Identification and verification of biomarkers associated with neutrophils in acute myocardial infarction: integrated analysis of bulk RNA-seq, expression quantitative trait loci, a... by Guoqing Liu, Xiangwen Lv, Jiahui Qin, Xingqing Long, Miaomiao Zhu, Chuwen Fu, Jian Xie, Peichun He

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Integrated Additive Manufacturing Trajectory Control and Repair Management for Spiral Bevel Gear Using Fractional-Order PID and Adaptive Fuzzy Neural Inference System by Hiyam Adil Habeeb, Abdul Hadi Azman, Mohd Rizal Alkahari, Dzuraidah Abd Wahab, Nurhasyimah Abd Aziz

“…The ANFIS model achieves good overall tracking of amplitude variations and accurate classification of repair methods. …”
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Integrating AI predictive analytics with naturopathic and yoga-based interventions in a data-driven preventive model to improve maternal mental health and pregnancy outcomes by Neha Irfan, Sherin Zafar, Kashish Ara Shakil, Mudasir Ahmad Wani, S. N. Kumar, A. Jaiganesh, K. M. Abubeker

“…Furthermore, ensemble methods enhanced predictive performance, highlighting their ability to balance accuracy, precision, recall, and F1 score. …”
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Integrative bioinformatics and machine learning identify iron metabolism genes MAP4, GPT, and HIRIP3 as diagnostic biomarkers and therapeutic targets in Alzheimer’s disease by Xiaoqiong An, Xiangguang Zeng, Zhenzhen Yi, Manni Cao, Yijia Wang, Wenfeng Yu, Wenfeng Yu, Zhenkui Ren, Zhenkui Ren

“…Recent evidence suggests a role for dysregulated iron metabolism in the pathogenesis of AD, although the precise molecular mechanisms remain largely undefined.Materials and methodsTo address the role of iron metabolism in AD, we utilized an integrative bioinformatics approach that combines weighted gene co-expression network analysis (WGCNA) with machine learning techniques, including LASSO regression and Generalized Linear Models (GLM), to identify hub genes associated with AD. …”
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A KNN-based model for non-invasive prediction of hemorrhagic shock severity in prehospital settings: integrating MAP, PBUCO2, PTCO2, and PPV by Peng Zhao, Wencai Pan, Xin Zou, Jiaqing Yang, Shihui Zhang, Yufei Liu, Yang Li

“…We developed a multi-parameter predictive model integrating mean arterial pressure (MAP), buccal mucosal CO₂ (PBUCO₂), transcutaneous oxygen (PTCO₂), and pulse pressure variation (PPV). using K-nearest neighbors (KNN) algorithm. …”
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Integrative single-cell RNA sequencing and bulk RNA sequencing reveals the characteristics of glutathione metabolism and protective role of GSTA4 gene in pancreatic cancer by Xinya Jia, Qiang Zhang, Zhe Wang, Jianliang Cao, Anran Song, Chao Lan, Yuepeng Hu

“…This study aims to investigate the prognostic significance of GSH metabolism-related genes in PC and to identify key molecular targets, thereby providing novel perspectives for targeted PC therapy.MethodsThe GSH metabolism gene set was retrieved from the KEGG database. …”
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Molecular signatures of preeclampsia subtypes determined through integrated weighted gene co-expression network analysis and differential gene expression analysis of placental tran... by Luhao Han, Fabricio da Silva Costa, Fabricio da Silva Costa, Anthony Perkins, Anthony Perkins, Olivia Holland, Olivia Holland

“…This study aims to use integrated bioinformatics analysis of placental transcriptomics to investigate subtype-specific molecular mechanisms associated with PE.MethodsA systematic search of the Gene Expression Omnibus (GEO) repository identified two datasets (GSE234729, n = 123; GSE75010, n = 157) for integrated Weighted Gene Co-expression Network Analysis (WGCNA) and differential gene expression analysis. …”
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A study on the influence of material gradient index on bending and stress responses of FGM rectangular plates using the Finite Element Method by Ahmad Reshad Noorı, Mohammad Omar Al Rousan, Hamza Diallo, Ayça Bilgin, Masihullah Noori

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Efficient one-stage detection of shrimp larvae in complex aquaculture scenarios by Guoxu Zhang, Tianyi Liao, Yingyi Chen, Ping Zhong, Zhencai Shen, Daoliang Li

“…Firstly, the transparent bodies and small sizes of shrimp larvae, combined with complex scenarios due to variations in light intensity and water turbidity, make it challenging for current detection methods to achieve high accuracy. …”
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A fully automated hybrid approach for processing high-frequency surface settlement data by Changyu Wang, Zude Ding, Annan Zhou, Zekun Zhu

“…The proposed method minimises manual intervention and reduces reliance on empirical design through the integration of the Mel Frequency Cepstral Coefficient (MFCC) based Convolutional Neural Networks (CNN), Extreme Learning Machine (ELM), and Variational Modal Decomposition (VMD) algorithms. …”
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The Role of Visual Information Quantity in Fine Motor Performance by Giulia Panconi, Vincenzo Sorgente, Sara Guarducci, Riccardo Bravi, Diego Minciacchi

“…Tracing tasks provide an ecological method for studying these movements and investigating sensorimotor processes. …”
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A Self-Attention Enhanced Deep CNN-LSTM-Based Irregular Surface Recognition Approach for Integration Into Lower Limb Prosthesis Systems to Ensure Safety Through Predictive Walking by Norazian Subari, Kamarul Hawari Ghazali, Yuanfa Ji

“…To address these challenges, integrating inertial measurement units (IMUs) with artificial intelligence (AI) techniques, particularly deep learning (DL) methods, has emerged as a promising solution for surface classification and safety enhancement. …”
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A Hierarchical and Self-Evolving Digital Twin (HSE-DT) Method for Multi-Faceted Battery Situation Awareness Realisation by Kai Zhao, Ying Liu, Yue Zhou, Wenlong Ming, Jianzhong Wu

“…Its hierarchical structure allows the integration of different estimation models, and the self-evolving method allows the method to adapt to changes in different operating conditions. …”
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Detection and Prediction of Wind and Solar Photovoltaic Power Ramp Events Based on Data-Driven Methods: A Critical Review by Jie Zhang, Xinchun Zhu, Yigong Xie, Guo Chen, Shuangquan Liu

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PortraitEmotion3D: A Novel Dataset and 3D Emotion Estimation Method for Artistic Portraiture Analysis by Shao Liu, Sos Agaian, Artyom Grigoryan

“…Evaluation of the PE3D dataset demonstrates our method’s high accuracy and robustness compared to existing state-of-the-art FER techniques. …”
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Multi-Objective Decision-Making Evaluation Method of Environmental Impact Associated with the Life Cycle of Agro-Friendly Biochar Materials by Shunyang Wang, Jing Wei, Hua Li, Da Ding, Yaxin Zhang, Yuen Zhu, Shaopo Deng, Yongming Luo

“…Sensitivity analysis further confirmed the robustness of the method, with impact variations ranging from 0.44 to 0.52, suggesting the model’s reliability in comparing different remediation materials. …”
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DMS-OGSTV: A Novel Infrared Small Target Detection Based on Spatial-Temporal Tensor Model by Xiaoling Ge, Weixian Qian, Zipeng Fu

“…Next, for more precise background estimation, we use an accurate low-rank approximation and extend the overlapping group sparse total variation (OGSTV) regularization from 2D to 3D. Compared to traditional variational methods, 3D-OGSTV better distinguishes edges from flat regions, improving background suppression and detection accuracy. …”
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ICT-Net: A Framework for Multi-Domain Cross-View Geo-Localization with Multi-Source Remote Sensing Fusion by Min Wu, Sirui Xu, Ziwei Wang, Jin Dong, Gong Cheng, Xinlong Yu, Yang Liu

“…Extensive experiments demonstrate that ICT-Net establishes new state-of-the-art localization accuracy on the CVUSA benchmark, achieving a top-1 recall rate improvement of 8.6% over previous methods. Additional validation on a challenging real-world dataset collected at Beihang University (BUAA) further confirms the framework’s effectiveness and practical applicability in complex urban environments, particularly showing 23% higher robustness to vegetation variations.…”
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Increasing Vegetation Cover Enhances Ecosystem Services in the Rare Earth Mining Area of China: Threshold Effects and Implications by Yuqing Liu, Zhubin Zheng, Jianzhong Li, Ge Liu, Shaohua Lei, Jie Xu, Wei Luo, Chao Du, Wei Huang, Chao Huang, Jingli Ren

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Applicability of Machine Learning and Mathematical Equations to the Prediction of Total Organic Carbon in Cambrian Shale, Sichuan Basin, China by Majia Zheng, Meng Zhao, Ya Wu, Kangjun Chen, Jiwei Zheng, Xianglu Tang, Dadong Liu

“…This study introduces three key innovations to address these challenges: (1) A Dynamic Weighting–Calibrated Random Forest Regression (DW-RFR) model integrating high-resolution Gamma-Ray-guided dynamic time warping (±0.06 m depth alignment precision derived from 237 core-log calibration points using cross-validation), Principal Component Analysis-Deyang–Anyue Rift Trough Shapley Additive Explanations (PCA-SHAP) hybrid feature engineering (89.3% cumulative variance, VIF < 4), and Bayesian-optimized ensemble learning; (2) systematic benchmarking against conventional ΔlogR (R² = 0.700, RMSE = 0.264) and multi-attribute joint inversion (R² = 0.734, RMSE = 0.213) methods, demonstrating superior accuracy (R² = 0.917, RMSE = 0.171); (3) identification of Gamma Ray (r = 0.82) and bulk density (r = −0.76) as principal TOC predictors, contrasted with resistivity’s thermal maturity-dependent signal attenuation (r = 0.32 at Ro > 3.0%). …”
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