Classification patterns identification of immunogenic cell death-related genes in heart failure based on deep learning by Zhihui Ma, Shixin Ma, Bin Chen, Yongjun Zhang, Jinmei Zeng, Jianping Tao, Yu Hu

“…Identified HF subtypes were further refined using differentially expressed genes, allowing for the assessment of immune infiltration and functional enrichment. Advanced machine learning techniques were used to identify diagnosis-related genes, and these genes were used to construct nomogram models. …”
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Machine learning identifies PYGM as a macrophage polarization–linked metabolic biomarker in rectal cancer prognosis by Chengyuan Xu, Chengyuan Xu, Siqi Zhang, Bin Sun, Zicheng Yu, Hailong Liu

“…Clinical tissue analyses and functional assays confirmed that PYGM is upregulated in rectal cancer and promotes tumor cell proliferation, migration, and M2 macrophage polarization.ConclusionsThis study firstly highlights PYGM as a key metabolic and immunological regulator in rectal cancer, with significant prognostic and therapeutic implications. …”
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Identification of ubiquitination-related key biomarkers and immune infiltration in Crohn’s disease by bioinformatics analysis and machine learning by Wei Chen, Zeyan Xu, Haitao Sun, Wen Feng, Zhenhua Huang

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Identification of clinical diagnostic and immune cell infiltration characteristics of acute myocardial infarction with machine learning approach by Huali Jiang, Weijie Chen, Benfa Chen, Tao Feng, Heng Li, Dan Li, Shanhua Wang, Weijie Li

“…Dysregulated expression of genes was screened and functionally analyzed. Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify significant module genes associated with AMI. …”
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What can be learned about caregivers in Canada from the analysis of families claiming the Canada caregiver credit? by Sung-Hee Jeon, Yuri Ostrovsky

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FORMATION OF PROFESSIONAL COMPETENCES OF FUTURE MOTOR VEHICLE PROFILE SPECIALISTS WITH THE USE OF TECHNOLOGIES OF DISTANCE LEARNING INTERACTION by Kuchma Oleksandr, Filatov Sergiy

“…Professional competence provides the specialist with the realization of motivational and promotional, gnostic, practical and operational, communicative, control and evaluation functions in professional activity. The analysis of modern distance learning tools showed their significant potential in updating the content, forms and methods of organizing the students’ professional training for the motor vehicle area of expertise. …”
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SSCC TD: a serial and simultaneous configural-cue compound stimuli representation for temporal difference learning. by Esther Mondragón, Jonathan Gray, Eduardo Alonso, Charlotte Bonardi, Dómhnall J Jennings

“…This modification significantly broadens the range of phenomena which the TD paradigm can explain, and allows it to predict phenomena which traditional TD solutions cannot, particularly effects that depend on compound stimuli functioning as a whole, such as pattern learning and serial structural discriminations, and context-related effects.…”
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A Privacy-Masking Learning Algorithm for Online Distributed Optimization over Time-Varying Unbalanced Digraphs by Rong Hu, Binru Zhang

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Research on elite hierarchical task offloading strategy based on reinforcement learning in edge-cloud collaboration scenario by Juan FANG, Zhiyuan YE, Mengyuan ZHANG, Jiamei SHI, Ziyi TENG

“…With the development of 5G and the enrichment of application functions, applications have put forward higher requirements on the computing capabilities of terminal devices.In order to improve the computing capabilities of terminal devices on applications and reduce the processing time of tasks, it is aimed at mobile edge computing environments, a task offloading method for edge-cloud collaboration was proposed，and an elite hierarchical evolutionary algorithm combined with reinforcement learning (RL-EHEA) was designed to perform offloading decisions, so that multiple tasks with dependencies and deadlines compete for computing resources.The simulation experiment results show that, compared with genetic algorithm (GA) and elite genetic algorithm (EGA), RL-EHEA can shorten task processing time and obtain better resource allocation strategy.…”
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Machine learning model for reproducing subjective sensations and alleviating sound-induced stress in individuals with developmental disorders by Itsuki Ichikawa, Yukie Nagai, Yukie Nagai, Yasuo Kuniyoshi, Yasuo Kuniyoshi, Yasuo Kuniyoshi, Makoto Wada

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The noble character-based learning in the ornaments of Kraton Yogyakarta: A visual analysis of Javanese cultural heritage by Dwi Retno Sri Ambarwati, Tjetjep Rohendi Rohidi, Syakir Syakir, Muhammad Ibnan Syarif, Hajar Pamadhi

“…In the context of art as a language, ornament also functions as a visual language, because in Javanese culture there is a tradition to express an idea, expression, and moral message containing learning about noble morals through ornamentation.  …”
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In search of a modern character of a doctor: what examples to learn from the greats? Part I by Yu. V. Rodionova

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ML‐UrineQuant: A machine learning program for identifying and quantifying mouse urine on absorbent paper by Warren G. Hill, Bryce MacIver, Gary A. Churchill, Mariana G. DeOliveira, Mark L. Zeidel, Marcelo Cicconet

“…Abstract The void spot assay has gained popularity as a way of assessing functional bladder voiding parameters in mice, but analyzing the size and distribution of urine spot patterns on filter paper with software remains problematic due to inter‐laboratory differences in image contrast and resolution quality and non‐void artifacts. …”
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Digitalizing metallic materials from image segmentation to multiscale solutions via physics informed operator learning by Shahed Rezaei, Kianoosh Taghikhani, Alexandre Viardin, Reza Najian Asl, Ali Harandi, Nikhil Vijay Jagtap, David Bailly, Hannah Naber, Alexander Gramlich, Tim Brepols, Mustapha Abouridouane, Ulrich Krupp, Thomas Bergs, Markus Apel

“…This work presents a digital framework for metallic materials using microscale features. We explore deep learning for two primary goals: (1) segmenting experimental images to extract microstructural topology, translated into spatial property distributions; and (2) learning mappings from digital microstructures to mechanical fields using physics-informed operator learning. …”
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Scalable machine learning approach to light induced order disorder phase transitions with ab initio accuracy by Andrea Corradini, Giovanni Marini, Matteo Calandra

“…Here, we present a novel approach that combines constrained density functional theory with machine learning, yielding highly reliable interatomic potentials capable of capturing electron-hole plasma effects on structural properties. …”
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Predicting bacterial phenotypic traits through improved machine learning using high-quality, curated datasets by Julia Koblitz, Lorenz Christian Reimer, Rüdiger Pukall, Jörg Overmann

“…Abstract Predicting prokaryotic phenotypes—observable traits that govern functionality, adaptability, and interactions—holds significant potential for fields such as biotechnology, environmental sciences, and evolutionary biology. …”
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Message spreading modeling from the perspective of social psychology, differential equation dynamics, and deep learning technique by Yuntao Li, Yan Zhang, Jiazhe Lin

“…Utilizing Lyapunov functionals, we carry out a dynamical analysis of the message spreading model. …”
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Learning the therapeutic targets of acute myeloid leukemia through multiscale human interactome network and community analysis by Suruthy Sivanathan, Ting Hu

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The brain ages optimally to model its environment: evidence from sensory learning over the adult lifespan. by Rosalyn J Moran, Mkael Symmonds, Raymond J Dolan, Karl J Friston

“…Our findings suggest that the lifetime accrual of sensory experience optimizes functional brain architectures to enable efficient and generalizable predictions of the world.…”
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Arlclustering: an R package for community detection in social networks based on user interaction and association rule learning by Mohamed El-Moussaoui, Mohamed Hanine, Ali Kartit, Tarik Agouti

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