Softening of Vibrational Modes and Anharmonicity Induced Thermal Conductivity Reduction in a‐Si:H at High Temperatures by Zhuo Chen, Yuejin Yuan, Yanzhou Wang, Penghua Ying, Shouhang Li, Cheng Shao, Wenyang Ding, Gang Zhang, Meng An

“…In this study, we developed a neuroevolution machine learning potential based on first‐principles calculations of energy, forces, and virial, which enables accurate modeling of interatomic interaction in both a‐Si:H and a‐Si systems. …”
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Advancements and Challenges in Video-Based Deception Detection: A Systematic Literature Review of Datasets, Modalities, and Methods by Yeni Dwi Rahayu, Chastine Fatichah, Anny Yuniarti, Yusti Probowati Rahayu

“…This review makes several novel contributions to advance the field: 1) provides a comprehensive framework for dataset evaluation and development; 2) identifies optimal strategies for multimodal integration and temporal modeling; 3) presents a structured approach to addressing ethical considerations; and 4) offers a detailed roadmap for future research priorities. …”
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Dynamic Dwell Time Adjustment in Wire Arc-Directed Energy Deposition: A Thermal Feedback Control Approach by Md Munim Rayhan, Abderrachid Hamrani, Fuad Hasan, Tyler Dolmetsch, Arvind Agarwal, Dwayne McDaniel

“…Future work should focus on integrating multi-axis thermal sensors, extending the framework to multi-material deposition scenarios and implementing machine learning algorithms for predictive thermal modeling.…”
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Advanced Human Pose Estimation and Event Classification Using Context-Aware Features and XGBoost Classifier by Wasim Wahid, Aisha Ahmed AlArfaj, Ebtisam Abdullah Alabdulqader, Touseef Sadiq, Hameedur Rahman, Ahmad Jalal

“…This paper presents an advanced approach to Human Pose Estimation (HPE) and Semantic Event Classification (SEC), emphasizing the need for sophisticated human skeleton models, context-aware feature extraction, and machine learning techniques for precise event recognition in daily life logs. …”
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Batch Reactor Design and Conception at Laboratory Scale for Solid-State Anaerobic Digestion: Practical Comparison Between 3D-Printed Digesters and Conventional Methods by Arnaud Dujany, Franco Otaola, Laura André, Amar Naji, Denis Luart, Mikel Leturia, André Pauss, Thierry Ribeiro

“…This study explores the feasibility of using 3D printing to rapidly design cost-effective laboratory-scale digesters for optimization experiments. Batch reactors were designed using fused deposition modeling (FDM) with polylactic acid (PLA) and stereolithography (SLA) with High Temp V2 resin. …”
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Gut microbiome alterations and hepatic encephalopathy post-TIPS in liver cirrhosis patients by Shengpeng Li, Zhengguo Xu, Hua Diao, An Zhou, Dianji Tu, Sumin Wang, Yunxuan Feng, Xiaojie Feng, Yi Lai, Shiming Yang, Bo Tang

“…Conclusion Multiple machine learning models revealed that P.vulgatus may serve as a significant predictive microbe for hepatic encephalopathy after TIPS, which may be closely related to its ability to metabolize ammonia. …”
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AI-driven discovery of synergistic drug combinations against pancreatic cancer by Mohsen Pourmousa, Sankalp Jain, Elena Barnaeva, Wengong Jin, Joshua Hochuli, Zina Itkin, Travis Maxfield, Cleber Melo-Filho, Andrew Thieme, Kelli Wilson, Carleen Klumpp-Thomas, Sam Michael, Noel Southall, Tommi Jaakkola, Eugene N. Muratov, Regina Barzilay, Alexander Tropsha, Marc Ferrer, Alexey V. Zakharov

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Classification of left and right-hand motor imagery in acute stroke patients using EEG microstate by Shiyang Lv, Xiangying Ran, Mengsheng Xia, Yehong Zhang, Ting Pang, Xuezhi Zhou, Zongya Zhao, Yi Yu, Zhixian Gao

“…Significant features were used to construct classification models using Linear Discriminant Analysis(LDA), Support Vector Machines(SVM), and K-Nearest Neighbors(KNN) algorithms. …”
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On the Effects of Parameters on Galaxy Properties in CAMELS and the Predictability of Ωm by Gabriella Contardo, Roberto Trotta, Serafina Di Gioia, David W. Hogg, Francisco Villaescusa-Navarro

“…Recent analyses of cosmological hydrodynamic simulations from CAMELS have shown that machine learning models can predict the parameter describing the total matter content of the universe, Ω _m , from the features of a single galaxy. …”
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Air pollution’s toll on adverse birth outcomes: key research insights from Chinese epidemiological studies by Hui Chang, Hui Chang, Hui Chang, Wanting Sun, Yuanyuan Tian, Yuanyuan Tian, Jing Wu, Yanru Yue, Yanru Yue, Wenhua Li, Wenhua Li, Xin Zhao, Xin Zhao, Xiaoan Zhang, Jian Jin, Jian Jin

“…Crucially, our analysis demonstrates how regional policy intervention attenuated birth risks in high-exposure zones, offering actionable models for policymakers. To resolve mechanistic uncertainties, we propose integrating machine learning and multi-omics approaches in future research. …”
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Automatic detection of lucky bamboo nodes based on Improved YOLOv7 by Jing Zhang, Jing Zhang, Jing Zhang, Ruoling Deng, Ruoling Deng, Ruoling Deng, Chengzhi Cai, Erpeng Zou, Haitao Liu, Haitao Liu, Mingxin Hou, Xinzhi Chen, Huamin Lin, Zhenye Wei

“…The model integrates a Squeeze-and-Excitation (SE) attention mechanism into the feature extraction network to enhance target localization and introduces a Weighted Intersection over Union (WIoU) loss function to optimize bounding box regression. …”
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Enhancing breast cancer classification using a deep sparse wavelet autoencoder approach by Sarah A. Alzakari, Salima Hassairi, Amel Ali Al. Hussan, Ridha Ejbali

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The Importance of the Deposit-Return System of Packaging in the Circular Economy System: Slovak Innovation Experience for Ukraine

“…Deposit return systems (DRSs) have proven effective in many EU countries and are gaining popularity. The Slovak DRS model, involving the widespread use of vending machines in retail stores and balanced incentives across the beverage supply chain, is effective and could serve as a model for Ukraine, as it aligns its systems with EU standards.…”
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Trauma team activation criteria for potential major trauma in the adult population: a narrative review by Alberto Garrido Callén, Manuel Pérez Torres, Dovami Vasco Castaño, Cui Jie Cui Liu, María González Gómez, María Muñoz Varea, Alfredo Bardal Ruiz, Sonia López Cuenca, Ana Martin Pellicer, Carmen Débora Merino Vega, Ignacio Fernandéz Martín-Caro, Diego Maqueda Lluva, Manuel Pérez Marquéz

“…Moving forward, continued research with new machine learning models and collaboration among trauma experts may be crucial for enhancing the precision and effectiveness of trauma triage, ultimately leading to improved patient outcomes and optimal resource allocation.…”
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Maximum carbon uptake potential through progressive management of plantation forests in Guangdong Province, China by Xueyan Li, Chongyuan Bi, Jianping Wu, Chaoqun Zhang, Wenting Yan, Zhenzhen Xiao, Ying-Ping Wang, Jiashun Ren, Yongxian Su

“…Here we employed fine-resolution satellite data, forest growth models, and machine learning to identify key drivers of carbon accumulation. …”
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Correlation between metformin use and mortality in acute respiratory failure: a retrospective ICU cohort study by Yunlin Yang, Jinfeng Liu, Yi Hou, Yuxun Wei, Liang Huang, Liang Huang, Wei Wei

“…We applied Kaplan–Meier survival curves, Cox proportional hazards models, and logistic regression to assess associations. …”
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Simulation analysis of residual stresses in cutting of spiral bevel gear tooth surfaces by the forming method by DAI Pengju, ZHANG Fengshou, MENG Qinghui

“…A response surface prediction model was developed to determine the optimal combination of cutting parameters, which was then validated through tests.ResultsThe results indicate that the machined tooth surface is initially characterized by tensile stress, which rapidly transitioned to compressive stress along the depth direction before gradually diminishing to zero. …”
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Artificial Intelligence in the Oil and Gas Industry: Applications, Challenges, and Future Directions by Marcelo dos Santos Póvoas, Jéssica Freire Moreira, Severino Virgínio Martins Neto, Carlos Antonio da Silva Carvalho, Bruno Santos Cezario, André Luís Azevedo Guedes, Gilson Brito Alves Lima

“…The results highlight the transformative impact of AI on production operations, with key applications including optimizing operations through real-time data analysis, predictive maintenance to anticipate failures, advanced reservoir management through improved modeling, image and video analysis for continuous equipment monitoring, and enhanced safety through immediate risk detection. …”
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Research on the Timing of Replacing Worn Milling Cutters by Using Wear Transition Percentage Constructed Based on Spindle Current Clutter Signals by Zhihao Liu, Min Wang, Zhishan Wang, Tao Zan, Xiangsheng Gao, Peng Gao

“…To address this issue, a novel method based on the wear transition percentage has been proposed to determine the optimal timing of replacing worn tools. This method does not require measuring tool wear and is suitable for different machining parameters. …”
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Revolutionizing diabetes treatment: computational insights into 4-hydroxy isoleucine derivatives and advanced molecular screening for antidiabetic compounds by Lakshmi Mounika Kelam, Manjinder Singh Gill, M. Elizabeth Sobhia

“…Methods: A multi-step computational workflow was employed to identify and optimize 4HILe derivatives as antidiabetic agents. …”
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