location with IMU Technology. Journal of Functional Morphology and Kinesiology, 9 (3). p. 140. ISSN 2411-5142

Article Subjects > Psychology Europe University of Atlantic > Research > Articles and books Abierto Inglés Myasthenia gravis (MG) is a neuromuscular disease of autoimmune etiology and chronic evolution. In addition to the muscle weakness and fatigue that characterize MG, in some studies patients show an inferior performance in cognitive tasks and difficulties in recognizing basic emotions from facial expressions. However, it remains unclear if these difficulties are due to anxious–depressive symptoms that these patients present or related to cognitive abilities, such as facial recognition. This study had a descriptive cross-sectional design with a sample of 92 participants, 52 patients with MG and 40 healthy controls. The data collection protocol included measures to assess recognition of facial expressions (BRFT), facial emotional expression (FEEL), and levels of anxiety and depression (HADS). The MG group had worse performance than the control group in recognizing “fear” (p = 0.001; r = 0.344), “happiness” (p = 0.000; r = 0.580), “disgust” (p = 0.000; r = 0.399), “surprise” (p = 0.000; r = 0.602), and “anger” (p = 0.007; r = 0.284). Likewise, the MG group also underperformed in facial recognition (p = 0.001; r = 0.338). These difficulties were not related to their levels of anxiety and depression. Alterations were observed both in the recognition of facial emotions and in facial recognition, without being mediated by emotional variables. These difficulties can influence the interpersonal interaction of patients with MG. metadata García-Sanchoyerto, Maddalen and Salgueiro, Monika and Ortega, Javiera and Rodríguez, Alicia Aurora and Parada-Fernández, Pamela and Amayra, Imanol mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, pamela.parada@uneatlantico.es, UNSPECIFIED (2024) Facial and Emotion Recognition Deficits in Myasthenia Gravis. Healthcare, 12 (16). p. 1582. ISSN 2227-9032

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés In contemporary society, depression has emerged as a prominent mental disorder that exhibits exponential growth and exerts a substantial influence on premature mortality. Although numerous research applied machine learning methods to forecast signs of depression. Nevertheless, only a limited number of research have taken into account the severity level as a multiclass variable. Besides, maintaining the equality of data distribution among all the classes rarely happens in practical communities. So, the inevitable class imbalance for multiple variables is considered a substantial challenge in this domain. Furthermore, this research emphasizes the significance of addressing class imbalance issues in the context of multiple classes. We introduced a new approach Feature group partitioning (FGP) in the data preprocessing phase which effectively reduces the dimensionality of features to a minimum. This study utilized synthetic oversampling techniques, specifically Synthetic Minority Over-sampling Technique (SMOTE) and Adaptive Synthetic (ADASYN), for class balancing. The dataset used in this research was collected from university students by administering the Burn Depression Checklist (BDC). For methodological modifications, we implemented heterogeneous ensemble learning stacking, homogeneous ensemble bagging, and five distinct supervised machine learning algorithms. The issue of overfitting was mitigated by evaluating the accuracy of the training, validation, and testing datasets. To justify the effectiveness of the prediction models, balanced accuracy, sensitivity, specificity, precision, and f1-score indices are used. Overall, comprehensive analysis demonstrates the discrimination between the Conventional Depression Screening (CDS) and FGP approach. In summary, the results show that the stacking classifier for FGP with SMOTE approach yields the highest balanced accuracy, with a rate of 92.81%. The empirical evidence has demonstrated that the FGP approach, when combined with the SMOTE, able to produce better performance in predicting the severity of depression. Most importantly the optimization of the training time of the FGP approach for all of the classifiers is a significant achievement of this research. metadata Shaha, Tumpa Rani and Begum, Momotaz and Uddin, Jia and Yélamos Torres, Vanessa and Alemany Iturriaga, Josep and Ashraf, Imran and Samad, Md. Abdus mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, vanessa.yelamos@funiber.org, josep.alemany@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2024) Feature group partitioning: an approach for depression severity prediction with class balancing using machine learning algorithms. BMC Medical Research Methodology, 24 (1). ISSN 1471-2288

Article Subjects > Biomedicine
Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Abierto Inglés Background Cognitive impairment is projected to affect a preponderant proportion of the aging population. Lifelong dietary habits have been hypothesized to play a role in preventing cognitive decline. Among the most studied dietary components, fish consumptionhas been extensively studied for its potential effects on the human brain. Aims To perform a meta-analysis of observational studies exploring the association between fish intake and cognitive impairment/decline and all types of dementia. Methods A systematic search of electronic databases was performed to identify observational studies providing quantitative data on fish consumption and outcomes of interest. Random effects models for meta-analyses using only extreme exposure categories, subgroup analyses, and dose-response analyses were performed to estimate cumulative risk ratios (RRs) and 95% confidence intervals (CIs). Results The meta-analysis comprised 35 studies. Individuals reporting the highest vs. the lowest fish consumption were associated with a lower likelihood of cognitive impairment/decline (RR = 0.82, 95% CI: 0.75, 0.90, I2 = 61.1%), dementia (RR = 0.82, 95% CI: 0.73, 0.93, I2 = 38.7%), and Alzheimer’s disease (RR = 0.80, 95% CI: 0.67, 0.96, I2 = 20.3%). The dose-response relation revealed a significantly decreased risk of cognitive impairment/decline and all cognitive outcomes across higher levels of fish intake up to 30% for 150 g/d (RR = 0.70, 95% CI: 0.52, 0.95). The results of this relation based on APOE ε4 allele status was mixed based on the outcome investigated. Conclusions Current findings suggest fish consumption is associated with a lower risk of cognitive impairment/decline in a dose-response manner, while for dementia and Alzheimer’s disease there is a need for further studies to improve the strength of evidence. metadata Godos, Justyna and Micek, Agnieszka and Currenti, Walter and Franchi, Carlotta and Poli, Andrea and Battino, Maurizio and Dolci, Alberto and Ricci, Cristian and Ungvari, Zoltan and Grosso, Giuseppe mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, maurizio.battino@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2024) Fish consumption, cognitive impairment and dementia: an updated dose-response meta-analysis of observational studies. Aging Clinical and Experimental Research, 36 (1). ISSN 1720-8319

Article Subjects > Biomedicine
Subjects > Nutrition Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Cardiovascular diseases (CVDs) are one of the main causes of mortality and morbidity worldwide. A healthy diet rich in plant-derived compounds such as (poly)phenols appears to have a key role in improving cardiovascular health. Flavan-3-ols represent a subclass of (poly)phenols of great interest for their possible health benefits. In this review, we summarized the results of clinical studies on vascular outcomes of flavan-3-ol supplementation and we focused on the role of the microbiota in CVD. Clinical trials included in this review showed that supplementation with flavan-3-ols mostly derived from cocoa products significantly reduces blood pressure and improves endothelial function. Studies on catechins from green tea demonstrated better results when involving healthy individuals. From a mechanistic point of view, emerging evidence suggests that microbial metabolites may play a role in the observed effects. Their function extends beyond the previous belief of ROS scavenging activity and encompasses a direct impact on gene expression and protein function. Although flavan-3-ols appear to have effects on cardiovascular health, further studies are needed to clarify and confirm these potential benefits and the rising evidence of the potential involvement of the microbiota. metadata Godos, Justyna and Romano, Giovanni Luca and Laudani, Samuele and Gozzo, Lucia and Guerrera, Ida and Dominguez Azpíroz, Irma and Martínez Díaz, Raquel and Quiles, José L. and Battino, Maurizio and Drago, Filippo and Giampieri, Francesca and Galvano, Fabio and Grosso, Giuseppe mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, irma.dominguez@unini.edu.mx, raquel.martinez@uneatlantico.es, jose.quiles@uneatlantico.es, maurizio.battino@uneatlantico.es, UNSPECIFIED, francesca.giampieri@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2024) Flavan-3-ols and Vascular Health: Clinical Evidence and Mechanisms of Action. Nutrients, 16 (15). p. 2471. ISSN 2072-6643

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés In the last decades, the world population and demand for any kind of product have grown exponentially. The rhythm of production to satisfy the request of the population has become unsustainable and the concept of the linear economy, introduced after the Industrial Revolution, has been replaced by a new economic approach, the circular economy. In this new economic model, the concept of “the end of life” is substituted by the concept of restoration, providing a new life to many industrial wastes. Leaves are a by-product of several agricultural cultivations. In recent years, the scientific interest regarding leaf biochemical composition grew, recording that plant leaves may be considered an alternative source of bioactive substances. Plant leaves’ main bioactive compounds are similar to those in fruits, i.e., phenolic acids and esters, flavonols, anthocyanins, and procyanidins. Bioactive compounds can positively influence human health; in fact, it is no coincidence that the leaves were used by our ancestors as a natural remedy for various pathological conditions. Therefore, leaves can be exploited to manufacture many products in food (e.g., being incorporated in food formulations as natural antioxidants, or used to create edible coatings or films for food packaging), cosmetic and pharmaceutical industries (e.g., promising ingredients in anti-aging cosmetics such as oils, serums, dermatological creams, bath gels, and other products). This review focuses on the leaves’ main bioactive compounds and their beneficial health effects, indicating their applications until today to enhance them as a harvesting by-product and highlight their possible reuse for new potential healthy products. metadata Regolo, Lucia and Giampieri, Francesca and Battino, Maurizio and Armas Diaz, Yasmany and Mezzetti, Bruno and Elexpuru Zabaleta, Maria and Mazas Pérez-Oleaga, Cristina and Tutusaus, Kilian and Mazzoni, Luca mail UNSPECIFIED, francesca.giampieri@uneatlantico.es, maurizio.battino@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, maria.elexpuru@uneatlantico.es, cristina.mazas@uneatlantico.es, kilian.tutusaus@uneatlantico.es, UNSPECIFIED (2024) From by-products to new application opportunities: the enhancement of the leaves deriving from the fruit plants for new potential healthy products. Frontiers in Nutrition, 11. ISSN 2296-861X

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Abierto Inglés Many medicinal plant extracts have been proven to have significant health benefits. In contrast, research has shown that some medicinal plant extracts can be toxic, genotoxic, mutagenic, or carcinogenic. Therefore, evaluation of the genotoxicity effects of plant extracts that are used as traditional medicine is essential to ensure they are safe for use and in the search for new medication. This review summarizes 52 published studies on the genotoxicity of 28 plant extracts used in traditional medicine. A brief overview of the selected plant extracts, including, for example, their medicinal uses, pharmacological effects, and primary identified compounds, as well as plant parts used, the extraction method, genotoxic assay, and phytochemicals responsible for genotoxicity effect were provided. The genotoxicity effect of selected plant extracts in most of the reviewed articles was based on the experimental conditions. Among different reviewed studies, A total of 6 plant extracts showed no genotoxic effect, other 14 plant extracts showed either genotoxic or mutagenic effect and 14 plant extracts showed anti-genotoxic effect against different genotoxic induced agents. In addition, 4 plant extracts showed both genotoxic and non-genotoxic effects and 6 plant extracts showed both genotoxic and antigenotoxic effects. While some suggestions on the responsible compounds of the genotoxicity effects were proposed, the proposed responsible phytochemicals were not individually tested for the genotoxicity potential to confirm the findings. In addition, the mechanisms by which most plant extracts exert their genotoxicity effect remain unidentified. Therefore, more research on the genotoxicity of medicinal plant extracts and their genotoxicity mechanisms is required. metadata Al-Naqeb, Ghanya and Kalmpourtzidou, Aliki and Giampieri, Francesca and De Giuseppe, Rachele and Cena, Hellas mail UNSPECIFIED, UNSPECIFIED, francesca.giampieri@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2024) Genotoxic and antigenotoxic medicinal plant extracts and their main phytochemicals: “A review”. Frontiers in Pharmacology, 15. ISSN 1663-9812

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books Abierto Inglés In the studies on Prehistoric Graphic Expression, there are recurrent discussions about the tracings generated by different observers of the same motif. Methodological issues concerning the role of archaeological imaging are often implied within those debates. Do the tracings belong to the observational data exposition chapter, or are they part of the interpretative conclusions? How can the current technological scenario help solve these problems? In 2017, we conducted new documentation of the Peña Tu rock shelter, a well-known site with an intriguing post-palaeolithic graphic collection documented on several occasions throughout the twentieth century. Our objective was to provide quantifiable and, if possible, objective documentation of the painted and engraved remnants on the shelter’s surface. To achieve this, we employed two data capture strategies. One strategy focused on analysing the vestiges of paintings using a hyperspectral sensor, while the other centred on the geometric definition of engravings and the rock support, utilising photogrammetric techniques and laser scanning. These approaches presented various parallax challenges. Despite these challenges, our results were highly satisfactory. We resolved uncertainties regarding the formal features of specific designs that had been subject to debate for a long time. Additionally, we discovered previously unpublished areas with traces of paintings. Lastly, we developed a map highlighting recent alterations and deteriorations, providing a valuable tool for assessing the site’s preservation status. In conclusion, by employing advanced technology and comprehensive documentation methods, we significantly contributed to understanding and preserving the prehistoric graphic expressions at the Peña Tu rock shelter. metadata Teira, Luis and Bayarri Cayón, Vicente and Ontañón, Roberto and Castillo, Elena and Arias, Pablo mail UNSPECIFIED, vicente.bayarri@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2024) Geometric and radiometric recording of prehistoric graphic expression: the case of Peña Tu (Asturias, Spain). Archaeological and Anthropological Sciences, 16 (2). ISSN 1866-9557

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Abierto Inglés Vegetarian diets are plant-based diets including all the edible foods from the Plant Kingdom, such as grains, legumes, vegetables, fruits, nuts, and seeds. Dairy and eggs can be added in small amounts in the lacto-ovo-vegetarian subtype, or not at all in the vegan subtype. The abundance of non-processed plant foods—typical of all well-planned diets, including vegetarian ones—can provide the body with numerous protective factors (fiber, phytocompounds), while limiting the intake of harmful nutrients like saturated fats, heme-iron, and cholesterol. The beneficial effects on health of this balance have been reported for many main chronic diseases, in both observational and intervention studies. The scientific literature indicates that vegetarians have a lower risk of certain types of cancer, overall cancer, overweight-obesity, type 2 diabetes, dyslipidemia, hypertension, and vascular diseases. Since the trend of following a vegetarian diet is increasing among citizens of developed countries, the knowledge in the field will benefit from further studies confirming the consistency of these findings and clarifying the effects of vegetarian diets on other controversial topics. metadata Baroni, Luciana and Rizzo, Gianluca and Galchenko, Alexey Vladimirovich and Zavoli, Martina and Serventi, Luca and Battino, Maurizio mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, maurizio.battino@uneatlantico.es (2024) Health Benefits of Vegetarian Diets: An Insight into the Main Topics. Foods, 13 (15). p. 2398. ISSN 2304-8158

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Wafer mappings (WM) help diagnose low-yield issues in semiconductor production by offering vital information about process anomalies. As integrated circuits continue to grow in complexity, doing efficient yield analyses is becoming more essential but also more difficult. Semiconductor manufacturers require constant attention to reliability and efficiency. Using the capabilities of convolutional neural network (CNN) models improved by hierarchical attention module (HAM), wafer hotspot detection is achieved throughout the fabrication process. In an effort to achieve accurate hotspot detection, this study examines a variety of model combinations, including CNN, CNN+long short-term memory (LSTM) LSTM, CNN+Autoencoder, CNN+artificial neural network (ANN), LSTM+HAM, Autoencoder+HAM, ANN+HAM, and CNN+HAM. Data augmentation strategies are utilized to enhance the model’s resilience by optimizing its performance on a variety of datasets. Experimental results indicate a superior performance of 94.58% accuracy using the CNN+HAM model. K-fold cross-validation results using 3, 5, 7, and 10 folds indicate mean accuracy of 94.66%, 94.67%, 94.66%, and 94.66%, for the proposed approach, respectively. The proposed model performs better than recent existing works on wafer hotspot detection. Performance comparison with existing models further validates its robustness and performance. metadata Shahroz, Mobeen and Ali, Mudasir and Tahir, Alishba and Fabian Gongora, Henry and Uc Ríos, Carlos Eduardo and Abdus Samad, Md and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, henry.gongora@uneatlantico.es, carlos.uc@unini.edu.mx, UNSPECIFIED, UNSPECIFIED (2024) Hierarchical Attention Module-Based Hotspot Detection in Wafer Fabrication Using Convolutional Neural Network Model. IEEE Access, 12. pp. 92840-92855. ISSN 2169-3536

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Much of nutrition research has been conventionally based on the use of simplistic in vitro systems or animal models, which have been extensively employed in an effort to better understand the relationships between diet and complex diseases as well as to evaluate food safety. Although these models have undeniably contributed to increase our mechanistic understanding of basic biological processes, they do not adequately model complex human physiopathological phenomena, creating concerns about the translatability to humans. During the last decade, extraordinary advancement in stem cell culturing, three-dimensional cell cultures, sequencing technologies, and computer science has occurred, which has originated a wealth of novel human-based and more physiologically relevant tools. These tools, also known as “new approach methodologies,” which comprise patient-derived organoids, organs-on-chip, multi-omics approach, along with computational models and analysis, represent innovative and exciting tools to forward nutrition research from a human-biology-oriented perspective. After considering some shortcomings of conventional in vitro and vivo approaches, here we describe the main novel available and emerging tools that are appropriate for designing a more human-relevant nutrition research. Our aim is to encourage discussion on the opportunity to explore innovative paths in nutrition research and to promote a paradigm-change toward a more human biology-focused approach to better understand human nutritional pathophysiology, to evaluate novel food products, and to develop more effective targeted preventive or therapeutic strategies while helping in reducing the number and replacing animals employed in nutrition research. metadata Cassotta, Manuela and Cianciosi, Danila and Elexpuru Zabaleta, Maria and Elío Pascual, Iñaki and Sumalla Cano, Sandra and Giampieri, Francesca and Battino, Maurizio mail manucassotta@gmail.com, UNSPECIFIED, maria.elexpuru@uneatlantico.es, inaki.elio@uneatlantico.es, sandra.sumalla@uneatlantico.es, francesca.giampieri@uneatlantico.es, maurizio.battino@uneatlantico.es (2024) Human‐based new approach methodologies to accelerate advances in nutrition research. Food Frontiers. pp. 1-32. ISSN 2643-8429

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books Abierto Inglés Accurate software cost estimation in Global Software Development (GSD) remains challenging due to reliance on historical data and expert judgments. Traditional models, such as the Constructive Cost Model (COCOMO II), rely heavily on historical and accurate data. In addition, expert judgment is required to set many input parameters, which can introduce subjectivity and variability in the estimation process. Consequently, there is a need to improve the current GSD models to mitigate reliance on historical data, subjectivity in expert judgment, inadequate consideration of GSD-based cost drivers and limited integration of modern technologies with cost overruns. This study introduces a novel hybrid model that synergizes the COCOMO II with Artificial Neural Networks (ANN) to address these challenges. The proposed hybrid model integrates additional GSD-based cost drivers identified through a systematic literature review and further vetted by industry experts. This article compares the effectiveness of the proposed model with state-of-the-art machine learning-based models for software cost estimation. Evaluating the NASA 93 dataset by adopting twenty-six GSD-based cost drivers reveals that our hybrid model achieves superior accuracy, outperforming existing state-of-the-art models. The findings indicate the potential of combining COCOMO II, ANN, and additional GSD-based cost drivers to transform cost estimation in GSD. metadata Ahmed, Mehmood and Ibrahim, Noraini B. and Nisar, Wasif and Ahmed, Adeel and Junaid, Muhammad and Soriano Flores, Emmanuel and Anand, Divya mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, emmanuel.soriano@uneatlantico.es, divya.anand@uneatlantico.es (2024) A Hybrid Model for Improving Software Cost Estimation in Global Software Development. Computers, Materials & Continua, 78 (1). pp. 1399-1422. ISSN 1546-2226

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production Abierto Inglés Broccoli has gained popularity as a highly consumed vegetable due to its nutritional and health properties. This study aimed to evaluate the composition profile and the antioxidant capacity of a hydrophilic extract derived from broccoli byproducts, as well as its influence on redox biology, Alzheimer’s disease markers, and aging in the Caenorhabditis elegans model. The presence of glucosinolate was observed and antioxidant capacity was demonstrated both in vitro and in vivo. The in vitro acetylcholinesterase inhibitory capacity was quantified, and the treatment ameliorated the amyloid-β- and tau-induced proteotoxicity in transgenic strains via SOD-3 and SKN-1, respectively, and HSP-16.2 for both parameters. Furthermore, a preliminary study on aging indicated that the extract effectively reduced reactive oxygen species levels in aged worms and extended their lifespan. Utilizing broccoli byproducts for nutraceutical or functional foods could manage vegetable processing waste, enhancing productivity and sustainability while providing significant health benefits. metadata Navarro-Hortal, María D. and Romero-Márquez, Jose M. and López-Bascón, M. Asunción and Sánchez-González, Cristina and Xiao, Jianbo and Sumalla Cano, Sandra and Battino, Maurizio and Forbes-Hernande, Tamara Y. and Quiles, José L. mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, sandra.sumalla@uneatlantico.es, maurizio.battino@uneatlantico.es, tamara.forbes@unini.edu.mx, jose.quiles@uneatlantico.es (2024) In Vitro and In Vivo Insights into a Broccoli Byproduct as a Healthy Ingredient for the Management of Alzheimer’s Disease and Aging through Redox Biology. Journal of Agricultural and Food Chemistry, 72 (10). pp. 5197-5211. ISSN 0021-8561

Article Subjects > Biomedicine Europe University of Atlantic > Research > Articles and books Abierto Inglés Amid growing concerns about antibiotic resistance, innovative strategies are imperative in addressing bacterial infections in aquaculture. Quorum quenching (QQ), the enzymatic inhibition of quorum sensing (QS), has emerged as a promising solution. This study delves into the QQ capabilities of the probiotic strain Bacillus velezensis D-18 and its products, particularly in Vibrio anguillarum 507 communication and biofilm formation. Chromobacterium violaceum MK was used as a biomarker in this study, and the results confirmed that B. velezensis D-18 effectively inhibits QS. Further exploration into the QQ mechanism revealed the presence of lactonase activity by B. velezensis D-18 that degraded both long- and short-chain acyl homoserine lactones (AHLs). PCR analysis demonstrated the presence of a homologous lactonase-producing gene, ytnP, in the genome of B. velezensis D-18. The study evaluated the impact of B. velezensis D-18 on V. anguillarum 507 growth and biofilm formation. The probiotic not only controls the biofilm formation of V. anguillarum but also significantly restrains pathogen growth. Therefore, B. velezensis D-18 demonstrates substantial potential for preventing V. anguillarum diseases in aquaculture through its QQ capacity. The ability to disrupt bacterial communication and control biofilm formation positions B. velezensis D-18 as a promising eco-friendly alternative to conventional antibiotics in managing bacterial diseases in aquaculture. metadata Monzón-Atienza, Luis and Bravo, Jimena and Torrecillas, Silvia and Gómez-Mercader, Antonio and Montero, Daniel and Ramos Vivas, Jose and Galindo-Villegas, Jorge and Acosta, Félix mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, jose.ramos@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2024) An In-Depth Study on the Inhibition of Quorum Sensing by Bacillus velezensis D-18: Its Significant Impact on Vibrio Biofilm Formation in Aquaculture. Microorganisms, 12 (5). p. 890. ISSN 2076-2607

Article Subjects > Teaching Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés The main aim of this study was to analyse the influence of e-learning training on the acquisition of competences in basketball coaches in Cantabria. The current landscape of basketball coach training shows an increasing demand for innovative training models and emerging pedagogies, including e-learning-based methodologies. The study sample consisted of fifty students from these courses, all above 16 years of age (36 males, 14 females). Among them, 16% resided outside the autonomous community of Cantabria, 10% resided more than 50 km from the city of Santander, 36% between 10 and 50 km, 14% less than 10 km, and 24% resided within Santander city. Data were collected through a Google Forms survey distributed by the Cantabrian Basketball Federation to training course students. Participation was voluntary and anonymous. The survey, consisting of 56 questions, was validated by two sports and health doctors and two senior basketball coaches. The collected data were processed and analysed using Microsoft® Excel version 16.74, and the results were expressed in percentages. The analysis revealed that 24.60% of the students trained through the e-learning methodology considered themselves fully qualified as basketball coaches, contrasting with 10.98% of those trained via traditional face-to-face methodology. The results of the study provide insights into important characteristics that can be adjusted and improved within the investigated educational process. Moreover, the study concludes that e-learning training effectively qualifies basketball coaches in Cantabria. metadata Alemany Iturriaga, Josep and Velarde-Sotres, Álvaro and Jorge, Javier and Giglio, Kamil mail josep.alemany@uneatlantico.es, alvaro.velarde@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2024) Influence of E-learning training on the acquisition of competences in basketball coaches in Cantabria. Cogent Education, 11 (1). ISSN 2331-186X

Article Subjects > Biomedicine Europe University of Atlantic > Research > Articles and books Abierto Inglés Plasma biomarkers for Alzheimer’s disease (AD) are a promising tool that may help in early diagnosis. However, their levels may be influenced by physiological parameters and comorbidities that should be considered before they can be used at the population level. For this purpose, we assessed the influences of different comorbidities on AD plasma markers in 208 cognitively unimpaired subjects. We analyzed both plasma and cerebrospinal fluid levels of Aβ40, Aβ42, and p-tau181 using the fully automated Lumipulse platform. The relationships between the different plasma markers and physiological variables were studied using linear regression models. The mean differences in plasma markers according to comorbidity groups were also studied. The glomerular filtration rate showed an influence on plasma Aβ40 and Aβ42 levels but not on the Aβ42/Aβ40 ratio. The amyloid ratio was significantly lower in diabetic and hypertensive subjects, and the mean p-tau181 levels were higher in hypertensive subjects. The glomerular filtration rate may have an inverse relationship on plasma Aβ40 and Aβ42 levels but not on the amyloid ratio, suggesting that the latter is a more stable marker to use in the general population. Cardiovascular risk factors might have a long-term effect on the amyloid ratio and plasma levels of p-tau181. metadata Martínez-Dubarbie, Francisco and Guerra-Ruiz, Armando and López-García, Sara and Irure-Ventura, Juan and Lage, Carmen and Fernández-Matarrubia, Marta and Pozueta-Cantudo, Ana and García-Martínez, María and Corrales Pardo, Andrea and Bravo, María and Martín-Arroyo, Juan and Infante, Jon and López-Hoyos, Marcos and García-Unzueta, María Teresa and Sánchez-Juan, Pascual and Rodríguez-Rodríguez, Eloy mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, andrea.corrales@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2024) Influence of Physiological Variables and Comorbidities on Plasma Aβ40, Aβ42, and p-tau181 Levels in Cognitively Unimpaired Individuals. International Journal of Molecular Sciences, 25 (3). p. 1481. ISSN 1422-0067

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Abierto Inglés The aim of this work is to develop different encapsulated propolis ingredients by spray-drying and to evaluate their bioaccessibility using simulated in vitro digestion. To achieve these goals, first, microparticles of a propolis extract with inulin as the coating polymer were prepared under the optimal conditions previously determined. Then, a fraction of inulin was replaced with other encapsulating agents, namely sodium alginate, pectin, and chitosan, to obtain different ingredients with controlled release properties in the gastrointestinal tract. The analysis of the phenolic profile in the propolis extract and microparticles showed 58 compounds tentatively identified, belonging mainly to phenolic acid derivatives and flavonoids. Then, the behavior of the free extract and the formulated microparticles under gastrointestinal conditions was studied through an in vitro gastrointestinal digestion process using the INFOGEST protocol. Digestion of the free extract resulted in the degradation of most compounds, which was minimized in the encapsulated formulations. Thus, all developed microparticles could be promising strategies for improving the stability of this bioactive extract under gastrointestinal conditions, thereby enhancing its beneficial effect. metadata Cea-Pavez, Inés and Manteca-Bautista, David and Morillo-Gomar, Alejandro and Quirantes-Piné, Rosa and Quiles, José L. mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, jose.quiles@uneatlantico.es (2024) Influence of the Encapsulating Agent on the Bioaccessibility of Phenolic Compounds from Microencapsulated Propolis Extract during "In Vitro" Gastrointestinal Digestion. Foods, 13 (3). p. 425. ISSN 2304-8158

Article Subjects > Psychology Europe University of Atlantic > Research > Articles and books Abierto Inglés, Español El estudio se enfoca en los problemas de conducta en niños de 8 a 11 años en San José, Costa Rica y su relación con el vínculo afectivo y las competencias parentales. Los problemas de conducta afectan la dinámica familiar, el rendimiento académico y social, son una de las principales problemáticas en la niñez. Se utilizó la escala E2P, para evaluar competencias parentales y la prueba ESPERI, para categorizar el comportamiento infantil. La muestra fue de 150 familias, con hijos que presentaban o no problemas de conducta. El análisis de las variables se realizó mediante un estudio categórico con el programa SPSS utilizando tablas cruzadas, chi cuadrado y coeficiente de contingencia. Los resultados muestran que las competencias parentales de alta frecuencia tienen un impacto en la reducción de comportamientos problemáticos, es decir entre más alta la competencia parental, menor es la manifestación de problemas de conducta. Aunque se esperaba una relación directa entre el vínculo afectivo (competencias vinculares) y los problemas de conducta, se encontró que las cuatro dimensiones de competencias parentales influyen reduciendo la reactividad conductual negativa. El análisis también incluyó pruebas estadísticas como el chi-cuadrado y el coeficiente de contingencia. A pesar de estos esfuerzos, se observaron correlaciones que no alcanzaron niveles significativos. Esto subraya la complejidad del fenómeno estudiado y destaca la importancia de futuras investigaciones para explorar más a fondo las relaciones entre estas variables. A pesar de esto, el análisis cualitativo proporciona información valiosa; sugiriendo la importancia de intervenciones para mejorar las competencias parentales. metadata Martín Ayala, Juan Luis and Durán Monge, Beatriz mail juan.martin@uneatlantico.es, UNSPECIFIED (2024) Influencia de las competencias parentales en la manifestación de problemas de conducta, en niños de 8 a 11 años, que residen en la provincia de San José, Costa Rica. MLS Psychology Research. ISSN 2605-5295

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books Abierto Inglés This paper highlights the fundamental role of integrating different geomatics and geophysical imaging technologies in understanding and preserving cultural heritage, with a focus on the Pavilion of Charles V in Seville (Spain). Using a terrestrial laser scanner, global navigation satellite system, and ground-penetrating radar, we constructed a building information modelling (BIM) system to derive comprehensive decision-making models to preserve this historical asset. These models enable the generation of virtual reconstructions, encompassing not only the building but also its subsurface, distributable as augmented reality or virtual reality online. By leveraging these technologies, the research investigates complex details of the pavilion, capturing its current structure and revealing insights into past soil compositions and potential subsurface structures. This detailed analysis empowers stakeholders to make informed decisions about conservation and management. Furthermore, transparent data sharing fosters collaboration, advancing collective understanding and practices in heritage preservation. metadata Zaragoza, María and Bayarri Cayón, Vicente and García, Francisco mail UNSPECIFIED, vicente.bayarri@uneatlantico.es, UNSPECIFIED (2024) Integrated Building Modelling Using Geomatics and GPR Techniques for Cultural Heritage Preservation: A Case Study of the Charles V Pavilion in Seville (Spain). Journal of Imaging, 10 (6). p. 128. ISSN 2313-433X

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Nanotechnology has opened new avenues for advanced research in various fields of soft materials. Materials scientists, chemists, physicists, and computational mathematicians have begun to take a keen interest in soft materials due to their potential applications in nanopatterning, membrane separation, drug delivery, nanolithography, advanced storage media, and nanorobotics. The unique properties of soft materials, particularly self-assembly, have made them useful in fields ranging from nanotechnology to biomedicine. The discovery of new morphologies in the diblock copolymer system in curved geometries is a challenging problem for mathematicians and theoretical scientists. Structural frustration under the effects of confinement in the system helps predict new structures. This mathematical study evaluates the effects of confinement and curvature on symmetric diblock copolymer melt using a cell dynamic simulation model. New patterns in lamella morphologies are predicted. The Laplacian involved in the cell dynamic simulation model is approximated by generating a 17-point stencil discretized to a polar grid by the finite difference method. Codes are programmed in FORTRAN to run the simulation, and IBM open DX is used to visualize the results. Comparison of computational results with existing studies validates this study and identifies defects and new patterns. metadata Iqbal, Muhammad Javed and Soomro, Inayatullah and Razzaq, Mirza Abdur and Omar-Martinez, Erislandy and Velázquez Martínez, Zaily Leticia and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, zaily.velazquez@unini.edu.mx, UNSPECIFIED (2024) Investigation of structural frustration in symmetric diblock copolymers confined in polar discs through cell dynamic simulation. Scientific Reports, 14 (1). ISSN 2045-2322

Article Subjects > Biomedicine
Subjects > Nutrition Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Isoflavones are a group of (poly)phenols, also defined as phytoestrogens, with chemical structures comparable with estrogen, that exert weak estrogenic effects. These phytochemical compounds have been targeted for their proven antioxidant and protective effects. Recognizing the increasing prevalence of cardiovascular diseases (CVD), there is a growing interest in understanding the potential cardiovascular benefits associated with these phytochemical compounds. Gut microbiota may play a key role in mediating the effects of isoflavones on vascular and endothelial functions, as it is directly implicated in isoflavones metabolism. The findings from randomized clinical trials indicate that isoflavone supplementation may exert putative effects on vascular biomarkers among healthy individuals, but not among patients affected by cardiometabolic disorders. These results might be explained by the enzymatic transformation to which isoflavones are subjected by the gut microbiota, suggesting that a diverse composition of the microbiota may determine the diverse bioavailability of these compounds. Specifically, the conversion of isoflavones in equol—a microbiota-derived metabolite—seems to differ between individuals. Further studies are needed to clarify the intricate molecular mechanisms behind these contrasting results. metadata Laudani, Samuele and Godos, Justyna and Romano, Giovanni Luca and Gozzo, Lucia and Di Domenico, Federica Martina and Dominguez Azpíroz, Irma and Martínez Díaz, Raquel and Giampieri, Francesca and Quiles, José L. and Battino, Maurizio and Drago, Filippo and Galvano, Fabio and Grosso, Giuseppe mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, irma.dominguez@unini.edu.mx, raquel.martinez@uneatlantico.es, francesca.giampieri@uneatlantico.es, jose.quiles@uneatlantico.es, maurizio.battino@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2024) Isoflavones Effects on Vascular and Endothelial Outcomes: How Is the Gut Microbiota Involved? Pharmaceuticals, 17 (2). p. 236. ISSN 1424-8247

Article Subjects > Biomedicine
Subjects > Psychology Europe University of Atlantic > Research > Articles and books Cerrado Inglés Background:With the arrival of disease-modifying treatments, it is mandatory to find new cognitive markers that are sensitive to Alzheimer’s disease (AD) pathology in preclinical stages. Objective:To determine the utility of a newly developed Learning and Associative Memory face test: LAM test. This study examined the relationship between AD cerebrospinal fluid (CSF) biomarkers and performance on LAM test, and assessed its potential clinical applicability to detect subtle changes in cognitively healthy subjects at risk for AD. Methods:We studied eighty cognitively healthy volunteers from the Valdecilla cohort. 61% were women and the mean age was 67.34 years (±6.416). All participants underwent a lumbar puncture for determination of CSF biomarkers and an extensive neuropsychological assessment, including performance on learning and associative memory indices of the LAM-test after 30 min and after 1 week, and two classic word lists to assess verbal episodic memory: the Rey Auditory Verbal Learning Test (RAVLT) and the Free and Cued Selective Reminding Test (FCSRT). We analyzed cognitive performance according to amyloid status (A+ versus A–) and to ATN model (A–T–N–; A+T–N–; A+T+N–/A+T+N+). Results:Performance on the LAM-test was significantly correlated with CSF Aβ ratio. A+ participants performed worse on both learning (mean difference = 2.19, p = 0.002) and memory LAM measures than A– (mean difference = 2.19, p = 0.004). A decline in performance was observed along the Alzheimer’s continuum, with significant differences between ATN groups. Conclusions:Our findings suggest that LAM test could be a useful tool for the early detection of subjects within the AD continuum, outperforming classical memory tests. metadata García-Martínez, María and Pozueta-Cantudo, Ana and Lage, Carmen and Martínez-Dubarbie, Francisco and López-García, Sara and Fernández-Matarrubia, Marta and Corrales Pardo, Andrea and Bravo, María and Cavada, Nadia C. and Anuarbe, Pedro and Infante, Jon and López-Higuera, José Miguel and Rodríguez-Cobo, Luis and Rodríguez-Rodríguez, Eloy and Butler, Christopher R. and Sánchez-Juan, Pascual mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, andrea.corrales@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2024) LAM Test: A New Cognitive Marker for Early Detection in Preclinical Alzheimer’s Disease. Journal of Alzheimer's Disease. pp. 1-15. ISSN 13872877

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books Abierto Inglés The Internet of Things (IoT) is a sophisticated network of objects embedded with electronic systems that enable devices to collect and exchange data. IoT is a recent trending leading technology and changing the way we live. However, it has several challenges especially efficiency, architecture, complexity, and network topology. The traditional technologies are not enough to provide support. It is evident from the literature that complex networks are used to study the topology and the structure of a network and are applied to modern technologies. Thus, the capability of powerful computational tools and the existence of theoretical frameworks enable complex networks to derive new approaches in analyzing IoT-based technologies in terms of improving efficiency, architecture, complexity, and topology. In this direction, limited research has been carried out. The integration aspect remains a key challenge. Therefore, in order to fill this gap. Herein, we design a comprehensive literature review. In this research effort, we explore a newly leading emerging technology named the Social Internet of Things (SIoT). It is developed to overcome the challenges in IoT. We discuss the importance and the key applications of SIoT. We first presented a conceptual view along with a recent technological roadmap. The big data play an important role in the modern world. We discuss big data and the 5 Vs along with suitable applications and examples. Then, we highlighted the key concepts in complex networks, scale-free, random networks, and small-world networks. We explored and presented various graph models and metrics aligned with social networks and the most recent trends. The novelty of this research is to propose a synergy of complex networks to the IoT, SIoT, and big data together. We discuss the advantages of integration in detail. We present a detailed discussion on complex networks emerging technologies and cyber-physical systems (CPS). Briefly, our literature review covers the most recent advancements and developments in 10 years. In addition, our critical analysis is based on up-to-date surveys and case studies. Finally, we outline the impact of recent emerging technologies on challenges applications, and solutions for the future. This paper provides a good reference for researchers and readers in the IoT domain. metadata Amin, Farhan and Abbasi, Rashid and Khan, Salabat and Abid, Muhammad Ali and Mateen, Abdul and de la Torre, Isabel and Kuc Castilla, Ángel Gabriel and García Villena, Eduardo mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, angel.kuc@uneatlantico.es, eduardo.garcia@uneatlantico.es (2024) Latest advancements and prospects in the next-generation of Internet of Things technologies. PeerJ Computer Science, 10. e2434. ISSN 2376-5992

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Background/Objectives. Traditional dietary patterns are being abandoned in Mediterranean countries, especially among younger generations. This study aimed to investigate the potential lifestyle determinants that can increase adherence to the Mediterranean diet in children and adolescents. Methods. This study is a cross-sectional analysis of data from five Mediterranean countries (Italy, Spain, Portugal, Egypt, and Lebanon) within the context of the EU-funded project DELICIOUS (UnDErstanding consumer food choices & promotion of healthy and sustainable Mediterranean Diet and LIfestyle in Children and adolescents through behavIOUral change actionS). This study comprised information on 2011 children and adolescents aged 6–17 years old collected during 2023. The main background characteristics of both children and parents, including age, sex, education, and family situation, were collected. Children’s eating (i.e., breakfast, place of eating, etc.) and lifestyle habits (i.e., physical activity level, sleep, and screen time) were also investigated. The level of adherence to the Mediterranean diet was assessed using the KIDMED index. Logistic regression analyses were performed to test for likelihood of higher adherence to the Mediterranean diet. Results. Major determinants of higher adherence to the Mediterranean diet were younger age, higher physical activity level, adequate sleep duration, and, among dietary habits, having breakfast and eating with family members and at school. Parents’ younger age and higher education were also determinants of higher adherence. Multivariate adjusted analyses showed that an overall healthier lifestyle and parents’ education were the factors independently associated with higher adherence to the Mediterranean diet. Conclusions. Higher adherence to the Mediterranean diet in children and adolescents living in the Mediterranean area is part of an overall healthy lifestyle possibly depending on parents’ cultural background. metadata Rosi, Alice and Scazzina, Francesca and Giampieri, Francesca and Álvarez-Córdova, Ludwig and Abdelkarim, Osama and Ammar, Achraf and Aly, Mohamed and Frias-Toral, Evelyn and Pons, Juancho and Vázquez-Araújo, Laura and Rodríguez Velasco, Carmen Lilí and Brito Ballester, Julién and Monasta, Lorenzo and Mata, Ana and Chacón, Adrián and Busó, Pablo and Grosso, Giuseppe mail UNSPECIFIED, UNSPECIFIED, francesca.giampieri@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, carmen.rodriguez@uneatlantico.es, julien.brito@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2024) Lifestyle Factors Associated with Children’s and Adolescents’ Adherence to the Mediterranean Diet Living in Mediterranean Countries: The DELICIOUS Project. Nutrients, 17 (1). p. 26. ISSN 2072-6643

Article Subjects > Social Sciences
Subjects > Psychology Europe University of Atlantic > Research > Articles and books Abierto Inglés Background: The COVID-19 pandemic introduced unprecedented challenges to medical education systems and medical students worldwide, making it necessary to adapt teaching to a remote methodology during the academic year 2020–2021. The aim of this study was to characterize the association between medical professionalism and dropout intention during the pandemic in Peruvian medical schools. Methods: A cross-sectional online-survey-based study was performed in four Peruvian medical schools (two public) during the academic year 2020–2021. Medical students, attending classes from home, answered three scales measuring clinical empathy, teamwork, and lifelong learning abilities (three elements of medical professionalism) and four scales measuring loneliness, anxiety, depression, and subjective wellbeing. In addition, 15 demographic, epidemiological, and academic variables (including dropout intention) were collected. Variables were assessed using multiple logistic regression analysis. Results: The study sample was composed of 1107 students (390 male). Eight variables were included in an explanatory model (Nagelkerke-R2 = 0.35). Anxiety, depression, intention to work in the private sector, and teamwork abilities showed positive associations with dropout intention while learning abilities, subjective wellbeing, studying in a public medical school, and acquiring a better perception of medicine during the pandemic showed a negative association with dropout intention. No association was observed for empathy. Conclusions: Each element measured showed a different role, providing new clues on the influence that medical professionalism had on dropout intention during the pandemic. This information can be useful for medical educators to have a better understanding of the influence that professionalism plays in dropout intention. metadata Hancco-Monrroy, Dante E. and Caballero-Apaza, Luz M. and Abarca-Fernández, Denices and Castagnetto, Jesus M. and Condori-Cardoza, Fany A. and De-Lama Moran, Raul and Carhuancho-Aguilar, Jose R. and Gutierrez, Sandra and Gonzales, Martha and Berduzco, Nancy and Delgado Bolton, Roberto C. and San-Martín, Montserrat and Vivanco, Luis mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, luis.vivanco@uneatlantico.es (2024) Medical Professionalism and Its Association with Dropout Intention in Peruvian Medical Students during the COVID-19 Pandemic. Behavioral Sciences, 14 (8). p. 641. ISSN 2076-328X

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés The prevalence of sleep disorders, characterized by issues with quality, timing, and sleep duration is increasing globally. Among modifiable risk factors, diet quality has been suggested to influence sleep features. The Mediterranean diet is considered a landmark dietary pattern in terms of quality and effects on human health. However, dietary habits characterized by this cultural heritage should also be considered in the context of overall lifestyle behaviors, including sleep habits. This study aimed to systematically revise the literature relating to adherence to the Mediterranean diet and sleep features in observational studies. The systematic review comprised 23 reports describing the relation between adherence to the Mediterranean diet and different sleep features, including sleep quality, sleep duration, daytime sleepiness, and insomnia symptoms. The majority of the included studies were conducted in the Mediterranean basin and reported a significant association between a higher adherence to the Mediterranean diet and a lower likelihood of having poor sleep quality, inadequate sleep duration, excessive daytime sleepiness or symptoms of insomnia. Interestingly, additional studies conducted outside the Mediterranean basin showed a relationship between the adoption of a Mediterranean-type diet and sleep quality, suggesting that biological mechanisms sustaining such an association may exist. In conclusion, current evidence suggests a relationship between adhering to the Mediterranean diet and overall sleep quality and different sleep parameters. The plausible bidirectional association should be further investigated to understand whether the promotion of a healthy diet could be used as a tool to improve sleep quality. metadata Godos, Justyna and Ferri, Raffaele and Lanza, Giuseppe and Caraci, Filippo and Rojas Vistorte, Angel Olider and Yélamos Torres, Vanessa and Grosso, Giuseppe and Castellano, Sabrina mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, angel.rojas@uneatlantico.es, vanessa.yelamos@funiber.org, UNSPECIFIED, UNSPECIFIED (2024) Mediterranean Diet and Sleep Features: A Systematic Review of Current Evidence. Nutrients, 16 (2). p. 282. ISSN 2072-6643

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books Abierto Inglés On the surface of the Cave of Altamira’s prehistoric paintings, a series of active deterioration processes are evident, leading to significant alterations of this invaluable heritage. This study proposes a comprehensive methodology for the systematic recording and management of these alterations. To achieve this, advanced microphotogrammetric monitoring techniques are employed, allowing for the acquisition of very high-resolution images that provide objective and quantifiable data that let us determine the evolution of the alterations. By comparing these images with those from earlier campaigns, the study tracks changes. The data collected through this protocol has helped with the development of new research avenues to understand, among the many alteration processes that impact paintings, the dynamics of water and fluid mechanics affecting the conservation of Cave of Altamira. These investigations help clarify how, why, and at what rate degradation processes such as pigment migration, washing, and bacterial colonization occur. The insights gained from these techniques inform indirect conservation measures aimed at reducing the deterioration of the cave art, located both on the Polychrome ceiling and throughout the rest of the Cave of Altamira. The results underline the importance of regular monitoring and the application of precise, non-invasive techniques to protect rock art from continued degradation. This research provides a model for similar conservation initiatives at other vulnerable heritage sites. metadata Prada, Alfredo and Bayarri Cayón, Vicente mail UNSPECIFIED, vicente.bayarri@uneatlantico.es (2024) Methodology for the Monitoring and Control of the Alterations Related to Biodeterioration and Physical-Chemical Processes Produced on the Paintings on the Ceiling of the Polychrome Hall at Altamira. Conservation, 4 (4). pp. 703-730. ISSN 2673-7159

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books Abierto Inglés This paper addresses the conservation problems of the cave of Altamira, a UNESCO World Heritage Site in Santillana del Mar, Cantabria, Spain, due to the effects of moisture and water inside the cave. The study focuses on the description of methods for estimating the trajectory and zones of humidity from the external environment to its eventual dripping on valuable cave paintings. To achieve this objective, several multisensor remote sensing techniques, both aerial and terrestrial, such as 3D laser scanning, a 2D ground penetrating radar, photogrammetry with unmanned aerial vehicles, and high-resolution terrestrial techniques are employed. These tools allow a detailed spatial analysis of the moisture and water in the cave. The paper highlights the importance of the dolomitic layer in the cave and how it influences the preservation of the ceiling, which varies according to its position, whether it is sealed with calcium carbonate, actively dripping, or not dripping. In addition, the crucial role of the central fracture and the areas of direct water infiltration in this process is examined. This research aids in understanding and conserving the site. It offers a novel approach to water-induced deterioration in rock art for professionals and researchers. metadata Bayarri Cayón, Vicente and Prada, Alfredo and García, Francisco and De Las Heras, Carmen and Fatás, Pilar mail vicente.bayarri@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2024) A Multisensory Analysis of the Moisture Course of the Cave of Altamira (Spain): Implications for Its Conservation. Remote Sensing, 16 (1). p. 197. ISSN 2072-4292

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés New approaches to software testing are required due to the rising complexity of today’s software applications and the rapid growth of software engineering practices. Among these methods, one that has shown promise is the introduction of Natural Language Processing (NLP) tools to software testing practices. NLP has witnessed a rise in popularity within all IT fields, especially in software engineering, where its use has improved the way we extract information from textual data. The goal of this systematic literature review (SLR) is to provide an in-depth analysis of the present body of the literature on the expanding subject of NLP-based software testing. Through a repeatable process, that takes into account the quality of the research, we examined 24 papers extracted from Web of Science and Scopus databases to extract insights about the usage of NLP techniques in the field of software testing. Requirements analysis and test case generation popped up as the most hot topics in the field. We also explored NLP techniques, software testing types, machine/deep learning algorithms, and NLP tools and frameworks used in the studied body of literature. This study also stressed some recurrent open challenges that need further work in future research such as the generalization of the NLP algorithm across domains and languages and the ambiguity in the natural language requirements. Software testing professionals and researchers can get important insights from the findings of this SLR, which will help them comprehend the advantages and challenges of using NLP in software testing. metadata Boukhlif, Mohamed and Hanine, Mohamed and Kharmoum, Nassim and Ruigómez Noriega, Atenea and García Obeso, David and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, atenea.ruigomez@uneatlantico.es, david.garcia@uneatlantico.es, UNSPECIFIED (2024) Natural Language Processing-Based Software Testing: A Systematic Literature Review. IEEE Access, 12. pp. 79383-79400. ISSN 2169-3536

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés The IoT (Internet of Things) has played a promising role in e-healthcare applications during the last decade. Medical sensors record a variety of data and transmit them over the IoT network to facilitate remote patient monitoring. When a patient visits a hospital he may need to connect or disconnect medical devices from the medical healthcare system frequently. Also, multiple entities (e.g., doctors, medical staff, etc.) need access to patient data and require distinct sets of patient data. As a result of the dynamic nature of medical devices, medical users require frequent access to data, which raises complex security concerns. Granting access to a whole set of data creates privacy issues. Also, each of these medical user need to grant access rights to a specific set of medical data, which is quite a tedious task. In order to provide role-based access to medical users, this study proposes a blockchain-based framework for authenticating multiple entities based on the trust domain to reduce the administrative burden. This study is further validated by simulation on the infura blockchain using solidity and Python. The results demonstrate that role-based authorization and multi-entities authentication have been implemented and the owner of medical data can control access rights at any time and grant medical users easy access to a set of data in a healthcare system. The system has minimal latency compared to existing blockchain systems that lack multi-entity authentication and role-based authorization. metadata Alam, Shadab and Aslam, Muhammad Shehzad and Altaf, Ayesha and Iqbal, Faiza and Nigar, Natasha and Castanedo Galán, Juan and Gavilanes Aray, Daniel and Díez, Isabel de la Torre and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, juan.castanedo@uneatlantico.es, daniel.gavilanes@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2024) Novel model to authenticate role-based medical users for blockchain-based IoMT devices. PLOS ONE, 19 (7). e0304774. ISSN 1932-6203

Article Subjects > Biomedicine Europe University of Atlantic > Research > Articles and books Abierto Inglés Objectives: Point-of-care testing available in prehospital settings requires the establishment of new medical decision points. The aim of the present work was to determine the cut-off of the lactate threshold that activates alert triggers for all-cause 2-day mortality. Design: Multicentre, prospective, ambulance-based, observational study. Setting: Patients treated via emergency medical services (EMSs) and delivered to the emergency department between 2019 and 2023 were selected in Spain. Participants: Adults with any acute disease. Primary and secondary outcome measures: Epidemiological data, vital signs and prehospital point-of-care glucose and lactate levels were obtained. The outcome was all-cause 2-day in-hospital mortality. The cut-offs were obtained via three different methods: (i) indirect (which considers survivors and non-survivors), direct (which considers only survivors) assessment and lactate quartile. Additionally, the quartile approach was used to determine the differences in lactate distribution between survivors and non-survivors. Three different back-to-back studies with the same methodology were used. Results: A total of 11 713 patients fulfilled the inclusion criteria. The mortality rate was 4.6% (542 patients). The difference in the median prehospital lactate concentration (mmol/L) between survivors and non-survivors was statistically significant (p<0.001): 2.29 (95% CI 1.43 to 3.38) and 7.14 (95% CI 5.11 to 9.71), respectively. Globally, the cut-off for all the studies combined was estimated by the direct method to be 3.71 mmol/L (95% CI 2.92 to 3.91), which was similar to the indirect value of 3.07 (95% CI 2.95 to 5.49) and the third quartile of 4.00. The mortality rate in patients who were less than 3.71 mmol/L was 0.004%, and that above that cut-off was 18%. Conclusions: This study established a real-world lactate cut-off for 2-day in-hospital mortality of 3.71 mmol/L (95% CI 2.92 to 3.91) on the basis of data from the EMS. Considering this cut-off point could improve patient management via EMS services, allowing quick identification of patients at high risk of clinical worsening. metadata Martín-Rodríguez, Francisco and Sanz-Garcia, Ancor and Zalama-Sánchez, Daniel and de Santos Castro, Pedro Ángel and Silva Alvarado, Eduardo René and Gracia Villar, Santos and Dzul López, Luis Alonso and Aparicio Obregón, Silvia and Calderón Iglesias, Rubén and del Pozo Vegas, Carlos and López-Izquierdo, Raúl mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, eduardo.silva@funiber.org, santos.gracia@uneatlantico.es, luis.dzul@uneatlantico.es, silvia.aparicio@uneatlantico.es, ruben.calderon@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2024) Novel prehospital lactate cut-off estimation for mortality: a multicentre observational study. BMJ Open, 14 (12). e091789. ISSN 2044-6055

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Cerrado Inglés Edible insects represent a viable option to address the current need for nutritious, safe, and eco-friendly foods. People native to the Amazon region have a long-standing tradition of consuming edible insects that are relatively unknown elsewhere. This research aimed to characterize the chemical, nutritional, and microbiological composition of the edible larva of the palm weevil Rhynchophorus palmarum L. (chontacuro) from the Amazonian lowlands of Ecuador. The larvae proved to be rich in lipids (∼50 %), proteins (∼20 %), fiber (∼6 %), and oleic acid, one of their predominant fatty acids along with palmitic acid. The larvae are also rich in vitamins (B6, B9, A, and E) and are a source of β-carotene, calcium, potassium, magnesium, and phosphorus. No evidence of toxic elements (metals) or pathogenic microorganisms was observed. In general, chontacuro larvae proved to be a safe and nutritious food, managing to fully or partially cover several of the Dietary Reference Intakes for several nutrients. metadata Chimbo-Gándara, Luis F. and Granda-Albuja, Genoveva and Mora, José R. and Llumiquinga, Erika and Ruiz-Uriguen, Melany and Machado, António and Cisneros-Heredia, Diego F. and Abreu-Naranjo, Reinier and Giampieri, Francesca and Tejera, Eduardo and Álvarez-Suárez, José M. mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, francesca.giampieri@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2024) Nutritional, functional, and safety characterization of the edible larva of the South American palm weevil (chontacuro) Rhynchophorus palmarum L. from Amazonian Ecuador. Journal of Food Composition and Analysis, 134. p. 106507. ISSN 08891575

Article Subjects > Social Sciences Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés To improve organisational performance, it is crucial to cultivate an environment and culture that, through shared values, attitudes, behaviours, and sentiments, enables all employees to feel comfortable in performing their work. This represents a recognised gap within the current Cuban business context. Drawing from identified challenges and the introduction of a values-based coaching programme at the state-owned company GEDEME to address this gap, the aim of this study is to evaluate the impact of the values-based coaching programme (CpV) on organisational culture among both tactical and strategic employees within GEDEME. The research adopts a mixed-methods design. On one hand, the non-parametric McNemar test was utilised to assess before-and-after differences, while a case-study approach facilitated the exploration of specific questions, such as identifying the values actually practised beyond those outlined in the formal business plan and understanding the extent and nature of value shifts following the implementation of the coaching programme. The results confirmed the primary hypothesis: the values-based coaching programme at GEDEME had a positive effect on employees' perceptions of organisational culture, resulting in a substantial increase in the number of values both practised and perceived by its members. metadata Caro Montero, Elizabeth and Soriano Flores, Emmanuel and Silva Alvarado, Eduardo René and Garat de Marin, Mirtha Silvana mail elizabeth.caro@uneatlantico.es, emmanuel.soriano@uneatlantico.es, eduardo.silva@funiber.org, silvana.marin@uneatlantico.es (2024) Organizational Culture Assessment Based on a Values-Based Coaching Program for Strategic Level Employees: The Case of GEDEME, Cuba. International Journal of Instructional Cases, 8 (2). pp. 139-163. ISSN 2399-830x

Article Subjects > Psychology Europe University of Atlantic > Research > Articles and books Abierto Inglés Introduction The aim of this study was to use cluster analysis based on the trajectory of five cognitive-emotional processes (worry, rumination, metacognition, cognitive reappraisal and expressive suppression) over time to explore differences in clinical and performance variables in primary care patients with emotional symptoms. Methods We compared the effect of adding transdiagnostic cognitive-behavioural therapy (TD-CBT) to treatment as usual (TAU) according to cluster membership and sought to determine the variables that predicted cluster membership. 732 participants completed scales about cognitive-emotional processes, anxiety and depressive symptoms, functioning, and quality of life (QoL) at baseline, posttreatment, and at 12 months. Longitudinal cluster analysis and logistic regression analyses were carried out. Results A two-cluster solution was chosen as the best fit, named as “less” or “more” improvement in cognitive-emotional processes. Individuals who achieved more improvement in cognitive-emotional processes showed lower emotional symptoms and better QoL and functioning at all three time points. TAU+TD-CBT, income level, QoL and anxiety symptoms were significant predictors of cluster membership. Conclusions These results underscore the value of adding TD-CBT to reduce maladaptive cognitive-emotional regulation strategies. These findings highlight the importance of the processes of change in therapy and demonstrate the relevance of the patient’s cognitive-emotional profile in improving treatment outcomes. metadata Chen, Mu-Hong and Barrio-Martínez, Sara and Rodriguez-Perez, Noelia and Priede, Amador and Medrano, Leonardo Adrián and Muñoz-Navarro, Roger and Moriana, Juan Antonio and Carpallo-González, María and Prieto-Vila, Maider and Ruiz-Rodríguez, Paloma and Cano-Vindel, Antonio and González-Blanch, César mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, cesar.gonzalezblanch@uneatlantico.es (2024) Patterns of cognitive-emotional change after cognitive-behavioural treatment in emotional disorders: A 12-month longitudinal cluster analysis. PLOS ONE, 19 (5). e0301746. ISSN 1932-6203

Article Subjects > Biomedicine Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés The evolution of the COVID-19 pandemic has been associated with variations in clinical presentation and severity. Similarly, prediction scores may suffer changes in their diagnostic accuracy. The aim of this study was to test the 30-day mortality predictive validity of the 4C and SEIMC scores during the sixth wave of the pandemic and to compare them with those of validation studies. This was a longitudinal retrospective observational study. COVID-19 patients who were admitted to the Emergency Department of a Spanish hospital from December 15, 2021, to January 31, 2022, were selected. A side-by-side comparison with the pivotal validation studies was subsequently performed. The main measures were 30-day mortality and the 4C and SEIMC scores. A total of 27,614 patients were considered in the study, including 22,361 from the 4C, 4,627 from the SEIMC and 626 from our hospital. The 30-day mortality rate was significantly lower than that reported in the validation studies. The AUCs were 0.931 (95% CI: 0.90–0.95) for 4C and 0.903 (95% CI: 086–0.93) for SEIMC, which were significantly greater than those obtained in the first wave. Despite the changes that have occurred during the coronavirus disease 2019 (COVID-19) pandemic, with a reduction in lethality, scorecard systems are currently still useful tools for detecting patients with poor disease risk, with better prognostic capacity. metadata de Santos Castro, Pedro Ángel and del Pozo Vegas, Carlos and Pinilla Arribas, Leyre Teresa and Zalama Sánchez, Daniel and Sanz-García, Ancor and Vásquez del Águila, Tony Giancarlo and González Izquierdo, Pablo and de Santos Sánchez, Sara and Mazas Pérez-Oleaga, Cristina and Dominguez Azpíroz, Irma and Elío Pascual, Iñaki and Martín-Rodríguez, Francisco mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, cristina.mazas@uneatlantico.es, irma.dominguez@unini.edu.mx, inaki.elio@uneatlantico.es, UNSPECIFIED (2024) Performance of the 4C and SEIMC scoring systems in predicting mortality from onset to current COVID-19 pandemic in emergency departments. Scientific Reports, 14 (1). ISSN 2045-2322

Article Subjects > Biomedicine Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés The evolution of the COVID-19 pandemic has been associated with variations in clinical presentation and severity. Similarly, prediction scores may suffer changes in their diagnostic accuracy. The aim of this study was to test the 30-day mortality predictive validity of the 4C and SEIMC scores during the sixth wave of the pandemic and to compare them with those of validation studies. This was a longitudinal retrospective observational study. COVID-19 patients who were admitted to the Emergency Department of a Spanish hospital from December 15, 2021, to January 31, 2022, were selected. A side-by-side comparison with the pivotal validation studies was subsequently performed. The main measures were 30-day mortality and the 4C and SEIMC scores. A total of 27,614 patients were considered in the study, including 22,361 from the 4C, 4,627 from the SEIMC and 626 from our hospital. The 30-day mortality rate was significantly lower than that reported in the validation studies. The AUCs were 0.931 (95% CI: 0.90–0.95) for 4C and 0.903 (95% CI: 086–0.93) for SEIMC, which were significantly greater than those obtained in the first wave. Despite the changes that have occurred during the coronavirus disease 2019 (COVID-19) pandemic, with a reduction in lethality, scorecard systems are currently still useful tools for detecting patients with poor disease risk, with better prognostic capacity. metadata de Santos Castro, Pedro Ángel and del Pozo Vegas, Carlos and Pinilla Arribas, Leyre Teresa and Zalama Sánchez, Daniel and Sanz-García, Ancor and Vásquez del Águila, Tony Giancarlo and González Izquierdo, Pablo and de Santos Sánchez, Sara and Mazas Pérez-Oleaga, Cristina and Dominguez Azpíroz, Irma and Elío Pascual, Iñaki and Martín-Rodríguez, Francisco mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, cristina.mazas@uneatlantico.es, irma.dominguez@unini.edu.mx, inaki.elio@uneatlantico.es, UNSPECIFIED (2024) Performance of the 4C and SEIMC scoring systems in predicting mortality from onset to current COVID-19 pandemic in emergency departments. Scientific Reports, 14 (1). ISSN 2045-2322

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Abierto Inglés Strong evidence supports the paramount importance of the composition of the diet for health. Not only diet should provide nutritional adequacy, but some foods and dietary components can also support the management of common chronic diseases, with mechanisms independent of nutritional adequacy. Among the various intervention diets, low-fat vegan diets have been shown to be effective for cardiometabolic health, mainly influencing insulin resistance, adiposity, and blood lipids. This type of diet relies on reducing or eliminating all added fats and choosing low-fat foods, mainly unprocessed whole-plant foods. We hereby propose a tool for planning low-fat vegan diets, the VegPlate Low-Fat (VP_LF), which has been obtained from a specific adaptation of the VegPlate method, which was already presented in previous publications for adults and some life stages and situations. The reduction in fats in the diet, which ranges between 10% and 15% of total energy, and the varied inclusion of foods from plant groups make it easier to provide adequate amounts of all nutrients with a normal- or lower-calorie intake, in comparison with diets that do not limit fat intakes. We expect that this new proposal will help nutrition professionals embrace low-fat diets as a first-line intervention for individuals affected by different health conditions who can benefit from these diets. metadata Baroni, Luciana and Rizzo, Gianluca and Zavoli, Martina and Battino, Maurizio mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, maurizio.battino@uneatlantico.es (2024) A Plant-Based Food Guide Adapted for Low-Fat Diets: The VegPlate Low-Fat (VP_LF). Foods, 13 (24). p. 4050. ISSN 2304-8158

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Pneumonia is a potentially life-threatening infectious disease that is typically diagnosed through physical examinations and diagnostic imaging techniques such as chest X-rays, ultrasounds or lung biopsies. Accurate diagnosis is crucial as wrong diagnosis, inadequate treatment or lack of treatment can cause serious consequences for patients and may become fatal. The advancements in deep learning have significantly contributed to aiding medical experts in diagnosing pneumonia by assisting in their decision-making process. By leveraging deep learning models, healthcare professionals can enhance diagnostic accuracy and make informed treatment decisions for patients suspected of having pneumonia. In this study, six deep learning models including CNN, InceptionResNetV2, Xception, VGG16, ResNet50 and EfficientNetV2L are implemented and evaluated. The study also incorporates the Adam optimizer, which effectively adjusts the epoch for all the models. The models are trained on a dataset of 5856 chest X-ray images and show 87.78%, 88.94%, 90.7%, 91.66%, 87.98% and 94.02% accuracy for CNN, InceptionResNetV2, Xception, VGG16, ResNet50 and EfficientNetV2L, respectively. Notably, EfficientNetV2L demonstrates the highest accuracy and proves its robustness for pneumonia detection. These findings highlight the potential of deep learning models in accurately detecting and predicting pneumonia based on chest X-ray images, providing valuable support in clinical decision-making and improving patient treatment. metadata Ali, Mudasir and Shahroz, Mobeen and Akram, Urooj and Mushtaq, Muhammad Faheem and Carvajal-Altamiranda, Stefanía and Aparicio Obregón, Silvia and Díez, Isabel De La Torre and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, stefania.carvajal@uneatlantico.es, silvia.aparicio@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2024) Pneumonia Detection Using Chest Radiographs With Novel EfficientNetV2L Model. IEEE Access, 12. pp. 34691-34707. ISSN 2169-3536

Article Subjects > Psychology Europe University of Atlantic > Research > Articles and books Abierto Español The post-pandemic stage covid-19 has revealed overloads, ambiguities, and conflicts of teachers in the performance of new roles in hybrid classrooms that demanded an urgent adaptation, this highlighted the need for priority attention to the mental health of teachers, however, there are still insufficient studies that transcend the diagnosis and are committed to establish proposals for improvement. OBJECTIVE: This study aims to establish a proposal for the promotion of positive mental health (PMH). METHODS: The study was deployed from a qualitative approach; using an ethnomethodological design that allowed studying how teachers create meanings and sense in their work context, an appreciative interview was conducted with an affirmative theme that allowed teachers to expose their experiences that were systematized and processed with ATLAS. ti software. The application of the interview was conducted online through a Google form, during the months of February and March 2023. Three hundred university professors who experienced the pandemic in universities in Brazil, Chile, Colombia, Ecuador, Mexico, and Peru participated, based on a convenience sampling. RESULTS: The results of the deductive phase confirmed Lluch's PMH theoretical framework; however, new nuances or variations have been identified, which must be considered in the complex and dynamic nature of each PMH factor. From there, the results of the inductive phase allowed revealing emerging concepts, that is, new categories that would have the function of improving the PMH factors, which is why they have been denominated: dynamizing nuclei. PMH dynamizing nuclei are adjustment to work environment, soft skills, work-family balance, self-motivation, self-efficacy, subjective well-being, proactive strategies, engagement, resilience. CONCLUSIONS: Finally, with the results of both phases, the creation of an integrated model was generated, which was evaluated by six experts in a round of feedback, who highlighted the relevance of the findings and offered recommendations that were considered in the study. The new integrated model has revealed an interesting association, since it not only legitimizes the PMH's dynamizing cores, but also informs on which specific factor of the PMH these cores have the greatest impact, which has a high guiding value for intervention and improvement based on focused strategies. metadata Deroncele-Acosta, Angel and Rojas Vistorte, Angel Olider and Sartor-Harada, Andresa and Ulloa-Guerra, Oscar and López-Mustelier, Rosendo and Cruzata-Martínez, Alejandro mail UNSPECIFIED, angel.rojas@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2024) Positive mental health of Latin American university professors: A scientific framework for intervention and improvement. Heliyon, 10 (2). e24813. ISSN 24058440

Article Subjects > Psychology Europe University of Atlantic > Research > Articles and books Cerrado Inglés The literature indicates that patients with schizophrenia spectrum disorders often show deficits in premorbid adjustment. Additionally, these impairments have been correlated with critical disease parameters, evident in both early and advanced stages. The principal objective of this study was to investigate the association between premorbid adjustment and functional outcomes a decade following the initial episode of psychosis. A cluster analysis was performed to group patients according to their premorbid adjustment scores as assessed with the Premorbid Adjustment Scale (PAS). The measurements of The Disability Assessment Scale (DAS), The Global Assessment of Function (GAF) scale, ​​and The Quality of Life Scale (QLS) were used to compare the functionality of the groups at a 10-year follow-up. A total of 231 patients were classified into three groups based on their premorbid adjustment: “good PAS”, “deteriorating PAS”, and “chronically poor PAS”. The three groups differed significantly in their sociodemographic and cognitive baseline characteristics. At the 10-year follow-up, “good PAS” group had better scores than the other groups in the variables of functionality and quality of life. The relationship found between premorbid adjustment and long-term functional results in patients with psychosis can help us predict the evolution of patients and act accordingly. metadata Setién-Suero, Esther and Ayesa-Arriola, Rosa and Peña, Javier and Ojeda, Natalia and Crespo-Facorro, Benedicto mail esther.setien@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2024) Premorbid adjustment as predictor of long-term functionality: Findings from a 10-year follow-up study in the PAFIP-cohort. Psychiatry Research, 331. p. 115674. ISSN 01651781 (In Press)

Article Subjects > Physical Education and Sport Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production Abierto Inglés (1) Background: The increasing life expectancy brings an increase in geriatric syndromes, specifically frailty. The literature shows that exercise is a key to preventing, or even reversing, frailty in community-dwelling populations. The main objective is to demonstrate how an intervention based on multicomponent exercise produces an improvement in frailty and pre-frailty in a community-dwelling population. (2) Methods: a prospective observational study of a multicomponent exercise program for geriatric revitalization with people aged over 65 holding Barthel Index scores equal to, or beyond, 90. The program was developed over 30 weeks, three times a week, in sessions lasting 45–50 min each. Frailty levels were registered by the Short Physical Performance Battery, FRAIL Questionnaire Screening Tool, and Timed “Up & Go” at the beginning of the program, 30 weeks later (at the end of the program), and following 13 weeks without training; (3) Results: 360 participants completed the program; a greater risk of frailty was found before the program started among older women living in urban areas, with a more elevated fat percentage, more baseline pathologies, and wider baseline medication use. Furthermore, heterogeneous results were observed both in training periods and in periods without physical activity. However, they are consistent over time and show improvement after training. They show a good correlation between TUG and SPPB; (4) Conclusions: A thirty-week multicomponent exercise program improves frailty and pre-frailty status in a community-dwelling population with no functional decline. Nevertheless, a lack of homogeneity is evident among the various tools used for measuring frailty over training periods and inactivity periods. metadata Morales-Sánchez, Almudena and Calvo Arenillas, José Ignacio and Gutiérrez Palmero, María José and Martín-Conty, José L. and Polonio-López, Begoña and Dzul Lopez, Luis Alonso and Mordillo-Mateos, Laura and Bernal-Jiménez, Juan José and Conty-Serrano, Rosa and Torres-Falguera, Francisca and Martínez Cano, Alfonso and Durantez-Fernández, Carlos mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, luis.dzul@unini.edu.mx, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2024) A Prospective Observational Study of Frailty in Geriatric Revitalization Aimed at Community-Dwelling Elderly. Journal of Clinical Medicine, 13 (9). p. 2514. ISSN 2077-0383

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés In the context of decision-making, the DEMATEL (Decision Making Trial and Evaluation Laboratory) method stands out for its systematic approach to complex systems. By incorporating fuzzy logic, the DEMATEL fuzzy method takes traditional techniques a step further, effectively managing the uncertainties and imprecision inherent in expert assessments. This hybrid method has proved useful in a variety of fields, including business, engineering, healthcare, environmental management, and education. Its ability to refine subjective judgments into actionable information enables decision-makers to improve organizational performance, optimize resource allocation, and achieve more accurate results. The development of software tools for these methods makes them more accessible and practical, enabling more effective analysis and application. In this paper, we propose a flexible implementation that integrates seamlessly into Python-based applications, offering full access to all parameters, matrices, and intermediary calculations of the method. Additionally, the tool also provides a user-friendly graphical interface. metadata Chekry, Abderrahman and Bakkas, Jamal and Hanine, Mohamed and Caro Montero, Elizabeth and Garat de Marin, Mirtha Silvana and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, elizabeth.caro@uneatlantico.es, silvana.marin@uneatlantico.es, UNSPECIFIED (2024) PyDEMATEL: A Python-based tool implementing DEMATEL and fuzzy DEMATEL methods for improved decision making. SoftwareX, 28. p. 101889. ISSN 23527110

Article Subjects > Teaching Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Español Esta investigación tuvo por objetivo valorar la utilización de un Instrumento para la evaluación de Entornos Virtuales de Aprendizaje (EVA), específicamente el DELES (Distance Education Learning Environments Survey) para el Proyecto Europeo de Educación Inclusiva denominado LOVEDISTANCE (Learning Optimization and Academic Inclusion Via Equitative Distance Teaching and Learning). El supuesto inicial es que el instrumento puede ser útil, pero está desactualizado y no necesariamente enfocado a los objetivos del proyecto LOVEDISTANCE, en particular al de Educación Inclusiva. El ejercicio académico se llevó a cabo en la Universidad de Levinsky, en Tel Aviv, Israel, y el análisis de la información se hizo con un enfoque cuanti-cualitativo, donde se utilizó, en una primera parte, la medida del consenso entre expertos para medir la fiabilidad estadística de las respuestas de los expertos, y después se realizó un análisis de la varianza (ANOVA) para determinar si existían diferencias significativas entre las medias de los grupos; posteriormente, se hizo un análisis cualitativo pormenorizado de las observaciones a partir de tres ejes de análisis: consideraciones del ejercicio investigativo, perfil de los investigadores y análisis de cada escala del instrumento. Algunas de las conclusiones más relevantes fueron que el instrumento es, en su mayoría, útil para los propósitos del proyecto LOVEDISTANCE, pero precisa mejoras en lo referido a las siguientes escalas: relevancia del aprendizaje para el alumno, apoyo por parte del instructor y la medición en la autonomía del estudiante. metadata Garat de Marin, Mirtha Silvana and Rodríguez Velasco, Carmen Lilí and Prola, Thomas and Soriano Flores, Emmanuel mail silvana.marin@uneatlantico.es, carmen.rodriguez@uneatlantico.es, thomas.prola@uneatlantico.es, emmanuel.soriano@uneatlantico.es (2024) Readaptación de un instrumento para la evaluación de entornos virtuales de aprendizaje en el proyecto europeo de educación inclusiva denominado LOVEDISTANCE. MLS Educational Research, 8 (1). ISSN 2603-5820

Article Subjects > Biomedicine Europe University of Atlantic > Research > Articles and books Abierto Inglés Background: Current standard of care for la-mUC pts who show no progression after platinum-based chemotherapy is maintenance with avelumab based on survival improvement (JAVELIN 100; Powles et al. NEJM 2020). However, the available RWD evidence on the use of avelumab in the E.U. is limited and there are concerns about the low uptake of this strategy based on figures from American series (Mamtani R et al; JAMA Netw Open 2023). We present here data on the use of avelumab in a large cohort of pts from different centres in Spain within the academic group GO NORTE. Methods: AVEBLADDER is a retrospective observational analysis in which clinical information was retrieved from pts treated across 14 centres in 13 provinces in Northern Spain. The study population included adult pts diagnosed with la/mUC (January 1, 2021-June 30, 2023) followed from date of diagnosis until death, loss to follow-up or end of study. Median overall survival (OS) was determined using the Kaplan-Meier method. Results: 419 pts were included. Median age was 71 [range 42-88]; 80% were males; 81% had primary bladder tumours and 94% predominant urothelial histology. Seventy three percent of pts had visceral/bony metastases and 59% were unfit for cisplatin. Most common 1st line treatment (tx) [88%] was platinum-based chemotherapy [median number of cycles 4]. Out of 369 pts who received platinum-based chemotherapy, non-progression (CR, PR or SD) was reported in 230 pts [62%], of whom only 85 pts [37%] received maintenance avelumab. Fifty-eight pts treated with avelumab were evaluable for response: 7 (10 %) achieved a CR, 12 (14%) PR, 22 (26%) SD and 17 (20%) PD. The most common reason for non-receiving avelumab in our series was lack of access/reimbursement according to country/region policy. Overall, 168 pts [40%] started 2nd line tx and atezolizumab was the most used agent, only 41 pts [24%] received third line tx. With a median follow-up of 11 months, 194 pts [46%] are still alive and median overall survival (OS) is estimated to be 28 months (95% CI 23-not reached) with maintenance avelumab vs 11 months (95% CI 9-13) for those who did not receive this drug. Conclusions: Despite the demonstrated improvement in OS for maintenance avelumab, its uptake in our series was low with roughly 40% of the pts. New policies and better access to the drug will most likely improve these figures and hopefully also the proportion of patients who progress to receive a third line where novel therapies are currently being implemented. AVEBLADDER is a study sponsored by GO NORTE a non-for-profit GU cooperative group. metadata Sotelo, Marta and Peláez, Mireia and Basterretxea, Laura and Varga, Estrella and Sánchez-Escribano, Ricardo and Pujol, Eduardo and Santander, Carmen and Martinez-Kareaga, Mireia and Arruti Ibarbia, Mikel and Rodríguez Ledesma, Inma and Álvarez-Fernández, Carlos and Piedra, Pablo and Calderero, Veronica and Lainez, Nuria and Verdun Aguilar, Juan Antonio and Gil-Arnaiz, Irene and Fernandez, Ricardo and Mazas Pérez-Oleaga, Cristina and Duran, Ignacio mail UNSPECIFIED, mireia.pelaez@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, cristina.mazas@uneatlantico.es, UNSPECIFIED (2024) Real-world data (RWD) with avelumab in patients (pts) with locally advanced or metastatic urothelial cancer (la-mUC): The AVEBLADDER study. Journal of Clinical Oncology, 42 (16_sup). e16559-e16559. ISSN 0732-183X

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books Abierto Inglés The conservation of Cultural Heritage in cave environments, especially those hosting cave art, requires comprehensive conservation strategies to mitigate degradation risks derived from climatic influences and human activities. This study, focused on the Polychrome Hall of the Cave of Altamira, highlights the importance of integrating remote sensing methodologies to carry out effective conservation actions. By coupling a georeferenced Ground Penetrating Radar (GPR) with a 1.6 GHz central-frequency antenna along with photogrammetry, we conducted non-invasive and high-resolution 3D studies to map preferential moisture pathways from the surface of the ceiling to the first 50 cm internally of the limestone structure. In parallel, we monitored the dynamics of surface water on the Ceiling and its correlation with pigment and other substance migrations. By standardizing our methodology, we aim to increase knowledge about the dynamics of infiltration water, which will enhance our understanding of the deterioration processes affecting cave paintings related to infiltration water. This will enable us to improve conservation strategies, suggesting possible indirect measures to reverse active deterioration processes. Integrating remote sensing techniques with geospatial analysis will aid in the validation and calibration of collected data, allowing for stronger interpretations of subsurface structures and conditions. All of this puts us in a position to contribute to the development of effective conservation methodologies, reduce alteration risks, and promote sustainable development practices, thus emphasizing the importance of remote sensing in safeguarding Cultural Heritage. metadata Bayarri Cayón, Vicente and Prada, Alfredo and García, Francisco and De Las Heras, Carmen and Fatás, Pilar mail vicente.bayarri@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2024) Remote Sensing and Environmental Monitoring Analysis of Pigment Migrations in Cave of Altamira’s Prehistoric Paintings. Remote Sensing, 16 (12). p. 2099. ISSN 2072-4292

Article Subjects > Biomedicine Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Cardiovascular diseases are among the leading causes of mortality worldwide, with dietary factors being the main risk contributors. Diets rich in bioactive compounds, such as (poly)phenols, have been shown to potentially exert positive effects on vascular health. Among them, resveratrol has gained particular attention due to its potential antioxidant and anti-inflammatory action. Nevertheless, the results in humans are conflicting possibly due to interindividual different responses. The gut microbiota, a complex microbial community that inhabits the gastrointestinal tract, has been called out as potentially responsible for modulating the biological activities of phenolic metabolites in humans. The present review aims to summarize the main findings from clinical trials on the effects of resveratrol interventions on endothelial and vascular outcomes and review potential mechanisms interesting the role of gut microbiota on the metabolism of this molecule and its cardioprotective metabolites. The findings from randomized controlled trials show contrasting results on the effects of resveratrol supplementation and vascular biomarkers without dose-dependent effect. In particular, studies in which resveratrol was integrated using food sources, i.e., red wine, reported significant effects although the resveratrol content was, on average, much lower compared to tablet supplementation, while other studies with often extreme resveratrol supplementation resulted in null findings. The results from experimental studies suggest that resveratrol exerts cardioprotective effects through the modulation of various antioxidant, anti-inflammatory, and anti-hypertensive pathways, and microbiota composition. Recent studies on resveratrol-derived metabolites, such as piceatannol, have demonstrated its effects on biomarkers of vascular health. Moreover, resveratrol itself has been shown to improve the gut microbiota composition toward an anti-inflammatory profile. Considering the contrasting findings from clinical studies, future research exploring the bidirectional link between resveratrol metabolism and gut microbiota as well as the mediating effect of gut microbiota in resveratrol effect on cardiovascular health is warranted. metadata Godos, Justyna and Romano, Giovanni Luca and Gozzo, Lucia and Laudani, Samuele and Paladino, Nadia and Dominguez Azpíroz, Irma and Martínez López, Nohora Milena and Giampieri, Francesca and Quiles, José L. and Battino, Maurizio and Galvano, Fabio and Drago, Filippo and Grosso, Giuseppe mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, irma.dominguez@unini.edu.mx, nohora.martinez@uneatlantico.es, francesca.giampieri@uneatlantico.es, jose.quiles@uneatlantico.es, maurizio.battino@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2024) Resveratrol and vascular health: evidence from clinical studies and mechanisms of actions related to its metabolites produced by gut microbiota. Frontiers in Pharmacology, 15. ISSN 1663-9812

Article Subjects > Social Sciences Europe University of Atlantic > Research > Articles and books Abierto Inglés Introduction: Osteopathy was originally introduced in rural America in 1874 as a comprehensive therapeutic approach aimed at promoting health. This approach was distinct and often conflicting with conventional/allopathic therapeutic methods available at that time to fight disease. We argue that, in struggling to achieve recognition within the American healthcare system and within the educational academic field that was about to be structured, the American osteopathic profession tried to protect itself from the charges of sectarism by starting to embrace principles of the biomedical paradigm. Methods: A comparative and historiographic review of the second version of the autobiography of AT Still (1908), the founder of osteopathy, against the first (1897) was chosen as an example of the adaptation of the American osteopathic profession to its evolving academic environment. Results: Although there were only a few substantial variations, we argue that they aimed to dampen the non-biological components of osteopathy, namely, its philosophical, spiritual, religious, emotional, and Native American roots, in an effort to gain respect and recognition within the emerging gold standard of the Western medical system. The shift towards a distinct, fully integrated profession within regulated Western healthcare systems was perceived by many professionals as a threat to AT Still’s original ideas, and the trend started when he was alive. Conclusion: Our findings suggest that a crucial conversation regarding the future of the professional identity must take place within the osteopathic community. metadata Tuscano, Silvia Clara and Haxton, Jason and Ciardo, Antonio and Ciullo, Luigi and Zegarra-Parodi, Rafael mail UNSPECIFIED (2024) The Revisions of the First Autobiography of AT Still, the Founder of Osteopathy, as a Step towards Integration in the American Healthcare System: A Comparative and Historiographic Review. Healthcare, 12 (2). p. 130. ISSN 2227-9032

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés The purpose of the study is to assess the risk of developing general eating disorders (ED), anorexia nervosa (AN), and bulimia nervosa (BN), as well as to examine the effects of gender, academic year, place of residence, faculty, and diet quality on that risk. Over two academic years, 129 first- and fourth-year Uneatlántico students were included in an observational descriptive study. The self-administered tests SCOFF, EAT-26, and BITE were used to determine the participants’ risk of developing ED. The degree of adherence to the Mediterranean diet (MD) was used to evaluate the quality of the diet. Data were collected at the beginning (T1) and at the end (T2) of the academic year. The main results were that at T1, 34.9% of participants were at risk of developing general ED, AN 3.9%, and BN 16.3%. At T2, these percentages were 37.2%, 14.7%, and 8.5%, respectively. At T2, the frequency of general ED in the female group was 2.5 times higher (OR: 2.55, 95% CI: 1.22–5.32, p = 0.012). The low-moderate adherence to the MD students’ group was 0.92 times less frequent than general ED at T2 (OR: 0.921, 95%CI: 0.385–2.20, p < 0.001). The most significant risk factor for developing ED is being a female in the first year of university. Moreover, it appears that the likelihood of developing ED generally increases during the academic year. metadata Eguren García, Imanol and Sumalla Cano, Sandra and Conde González, Sandra and Vila-Martí, Anna and Briones Urbano, Mercedes and Martínez Díaz, Raquel and Elío Pascual, Iñaki mail imanol.eguren@uneatlantico.es, sandra.sumalla@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, mercedes.briones@uneatlantico.es, raquel.martinez@uneatlantico.es, inaki.elio@uneatlantico.es (2024) Risk Factors for Eating Disorders in University Students: The RUNEAT Study. Healthcare, 12 (9). p. 942. ISSN 2227-9032

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés With the rapid increase of users over social media, cyberbullying, and hate speech problems have arisen over the past years. Automatic hate speech detection (HSD) from text is an emerging research problem in natural language processing (NLP). Researchers developed various approaches to solve the automatic hate speech detection problem using different corpora in various languages, however, research on the Urdu language is rather scarce. This study aims to address the HSD task on Twitter using Roman Urdu text. The contribution of this research is the development of a hybrid model for Roman Urdu HSD, which has not been previously explored. The novel hybrid model integrates deep learning (DL) and transformer models for automatic feature extraction, combined with machine learning algorithms (MLAs) for classification. To further enhance model performance, we employ several hyperparameter optimization (HPO) techniques, including Grid Search (GS), Randomized Search (RS), and Bayesian Optimization with Gaussian Processes (BOGP). Evaluation is carried out on two publicly available benchmarks Roman Urdu corpora comprising HS-RU-20 corpus and RUHSOLD hate speech corpus. Results demonstrate that the Multilingual BERT (MBERT) feature learner, paired with a Support Vector Machine (SVM) classifier and optimized using RS, achieves state-of-the-art performance. On the HS-RU-20 corpus, this model attained an accuracy of 0.93 and an F1 score of 0.95 for the Neutral-Hostile classification task, and an accuracy of 0.89 with an F1 score of 0.88 for the Hate Speech-Offensive task. On the RUHSOLD corpus, the same model achieved an accuracy of 0.95 and an F1 score of 0.94 for the Coarse-grained task, alongside an accuracy of 0.87 and an F1 score of 0.84 for the Fine-grained task. These results demonstrate the effectiveness of our hybrid approach for Roman Urdu hate speech detection. metadata Ashiq, Waqar and Kanwal, Samra and Rafique, Adnan and Waqas, Muhammad and Khurshaid, Tahir and Caro Montero, Elizabeth and Bustamante Alonso, Alicia and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, elizabeth.caro@uneatlantico.es, alicia.bustamante@uneatlantico.es, UNSPECIFIED (2024) Roman urdu hate speech detection using hybrid machine learning models and hyperparameter optimization. Scientific Reports, 14 (1). ISSN 2045-2322

Article Subjects > Physical Education and Sport
Subjects > Teaching Europe University of Atlantic > Research > Articles and books Abierto Italiano The objective of this study was to understand the perceptions of Primary (PrE) and Secondary Education (SE) students in Cantabria about the subject of physical education (PE) and their teachers. A descriptive, comparative relational analytical cross-sectional design was used. A total of 1164 students (387 from PrE and 777 from SE) answered an ad hoc questionnaire on their satisfaction with their PE classes (eight items) and teachers (nine items). The results indicate that the PrE students were more satisfied than the SE students regarding the following statements about PE: more hours per week (p < 0.001); classes and subjects that I like the most (p < 0.001); I enjoy and have fun (p < 0.001); interesting and motivating (p < 0.001); and useful for life (p < 0.001) and easy (p = 0.006). The boys’ responses reflected higher values than the girls’ on all the previous items (p < 0.005). Regarding their thinking about their PE teachers, statistically significant differences were found in the PrE students’ responses compared with those of the SE students for the following: explains well and is easily understood (p = 0.006); stimulates and encourages participation (p = 0.050); cares and is interested in the students (p = 0.031); treat boys and girls the same (p < 0.001); and I prefer a woman because she understands me better (p = 0.021). Therefore, the male and primary-stage students showed more positive attitudes towards PE. In general, there was a favorable disposition towards PE and towards teachers, which must be taken into account to achieve SDG 4. metadata González-Gutiérrez, Iván and López-García, Sergio and Barcala Furelos, Martín and Mecías-Calvo, Marcos and Navarro-Patón, Rubén mail ivan.gutierrez@uneatlantico.es, UNSPECIFIED, martin.barcala@uneatlantico.es, marcos.mecias@uneatlantico.es, UNSPECIFIED (2024) Schoolchildren’s Thinking on the Subject and Teachers of Physical Education According to Gender and Educational Grade. Education Sciences, 14 (8). p. 914. ISSN 2227-7102

Article Subjects > Comunication Europe University of Atlantic > Research > Articles and books Cerrado Inglés The escalating prevalence of pornography consumption among the youth has raised significant concern within the scientific community. This study aims to systematically examine scholarly literature on adolescence and engagement with pornography. Employing a conceptual framework, a qualitative literature review was conducted. Data analysis involved compiling abstracts and employing the AI coding system of Atlas.ti 23. These narrative approaches include (1) adolescent online health and pornographic education, (2) youth sexual identity shaped by online pornographic content, (3) and government policies promoting (in)formed sex education. The study's conclusions underscore the detrimental effects of unregulated access to online pornographic content on adolescents, manifesting in distorted self-image, diminished self-esteem, and altered body perceptions. This phenomenon highlights the imperative of promoting comprehensive sex education. Media literacy is identified as a pivotal initiative to foster understanding of stereotypical representations and their societal and personal impacts. metadata Rojas-Estrada, Elizabeth-Guadalupe and Vizcaíno-Verdú, Arantxa and Bonilla-del-Río, Mónica mail UNSPECIFIED, UNSPECIFIED, monica.bonilla@uneatlantico.es (2024) Sexual (Mis): Pornography and Adolescence in the Digital Space. Comprehensive Sexuality Education for Gender-Based Violence Prevention. pp. 265-284. ISSN 2326-8905

Article Subjects > Biomedicine Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Assessment of side effects associated with COVID-19 vaccination is required to monitor safety issues and acceptance of vaccines in the long term. We found a significant knowledge gap in the safety profile of COVID-19 vaccines in Bangladesh. We enrolled 1805 vaccine recipients from May 5, 2021, to April 4, 2023. Kruskal-Wallis test and χ2 test were performed. Multivariable logistic regression was also performed. First, second and third doses were administered among 1805, 1341, and 923 participants, respectively. Oxford–AstraZeneca (2946 doses) was the highest administered followed by Sinopharm BIBP (551 doses), Sinovac (214 doses), Pfizer-BioNTech (198 doses), and Moderna (160 doses), respectively. Pain at the injection site (80-90%, 3200–3600), swelling (85%, 3458), redness (78%, 3168), and heaviness in hand (65%, 2645) were the most common local effects, and fever (85%, 3458), headache (82%, 3336), myalgia (70%, 2848), chills (67%, 2726), muscle pain (60%, 2441) were the most prevalent systemic side effects reported within 48 h of vaccination. Thrombosis was only reported among the Oxford–AstraZeneca recipients (3.5-5.7%). Both local and systemic effects were significantly associated with the Oxford–AstraZeneca (p-value < 0.05), Pfizer–BioNTech (p-value < 0.05), and Moderna (p-value < 0.05) vaccination. Chronic urticaria and psoriasis were reported by 55-60% of the recipients after six months or later. The highest percentage of local and systemic effects after 2nd and 3rd dose were found among recipients of Moderna followed by Pfizer-BioNTech and Oxford–AstraZeneca. Homogenous doses of Oxford–AstraZeneca and heterogenous doses of Moderna and Pfizer-BioNTech were significantly associated with elevated adverse effects. Females, aged above 60 years with preexisting health conditions had higher risks. Vaccination with Pfizer-BioNTech (OR 4.34, 95% CI 3.95–4.58) had the highest odds of severe and long-term effects followed by Moderna (OR 4.15, 95% CI 3.92–4.69) and Oxford–AstraZeneca (OR 3.89, 95% CI 3.45–4.06), respectively. This study will provide an integrated insight into the safety profile of COVID-19 vaccines. metadata Sharif, Nadim and Opu, Rubayet Rayhan and Saha, Tama and Khan, Afsana and Aljohani, Abrar and Alsuwat, Meshari A. and García, Carlos O. and Vázquez, Annia A. and Alzahrani, Khalid J. and Miramontes-González, J. Pablo and Dey, Shuvra Kanti mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, annia.almeyda@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2024) Side effects associated with homogenous and heterogenous doses of Oxford–AstraZeneca vaccine among adults in Bangladesh: an observational study. Scientific Reports, 14 (1). ISSN 2045-2322

Article Subjects > Biomedicine Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Assessment of side effects associated with COVID-19 vaccination is required to monitor safety issues and acceptance of vaccines in the long term. We found a significant knowledge gap in the safety profile of COVID-19 vaccines in Bangladesh. We enrolled 1805 vaccine recipients from May 5, 2021, to April 4, 2023. Kruskal-Wallis test and χ2 test were performed. Multivariable logistic regression was also performed. First, second and third doses were administered among 1805, 1341, and 923 participants, respectively. Oxford–AstraZeneca (2946 doses) was the highest administered followed by Sinopharm BIBP (551 doses), Sinovac (214 doses), Pfizer-BioNTech (198 doses), and Moderna (160 doses), respectively. Pain at the injection site (80-90%, 3200–3600), swelling (85%, 3458), redness (78%, 3168), and heaviness in hand (65%, 2645) were the most common local effects, and fever (85%, 3458), headache (82%, 3336), myalgia (70%, 2848), chills (67%, 2726), muscle pain (60%, 2441) were the most prevalent systemic side effects reported within 48 h of vaccination. Thrombosis was only reported among the Oxford–AstraZeneca recipients (3.5-5.7%). Both local and systemic effects were significantly associated with the Oxford–AstraZeneca (p-value < 0.05), Pfizer–BioNTech (p-value < 0.05), and Moderna (p-value < 0.05) vaccination. Chronic urticaria and psoriasis were reported by 55-60% of the recipients after six months or later. The highest percentage of local and systemic effects after 2nd and 3rd dose were found among recipients of Moderna followed by Pfizer-BioNTech and Oxford–AstraZeneca. Homogenous doses of Oxford–AstraZeneca and heterogenous doses of Moderna and Pfizer-BioNTech were significantly associated with elevated adverse effects. Females, aged above 60 years with preexisting health conditions had higher risks. Vaccination with Pfizer-BioNTech (OR 4.34, 95% CI 3.95–4.58) had the highest odds of severe and long-term effects followed by Moderna (OR 4.15, 95% CI 3.92–4.69) and Oxford–AstraZeneca (OR 3.89, 95% CI 3.45–4.06), respectively. This study will provide an integrated insight into the safety profile of COVID-19 vaccines. metadata Sharif, Nadim and Opu, Rubayet Rayhan and Saha, Tama and Khan, Afsana and Aljohani, Abrar and Alsuwat, Meshari A. and García, Carlos O. and Vázquez, Annia A. and Alzahrani, Khalid J. and Miramontes-González, J. Pablo and Dey, Shuvra Kanti mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, annia.almeyda@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2024) Side effects associated with homogenous and heterogenous doses of Oxford–AstraZeneca vaccine among adults in Bangladesh: an observational study. Scientific Reports, 14 (1). ISSN 2045-2322

Article Subjects > Biomedicine
Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Telephysiotherapy has emerged as a vital solution for delivering remote healthcare, particularly in response to global challenges such as the COVID-19 pandemic. This study seeks to enhance telephysiotherapy by developing a system capable of accurately classifying physiotherapeutic exercises using PoseNet, a state-of-the-art pose estimation model. A dataset was collected from 49 participants (35 males, 14 females) performing seven distinct exercises, with twelve anatomical landmarks then extracted using the Google MediaPipe library. Each landmark was represented by four features, which were used for classification. The core challenge addressed in this research involves ensuring accurate and real-time exercise classification across diverse body morphologies and exercise types. Several tree-based classifiers, including Random Forest, Extra Tree Classifier, XGBoost, LightGBM, and Hist Gradient Boosting, were employed. Furthermore, two novel ensemble models called RandomLightHist Fusion and StackedXLightRF are proposed to enhance classification accuracy. The RandomLightHist Fusion model achieved superior accuracy of 99.6%, demonstrating the system’s robustness and effectiveness. This innovation offers a practical solution for providing real-time feedback in telephysiotherapy, with potential to improve patient outcomes through accurate monitoring and assessment of exercise performance. metadata Hussain, Shahzad and Siddiqui, Hafeez Ur Rehman and Saleem, Adil Ali and Raza, Muhammad Amjad and Alemany Iturriaga, Josep and Velarde-Sotres, Álvaro and Díez, Isabel De la Torre and Dudley, Sandra mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, josep.alemany@uneatlantico.es, alvaro.velarde@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2024) Smart Physiotherapy: Advancing Arm-Based Exercise Classification with PoseNet and Ensemble Models. Sensors, 24 (19). p. 6325. ISSN 1424-8220

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Plant stress reduction research has advanced significantly with the use of Artificial Intelligence (AI) techniques, such as machine learning and deep learning. This is a significant step toward sustainable agriculture. Innovative insights into the physiological responses of plants mostly crops to drought stress have been revealed through the use of complex algorithms like gradient boosting, support vector machines (SVM), recurrent neural network (RNN), and long short-term memory (LSTM), combined with a thorough examination of the TYRKC and RBR-E3 domains in stress-associated signaling proteins across a range of crop species. Modern resources were used in this study, including the UniProt protein database for crop physiochemical properties associated with specific signaling domains and the SMART database for signaling protein domains. These insights were then applied to deep learning and machine learning techniques after careful data processing. The rigorous metric evaluations and ablation analysis that typified the study’s approach highlighted the algorithms’ effectiveness and dependability in recognizing and classifying stress events. Notably, the accuracy of SVM was 82%, while gradient boosting and RNN showed 96%, and 94%, respectively and LSTM obtained an astounding 97% accuracy. The study observed these successes but also highlights the ongoing obstacles to AI adoption in agriculture, emphasizing the need for creative thinking and interdisciplinary cooperation. In addition to its scholarly value, the collected data has significant implications for improving resource efficiency, directing precision agricultural methods, and supporting global food security programs. Notably, the gradient boosting and LSTM algorithm outperformed the others with an exceptional accuracy of 96% and 97%, demonstrating their potential for accurate stress categorization. This work highlights the revolutionary potential of AI to completely disrupt the agricultural industry while simultaneously advancing our understanding of plant stress responses. metadata Ali, Tariq and Rehman, Saif Ur and Ali, Shamshair and Mahmood, Khalid and Aparicio Obregón, Silvia and Calderón Iglesias, Rubén and Khurshaid, Tahir and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, silvia.aparicio@uneatlantico.es, ruben.calderon@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2024) Smart agriculture: utilizing machine learning and deep learning for drought stress identification in crops. Scientific Reports, 14 (1). ISSN 2045-2322

Article Subjects > Biomedicine Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Interleukin-10, a highly effective cytokine recognized for its anti-inflammatory properties, plays a critical role in the immune system. In addition to its well-documented capacity to mitigate inflammation, IL-10 can unexpectedly demonstrate pro-inflammatory characteristics under specific circumstances. The presence of both aspects emphasizes the vital need to identify the IL-10-induced peptide. To mitigate the drawbacks of manual identification, which include its high cost, this study introduces StackIL10, an ensemble learning model based on stacking, to identify IL-10-inducing peptides in a precise and efficient manner. Ten Amino-acid-composition-based Feature Extraction approaches are considered. The StackIL10, stacking ensemble, the model with five optimized Machine Learning Algorithm (specifically LGBM, RF, SVM, Decision Tree, KNN) as the base learners and a Logistic Regression as the meta learner was constructed, and the identification rate reached 91.7%, MCC of 0.833 with 0.9078 Specificity. Experiments were conducted to examine the impact of various enhancement techniques on the correctness of IL-10 Prediction. These experiments included comparisons between single models and various combinations of stacking-based ensemble models. It was demonstrated that the model proposed in this study was more effective than singular models and produced satisfactory results, thereby improving the identification of peptides that induce IL-10. metadata Usmani, Salman Sadullah and Tuhin, Izaz Ahmmed and Mia, Md. Rajib and Islam, Md. Monirul and Mahmud, Imran and Uc Ríos, Carlos Eduardo and Fabian Gongora, Henry and Ashraf, Imran and Samad, Md. Abdus mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, carlos.uc@unini.edu.mx, henry.gongora@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2024) StackIL10: A stacking ensemble model for the improved prediction of IL-10 inducing peptides. PLOS ONE, 19 (11). e0313835. ISSN 1932-6203

Article Subjects > Biomedicine
Subjects > Physical Education and Sport Europe University of Atlantic > Research > Articles and books Abierto Inglés Physical exercise both during and after curative cancer treatment has been shown to reduce side effects. Evidence in the metastatic cancer setting is scarce, and interventions that improve health-related quality of life (HRQOL) are much needed for patients with metastatic breast cancer (MBC). The multinational randomized controlled PREFERABLE-EFFECT trial assessed the effects of exercise on fatigue and HRQOL in patients with MBC. In total, 357 patients with MBC and a life expectancy of ≥6 months but without unstable bone metastases were recruited at eight study centers across five European countries and Australia. Participants were randomly assigned (1:1) to usual care (control group, n = 179) or a 9-month supervised exercise program (exercise group, n = 178). Intervention effects on physical fatigue (European Organization for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire (QLQ)-FA12 scale) and HRQOL (EORTC QLQ-C30 summary score) were determined by comparing the change from baseline to 3, 6 (primary timepoint) and 9 months between groups using mixed models for repeated measures, adjusted for baseline values of the outcome, line of treatment (first or second versus third or higher) and study center. Exercise resulted in significant positive effects on both primary outcomes. Physical fatigue was significantly lower (−5.3 (95% confidence interval (CI), −10.0 to −0.6), Bonferroni–Holm-adjusted P = 0.027; Cohen's effect size, 0.22) and HRQOL significantly higher (4.8 (95% CI, 2.2–7.4), Bonferroni–Holm-adjusted P = 0.0003; effect size, 0.33) in the exercise group than in the control group at 6 months. Two serious adverse events occurred (that is, fractures), but both were not related to bone metastases. These results demonstrate that supervised exercise has positive effects on physical fatigue and HRQOL in patients with MBC and should be recommended as part of supportive care. metadata Hiensch, Anouk E. and Depenbusch, Johanna and Schmidt, Martina E. and Monninkhof, Evelyn M. and Peláez, Mireia and Clauss, Dorothea and Gunasekara, Nadira and Zimmer, Philipp and Belloso, Jon and Trevaskis, Mark and Rundqvist, Helene and Wiskemann, Joachim and Müller, Jana and Sweegers, Maike G. and Fremd, Carlo and Altena, Renske and Gorecki, Maciej and Bijlsma, Rhodé and van Leeuwen-Snoeks, Lobke and ten Bokkel Huinink, Daan and Sonke, Gabe and Lahuerta, Ainhara and Mann, G. Bruce and Francis, Prudence A. and Richardson, Gary and Malter, Wolfram and van der Wall, Elsken and Aaronson, Neil K. and Senkus, Elzbieta and Urruticoechea, Ander and Zopf, Eva M. and Bloch, Wilhelm and Stuiver, Martijn M. and Wengstrom, Yvonne and Steindorf, Karen and May, Anne M. mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, mireia.pelaez@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2024) Supervised, structured and individualized exercise in metastatic breast cancer: a randomized controlled trial. Nature Medicine. ISSN 1078-8956

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books Abierto Inglés This study addresses the features of the internal structure of the geological layers adjacent to the Polychrome Hall ceiling of the Cave of Altamira (Spain) and their link to the distribution of moisture and geological discontinuities mainly as fractures, joints, bedding planes and detachments, using 3D Ground Penetrating Radar (GPR) mapping. In this research, 3D GPR data were collected with 300 MHz, 800 MHz and 1.6 GHz center frequency antennas. The data recorded with these three frequency antennas were combined to further our understanding of the layout of geological discontinuities and how they link to the moisture or water inputs that infiltrate and reach the ceiling surface where the rock art of the Polychrome Hall is located. The same 1 × 1 m2 area was adopted for 3D data acquisition with the three antennas, obtaining 3D isosurface (isoattribute-surface) images of internal distribution of moisture and structural features of the Polychrome Hall ceiling. The results derived from this study reveal significant insights into the overlying karst strata of Polychrome Hall, particularly the interface between the Polychrome Layer and the underlying Dolomitic Layer. The results show moisture patterns associated with geological features such as fractures, joints, detachments of strata and microcatchments, elucidating the mechanisms driving capillary rise and water infiltration coming from higher altitudes. The study primarily identifies areas of increased moisture content, correlating with earlier observations and enhancing our understanding of water infiltration patterns. This underscores the utility of 3D GPR as an essential tool for informing and putting conservation measures into practice. By delineating subsurface structures and moisture dynamics, this research contributes to a deeper analysis of the deterioration processes directly associated with the infiltration water both in this ceiling and in the rest of the Cave of Altamira, providing information to determine its future geological and hydrogeological evolution. metadata Bayarri Cayón, Vicente and Prada, Alfredo and García, Francisco and De Las Heras, Carmen and Fatás, Pilar mail vicente.bayarri@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2024) Tracking Moisture Dynamics in a Karst Rock Formation Combining Multi-Frequency 3D GPR Data: A Strategy for Protecting the Polychrome Hall Paintings in Altamira Cave. Remote Sensing, 16 (20). p. 3905. ISSN 2072-4292

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Driving while drowsy poses significant risks, including reduced cognitive function and the potential for accidents, which can lead to severe consequences such as trauma, economic losses, injuries, or death. The use of artificial intelligence can enable effective detection of driver drowsiness, helping to prevent accidents and enhance driver performance. This research aims to address the crucial need for real-time and accurate drowsiness detection to mitigate the impact of fatigue-related accidents. Leveraging ultra-wideband radar data collected over five minutes, the dataset was segmented into one-minute chunks and transformed into grayscale images. Spatial features are retrieved from the images using a two-dimensional Convolutional Neural Network. Following that, these features were used to train and test multiple machine learning classifiers. The ensemble classifier RF-XGB-SVM, which combines Random Forest, XGBoost, and Support Vector Machine using a hard voting criterion, performed admirably with an accuracy of 96.6%. Additionally, the proposed approach was validated with a robust k-fold score of 97% and a standard deviation of 0.018, demonstrating significant results. The dataset is augmented using Generative Adversarial Networks, resulting in improved accuracies for all models. Among them, the RF-XGB-SVM model outperformed the rest with an accuracy score of 99.58%. metadata Siddiqui, Hafeez Ur Rehman and Akmal, Ambreen and Iqbal, Muhammad and Saleem, Adil Ali and Raza, Muhammad Amjad and Zafar, Kainat and Zaib, Aqsa and Dudley, Sandra and Arambarri, Jon and Kuc Castilla, Ángel Gabriel and Rustam, Furqan mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, jon.arambarri@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2024) Ultra-Wide Band Radar Empowered Driver Drowsiness Detection with Convolutional Spatial Feature Engineering and Artificial Intelligence. Sensors, 24 (12). p. 3754. ISSN 1424-8220

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés Over the last decades, the Mediterranean diet gained enormous scientific, social, and commercial attention due to proven positive effects on health and undeniable taste that facilitated a widespread popularity. Researchers have investigated the role of Mediterranean-type dietary patterns on human health all around the world, reporting consistent findings concerning its benefits. However, what does truly define the Mediterranean diet? The myriad of dietary scores synthesizes the nutritional content of a Mediterranean-type diet, but a variety of aspects are generally unexplored when studying the adherence to this dietary pattern. Among dietary factors, the main characteristics of the Mediterranean diet, such as consumption of fruit and vegetables, olive oil, and cereals should be accompanied by other underrated features, such as the following: (i) specific reference to whole-grain consumption; (ii) considering the consumption of legumes, nuts, seeds, herbs and spices often untested when exploring the adherence to the Mediterranean diet; (iii) consumption of eggs and dairy products as common foods consumed in the Mediterranean region (irrespectively of the modern demonization of dietary fat intake). Another main feature of the Mediterranean diet includes (red) wine consumption, but more general patterns of alcohol intake are generally unmeasured, lacking specificity concerning the drinking occasion and intensity (i.e., alcohol drinking during meals). Among other underrated aspects, cooking methods are rather simple and yet extremely varied. Several underrated aspects are related to the quality of food consumed when the Mediterranean diet was first investigated: foods are locally produced, minimally processed, and preserved with more natural methods (i.e., fermentation), strongly connected with the territory with limited and controlled impact on the environment. Dietary habits are also associated with lifestyle behaviors, such as sleeping patterns, and social and cultural values, favoring commensality and frugality. In conclusion, it is rather reductive to consider the Mediterranean diet as just a pattern of food groups to be consumed decontextualized from the social and geographical background of Mediterranean culture. While the methodologies to study the Mediterranean diet have demonstrated to be useful up to date, a more holistic approach should be considered in future studies by considering the aforementioned underrated features and values to be potentially applied globally through the concept of a “Planeterranean” diet. metadata Godos, Justyna and Scazzina, Francesca and Paternò Castello, Corrado and Giampieri, Francesca and Quiles, José L. and Briones Urbano, Mercedes and Battino, Maurizio and Galvano, Fabio and Iacoviello, Licia and de Gaetano, Giovanni and Bonaccio, Marialaura and Grosso, Giuseppe mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, francesca.giampieri@uneatlantico.es, jose.quiles@uneatlantico.es, mercedes.briones@uneatlantico.es, maurizio.battino@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2024) Underrated aspects of a true Mediterranean diet: understanding traditional features for worldwide application of a “Planeterranean” diet. Journal of Translational Medicine, 22 (1). ISSN 1479-5876

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés This paper studies the latest and state-of-the-art underwater thermal energy harvesting algorithms and techniques designed in the latest decade (2014-2024). The techniques are classified based on their unique operations for energy harvesting. This classification includes thermal energy harvesting using a phase change material (PCM), thermoelectric generator (TEG) and multi-source harvesting. Every class of techniques is described by its operation using a schematic diagram and a mathematical model to fully understand its working principle. Moreover, every individual technique is also described in terms of its operation, amount of harvested energy/power and the aspect(s) where margin of further improvement exists. Also, a comparative analysis of the classified algorithms is performed with each other as well as with other underwater energy harvesting techniques (solar, piezoelectric, wave) to highlight their effectiveness and feasibility in a diverse set of underwater and various other applications. The classified techniques are also compared in terms of harvested output to indicate their harvesting efficiency. Furthermore, the publications made in the latest decade in terms of thermal energy harvesting using PCM, TEG and multi-source methods are also graphically depicted. Such a description of the studied techniques and classified methods is unique from the already existing underwater energy harvesting reviews in literature where an in-depth and thorough analysis is absent, rather only marginal description is given. The harvesting results indicate that hybrid (multi-source) and PCM methods have the greatest amount of harvested power and energy, respectively. Finally, the research challenges in underwater thermal energy harvesting are specified and areas of further research are highlighted for future investigation. metadata Khan, Anwar and Gracia Villar, Santos and Dzul López, Luis Alonso and Almaleh, Abdulaziz and Alqahtani, Abdullah M. and Alnaimi, Raja’A mail UNSPECIFIED, santos.gracia@uneatlantico.es, luis.dzul@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2024) Underwater Thermal Energy Harvesting: Frameworks, Challenges, Applications, and Future Investigation. IEEE Access, 12. pp. 174371-174386. ISSN 2169-3536

Article Subjects > Comunication Europe University of Atlantic > Research > Articles and books Abierto Inglés The current media ecosystem, marked by immediacy and social networks dynamics, has created a fertile field for disinformation. Faced with its exponential growth, since 2014, research has focused on combating false content in the media. From a descriptive approach, this study has analyzed 200 documents on fact-checking and fake news published between 2014 and 2022 in scientific journals indexed in Scopus. This study has found that Europe and the United States are leading the way in the number of journals and authors publishing on the subject. The United States universities are the ones that host the most significant number of authors working on fact-checking, while the methodologies used, mostly ad hoc due to the novelty of the topic, allow to reflect on the need to promote work focused on the design, testing, and evaluation of prototypes or real experiences within the field. The most common contributions analyzed include typologies of false content and media manipulation mechanisms, models for evaluating and detecting disinformation, proposals to combat false content and strengthen verification mechanisms, studies on the role of social media in the spread of disinformation, efforts to develop media literacy among the public and journalists, case studies of fact-checkers, identification of factors that influence the belief in fake news, and analysis of the relationship between disinformation, verification, politics, and democracy. It is concluded that it is essential to develop research that connects the academy with the industry to raise awareness of the need to address these issues among the different actors in the media scenario. metadata Tejedor, Santiago and Romero-Rodríguez, Luis M. and Gracia Villar, Mónica mail UNSPECIFIED, UNSPECIFIED, monica.gracia@uneatlantico.es (2024) Unveiling the truth: A systematic review of fact-checking and fake news research in social sciences. Online Journal of Communication and Media Technologies, 14 (2). e202427. ISSN 1986-3497

Article Subjects > Biomedicine
Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Virtual histopathology is an emerging technology in medical imaging that utilizes advanced computational methods to analyze tissue images for more precise disease diagnosis. Traditionally, histopathology relies on manual techniques and expertise, often resulting in time-consuming processes and variability in diagnoses. Virtual histopathology offers a more consistent, and automated approach, employing techniques like machine learning, deep learning, and image processing to simulate staining and enhance tissue analysis. This review explores the strengths, limitations, and clinical applications of these methods, highlighting recent advancements in virtual histopathological approaches. In addition, important areas are identified for future research to improve diagnostic accuracy and efficiency in clinical settings. metadata Imran, Muhammad Talha and Shafi, Imran and Ahmad, Jamil and Butt, Muhammad Fasih Uddin and Gracia Villar, Santos and García Villena, Eduardo and Khurshaid, Tahir and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, santos.gracia@uneatlantico.es, eduardo.garcia@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2024) Virtual histopathology methods in medical imaging - a systematic review. BMC Medical Imaging, 24 (1). ISSN 1471-2342

Article Subjects > Psychology Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production Cerrado Inglés Introduction: Trait driving anger is a widely studied personality variable in the field of road safety, due to its strong relationship with both risky behavior on the road and crash-related events. The Deffenbacher’s Driving Anger Scale theoretical approach has underlined different situations that could provoke anger in drivers, although trait driving anger is usually analyzed as a whole. Trait general anger has been proposed as one of the most relevant predictors of trait driving anger, showing moderate relationships with it. Method: The current research aimed to analyze the relationship between trait general anger and each one of the situations provoking anger, as well as to search for personality variables that could moderate these relationships. Based on literature review, it was expected that self-esteem would moderate both Discourtesy and Hostile gestures, Type-A behavior pattern would moderate both Slow driving and Traffic obstructions, and conscientiousness would moderate both Police presence and Illegal driving. A sample of 417 drivers (Mage = 31.24, SDage = 13.59, 64.5% females) taken from the Spanish general population completed a set of self-reports. Results: The results showed significant moderation effects in the case of Hostile gestures, Discourtesy, Illegal driving, and Slow driving. Conditional processes of these moderations were analyzed. Lastly, practical implications are discussed, allowing for tailored interventions to be implemented based on individual drivers' tendencies. Therefore, interventions should address different triggers of driving anger: boosting self-esteem for those angered by disrespect, targeting Type-A behavior reduction for those angered by traffic slowdowns, and promoting conscientiousness enhancement for those angered by others' risky driving. metadata Herrero-Fernández, David and Bogdan-Ganea, Smaranda R. and Álvarez Ferradas, Carla and Martín Ayala, Juan Luis mail david.herrero@uneatlantico.es, UNSPECIFIED, carla.alvarez@uneatlantico.es, juan.martin@uneatlantico.es (2024) Which drivers drive as they live and who are transformed while driving? Analysis of moderators in the relationship between general anger and driving anger. Journal of Safety Research, 90. pp. 295-305. ISSN 00224375

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Background/Objectives: The diet quality of younger individuals is decreasing globally, with alarming trends also in the Mediterranean region. The aim of this study was to assess diet quality and adequacy in relation to country-specific dietary recommendations for children and adolescents living in the Mediterranean area. Methods: A cross-sectional survey was conducted of 2011 parents of the target population participating in the DELICIOUS EU-PRIMA project. Dietary data and cross-references with food-based recommendations and the application of the youth healthy eating index (YHEI) was assessed through 24 h recalls and food frequency questionnaires. Results: Adherence to recommendations on plant-based foods was low (less than ∼20%), including fruit and vegetables adequacy in all countries, legume adequacy in all countries except for Italy, and cereal adequacy in all countries except for Portugal. For animal products and dietary fats, the adequacy in relation to the national food-based dietary recommendations was slightly better (∼40% on average) in most countries, although the Eastern countries reported worse rates. Higher scores on the YHEI predicted adequacy in relation to vegetables (except Egypt), fruit (except Lebanon), cereals (except Spain), and legumes (except Spain) in most countries. Younger children (p < 0.005) reporting having 8–10 h adequate sleep duration (p < 0.001), <2 h/day screen time (p < 0.001), and a medium/high physical activity level (p < 0.001) displayed a better diet quality. Moreover, older respondents (p < 0.001) with a medium/high educational level (p = 0.001) and living with a partner (p = 0.003) reported that their children had a better diet quality. Conclusions: Plant-based food groups, including fruit, vegetables, legumes, and even (whole-grain) cereals are underrepresented in the diets of Mediterranean children and adolescents. Moreover, the adequate consumption of other important dietary components, such as milk and dairy products, is rather disregarded, leading to substantially suboptimal diets and poor adequacy in relation to dietary guidelines. metadata Giampieri, Francesca and Rosi, Alice and Scazzina, Francesca and Frias-Toral, Evelyn and Abdelkarim, Osama and Aly, Mohamed and Zambrano-Villacres, Raynier and Pons, Juancho and Vázquez-Araújo, Laura and Sumalla Cano, Sandra and Elío Pascual, Iñaki and Monasta, Lorenzo and Mata, Ana and Pardo, María Isabel and Busó, Pablo and Grosso, Giuseppe mail francesca.giampieri@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, sandra.sumalla@uneatlantico.es, inaki.elio@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2024) Youth Healthy Eating Index (YHEI) and Diet Adequacy in Relation to Country-Specific National Dietary Recommendations in Children and Adolescents in Five Mediterranean Countries from the DELICIOUS Project. Nutrients, 16 (22). p. 3907. ISSN 2072-6643

Article Subjects > Biomedicine
Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Cerrado Inglés Colorectal cancer often leads to metastasis, with cancer stem cells (CSCs) playing a pivotal role in this process. Two closely linked mechanisms, epithelial-mesenchymal transition and angiogenesis, contribute to metastasis and recent research has also highlighted the impact of telomere replication on this harmful tumor progression. Standard chemotherapy alone can inadvertently promote drug-resistant CSCs, posing a challenge. Combining chemotherapy with other compounds, including natural ones, shows promise in enhancing effectiveness while minimizing side effects. This study investigated the anti-metastatic potential of Manuka honey, both alone and in combination with 5-Fluorouracil, using a 3D model of colon spheres enriched with CSCs-like cells. In summary, it was observed that the treatment reduced migration ability by increasing the expression of E-cadherin through the downregulation of transcription factors Slug, Snail, and Twist. Additionally, it downregulated pro-angiogenic factors and shortened CSC telomeres by downregulating c-Myc, demonstrating an effective anti-metastatic potential. This study suggests new research opportunities for studying the impact of natural compounds when combined with pharmaceuticals, with the potential to enhance effectiveness and reduce side effects. metadata Cianciosi, Danila and Forbes-Hernández, Tamara Yuliett and Armas Diaz, Yasmany and Elexpuru Zabaleta, Maria and Quiles, José L. and Battino, Maurizio and Giampieri, Francesca mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, maria.elexpuru@uneatlantico.es, jose.quiles@uneatlantico.es, maurizio.battino@uneatlantico.es, francesca.giampieri@uneatlantico.es (2024) The anti-metastatic effect of Manuka honey on colonspheres enriched with cancer stem cells: how does it influence the epithelial-mesenchymal transition process, angiogenesis, and telomere length? Food & Function. ISSN 2042-6496

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
Fundación Universitaria Internacional de Colombia > Research > Scientific Production Abierto Inglés Named Entity Recognition (NER) is a natural language processing task that has been widely explored for different languages in the recent decade but is still an under-researched area for the Urdu language due to its rich morphology and language complexities. Existing state-of-the-art studies on Urdu NER use various deep-learning approaches through automatic feature selection using word embeddings. This paper presents a deep learning approach for Urdu NER that harnesses FastText and Floret word embeddings to capture the contextual information of words by considering the surrounding context of words for improved feature extraction. The pre-trained FastText and Floret word embeddings are publicly available for Urdu language which are utilized to generate feature vectors of four benchmark Urdu language datasets. These features are then used as input to train various combinations of Long Short-Term Memory (LSTM), Bidirectional LSTM (BiLSTM), Gated Recurrent Unit (GRU), CRF, and deep learning models. The results show that our proposed approach significantly outperforms existing state-of-the-art studies on Urdu NER, achieving an F-score of up to 0.98 when using BiLSTM+GRU with Floret embeddings. Error analysis shows a low classification error rate ranging from 1.24% to 3.63% across various datasets showing the robustness of the proposed approach. The performance comparison shows that the proposed approach significantly outperforms similar existing studies. metadata Khan, Hikmat Ullah and Anam, Rimsha and Anwar, Muhammad Waqas and Jamal, Muhammad Hasan and Bajwa, Usama Ijaz and Diez, Isabel de la Torre and Silva Alvarado, Eduardo René and Soriano Flores, Emmanuel and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, eduardo.silva@funiber.org, emmanuel.soriano@uneatlantico.es, UNSPECIFIED (2024) A deep learning approach for Named Entity Recognition in Urdu language. PLOS ONE, 19 (3). e0300725. ISSN 1932-6203

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Accurately predicting the remaining useful life (RUL) of lithium-ion (Li-ion) batteries is vital for improving battery performance and safety in applications such as consumer electronics and electric vehicles. While the prediction of RUL for these batteries is a well-established field, the current research refines RUL prediction methodologies by leveraging deep learning techniques, advancing prediction accuracy. This study proposes AccuCell Prodigy, a deep learning model that integrates auto-encoders and long short-term memory (LSTM) layers to enhance RUL prediction accuracy and efficiency. The model’s name reflects its precision (“AccuCell”) and predictive strength (“Prodigy”). The proposed methodology involves preparing a dataset of battery operational features, split using an 80–20 ratio for training and testing. Leveraging 22 variations of current (critical parameter) across three Li-ion cells, AccuCell Prodigy significantly reduces prediction errors, achieving a mean square error of 0.1305%, mean absolute error of 2.484%, and root mean square error of 3.613%, with a high R-squared value of 0.9849. These results highlight its robustness and potential for advancing battery health management. metadata Iftikhar, Mahrukh and Shoaib, Muhammad and Altaf, Ayesha and Iqbal, Faiza and Gracia Villar, Santos and Dzul López, Luis Alonso and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, santos.gracia@uneatlantico.es, luis.dzul@uneatlantico.es, UNSPECIFIED (2024) A deep learning approach to optimize remaining useful life prediction for Li-ion batteries. Scientific Reports, 14 (1). ISSN 2045-2322

Article Subjects > Physical Education and Sport Europe University of Atlantic > Research > Articles and books Abierto Inglés Aim The main objective of the study was to report the changes that have taken place in the practice of physical exercise during confinement and to examine the factors that favor or detract from it. Material and methods To determine the objective, a survey was carried out in the United States during the pandemic and a sample of 511 participants was obtained. A binary logit model was used to process the data, as well as several independence tests. Results The main result of this study is the increase in the practice of physical activity of the individuals surveyed during the pandemic. Some of the elements that most influenced this increase were annual family income, education level, and eating habits, but these results are subject to change depending on the respondent’s body mass index. On the other hand, the results also show changes in physical exercise habits during the pandemic, especially in the time of the week when it is performed, and these changes are highly correlated with the use of electronic devices, hours of sleep, and physical condition of the respondents before the pandemic. Conclusion Determining the different factors that affect the practice of physical exercise during pandemic periods seems to be important to determine in which populations it is more important to act or what resources are necessary when implementing physical exercise programs in specific situations such as pandemics. metadata Pulgar, Susana and Mazas Pérez-Oleaga, Cristina and Kaviani, Sepideh and Butts-Wilmsmeyer, Carolyn and Fernandez-del-Valle, Maria mail susana.pulgar@uneatlantico.es, cristina.mazas@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2024) An empirical analysis of factors determining changes in physical exercise during the COVID-19 pandemic. Journal of Public Health. ISSN 2198-1833

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés The essence of quantum machine learning is to optimize problem-solving by executing machine learning algorithms on quantum computers and exploiting potent laws such as superposition and entanglement. Support vector machine (SVM) is widely recognized as one of the most effective classification machine learning techniques currently available. Since, in conventional systems, the SVM kernel technique tends to sluggish down and even fail as datasets become increasingly complex or jumbled. To compare the execution time and accuracy of conventional SVM classification to that of quantum SVM classification, the appropriate quantum features for mapping need to be selected. As the dataset grows complex, the importance of selecting an appropriate feature map that outperforms or performs as well as the classification grows. This paper utilizes conventional SVM to select an optimal feature map and benchmark dataset for predicting air quality. Experimental evidence demonstrates that the precision of quantum SVM surpasses that of classical SVM for air quality assessment. Using quantum labs from IBM’s quantum computer cloud, conventional and quantum computing have been compared. When applied to the same dataset, the conventional SVM achieved an accuracy of 91% and 87% respectively, whereas the quantum SVM demonstrated an accuracy of 97% and 94% respectively for air quality prediction. The study introduces the use of quantum Support Vector Machines (SVM) for predicting air quality. It emphasizes the novel method of choosing the best quantum feature maps. Through the utilization of quantum-enhanced feature mapping, our objective is to exceed the constraints of classical SVM and achieve unparalleled levels of precision and effectiveness. We conduct precise experiments utilizing IBM’s state-of-the-art quantum computer cloud to compare the performance of conventional and quantum SVM algorithms on a shared dataset. metadata Farooq, Omer and Shahid, Maida and Arshad, Shazia and Altaf, Ayesha and Iqbal, Faiza and Vera, Yini Airet Miro and Flores, Miguel Angel Lopez and Ashraf, Imran mail UNSPECIFIED (2024) An enhanced approach for predicting air pollution using quantum support vector machine. Scientific Reports, 14 (1). ISSN 2045-2322

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Video content on the web platform has increased explosively during the past decade, thanks to the open access to Facebook, YouTube, etc. YouTube is the second-largest social media platform nowadays containing more than 37 million YouTube channels. YouTube revealed at a recent press event that 30,000 new content videos per hour and 720,000 per day are posted. There is a need for an advanced deep learning-based approach to categorize the huge database of YouTube videos. This study aims to develop an artificial intelligence-based approach to categorize YouTube videos. This study analyzes the textual information related to videos like titles, descriptions, user tags, etc. using YouTube exploratory data analysis (YEDA) and shows that such information can be potentially used to categorize videos. A deep convolutional neural network (DCNN) is designed to categorize YouTube videos with efficiency and high accuracy. In addition, recurrent neural network (RNN), and gated recurrent unit (GRU) are also employed for performance comparison. Moreover, logistic regression, support vector machines, decision trees, and random forest models are also used. A large dataset with 9 classes is used for experiments. Experimental findings indicate that the proposed DCNN achieves the highest receiver operating characteristics (ROC) area under the curve (AUC) score of 99% in the context of YouTube video categorization and 96% accuracy which is better than existing approaches. The proposed approach can be used to help YouTube users suggest relevant videos and sort them by video category. metadata Raza, Ali and Younas, Faizan and Siddiqui, Hafeez Ur Rehman and Rustam, Furqan and Gracia Villar, Mónica and Silva Alvarado, Eduardo René and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, monica.gracia@uneatlantico.es, eduardo.silva@funiber.org, UNSPECIFIED (2024) An improved deep convolutional neural network-based YouTube video classification using textual features. Heliyon, 10 (16). e35812. ISSN 24058440

Article Subjects > Psychology Europe University of Atlantic > Research > Articles and books Cerrado Inglés Introduction Aggressive behaviour on the road is still one of the most studied constructs within human factor due to its strong relationship with crash-related events. Objective The aim of the current research was to analyse the relationship among vital stress, emotion dysregulation, and aggressive behaviour in this specific context. Method A sample composed of 410 Spanish drivers (62.8% female, Mage = 36.12, SDage = 12.99) taken from the general population was tested. Results The results showed positive and significant bivariate correlations among almost all of the variables. The multiple mediation model showed a partial mediation effect of emotion dysregulation, with a significant effect on the whole model, and more specifically, on both the lack of control and life interference. Conclusion The relevance of developing clinical interventions to improve emotion regulation abilities in aggressive drivers is discussed. metadata Herrero-Fernández, David and Parada-Fernández, Pamela and Rodríguez-Arcos, Irene and Brito Ballester, Julién and Rodríguez Velasco, Carmen Lilí mail david.herrero@uneatlantico.es, pamela.parada@uneatlantico.es, UNSPECIFIED, julien.brito@uneatlantico.es, carmen.rodriguez@uneatlantico.es (2024) The mediation effect of emotion dysregulation in the relationship between stress and aggression on the road. European Review of Applied Psychology, 74 (4). p. 100980. ISSN 11629088

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Abierto Inglés Red raspberries are gaining attention more and more for their nutritional and bioactive components, with potential health effects such as antitumor properties. This review aims to describe the antioxidant activities of red raspberries, emphasizing the role of anthocyanins and ellagitannins as primary contributors among red raspberry polyphenols; it also outlined the connection between red raspberries and their role in inhibiting cancer cell growth by regulating oxidative stress. Numerous studies suggest that red raspberries are able to block cancer cell progression by inhibiting proliferation, migration, and autophagy, as well as regulating the cell cycle, angiogenesis, and DNA damage repair. This review sheds light to the growing evidence supporting antioxidants as a crucial link between fruit consumption and cancer prevention. metadata Qi, Zexiu and Yang, Bei and Giampieri, Francesca and Cianciosi, Danila and Alvarez-Suarez, José Miguel and Elexpuru Zabaleta, Maria and Quiles, José L. and Forbes-Hernandez, Tamara Y. and Zhang, Di and Bai, Weibin and Tian, Lingmin and Mezzetti, Bruno and Battino, Maurizio and Armas Diaz, Yasmany mail UNSPECIFIED, UNSPECIFIED, francesca.giampieri@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, maria.elexpuru@uneatlantico.es, jose.quiles@uneatlantico.es, tamara.forbes@unini.edu.mx, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, maurizio.battino@uneatlantico.es, UNSPECIFIED (2024) The preventive and inhibitory effects of red raspberries on cancer. Journal of Berry Research, 14 (1). pp. 61-71. ISSN 18785093

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés Air-writing is a widely used technique for writing arbitrary characters or numbers in the air. In this study, a data collection technique was developed to collect hand motion data for Bengali air-writing, and a motion sensor-based data set was prepared. The feature set as then utilized to determine the most effective machine learning (ML) model among the existing well-known supervised machine learning models to classify Bengali characters from air-written data. Our results showed that medium Gaussian SVM had the highest accuracy (96.5%) in the classification of Bengali character from air writing data. In addition, the proposed system achieved over 81% accuracy in real-time classification. The comparison with other studies showed that the existing supervised ML models predicted the created data set more accurately than many other models that have been suggested for other languages. metadata Kader, Mohammed Abdul and Ullah, Muhammad Ahsan and Islam, Md Saiful and Ferriol Sánchez, Fermín and Samad, Md Abdus and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, fermin.ferriol@unini.edu.mx, UNSPECIFIED, UNSPECIFIED (2024) A real-time air-writing model to recognize Bengali characters. AIMS Mathematics, 9 (3). pp. 6668-6698. ISSN 2473-6988

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books Abierto Inglés In recent years, the Internet of Things (IoT) has become one of the most familiar names creating a benchmark and scaling new heights. IoT an indeed future of the communication that has transformed the objects (things) of the real world into smarter devices. With the advent of IoT technology, this decade is witnessing a transformation from traditional agriculture approaches to the most advanced ones. Limited research has been carried out in this direction. Thus, herein we present various technological aspects involved in IoT-based cultivation. The role and the key components of smart farming using IoT were examined, with a focus on network technologies, including layers, protocols, topologies, network architecture, etc. We also delve into the integration of relevant technologies such as cloud computing, big data analytics, and the integration of IoT-based cultivation. We explored various security issues in modern IoT cultivation and also emphasized the importance of safeguarding sensitive agricultural data. Additionally, a comprehensive list of applications based on sensors and mobile devices is provided, offering refined solutions for greenhouse management. The principles and regulations established by different countries for IoT-based cultivation systems are presented, demonstrating the global recognition of these technologies. Furthermore, a selection of successful use cases and real-world scenarios and applications were presented. Finally, the open research challenges and solutions in modern IoT-based cultivation were discussed. metadata ur Rehman, Attique and Lu, Songfeng and Ashraf, Muhammad Awais and Iqbal, Muhammad Shahid and Nawabi, Awais khan and Amin, Farhan and Abbasi, Rashid and Torre, Isabel de la and Gracia Villar, Santos and Dzul López, Luis Alonso and Heyat, Md. Belal Bin mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, santos.gracia@uneatlantico.es, luis.dzul@uneatlantico.es, UNSPECIFIED (2024) The role of Internet of Things (IoT) technology in modern cultivation for the implementation of greenhouses. PeerJ Computer Science, 10. e2309. ISSN 2376-5992

Article Subjects > Psychology Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production Cerrado Inglés Introduction: Road crashes are still one of the main causes of death around the world. Risky behavior has been proposed as one of the foremost predictors, with the theoretical framework of aberrant behavior emerging as a predominant approach for its examination. Sensation seeking has been pointed out as one of the main personality predictors of aberrant behavior. The current research aimed to investigate the moderated-moderation effect of both risk perception and self-esteem in the relationship between sensation seeking and aberrant behavior. Method: Two studies were conducted. The first study aimed to analyze the psychometric properties of the Spanish version of the Risk Perception Scale (RPS), a 10-item self-report to assess risk perception. A sample composed of 471 Spanish drivers (319 female, Mage = 29.75) completed the RPS. In the second study, a different sample of 236 Spanish drivers (129 female, Mage = 38.49) completed a set of self-reports aiming both to analyze the concurrent and divergent validity of the RPS, and to test the main moderated-moderation hypothesis. Results: With respect to the first study, the confirmatory factor analysis (CFA) supported a 7-item version which fitted in a single reliable factor (α = .74). Regarding the second study, the results supported both the concurrent and divergent validity of the RPS. Likewise, it was verified the moderated-moderation effect in the case of ordinary violations (R2 = .34), aggressive violations (R2 = .20), and lapses (R2 = .12). Conclusions: The RPS is a useful self-report to assess subjective risk perception in Spanish drivers. Both self-esteem and risk perception affect the relationship between sensation seeking and aberrant driving behavior. Practical implications: Intervention programs aiming to reduce aberrant driving behavior should be focused on reducing sensation seeking tendencies while simultaneously enhancing both risk perception skills and self-esteem. metadata Herrero-Fernández, David and Bogdan-Ganea, Smaranda R. and Setién-Suero, Esther and Martín Ayala, Juan Luis mail david.herrero@uneatlantico.es, UNSPECIFIED, esther.setien@uneatlantico.es, juan.martin@uneatlantico.es (2024) The role of subjective risk perception and self-esteem in the relationship between sensation seeking and aberrant behaviors on the road: A moderated-moderation model. Journal of Safety Research, 90. pp. 31-42. ISSN 00224375

2023

Article Subjects > Biomedicine
Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Pregnancy-associated anemia is a significant health issue that poses negative consequences for both the mother and the developing fetus. This study explores the triggering factors of anemia among pregnant females in India, utilizing data from the Demographic and Health Survey 2019–21. Chi-squared and gamma tests were conducted to find out the relationship between anemia and various socioeconomic and sociodemographic elements. Furthermore, ordinal logistic regression and multinomial logistic regression were used to gain deeper insight into the factors that affect anemia among pregnant women in India. According to these findings, anemia affects about 50% of pregnant women in India. Anemia is significantly associated with various factors such as geographical location, level of education, and wealth index. The results of our study indicate that enhancing education and socioeconomic status may serve as viable approaches for mitigating the prevalence of anemia disease developed in pregnant females in India. Employing both Ordinal and Multinominal logistic regression provides a more comprehensive understanding of the risk factors associated with anemia, enabling the development of targeted interventions to prevent and manage this health condition. This paper aims to enhance the efficacy of anemia prevention and management strategies for pregnant women in India by offering an in-depth understanding of the causative factors of anemia. metadata Talin, Iffat Ara and Abid, Mahmudul Hasan and Samad, Md Abdus and Dominguez Azpíroz, Irma and de la Torre Diez, Isabel and Ashraf, Imran and Nahid, Abdullah-Al mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, irma.dominguez@unini.edu.mx, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2023) Exploring factors influencing the severity of pregnancy anemia in India: a study using proportional odds model. Scientific Reports, 13 (1). ISSN 2045-2322

Article Subjects > Biomedicine Europe University of Atlantic > Research > Articles and books Abierto Inglés Background The exposure of breast cancer to extremely low frequency magnetic fields (ELF-MFs) results in various biological responses. Some studies have suggested a possible cancer-enhancing effect, while others showed a possible therapeutic role. This study investigated the effects of in vitro exposure to 50 Hz ELF-MF for up to 24 h on the viability and cellular response of MDA-MB-231 and MCF-7 breast cancer cell lines and MCF-10A breast cell line. Methods and results The breast cell lines were exposed to 50 Hz ELF-MF at flux densities of 0.1 mT and 1.0 mT and were examined 96 h after the beginning of ELF-MF exposure. The duration of 50 Hz ELF-MF exposure influenced the cell viability and proliferation of both the tumor and nontumorigenic breast cell lines. In particular, short-term exposure (4–8 h, 0.1 mT and 1.0 mT) led to an increase in viability in breast cancer cells, while long and high exposure (24 h, 1.0 mT) led to a decrease in viability and proliferation in all cell lines. Cancer and normal breast cells exhibited different responses to ELF-MF. Mitochondrial membrane potential and reactive oxygen species (ROS) production were altered after ELF-MF exposure, suggesting that the mitochondria are a probable target of ELF-MF in breast cells. Conclusions The viability of breast cells in vitro is influenced by ELF-MF exposure at magnetic flux densities compatible with the limits for the general population and for workplace exposures. The effects are apparent after 96 h and are related to the ELF-MF exposure time. metadata Elexpuru Zabaleta, Maria and Lazzarini, Raffaella and Tartaglione, Maria Fiorella and Piva, Francesco and Ciarapica, Veronica and Marinelli Busilacchi, Elena and Poloni, Antonella and Valentino, Matteo and Santarelli, Lory and Bracci, Massimo mail maria.elexpuru@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2023) A 50 Hz magnetic field influences the viability of breast cancer cells 96 h after exposure. Molecular Biology Reports. ISSN 0301-4851

Article Subjects > Biomedicine
Subjects > Psychology Europe University of Atlantic > Research > Articles and books Abierto Inglés Background The arrival of new disease-modifying treatments for Alzheimer’s disease (AD) requires the identification of subjects at risk in a simple, inexpensive, and non-invasive way. With tools allowing an adequate screening, it would be possible to optimize the use of these treatments. Plasma markers of AD are very promising, but it is necessary to prove that alterations in their levels are related to alterations in gold standard markers such as cerebrospinal fluid or PET imaging. With this research, we want to evaluate the performance of plasma Aβ40, Aβ42, and p-tau181 to detect the pathological changes in CSF using the automated Lumipulse platform. Methods Both plasma and CSF Aβ40, Aβ42, and p-tau181 have been evaluated in a group of 208 cognitively unimpaired subjects with a 30.3% of ApoE4 carriers. We have correlated plasma and CSF values of each biomarker. Then, we have also assessed the differences in plasma marker values according to amyloid status (A − / +), AD status (considering AD + subjects to those A + plus Tau +), and ATN group defined by CSF. Finally, ROC curves have been performed, and the area under the curve has been measured using amyloid status and AD status as an outcome and different combinations of plasma markers as predictors. Results Aβ42, amyloid ratio, p-tau181, and p-tau181/Aβ42 ratio correlated significantly between plasma and CSF. For these markers, the levels were significantly different in the A + / − , AD + / − , and ATN groups. Amyloid ratio predicts amyloid and AD pathology in CSF with an AUC of 0.89. Conclusions Plasma biomarkers of AD using the automated Lumipulse platform show good diagnostic performance in detecting Alzheimer’s pathology in cognitively unimpaired subjects. metadata Martínez-Dubarbie, Francisco and Guerra-Ruiz, Armando and López-García, Sara and Lage, Carmen and Fernández-Matarrubia, Marta and Infante, Jon and Pozueta-Cantudo, Ana and García-Martínez, María and Corrales Pardo, Andrea and Bravo, María and López-Hoyos, Marcos and Irure-Ventura, Juan and Sánchez-Juan, Pascual and García-Unzueta, María Teresa and Rodríguez-Rodríguez, Eloy mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, andrea.corrales@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2023) Accuracy of plasma Aβ40, Aβ42, and p-tau181 to detect CSF Alzheimer’s pathological changes in cognitively unimpaired subjects using the Lumipulse automated platform. Alzheimer's Research & Therapy, 15 (1). ISSN 1758-9193

Article Subjects > Physical Education and Sport Europe University of Atlantic > Research > Articles and books Abierto Español La población mundial envejece de forma progresiva, necesitando conocer las necesidades de las personas mayores para mejorar sus niveles de calidad de vida, en especial, a través del ejercicio físico. Actualmente, se desconocen los niveles reales de ejercicio físico en esta población, así como los niveles de calidad de vida y dependencia en muchas regiones mundiales. Por ello, el objetivo principal fue analizar los niveles de práctica de actividad física del adulto mayor, así como la asociación del ejercicio en su calidad de vida. Para ello, 344 adultos mayores de la Ciudad Autónoma de Buenos Aires (Argentina) respondieron a un cuestionario ad-hoc elaborado por un Comité de expertos y basados en herramientas validadas sobre ejercicio físico, dependencia y calidad de vida. Los principales hallazgos fueron que un 34.6% de la población no realiza actividad física semanalmente, gran parte de la población mostró tener alto nivel de independencia y se encontró asociación positiva entre las personas más activas y los mayores niveles de calidad de vida. Según estos resultados, se deben diseñar y aplicar nuevas estrategias de ejercicio físico comunitario para aumentar los niveles de calidad de vida e independencia incrementando el volumen y frecuencia de ejercicio físico en personas mayores, especialmente realizado de forma colectiva. metadata Vázquez, Luciano Ángel and Patón, Rubén Navarro and Álvarez, Oliver Ramos and Mecías-Calvo, Marcos and Lago-Fuentes, Carlos mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, marcos.mecias@uneatlantico.es, carlos.lago@uneatlantico.es (2023) Actividad física y calidad de vida de adultos mayores en Argentina: un estudio transversal (Physical activity and quality of life in Argentinian older adults: a cross-sectional study). Retos, 48. pp. 86-93. ISSN 1579-1726

Article Subjects > Social Sciences Europe University of Atlantic > Research > Articles and books Abierto Español Los cuentos se ambientan en un trasfondo cristiano con el fin de provocar cierta catarsis a través de los contextos que plantean: por un lado, una pequeña niña enferma que se halla postrada en la cama y, por otro, una madre que llora la pérdida prematura de su joven hija.A través de estos cuentos, Stifter retrata diferentes actitudes propias de la naturaleza humana ante las dificultades terrenales. En «La Misericordia» se puede identificar la reacción infantil de una niña, agobiada por haber pecado y recelosa de Dios y de su virtud del perdón; asimismo, en «Muerte de una joven», se manifiesta el desgarro de una madre por la pérdida de un ser querido y la falta de esperanza en la vida eterna, consecuencia de la obnubilación tras haberse dejado dominar por el dolor.Igualmente, la actitud de Dios se evidencia en ambos cuentos por medio de sus actos: en el primero, se demuestra cómo Dios escucha y cuida de todos, además del hecho de que, para Él, la persona vale por encima de todo, ya que perdona a la niña sus pecados y la sana de su enfermedad. Del mismo modo, en el segundo cuento, Dios explica a través del ángel la necesidad de tener esperanza en la vida eterna, pues se lleva a cada alma en el momento en el que la encuentra más madura y la bendice con la vida eterna, libre de los castigos y sufrimientos propios del mundo terrenal. Por tanto, en el cuento se concibe la muerte como un acto de misericordia de Dios, pues «después de morir, recibe en su alma inmortal su retribución eterna». (Catecismo de la Iglesia Católica, art. 12: 1021). Por último, cabe destacar que, mediante el retrato de dichas actitudes, Stifter describe el mundo ideal en el que muestra cuáles serían las actitudes esperadas ante estas situaciones y lo contrasta con su vida personal llena de frustración ya que, como se señaló anteriormente él, a diferencia de los cuentos, no tuvo un final feliz. metadata Quijano-Peña, Paula mail paula.quijano@uneatlantico.es (2023) Adalbert STIFTER, «La misericordia» y «Muerte de una joven». Hermēneus. Revista de traducción e interpretación (24). pp. 633-641. ISSN 2530-609X

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Adaptive equalization is crucial in mitigating distortions and compensating for frequency response variations in communication systems. It aims to enhance signal quality by adjusting the characteristics of the received signal. Particle swarm optimization (PSO) algorithms have shown promise in optimizing the tap weights of the equalizer. However, there is a need to enhance the optimization capabilities of PSO further to improve the equalization performance. This paper provides a comprehensive study of the issues and challenges of adaptive filtering by comparing different variants of PSO and analyzing the performance by combining PSO with other optimization algorithms to achieve better convergence, accuracy, and adaptability. Traditional PSO algorithms often suffer from high computational complexity and slow convergence rates, limiting their effectiveness in solving complex optimization problems. To address these limitations, this paper proposes a set of techniques aimed at reducing the complexity and accelerating the convergence of PSO. metadata Khan, Arooj and Shafi, Imran and Khawaja, Sajid Gul and de la Torre Díez, Isabel and López Flores, Miguel Ángel and Castanedo Galán, Juan and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, miguelangel.lopez@uneatlantico.es, juan.castanedo@uneatlantico.es, UNSPECIFIED (2023) Adaptive Filtering: Issues, Challenges, and Best-Fit Solutions Using Particle Swarm Optimization Variants. Sensors, 23 (18). p. 7710. ISSN 1424-8220

Article Subjects > Social Sciences
Subjects > Teaching Europe University of Atlantic > Research > Articles and books Abierto Inglés English as a Foreign Language (EFL) has become the course that most universities have decided to include in their curricula due to the necessity of acquiring English for their future careers in the globalized world we are living nowadays. In order to expand the knowledge of students, at the Universidad Europea del Atlántico – a private university based in Cantabria, Spain – three sessions of English for Specific Purposes (ESP) have been included in the subjects of EFL as part of the compulsory curricula of the different degrees offered. The aim of the present study was to analyze the degree of usefulness and appropriateness of the designed ESP sessions for the degrees in Sports Sciences and Psychology – which are mixed in the English classroom – through the design of a rubric that could check their validity for both the level of English and the level of knowledge in these specific topics for these students in their second academic year at university. The main conclusion was that the degree of relevance, utility and usefulness of the ESP materials taught depends on the teacher, his/her degree of implication, knowledge, and strategies he/she uses when creating these materials. metadata Lourido Badía, Inés mail ines.lourido@uneatlantico.es (2023) Analysis of english for specific purposes materials: sports sciences and psychology ESP materials in the ELF classroom. Journal of Teaching English for Specific and Academic Purposes. pp. 777-792. ISSN 2334-9182

Article Subjects > Engineering
Subjects > Comunication Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Chatbots are AI-powered programs designed to replicate human conversation. They are capable of performing a wide range of tasks, including answering questions, offering directions, controlling smart home thermostats, and playing music, among other functions. ChatGPT is a popular AI-based chatbot that generates meaningful responses to queries, aiding people in learning. While some individuals support ChatGPT, others view it as a disruptive tool in the field of education. Discussions about this tool can be found across different social media platforms. Analyzing the sentiment of such social media data, which comprises people’s opinions, is crucial for assessing public sentiment regarding the success and shortcomings of such tools. This study performs a sentiment analysis and topic modeling on ChatGPT-based tweets. ChatGPT-based tweets are the author’s extracted tweets from Twitter using ChatGPT hashtags, where users share their reviews and opinions about ChatGPT, providing a reference to the thoughts expressed by users in their tweets. The Latent Dirichlet Allocation (LDA) approach is employed to identify the most frequently discussed topics in relation to ChatGPT tweets. For the sentiment analysis, a deep transformer-based Bidirectional Encoder Representations from Transformers (BERT) model with three dense layers of neural networks is proposed. Additionally, machine and deep learning models with fine-tuned parameters are utilized for a comparative analysis. Experimental results demonstrate the superior performance of the proposed BERT model, achieving an accuracy of 96.49%. metadata R, Sudheesh and Mujahid, Muhammad and Rustam, Furqan and Shafique, Rahman and Chunduri, Venkata and Gracia Villar, Mónica and Brito Ballester, Julién and Diez, Isabel de la Torre and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, monica.gracia@uneatlantico.es, julien.brito@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2023) Analyzing Sentiments Regarding ChatGPT Using Novel BERT: A Machine Learning Approach. Information, 14 (9). p. 474. ISSN 2078-2489

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Cerrado Inglés Diets enriched in plant-based foods are associated with the maintenance of a good well-being and with the prevention of many non-communicable diseases. The health effects of fruits and vegetables consumption are mainly due to the presence of micronutrients, including vitamins and minerals, and polyphenols, plant secondary metabolites. One of the most important classes of phenolic compounds are anthocyanins, that confer the typical purple-red color to many foods, such as berries, peaches, plums, red onions, purple corn, eggplants, as well as purple carrots, sweet potatoes and red cabbages, among others. This commentary aims to briefly highlight the progress made by science in the last years, focusing on some unexpected aspects related with anthocyanins, such as their bioavailability, their health effects and their relationship with gut microbiota metadata Giampieri, Francesca and Cianciosi, Danila and Alvarez-Suarez, José M. and Quiles, José L. and Forbes-Hernández, Tamara Y. and Navarro-Hortal, María D. and Machì, Michele and Pali-Casanova, Ramón and Martínez Espinosa, Julio César and Chen, Xiumin and Zhang, Di and Bai, Weibin and Lingmin, Tian and Mezzetti, Bruno and Battino, Maurizio and Diaz, Yasmany Armas mail francesca.giampieri@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, jose.quiles@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, ramon.pali@unini.edu.mx, ulio.martinez@unini.edu.mx, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, maurizio.battino@uneatlantico.es, UNSPECIFIED (2023) Anthocyanins: what do we know until now? Journal of Berry Research. pp. 1-6. ISSN 18785093

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Abierto Inglés Antimicrobial resistance is a global concern with significant public health implications. We investigated the role of fresh vegetables and their cultivation environments as reservoirs for antimicrobial-resistant Enterobacter cloacae complex (ECC) strains. The study focused on AmpC-producing ECC isolates and their resistance to colistin, a last resort antibiotic. AmpC-producing ECC isolates were detected and confirmed in 10.2% of the 235 samples examined, with no significant difference (p > 0.05) in prevalence between farm and street market samples. Further analysis of 24 AmpC-ECC isolates revealed that 16.7% exhibited resistance to colistin. A colistin-resistant E. kobei strain (AG07E) was detected in irrigation water from a vegetable farm for the first time in Spain. This strain carried the mcr-9.1 gene, demonstrating transferability. It was included in ST56 which is predominantly reported in clinical E. kobei harbouring the mcr-9 gene. Additionally, we identified a multidrug-resistant E. kobei strain (ZA03E) from carrot samples, exhibiting colistin resistance and potential human pathogenicity. This strain belonged to ST125 which has clonal relationships with strains in ST56. Our findings emphasise the importance of monitoring and addressing antimicrobial-resistant ECC strains in fresh vegetables and their production environments, particularly the water, to mitigate potential risks to public health from a One Health perspective. metadata Pintor-Cora, Alberto and Alegría, Ángel and Ramos Vivas, Jose and García-López, María-Luisa and Santos, Jesús A. and Rodríguez-Calleja, Jose M. mail UNSPECIFIED, UNSPECIFIED, jose.ramos@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2023) Antimicrobial-resistant Enterobacter cloacae complex strains isolated from fresh vegetables intended for raw consumption and their farm environments in the Northwest of Spain. LWT, 188. p. 115382. ISSN 00236438

Article Subjects > Biomedicine
Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés In the last decade, artificial intelligence (AI) and AI-mediated technologies have undergone rapid evolution in healthcare and medicine, from apps to computer software able to analyze medical images, robotic surgery and advanced data storage system. The main aim of the present commentary is to briefly describe the evolution of AI and its applications in healthcare, particularly in nutrition and clinical biochemistry. Indeed, AI is revealing itself to be an important tool in clinical nutrition by using telematic means to self-monitor various health metrics, including blood glucose levels, body weight, heart rate, fat percentage, blood pressure, activity tracking and calorie intake trackers. In particular, the application of the most common digital technologies used in the field of nutrition as well as the employment of AI in the management of diabetes and obesity, two of the most common nutrition-related pathologies worldwide, will be presented. metadata Salinari, Alessia and Machì, Michele and Armas Diaz, Yasmany and Cianciosi, Danila and Qi, Zexiu and Yang, Bei and Ferreiro Cotorruelo, Maria Soledad and Gracia Villar, Santos and Dzul López, Luis Alonso and Battino, Maurizio and Giampieri, Francesca mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, santos.gracia@uneatlantico.es, luis.dzul@uneatlantico.es, maurizio.battino@uneatlantico.es, francesca.giampieri@uneatlantico.es (2023) The Application of Digital Technologies and Artificial Intelligence in Healthcare: An Overview on Nutrition Assessment. Diseases, 11 (3). p. 97. ISSN 2079-9721

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Chronic obstructive pulmonary disease (COPD) is a severe and chronic ailment that is currently ranked as the third most common cause of mortality across the globe. COPD patients often experience debilitating symptoms such as chronic coughing, shortness of breath, and fatigue. Sadly, the disease frequently goes undiagnosed until it is too late, leaving patients without the care they desperately need. So, COPD detection at an early stage is crucial to prevent further damage to the lungs and improve quality of life. Traditional COPD detection methods often rely on physical examinations and tests such as spirometry, chest radiography, blood gas tests, and genetic tests. However, these methods may not always be accurate or accessible. One of the key vital signs for detecting COPD is the patient’s respiration rate. However, it is crucial to consider a patient’s medical and demographic characteristics simultaneously for better detection results. To address this issue, this study aims to detect COPD patients using artificial intelligence techniques. To achieve this goal, a novel framework is proposed that utilizes ultra-wideband (UWB) radar-based temporal and spectral features to build machine learning and deep learning models. This new set of temporal and spectral features is extracted from respiration data collected non-invasively from 1.5 m distance using UWB radar. Different machine learning and deep learning models are trained and tested on the collected dataset. The findings are promising, with a high accuracy score of 100% for COPD detection. This means that the proposed framework could potentially save lives by identifying COPD patients at an early stage. The k-fold cross-validation technique and performance comparison with the state-of-the-art studies are applied to validate its performance, ensuring that the results are robust and reliable. The high accuracy score achieved in the study implies that the proposed framework has the potential for the efficient detection of COPD at an early stage. metadata Siddiqui, Hafeez-Ur-Rehman and Raza, Ali and Saleem, Adil Ali and Rustam, Furqan and Díez, Isabel de la Torre and Gavilanes Aray, Daniel and Lipari, Vivian and Ashraf, Imran and Dudley, Sandra mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, daniel.gavilanes@uneatlantico.es, vivian.lipari@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2023) An Approach to Detect Chronic Obstructive Pulmonary Disease Using UWB Radar-Based Temporal and Spectral Features. Diagnostics, 13 (6). p. 1096. ISSN 2075-4418

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Cerrado Inglés Wine is a highly complex mixture of components with different chemical natures. These components largely define wine’s appearance, aroma, taste, and mouthfeel properties. Among them, aroma is among the most important indicators of wine’s sensory characteristics. The essence of winemaking ecosystem is the process of metabolic activities of diverse microbes including yeasts, lactic acid bacteria, and molds, which result in wines with complicated and diversified aromas. A better understanding of how these microbes affect wine’s aroma is a crucial step to producing premium quality wine. This study illustrates existing knowledge on the diversity and classification of wine aroma compounds and their microbial origin. Their contributions to wine characteristics are discussed, as well. Furthermore, we review the relationship between these microbes and wine aroma characteristics. This review broadens the discussion of wine aroma compounds to include more modern microbiological concepts, and it provides relevant background and suggests new directions for future research. metadata Liu, Shuxun and Lou, Ying and Li, Yixian and Zhao, Yan and Laaksonen, Oskar and Li, Ping and Zhang, Jiaojiao and Battino, Maurizio and Yang, Baoru and Gu, Qing mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, maurizio.battino@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2023) Aroma characteristics of volatile compounds brought by variations in microbes in winemaking. Food Chemistry, 420. p. 136075. ISSN 03088146

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
University of La Romana > Research > Scientific Production Abierto Inglés Behavioral economics and artificial intelligence (AI) have been two rapidly growing fields of research over the past few years. While behavioral economics aims to combine concepts from psychology, sociology, and neuroscience with classical economic thoughts to understand human decision-making processes in the complex economic environment, AI on the other hand, focuses on creating intelligent machines that can mimic human cognitive abilities such as learning, problem-solving, decision-making, and language understanding. The intersection of these two fields has led to thrilling research theories and practical applications. This study provides a bibliometric analysis of the literature on AI and behavioral economics to gain insight into research trends in this field. We conducted this bibliometric analysis using the Web of Science database on articles published between 2012 and 2022 that were related to AI and behavioral economics. VOSviewer and Bibliometrix R package were utilized to identify influential authors, journals, institutions, and countries in the field. Network analysis was also performed to identify the main research themes and their interrelationships. The analysis revealed that the number of publications on AI and behavioral economics has been increasing steadily over the past decade. We found that most studies focused on customer and consumer behavior, including topics such as decision-making under uncertainty, neuroeconomics, and behavioral game theory, combined mainly with machine learning and deep learning techniques. We also identified several emerging themes, including the use of AI in nudging and prospect theory in behavioral finance, as well as undeveloped themes such as AI-driven behavioral macroeconomics. The findings suggests that there is a need for more interdisciplinary collaboration between researchers in behavioral economics and AI. We also suggest that future research on AI and behavioral economics further consider the ethical implications of using AI and behavioral insights in decision-making. This study can serve as a valuable resource for researchers interested in AI and behavioral economics. metadata Aoujil, Zakaria and Hanine, Mohamed and Soriano Flores, Emmanuel and Samad, Md Abdu and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, emmanuel.soriano@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2023) Artificial Intelligence and Behavioral Economics: A Bibliographic Analysis of Research Field. IEEE Access. p. 1. ISSN 2169-3536 (In Press)

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés The precise prediction of power estimates of wind–solar renewable energy sources becomes challenging due to their intermittent nature and difference in intensity between day and night. Machine-learning algorithms are non-linear mapping functions to approximate any given function from known input–output pairs and can be used for this purpose. This paper presents an artificial neural network (ANN)-based method to predict hybrid wind–solar resources and estimate power generation by correlating wind speed and solar radiation for real-time data. The proposed ANN allows optimization of the hybrid system’s operation by efficient wind and solar energy production estimation for a given set of weather conditions. The proposed model uses temperature, humidity, air pressure, solar radiation, optimum angle, and target values of known wind speeds, solar radiation, and optimum angle. A normalization function to narrow the error distribution and an iterative method with the Levenberg–Marquardt training function is used to reduce error. The experimental results show the effectiveness of the proposed approach against the existing wind, solar, or wind–solar estimation methods. It is envisaged that such an intelligent yet simplified method for predicting wind speed, solar radiation, and optimum angle, and designing wind–solar hybrid systems can improve the accuracy and efficiency of renewable energy generation. metadata Shafi, Imran and Khan, Harris and Farooq, Muhammad Siddique and Diez, Isabel de la Torre and Miró Vera, Yini Airet and Castanedo Galán, Juan and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, yini.miro@uneatlantico.es, juan.castanedo@uneatlantico.es, UNSPECIFIED (2023) An Artificial Neural Network-Based Approach for Real-Time Hybrid Wind–Solar Resource Assessment and Power Estimation. Energies, 16 (10). p. 4171. ISSN 1996-1073

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Cerrado Inglés Asparagus species is recognized as a perennial herb with several valuable functional ingredients, and has been widely used as medicine and food since ancient times. Among its main chemical constituents, saponins play a vital role in the health benefits and biological activities including anti-cancer, antioxidant, immunomodulatory, anti-microbial, anti-inflammatory, and hypoglycemic. This review summarizes the preparation methods, structure and classification, biological functions, as well as the food and non-food applications of asparagus saponins, with a special emphasis on its anti-cancer effects in vitro and in vivo. Further, the main challenges and limitations of the current research trends in asparagus saponins are highlighted after a detailed analysis of the recent research information. This review bridges the gap between bioactive components and human health and aids current research on functional and health-promoting foods and medicinal application of Asparagus saponins. metadata Zhang, Fan and Chen, Shengxiong and Zhang, Jianguo and Thakur, Kiran and Battino, Maurizio and Cao, Hui and Farag, Mohamed A. and Xiao, Jianbo and Wei, Zhaojun mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, maurizio.battino@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2023) Asparagus saponins: effective natural beneficial ingredient in functional foods, from preparation to applications. Critical Reviews in Food Science and Nutrition. pp. 1-19. ISSN 1040-8398

Article Subjects > Biomedicine
Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Abierto Inglés Metabolic syndrome, obesity and diabetes mellitus are the most common metabolic disorders (MDs) in the world, characterized by abnormalities in body's metabolic processes. The typical diagnosis of MDs is usually executed by monitoring the levels of specific biochemical markers, but diagnostic imaging may provide valuable complementary information in MDs, offering advantages in diagnosis, target organ monitoring, follow-up, and development of new therapeutic approaches. The aim of this review is to summarize and discuss the studies published in the literature about the connection between images deriving from the diagnostic techniques and the key biochemical markers in the main MDs, in order to gain a comprehensive view of the different disorders. metadata Cianciosi, Danila and Diaz, Yasmany Armas and Grosso, Giuseppe and Quiles, José L. and Giampieri, Francesca and Battino, Maurizio mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, jose.quiles@uneatlantico.es, francesca.giampieri@uneatlantico.es, maurizio.battino@uneatlantico.es (2023) Association between diagnostic imaging and biochemical markers: a possible tool for monitoring metabolic disorders. Current Opinion in Food Science. p. 101109. ISSN 22147993

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Project-based organizations need to procure different commodities, and the failure/success of a project depends heavily on procurement management. Companies must refine and develop methods to simplify and optimize the procurement process in a highly competitive environment. This paper presents a methodology to help managers of project-based organizations analyze procurement processes to determine the optimal framework for simultaneously addressing multiple objectives. These goals include minimizing the time between the generation and required approval for a purchase, identifying unnamed activities, and allocating the budget efficiently. In this paper, we apply process mining algorithms to a dataset consisting of event logs on Oracle Financials-based enterprise resource planning (ERP) procurement processes in ERP systems and demonstrate interesting results leading to project procurement intelligence (PPI). The provided log data is the real-life data consisting of 180,462 events referring to seven activities within 43,101 cases. The logged procurement processes are filtered and analyzed using the open-source process mining frameworks PrOM and Disco. As a result of the process mining activities, a simulation of the discovered process model derived from the event log of the entire procurement process is presented, and the most frequent potential behaviors are identified. This analysis and extraction of frequent processes from corporate event logs help organizations understand, adapt, and redesign procurement operations and, most importantly, make them more efficient and of higher quality. This study shows that after the successful formulation of guiding principles, data refinement, and process structure optimization, the case study results are considered significant by the organization’s management. metadata Butt, Naveed Anwer and Mahmood, Zafar and Sana, Muhammad Usman and Díez, Isabel de la Torre and Castanedo Galán, Juan and Brie, Santiago and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, juan.castanedo@uneatlantico.es, santiago.brie@uneatlantico.es, UNSPECIFIED (2023) Behavioral and Performance Analysis of a Real-Time Case Study Event Log: A Process Mining Approach. Applied Sciences, 13 (7). p. 4145. ISSN 2076-3417

Article Subjects > Physical Education and Sport Europe University of Atlantic > Research > Articles and books Abierto Inglés, Español El objetivo del estudio fue analizar los beneficios que el ejercicio físico produce en mujeres diagnosticadas de cáncer de seno invasivo y se encuentran entre las fases I a IIIA, recibiendo tratamiento de quimioterapia, radioterapia o ambos simultáneamente. Las bases de datos de PubMed y Google Académico fueron consultadas hasta abril de 2022 arrojando un total de 29.410 resultados. Tras aplicar los criterios de exclusión fijados, el número de artículos seleccionados que aportaban datos relevantes para el desarrollo del estudio se redujeron a siete. Los autores demostraron que practicar ejercicio aeróbico durante un periodo de entre doce y dieciséis semanas a razón de dos días semanales, en sesiones inferiores a la hora de duración y en las que se realicen ejercicios a intensidades entre el 60%-80% de la FCmáx generaba adaptaciones beneficiosas. De igual manera, practicar entrenamiento de fuerza a intensidades entre el 60%-80% de la 1RM, generó mejoras en el estado de salud, los parámetros psicológicos y disminuyó los síntomas de dolor y la fatiga, entre otros. El estudio concluyó que la práctica de ejercicio físico en estas pacientes, incluyendo las modalidades de entrenamiento aeróbico o de fuerza de manera supervisada y personalizada, resultaba beneficioso, totalmente seguro y generaba beneficios tales como: la disminución de la sensación de fatiga, el refuerzo de la musculatura o la contribución a la adherencia de actividad física diaria, lo que resultó en una mejora en su calidad de vida. metadata Lago-Fuentes, Carlos and Pulgar, Susana and Sánchez Calderón, Raúl mail carlos.lago@uneatlantico.es, susana.pulgar@uneatlantico.es, UNSPECIFIED (2023) Beneficios del ejercicio físico en mujeres diagnosticadas de cáncer de seno invasivo. Una revisión sistemática. MLS Sport Research, 3 (2). ISSN 2792-7156

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Cerrado Inglés Betalains are water-soluble, nitrogen-containing vacuolar pigment and can be divided into two subclasses: the yellow – orange betaxanthins and the red – violet betacyanin. These pigments can be found mainly in Latin America, but also in some parts of Asia, Africa, Australia and in the Mediterranean area. In this work an overview related with the status of research about betalains extracted from Opuntia spp and the enforces made to evaluate their positive incidence in the human body is provided. Several studies enhance their anticancer, anti-inflammatory and antioxidant properties. They also exhibit antimicrobial and antidiabetic effect. Taking into account these properties, betalains seem to be a promising natural alternative as a colorant to replace the synthetic ones in the food additive industry. In addition, the use of Opuntia spp fruits as possible colorant sources in the Food Industry, may contribute positively to the sustainable development in semi-arid regions. metadata Armas Diaz, Yasmany and Qi, Zexiu and Yang, Bei and Martínez López, Nohora Milena and Briones Urbano, Mercedes and Cianciosi, Danila mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, nohora.martinez@uneatlantico.es, mercedes.briones@uneatlantico.es, UNSPECIFIED (2023) Betalains: The main bioactive compounds of Opuntia spp and their possible health benefits in the Mediterranean diet. Mediterranean Journal of Nutrition and Metabolism, 16 (3). pp. 181-190. ISSN 1973798X

Article Subjects > Biomedicine Europe University of Atlantic > Research > Articles and books Abierto Inglés Tagetes erecta is an edible flower deeply rooted in traditional Mexican culture. It holds a central role in the most popular and iconic Mexican celebration, “the Day of the Dead”. Furthermore, it is currently receiving interest as a potential therapeutic agent, motivated mainly by its polyphenol content. The present study aims to evaluate the biological activity of an extract synthesized from the petals of the edible flower T. erecta. This extract showed significant antioxidant scores measured by the most common in vitro methodologies (FRAP, ABTS, and DPPH), with values of 1475.3 μM trolox/g extr, 1950.3 μM trolox/g extr, and 977.7 μM trolox/g extr, respectively. In addition, up to 36 individual polyphenols were identified by chromatography. Regarding the biomedical aspects of the petal extract, it exhibited antitumoral activity against ovarian carcinoma cells evaluated by the MTS assay, revealing a lower value of IC50 compared to other flower extracts. For example, the extract from T. erecta reported an IC50 value half as low as an extract from Rosa × hybrida and six times lower than another extract from Tulbaghia violacea. This antitumoral effect of T. erecta arises from the induction of the apoptotic process; thus, incubating ovarian carcinoma cells with the petal extract increased the rate of apoptotic cells measured by flow cytometry. Moreover, the extract also demonstrated efficacy as a therapeutic agent against tauopathy, a feature of Alzheimer’s disease (AD) in the Caenorhabditis elegans experimental model. Treating worms with the experimental extract prevented disfunction in several motility parameters such as wavelength and swimming speed. Furthermore, the T. erecta petal extract prevented the release of Reactive Oxygen Species (ROS), which are associated with the progression of AD. Thus, treatment with the extract resulted in an approximate 20% reduction in ROS production. These findings suggest that these petals could serve as a suitable source of polyphenols for biomedical applications. metadata Rivas-García, Lorenzo and Crespo-Antolín, Lara and Forbes-Hernández, Tamara Y. and Romero-Márquez, Jose M. and Navarro-Hortal, María D. and Arredondo, Miguel and Llopis, Juan and Quiles, José L. and Sánchez-González, Cristina mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, jose.quiles@uneatlantico.es, UNSPECIFIED (2023) Bioactive Properties of Tagetes erecta Edible Flowers: Polyphenol and Antioxidant Characterization and Therapeutic Activity against Ovarian Tumoral Cells and Caenorhabditis elegans Tauopathy. International Journal of Molecular Sciences, 25 (1). p. 280. ISSN 1422-0067

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Internet of Things (IoT) has made significant strides in energy management systems recently. Due to the continually increasing cost of energy, supply–demand disparities, and rising carbon footprints, the need for smart homes for monitoring, managing, and conserving energy has increased. In IoT-based systems, device data are delivered to the network edge before being stored in the fog or cloud for further transactions. This raises worries about the data’s security, privacy, and veracity. It is vital to monitor who accesses and updates this information to protect IoT end-users linked to IoT devices. Smart meters are installed in smart homes and are susceptible to numerous cyber attacks. Access to IoT devices and related data must be secured to prevent misuse and protect IoT users’ privacy. The purpose of this research was to design a blockchain-based edge computing method for securing the smart home system, in conjunction with machine learning techniques, in order to construct a secure smart home system with energy usage prediction and user profiling. The research proposes a blockchain-based smart home system that can continuously monitor IoT-enabled smart home appliances such as smart microwaves, dishwashers, furnaces, and refrigerators, among others. An approach based on machine learning was utilized to train the auto-regressive integrated moving average (ARIMA) model for energy usage prediction, which is provided in the user’s wallet, to estimate energy consumption and maintain user profiles. The model was tested using the moving average statistical model, the ARIMA model, and the deep-learning-based long short-term memory (LSTM) model on a dataset of smart-home-based energy usage under changing weather conditions. The findings of the analysis reveal that the LSTM model accurately forecasts the energy usage of smart homes. metadata Iqbal, Faiza and Altaf, Ayesha and Waris, Zeest and Gavilanes Aray, Daniel and López Flores, Miguel Ángel and Díez, Isabel de la Torre and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, daniel.gavilanes@uneatlantico.es, miguelangel.lopez@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2023) Blockchain-Modeled Edge-Computing-Based Smart Home Monitoring System with Energy Usage Prediction. Sensors, 23 (11). p. 5263. ISSN 1424-8220

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Breast cancer is prevalent in women and the second leading cause of death. Conventional breast cancer detection methods require several laboratory tests and medical experts. Automated breast cancer detection is thus very important for timely treatment. This study explores the influence of various feature selection technique to increase the performance of machine learning methods for breast cancer detection. Experimental results shows that use of appropriate features tend to show highly accurate prediction metadata Shafique, Rahman and Rustam, Furqan and Choi, Gyu Sang and Díez, Isabel de la Torre and Mahmood, Arif and Lipari, Vivian and Rodríguez Velasco, Carmen Lilí and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, vivian.lipari@uneatlantico.es, carmen.rodriguez@uneatlantico.es, UNSPECIFIED (2023) Breast Cancer Prediction Using Fine Needle Aspiration Features and Upsampling with Supervised Machine Learning. Cancers, 15 (3). p. 681. ISSN 2072-6694

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Universidad Internacional do Cuanza > Research > Scientific Production Cerrado Inglés Agriculture is an important sector that plays an essential role in the economic development of a country. Each year farmers face numerous challenges in producing good quality crops. One of the major reasons behind the failure of the harvest is the use of unscientific agricultural practices. Moreover, every year enormous crop loss is encountered either by pests, specific diseases, or natural disasters. It raises a strong concern to employ sustainable advanced technologies to address agriculture-related issues. In this paper, a sustainable real-time crop disease detection and prevention system, called CROPCARE is proposed. The system integrates mobile vision, Internet of Things (IoT), and Google Cloud services for sustainable growth of crops. The primary function of the proposed intelligent system is to detect crop diseases through the CROPCARE -mobile application. It uses Super-Resolution Convolution Network (SRCNN) and the pretrained model MobileNet-V2 to generate a decision model trained over various diseases. To maintain sustainability, the mobile app is integrated with IoT sensors and Google Cloud services. The proposed system also provides recommendations that help farmers know about current soil conditions, weather conditions, disease prevention methods, etc. It supports both Hindi and English dictionaries for the convenience of the farmers. The proposed approach is validated by using the PlantVillage dataset. The obtained results confirm the performance strength of the proposed system. metadata Garg, Garima and Gupta, Shivam and Mishra, Preeti and Vidyarthi, Ankit and Singh, Aman and Ali, Asmaa mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es, UNSPECIFIED (2023) CROPCARE: An Intelligent Real-Time Sustainable IoT System for Crop Disease Detection Using Mobile Vision. IEEE Internet of Things Journal. p. 1. ISSN 2372-2541

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés Alpha-linolenic acid (ALA) is a long-chain polyunsaturated essential fatty acid of the Ω3 series found mainly in vegetables, especially in the fatty part of oilseeds, dried fruit, berries, and legumes. It is very popular for its preventive use in several diseases: It seems to reduce the risk of the onset or decrease some phenomena related to inflammation, oxidative stress, and conditions of dysregulation of the immune response. Recent studies have confirmed these unhealthy situations also in patients with severe coronavirus disease 2019 (COVID-19). Different findings (in vitro, in vivo, and clinical ones), summarized and analyzed in this review, have showed an important role of ALA in other various non-COVID physiological and pathological situations against “cytokines storm,” chemokines secretion, oxidative stress, and dysregulation of immune cells that are also involved in the infection of the 2019 novel coronavirus. According to the effects of ALA against all the aforementioned situations (also present in patients with a severe clinical picture of severe acute respiratory syndrome-(CoV-2) infection), there may be the biologic plausibility of a prophylactic effect of this compound against COVID-19 symptoms and fatality. metadata Cianciosi, Danila and Diaz, Yasmany Armas and Gaddi, Antonio Vittorino and Capello, Fabio and Savo, Maria Teresa and Pali-Casanova, Ramón and Martínez Espinosa, Julio César and Pascual Barrera, Alina Eugenia and Navarro‐Hortal, Maria‐Dolores and Tian, Lingmin and Bai, Weibin and Giampieri, Francesca and Battino, Maurizio mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, ramon.pali@unini.edu.mx, ulio.martinez@unini.edu.mx, alina.pascual@unini.edu.mx, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, francesca.giampieri@uneatlantico.es, UNSPECIFIED (2023) Can alpha‐linolenic acid be a modulator of “cytokine storm,” oxidative stress and immune response in SARS‐CoV‐2 infection? Food Frontiers. ISSN 2643-8429

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Cerrado Inglés Manuka honey, which is rich in pinocembrin, quercetin, naringenin, salicylic, p-coumaric, ferulic, syringic and 3,4-dihydroxybenzoic acids, has been shown to have pleiotropic effects against colon cancer cells. In this study, potential chemosensitizing effects of Manuka honey against 5-Fluorouracil were investigated in colonspheres enriched with cancer stem cells (CSCs), which are responsible for chemoresistance. Results showed that 5-Fluorouracil increased when it was combined with Manuka honey by downregulating the gene expression of both ATP-binding cassette sub-family G member 2, an efflux pump and thymidylate synthase, the main target of 5-Fluorouracil which regulates the ex novo DNA synthesis. Manuka honey was associated with decreased self-renewal ability by CSCs, regulating expression of several genes in Wnt/β-catenin, Hedgehog and Notch pathways. This preliminary study opens new areas of research into the effects of natural compounds in combination with pharmaceuticals and, potentially, increase efficacy or reduce adverse effects. metadata Cianciosi, Danila and Armas Diaz, Yasmany and Alvarez-Suarez, José M. and Chen, Xiumin and Zhang, Di and Martínez López, Nohora Milena and Briones Urbano, Mercedes and Quiles, José L. and Amici, Adolfo and Battino, Maurizio and Giampieri, Francesca mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, nohora.martinez@uneatlantico.es, mercedes.briones@uneatlantico.es, jose.quiles@uneatlantico.es, UNSPECIFIED, maurizio.battino@uneatlantico.es, francesca.giampieri@uneatlantico.es (2023) Can the phenolic compounds of Manuka honey chemosensitize colon cancer stem cells? A deep insight into the effect on chemoresistance and self-renewal. Food Chemistry, 427. p. 136684. ISSN 03088146

Article Subjects > Teaching Europe University of Atlantic > Research > Articles and books Abierto Español El propósito de este artículo de investigación fue realizar una clasificación basada en redes neuronales, para pronosticar el nivel de satisfacción de una muestra de egresados, correspondiente a diferentes programas de posgrado del área de salud de una institución educativa latinoamericana bajo una metodología e-learning. Con este fin, se instrumentalizó un modelo en un cuestionario de escala de Likert que, tras ser validado, resultó con una confiabilidad de 0.791. Asimismo, el índice global medio de satisfacción de los egresados fue de 2.66/4, observando una mejor puntuación en el apartado de logística de materiales y en el manejo y soporte técnico del campus virtual, mientras que las puntuaciones más bajas se refirieron a aspectos relacionados con la comunicación extra-centro y las facilidades ofrecidas por la institución para la mejora del contexto económico y social del participante. Finalmente, el algoritmo de clasificación y predicción probabilística de la red neuronal obtuvo una precisión del 96.8%, lo que indicó un excelente grado de ajuste del modelo. La metodología seguida y el rigor en la determinación de la validez y confiabilidad del instrumento, así como el posterior análisis de resultados, refrendado con la revisión de la información documentada, hace presuponer la aplicación del instrumento a otros programas multidisciplinares para la toma de decisiones con garantías en el ámbito educativo. metadata Soriano Flores, Emmanuel and Rodríguez Velasco, Carmen Lilí and Brito Ballester, Julién and Gracia Villar, Mónica and Dominguez Azpíroz, Irma mail emmanuel.soriano@uneatlantico.es, carmen.rodriguez@uneatlantico.es, julien.brito@uneatlantico.es, monica.gracia@uneatlantico.es, irma.dominguez@unini.edu.mx (2023) Clasificación y pronóstico del nivel de satisfacción de egresados de programas de salud en el contexto de una metodología de aprendizaje automático: un análisis de caso orientado a posgrados online de una institución educativa iberoamericana. MLS Educational Research, 7 (2). ISSN 2603-5820

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés UNSPECIFIED metadata Ali, Omer and Abbas, Qamar and Mahmood, Khalid and Bautista Thompson, Ernesto and Arambarri, Jon and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, ernesto.bautista@unini.edu.mx, jon.arambarri@uneatlantico.es, UNSPECIFIED (2023) Competitive Coevolution-Based Improved Phasor Particle Swarm Optimization Algorithm for Solving Continuous Problems. Mathematics, 11 (21). p. 4406. ISSN 2227-7390

Article Subjects > Biomedicine
Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Artificial intelligence has made substantial progress in medicine. Automated dental imaging interpretation is one of the most prolific areas of research using AI. X-ray and infrared imaging systems have enabled dental clinicians to identify dental diseases since the 1950s. However, the manual process of dental disease assessment is tedious and error-prone when diagnosed by inexperienced dentists. Thus, researchers have employed different advanced computer vision techniques, and machine- and deep-learning models for dental disease diagnoses using X-ray and near-infrared imagery. Despite the notable development of AI in dentistry, certain factors affect the performance of the proposed approaches, including limited data availability, imbalanced classes, and lack of transparency and interpretability. Hence, it is of utmost importance for the research community to formulate suitable approaches, considering the existing challenges and leveraging findings from the existing studies. Based on an extensive literature review, this survey provides a brief overview of X-ray and near-infrared imaging systems. Additionally, a comprehensive insight into challenges faced by researchers in the dental domain has been brought forth in this survey. The article further offers an amalgamative assessment of both performances and methods evaluated on public benchmarks and concludes with ethical considerations and future research avenues. metadata Shafi, Imran and Fatima, Anum and Afzal, Hammad and Díez, Isabel de la Torre and Lipari, Vivian and Breñosa, Jose and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, vivian.lipari@uneatlantico.es, josemanuel.brenosa@uneatlantico.es, UNSPECIFIED (2023) A Comprehensive Review of Recent Advances in Artificial Intelligence for Dentistry E-Health. Diagnostics, 13 (13). p. 2196. ISSN 2075-4418

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production Abierto Inglés Renewable energy solutions are appropriate for on-grid and off-grid applications, acting as a supporter for the utility network or rural locations without the need to develop or extend costly and difficult grid infrastructure. As a result, hybrid renewable energy sources have become a popular option for grid-connected or standalone systems. This paper examines hybrid renewable energy power production systems with a focus on energy sustainability, reliability due to irregularities, techno-economic feasibility, and being environmentally friendly. In attaining a reliable, clean, and cost-effective system, sizing optimal hybrid renewable energy sources (HRES) is a crucial challenge. The presenters went further to outline the best sizing approach that can be used in HRES, taking into consideration the key components, parameters, methods, and data. Moreover, the goal functions, constraints from design, system components, optimization software tools, and meta-heuristic algorithm methodologies were highlighted for the available studies in this timely synopsis of the state of the art. Additionally, current issues resulting from scaling HRES were also identified and discussed. The latest trends and advances in planning problems were thoroughly addressed. Finally, this paper provides suggestions for further research into the appropriate component sizing in HRES. metadata Agajie, Takele Ferede and Ali, Ahmed and Fopah-Lele, Armand and Amoussou, Isaac and Khan, Baseem and Rodríguez Velasco, Carmen Lilí and Tanyi, Emmanuel mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, carmen.rodriguez@uneatlantico.es, UNSPECIFIED (2023) A Comprehensive Review on Techno-Economic Analysis and Optimal Sizing of Hybrid Renewable Energy Sources with Energy Storage Systems. Energies, 16 (2). p. 642. ISSN 1996-1073

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés In the field of natural language processing, machine translation is a colossally developing research area that helps humans communicate more effectively by bridging the linguistic gap. In machine translation, normalization and morphological analyses are the first and perhaps the most important modules for information retrieval (IR). To build a morphological analyzer, or to complete the normalization process, it is important to extract the correct root out of different words. Stemming and lemmatization are techniques commonly used to find the correct root words in a language. However, a few studies on IR systems for the Urdu language have shown that lemmatization is more effective than stemming due to infixes found in Urdu words. This paper presents a lemmatization algorithm based on recurrent neural network models for the Urdu language. However, lemmatization techniques for resource-scarce languages such as Urdu are not very common. The proposed model is trained and tested on two datasets, namely, the Urdu Monolingual Corpus (UMC) and the Universal Dependencies Corpus of Urdu (UDU). The datasets are lemmatized with the help of recurrent neural network models. The Word2Vec model and edit trees are used to generate semantic and syntactic embedding. Bidirectional long short-term memory (BiLSTM), bidirectional gated recurrent unit (BiGRU), bidirectional gated recurrent neural network (BiGRNN), and attention-free encoder–decoder (AFED) models are trained under defined hyperparameters. Experimental results show that the attention-free encoder-decoder model achieves an accuracy, precision, recall, and F-score of 0.96, 0.95, 0.95, and 0.95, respectively, and outperforms existing models metadata Hafeez, Rabab and Anwar, Muhammad Waqas and Jamal, Muhammad Hasan and Fatima, Tayyaba and Martínez Espinosa, Julio César and Dzul López, Luis Alonso and Bautista Thompson, Ernesto and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, ulio.martinez@unini.edu.mx, luis.dzul@uneatlantico.es, ernesto.bautista@unini.edu.mx, UNSPECIFIED (2023) Contextual Urdu Lemmatization Using Recurrent Neural Network Models. Mathematics, 11 (2). p. 435. ISSN 2227-7390

Article Subjects > Psychology Europe University of Atlantic > Research > Articles and books Abierto Inglés Several randomised controlled trials (RCT) have demonstrated the superiority of transdiagnostic group cognitive-behavioural therapy (TD-CBT) to treatment as usual (TAU) for emotional disorders in primary care. To date, however, no RCTs have been conducted to compare TD-CBT to another active intervention in this setting. Our aim is to conduct a single-blind RCT to compare group TD-CBT plus TAU to progressive muscle relaxation (PMR) plus TAU in adults (age 18 to 65 years) with a suspected emotional disorder. We expect that TD-CBT + TAU will be more cost-effective than TAU + PMR, and that these gains will be maintained at the 12-month follow-up. Seven therapy sessions (1.5 hours each) will be offered over a 24-week period. The study will be carried out at four primary care centres in Cantabria, Spain. The study will take a societal perspective. Psychological assessments will be made at three time points: baseline, post-treatment, and at 12-months. The following variables will be evaluated: clinical symptoms (anxiety, depression, and/or somatic); functioning; quality of life (QoL); cognitive-emotional factors (rumination, worry, attentional and interpretative biases, emotion regulation and meta-cognitive beliefs); and satisfaction with treatment. Data on health service use, medications, and sick days will be obtained from electronic medical records. Primary outcome measures will include: incremental cost-effectiveness ratios (ICER) and incremental cost-utility ratios (ICURs). Secondary outcome measures will include: clinical symptoms, QoL, functioning, and treatment satisfaction. Bootstrap sampling will be used to assess uncertainty of the results. Secondary moderation and mediation analyses will be conducted. Two questionnaires will be administered at sessions 1, 4, and 7 to assess therapeutic alliance and group satisfaction. If this trial is successful, widespread application of this cost-effective treatment could greatly improve access to psychological treatment for emotional disorders in the context of increasing demand for mental healthcare in primary care. metadata Moreno-Peral, Patricia and González-Blanch, César and Barrio-Martínez, Sara and Priede, Amador and Martínez-Gómez, Sandra and Pérez-García-Abad, Saioa and Miras-Aguilar, María and Ruiz-Gutiérrez, José and Muñoz-Navarro, Roger and Ruiz-Rodríguez, Paloma and Medrano, Leonardo A. and Prieto-Vila, Maider and Carpallo-González, María and Aguilera-Martín, Ángel and Gálvez-Lara, Mario and Cuadrado, Fátima and Moreno, Eliana and García-Torres, Francisco and Venceslá, José F. and Corpas, Jorge and Jurado-González, Francisco J. and Moriana, Juan A. and Cano-Vindel, Antonio mail UNSPECIFIED, cesar.gonzalezblanch@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2023) Cost-effectiveness of transdiagnostic group cognitive behavioural therapy versus group relaxation therapy for emotional disorders in primary care (PsicAP-Costs2): Protocol for a multicentre randomised controlled trial. PLOS ONE, 18 (3). e0283104. ISSN 1932-6203

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Abierto Inglés, Español Las alteraciones metabólicas suponen hoy en día una de las afecciones más padecidas en todo el mundo. Es por ello, que la indagación en el estudio sobre la influencia de la hora de la ingesta en el metabolismo de un nutriente, es de gran importancia para el desarrollo y aplicación de nuevos tratamientos en lo que a estas enfermedades respecta. Mediante esta revisión bibliográfica, a través de la búsqueda bibliográfica profunda en diferentes bases de datos, se han obtenido diversos archivos, documentos, artículos y estudios que han servido para el análisis, desarrollo y ejecución del vigente artículo. La molécula de la glucosa presenta niveles más acentuados en la tarde versus la mañana, debido a la disminución de la actividad de la insulina con el avance del día. La mayoría de los lípidos presentan sus niveles más altos en la mañana, a excepción de los triglicéridos mostrándolos en la tarde. En cuanto a las proteínas se necesita más estudio para su conocimiento en este aspecto. Se requiere de más investigación para poder obtener una conclusión más exacta. Aun así, se puede concluir en que la hora de la ingesta es un factor que afecta en la ritmicidad de los procesos metabólicos, interfiriendo y alterando la actividad y respuesta de los nutrientes. metadata Conde González, Sandra mail UNSPECIFIED (2023) Crononutrición: efecto de la hora de la ingesta en el metabolismo de los nutrientes. MLS Health & Nutrition Research, 1 (2).

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés This paper presents a current- and voltage-driven protection scheme for transmission lines based on a hybrid mix of Stockwell transform (ST) and Hilbert transform (HT). Use of both current and voltage waveforms to detect and categorize faults, improves the reliability of this protection scheme and avoids false tripping. Current and voltage waveforms captured during a period of fault are analyzed using ST to compute a median intermediate fault index (MIFI), a maximum value intermediate fault index (MVFI), and a summation intermediate fault index (SIFI). Current and voltage signals are analyzed via applying HT to compute a Hilbert fault index (HFI). The proposed hybrid current and voltage fault index (HCVFI) is obtained from the MIFI, MVFI, SIFI, and HFI. A threshold magnitude for this hybrid current and voltage fault index (HCVFITH) is set to 500 to identify the faulty phase. The HCVFIT is selected after testing the method for various conditions of different fault locations, different fault impedances, different fault occurrence angles, and reverse flows of power. Fault classification is performed using the number of faulty phases and an index for ground detection (IGD). The ground involved in a fault is detected by comparison of peak IGD magnitude with a threshold for ground detection (THGD). THGD is considered equal to 1000 in this study. The study is carried out using a two-terminal transmission line modeled in MATLAB software. The performance of the proposed technique is better compared to a discrete wavelet transform (DWT)-based technique, a time–frequency approach, and an alienation method. Our algorithm effectively detected an AG fault, observed on a practical transmission line. metadata Tang, Ligang and Mahela, Om Prakash and Khan, Baseem and Miró Vera, Yini Airet mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, yini.miro@uneatlantico.es (2023) Current- and Voltage-Actuated Transmission Line Protection Scheme Using a Hybrid Combination of Signal Processing Techniques. Sustainability, 15 (7). p. 5715. ISSN 2071-1050

Article Subjects > Biomedicine
Subjects > Nutrition Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production Abierto Inglés The genus Aeromonas has received constant attention in different areas, from aquaculture and veterinary medicine to food safety, where more and more frequent isolates are occurring with increased resistance to antibiotics. The present paper studied the interaction of Aeromonas strains isolated from fresh produce and water with different eukaryotic cell types with the aim of better understanding the cytotoxic capacity of these strains. To study host-cell pathogen interactions in Aeromonas, we used HT-29, Vero, J774A.1, and primary mouse embryonic fibroblasts. These interactions were analyzed by confocal microscopy to determine the cytotoxicity of the strains. We also used Galleria mellonella larvae to test their pathogenicity in this experimental model. Our results demonstrated that two strains showed high cytotoxicity in epithelial cells, fibroblasts, and macrophages. Furthermore, these strains showed high virulence using the G. mellonella model. All strains used in this paper generally showed low levels of resistance to the different families of the antibiotics being tested. These results indicated that some strains of Aeromonas present in vegetables and water pose a potential health hazard, displaying very high in vitro and in vivo virulence. This pathogenic potential, and some recent concerning findings on antimicrobial resistance in Aeromonas, encourage further efforts in examining the precise significance of Aeromonas strains isolated from foods for human consumption. metadata Pintor-Cora, Alberto and Tapia Martínez, Olga and Elexpuru Zabaleta, Maria and Ruiz de Alegría, Carlos and Rodríguez-Calleja, Jose M. and Santos, Jesús A. and Ramos Vivas, Jose mail UNSPECIFIED, olga.tapia@uneatlantico.es, maria.elexpuru@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, jose.ramos@uneatlantico.es (2023) Cytotoxicity and Antimicrobial Resistance of Aeromonas Strains Isolated from Fresh Produce and Irrigation Water. Antibiotics, 12 (3). p. 511. ISSN 2079-6382

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Automated dental imaging interpretation is one of the most prolific areas of research using artificial intelligence. X-ray imaging systems have enabled dental clinicians to identify dental diseases. However, the manual process of dental disease assessment is tedious and error-prone when diagnosed by inexperienced dentists. Thus, researchers have employed different advanced computer vision techniques, as well as machine and deep learning models for dental disease diagnoses using X-ray imagery. In this regard, a lightweight Mask-RCNN model is proposed for periapical disease detection. The proposed model is constructed in two parts: a lightweight modified MobileNet-v2 backbone and region-based network (RPN) are proposed for periapical disease localization on a small dataset. To measure the effectiveness of the proposed model, the lightweight Mask-RCNN is evaluated on a custom annotated dataset comprising images of five different types of periapical lesions. The results reveal that the model can detect and localize periapical lesions with an overall accuracy of 94%, a mean average precision of 85%, and a mean insection over a union of 71.0%. The proposed model improves the detection, classification, and localization accuracy significantly using a smaller number of images compared to existing methods and outperforms state-of-the-art approaches metadata Fatima, Anum and Shafi, Imran and Afzal, Hammad and Mahmood, Khawar and Díez, Isabel de la Torre and Lipari, Vivian and Brito Ballester, Julién and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, vivian.lipari@uneatlantico.es, julien.brito@uneatlantico.es, UNSPECIFIED (2023) Deep Learning-Based Multiclass Instance Segmentation for Dental Lesion Detection. Healthcare, 11 (3). p. 347. ISSN 2227-9032

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Monitoring tool conditions and sub-assemblies before final integration is essential to reducing processing failures and improving production quality for manufacturing setups. This research study proposes a real-time deep learning-based framework for identifying faulty components due to malfunctioning at different manufacturing stages in the aerospace industry. It uses a convolutional neural network (CNN) to recognize and classify intermediate abnormal states in a single manufacturing process. The manufacturing process for aircraft factory products comprises different phases; analyzing the components after the integration is labor-intensive and time-consuming, which often puts the company’s stake at high risk. To overcome these challenges, the proposed AI-based system can perform inspection and defect detection and alleviate the probability of components’ needing to be re-manufacturing after being assembled. In addition, it analyses the impact value, i.e., rework delays and costs, of manufacturing processes using a statistical process control tool on real-time data for various manufactured components. Defects are detected and classified using the CNN and teachable machine in the single manufacturing process during the initial stage prior to assembling the components. The results show the significance of the proposed approach in improving operational cost management and reducing rework-induced delays. Ground tests are conducted to calculate the impact value followed by the air tests of the final assembled aircraft. The statistical results indicate a 52.88% and 34.32% reduction in time delays and total cost, respectively. metadata Shafi, Imran and Mazhar, Muhammad Fawad and Fatima, Anum and Álvarez, Roberto Marcelo and Miró Vera, Yini Airet and Martínez Espinosa, Julio César and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, roberto.alvarez@uneatlantico.es, yini.miro@uneatlantico.es, ulio.martinez@unini.edu.mx, UNSPECIFIED (2023) Deep Learning-Based Real Time Defect Detection for Optimization of Aircraft Manufacturing and Control Performance. Drones, 7 (1). p. 31. ISSN 2504-446X

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Cerrado Inglés Given that it provides nourishment for more than half of humanity, rice is regarded as one of the most significant plants in the world in agriculture. The quantity and quality of the product may be impacted by diseases that can damage rice plants which can occasionally cause crop losses ranging from 30 to 60%. This manuscript proposed a Convolutional Neural Network (CNN) and Visual Geometry Group (VGG)19 i.e. CNN-VGG19 model with a transfer learning-based method for the precise identification and classification of rice leaf diseases. This scheme employs a transfer learning technique based on the VGG19 which can identify the brown spot class. The accuracy is 93.0% in the deployment of the dataset of rice leaf disease. The other parameters are sensitivity, specificity, precision and F1-score with 89.9%, 94.7%, 92.4% and 90.5% respectively. The developed technique obtained better results as compared to the existing baseline models. metadata Dogra, Roopali and Rani, Shalli and Singh, Aman and Albahar, Marwan Ali and Pascual Barrera, Alina Eugenia and Alkhayyat, Ahmed mail UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es, UNSPECIFIED, alina.pascual@unini.edu.mx, UNSPECIFIED (2023) Deep learning model for detection of brown spot rice leaf disease with smart agriculture. Computers and Electrical Engineering, 109. p. 108659. ISSN 00457906

Article Subjects > Social Sciences Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés This research aims to gather opinions from experts in the European tourism sector regarding training needs to address severe crises, such as Covid, in Small and Medium-Sized Enterprises (SMEs) across five countries: Spain, Iceland, Ireland, Scotland, and Germany. This study was conducted within the scope of the European TC-NAV project, which is funded by the European Union. The ultimate goal of this project is to develop training solutions for European SMEs Most existing literature on tourism crises primarily examines the impact on destinations as a whole rather than on individual tourism enterprises. Thus, this research is both relevant and timely The methodology employed was qualitative, and data being collected using a 9-question interview guide. This guide underwent validation by experts, achieving a Cronbach's Alpha value of 0.7. In total, 30 individuals were interviewed: 5 civil servants, 9 company directors, 5 university professors, 6 researchers, and 5 entrepreneurs. Some notable findings include the importance of innovation for change, promoting sustainable tourism, fostering informal partnerships among regional companies, the essential role of government support, the benefits of flexible planning and service digitisation, and the ongoing need for training and upskilling. metadata Soriano Flores, Emmanuel and Prola, Thomas and Halldórsdóttir, Íris Hrund Halldórsdóttir and Taylor, Steve mail emmanuel.soriano@uneatlantico.es, thomas.prola@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2023) Diagnosing Training Needs in European Tourism SMEs: The TC-NAV Project for Managing and Overcoming Virulent Crises. Kurdish Studies, 11 (2). pp. 2011-2022. ISSN 2051-4883

Article Subjects > Biomedicine
Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Abierto Inglés The rise of life expectancy in current societies is not accompanied, to date, by a similar increase in healthspan, which represents a great socio-economic problem. It has been suggested that aging can be manipulated and then, the onset of all age-associated chronic disorders can be delayed because these pathologies share age as primary underlying risk factor. One of the most extended ideas is that aging is consequence of the accumulation of molecular damage. According to the oxidative damage theory, antioxidants should slow down aging, extending lifespan and healthspan. The present review analyzes studies evaluating the effect of dietary antioxidants on lifespan of different aging models and discusses the evidence on favor of their antioxidant activity as anti-aging mechanisms. Moreover, possible causes for differences between the reported results are evaluated. metadata Varela-López, Alfonso and Romero-Márquez, José M. and Navarro-Hortal, María D. and Ramirez-Tortosa, César L. and Battino, Maurizio and Forbes-Hernández, Tamara Y. and Quiles, José L. mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, maurizio.battino@uneatlantico.es, UNSPECIFIED, jose.quiles@uneatlantico.es (2023) Dietary antioxidants and lifespan: Relevance of environmental conditions, diet, and genotype of experimental models. Experimental Gerontology, 178. p. 112221. ISSN 05315565

Article Subjects > Physical Education and Sport Europe University of Atlantic > Research > Articles and books Abierto Español El objetivo del presente estudio es comparar el perfil de los estados de ánimo (EA) en jóvenes escolares que practican diferentes deportes extraescolares de manera federada respecto a escolares de Educación Primaria y Secundaria que no están federados. Seleccionándose un total de 329 sujetos (141 deportistas y 188 escolares no practicantes). Los EA se evaluaron mediante el cuestionario Profile of Moods States (POMS). La comparación se realizó en base al deporte practicado y en función de si eran deportistas federados o no federados. Los resultados muestran valores más elevados en la escala del vigor, así como diferencias significativas en las escalas depresión y fatiga entre los deportistas. Además, se observan diferencias entre no federados escolares para la depresión, hostilidad y tensión. Se concluye que los deportistas muestran valores que se asocian con el denominado perfil iceberg. metadata Fernández García, Javier and Cañada, Fernando Calahorro and Luque, Gema Torres mail javier.fernandez@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2023) Diferencia del perfil de los estados de ánimo en jóvenes escolares que practican deporte extraescolar federado vs no federados (Difference in the profile of moods in young schoolchildren who practice federated extracurricular sports vs. schoolchildren). Retos, 47. pp. 738-743. ISSN 1579-1726

Book Section Subjects > Teaching Europe University of Atlantic > Research > Articles and books Abierto Inglés UNSPECIFIED metadata Bazaco Gómez, Carmelo and Quijano-Peña, Paula mail carmelo.bazaco@uneatlantico.es, paula.quijano@uneatlantico.es (2023) Discourse creation: translation technique or spanish film pattern. A case study. In: Nuevas teorías y aproximaciones a estudios sobre lengua, lingüística y traducción. Dykinson, Madrid, pp. 936-947. ISBN 9788411228305

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production Abierto Español Las metodologías para el diseño y gestión de proyectos son cada vez más necesarias y aplicadas con mayor frecuencia en el sector público en Latinoamérica. Continuamente hay actualizaciones y nuevos enfoques en la gestión de proyectos de inversión, por lo que el estudio en las metodologías es relevante a nivel investigativo. El diseño de instrumentos de investigación confiables que sirvan para promover el uso de estas metodologías es importante para asegurar la calidad en el proceso. Por lo que el objetivo de este estudio es diseñar y validar un instrumento que permita recolectar y gestionar sistemáticamente información de proyectos para obtener las variables que permitan definir la metodología apropiada para cada organización, en este estudio se ha tomado como referencia en el sector público la Subsecretaría de Recursos Pesqueros (SRP) en Ecuador. El instrumento, toma como referencia la Norma International Organization for Standardization (ISO) 10006, la Guía de Fundamentos de Gestión de Proyectos, por su nombre en inglés Project Management Body of Knowledge (PMBOK), las Metodologías de Diseño de Proyectos de la Universidad Politécnica de Cataluña (MDP-UPC) y de la Secretaría Nacional de Planificación y Desarrollo (SENPLADES) del Ecuador. Como resultado, se desarrolló una encuesta, a cuyo instrumento se realizó la validación interna y externa en función de parámetros de confiabilidad, contenido y constructo. Se realizó análisis factorial para determinar variables utilizando sistema estadístico SPSS. Finalmente, se cuenta con la validación del instrumento diseñado asegurando que es confiable y cumple con los parámetros necesarios para obtener variables que definan la metodología para elaboración de proyectos en el sector público de Ecuador. metadata Bazurto Roldán, José Antonio and Álvarez, Roberto Marcelo and Miró Vera, Yini Airet and Brie, Santiago mail jose.bazurto@unini.org, roberto.alvarez@uneatlantico.es, yini.miro@uneatlantico.es, santiago.brie@uneatlantico.es (2023) Diseño y validación de un instrumento de investigación para proponer metodología de gestión de proyectos. Revista de Iniciación Científica, 9 (1). ISSN 2412-0464

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés Internet security is a major concern these days due to the increasing demand for information technology (IT)-based platforms and cloud computing. With its expansion, the Internet has been facing various types of attacks. Viruses, denial of service (DoS) attacks, distributed DoS (DDoS) attacks, code injection attacks, and spoofing are the most common types of attacks in the modern era. Due to the expansion of IT, the volume and severity of network attacks have been increasing lately. DoS and DDoS are the most frequently reported network traffic attacks. Traditional solutions such as intrusion detection systems and firewalls cannot detect complex DDoS and DoS attacks. With the integration of artificial intelligence-based machine learning and deep learning methods, several novel approaches have been presented for DoS and DDoS detection. In particular, deep learning models have played a crucial role in detecting DDoS attacks due to their exceptional performance. This study adopts deep learning models including recurrent neural network (RNN), long short-term memory (LSTM), and gradient recurrent unit (GRU) to detect DDoS attacks on the most recent dataset, CICDDoS2019, and a comparative analysis is conducted with the CICIDS2017 dataset. The comparative analysis contributes to the development of a competent and accurate method for detecting DDoS attacks with reduced execution time and complexity. The experimental results demonstrate that models perform equally well on the CICDDoS2019 dataset with an accuracy score of 0.99, but there is a difference in execution time, with GRU showing less execution time than those of RNN and LSTM. metadata Ramzan, Mahrukh and Shoaib, Muhammad and Altaf, Ayesha and Arshad, Shazia and Iqbal, Faiza and Kuc Castilla, Ángel Gabriel and Ashraf, Imran mail UNSPECIFIED (2023) Distributed Denial of Service Attack Detection in Network Traffic Using Deep Learning Algorithm. Sensors, 23 (20). p. 8642. ISSN 1424-8220

Article Subjects > Psychology Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production Cerrado Inglés Aggressive behaviour is a common response in different contexts all around the world. General aggression theories, such as the frustration-aggression theory, try to explain this behaviour in any context. However, situational specificity could play a relevant role in this issue, so proneness to behave aggressively may depend more on the context than on a general root or personality trait. With the aim of shedding light in this field, the current research aimed to analyse the relationship between aggressive behaviour on the road and intimate relationships. A sample composed of 275 participants who had a driving license and lived with an intimate partner completed a set of self-reports regarding aggressive behaviour in both contexts. The results suggested a convergence in the way of expressing anger, except in the case of adaptive aggression. A SEM-based approach indicated that the measured aggressive variables fitted better in two highly correlated factors rather than a single one, suggesting the relevance of the situational specificity in the prediction of aggressive behaviour in both contexts. Practical implications regarding evaluation and intervention for aggression reduction are discussed, as well as the limitations of the current research. metadata Herrero-Fernández, David and Parada-Fernández, Pamela and Rodríguez-Arcos, Irene and Martín Ayala, Juan Luis and Castaño Castaño, Sergio mail david.herrero@uneatlantico.es, pamela.parada@uneatlantico.es, UNSPECIFIED, juan.martin@uneatlantico.es, sergio.castano@uneatlantico.es (2023) Do people drive as they live together? Associations between aggressive behaviour on the road and intimate relationships. Transportation Research Part F: Traffic Psychology and Behaviour, 95. pp. 251-260. ISSN 13698478

Article Subjects > Physical Education and Sport Europe University of Atlantic > Research > Articles and books Cerrado Inglés Morenas-Aguilar, MD, Ruiz-Alias, SA, Blanco, AM, Lago-Fuentes, C, García-Pinillos, F, and Pérez-Castilla, A. Does the menstrual cycle impact the maximal neuromuscular capacities of women? An analysis before and after a graded treadmill test to exhaustion. J Strength Cond Res 37(11): 2185–2191, 2023. This study explored the effect of the menstrual cycle (MC) on the maximal neuromuscular capacities of the lower-body muscles obtained before and after a graded exercise test conducted on a treadmill to exhaustion. Sixteen physically active women were tested at −11 ± 3, −5 ± 3, and 5 ± 3 days from the luteinizing peak for the early follicular, late follicular, and midluteal phases. In each session, the individualized load-velocity (L-V) relationship variables (load-axis intercept [L0], velocity-axis intercept [v0], and area under the L-V relationship line [Aline]) were obtained before and after a graded exercise test conducted on a treadmill to exhaustion using the 2-point method (3 countermovement jumps with a 0.5-kg barbell and 2 back squats against a load linked to a mean velocity of 0.55 m·second−1). At the beginning of each session, no significant differences were reported for L0 (p = 0.726; ES ≤ 0.18), v0 (p = 0.202; ES ≤ 0.37), and Aline (p = 0.429; ES ≤ 0.30) between the phases. The MC phase × time interaction did not reach statistical significance for any L-V relationship variable (p ≥ 0.073). A significant main effect of “time” was observed for L0 (p < 0.001; ES = −0.77) and Aline (p = 0.002; ES = −0.59) but not for v0 (p = 0.487; ES = 0.12). These data suggest that the lower-body maximal neuromuscular capacities obtained before and after a graded treadmill test are not significantly affected by MC, although there is a high variability in the individual response. metadata Morenas-Aguilar, María Dolores and Ruiz-Alias, Santiago A. and Blanco, Aitor Marcos and Lago-Fuentes, Carlos and García-Pinillos, Felipe and Pérez-Castilla, Alejandro mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, carlos.lago@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2023) Does the Menstrual Cycle Impact the Maximal Neuromuscular Capacities of Women? An Analysis Before and After a Graded Treadmill Test to Exhaustion. Journal of Strength and Conditioning Research, 37 (11). pp. 2185-2191. ISSN 1064-8011

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Traffic accidents present significant risks to human life, leading to a high number of fatalities and injuries. According to the World Health Organization’s 2022 worldwide status report on road safety, there were 27,582 deaths linked to traffic-related events, including 4448 fatalities at the collision scenes. Drunk driving is one of the leading causes contributing to the rising count of deadly accidents. Current methods to assess driver alcohol consumption are vulnerable to network risks, such as data corruption, identity theft, and man-in-the-middle attacks. In addition, these systems are subject to security restrictions that have been largely overlooked in earlier research focused on driver information. This study intends to develop a platform that combines the Internet of Things (IoT) with blockchain technology in order to address these concerns and improve the security of user data. In this work, we present a device- and blockchain-based dashboard solution for a centralized police monitoring account. The equipment is responsible for determining the driver’s impairment level by monitoring the driver’s blood alcohol concentration (BAC) and the stability of the vehicle. At predetermined times, integrated blockchain transactions are executed, transmitting data straight to the central police account. This eliminates the need for a central server, ensuring the immutability of data and the existence of blockchain transactions that are independent of any central authority. Our system delivers scalability, compatibility, and faster execution times by adopting this approach. Through comparative research, we have identified a significant increase in the need for security measures in relevant scenarios, highlighting the importance of our suggested model. metadata Farooq, Hamza and Altaf, Ayesha and Iqbal, Faiza and Castanedo Galán, Juan and Gavilanes Aray, Daniel and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, juan.castanedo@uneatlantico.es, daniel.gavilanes@uneatlantico.es, UNSPECIFIED (2023) DrunkChain: Blockchain-Based IoT System for Preventing Drunk Driving-Related Traffic Accidents. Sensors, 23 (12). p. 5388. ISSN 1424-8220

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production Abierto Inglés Ubiquitous data monitoring and processing with minimal latency is one of the crucial challenges in real-time and scalable applications. Internet of Things (IoT), fog computing, edge computing, cloud computing, and the edge of things are the spine of all real-time and scalable applications. Conspicuously, this study proposed a novel framework for a real-time and scalable application that changes dynamically with time. In this study, IoT deployment is recommended for data acquisition. The Pre-Processing of data with local edge and fog nodes is implemented in this study. The threshold-oriented data classification method is deployed to improve the intrusion detection mechanism’s performance. The employment of machine learning-empowered intelligent algorithms in a distributed manner is implemented to enhance the overall response rate of the layered framework. The placement of respondent nodes near the framework’s IoT layer minimizes the network’s latency. For economic evaluation of the proposed framework with minimal efforts, EdgeCloudSim and FogNetSim++ simulation environments are deployed in this study. The experimental results confirm the robustness of the proposed system by its improvised threshold-oriented data classification and intrusion detection approach, improved response rate, and prediction mechanism. Moreover, the proposed layered framework provides a robust solution for real-time and scalable applications that changes dynamically with time. metadata Aldribi, Abdulaziz and Singh, Aman and Breñosa, Jose mail UNSPECIFIED, aman.singh@uneatlantico.es, josemanuel.brenosa@uneatlantico.es (2023) Edge of Things Inspired Robust Intrusion Detection Framework for Scalable and Decentralized Applications. Computer Systems Science and Engineering, 46 (3). pp. 3865-3881. ISSN 0267-6192

Article Subjects > Psychology Europe University of Atlantic > Research > Articles and books Cerrado Inglés Despite the high economic costs associated with emotional disorders, relatively few studies have examined the variation in costs according to whether or not the patient has achieved a reliable recovery or not. The aim of this study was to explore differences in health care costs and productivity losses between primary care patients from a previous RCT—PsicAP— with emotional symptoms who achieved a reliable recovery versus and those who did not after transdiagnostic cognitive-behavioural therapy (TD-CBT) plus treatment as usual (TAU) or TAU alone. Sociodemographic and cost data were obtained for 134 participants treated at five primary care centres in Madrid for the 12-month post-treatment period. Reliable recovery rates were higher in the patients who received TD-CBT+TAU versus TAU alone (66% versus 34%; chi-square= 13.78; df=1; p< .001). Patients who did not achieve reliable recovery incurred in more costs, especially associated with GP consultations (t=3.01; df=132; p=.003), use of emergency departments (t= 2.20; df= 132; p=.030), total health care costs (t=2.01; df=132; p=.040), and sick leaves (t=1.97; df=132; p=.048). These findings underscore the societal importance of achieving a reliable recovery in patients with emotional disorders, and further support the value of adding TD-CBT to TAU in the primary care setting. metadata Barrio-Martínez, Sara and Ruiz-Rodríguez, Paloma and Adrián Medrano, Leonardo and Priede, Amador and Muñoz-Navarro, Roger and Antonio Moriana, Juan and Carpallo-González, María and Prieto-Vila, Maider and Cano-Vindel, Antonio and González-Blanch, César mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, cesar.gonzalezblanch@uneatlantico.es (2023) Effect of reliable recovery on health care costs and productivity losses in emotional disorders. Behavior Therapy. ISSN 00057894

Article Subjects > Engineering
Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Abierto Inglés The present study assessed the responses, in terms of vegetative, productive, qualitative, and nutritional features, of plants and berries of three remontant strawberry cultivars cultivated in soil and irrigated using three irrigation regimes: standard irrigation regime (W100), 20% (W80) less irrigation than the standard irrigation, and 40% (W60) less irrigation than the standard irrigation. The tested plants were “Albion”, “San Andreas”, and “Monterey”, which were cultivated in the east coast area of Marche, Italy. Specifically, the study examined the response of the genotype to irrigation deficit, highlighting the performance of the “Monterey” cultivar, which showed improvement in terms of fruit firmness, folate content, and antioxidant capacity at the W80 irrigation regime without a significant yield reduction. In all the cultivars, when irrigation was reduced by up to 20% of the standard irrigation regime (W100), there were no significant losses of yield or reduction in the fruits’ sensorial quality or antioxidant activity. The results showed that the standard irrigation regime (W100) commonly adopted by the farmers in the Marche area uses more water than necessary. With more accurate water management, it will be possible to save almost 226 m3 of water per hectare per cultivation cycle. metadata Marcellini, Micol and Raffaelli, Davide and Mazzoni, Luca and Pergolotti, Valeria and Balducci, Francesca and Armas Diaz, Yasmany and Mezzetti, Bruno and Capocasa, Franco mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, bruno.mezzetti@uneatlantico.es, UNSPECIFIED (2023) Effects of Different Irrigation Rates on Remontant Strawberry Cultivars Grown in Soil. Horticulturae, 9 (9). p. 1026. ISSN 2311-7524

Article Subjects > Biomedicine Europe University of Atlantic > Research > Articles and books Abierto Inglés Extremely low-frequency electromagnetic fields (ELF-MF) can modify the cell viability and regulatory processes of some cell types, including breast cancer cells. Breast cancer is a multifactorial disease where a role for ELF-MF cannot be excluded. ELF-MF may influence the biological properties of breast cells through molecular mechanisms and signaling pathways that are still unclear. This study analyzed the changes in the cell viability, cellular morphology, oxidative stress response and alteration of proteomic profile in breast cancer cells (MDA-MB-231) exposed to ELF-MF (50 Hz, 1 mT for 4 h). Non-tumorigenic human breast cells (MCF-10A) were used as control cells. Exposed MDA-MB-231 breast cancer cells increased their viability and live cell number and showed a higher density and length of filopodia compared with the unexposed cells. In addition, ELF-MF induced an increase of the mitochondrial ROS levels and an alteration of mitochondrial morphology. Proteomic data analysis showed that ELF-MF altered the expression of 328 proteins in MDA-MB-231 cells and of 242 proteins in MCF-10A cells. Gene Ontology term enrichment analysis demonstrated that in both cell lines ELF-MF exposure up-regulated the genes enriched in “focal adhesion” and “mitochondrion”. The ELF-MF exposure decreased the adhesive properties of MDA-MB-231 cells and increased the migration and invasion cell abilities. At the same time, proteomic analysis, confirmed by Real Time PCR, revealed that transcription factors associated with cellular reprogramming were upregulated in MDA-MB-231 cells and downregulated in MCF-10A cells after ELF-MF exposure. MDA-MB-231 breast cancer cells exposed to 1 mT 50 Hz ELF-MF showed modifications in proteomic profile together with changes in cell viability, cellular morphology, oxidative stress response, adhesion, migration and invasion cell abilities. The main signaling pathways involved were relative to focal adhesion, mitochondrion and cellular reprogramming. metadata Lazzarini, Raffaella and Elexpuru Zabaleta, Maria and Piva, Francesco and Giulietti, Matteo and Fulgenzi, Gianluca and Tartaglione, Maria Fiorella and Zingaretti, Laura and Tagliabracci, Adriano and Valentino, Matteo and Santarelli, Lory and Bracci, Massimo mail UNSPECIFIED, maria.elexpuru@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2023) Effects of extremely low-frequency magnetic fields on human MDA-MB-231 breast cancer cells: proteomic characterization. Ecotoxicology and Environmental Safety, 253. p. 114650. ISSN 01476513

Article Subjects > Teaching Europe University of Atlantic > Research > Articles and books Abierto Español En este artículo se reflexiona sobre la relevancia de la comunicación y competencias orales mediante unas prácticas de aula llevadas a cabo en una clase de español como lengua extranjera en un contexto universitario entre un centro educativo de París y otro de Santander. Mediante la aplicación de estas actividades con el uso de videograbaciones y videollamadas se observaron conductas positivas entre el alumnado, quien puso en práctica una serie de competencias asociadas a la lengua oral. Las actividades únicamente se pusieron en práctica en una única ocasión, aunque una aplicación continuada podría suponer una mejora significativa de competencias orales. metadata Sánchez-Bejerano, Lucía mail lucia.sanchez@uneatlantico.es (2023) El uso de la videograbación y la videollamada para la enseñanza de español como lengua extranjera. Doblele. Revista de lengua y literatura, 9. pp. 174-184. ISSN 2462-3733

Article Subjects > Social Sciences Europe University of Atlantic > Research > Articles and books Abierto Español El presente estudio muestra una investigación realizada en la Universidad Europea del Atlántico, Santander, en la que se perseguía realizar una propuesta de mejora para el trabajo de la comprensión lectora en la asignatura de Inglés Instrumental II. Esta propuesta tenía que recoger estrategias de lectura y el uso de organizadores visuales textuales. Para ello se analizaron 11 lecturas del libro de texto Macmillan Hub B1+/B2- y se complementaron las actividades con un entrenamiento en estrategias de lectura y el uso de un organizador textual específico según la necesidad del texto. Para la aplicación se valoró por un lado el desempeño previo y posterior en comprensión lectora y el desempeño de 5 actividades de evaluación continua en comprensión de textos. La muestra del estudio, n=57, fueron estudiantes de segundo curso del Grado en Ciencias de la Actividad Física y el Deporte y el Grado en Psicología, divididos en Grupo Experimental, GE, (n=31) y Grupo de Control, GC, (n=26). Los resultados mostraron diferencias significativas de hasta 2.8 puntos sobre 10 en el caso del GE respecto al de control. Por tanto, se considera que el uso de estrategias de lectura combinadas con el entrenamiento en el uso de organizadores visuales del texto contribuye a una mejora en la comprensión lectora. metadata Sánchez-Bejerano, Lucía and Pérez Fernández, Lucila María and Griffin, Kim Lori mail lucia.sanchez@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2023) El uso de organizadores textuales para comprensión lectora en lengua meta, una experiencia durante la pandemia por la Covid-19. Educatio Siglo XXI, 41 (1). pp. 55-84.

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Abierto Inglés Vanadium (V) is a trace mineral whose biological activity, role as a micronutrient, and pharmacotherapeutic applications remain unknown. Over the last years, interest in V has increased due to its potential use as an antidiabetic agent mediated by its ability to improve glycemic metabolism. However, some toxicological aspects limit its potential therapeutic application. The present study aims to evaluate the effect of the co-treatment with copper (Cu) and bis(maltolato)oxovanadium(IV) (BMOV) as a possible strategy to reduce the toxicity of BMOV. Treating hepatic cells with BMOV reduced cell viability under the present conditions, but cell viability was corrected when cells were co-incubated with BMOV and Cu. Additionally, the effect of these two minerals on nuclear and mitochondrial DNA was evaluated. Co-treatment with both metals reduced the nuclear damage caused by BMOV. Moreover, treatment with these two metals simultaneously tended to reduce the ND1/ND4 deletion of the mitochondrial DNA produced with the treatment using BMOV alone. In conclusion, these results showed that combining Cu and V could effectively reduce the toxicity associated with V and enhance its potential therapeutic applications. metadata Rivas-García, Lorenzo and López-Varela, Alfonso and Quiles, José L. and Montes-Bayón, María and Aranda, Pilar and Llopis, Juan and Sánchez-González, Cristina mail UNSPECIFIED, UNSPECIFIED, jose.quiles@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2023) Elucidating the Therapeutic Potential of Bis(Maltolato)OxoVanadium(IV): The Protective Role of Copper in Cellular Metabolism. International Journal of Molecular Sciences, 24 (11). p. 9367. ISSN 1422-0067

Article Subjects > Teaching
Subjects > Comunication
Subjects > Psychology Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Communication professionals are experiencing a growing level of exposure to traumatic events as a result of their involvement in the coverage of various tragedies, including accidents, climatic disasters, rights violations, and acts of terrorism. However, it is worth noting that journalism and communication university courses often lack comprehensive instruction on effectively managing emotional challenges, anxiety, trauma, self-care, and the prevention of vicarious trauma. The objective of this study is to assess the inclusion of emotional management within the curricula of Journalism and Communication programmes offered by two universities in Catalonia, namely the University of Barcelona and the Autonomous University of Barcelona. In order to accomplish this objective, a series of semi-structured interviews were carried out with a total of twelve (12) professors who specialise in the fields of Journalism and Communication. Additionally, a thorough analysis was conducted on a set of 97 study plan guides. The results indicate that none of the participants in the interviews possess knowledge regarding any existing training programmes focused on emotional management. Furthermore, they unanimously agree on the importance of implementing such courses. The study plans did not include any subjects that were specifically dedicated to the topic of emotional management. This study presents a set of strategies aimed at creating a cross-disciplinary teaching-learning model that offers a comprehensive educational experience for students. This entails integrating precise subject matter on the previously mentioned topics, fostering critical contemplation and discourse regarding emotions within the educational setting, and advocating for ethical and sound professional behaviours. metadata Escudero, Carolina and Prola, Thomas and Fraga, Leticia and Soriano Flores, Emmanuel mail UNSPECIFIED, thomas.prola@uneatlantico.es, leticia.fraga@uneatlantico.es, emmanuel.soriano@uneatlantico.es (2023) Emotional Management in Journalism and Communication Studies. Social Space, 23 (2). pp. 507-534.

Article Subjects > Social Sciences Europe University of Atlantic > Research > Articles and books Abierto Inglés The capital structure has been extensively analysed in the empirical literature. Despite of the great contribution of the technological industry to the global economy, little research has been conducted regarding corporate finance of ICT firms. Moreover, the previous literature barely considers the effect of macroeconomic variables on financial decisions, focusing much more on internal determinants, such as cash flow, firm’s size or growth opportunities. The objective of this work is to reduce this gap by disentangling the reasons behind the financial decisions of technological firms. The sample included 1,510 public ICT firms from 23 countries over the period 2004 – 2019 (17,342 observations). The variables used in this study are obtained from S&P Capital IQ, World Development Indicators, Main Science and Technology Indicators from OECD, and FMI dataset. The two-step system generalized method of moments (GMM) was used as methodology. Consistent with the extant literature, more profitable and liquid ICT firms and those with an increased non-debt tax shields are less leveraged. However, the companies which present higher risk, measured as volatility of EBIT, increase their use of debt financing. Contrary to the findings of many other studies, the analysis of a firm’s size and tangible assets shows non-conclusive results. Regarding macroeconomic determinants, only economic growth and foreign direct investment inflows were found to generate a positive effect on financial decisions of ICT firms. The findings of this work can be used to design and develop policies, measures, and facilitate mechanisms for optimal management of the financing decisions of ICT firms. metadata Alexeeva-Alexeev, Inna mail inna.alexeeva@uneatlantico.es (2023) The Empirical Study of the Impact of Firm-and Country-level Factors on Debt Financing Decisions of ICT Firms. Scientific Annals of Economics and Business, 70. pp. 55-84.

Article Subjects > Biomedicine
Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés A novel approach is presented in this study for the classification of lower limb disorders, with a specific emphasis on the knee, hip, and ankle. The research employs gait analysis and the extraction of PoseNet features from video data in order to effectively identify and categorize these disorders. The PoseNet algorithm facilitates the extraction of key body joint movements and positions from videos in a non-invasive and user-friendly manner, thereby offering a comprehensive representation of lower limb movements. The features that are extracted are subsequently standardized and employed as inputs for a range of machine learning algorithms, such as Random Forest, Extra Tree Classifier, Multilayer Perceptron, Artificial Neural Networks, and Convolutional Neural Networks. The models undergo training and testing processes using a dataset consisting of 174 real patients and normal individuals collected at the Tehsil Headquarter Hospital Sadiq Abad. The evaluation of their performance is conducted through the utilization of K-fold cross-validation. The findings exhibit a notable level of accuracy and precision in the classification of various lower limb disorders. Notably, the Artificial Neural Networks model achieves the highest accuracy rate of 98.84%. The proposed methodology exhibits potential in enhancing the diagnosis and treatment planning of lower limb disorders. It presents a non-invasive and efficient method of analyzing gait patterns and identifying particular conditions. metadata Siddiqui, Hafeez Ur Rehman and Saleem, Adil Ali and Raza, Muhammad Amjad and Gracia Villar, Santos and Dzul Lopez, Luis and Diez, Isabel de la Torre and Rustam, Furqan and Dudley, Sandra mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, santos.gracia@uneatlantico.es, luis.dzul@unini.edu.mx, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2023) Empowering Lower Limb Disorder Identification through PoseNet and Artificial Intelligence. Diagnostics, 13 (18). p. 2881. ISSN 2075-4418

Book Section Subjects > Teaching Europe University of Atlantic > Research > Articles and books Abierto Español UNSPECIFIED metadata Alexeeva-Alexeev, Inna and Mazas Pérez-Oleaga, Cristina and Sámano Celorio, María Luisa mail inna.alexeeva@uneatlantico.es, cristina.mazas@uneatlantico.es, marialuisa.samano@uneatlantico.es (2023) Emprendimiento basado en el liderazgo: diagnóstico de las habilidades de liderazgo entre los estudiantes universitarios. In: Nuevas tendencias en gestión e innovación empresarial. Adaptación a los nuevos escenarios globales y domésticos. Conocimiento Contemporáneo . Dykinson, Madrid, pp. 193-218. ISBN 9788411229241

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Cricket has a massive global following and is ranked as the second most popular sport globally, with an estimated 2.5 billion fans. Batting requires quick decisions based on ball speed, trajectory, fielder positions, etc. Recently, computer vision and machine learning techniques have gained attention as potential tools to predict cricket strokes played by batters. This study presents a cutting-edge approach to predicting batsman strokes using computer vision and machine learning. The study analyzes eight strokes: pull, cut, cover drive, straight drive, backfoot punch, on drive, flick, and sweep. The study uses the MediaPipe library to extract features from videos and several machine learning and deep learning algorithms, including random forest (RF), support vector machine, k-nearest neighbors, decision tree, linear regression, and long short-term memory to predict the strokes. The study achieves an outstanding accuracy of 99.77% using the RF algorithm, outperforming the other algorithms used in the study. The k-fold validation of the RF model is 95.0% with a standard deviation of 0.07, highlighting the potential of computer vision and machine learning techniques for predicting batsman strokes in cricket. The study’s results could help improve coaching techniques and enhance batsmen’s performance in cricket, ultimately improving the game’s overall quality. metadata Siddiqui, Hafeez Ur Rehman and Younas, Faizan and Rustam, Furqan and Soriano Flores, Emmanuel and Brito Ballester, Julién and Diez, Isabel de la Torre and Dudley, Sandra and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, emmanuel.soriano@uneatlantico.es, julien.brito@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2023) Enhancing Cricket Performance Analysis with Human Pose Estimation and Machine Learning. Sensors, 23 (15). p. 6839. ISSN 1424-8220

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Classification is a commonly used technique in data mining and is applied in various fields such as sentiment analysis, fraud detection, and fault diagnosis. Multiclass classification, which involves more than two classes, is more complex than binary classification. There are mainly two ways to approach multiclass classification, one is to expand the binary classifier into a multiclass classifier through various strategies and the other is to divide the multiclass classification problem into multiple binary problems (binarization). Two popular approaches for binarization are One vs One (OvO) and One vs All (OvA). It is simpler to aggregate the outputs of all binary classifiers as the number of classifiers decreases. However, it causes an imbalance of positive and negative sample numbers, which affects the classification effect of each binary classifier. In this article, we contribute to the field of ensemble learning and multi-class classification by proposing a new method called Ensemble Partition Sampling (EPS). This article presents a new approach to multiclass classification using an "Ensemble Partition Sampling" method within the "one-vs-all" (OvA) framework. The primary goal of this method is to tackle the problem of data imbalance by incorporating ensemble learning and preprocessing techniques into each binary dataset. The study found that Ensemble Partition Sampling (EPS) is the most effective method for imbalanced and multiclass imbalanced classification, outperforming other methods including OvA, SMOTE, k-means-SMOTE, Bagging-RB, DES-MI, OvO-EASY, and OvO-SMB. The study used CART, Random Forest, and SVM as classifiers, and the results consistently showed that EPS outperformed all other algorithms. The findings suggest that EPS is a highly effective method for improving classification performance in imbalanced and multiclass imbalanced datasets. metadata Jabir, Brahim and Díez, Isabel De la Torre and Bautista Thompson, Ernesto and Ramírez-Vargas, Debora L. and Kuc Castilla, Ángel Gabriel mail UNSPECIFIED (2023) Ensemble Partition Sampling (EPS) for Improved Multi-Class Classification. IEEE Access. p. 1. ISSN 2169-3536

Article Subjects > Physical Education and Sport Europe University of Atlantic > Research > Articles and books Abierto Español El objetivo principal de esta revisión fue evaluar la eficacia de un programa de ejercicio físico (EF) en pacientes con cáncer de mama (CM) y sus efectos sobre la calidad de vida, la fatiga percibida, la depresión y la condición física. Se realizó una búsqueda sistemática, basada en las directrices PRISMA, utilizando tres bases de datos diferentes: Medline, Pubmed y Google Académico. Los criterios de inclusión fueron; adultos (>18 años), pacientes con CM durante la terapia adyuvante, intervenciones de EF con el efecto de influir en la calidad de vida, la fatiga y la condición física. Así mismo, los criterios de exclusión fueron; realizar la intervención de EF después de la enfermedad, artículos publicados antes del 2010 o en idiomas que no fueran inglés, castellano y/o francés. Los resultados incluyeron cinco artículos para la revisión y todos los estudios mostraron mejoras en la calidad de vida, la condición física y/o en la composición corporal, además de en la percepción de fatiga percibida y de la depresión. Se puede llegar a la conclusión de que las incorporaciones complementarias de programas de EF sistematizado durante la terapia adyuvante a mujeres con CM ofrece tanto mejoras en la calidad de vida, como en la condición física y una disminución de la fatiga y la depresión, sea cual sea el tipo de programa de entrenamiento (resistencia, fuerza o combinación de ambas). metadata Santiago García, Marta Victoria and Charda Colina, Andrea and Pulgar, Susana mail UNSPECIFIED, UNSPECIFIED, susana.pulgar@uneatlantico.es (2023) Evaluación de los efectos del ejercicio físico en pacientes con cáncer de mama: una revisión sistemática. MLS Sport Research, 3 (1). ISSN 2792-7156

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Abierto Inglés Biofilms are associated with infections that are resistant to conventional therapies, contributing to the antimicrobial resistance crisis. The need for alternative approaches against biofilms is well-known. Although natural products like stingless bee honeys (tribe: Meliponini) constitute an alternative treatment, much is still unknown. Our main goal was to evaluate the antibiofilm activity of stingless bee honey samples against multidrug-resistant (MDR) pathogens through biomass assays, fluorescence (cell count and viability), and scanning electron (structural composition) microscopy. We analyzed thirty-five honey samples at 15% (v/v) produced by ten different stingless bee species (Cephalotrigona sp., Melipona sp., M. cramptoni, M. fuscopilosa, M. grandis, M. indecisa, M. mimetica, M. nigrifacies, Scaptotrigona problanca, and Tetragonisca angustula) from five provinces of Ecuador (Tungurahua, Pastaza, El Oro, Los Ríos, and Loja) against 24-h biofilms of Staphylococcus aureus, Klebsiella pneumoniae, Candida albicans, and Candida tropicalis. The present honey set belonged to our previous study, where the samples were collected in 2018–2019 and their physicochemical parameters, chemical composition, mineral elements, and minimal inhibitory concentration (MIC) were screened. However, the polyphenolic profile and their antibiofilm activity on susceptible and multidrug-resistant pathogens were still unknown. According to polyphenolic profile of the honey samples, significant differences were observed according to their geographical origin in terms of the qualitative profiles. The five best honey samples (OR24.1, LR34, LO40, LO48, and LO53) belonging to S. problanca, Melipona sp., and M. indecisa were selected for further analysis due to their high biomass reduction values, identification of the stingless bee specimens, and previously reported physicochemical parameters. This subset of honey samples showed a range of 63–80% biofilm inhibition through biomass assays. Fluorescence microscopy (FM) analysis evidenced statistical log reduction in the cell count of honey-treated samples in all pathogens (P <0.05), except for S. aureus ATCC 25923. Concerning cell viability, C. tropicalis, K. pneumoniae ATCC 33495, and K. pneumoniae KPC significantly decreased (P <0.01) by 21.67, 25.69, and 45.62%, respectively. Finally, scanning electron microscopy (SEM) analysis demonstrated structural biofilm disruption through cell morphological parameters (such as area, size, and form). In relation to their polyphenolic profile, medioresinol was only found in the honey of Loja, while scopoletin, kaempferol, and quercetin were only identified in honey of Los Rios, and dihydrocaffeic and dihydroxyphenylacetic acids were only detected in honey of El Oro. All the five honey samples showed dihydrocoumaroylhexose, luteolin, and kaempferol rutinoside. To the authors’ best knowledge, this is the first study to analyze stingless bees honey-treated biofilms of susceptible and/or MDR strains of S. aureus, K. pneumoniae, and Candida species. metadata Cabezas-Mera, Fausto Sebastián and Atiencia-Carrera, María Belén and Villacrés-Granda, Irina and Proaño, Adrian Alexander and Debut, Alexis and Vizuete, Karla and Herrero-Bayo, Lorena and Gonzalez-Paramás, Ana M. and Giampieri, Francesca and Abreu-Naranjo, Reinier and Tejera, Eduardo and Álvarez-Suarez, José M. and Machado, António mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, francesca.giampieri@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2023) Evaluation of the polyphenolic profile of native Ecuadorian stingless bee honeys (Tribe: Meliponini) and their antibiofilm activity on susceptible and multidrug-resistant pathogens: An exploratory analysis. Current Research in Food Science, 7. p. 100543. ISSN 26659271

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books Abierto Inglés In this research, a neural network (NN) model for metal price forecasting based on an evolutionary approach is proposed. Both the neural network model’s network parameters and network architecture are selected automatically. The time series metal price data set is used to construct a novel fitness function that takes into account both error minimizations and the reproduction of the auto-correlation function. Calculating the average entropy values allowed the selection of the input parameter count for the neural network model. Gold price forecasting was performed using the proposed methodology. The optimal hidden node number, learning rate, and momentum are 9, 0.026, and 0.76, respectively, according to the evolutionary-based NN model. The proposed strategy is shown to reduce estimation error while also reproducing the auto-correlation function of the time series data set by the validation results with gold price data. The performance of the proposed method is better than other current methods, according to a comparison study. metadata Joshi, Devendra and Chithaluru, Premkumar and Anand, Divya and Hajjej, Fahima and Aggarwal, Kapil and Yélamos Torres, Vanessa and Bautista Thompson, Ernesto mail UNSPECIFIED, UNSPECIFIED, divya.anand@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, vanessa.yelamos@funiber.org, ernesto.bautista@unini.edu.mx (2023) An Evolutionary Technique for Building Neural Network Models for Predicting Metal Prices. Mathematics, 11 (7). p. 1675. ISSN 2227-7390

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Abierto Inglés The leaves of the olive tree (Olea europaea L.) are one of the major solid wastes from the olive industry. Globally, the European Union is the largest producer of olive by-products, with Spain, Italy, Greece, and Portugal accounting for almost the entire production. Many questions remain to be solved concerning olive leaves (OL), including those related to possible differences in composition and/or biological activities depending on their geographical origin. In the present work, OL from Spain, Italy, Greece, and Portugal have been characterized according to their phytochemical profile, antioxidant capacity, neuroprotective activity, and anti-inflammatory effects. The Spanish and Italian OL samples presented the highest antioxidant and neuroprotective activities, while the Greek OL showed the lowest. These results were strongly associated with the content of oleoside methyl ester and p-hydroxybenzoic acid for the Spanish and Italian samples, respectively, whereas the content of decarboxymethyl elenolic acid dialdehyde form (hydrated) was negatively associated with the mentioned biological activities of the Greek samples. No country-related effect was observed in the anti-inflammatory activity of OL. Comprehensively, this work could provide a useful tool for manufacturers and R&D departments in making environmentally friendly decisions on how OL can be used to generate nutraceutical products based on the composition and origin of this by-product. metadata Romero-Márquez, Jose M. and Navarro-Hortal, María D. and Forbes-Hernández, Tamara Y. and Varela-López, Alfonso and Puentes, Juan G. and Pino-García, Raquel Del and Sánchez-González, Cristina and Elío Pascual, Iñaki and Battino, Maurizio and García, Roberto and Sánchez, Sebastián and Quiles, José L. mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, inaki.elio@uneatlantico.es, maurizio.battino@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, jose.quiles@uneatlantico.es (2023) Exploring the Antioxidant, Neuroprotective, and Anti-Inflammatory Potential of Olive Leaf Extracts from Spain, Portugal, Greece, and Italy. Antioxidants, 12 (8). p. 1538. ISSN 2076-3921

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Abierto Inglés Ocimum is considered the largest genus in the Lamiacea family. The genus includes basil, a group of aromatic plants with a wide range of culinary uses that nowadays draws attention for its medicinal and pharmaceutical potential. This systematic review intends to explore the chemical composition of nonessential oils and their variation across different Ocimum species. Moreover, we aimed to identify the state of knowledge regarding the molecular space in this genus as well as the different methods of extraction/identification and geographical location. Seventy-nine eligible articles were selected for the final analysis, from which we extracted more than 300 molecules. We found that the countries with the highest number of studies into Ocimum species are India, Nigeria, Brazil, and Egypt. However, from all known species of Ocimum, only 12 were found to have an extensive chemical characterization, particularly Ocimum basilicum and Ocimum tenuiflorum. Our study focused especially on alcoholic, hydroalcoholic, and water extracts, in which the main techniques for compound identifications are GC-MS, LC-MS, and LC-UV. Across the compiled molecules, we found a wide variety of compounds, especially flavonoids, phenolic acids, and terpenoids, suggesting that this genus could be a very useful source of possible bioactive compounds. The information collected in this review also emphasizes the huge gap between the vast number of Ocimum species discovered and the number of studies in each of them that determined the chemical characterization. metadata Beltrán-Noboa, Andrea and Jordan-Álvarez, Alejandro and Guevara-Terán, Mabel and Gallo, Blanca and Berrueta, Luis A. and Giampieri, Francesca and Battino, Maurizio and Álvarez-Suarez, José M. and Tejera, Eduardo mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, francesca.giampieri@uneatlantico.es, maurizio.battino@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2023) Exploring the Chemistry of Ocimum Species under Specific Extractions and Chromatographic Methods: A Systematic Review. ACS Omega. ISSN 2470-1343

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés A new artificial intelligence-based approach is proposed by developing a deep learning (DL) model for identifying the people who violate the face mask protocol in public places. To achieve this goal, a private dataset was created, including different face images with and without masks. The proposed model was trained to detect face masks from real-time surveillance videos. The proposed face mask detection (FMDNet) model achieved a promising detection of 99.0% in terms of accuracy for identifying violations (no face mask) in public places. The model presented a better detection capability compared to other recent DL models such as FSA-Net, MobileNet V2, and ResNet by 24.03%, 5.0%, and 24.10%, respectively. Meanwhile, the model is lightweight and had a confidence score of 99.0% in a resource-constrained environment. The model can perform the detection task in real-time environments at 41.72 frames per second (FPS). Thus, the developed model can be applicable and useful for governments to maintain the rules of the SOP protocol. metadata Benifa, J. V. Bibal and Chola, Channabasava and Muaad, Abdullah Y. and Hayat, Mohd Ammar Bin and Bin Heyat, Md Belal and Mehrotra, Rajat and Akhtar, Faijan and Hussein, Hany S. and Ramírez-Vargas, Debora L. and Kuc Castilla, Ángel Gabriel and Díez, Isabel de la Torre and Khan, Salabat mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, debora.ramirez@unini.edu.mx, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2023) FMDNet: An Efficient System for Face Mask Detection Based on Lightweight Model during COVID-19 Pandemic in Public Areas. Sensors, 23 (13). p. 6090. ISSN 1424-8220

Article Subjects > Psychology Europe University of Atlantic > Research > Articles and books Abierto Inglés Background Although health public services recommend prevention strategies for COVID-19 some of these recommendations have not been taken seriously by young people. Understanding why some people comply with these recommendations and others do not seem to be crucial in helping public health services to predict behavior and compliance with rules, especially for young people. Previous studies suggest that knowledge, attitudes, and practices (KAP) are useful to assess compliance with the preventive measures and public health policies. Being afraid has also been found to correlate with more engagement with preventive measures. This study aims to assess the KAP and fear of COVID-19 of Spanish university students and to understand the relation between diagnosis, KAP and the level of fear. Method Participants of this cross-sectional study were 598 college students (69.4% women) from different Spanish Universities. Data were collected for a month using an online questionnaire through Sphinx iQ2. Results Levels of KAP among Spanish students were satisfactory and results suggest the presence of fear among them. More importantly, fear of COVID-19 mediated the impact of the diagnosis on the KAP. Conclusions Feeling fear seems to be the mechanism underlying the relationship between diagnosis and KAP. Diagnosis is associated with KAP when the diagnosis it is accompanied by measures of fear. KAP, diagnosis, or perceived fear of COVID must be taken together in consideration for health interventions and public health campaigns design. metadata Cancela, Ana and González-Noriega, Mar and Visiers, Ana mail UNSPECIFIED, UNSPECIFIED, ana.visiers@uneatlantico.es (2023) Fear of COVID-19: the mediation role between the COVID-19 diagnosis and KAP in Spanish university students. BMC Public Health, 23 (1). ISSN 1471-2458

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Abierto Inglés Epidemiological studies have shown that eating fish significantly reduces cardiovascular disease (CVD) incidence and mortality. However, more focused meta-analyses based on the most recent results from prospective cohort studies are needed. This systematic review and meta-analysis aims to update the association between fish intake and cardiovascular disease (CVD) risk using recent prospective studies. A systematic review and meta-analysis following the PRISMA guideline was conducted based on a random effects synthesis of multivariable-adjusted relative risks (RRs) of high vs. low categories of fish intake in relation to CVD incidence and mortality. Non-linear meta-regression was applied to investigate the shape of the association between fish intake and CVD risk. Sensitivity analysis and stratifications by type of CVD outcome, type of fish intake and type of cooking were performed. Based on 18 papers reporting 17 independent estimates of CVD risk (1,442,407 participants and 78,805 fatal and non-fatal CVD events), high vs. low intake of fish corresponded to about 8% reduced CVD risk (RR = 0.93 [0.88–0.98]). According to a non-linear dose–response meta-regression, 50 g of fish intake per day corresponded to a statistically significant 9% reduced fatal and non-fatal CVD risk (RR = 0.92 [0.90–0.95]). Similarly, fish intake in the range of a weekly intake of two to three portions of fish with a size of 150 g resulted in 8% fatal and non-fatal CVD risk reduction (RR = 0.93 [0.91–0.96]). The recommended two portions of fish a week reduces the risk of CVD outcomes by approximately 10%. A full portion of fish a day reduces CVD risk by up to 30%. metadata Ricci, Hannah and Gaeta, Maddalena and Franchi, Carlotta and Poli, Andrea and Battino, Maurizio and Dolci, Alberto and Schmid, Daniela and Ricci, Cristian mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, maurizio.battino@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2023) Fish Intake in Relation to Fatal and Non-Fatal Cardiovascular Risk: A Systematic Review and Meta-Analysis of Cohort Studies. Nutrients, 15 (21). p. 4539. ISSN 2072-6643

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Abierto Inglés Food knowledge (FK) is one of the factors that contribute to malnutrition conditions in developing countries, together with food safety, food security and food access. FK is defined as ‘the competence to understand healthy nutrition concepts’; it impacts individuals’ life due to its relationship with food behaviour and eating habits. Therefore, acting on FK can represent a starting point for improving the health status of vulnerable populations. The authors present a total score of an FK questionnaire (FKQ) and its relation to the socio-demographic characteristics of a specific target population: Tanzanian women of childbearing age. The results of the manuscript complement evidence of construct validity of the FKQ by providing an algorithm to compute a total score as a measure of FK. The strength of this tool, and its score, lies in the fact that the questionnaire has been validated and is easy to administer. metadata Conti, Maria Vittoria and Gnesi, Marco and Mshanga, Naelijwa and De Giuseppe, Rachele and Giampieri, Francesca and Cena, Hellas mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, francesca.giampieri@uneatlantico.es, UNSPECIFIED (2023) Food knowledge level among Tanzanian women of childbearing age: developing a score for the food knowledge questionnaire. Journal of Nutritional Science, 12. ISSN 2048-6790

Article Subjects > Engineering
Subjects > Teaching Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés The purpose of this research article was to contrast the benefits of the optimal probability threshold adjustment technique with other imbalanced data processing techniques, in its application to the prediction of post-graduate students’ late dropout from distance learning courses in two universities in the Ibero-American space. In this context, the optimization of the Logistic Regression, Random Forest, and Neural Network classifiers, together with different techniques, attributes, and algorithms (Hyperparameters, SMOTE, SMOTE_SVM, and ADASYN) resulted in a set of metrics for decision-making, prioritizing the reduction of false negatives. The best model was the Neural Network model in combination with SMOTE_SVM, obtaining a recall index of 0.75 and an f1-Score of 0.60. Likewise, the robustness of the Random Forest classifier for imbalanced data was demonstrated by achieving, with an optimal threshold of 0.427, very similar metrics to those obtained by the consensus of the three best models found. This demonstrates that, for Random Forest, the optimal prediction probability threshold is an excellent alternative to resampling techniques with different optimal thresholds. Finally, it is hoped that this research paper will contribute to boost the application of this simple but powerful technique, which is highly underrated with respect to data resampling techniques for imbalanced data. metadata Rodríguez Velasco, Carmen Lilí and García Villena, Eduardo and Brito Ballester, Julién and Durántez Prados, Frigdiano Álvaro and Silva Alvarado, Eduardo René and Crespo Álvarez, Jorge mail carmen.rodriguez@uneatlantico.es, eduardo.garcia@uneatlantico.es, julien.brito@uneatlantico.es, durantez@uneatlantico.es, eduardo.silva@funiber.org, jorge.crespo@uneatlantico.es (2023) Forecasting of Post-Graduate Students’ Late Dropout Based on the Optimal Probability Threshold Adjustment Technique for Imbalanced Data. International Journal of Emerging Technologies in Learning (iJET), 18 (04). pp. 120-155. ISSN 1863-0383

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés In the Internet of things (IoT), data packets are accumulated and disseminated across IoT devices without human intervention, therefore the privacy and security of sensitive data during transmission are crucial. For this purpose, multiple routing techniques exist to ensure security and privacy in IoT Systems. One such technique is the routing protocol for low power and lossy networks (RPL) which is an IPv6 protocol commonly used for routing in IoT systems. Formal modeling of an IoT system can validate the reliability, accuracy, and consistency of the system. This paper presents the formal modeling of RPL protocol and the analysis of its security schemes using colored Petri nets that applies formal validation and verification for both the secure and non-secure modes of RPL protocol. The proposed approach can also be useful for formal modeling-based verification of the security of the other communication protocols. metadata Balfaqih, Mohammed and Ahmad, Farooq and Chaudhry, Muhammad Tayyab and Jamal, Muhammad Hasan and Sohail, Muhammad Amar and Gavilanes Aray, Daniel and Masías Vergara, Manuel and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, daniel.gavilanes@uneatlantico.es, manuel.masias@uneatlantico.es, UNSPECIFIED (2023) Formal modeling and analysis of security schemes of RPL protocol using colored Petri nets. PLOS ONE, 18 (8). e0285700. ISSN 1932-6203

Article Subjects > Engineering
Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Abierto Inglés Nitrogen plays a vital role in plants’ biochemical and physiological functions, and it contributes significantly to increasing plant yield and fruit quality. Plants that efficiently absorb and utilize nitrogen enhance the efficiency of fertilizers, reducing their input costs and preventing ecosystem damage. Thus, an adequate nitrogen supply can significantly improve plant growth, fruit quality, and nutritional value. This research focused on evaluating the plant vegetative and productive performance and fruit quality of three short-day strawberry genotypes (“Cristina”, “Romina”, and “Sibilla”) that were fertilized with different amounts of nitrogen, in a crop that was protected under a plastic tunnel. The trial was conducted during two cultivation cycles. The nitrogen rates were 113, 90, and 68 kg/ha for the first year, and 118, 97, and 76 kg/ha for the second. Reduced nitrogen inputs did not significantly affect plant height, indicating that decreased nutritional intake does not harm plant development. The fruit sugar content value remained stable across all nitrogen supplies, as did the fruit titratable acidity. The cultivars maintained a medium fruit firmness at a 60% nitrogen supply, and the Chroma index was not affected. This study found that reducing nitrogen inputs did not have a significant negative impact on the three tested cultivars, making them suitable for cultivation with reduced nitrogen inputs to reduce the environmental impact and save growers’ inputs. metadata Marcellini, Micol and Raffaelli, Davide and Pergolotti, Valeria and Balducci, Francesca and Marcellini, Mirco and Capocasa, Franco and Mezzetti, Bruno and Mazzoni, Luca mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, bruno.mezzetti@uneatlantico.es, UNSPECIFIED (2023) Growth and Yield of Strawberry Cultivars under Low Nitrogen Supply in Italy. Horticulturae, 9 (11). p. 1165. ISSN 2311-7524

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Cerrado Inglés Saponins, consisting of sapogenins as their aglycones and carbohydrate chains, are widely found in plants and some marine organisms. Due to the complexity of the structure of saponins, involving different types of sapogenins and sugar moieties, investigation of their absorption and metabolism is limited, which further hinders the explanation of their bioactivities. Large molecular weight and complex structures limit the direct absorption of saponins rendering their low bioavailability. As such, their major modes of action may be due to interaction with the gastrointestinal environment, such as enzymes and nutrients, and interaction with the gut microbiota. Many studies have reported the interaction between saponins and gut microbiota, that is, the effects of saponins on changing the composition of gut microbiota, and gut microbiota playing an indispensable role in the biotransformation of saponins into sapogenins. However, the metabolic routes of saponins by gut microbiota and their mutual interactions are still sparse. Thus, this review summarizes the chemistry, absorption, and metabolic pathways of saponins, as well as their interactions with gut microbiota and impacts on gut health, to better understand how saponins exert their health-promoting functions. metadata Zhang, Yu and Hao, Ruojie and Chen, Junda and Li, Sen and Huang, Kai and Cao, Hongwei and Farag, Mohamed A. and Battino, Maurizio and Daglia, Maria and Capanoglu, Esra and Zhang, Fan and Sun, Qiqi and Xiao, Jianbo and Sun, Zhenliang and Guan, Xiao mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, maurizio.battino@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2023) Health benefits of saponins and its mechanisms: perspectives from absorption, metabolism, and interaction with gut. Critical Reviews in Food Science and Nutrition. pp. 1-22. ISSN 1040-8398

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Cerrado Inglés Background The house cricket (A. domesticus) is one of the edible insects that are gaining attention as a new source of protein and nutrients with potential use in the food industry as a safe and environmentally sustainable option with high biological value. Scope and approach Here, we review the published literature on studies of chemical composition, nutritional value, and potential risks that the consumption of house crickets entails. We discuss the benefits of consuming A. domesticus from a nutritional point of view, as well as information concerning the properties of its components for use in the food industry. metadata Pilco-Romero, Gabriela and Chisaguano-Tonato, Aida M. and Herrera-Fontana, María E. and Chimbo-Gándara, Luis F. and Sharifi-Rad, Majid and Giampieri, Francesca and Battino, Maurizio and Vernaza, María Gabriela and Álvarez-Suárez, José M. mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, francesca.giampieri@uneatlantico.es, maurizio.battino@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2023) House cricket (Acheta domesticus): A review based on its nutritional composition, quality, and potential uses in the food industry. Trends in Food Science & Technology, 142. p. 104226. ISSN 09242244

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés Forecasting of sediment load (SL) is essential for reservoir operations, design of water resource structures, risk management, water resource planning and for preventing natural disasters in the river basin systems. Direct measurement of SL is difficult, labour intensive, and expensive. The development of an accurate and reliable model for forecasting the SL is required. Sediment transport is highly non-linear and is influenced by a variety of factors. Forecasting of the SL using various conventional methods is not highly accurate because of the association of various complex phenomena. In this study, major key factors such as rock type (RT), relief (R), rainfall (RF), water discharge (WD), temperature (T), catchment area (CA), and SL are recognized in developing the one-step-ahead SL forecasting model in the Mahanadi River (MR), which is among India’s largest rivers. Artificial neural networks (ANN) in conjunction with multi-objective genetic algorithm (ANN-MOGA)-based forecasting models were developed for forecasting the SL in the MR. The ANN-MOGA model was employed to optimize the two competing objective functions (bias and error variance) with simultaneous optimization of all associated ANN parameters. The performances of the proposed novel model were finally compared to other existing methods to verify the forecasting capability of the model. The ANN-MOGA model improved the performance by 12.81% and 10.19% compared to traditional AR and MAR regression models, respectively. The results suggested that hybrid ANN-MOGA models outperform traditional autoregressive and multivariate autoregressive forecasting models. Overall, hybrid ANN-MOGA intelligent techniques are recommended for the forecasting of SL in rivers metadata Yadav, Arvind and Ali Albahar, Marwan and Chithaluru, Premkumar and Singh, Aman and Alammari, Abdullah and Kumar, Gogulamudi Vijay and Miró Vera, Yini Airet mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, aman.singh@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, yini.miro@uneatlantico.es (2023) Hybridizing Artificial Intelligence Algorithms for Forecasting of Sediment Load with Multi-Objective Optimization. Water, 15 (3). p. 522. ISSN 2073-4441

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés With the advancement in information technology, digital data stealing and duplication have become easier. Over a trillion bytes of data are generated and shared on social media through the internet in a single day, and the authenticity of digital data is currently a major problem. Cryptography and image watermarking are domains that provide multiple security services, such as authenticity, integrity, and privacy. In this paper, a digital image watermarking technique is proposed that employs the least significant bit (LSB) and canny edge detection method. The proposed method provides better security services and it is computationally less expensive, which is the demand of today’s world. The major contribution of this method is to find suitable places for watermarking embedding and provides additional watermark security by scrambling the watermark image. A digital image is divided into non-overlapping blocks, and the gradient is calculated for each block. Then convolution masks are applied to find the gradient direction and magnitude, and non-maximum suppression is applied. Finally, LSB is used to embed the watermark in the hysteresis step. Furthermore, additional security is provided by scrambling the watermark signal using our chaotic substitution box. The proposed technique is more secure because of LSB’s high payload and watermark embedding feature after a canny edge detection filter. The canny edge gradient direction and magnitude find how many bits will be embedded. To test the performance of the proposed technique, several image processing, and geometrical attacks are performed. The proposed method shows high robustness to image processing and geometrical attacks metadata Faheem, Zaid Bin and Ishaq, Abid and Rustam, Furqan and de la Torre Díez, Isabel and Gavilanes, Daniel and Masías Vergara, Manuel and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, daniel.gavilanes@uneatlantico.es, manuel.masias@uneatlantico.es, UNSPECIFIED (2023) Image Watermarking Using Least Significant Bit and Canny Edge Detection. Sensors, 23 (3). p. 1210. ISSN 1424-8220

Article Subjects > Engineering Universidad Internacional do Cuanza > Research > Scientific Production
Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production Abierto Inglés This research paper aims to examine the impact of innovative HRM practices, including employee participation, performance appraisal, reward and compensation, recruitment and selection, and redeployment–retraining on firm performance. For this purpose, four different models are utilized to examine the impact of innovative HRM department practices on the performance of small and medium enterprises (SMEs) in a country. The dependent variable, firm performance, is proxified by different variables such as labor productivity, product innovation, process innovation, and marketing innovation. For empirical analysis, primary data are collected using a questionnaire. Estimation is conducted using ordinary least squares (OLS) and logit regression techniques. The estimated results indicate that most innovative HRM practices have a statistically significant impact on firm performance in terms of labor productivity, product, process, and marketing innovations. These results imply that SMEs in a country may observe the benefits of devoting greater attention to innovative HRM practices to achieve their future growth potential. metadata Aslam, Mahvish and Shafi, Imran and Ahmed, Jamil and Garat de Marin, Mirtha Silvana and Soriano Flores, Emmanuel and Rojo Gutiérrez, Marco Antonio and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, silvana.marin@uneatlantico.es, emmanuel.soriano@uneatlantico.es, marco.rojo@unini.edu.mx, UNSPECIFIED (2023) Impact of Innovation-Oriented Human Resource on Small and Medium Enterprises’ Performance. Sustainability, 15 (7). p. 6273. ISSN 2071-1050

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Abierto Inglés Leiomyosarcoma is an aggressive soft tissue sarcoma derived from the smooth muscle cells of the uterus. We tested the effect of Romina strawberry extract treatment on three-dimensional cultured uterine leiomyosarcoma cells. We established 3D cultures in agarose gel, where the cells seeded were able to form spheroids. We performed the observation and counting of the spheroids with a phase-contrast optical microscope, finding a decrease in the number of spheroids formed in the plates after 24 and 48 h treatment with 250 µg/mL of cultivar Romina strawberry extract. We also characterized the spheroids morphology by DNA binding fluorescent-stain observation, hematoxylin and eosin stain, and Masson’s trichrome stain. Finally, the real-time PCR showed a reduced expression of extracellular matrix genes after strawberry treatment. Overall, our data suggest that the fruit extract of this strawberry cultivar may be a useful therapeutic adjuvant for the management of uterine leiomyosarcoma. metadata Greco, Stefania and Pellegrino, Pamela and Giampieri, Francesca and Capocasa, Franco and Delli Carpini, Giovanni and Battino, Maurizio and Mezzetti, Bruno and Giannubilo, Stefano Raffaele and Ciavattini, Andrea and Ciarmela, Pasquapina mail UNSPECIFIED, UNSPECIFIED, francesca.giampieri@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, maurizio.battino@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2023) The In Vitro Effects of Romina Strawberry Extract on 3D Uterine Leiomyosarcoma Cells. Nutrients, 15 (11). p. 2557. ISSN 2072-6643

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés There is growing evidence that Alzheimer’s disease (AD) can be prevented by reducing risk factors involved in its pathophysiology. Food-derived bioactive molecules can help in the prevention and reduction of the progression of AD. Honey, a good source of antioxidants and bioactive molecules, has been tied to many health benefits, including those from neurological origin. Monofloral avocado honey (AH) has recently been characterized but its biomedical properties are still unknown. The aim of this study is to further its characterization, focusing on the phenolic profile. Moreover, its antioxidant capacity was assayed both in vitro and in vivo. Finally, a deep analysis on the pathophysiological features of AD such as oxidative stress, amyloid-β aggregation, and protein-tau-induced neurotoxicity were evaluated by using the experimental model C. elegans. AH exerted a high antioxidant capacity in vitro and in vivo. No toxicity was found in C. elegans at the dosages used. AH prevented ROS accumulation under AAPH-induced oxidative stress. Additionally, AH exerted a great anti-amyloidogenic capacity, which is relevant from the point of view of AD prevention. AH exacerbated the locomotive impairment in a C. elegans model of tauopathy, although the real contribution of AH remains unclear. The mechanisms under the observed effects might be attributed to an upregulation of daf-16 as well as to a strong ROS scavenging activity. These results increase the interest to study the biomedical applications of AH; however, more research is needed to deepen the mechanisms under the observed effects metadata Romero-Márquez, Jose M. and Navarro-Hortal, María D. and Orantes, Francisco J. and Esteban-Muñoz, Adelaida and Mazas Pérez-Oleaga, Cristina and Battino, Maurizio and Sánchez-González, Cristina and Rivas-García, Lorenzo and Giampieri, Francesca and Quiles, José L. and Forbes-Hernandez, Tamara Y. mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, cristina.mazas@uneatlantico.es, maurizio.battino@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, francesca.giampieri@uneatlantico.es, jose.quiles@uneatlantico.es, tamara.forbes@unini.edu.mx (2023) In Vivo Anti-Alzheimer and Antioxidant Properties of Avocado (Persea americana Mill.) Honey from Southern Spain. Antioxidants, 12 (2). p. 404. ISSN 2076-3921

Article Subjects > Nutrition Europe University of Atlantic > Research > Articles and books Cerrado Inglés Diabetes is a metabolic disease due to impaired or defective insulin secretion and is considered one of the most serious chronic diseases worldwide. Gamma-aminobutyric acid (GABA) is a naturally occurring non-protein amino acid commonly present in a wide range of foods. A number of studies documented that GABA has good anti-diabetic potential. This review summarized the available dietary sources of GABA as well as animal and human studies on the anti-diabetic properties of GABA, while also discussing the underlying mechanisms. GABA may modulate diabetes through various pathways such as inhibiting the activities of α-amylase and α-glucosidase, promoting β-cell proliferation, stimulating insulin secretion from β-cells, inhibiting glucagon secretion from α-cells, improving insulin resistance and glucose tolerance, and increasing antioxidant and anti-inflammatory activities. However, further mechanistic studies on animals and human are needed to confirm the therapeutic effects of GABA against diabetes. metadata Sun, Yu and Mehmood, Arshad and Giampieri, Francesca and Battino, Maurizio and Chen, Xiumin mail UNSPECIFIED, UNSPECIFIED, francesca.giampieri@uneatlantico.es, maurizio.battino@uneatlantico.es, UNSPECIFIED (2023) Insights into the cellular, molecular, and epigenetic targets of gamma-aminobutyric acid against diabetes: a comprehensive review on its mechanisms. Critical Reviews in Food Science and Nutrition. pp. 1-18. ISSN 1040-8398

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books Abierto Inglés Rock art offers traces of our most remote past and was made with mineral and organic substances in shelters, walls, or the ceilings of caves. As it is notably fragile, it is fortunate that some instances remain intact—but a variety of natural and anthropogenic factors can lead to its disappearance. Therefore, as a valuable cultural heritage, rock art requires special conservation and protection measures. Geomatic remote-sensing technologies such as 3D terrestrial laser scanning (3DTLS), drone flight, and ground-penetrating radar (GPR) allow us to generate exhaustive documentation of caves and their environment in 2D, 2.5D, and 3D. However, only its combined use with 3D geographic information systems (GIS) lets us generate new cave maps with details such as overlying layer thickness, sinkholes, fractures, joints, and detachments that also more precisely reveal interior–exterior interconnections and gaseous exchange; i.e., the state of senescence of the karst that houses the cave. Information of this kind is of great value for the research, management, conservation, monitoring, and dissemination of cave art. metadata Bayarri Cayón, Vicente and Prada, Alfredo and García, Francisco and Díaz-González, Lucía M. and De Las Heras, Carmen and Castillo, Elena and Fatás, Pilar mail vicente.bayarri@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2023) Integration of Remote-Sensing Techniques for the Preventive Conservation of Paleolithic Cave Art in the Karst of the Altamira Cave. Remote Sensing, 15 (4). p. 1087. ISSN 2072-4292

Article Subjects > Teaching Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Regulatory dispersion and a utilitarian use of sustainability deepen the gap within the teaching–learning process and limit the introduction of sustainable criteria in organizations through projects. The objective of this research consisted in developing a sustainable and holistic educational proposal for an online postgraduate program belonging to the Universidad Europea del Atlántico (UNEATLANTICO) within the field of projects. The proposal was based on the instrumentalization of a model comprised of national and international bibliographic references, resulting in a sustainability guide with significant improvements in relation to the reference standard par excellence: ISO 26000:2010. This guide formed the basis of a sustainability management plan, which was key in the project methodology and during the development of sustainable objectives and descriptors for each of the subjects. Lastly, the entities, attributes, and cardinal relationships were established for the development of a physical model used to facilitate the management of all this information within a SQL database. The rigor when determining the educational program, as well as the subsequent analysis of results as supported by the literature review, presupposes the application of this methodology toward other multidisciplinary programs contributing to the adoption of good sustainability practices within the educational field metadata Gracia Villar, Mónica and Álvarez, Roberto Marcelo and Brie, Santiago and Miró Vera, Yini Airet and García Villena, Eduardo mail monica.gracia@uneatlantico.es, roberto.alvarez@uneatlantico.es, santiago.brie@uneatlantico.es, yini.miro@uneatlantico.es, eduardo.garcia@uneatlantico.es (2023) Integration of Sustainable Criteria in the Development of a Proposal for an Online Postgraduate Program in the Projects Area. Education Sciences, 13 (1). p. 97. ISSN 2227-7102

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés Agriculture is a critical domain, where technology can have a significant impact on increasing yields, improving crop quality, and reducing environmental impact. The use of renewable energy sources such as solar power in agriculture has gained momentum in recent years due to the potential to reduce the carbon footprint of farming operations. In addition to providing a source of clean energy, solar tracking systems can also be used for remote weather monitoring in the agricultural field. The ability to collect real-time data on weather parameters such as temperature, humidity, and rainfall can help farmers make informed decisions on irrigation, pest control, and other crop management practices. The main idea of this study is to present a system that can improve the efficiency of solar panels to provide constant power to the sensor in the agricultural field and transfer real-time data to the app. This research presents a mechanism to improve the arrangement of a photovoltaic (PV) array with solar power and to produce maximum energy. The proposed system changes its direction in two axes (azimuth and elevation) by detecting the difference between the position of the sun and the panel to track the sun using a light-dependent resistor. A testbed with a hardware experimental setup is designed to test the system’s capability to track according to the position of the sun effectively. In the end, real-time data are displayed using the Android app, and the weather data are transferred to the app using a GSM/WiFi module. This research improves the existing system, and results showed that the relative increase in power generation was up to 52%. Using intelligent artificial intelligence techniques with the QoS algorithm, the quality of service produced by the existing system is improved. metadata Kanwal, Tabassum and Rehman, Saif Ur and Ali, Tariq and Mahmood, Khalid and Gracia Villar, Santos and Dzul Lopez, Luis and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, santos.gracia@uneatlantico.es, luis.dzul@unini.edu.mx, UNSPECIFIED (2023) An Intelligent Dual-Axis Solar Tracking System for Remote Weather Monitoring in the Agricultural Field. Agriculture, 13 (8). p. 1600. ISSN 2077-0472

Article Subjects > Comunication Europe University of Atlantic > Research > Articles and books Abierto Inglés The development of digital technologies and the evolution of open innovation approaches have enabled the creation of diverse virtual organizations and enterprises coordinating their activities primarily online. The open innovation platform titled “International Natural Product Sciences Taskforce” (INPST) was established in 2018, to bring together in collaborative environment individuals and organizations interested in natural product scientific research, and to empower their interactions by using digital communication tools. Methods In this work, we present a general overview of INPST activities and showcase the specific use of Twitter as a powerful networking tool that was used to host a one-week “2021 INPST Twitter Networking Event” (spanning from 31st May 2021 to 6th June 2021) based on the application of the Twitter hashtag #INPST. Results and Conclusion The use of this hashtag during the networking event period was analyzed with Symplur Signals (https://www.symplur.com/), revealing a total of 6,036 tweets, shared by 686 users, which generated a total of 65,004,773 impressions (views of the respective tweets). This networking event's achieved high visibility and participation rate showcases a convincing example of how this social media platform can be used as a highly effective tool to host virtual Twitter-based international biomedical research events. metadata Singla, Rajeev K. and De, Ronita and Efferth, Thomas and Mezzetti, Bruno and Sahab Uddin, Md. and Sanusi, X. and Ntie-Kang, Fidele and Wang, Dongdong and Schultz, Fabien and Kharat, Kiran R. and Devkota, Hari Prasad and Battino, Maurizio and Sur, Daniel and Lordan, Ronan and Patnaik, Sourav S and Tsagkaris, Christos and Sai, Chandragiri Siva and Tripathi, Surya Kant and Găman, Mihnea-Alexandru and Ahmed, Mosa E.O. and González-Burgos, Elena and Babiaka, Smith B. and Paswan, Shravan Kumar and Odimegwu, Joy Ifunanya and Akram, Faizan and Simal-Gandara, Jesus and Urquiza, Mágali S. and Tikhonov, Aleksei and Mondal, Himel and Singla, Shailja and Lonardo, Sara Di and Mulholland, Eoghan J and Cenanovic, Merisa and Maigoro, Abdulkadir Yusif and Giampieri, Francesca and Lee, Soojin and Tzvetkov, Nikolay T. and Louka, Anna Maria and Verma, Pritt and Chopra, Hitesh and Olea, Scarlett Perez and Khan, Johra and Alvarez Suarez, José M. and Zheng, Xiaonan and Tomczyk, Michał and Sabnani, Manoj Kumar and Medina, Christhian Delfino Villanueva and Khalid, Garba M. and Boyina, Hemanth Kumar and Georgiev, Milen I. and Supuran, Claudiu T. and Sobarzo-Sánchez, Eduardo and Fan, Tai-Ping and Pittala, Valeria and Sureda, Antoni and Braidy, Nady and Russo, Gian Luigi and Vacca, Rosa Anna and Banach, Maciej and Lizard, Gérard and Zarrouk, Amira and Hammami, Sonia and Orhan, Ilkay Erdogan and Aggarwal, Bharat B. and Perry, George and Miller, Mark JS and Heinrich, Michael and Bishayee, Anupam and Kijjoa, Anake and Arkells, Nicolas and Bredt, David and Wink, Michael and Fiebich, Bernd l. and Kiran, Gangarapu and Yeung, Andy Wai Kan and Gupta, Girish Kumar and Santini, Antonello and Lucarini, Massimo and Durazzo, Alessandra and El-Demerdash, Amr and Dinkova-Kostova, Albena T. and Cifuentes, Alejandro and Souto, Eliana B. and Zubair, Muhammad Asim Masoom and Badhe, Pravin and Echeverría, Javier and Horbańczuk, Jarosław Olav and Horbanczuk, Olaf K. and Sheridan, Helen and Sheshe, Sadeeq Muhammad and Witkowska, Anna Maria and Abu-Reidah, Ibrahim M. and Riaz, Muhammad and Ullah, Hammad and Oladipupo, Akolade R. and Lopez, Víctor and Sethiya, Neeraj Kumar and Shrestha, Bhupal Govinda and Ravanan, Palaniyandi and Gupta, Subash Chandra and Alzahrani, Qushmua E. and Dama Sreedhar, Preethidan and Xiao, Jianbo and Moosavi, Mohammad Amin and Subramani, Parasuraman Aiya and Singh, Amit Kumar and Chettupalli, Ananda Kumar and Patra, Jayanta Kumar and Singh, Gopal and Karpiński, Tomasz M. and Al-Rimawi, Fuad and Abiri, Rambod and Ahmed, Atallah F. and Barreca, Davide and Vats, Sharad and Amrani, Said and Fimognari, Carmela and Mocan, Andrei and Hritcu, Lucian and Semwal, Prabhakar and Shiblur Rahaman, Md. and Emerald, Mila and Akinrinde, Akinleye Stephen and Singh, Abhilasha and Joshi, Ashima and Joshi, Tanuj and Khan, Shafaat Yar and Balla, Gareeballah Osman Adam and Lu, Aiping and Pai, Sandeep Ramchandra and Ghzaiel, Imen and Acar, Niyazi and Es-Safi, Nour Eddine and Zengin, Gokhan and Kureshi, Azazahemad A. and Sharma, Arvind Kumar and Baral, Bikash and Rani, Neeraj and Jeandet, Philippe and Gulati, Monica and Kapoor, Bhupinder and Mohanta, Yugal Kishore and Emam-Djomeh, Zahra and Onuku, Raphael and Depew, Jennifer R. and Atrooz, Omar M. and Goh, Bey Hing and Andrade, Jose Carlos and Konwar, Bikramjit and Shine, VJ and Ferreira, João Miguel Lousa Dias and Ahmad, Jamil and Chaturvedi, Vivek K. and Skalicka-Woźniak, Krystyna and Sharma, Rohit and Gautam, Rupesh K. and Granica, Sebastian and Parisi, Salvatore and Kumar, Rishabh and Atanasov, Atanas G. and Shen, Bairong mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, maurizio.battino@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, francesca.giampieri@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2023) The International Natural Product Sciences Taskforce (INPST) and the power of Twitter networking exemplified through #INPST hashtag analysis. Phytomedicine, 108. p. 154520. ISSN 09447113

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés The Internet of Things (IoT) has positioned itself globally as a dominant force in the technology sector. IoT, a technology based on interconnected devices, has found applications in various research areas, including healthcare. Embedded devices and wearable technologies powered by IoT have been shown to be effective in patient monitoring and management systems, with a particular focus on pregnant women. This study provides a comprehensive systematic review of the literature on IoT architectures, systems, models and devices used to monitor and manage complications during pregnancy, postpartum and neonatal care. The study identifies emerging research trends and highlights existing research challenges and gaps, offering insights to improve the well-being of pregnant women at a critical moment in their lives. The literature review and discussions presented here serve as valuable resources for stakeholders in this field and pave the way for new and effective paradigms. Additionally, we outline a future research scope discussion for the benefit of researchers and healthcare professionals. metadata Hossain, Mohammad Mobarak and Kashem, Mohammod Abul and Islam, Md. Monirul and Sahidullah, Md. and Mumu, Sumona Hoque and Uddin, Jia and Gavilanes Aray, Daniel and de la Torre Diez, Isabel and Ashraf, Imran and Samad, Md Abdus mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, daniel.gavilanes@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2023) Internet of Things in Pregnancy Care Coordination and Management: A Systematic Review. Sensors, 23 (23). p. 9367. ISSN 1424-8220

Book Section Subjects > Teaching Europe University of Atlantic > Research > Articles and books Abierto Español UNSPECIFIED metadata Quijano-Peña, Paula mail paula.quijano@uneatlantico.es (2023) Introduciendo la posedición en el aula de traducción especializada. In: El poder de la innovación educativa: cómo las tecnologías están revolucionando el aprendizaje. Horizonte Académico (12). Egregius, Sevilla, pp. 245-256. ISBN 978-84-1177-033-0

Article Subjects > Engineering Europe University of Atlantic > Research > Articles and books
Fundación Universitaria Internacional de Colombia > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Universidad Internacional do Cuanza > Research > Scientific Production Abierto Inglés An Internet of Things (IoT) network is prone to many ways of threatening individuals. IoT sensors are lightweight, lack complicated security protocols, and face threats to privacy and confidentiality. Hackers can attack the IoT network and access personal information and confidential data for blackmailing, and negatively manipulate data. This study aims to propose an IoT threat protection system (IoTTPS) to protect the IoT network from threats using an ensemble model RKSVM, comprising a random forest (RF), K nearest neighbor (KNN), and support vector machine (SVM) model. The software-defined networks (SDN)-based IoT network datasets such as KDD cup 99, NSL-KDD, and CICIDS are used for threat detection based on machine learning. The experimental phase is conducted by using a decision tree (DT), logistic regression (LR), Naive Bayes (NB), RF, SVM, gradient boosting machine (GBM), KNN, and the proposed ensemble RKSVM model. Furthermore, performance is optimized by adding a grid search hyperparameter optimization technique with K-Fold cross-validation. As well as the NSL-KDD dataset, two other datasets, KDD and CIC-IDS 2017, are used to validate the performance. Classification accuracies of 99.7%, 99.3%, 99.7%, and 97.8% are obtained for DoS, Probe, U2R, and R2L attacks using the proposed ensemble RKSVM model using grid search and cross-fold validation. Experimental results demonstrate the superior performance of the proposed model for IoT threat detection. metadata Akram, Urooj and Sharif, Wareesa and Shahroz, Mobeen and Mushtaq, Muhammad Faheem and Gavilanes Aray, Daniel and Bautista Thompson, Ernesto and Diez, Isabel de la Torre and Djuraev, Sirojiddin and Ashraf, Imran mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, daniel.gavilanes@uneatlantico.es, ernesto.bautista@unini.edu.mx, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2023) IoTTPS: Ensemble RKSVM Model-Based Internet of Things Threat Protection System. Sensors, 23 (14). p. 6379. ISSN 1424-8220

Article Subjects > Teaching
Subjects > Comunication
Subjects > Psychology Europe University of Atlantic > Research > Articles and books Abierto Español A medida que los medios extienden mundialmente la concienciación sobre la inclusión y la diversidad intercultural, en redes sociales como TikTok emergen nuevas vías para el debate, lo que afecta, entre otros, al público infantil. Una muestra de ello son los populares vídeos-reacción que, ante lanzamientos cinematográficos como el teaser del live action de La Sirenita de Disney, construyen cadenas de interacción en las que se polemiza sobre la representación simbólica, la descentralización colonial, la ruptura estereotípica o el imaginario caucásico en la infancia. Este estudio explora las reacciones infantiles y el sentimiento comunitario desplegado en TikTok mediante el análisis cualitativo de 50 vídeo-reacciones y el análisis de sentimiento de 11,510 comentarios. Para ello, se desarrolló un análisis de contenido inductivo que introducía 10 códigos, como “diversidad e inclusión”, “emociones”, “prejuicios” e “identidad racial/étnica”, y un análisis de sentimiento codificado con procesamiento del lenguaje natural e inteligencia artificial basado en el modelo GPT de OpenAI. Los resultados revelan que la representación de una protagonista afroamericana, Halle Bailey, es bien recibida por los menores, generando un positivismo generalizado en torno a la diversidad intercultural. La tez negra y el cabello castaño cobrizo frente a la que fue un icono caucásico y pelirrojo parece no amedrentar a los infantes, que expresan entusiasmo y emoción ante su papel. Esta representación denota una suerte de positivismo generalizado, en el que el imaginario “Disneyzado” adulto e infantil apunta hacia un futuro basado en la diversidad y la autoestima infantil. metadata Bonilla-del-Río, Mónica and Vizcaíno-Verdú, Arantxa mail monica.bonilla@uneatlantico.es, UNSPECIFIED (2023) “¡La Sirenita es como yo!”: diversidad intercultural, inclusión y autoestima infantil en TikTok. Psychology, Society & Education, 15 (3). pp. 57-70. ISSN 1989-709X

Book Subjects > Social Sciences Europe University of Atlantic > Research > Articles and books Cerrado Español El objeto de esta monografía es el estudio diacrónico y pormenorizado de la adopción, tomando como referencia el texto originario del Código Civil de 1889 y el análisis doctrinal que hicieron los principales civilistas y jurisconsultos de la época. Con una visión práctica y una fuerte base teórica, tanto en el ámbito del Derecho civil como de la Sociología jurídica, este libro pretende llenar un vacío derivado de la falta de un análisis específico, compilatorio, doctrinal y monográfico, respecto a como ha ido evolucionando la adopción en cada una de las reformas que se han sucedido (dieciséis) desde el año 1889 hasta la actualidad. Asimismo y con un enorme rigor académico, Manuel Baelo Álvarez escudriña la exégesis de cada uno de los artículos del vigente Código Civil, su normatividad, el significado y la utilidad sociojurídica de la adopción, no solo en España, sino también en aquellos territorios en los que nuestro Código Civil estuvo presente, como Filipinas, Puerto Rico, Cuba y el Golfo de Guinea (Guinea Ecuatorial). metadata Baelo Álvarez, Manuel mail manuel.baelo@uneatlantico.es (2023) La adopción en el Código Civil: evolución normativa, doctrinal y sociojurídica desde 1889 hasta la actualidad. Tirant lo Blanch, Valencia. ISBN 9788411690041

Article Subjects > Teaching
Subjects > Comunication Europe University of Atlantic > Research > Articles and books Abierto Español La presente investigación tiene como objetivo, mostrar la importancia de explorar y aplicar nuevas vías o canales de difusión acordes a las necesidades y demandas actuales, para llegar a un público joven en materia de divulgación y conocimiento científico. Es por ello, que a través de este estudio se pretende evidenciar no sólo la eficacia, sino también, el valor que los jóvenes universitarios dan a las redes sociales como uno de los principales canales de consulta de información. Para ello, se ha realizado una encuesta a 188 estudiantes de catorce grados universitarios a través de la cual, se ha podido conocer y valorar los motivos de su escaso interés en la lectura y consulta de revistas y publicaciones científicas. Observando en este sentido, cómo uno de los problemas a los que se enfrenta la divulgación científica española es la falta de medios de difusión existentes y aplicables, especialmente si se desea llegar a un público joven. De este modo, se subraya la idea de que las redes sociales pueden ser un canal potencial para la difusión y mayor alcance del conocimiento científico en cualquier área. Por todo ello, el presente estudio llevaría a un nuevo planteamiento el cual permita abordar las estrategias a desarrollar por parte de las revistas académicas en aquellas redes sociales donde se concentran más jóvenes universitarios. metadata Alemany Iturriaga, Josep and Garay, Helena and Arnaiz García, Clara mail josep.alemany@uneatlantico.es, helena.garay@uneatlantico.es, clara.arnaiz@uneatlantico.es (2023) La importancia de la aplicación y uso de las redes sociales en la divulgación científica dirigida a jóvenes universitarios. MLS Educational Research, 8 (1). ISSN 2603-5820

Article Subjects > Physical Education and Sport Europe University of Atlantic > Research > Articles and books Abierto Español Introducción: Evaluar la literatura científica existente sobre la relación entre las fluctuaciones hormonales y la capacidad de producir fuerza, y establecer qué fase del CM es la más adecuada para aplicar mayor carga en entrenamiento de fuerza. Método: Se realizó una búsqueda bibliográfica a través de la base de datos PubMed. Los artículos incluidos fueron aquellos que estuvieran redactados en inglés o español y que estuvieran relacionados con la producción de fuerza en mujeres eumenorreicas. Resultados: En cuanto a la fuerza de prensión se obtuvieron resultados muy dispares que pueden derivar del nivel de entrenamiento de las participantes, así como del método utilizado para determinar las fases, ya que pocos coincidieron. Si observamos los estudios relacionados con la fuerza isométrica no se obtuvieron diferencias significativas a lo largo del ciclo menstrual, aunque habría que fijarse en las fases evaluadas y el método para evaluar dichas fases. En cuanto a la fuerza del miembro inferior los resultados indicaron mejores valores de fuerza en la fase folicular. Por último, los resultados relacionados con la contracción voluntaria máxima indicaron mejores valores en la fase lútea y de ovulación. Discusión y conclusión: En conclusión, la capacidad de producir fuerza es mayor en diferentes fases según la prueba de fuerza realizada, la mayor incertidumbre se dio en la fuerza de prensión donde no queda clara cuál es la fase en la que se produce mayor fuerza ya que los resultados son muy diferentes. Sin embargo, parece que la capacidad para generar fuerza isométrica no varía a lo largo del ciclo menstrual y la fuerza máxima está relacionada con la fase folicular donde se da el pico de estrógeno. En cuanto a la contracción voluntaria máxima se dan dos resultados diferentes que ofrecen dudas sobre en qué fase se genera más este tipo de fuerza. metadata Lago-Fuentes, Carlos and Osmani, Florent and De la Fuente de la Parte, Diego mail carlos.lago@uneatlantico.es, florent.osmani@uneatlantico.es, UNSPECIFIED (2023) La influencia del ciclo menstrual en el entrenamiento de fuerza: revisión bibliográfica. MLS Sport Research, 3 (1). ISSN 2792-7156

Article Subjects > Biomedicine Europe University of Atlantic > Research > Articles and books Abierto Inglés Aims Nuclear envelope integrity is essential for compartmentalisation of nucleus and cytoplasm. Importantly, mutations in genes encoding nuclear envelope and associated proteins are the second-highest cause of familial dilated cardiomyopathy. One such nuclear envelope protein that causes cardiomyopathy in humans and affects mouse heart development is Lem2. However, its role in heart remains poorly understood. Methods and results We generated mice in which Lem2 was specifically ablated either in embryonic cardiomyocytes (Lem2 cKO) or adult cardiomyocytes (Lem2 iCKO) and carried out detailed physiological, tissue and cellular analyses. High resolution episcopic microscopy was used for 3D reconstructions and detailed morphological analyses. RNA-sequencing and immunofluorescence identified altered pathways and cellular phenotypes, and cardiomyocytes were isolated to interrogate nuclear integrity in more detail. In addition, echocardiography provided physiological assessment of Lem2 iCKO adult mice. We found that Lem2 was essential for cardiac development, and hearts from Lem2 cKO mice were morphologically and transcriptionally underdeveloped. Lem2 cKO hearts displayed high levels of DNA damage, nuclear rupture, and apoptosis. Crucially, we found that these defects were driven by muscle contraction as they were ameliorated by inhibiting myosin contraction and L-type calcium channels. Conversely, reducing Lem2 levels to ∼45% in adult cardiomyocytes did not lead to overt cardiac dysfunction up to 18 months of age. Conclusions Our data suggest that Lem2 is critical for integrity at the nascent nuclear envelope in fetal hearts, and protects the nucleus from the mechanical forces of muscle contraction. In contrast, the adult heart is not detectably affected by partial Lem2 depletion, perhaps owing to a more established nuclear envelope and increased adaptation to mechanical stress. Taken together, these data provide insights into mechanisms underlying cardiomyopathy in patients with mutations in Lem2 and cardio-laminopathies in general. metadata Ross, Jacob A and Arcos-Villacis, Nathaly and Battey, Edmund and Boogerd, Cornelis and Avalos Orellana, Constanza and Marhuenda, Emilie and Swiatlowska, Pamela and Hodzic, Didier and Prin, Fabrice and Mohun, Tim and Catibog, Norman and Tapia Martínez, Olga and Gerace, Larry and Iskratsch, Thomas and Shah, Ajay M and Stroud, Matthew J mail UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, olga.tapia@uneatlantico.es, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED, UNSPECIFIED (2023) Lem2 is essential for cardiac development by maintaining nuclear integrity. Cardiovascular Research. ISSN 0008-6363

Book Section Subjects > Teaching Europe University of Atlantic > Research > Articles and books Abierto Español El debate en formato de Liga de debate se ha venido conformando en los últimos años como una actividad de extensión curricular o cultural en la mayoría de universidades en España. Sin embargo, son escasos los estudios empíricos que muestren la percepción de mejora real por parte del alumnado. Por tanto, se plantea un estudio global enfocado en la Liga de debate como herramienta educativa en la enseñanza universitaria. Para ello, como primer paso, se realiza un diagnóstico del alumnado universitario y la evolución de las habilidades necesarias para el debate después de la experiencia formativo-práctica realizada en la Universidad Europea del Atlántico (Cantabria) durante el curso 2020-2021. La muestra incluye a 153 alumnos procedentes de diversas carreras. El instrumento es una encuesta, con la escala de Likert, aplicada antes y después de la Liga. Los resultados revelan una mejora sustancial de conocimientos y habilidades después de haber participado en esta actividad. Este diagnóstico refuerza la hipótesis inicial sobre la efectividad de la Liga de Debate como actividad formativo-práctica y sienta bases para la definición y pilotaje de la misma como una metodología educativa emergente de aprendizaje cooperativo en el entorno universitario metadata Alexeeva-Alexeev, Inna and Alonso-Campo, María Araceli mail inna.alexeeva@uneatlantico.es, araceli.alonso@uneatlantico.es (2023) Liga de Debate como herramienta emergente para el aprendizaje cooperativo: análisis empírico de la mejora de competencias en enseñanza superior. In: Innovación educativa y formación docente: últimas aportaciones en la investigación. Dykinson, Madrid, pp. 356-365.