AlphaFold-based AI docking reveals AMPK/SIRT1-TFEB pathway modulation by traditional Chinese medicine in metabolic-associated fatty liver disease by Lulu Zhang, Yi Zheng, Mingyan Shao, Aiping Chen, Meiyi Liu, Wenlong Sun, Tianxing Li, Yini Fang, Yang Dong, Shipeng Zhao, Hui Luo, Juan Feng, Qi Wang, Lingru Li, Yanfei Zheng

“…This study investigated QGJZF’s effects in high-fat diet-induced zebrafish and golden hamsters, and in palmitate (PA) and oleic acid (OA) - induced HepG2 cells, using the SymMap database to identify potential targets and pathways of QGJZF in MAFLD and AlphaFold algorithms to predict protein structures. In vivo, QGJZF significantly alleviated hepatic lipid deposition. …”
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Fuzzy logic-based particle swarm optimization for integrated energy management system considering battery storage degradation by Oladimeji Ibrahim, Mohd Junaidi Abdul Aziz, Razman Ayop, Ahmed Tijjani Dahiru, Wen Yao Low, Mohd Herwan Sulaiman, Temitope Ibrahim Amosa

“…Overall, the FLB-PSO algorithm outperforms traditional PSO in terms of robustness to system dynamics, convergence rate, operational cost reduction, and improved energy efficiency.…”
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Risk Assessment of High-Voltage Power Grid Under Typhoon Disaster Based on Model-Driven and Data-Driven Methods by Xiao Zhou, Jiang Li

“…To investigate the impact of typhoon disasters on high-voltage power grids, a comprehensive risk assessment method that integrates model-driven and data-driven approaches is proposed, which can predict power grid faults in advance and provide support for power grid operators to generate emergency dispatching plans. …”
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Crack Detection Method of Sleeper Based on Cascade Convolutional Neural Network by Liming Li, Shubin Zheng, Chenxi Wang, Shuguang Zhao, Xiaodong Chai, Lele Peng, Qianqian Tong, Ji Wang

“…The sleeper is inputted into CEDNet for crack feature extraction to predict the coarse crack saliency map. The prediction graph is inputted into CRRNet to improve its edge information and local region to achieve optimization. …”
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Processivity and coupling in messenger RNA transcription. by Stuart Aitken, Marie-Cécile Robert, Ross D Alexander, Igor Goryanin, Edouard Bertrand, Jean D Beggs

“…We demonstrate that these alternatives have a significant impact on the predicted distributions. Models are simulated by the Gillespie algorithm, and the third and fourth moments of the resulting distribution are computed in order to characterise the length of the tail, and sharpness of the peak. …”
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The global invasion risk of rice yellow stem borer Scirpophaga incertulas Walker (Lepidoptera:Crambidae) under current and future climate scenarios. by Shravani Sanyal, A V M Subba Rao, H Timmanna, G Baradevanal, Santanu Kumar Bal, M A Sarath Chandran, P R Shashank, V K Singh, P K Ghosh

“…The pest identity was confirmed with morphological taxonomy, and the possible habitat distribution and further spread in future climate scenarios were modelled using the MaxEnt algorithm. The climate niche for S. incertulas was also established by analyzing the correlation between the pest occurrence data of 143 locations in India and seven bioclimatic variables viz., bio01, bio02, bio03, bio05, bio12, bio13, and bio15, were chosen for predicting the distribution of S. incertulas. …”
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Estimation of drought-induced forest decline of Scots pine in the Navarrese Pyrenees (Spain) by Marina Rodes-Blanco, Paloma Ruiz-Benito, Miguel A. Zavala, Inmaculada Aguado, Mariano García

“…Identifying and predicting areas affected by drought-induced forest decline using remote sensing is key for monitoring forest-responses to drought, as well as for forest conservation and management. …”
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Data Balancing Techniques Using the PCA-KMeans and ADASYN for Possible Stroke Disease Cases by Uung Ungkawa, Muhammad Avilla Rafi

“…This condition can cause the minority class prediction to be wrong because the model tends to predict the majority class. …”
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A robust, deep learning-based analysis of time-domain signals for NMR spectroscopy by Kyungdoe Han, Eunhee Kim, Kyoung-Seok Ryu, Donghan Lee

“…As a proof of concept, we present the resulting spectra, along with peak lists predicted by supplying only FID input to the deep learning algorithm. …”
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Improving winter condition simulations in SURFEX-TEB v9.0 with a multi-layer snow model and ice by G. Colas, V. Masson, F. Bouttier, L. Bouilloud, L. Pavan, V. Karsisto

“…We have developed an ice content prediction to account for the freezing and melting of the water content on the surface. …”
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The Stability and Failure of Deep Underground Structures at Potash Mining Deposits by Yiqiang Zhang, Siarhei Lapatsin, Michael Zhuravkov, Guangbin Yu, Ivan Karpovich

“…The numerical simulations are conducted using a specific coupled algorithm of the finite element method (FEM) and distinct element method (DEM), which allows not only the prediction of dangerous zones in the undermined rock mass but also to simulation of the block fracture of the rock mass directly. …”
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Immune status assessment based on plasma proteomics with meta graph convolutional networks by Min Zhang, Nan Xu, Qi Cheng, Jing Ye, Shiwei Wu, Haoliang Liu, Chengkui Zhao, Lei Yu, Weixing Feng

“…Abstract Plasma proteins, especially immune-related proteins, are vital for assessing immune health and predicting disease risks. Despite their significance, the link between these proteins and systemic immune function remains unclear. …”
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Calibration Transfer of Soil Total Carbon and Total Nitrogen between Two Different Types of Soils Based on Visible-Near-Infrared Reflectance Spectroscopy by Xue-Ying Li, Yan Liu, Mei-Rong Lv, Yan Zou, Ping-Ping Fan

“…The RMSEP decreased from 2.42 to approximately 0.04 for TN and from 15.74 to approximately 0.4 for TC. The WMPDS-S/B algorithm had advantages in selecting fewer known samples and obtaining better prediction results. …”
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Interpretable machine learning model of effective mass in perovskite oxides with cross-scale features by Changjiao Li, Zhengtao Huang, Hua Hao, Zhonghui Shen, Guanghui Zhao, Ben Xu, Hanxing Liu

“…The interpretability of machine learning reveals associations between input features and predicted physical properties in models, which are essential for discovering new materials. …”
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Enhancing decision-making on detractor-causing failures: an approach combining data mining and machine learning by Yuri A. V. da Silva, Geraldo Cardoso de Oliveira Neto, Gustavo Lima, Sidnei A. de Araújo, Rodrigo Neri Bueno da Silva, Francisco Elanio Bezerra, Marlene Amorim

“…In this context, this study proposes a methodology that combines data mining (DM) and machine learning (ML) to analyze and predict the root causes of detractors using transactional data from the big data repository of a major sports retail company. …”
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Demystifying multiple sclerosis diagnosis using interpretable and understandable artificial intelligence by Chadaga Krishnaraj, Khanna Varada Vivek, Prabhu Srikanth, Sampathila Niranjana, Chadaga Rajagopala, Palkar Anisha

“…Hence, supervised machine learning (ML) algorithms and several hyperparameter tuning techniques, including Bayesian optimization, have been utilized in this study to predict MS in patients. …”
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Strategies and Challenges in Detecting XSS Vulnerabilities Using an Innovative Cookie Collector by Germán Rodríguez-Galán, Eduardo Benavides-Astudillo, Daniel Nuñez-Agurto, Pablo Puente-Ponce, Sonia Cárdenas-Delgado, Mauricio Loachamín-Valencia

“…Machine learning models were developed to classify suspicious web domains and predict their vulnerability to XSS attacks. Additionally, clustering algorithms enabled user segmentation based on cookie data, identification of behavioral patterns, enhanced personalized web recommendations, and browsing experience optimization. …”
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The Impact of AI-Driven Application Programming Interfaces (APIs) on Educational Information Management by David Pérez-Jorge, Miriam Catalina González-Afonso, Anthea Gara Santos-Álvarez, Zeus Plasencia-Carballo, Carmen de los Ángeles Perdomo-López

“…The findings highlight five main benefits: data interoperability, personalized learning, automated feedback, real-time student monitoring, and predictive performance analytics. All studies addressed personalization, 74.1% focused on platform integration, and 37% examined automated feedback. …”
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Maglev Derived Systems: An Interoperable Freight Vehicle Application Focused on Minimal Modifications to the Rail Infrastructure and Vehicles by Jesus Felez, Miguel A. Vaquero-Serrano, William Z. Liu, Carlos Casanueva, Michael Schultz-Wildelau, Gerard Coquery, Pietro Proietti

“…Target speed profiles were precomputed using dynamic programming, while a model predictive control algorithm determined the optimal train state and control trajectories. …”
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Mapping the landscape of AI and ML in vaccine innovation: A bibliometric study by Jirui Niu, Ruotian Deng, Zipu Dong, Xue Yang, Zhaohui Xing, Yin Yu, Jian Kang

“…By leveraging data-driven insights and predictive modeling, AI can streamline processes such as antigen discovery, clinical trial design, and risk assessment, thereby enabling faster responses to public health emergencies. …”
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