Computational simulation of short-range order structures in high-entropy alloys: a review on formation patterns, multiscale characterization, and performance modulation mechanisms by Hongyang Liu, Bo Chen, Rong Chen, Jingzhi He, Dongdong Kang, Jiayu Dai

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Fracture Resistance and Stress Distribution Pattern of Different Posts-Core Systems in Immature Teeth: An In Vitro Study and 3D Finite Element Analysis by Shahnaz Khadar, Kishor Sapkale, Pravinkumar G. Patil, Sayed Abrar, Manoj Ramugade, Febel Huda

“…The purpose of this study was to evaluate the fracture resistance of simulated immature teeth restored with different intraradicular posts and assess their stress distribution pattern using 3D Finite Element Analysis (FEA). Methods. …”
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Characterising the spatio-temporal patterns of water quality parameters in the cradle of humankind world heritage site using Sentinel-2 and random forest regressor by Sinesipho Ngamile, Sinesipho Ngamile, Mahlatse Kganyago, Sabelo Madonsela, Sabelo Madonsela, Vuyelwa Mvandaba

“…These findings highlight the potential of Sentinel-2 MSI data and machine learning models for monitoring dynamic water quality variations in freshwater ecosystems.…”
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Surgery-specific patterns of perioperative amino acid administration and associated acute kidney injury risk: a large-scale retrospective cohort study by Jin Lina, Zhang Rui, Yu Xianjun, Wu Xiuqing, Zhang Yingli, Huang Yukun, Zhang Yiwei, Huang Changshun, Zhu Binbin

“…Abstract Background Recent trials demonstrated renoprotective effects of amino acid infusion in cardiac surgery patients, but real-world utilization patterns and outcomes across surgical specialties remain unknown. …”
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Coastal Urban Ecological Security Pattern Identification Integrating Land Subsidence Factors: A Deep Learning-Based Case Study of Zhuhai City by Yuan Shaoxiong, Gong Qinghua, Ye Yuyao, Wang Jun, Hao Yinlei, Zhang Yaze, Liu Bowen

“…Although Ecological Security Pattern (ESP) construction is important for ecosystem stability and sustainable development, traditional approaches rarely incorporate vertical geological factors, such as land subsidence. …”
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Recognition of Process Disturbances for an SPC/EPC Stochastic System Using Support Vector Machine and Artificial Neural Network Approaches by Yuehjen E. Shao

“…This study proposes the integration of support vector machine (SVM) and artificial neural network (ANN) approaches to recognize the disturbance patterns of the underlying disturbances. …”
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Selection of target-binding proteins from the information of weakly enriched phage display libraries by deep sequencing and machine learning by Tomoyuki Ito, Thuy Duong Nguyen, Yutaka Saito, Yoichi Kurumida, Hikaru Nakazawa, Sakiya Kawada, Hafumi Nishi, Koji Tsuda, Tomoshi Kameda, Mitsuo Umetsu

“…The clustering analysis of the deep sequencing data from appropriate steps revealed no distinct sequence patterns, but a Bayesian machine learning model trained with the selected deep sequencing data supplied nine clusters with distinct sequence patterns. …”
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Enhancing Student Management Through Hybrid Machine Learning and Rough Set Models: A Framework for Positive Learning Environments by Ateeq Ur Rehman Butt, Hamid Ali, Muhammad Asif, Hessa Alfraihi, Mohamad Khairi Ishak, Khalid Ammar

“…The model combines classification algorithms with rough set-based decision rules to analyze complex student data, including academic performance, behavior patterns, and levels of engagement. The ML layered approach detects patterns and outliers, supporting data-driven decisions to improve student well-being and educational outcomes. …”
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High-performance glass classification using advanced machine learning and deep learning algorithms with a comprehensive feature analysis by Mohammed Bouziane, Abdelghani Bouziane, Samia Larguech, Khatir Naima, Mohammad Salman Haque, Younes Menni

“…Exploratory Data Analysis provides significant patterns and verifies pre-determined glass classes through clustering techniques like Gaussian Mixture Models. …”
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Utilizing machine and deep learning algorithms to identify learning-related features in electroencephalography data during second language acquisition by Talal A. Aldhaheri, Sonali B. Kulkarni, Pratibha R. Bhise, Mohammed Tawfik

“…This study contributes to neurolinguistics by demonstrating how machine learning can effectively classify EEG patterns related to language learning, paving the way for future research on cognitive and computational models of SLA.…”
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Feature extraction and classification of digital rock images via pre-trained convolutional neural network and unsupervised machine learning by Masashige Shiga, Masao Sorai, Tetsuya Morishita, Masaatsu Aichi, Naoki Nishiyama, Takashi Fujii

“…To enhance the interpretability of the machine learning approach, we proposed a patch-based analysis to identify local characteristic textural patterns that contribute significantly to the classification of individual rock samples. …”
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A hybrid machine learning approach to unravel monsoon variability and meteorological dynamics of Pakistan's 2010 and 2022 historic floods by Sana Nazli, Jiahong Liu, Tianxu Song, Shan-e-hyder Soomro, Haibin Wang

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Understanding the Impact of Street Environments on Traffic Crash Risk from the Perspective of Aging People: An Interpretable Machine Learning Approach by Ketong Shen, Jian Liu, Xintao Liu

“…Specifically, we use segmented street view images to train models that predict crash risk levels based on normalized crash frequencies, with separate models developed for older and non-older populations. Interpretable machine learning methods are then employed to identify key environmental contributors and to compare their spatial contribution patterns across age groups. …”
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CodeTranFix: A Neural Machine Translation Approach for Context-Aware Java Program Repair with CodeBERT by Yiwei Lu, Shuxia Ye, Liang Qi

“…Automated program repair (APR) plays a vital role in enhancing software quality and reducing developer maintenance efforts. Neural Machine Translation (NMT)-based methods demonstrate notable potential by learning translation patterns from bug-fix code pairs. …”
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Early detection of emerging SARS-CoV-2 Variants from wastewater through genome sequencing and machine learning by Xiaowei Zhuang, Van Vo, Michael A. Moshi, Ketan Dhede, Nabih Ghani, Shahraiz Akbar, Ching-Lan Chang, Angelia K. Young, Erin Buttery, William Bendik, Hong Zhang, Salman Afzal, Duane Moser, Dietmar Cordes, Cassius Lockett, Daniel Gerrity, Horng-Yuan Kan, Edwin C. Oh

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T-cell receptor dynamics in digestive system cancers: a multi-layer machine learning approach for tumor diagnosis and staging by Changjin Yuan, Bin Wang, Hong Wang, Fang Wang, Xiangze Li, Ya’nan Zhen

“…Distinct V-J gene recombination patterns were identified, with CRC showing enrichment in TRBV*-TRBJ* combinations, while GC exhibited higher levels of γδT-cell-related recombination. …”
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Identification of a deubiquitinating gene-related signature in ovarian cancer using integrated transcriptomic analysis and machine learning framework by Suwan Hu, Mengting Wang

“…High-risk patients, as classified by the DRS, showed significantly poorer survival outcomes and distinct immune infiltration patterns compared to low-risk patients. Conclusion This study provides comprehensive insights into DUB gene expression patterns across different cell populations in ovarian carcinoma. …”
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High-resolution energy consumption forecasting of a university campus power plant based on advanced machine learning techniques by Saad A. Alsamraee, Sanjeev Khanna

“…Finally, during the deployment phase, the optimal model was employed to forecast energy demand for the full year 2023—the primary objective of this study—exhibiting high robustness through close adherence to actual demand patterns.…”
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Machine Learning-Assisted 3D Flexible Organic Transistor for High-Accuracy Metabolites Analysis and Other Clinical Applications by Caizhi Liao, Huaxing Wu, Luigi G. Occhipinti

“…Machine learning algorithms further enhance the analytical capabilities of FOT sensors by effectively processing complex data, identifying patterns, and predicting diagnostic outcomes with 100% high accuracy. …”
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Machine learning-optimized dual-band wearable antenna for real-time remote patient monitoring in biomedical IoT systems by Umar Musa, Amor Smida, Muhammad S. Yahya, Mohamed I. Waly, Jun Jiat Tiang, Nazih Khaddaj Mallat, Surajo Muhammad, Abubakar Salisu

“…Bidirectional and directional radiation patterns are noted in the E-plane, while the H-plane exhibits omnidirectional patterns at the lower and upper bands. …”
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