Accurate and Noninvasive Dysphagia Assessment via a Soft High‐Density sEMG Electrode Array Conformal to the Submental and Infrahyoid Muscles by Weijie Hong, Lin Mao, Kai Lin, Chongyuan Huang, Yanyan Su, Shun Zhang, Chengjun Wang, Daming Wang, Jizhou Song, Zuobing Chen

“…Abstract Accurate, noninvasive dysphagia assessment is important for rehabilitation therapy but current clinical diagnostic methods are either invasive or subjective. Surface electromyography (sEMG) that monitors muscle activity during swallowing, offers a promising alternative. …”
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Assessment Method for Feeding Intensity of Fish Schools Using MobileViT-CoordAtt by Shikun Liu, Xingguo Liu, Haisheng Zou

“…However, complex backgrounds in real-world aquaculture scenarios—such as water surface reflections, wave disturbances, and the stochastic movement of fish schools—pose significant challenges to the precise extraction of feeding-related features. …”
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A Glacier Ice Thickness Estimation Method Based on Deep Convolutional Neural Networks by Zhiqiang Li, Jia Li, Xuyan Ma, Lei Guo, Long Li, Jiahao Dian, Lingshuai Kong, Huiguo Ye

“…However, obtaining internal and basal glacier parameters required by physical models is challenging, often leading to simplified models that struggle to capture the nonlinear characteristics of ice flow and resulting in significant uncertainties. …”
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Research on the Impact of Shot Selection on Neuromuscular Control Strategies During Basketball Shooting by Qizhao Zhou, Shiguang Wu, Jiashun Zhang, Zhengye Pan, Ziye Kang, Yunchao Ma

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Impact of training data composition on the generalizability of convolutional neural network aortic cross-section segmentation in four-dimensional magnetic resonance flow imaging by Chiara Manini, Markus Hüllebrand, Lars Walczak, Sarah Nordmeyer, Lina Jarmatz, Titus Kuehne, Heiko Stern, Christian Meierhofer, Andreas Harloff, Jennifer Erley, Sebastian Kelle, Peter Bannas, Ralf Felix Trauzeddel, Jeanette Schulz-Menger, Anja Hennemuth

“…Model performance was evaluated using Dice score, Hausdorff distance, and average symmetric surface distance on test data, datasets with characteristics not represented in the training set (model-specific), and an overall evaluation set. …”
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Interpretable graph methods for determining nanoparticles ordering in electron microscopy image by M.Y. Kurbakov, V.V. Sulimova, O.S. Seredin, A.V. Kopylov

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Effects of Stretch-Bending Straightening on the Tensile Properties of Cold Rolled Packaging Steel by Sebastian Möller, Dimitrios Nouskalis, Björn Ehmke, Dirk Matusch, Christian Dresbach, Holm Altenbach

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Automatic Identification Model for Landslide Disaster Using Remote Sensing Images Based on Improved Multiresunet by Zhenyu Zhao, Shucheng Tan, Qinghua Zhang, Hui Chen

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Artificial intelligence models utilize lifestyle factors to predict dry eye related outcomes by Andrew D. Graham, Jiayun Wang, Tejasvi Kothapalli, Jennifer E. Ding, Helen Tasho, Alisa Molina, Vivien Tse, Sarah M. Chang, Stella X. Yu, Meng C. Lin

“…The results emphasize the importance of lifestyle, subject, and environmental characteristics in the etiology of ocular surface disease. …”
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A Comparative Analysis of Different Algorithms for Estimating Evapotranspiration with Limited Observation Variables: A Case Study in Beijing, China by Di Sun, Hang Zhang, Yanbing Qi, Yanmin Ren, Zhengxian Zhang, Xuemin Li, Yuping Lv, Minghan Cheng

“…Remote sensing (RS) technology presents an efficient approach for estimating ET at regional scales; however, existing RS retrieval algorithms for ET are intricate and necessitate a multitude of parameters. The land surface temperature–vegetation index (LST-VI) space method and statistical regression by machine learning (ML) offer the benefits of simplicity and straightforward implementation. …”
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Heat Risk Assessment in Arid Zones Based on Local Climate Zones: A Case of Urumqi, China by Hongxuan Lan, Hongchi Zhang, Jialu Gao, Jin Bai, Hanxuan Wang, Cheng Lu, Haoxuan Geng

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Global Predictability of Marine Heatwave Induced Rapid Intensification of Tropical Cyclones by Soheil Radfar, Ehsan Foroumandi, Hamed Moftakhari, Hamid Moradkhani, Gregory R. Foltz, Alex Sen Gupta

“…Building upon this, we propose an ensemble machine learning model for RI forecasting based on storm and MHW characteristics. …”
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A Defect Detection Method for Flexible Thermal Control Film Manufacturing Process Driven by Digital Twin by LI Rongyi, TIAN Shuaiqi, DAI Mingqiu, XU Youqiang, LI Xianbin, HOU Kailin

“…The thermal radiation characteristics of flexible thermal control films are the core elements determining the accuracy of thermal balance control on the surface of spacecraft. …”
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Influencing factors of cross screening rate and its intelligent prediction model by Lala ZHAO, Feng XU, Chenlong DUAN, Chenhao GUO, Wei WANG, Haishen JIANG, Jinpeng QIAO

“…The Spearman correlation coefficient matrix heat map was used to analyze the correlation between the four characteristic variables of feed rate, external water content, sieve surface inclination and sieve shaft speed and the screening rate and the correlation between the characteristics. …”
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Reconstruction of Random Structures Based on Generative Adversarial Networks: Statistical Variability of Mechanical and Morphological Properties by Mikhail Tashkinov, Yulia Pirogova, Evgeniy Kononov, Aleksandr Shalimov, Vadim V. Silberschmidt

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Urban flood mapping by fully mining and adaptive fusion of the polarimetric and spatial information of Sentinel-1 images by Qi Zhang, Xiangyun Hu

“…Thus, this paper proposes a novel, unsupervised multi-scale machine learning (ML) approach for urban flood mapping with SAR images from the perspective of information mining and fusion. …”
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Combined identification and attenuation of anomalous amplitude noises in nodal land seismic data by Xinjun Mao, Wen Yang, Zhichao Pang, Qiang Zhou, Haibo Mao, Dongjun Zhang, Xiaotao Wang, Long Pan

“…Furthermore, the window-based threshold computation can inadvertently damage non-noise strong amplitude signals, like near-offset traces or surface waves. In this study, we take advantage of the distinctive characteristics of seismic data acquired by nodal instruments. …”
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Optimization of Rituximab Therapy in Adult Patients With PLA2R1-Associated Membranous Nephropathy With Artificial Intelligence by Alexandre Destere, Maxime Teisseyre, Diane Merino, Marion Cremoni, Alexandre O Gérard, Thomas Crepin, Noémie Jourde-Chiche, Daisy Graça, Kévin Zorzi, Céline Fernandez, Vesna Brglez, Sylvia Benzaken, Vincent L.M. Esnault, Sylvain Benito, Milou-Daniel Drici, Barbara Seitz-Polski

“…We developed a machine learning algorithm to predict the risk of underdosing based on patients’ characteristics at rituximab infusion. …”
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A Complete EDA and DL Pipeline for Softwarized 5G Network Intrusion Detection by Abdallah Moubayed

“…Concurrently, the deployment of 5G networks has led to a surge in network-related attacks, due to expanded attack surfaces. Machine learning (ML), particularly deep learning (DL), has emerged as a promising tool for addressing these security challenges in 5G networks. …”
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Water pollution and water quality assessment and application of criterion impact loss (CILOS), geographical information system (GIS), artificial neural network (ANN) and decision-l... by Abhijeet Das

“…This study has brought attention to a drinking water quality assessment of surface water, by integrated use of CILOS (Criterion Impact Loss) based WQI (CILOS-WQI), with association by reliability based MCDMs (Multiple-criteria decision making) techniques namely: Evaluation based on Distance from Average Solution (EDAS) and Machine Learning (ML) based-Artificial Neural Network (ANN) technique. …”
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