Using optimized dimensionality reduction and machine learning to explain driving processes of phytoplankton community assembly in large mountain rivers by Jingxu Ye, Daikui Li, Qi Liu, Jianying Song, Jiawei Song, Zhigang Zu, Yujun Yi

“…Further, factor integration was performed using projection pursuit optimized by PSA, combined with BRT. …”
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Enhancing neurological disease diagnostics: fusion of deep transfer learning with optimization algorithm for acute brain stroke prediction using facial images by Fadwa Alrowais, Mohammed Alqahtani, Jahangir Khan, Achraf Ben Miled, Da’ad Albalawneh, Abdulwhab Alkharashi, Samah Al Zanin, Radwa Marzouk

“…Furthermore, fusion models such as Inception-V3 and EfficientNet-B0 perform the feature extraction. …”
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MRI assessment of the abdominal adipose tissue and the state of the abdominal aorta in patients with coronary artery disease: association with metabolic disorders by N. I. Ryumshina, O. A. Koshelskaya, I. V. Kologrivova, O. A. Kharitonova, K. A. Nasekina, V. Yu. Ussov

“…Magnetic resonance imaging (MRI) was performed on a 1.5 T MRI scanner using T2-weighted spin-echo modes. …”
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Unveiling the Therapeutic Potential of Baicalin in Intervertebral Disc Degeneration: Integrative Bulk and Single-Cell Transcriptome Analysis with Experimental Validation of PANopto... by Wang X, Gao S, Zhou D, Cai W, Lv J, Wei Z, Song C, Shan X, Liu Z

“…Moreover, baicalin alleviated IL-1β-induced cell death in NPCs and improved histological features in the rat IVDD model.Conclusion: Our findings reveal a critical role of PANoptosis in IVDD progression and demonstrate that baicalin alleviates disc degeneration by inhibiting PANoptosis. …”
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Assessment of geoecological conditions in Son La province (Vietnam) and natural risk prevention by T. N. Nguyen, V. N. Ekzaryan

“…Studying and assessing the current state of the geoecological conditions in Son La province, Vietnam and the proposal of measures for the transiton to models of sustainable development of the territory.Materials and methods. …”
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Myo‐Guide: A Machine Learning‐Based Web Application for Neuromuscular Disease Diagnosis With MRI by Jose Verdu‐Diaz, Carla Bolano‐Díaz, Alejandro Gonzalez‐Chamorro, Sam Fitzsimmons, Jodi Warman‐Chardon, Goknur Selen Kocak, Debora Mucida‐Alvim, Ian C. Smith, John Vissing, Nanna Scharff Poulsen, Sushan Luo, Cristina Domínguez‐González, Laura Bermejo‐Guerrero, David Gomez‐Andres, Javier Sotoca, Anna Pichiecchio, Silvia Nicolosi, Mauro Monforte, Claudia Brogna, Eugenio Mercuri, Jorge Alfredo Bevilacqua, Jorge Díaz‐Jara, Benjamín Pizarro‐Galleguillos, Peter Krkoska, Jorge Alonso‐Pérez, Montse Olivé, Erik H. Niks, Hermien E. Kan, James Lilleker, Mark Roberts, Bianca Buchignani, Jinhong Shin, Florence Esselin, Emmanuelle Le Bars, Anne Marie Childs, Edoardo Malfatti, Anna Sarkozy, Luke Perry, Sniya Sudhakar, Edmar Zanoteli, Filipe Tupinamba Di Pace, Emma Matthews, Shahram Attarian, David Bendahan, Matteo Garibaldi, Laura Fionda, Alicia Alonso‐Jiménez, Robert Carlier, Ali Asghar Okhovat, Shahriar Nafissi, Atchayaram Nalini, Seena Vengalil, Kieren Hollingsworth, Chiara Marini‐Bettolo, Volker Straub, Giorgio Tasca, Jaume Bacardit, Jordi Díaz‐Manera, the Myo‐Guide Consortium

“…To address class imbalance, training and evaluation were conducted using class‐balanced metrics. The model's performance was compared against four expert clinicians using 14 previously unseen MRI scans. …”
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Machine learning applied to wearable fitness tracker data and the risk of hospitalizations and cardiovascular events by John Kundrick, Aditi Naniwadekar, Virginia Singla, Krishna Kancharla, Aditya Bhonsale, Andrew Voigt, Alaa Shalaby, N.A. Mark Estes, Sandeep K Jain, Samir Saba

“…For the CVD events, the best prediction model was gradient boosting (AUROC=0.80, accuracy=0.71, F1 score=0.15).Conclusion: ML models applied to Fitbit data demonstrate promise in predicting clinical outcomes with strong performance for predicting all-cause hospitalizations and modest performance for predicting incident CVD. …”
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Mitigating Catastrophic Forgetting in Pest Detection Through Adaptive Response Distillation by Hongjun Zhang, Zhendong Yin, Dasen Li, Yanlong Zhao

“…Pest detection in agriculture faces the challenge of adapting to new pest species while preserving the ability to recognize previously learned ones. Traditional model fine-tuning approaches often result in catastrophic forgetting, where the acquisition of new classes significantly impairs the recognition performance of existing ones. …”
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A Comparative Analysis of Convolutional Neural Network (CNN): MobileNetV2 and Xception for Butterfly Species Classification by Mehta Pradnyatama, Christy Atika Sari, Eko Hari Rachmawanto, Hussain Md Mehedul Islam

“…This study contributes to entomological research and highlights trade-offs between model complexity and performance in fine-grained classification tasks, supporting implementation decisions for butterfly identification systems in practical applications.…”
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Analysis and Optimization of a Moving Magnet Permanent Magnet Synchronous Planar Motor with Split Halbach Arrays by Ronglu Wang, Lu Zhang, Chenyang Shi, Chunqiu Zhao, Kai Yang

“…This paper investigates an improved permanent magnet synchronous planar motor (PMSPM) featuring a moving magnet configuration to enhance thrust density and positioning accuracy. …”
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A Unified Machine Learning Framework for Li-Ion Battery State Estimation and Prediction by Afroditi Fouka, Alexandros Bousdekis, Katerina Lepenioti, Gregoris Mentzas

“…The proposed framework supports flexible configurations across multiple dimensions, including feature engineering, model selection, and training/testing strategies. …”
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A Lightweight Kernel Density Estimation and Adaptive Synthetic Sampling Method for Fault Diagnosis of Rotating Machinery with Imbalanced Data by Wenhao Lu, Wei Wang, Xuefei Qin, Zhiqiang Cai

“…KAMS effectively handles data imbalances commonly found in industrial applications and is optimized for real-time monitoring. The model employs the Kernel Density Estimation Adaptive Synthetic Sampling (KDE-ADASYN) algorithm for oversampling to balance the data, applies fast Fourier transform (FFT) to convert time-domain signals into frequency-domain signals, and utilizes a 1D-MobileNet network enhanced with a Squeeze-and-Excitation (SE) block for feature extraction and fault diagnosis. …”
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Automatic detection of foreign object intrusion along railway tracks based on MACENet. by Xichun Chen, Yu Tian, Ming Li, Bin Lv, Shuo Zhang, Zixian Qu, Jianqing Wu, Shiya Cheng

“…The incorporation of DCNv3 allows the model to dynamically adapt its sampling positions according to actual object shapes, significantly enhancing feature extraction accuracy, especially for irregularly shaped intrusions. …”
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SR-DETR: Target Detection in Maritime Rescue from UAV Imagery by Yuling Liu, Yan Wei

“…The proposed approach is validated through experiments and achieves an mAP of 86.5%, which surpasses the baseline RT-DETR model’s performance of 83.2%. These outcomes highlight the practicality and reliability of our method in detecting individuals overboard, contributing to more precise and resource-efficient solutions for real-time maritime rescue efforts.…”
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Fault Diagnosis of Low-Noise Amplifier Circuit Based on Fusion Domain Adaptation Method by Chao Zhang, Peng Du, Dingyu Zhou, Zhijie Dong, Shilie He, Zhenwei Zhou

“…Firstly, a domain-adaptive diagnostic model was established based on the feature extraction capabilities of CNNs. …”
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Knowledge distillation-enhanced marine optical remote sensing object detection with transformer and dual-path architecture by Yubin Yuan, Yiquan Wu, Langyue Zhao, Yuqi Liu, Jinlin Chen

“…To balance detection accuracy with computational efficiency, a knowledge distillation framework is implemented where a compact student model learns distilled representations through multi-granularity alignment with a teacher network, encompassing intermediate feature guidance and output-level probability calibration. …”
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Edge-Optimized Lightweight YOLO for Real-Time SAR Object Detection by Caiguang Zhang, Ruofeng Yu, Shuwen Wang, Fatong Zhang, Shaojia Ge, Shuangshuang Li, Xuezhou Zhao

“…Then, a Fast Feature Pyramid Network is constructed to enable efficient multi-scale feature fusion. …”
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Real-Time Aerial Multispectral Object Detection with Dynamic Modality-Balanced Pixel-Level Fusion by Zhe Wang, Qingling Zhang

“…Combining visible and infrared sensors can overcome limitations under low-light conditions, enabling full-time tasks. While feature-level fusion methods exhibit comparable performances in visible–infrared multispectral object detection, they suffer from heavy model size, inadequate inference speed and visible light preferences caused by inherent modality imbalance, limiting their applications in airborne platform deployment. …”
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Non-Uniformity Correction of Spatial Object Images Using Multi-Scale Residual Cycle Network (CycleMRSNet) by Chunfeng Jiang, Zhengwei Li, Yubo Wang, Tao Chen

“…To evaluate the performance of CycleMRSNet, we trained the model using a small-scale dataset and conducted corrections on simulated and real images within the test set. …”
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Scalable architecture for autonomous malware detection and defense in software-defined networks using federated learning approaches by Ripal Ranpara, Shobhit K. Patel, Om Prakash Kumar, Fahad Ahmed Al-Zahrani

“…Our architecture minimizes privacy risks by ensuring that raw data never leaves the device; only model updates are shared for aggregation at the global level. …”
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