Single-Cell Sequence and Machine Learning Identify a CD79A+B Cells-Related Transcriptional Signature for Predicting Clinical Outcomes and Immune Microenvironment in Breast Cancer by Haihong Hu, Wendi Zhan, Hongxia Zhu, Bo Hao, Ting Yan, Jingdi Zhang, Siyu Wang, Taolan Zhang

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Using graph neural network and symbolic regression to model disordered systems by Ruoxia Chen, Mathieu Bauchy, Wei Wang, Yizhou Sun, Xiaojie Tao, Jaime Marian

“…The accuracy of MD simulations depends on the precision of the interatomic potential function, which dictates the calculations of atom movements. …”
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A Novel Evolutionary Deep Learning Approach for PM_2.5 Prediction Using Remote Sensing and Spatial–Temporal Data: A Case Study of Tehran by Mehrdad Kaveh, Mohammad Saadi Mesgari, Masoud Kaveh

“…Training LSTM models, however, is an NP-hard problem, with gradient-based methods facing limitations such as getting trapped in local minima, high computational costs, and the need for continuous objective functions. To overcome these issues, we propose integrating the novel orchard algorithm (OA) with LSTM to optimize air pollution forecasting. …”
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Comprehensive examination of resting state fMRI connectomics yields new insights into brain function deficits in Gulf War illness after accounting for heterogeneity in brain impair... by Guangming Yang, Robert W. Haley, Ying Guo, Kaundinya S. Gopinath

“…Resting state fMRI (rsfMRI) is a uniquely useful brain imaging technique in that in a 10-min fMRI scan it can probe numerous brain function domains simultaneously. In this study, we employed a connectomics approach and machine learning on rsfMRI data from a cohort of GW veterans to extract neuroimaging biomarkers specific to each of the three Haley GWI syndromes. …”
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Clinical Phenotype Identification and Validation of Patients with Sepsis in the Intensive Care Unit by GONG Chao, YU Na, CHEN Haoran

“…The phenotype 1 patients had the highest risk of death (28-day mortality of 46.4%), dominated by abnormal renal function and elevated disease severity scores, while the phenotype 3 patients had the lowest risk of death (28-day mortality of 11.2%), and the best neurological function score. …”
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Analyse de pratiques de tutorat dans un campus numérique de maîtrise de français langue étrangère à distance by Christelle Celik

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Exploring the biological functions and immune regulatory roles of IRAK3, TNFRSF1A, CX3CR1, and JUNB in T2DM combined with MAFLD: integrated bioinformatics and single-cell analysis by Qin Wang, Xiaoqi Li, Kaidierdan Wushoulaji, Jinyang Wang, Li Wan, Ye Yang, Xueli Gong

“…Functional enrichment analysis, immune infiltration analysis, and validation of gene significance in T2DM combined with MAFLD progression were conducted using animal experiments to understand the biological functions and immunomodulatory roles of key biomarkers. …”
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Diabetes-related distress and psychological burden in patients with type 1 and type 2 diabetes – the role of child maltreatment, personality functioning, and epistemic trust: findi... by Sandra Zara, Imogen Carla Ullrich, Anna Maria Leveling, Friederike Gisela Genoveva Saretzki, Jana Schmitz, Michael Eckhard, Johannes Kruse, Johannes Kruse, Johannes Kruse, Hanna Kampling, Hanna Kampling

“…We included epistemic trust (openness for social learning) and its impairments mistrust (the tendency to consider information sources as unreliable or ill-intended) and credulity (lack of vigilance and discrimination between trustworthy and untrustworthy information) as covariates.MethodsIn a sample of n=119 patients with type 1 or 2 diabetes aged 18-69, self-report questionnaires assessed diabetes-related distress (PAID-5), psychological burden (PHQ-D, PHQ-9, PHQ-15), child maltreatment (CTQ), personality functioning (OPD-SQS), and epistemic trust, mistrust, and credulity (ETMCQ). …”
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Frontotemporal structure preservation underlies the protective effect of lifetime intellectual cognitive reserve on cognition in the elderly by Dandan Wang, Xin Li, Mingxi Dang, Shaokun Zhao, Feng Sang, Zhanjun Zhang

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Insulator detection based on SE-YOLOv5s by Qing TIAN, Rong HU, Zuoyong LI, Yuanzheng CAI, Zhaochai YU

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YOLO-WWBi: An Optimized YOLO11 Algorithm for PCB Defect Detection by Yi Zhao, Zhidi Jiang

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Predicting amyloid proteins using attention-based long short-term memory by Zhuowen Li

“…It can be recognized by severe memory impairment in the late stage, affecting cognitive function and general daily living. Reliable evidence confirms that the enhanced symptoms of AD are linked to the accumulation of amyloid proteins. …”
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An Aeromagnetic Compensation Algorithm Based on a Temporal Convolutional Network by Han Wang, Boxin Zuo

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History and Activities Developed by Student Scientific Societies in Latin American Medical Education by Castro-Rodríguez, Yuri Alejandro

“…Introduction: Student scientific societies (SSS) are learning communities where students develop their research competencies. …”
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An Adaptive CNN-Based Approach for Improving SWOT-Derived Sea-Level Observations Using Drifter Velocities by Sarah Asdar, Bruno Buongiorno Nardelli

“…We train the model with a custom loss function that accounts for the differences between geostrophic velocities computed from SWOT sea-surface topography and simultaneous in-situ drifter velocities. …”
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Supporting the editing of dot maps using the spectral clustering algorithm by Dziuba Natalia, Szombara Stanisław

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SVF: Support Vector Federation by Mirko Polato, Roberto Esposito, Lorenzo Sciandra

“…In recent years, Federated Learning applied to neural networks has garnered significant attention, yet applying this approach to other machine learning algorithms remains underexplored. …”
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How to think about designing smart antibodies in the age of genAI: integrating biology, technology, and experience by Andrew Buchanan, Eric Bennett, Rebecca Croasdale-Wood, Andreas Evers, Brian Fennell, Norbert Furtmann, Konrad Krawczyk, Sandeep Kumar, Christopher James Langmead, Melody Shahsavarian, Christine Elaine Tinberg

“…The field is now transitioning from classical monospecific antibodies to innovative smart biologics that employ diverse mechanisms of action, such as targeting, antagonism, agonism, and target-independent function. This evolution is being assisted, augmented, and potentially disrupted by artificial intelligence and machine learning (AI/ML) technologies. …”
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An Experimental Comparison of Self-Adaptive Differential Evolution Algorithms to Induce Oblique Decision Trees by Rafael Rivera-López, Efrén Mezura-Montes, Juana Canul-Reich, Marco-Antonio Cruz-Chávez

“…Our proposal includes (1) an alternative initialization strategy that reduces redundant nodes and (2) a fitness function that penalizes excessive leaf nodes, promoting smaller and more accurate decision trees. …”
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ENDNet: Extra-Node Decision Network for Subgraph Matching by Masaki Shirotani, Motoki Amagasaki, Masato Kiyama

“…Although graph neural networks (GNNs) are commonly used in learning-based subgraph matching, they face challenges due to their convolution process. …”
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