Real-Time Fault Diagnosis of Mooring Chain Jack Hydraulic System Based on Multi-Scale Feature Fusion Under Diverse Operating Conditions by Yujia Liu, Wenhua Li, Haoran Ye, Shanying Lin, Lei Hong

“…Hence, this paper proposes a real-time fault diagnosis method of the CJ hydraulic system based on multi-scale feature fusion. Firstly, the model incorporates a convolutional neural network (CNN) layer to extract localized spatial features from multivariate time-series data, effectively identifying fault patterns over the associated short intervals. …”
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Stenting and cell technologies in the treatment of atherosclerotic renovascular hypertension Part 3. Some genetic, pharmacological, and radio-ecological features of malignant renov... by A. N. Kharlamov, Ya. L. Gablnsky, E. K. Bos, P. A. Davidovich, V. S. Veselova

“…Primary combined end-point included the following: genetic analysis of monogenic disease, chromosome aberrations, genotypes and allele patterns for main polymorphic candidate genes participating in arterial hypertension (AH) and atherosclerosis pathogenesis; pharmacogenetic features of lipid-lowering and antihypertensive pharmaceutical therapy effectiveness; incorporated gamma-nuclide activity in critical organs.Results. …”
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Machine Learning Enabled Prediction of Biologically Relevant Gene Expression Using CT‐Based Radiomic Features in Non‐Small Cell Lung Cancer by Shrey S. Sukhadia, Christoph Sadée, Olivier Gevaert, Shivashankar H. Nagaraj

“…Results Our ML‐based radiogenomic modeling identified specific imaging features—wavelet, three‐dimensional local binary patterns, and logarithmic sigma of gray‐level variance—as predictive indicators for high (1) vs. low (0) gene expression of pivotal NSCLC‐related genes: SLC35C1, BCL2L1, and MAPK1. …”
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<i>cBP-Tnet</i>: Continuous Blood Pressure Estimation Using Multi-Task Transformer Network with Automatic Photoplethysmogram Feature Extraction by Angelino A. Pimentel, Ji-Jer Huang, Aaron Raymond A. See

“…This research proposes <i>cBP-Tnet</i>, an efficient single-channel and model multi-task Transformer network designed for PPG signal automatic feature extraction. <i>cBP-Tnet</i> employed specialized hyperparameters—integrating adaptive Kalman filtering, outlier elimination, signal synchronization, and data augmentation—leveraging multi-head self-attention and multi-task learning strategies to identify subtle and shared waveform patterns associated with systolic blood pressure (SBP) and diastolic blood pressure (DBP). …”
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Arrears behavior prediction of power users based on BP neural network and multi-scale feature learning: a refined risk assessment framework by Liang Yu, Yuanshen Hong, Hua Lin, Xu Jiang, Ziming Song

“…These results indicate that the proposed method offers significant improvements in capturing user behavior patterns and enhancing prediction accuracy. The study concludes that the effective fusion of multi-scale features not only enhances the model’s prediction performance but also strengthens its generalization ability. …”
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Multi-Feature Fusion-Based Speech Disorder Classification Using MobileNetV3-EfficientNetB7, Linformer-Performer, and SHAP-Aware XGBoost by Abdul Rahaman Wahab Sait, Suresh Sankaranarayanan, P. Gouthaman

“…Hybrid MobileNet V3-EfficientNet B7and Linformer-Performer are employed to extract diverse features from the Mel-Spectrograms. An attention-based feature fusion is used to identify critical features indicating the SD patterns from the extracted features. …”
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Distinctive features of IncRNA and mRNA between severe and mild patients with influenza a (H1N1) virus pneumonia by Dangsheng Xiao, Jinyou Li, Xuehui Zhao, Yongtao Li, Haifeng Lu, Jiezuan Yang

“…This research sheds light on the distinct transcriptomic features contributing to the pathogenesis of severe H1N1 infections, offering insights into differential diagnosis and potential therapeutic targets. …”
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Extraction and Spatiotemporal Analysis of Rubber Plantations on Hainan Island, China (1990&#x2013;2023) Using Phenological and Multivariate Remote Sensing Features by Donghua Wang, Huichun Ye, Yanan You, Chaojia Nie, Jingjing Wang, Jingjuan Liao, Bingsun Wu, Lixia Shen, Dailiang Peng

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Pathological and clinical insights into DICER1 hotspot mutated Sertoli-Leydig cell tumors: a comparative analysis by Zhuoyao Lyu, Yilin Liu, Jingci Chen, Pengyan Wang, Zhaohui Lu, Xiaoyan Chang, Xianlong Chen, Heng Ma, Shengwei Mo, Shuangni Yu, Jie Chen

“…Clinical information, such as patients' symptoms, tumor staging, prognosis, and pathological features, such as tumor differentiation and growth patterns, were collected. …”
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ANCA-related vasculitis incidence and features before and during the COVID-19 pandemic in Los Angeles, Biobio Province, Chile: an observational retrospective analysis by Daniel Enos, Daniel Enos, Daniel Enos, Mariel Hernández, Mariel Hernández, Gonzalo P. Méndez, Lysis Cáceres, Ignacia Bravo, Josefina Jobet, Simón Castro, Lorena Cornejo, Catalina Vega, Andrés Salazar

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Directional hand movement can be classified from insular cortex SEEG signals using recurrent neural networks and high-gamma band features by Xiecheng Shao, Ryan S. Chung, Jonathon M. Cavaleri, Roberto Martin Del Campo-Vera, Miguel Parra, Shivani Sundaram, Selena Zhang, Ashwitha Surabhi, Ryan J. McGinn, Charles Y. Liu, Spencer S. Kellis, Brian Lee

“…Demixed Principal Component Analysis (dPCA) was used for dimension reduction (d = 10) and feature extraction from the time-frequency analysis. …”
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Drunk Driver Detection Using Thermal Facial Images by Chin-Heng Chai, Siti Fatimah Abdul Razak, Sumendra Yogarayan, Ramesh Shanmugam

“…This study aims to investigate and propose a machine learning approach that can accurately detect alcohol consumption by analyzing the thermal patterns of facial features. Thermal images from the Tufts Face Database and self-collected images were utilized to train the models in identifying temperature variations in specific facial regions. …”
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On-Site Investigation and Diagnosis of Hazardous Street Section in Erbil Street Network by Abdulhakim Othman Salih kozapanky

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Single-nucleus transcriptomics reveals a distinct microglial state and increased MSR1-mediated phagocytosis as common features across dementia subtypes by Sook-Yoong Chia, Mengwei Li, Zhihong Li, Haitao Tu, Jolene Wei Ling Lee, Lifeng Qiu, Jingjing Ling, Richard Reynolds, Salvatore Albani, Eng-King Tan, Adeline Su Lyn Ng, Jinmiao Chen, Li Zeng

“…While these subtypes share clinical, genetic, and pathological features, their transcriptomic similarities and differences remain poorly understood. …”
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A Grey Wolf Optimisation-Based Framework for Emotion Recognition on Electroencephalogram Data by Ram Avtar Jaswal, Sunil Dhingra

“…Human emotions trigger reflective transformations within the brain, leading to unique patterns of neural activity and behaviour. This study connects the power of electroencephalogram (EEG) data to investigate the intricate impacts of emotions, considering their reflective significance in our daily lives, in depth. …”
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Influence of the South Asian High and Western Pacific Subtropical High Pressure Systems on the Risk of Heat Stroke in Japan by Takehiro Morioka, Kenta Tamura, Tomonori Sato

“…Large-scale circulation anomalies similar to the Pacific–Japan teleconnection are found on DH days, suggesting that both high humidity and cloudless conditions are among the large-scale features controlled by this teleconnection. Early countermeasures to mitigate heat stroke risk, including advisories for outdoor activities, should be taken when DH-like weather patterns are predicted.…”
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Environmental complaints in Aveiro, Portugal: actors, concerns, territorial pattern, and resolutions / Reclamações ambientais em Aveiro, Portugal: atores, preocupações, padrão terr... by Daniela Salgado Carvalho, Teresa Fidélis

“…It also contains a brief review of the most recent urban environmentalquality challenges in the European context together with a description of the main features ofthe associated political and legal framework in Portugal. …”
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Explainable machine learning-driven models for predicting Parkinson’s disease and its prognosis: obesity patterns associations and models development using NHANES 1999–2018 data... by Jiaxin Fan, Shuai Cao, Hang Peng, Yuanjie Zhi, Shuqin Zhan, Rui Li

“…We aimed to investigate the associations of obesity patterns on PD and all-cause mortality, while developing machine learning (ML)-driven predictive and prognostic models for PD. …”
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Advanced hybrid deep learning model for enhanced evaluation of osteosarcoma histopathology images by Arezoo Borji, Arezoo Borji, Arezoo Borji, Gernot Kronreif, Bernhard Angermayr, Bernhard Angermayr, Sepideh Hatamikia, Sepideh Hatamikia

“…The CNN model extracts local features, while the ViT captures global patterns from histopathological images. …”
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Pattern of Expression of PML-RARα Transcripts in Acute Promyelocytic Leukemia Patients and Its Correlation with Overall Survival: A Retrospective Study from Western India by Shweta Gondha, Prerna Walia, Beena Brahmbhatt, Jayendrakumar Patel, Toral Mandalia, Disha Jethva

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