Shared diagnostic genes and potential mechanism between PCOS and recurrent implantation failure revealed by integrated transcriptomic analysis and machine learning by Wenhui Chen, Wenhui Chen, Wenhui Chen, Qingling Yang, Qingling Yang, Qingling Yang, Linli Hu, Linli Hu, Linli Hu, Mengchen Wang, Mengchen Wang, Mengchen Wang, Ziyao Yang, Ziyao Yang, Ziyao Yang, Xinxin Zeng, Xinxin Zeng, Xinxin Zeng, Yingpu Sun, Yingpu Sun, Yingpu Sun

“…By analyzing differentially expressed genes (DEGs) and module genes using weighted gene co-expression networks (WGCNA), functional enrichment analysis, and three machine learning algorithms, we identified twelve diseases shared genes, and two diagnostic genes, including GLIPR1 and MAMLD1. …”
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HoloMoA: a holography and deep learning tool for the identification of antimicrobial mechanisms of action and the detection of novel MoA by Zohreh Sedaghat, Benoît Courbon, Héloïse Botrel, Hélène Dugua, Pawel Tulinski, Laethitia Alibaud, Lucia Pagani, Derry Mercer, Cyril Guyard, Christophe Védrine, Sophie Dixneuf

“…Our rapid, robust, affordable and versatile tool is based on the combination of time-lapse Digital Inline Holographic Microscopy (DIHM) and Deep Learning (DL). In combination with hologram reconstruction. …”
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Industrial-Grade 3D Detection for Laser Cleaning of Metallic Components Based on Neural Radiance Fields and Temporal-Spatial Learning by Dandan Qi

“…Introduce spherical harmonic functions to replace traditional position encoding functions, enhance the anisotropic reflectance modeling ability and significantly reduce the network parameter scale. …”
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Identifying a prognostic signature for clear cell renal cell carcinoma: the convergence of single-cell and bulk sequencing with machine learning by Yude Hong, Xiao Hu, Libo Chen, Mingyong Li, Mingxiao Zhang, Weiming Deng

“…Thus, we used a novel computational framework to construct a consensus machine learning-related signature (MLRS) to predict prognosis and screen patients effectively for immunotherapy.MethodsAn integrative machine learning procedure involving 10 methods was used to contract MLRS. …”
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Moving beyond post hoc explainable artificial intelligence: a perspective paper on lessons learned from dynamical climate modeling by R. J. O'Loughlin, D. Li, R. Neale, T. A. O'Brien, T. A. O'Brien

“…In this review and perspective paper, we suggest that, in addition to using XAI methods, AI researchers in climate science can learn from past successes in the development of physics-based dynamical climate models. …”
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Automated Recipe Generation AI Tool from Food Images using Machine Learning. Approach for Ingredient Extraction and Cooking Instructions by Lwamaza, Eddy, Nuwasiima, Happy

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Type A, Or Type B, That Is The Question; A Critical Examination Of Productoriented And Process-oriented Syllabuses In Foreign Language Learning And Teaching by Abla Benbellal

“…The discussion focuses on the characteristics of both types, the different views of language and language learning that influenced the classification of the two syllabus types as well as the benefits and drawbacks of each type in foreign language learning and teaching. …”
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Deep learning analysis of fMRI data for predicting Alzheimer's Disease: A focus on convolutional neural networks and model interpretability. by Xiao Zhou, Sanchita Kedia, Ran Meng, Mark Gerstein

“…Here, we explore deep learning methods for the early detection of AD. We consider both genetic risk factors and functional magnetic resonance imaging (fMRI) data. …”
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Implementation of PAI Teacher's Professional Competence in Improving Student Learning Outcomes at SMP N 5 Negeri Agung, Way Kanan by Ayu Alawiyah, Ayu Wahyuni, Yasir Adibroto

“…This has an impact on students' learning outcomes which are still low. Administratively, learning is running, but not functionally effective. …”
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Explainable Siamese Neural Networks for Detection of High Fall Risk Older Adults in the Community Based on Gait Analysis by Christos Kokkotis, Kyriakos Apostolidis, Dimitrios Menychtas, Ioannis Kansizoglou, Evangeli Karampina, Maria Karageorgopoulou, Athanasios Gkrekidis, Serafeim Moustakidis, Evangelos Karakasis, Erasmia Giannakou, Maria Michalopoulou, Georgios Ch Sirakoulis, Nikolaos Aggelousis

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DeepSeek vs. ChatGPT vs. Claude: A comparative study for scientific computing and scientific machine learning tasks by Qile Jiang, Zhiwei Gao, George Em Karniadakis

“…Specifically, we evaluate their proficiency in solving traditional numerical problems in scientific computing as well as leveraging scientific machine learning techniques for PDE-based problems. We designed all our experiments so that a nontrivial decision is required, e.g, defining the proper space of input functions for neural operator learning. …”
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Reducing Computational Time in Pixel-Based Path Planning for GMA-DED by Using Multi-Armed Bandit Reinforcement Learning Algorithm by Rafael P. Ferreira, Emil Schubert, Américo Scotti

“…The results outstand the artificially intelligent role of the Reinforcement Learning technique in printing more efficiently functional structures.…”
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Development and Validation of Machine Learning Models for Outcome Prediction in Patients with Poor-Grade Aneurysmal Subarachnoid Hemorrhage Following Endovascular Treatment by Du S, Wu Y, Tao J, Shu L, Yan T, Xiao B, Lv S, Ye M, Gong Y, Zhu X, Hu P, Wu M

“…However, there still exists a worse percentage of poor functional outcome in patients with poor-grade aneurysmal subarachnoid hemorrhage (aSAH) undergoing EVT. …”
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An unfortunate natural experiment in learning how to provide services to those in need: The case of Ukrainian war refugees with disabilities in Warsaw and Bucharest. by Monika Nowicka, Alexandra Deliu, Bogdan Voicu, Magdalena Szarota

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Enhancing Missense Variant Pathogenicity Prediction with MissenseNet: Integrating Structural Insights and ShuffleNet-Based Deep Learning Techniques by Jing Liu, Yingying Chen, Kai Huang, Xiao Guan

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Oxidative stress affects sperm health and fertility—Time to apply facts learned at the bench to help the patient: Lessons for busy clinicians by Pallav Sengupta, Germar‐M. Pinggera, Aldo E. Calogero, Ashok Agarwal

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Inspecting the potential of thymol as a therapeutic agent for treating Alzheimer's disease by Muhammad Waleed Imran, Sanwal Sardar Nawaz, Muhammad Moaz

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A deep learning based intrusion detection system for CAN vehicle based on combination of triple attention mechanism and GGO algorithm by Hongwei Yang, Mehdi Effatparvar

“…Within the initial phase, the major features have been extracted, and TAN functions as a descriptor of feature. Then, the discriminating categorizer classifies the current features. …”
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Spacecraft Intelligent Fault Diagnosis under Variable Working Conditions via Wasserstein Distance-Based Deep Adversarial Transfer Learning by Gang Xiang, Kun Tian

“…In recent years, deep learning methods which promote the accuracy and efficiency of fault diagnosis task without any extra requirement of artificial feature extraction have elicited the attention of researchers in the field of manufacturing industry as well as aerospace. …”
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A data-centric approach to terminal unit’s fault categorization and optimal positioning in building HVAC systems using ensemble learning by Maitreyee Dey, Preeti Patel, Soumya Prakash Rana

“…The dataset comprises over 2 million data points collected from 730 TUs, enabling a comprehensive analysis of their functionality and the impact of suboptimal thermostat placements. …”
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