Gut microbial composition associated with risk of premature aging in women with Yin-deficiency constitution by Yingying Zhai, Yingying Zhai, Jing Li, Jing Li, Yanqi Cao, Yanqi Cao, Yufei Li, Yufei Li, Xuejie Bao, Xuejie Bao, Jinfeng Liang, Jinfeng Liang, Qi Liu, Qi Liu, Yifan Xia, Ruoxi Yu

“…The YinDC group had the most functional gene pathways associated with the metabolism.ConclusionOur study demonstrated that the gut microbiota was associated with premature aging in women with YinDC, potentially providing preliminary evidence and guidance for personalized anti-aging strategies.…”
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PathNetDRP: a novel biomarker discovery framework using pathway and protein–protein interaction networks for immune checkpoint inhibitor response prediction by Dohee Lee, Jaegyoon Ahn, Jonghwan Choi

“…Given these limitations, we developed PathNetDRP, a framework that integrates biological pathways, protein-protein interaction networks, and machine learning to identify functionally relevant biomarkers for ICI response prediction. …”
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SELECTION OF DIGITAL TOOLS FOR ORGANIZING STUDENTS' GROUP WORK IN DISTANCE EDUCATION by Olena G. Glazunova, Andrii M. Hurzhii, Valentyna I. Korolchuk, Tetiana V. Voloshyna

“…To obtain expert assessment of the defined criteria and indicators, we engaged seventeen researchers and educators who have practical experience using digital tools in distance learning. Our study identified three important criteria for selecting digital tools for group work with educational content, namely: design, functional-technological, education-communication ones. …”
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Unveiling the impact of bisphenol a exposure on gene expression and immune response in diabetic nephropathy through integrative toxicogenomics and molecular dynamics approaches by Yan Zhang, Shan Lu, Yijun Dong, Jin Shang

“…Enrichment analyses were performed to elucidate the functional implications of these genes, and machine learning models (LASSO, RF, SVM-RFE) were employed to identify key feature genes. …”
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Bridging the Gap: ChatGPT’s Role in Enhancing STEM Education by Lingfei Luan, Xi Lin, Yan Dai

“…Investigation into collaboration dynamics of learning found that feedback given by humans tends to be more positive (63 vs. 40 in sentiment score) and also more focused on improvement and understanding. …”
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A Frequency-Shifting Variational Mode Decomposition-Based Approach to MI-EEG Signal Classification for BCIs by Haiqin Xu, Shahzada Ali Hassan, Waseem Haider, Youchao Sun, Xiaojun Yu

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Integration of multi-omics profiling reveals an epigenetic-based molecular classification of lung adenocarcinoma: implications for drug sensitivity and immunotherapy response predi... by Ning Wang, Yinan Li, Yaoyao Wang, Wenting Wang

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Brain Tumour Segmentation Using Choquet Integrals and Coalition Game by Makhlouf Derdour, Mohammed El Bachir Yahiaoui, Moustafa Sadek Kahil, Mohamed Gasmi, Mohamed Chahine Ghanem

“…While many studies have explored ensemble learning techniques in this area, most rely on aggregation functions like the Weighted Arithmetic Mean (WAM) without accounting for the interdependencies between classifier subsets. …”
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Multimodal Fusion and Cutting-Edge AI-Based Smart Vending Machines for Electronic Component Management by M. Karthiga, Syarifah Bahiyah Rahayu, E. Suganya, S. Sankarananth, S. Sountharrajan, K. Venkatesan

“…YOLO v8 and transfer learning are integrated along with custom loss functions and model optimisation to produce a model that significantly outperforms existing solutions. …”
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Timing-specific effects of single-session M1 anodal tDCS on motor sequence retention in healthy older adults by Rohan Puri, Mark R. Hinder, Melanie Krüger, Jeffery J. Summers

“…Anodal transcranial direct current stimulation (tDCS) may assist in counteracting age-related decline in cognitive and motor functions. The current study investigated the potential impact of anodal tDCS, and the timing of its application, in mitigating age-related deficits in motor sequence learning.Forty-eight healthy older adults received, over the primary motor cortex (M1), tDCS – anodal and sham at least 1 week apart – before, during or after an explicit sequence-learning task with electrophysiological measures of corticospinal excitability (CSE) and short-interval intracortical inhibition (SICI) also obtained.Bayesian analyses revealed no generalised benefit of anodal tDCS to motor acquisition and immediate retention. …”
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A Hybrid Efficient U-Net Framework for Detection of Anterior Belly of the Digastric Muscle on Ultrasonography by Sule Erdem, Suheda Erdem, Muammer Turkoglu, Abdulkadir Sengur, Nebras M. Sobahi

“…The digastric muscle is an important muscle involved in functions such as chewing and swallowing. Ultrasonography is the preferred method for imaging the soft tissues of the head and neck but is highly operator-dependent. …”
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Desarrollo social y educación superior / Social Development and Higher Education by Carolina España Chavarría

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Modern digital educational tools and digital competence: analysis of cases and trends by O. V. Kalimullina, I. V. Trotsenko

“…The author of this paper attempted to structure and characterize the existing digital educational tools in terms of functions and capabilities for users, characteristics of user interactions in tools. …”
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Lactylation associated biomarkers and immune infiltration in aortic dissection by Jianfeng Ye, Yuntao Fu, Yuanjia Ke, Huanting Liu, Sini Fang, Yumeng Lei, Ying Mao, Liqiu Yan, Youcheng Wang

“…Machine learning methods, including LASSO and Random Forest, were employed to identify key diagnostic genes. …”
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Development of a neural network for diagnosing the risk of depression according to the experimental data of the stop signal paradigm by M. O. Zelenskih, A. E. Saprygin, S. S. Tamozhnikov, P. D. Rudych, D. A. Lebedkin, A.  N. Savostyanov

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Optimizing hybrid models for forest leaf and canopy trait mapping from EnMAP hyperspectral data with limited field samples by Nizom Farmonov, Susanne Walden, Eric Martinée, Christian Lampei, Mona Schreiber, Lars Opgenoorth, Anjaharinony Andry Ny Aina Rakotomalala, Tobias Müller, Nina Farwig, Stefan Pinkert, Lucy Saueressig, Annabell Rosemarie Wagner, Robert R. Junker, Jochem Verrelst, Jörg Bendix

“…Accurate estimation of functional vegetation traits is essential for understanding ecosystem dynamics and supporting environmental monitoring. …”
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Integrated pixel-level crack detection and quantification using an ensemble of advanced U-Net architectures by Rakshitha R, Srinath S, N Vinay Kumar, Rashmi S, Poornima B V

“…A key contribution of this study is the evaluation of loss functions, including Binary Cross-Entropy (BCE) Loss, Dice Loss, and Binary Focal Loss. …”
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Research on the Wetland Vegetation Classification Method Based on Cross-Satellite Hyperspectral Images by Min Yang, Jing Qin, Xiaodan Wang, Yanfeng Gu

“…Supervised contrastive learning is utilized to prevent redundant learning of the same training images. …”
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Identification and attribution analysis of integrated ecological zones based on the XGBoost-SHAP model: A case study of Chengdu, China by Xiaobin Huang, Xiaosheng Liu, Yuanhang Jin, Xue Gao, Youliang Chen

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Classification of SERS spectra for agrochemical detection using a neural network with engineered features by Mateo Frausto-Avila, Monserrat Ochoa-Elias, Jose Pablo Manriquez-Amavizca, María del Carmen González-López, Gonzalo Ramírez-García, Mario Alan Quiroz-Juárez

“…In this context, we present a machine-learning model based on a feedforward neural network for the rapid and accurate classification of SERS spectra. …”
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