Advancing arabic dialect detection with hybrid stacked transformer models by Hager Saleh, Hager Saleh, Hager Saleh, Abdulaziz AlMohimeed, Rasha Hassan, Mandour M. Ibrahim, Saeed Hamood Alsamhi, Moatamad Refaat Hassan, Sherif Mostafa

“…Recent advances in deep learning (DL) models have shown promise in overcoming potential challenges in identifying Arabic dialects. …”
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Ratio of Skeletal Muscle Mass to Visceral Fat Area Is a Useful Marker for Assessing Left Ventricular Diastolic Dysfunction among Koreans with Preserved Ejection Fraction: An Analys... by Jin Kyung Oh, Yuri Seo, Wonmook Hwang, Sami Lee, Yong-Hoon Yoon, Kyupil Kim, Hyun Woong Park, Jae-Hyung Roh, Jae-Hwan Lee, Minsu Kim

“…This study investigated the association between the ratio of skeletal muscle mass to visceral fat area (SVR) and left ventricular diastolic dysfunction (LVDD) in patients with preserved ejection fraction using random forest machine learning. Methods : In total, 1,070 participants with preserved left ventricular ejection fraction who underwent comprehensive health examinations, including transthoracic echocardiography and bioimpedance body composition analysis, were enrolled. …”
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Quantifying Baryonic Feedback on the Warm–Hot Circumgalactic Medium in CAMELS Simulations by Isabel Medlock, Chloe Neufeld, Daisuke Nagai, Daniel Anglés-Alcázar, Shy Genel, Benjamin D. Oppenheimer, Xavier Sims, Priyanka Singh, Francisco Villaescusa-Navarro

“…Using the SIMBA and IllustrisTNG suites from the Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) project, we explore the effect of parameters governing the subgrid implementation of stellar and AGN feedback. …”
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Job satisfaction amongst special education teachers by Z. S. Alkayed, S. M. Al Ali, M. M. Al Masa’deh

“…The study contributes to understanding of the factors shaping student teachers’ perspectives and underscores the importance of promoting job satisfaction and positive attitudes among special education teachers to foster a supportive learning environment.                Practical significance of this study is that it provides valuable insights for the field of special education and teacher training. …”
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Effectiveness of flipped classrooms in Chinese students of clinical medicine major undergoing clinical practice: a meta-analysis by Xinrui Sun, Xin Yuan, Linyu Zhang, Yi Zhang, Xue Xiao, Hanmin Liu, Fang Ma

“…While flipped classrooms have gained popularity for their potential to enhance learning outcomes, the effectiveness of this approach in clinical settings remains underexplored. …”
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Trends and Gaps in Digital Precision Hypertension Management: Scoping Review by Namuun Clifford, Rachel Tunis, Adetimilehin Ariyo, Haoxiang Yu, Hyekyun Rhee, Kavita Radhakrishnan

“…The most commonly used digital technologies were mobile phones (33/46, 72%), blood pressure monitors (18/46, 39%), and machine learning algorithms (11/46, 24%). In total, 45% (21/46) of the studies either did not report race or ethnicity data (14/46, 30%) or partially reported this information (7/46, 15%). …”
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Analisis Sistem Pelaksanaan Kelas Ibu Hamil di Puskesmas Malalak dan Biaro Kabupaten Agam by Ayu Nurdiyan, Desmiwarti ., Rizanda Machmud

“…<br />Kata kunci: puskesmas, analisis sistem, kelas ibu hamil</p><p>Abstract<br />Antenatal class is a learning tool for pregnant women to obtain sufficient knowledge to prevent complication, increase coverage of antenatal visits and having child delivery at the health care practitioner. …”
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KMT2C/KMT2D-dependent H3K4me1 mediates changes in DNA replication timing and origin activity during a cell fate transition by Deniz Gökbuget, Liana Goehring, Ryan M. Boileau, Kayla Lenshoek, Tony T. Huang, Robert Blelloch

“…The causal relationships between these features and DNA replication timing (RT), especially during cell fate changes, are largely unknown. Using machine learning, we quantify 21 chromatin features predicting local RT and RT changes during differentiation in embryonic stem cells (ESCs). …”
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ARES by Josué Miguel de Oliveira, François Isnaldo Dias Caldeira, Lucas Ribeiro Monteiro, Kellen Cristina da Silva Gasque

“…Resultados: Repositórios virtuais e bibliotecas digitais, impulsionados pela popularização da EaD e do e-learning, têm impacto significativo na pesquisa global, mas a acessibilidade ainda é desigual. …”
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Measuring Empathy among Dental Students and Interns: A Cross-Sectional Study from Dammam, Saudi Arabia by Muhammad Nazir, Muhanad Alhareky, Abdulrahman Alqahtani, Leenah Alsulaimi, Reema Alotaibi, Najwa Yousef, Fatimah Abushal, Jehan Alhumaid

“…Empathy should be integrated into dental curricula for effective student learning and positive patient care outcomes.…”
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AI Chatbots and Cognitive Control: Enhancing Executive Functions Through Chatbot Interactions: A Systematic Review by Pantelis Pergantis, Victoria Bamicha, Charalampos Skianis, Athanasios Drigas

“…<b>Conclusions</b>: AI chatbots are an innovative artificial intelligence tool that can function as a digital assistant for learning and expanding executive skills, contributing to the cognitive, metacognitive, and social development of the individual. …”
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Anti-TROVE2 Antibody Determined by Immune-Related Array May Serve as a Predictive Marker for Adalimumab Immunogenicity and Effectiveness in RA by Po-Ku Chen, Joung-Liang Lan, Yi-Ming Chen, Hsin-Hua Chen, Shih-Hsin Chang, Chia-Min Chung, Nurul H. Rutt, Ti-Myen Tan, Raja Nurashirin Raja Mamat, Nur Diana Anuar, Jonathan M. Blackburn, Der-Yuan Chen

“…The biomarkers were identified for predicting ADAb development and therapeutic response using the immune-related microarray and machine learning approach. ADAb-positive patients had lower drug levels at week 24 (median=0.024 μg/ml) compared with ADAb-negative patients (median=6.38 μg/ml, p<0.001). …”
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Identifying neurobiological heterogeneity in clinical high-risk psychosis: a data-driven biotyping approach using resting-state functional connectivity by Xiaochen Tang, Yanyan Wei, Jiaoyan Pang, Lihua Xu, Huiru Cui, Xu Liu, Yegang Hu, Mingliang Ju, Yingying Tang, Bin Long, Wei Liu, Min Su, Tianhong Zhang, Jijun Wang

“…Functional connectivity (FC) features that were correlated with symptom severity were subjected to the single-cell interpretation through multikernel learning (SIMLR) algorithm in order to identify latent homogeneous subgroups. …”
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Aqueous foams in microgravity, measuring bubble sizes by Pasquet, Marina, Galvani, Nicolo, Pitois, Olivier, Cohen-Addad, Sylvie, Höhler, Reinhard, Chieco, Anthony T., Dillavou, Sam, Hanlan, Jesse M., Durian, Douglas J., Rio, Emmanuelle, Salonen, Anniina, Langevin, Dominique

“…Extracting the bubble size distribution from images of a foam surface is difficult so we have used three different procedures: manual analysis, automatic analysis with a customized Python script and machine learning analysis. Once various pitfalls were identified and taken into account, all the three procedures yield identical results within error bars. …”
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Are neurasthenia and depression the same disease entity? An electroencephalography study by Ge Dang, Lin Zhu, Chongyuan Lian, Silin Zeng, Xue Shi, Zian Pei, Xiaoyong Lan, Jian Qing Shi, Nan Yan, Yi Guo, Xiaolin Su

“…The demographic and clinical characteristics, EEG power spectral density, and functional connectivity were compared between the neurasthenia and MDD groups. Machine Learning methods such as random forest, logistic regression, support vector machines, and k nearest neighbors were also used for classification between groups to extend the identification that there is a significant different pattern between neurasthenia and MDD. …”
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Blockade of IL-17A/IL-17R Pathway Protected Mice from Sepsis-Associated Encephalopathy by Inhibition of Microglia Activation by Bo Ye, Tianzhu Tao, Andong Zhao, Liyuan Wen, Xiaofei He, Yi Liu, Qiang Fu, Weidong Mi, Jingsheng Lou

“…Septic peritonitis induced significant impairment of learning memory and exploratory activity, which was associated with a higher expression of IL-17A, IL-1β, and TNF-α in the brain homogenate. …”
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Providing a General Model for the Successful Implementation of Digital Transformation in Organizations by Haidar Ahmadi, Najme Parsaei, Seyyed Hamed Hashemi, Hamidreza Nematollahi

“…Conclusion Digital transformation extends beyond the mere adoption of emerging technologies such as artificial intelligence and machine learning; it represents a paradigm shift in how traditional management and operational practices are conducted across various functions, including product development, engineering, marketing, sales, and service delivery. …”
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Identifying the causes and consequences of pregnancy in Iranian Kurdish women under the age of 18: A grounded theory study by Javad Yoosefi lebni, Ahmad Ahmadi, Seyed Fahim Irandoost, Mandana Saki, Hossein Safari, Nafiul Mehedi

“…Results: After the data analysis and coding process, the conceptual model of causes and consequences of pregnancy in adolescents emerged, including 1) predisposing conditions (sociocultural factors: Social learning, misconceptions about fertility and childbirth, preventing stigma), 2) causal conditions (individual factors: lack of knowledge on how to prevent pregnancy, improper use of contraceptives, inadequate knowledge about the risks of pregnancy in adolescence, fear of the side effects of using contraceptives, filling the vacuum of loneliness, family factors: husband's and his family's pressure, committing her husband to life, consolidating her position in family), 3) intervening conditions (structural factors: no barriers to pregnancy, difficult access to contraceptives), 4) strategies and interactions (positive reactions: trying to prepare herself for raising a child, taking better care of herself and her child, negative reactions: trying to kill herself and the kid, fear and concealment), and 5) consequences (destructive consequences: threats to the health of the child, threat to mother's health, inadequate access to health services, constructive consequences: increase of support, strengthen the sense of empowerment). …”
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Tackling the Problem of Distributional Shifts: Correcting Misspecified, High-dimensional Data-driven Priors for Inverse Problems by Gabriel Missael Barco, Alexandre Adam, Connor Stone, Yashar Hezaveh, Laurence Perreault-Levasseur

“…With the advent of machine learning, the use of data-driven population-level distributions (encoded, e.g., in a trained deep neural network) as priors is emerging as an appealing alternative to simple parametric priors in a variety of inverse problems. …”
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Genetic Biomarkers and Circulating White Blood Cells in Osteoarthritis: A Bioinformatics and Mendelian Randomization Analysis by Yimin Pan, Xiaoshun Sun, Jun Tan, Chao Deng, Changwu Wu, Georg Osterhoff, Nikolas Schopow

“…The bioinformatics methods utilized include the Limma package, WGCNA, PPI network analysis, and machine learning algorithms. Genetic variants were used as instrumental variables to evaluate the potential causal impact of circulating white blood cell (WBC) counts on OA. …”
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