Facial Expression Recognition and Digital Images Infosecurity for Prevention Care System Application in Sudden Infant Death Syndrome Monitoring by Chih-Te Tsai, Chia-Hung Lin, Hsiang-Yueh Lai, Yu-En Cheng, Ping-Tzan Huang, Neng-Sheng Pai, Chien-Ming Li

“…Thus, to ensure secure SIDS monitoring, the SAES-based scheme implements robust block encryption and decryption processes to protect the privacy and security of infant images, while the YOLOv10 model enhances real-time OD, feature extraction, and pattern recognition capabilities. …”
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Incident duration prediction through integration of uncertainty and risk factor evaluation: A San Francisco incidents case study. by Amirreza Salehi, Ardavan Babaei, Majid Khedmati

“…Through a rigorous analysis of feature importance using top-performing predictive models, we identify the "Risk" factor as a critical determinant of incident duration. …”
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Comparison of Diffuse Reflectance and Diffuse Transmittance Vis/NIR Spectroscopy for Assessing Soluble Solids Content in Kiwifruit Coupled with Chemometrics by Yu Xia, Wei Zhang, Tianci Che, Jinghao Hu, Shangqiao Cao, Wenbo Liu, Jie Kang, Wei Tang, Hongbo Li

“…Various preprocessing methods and feature wavelength selection techniques were employed, and regression models were constructed using partial least squares (PLS) analysis. …”
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Gut microbiota alterations are linked to COVID-19 severity in North African and European populations by Marius Bredon, Pierre Hausfater, Loubna Khalki, Youssef Tijani, Amine Cheikh, Loic Brot, Laura Creusot, Nathalie Rolhion, Francois Trottein, Gérard Lambeau, Sophie Georgin-Lavialle, Alexandre Bleibtreu, Jean-Luc Baudel, Antoine Lefèvre, Patrick Emond, Florence Tubach, Noémie Simon-Tillaux, Tabassome Simon, Guy Gorochov, Younes Zaid, Harry Sokol

“…Machine learning models accurately predicted disease severity based on gut microbial profiles in the Moroccan cohort, though not in the French cohort. …”
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Laboratory and Numerical Study of Hydraulic Loss and Discharge Coefficient in Rectangular Labyrinth and Piano Key Weirs by R. Ghasemi Ghasemvand, M. Heidarnejad, A.R. Masjedi, A. Bordbar

“…The ARCL weir shows the highest hydraulic loss with increasing Froude number compared to the other weirs. All weirs modeled using FLOW-3D software showed values (Cd and Hf/P) that exceeded those from physical modeling, which is significant in terms of safety factors. …”
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Gravity-based microfiltration reveals unexpected prevalence of circulating tumor cell clusters in ovarian and colorectal cancer by Anne Meunier, Javier Alejandro Hernández-Castro, Nicholas Chahley, Laudine Communal, Sara Kheireddine, Newsha Koushki, Nadia Davoudvandi, Sara Al Habyan, Benjamin Péant, Anthoula Lazaris, Andy Ng, Teodor Veres, Luke McCaffrey, Diane Provencher, Peter Metrakos, Anne-Marie Mes-Masson, David Juncker

“…Optimal flow rate and pore size for cCTC isolation are determined by GµF of cultured ovarian single cells and cell clusters spiked in healthy blood. We perform GµF of blood from orthotopic ovarian cancer mouse models and characterize the morphological features of scCTCs and cCTCs, and the expression of molecular markers for aggressiveness. …”
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Rare Variants Cause Charcot‐Marie‐Tooth Disease in Malian Families by Abdoulaye Yalcouyé, Lassana Cissé, Salimata Diarra, Seybou H. Diallo, Salia Bamba, Patra Yeetong, Boubacar Maiga, Kékouta Dembélé, Dramane Coulibaly, Salimata Diallo, Abdoulaye Taméga, Alassane Baneye Maiga, Hamidou O. Ba, Vorasuk Shotelersuk, Kenneth H. Fischbeck, Cheick O. Guinto, Guida Landouré

“…Deleteriousness was checked using several in silico prediction tools and protein modeling. Results Nine patients (three males and six females) from four families were enrolled. …”
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Cellular senescence induced by cholesterol accumulation is mediated by lysosomal ABCA1 in APOE4 and AD by Shaowei Wang, Boyang Li, Jie Li, Zhiheng Cai, Cristelle Hugo, Yi Sun, Lu Qian, Julia TCW, Helena C. Chui, Dante Dikeman, Isaac Asante, Stan G. Louie, David A. Bennett, Zoe Arvanitakis, Alan T. Remaley, Bilal E. Kerman, Hussein N. Yassine

“…Additionally, we used APOE4-TR mice and induced pluripotent stem cell (iPSC) models to explore cholesterol-ABCA1-senescence pathways. …”
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Integrating molecular QTL data into genome-wide genetic association analysis: Probabilistic assessment of enrichment and colocalization. by Xiaoquan Wen, Roger Pique-Regi, Francesca Luca

“…We detail a computational procedure to seamlessly perform enrichment, fine-mapping and colocalization analyses, which is a distinct feature compared to the existing colocalization analysis procedures in the literature. …”
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Discrimination Analysis for Predicting Defect-Prone Software Modules by Ying Ma, Ke Qin, Shunzhi Zhu

“…Unlike the prior works, we try to exploit the kernel method to nonlinearly map the data into a high-dimensional feature space. By combating these two problems, we propose an algorithm based on kernel discrimination analysis called KDC to build more effective prediction model. …”
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Public Sentiment Analysis on the Boycott Israel Movement on Platform X Using Random Forest and Logistic Regression Algorithms by Rachmayanti Tri Agustin, Yana Cahyana, Kiki Ahmad Baihaqi, Tatang Rohana

“…The Random Forest model achieved an accuracy of 70%, while Logistic Regression reached 68%. …”
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Improving the Solution of Least Squares Support Vector Machines with Application to a Blast Furnace System by Ling Jian, Shuqian Shen, Yunquan Song

“…The MINRES method-based LS-SVM can effectively perform feature reduction and model selection simultaneously, so it is a practical tool for the silicon trend prediction task.…”
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Analysis of Therapeutic Targets of A Novel Peptide Athycaltide-1 in the Treatment of Isoproterenol-Induced Pathological Myocardial Hypertrophy by Xi Zheng, Fuxiang Su, Ze Kang, Jingyuan Li, Chenyang Zhang, Yujia Zhang, Liying Hao

“…Protein network analysis was then performed using the STRING software. Functional analysis revealed that Hspa1 protein, oxidative stress, and MAPK signaling pathway were significantly involved in the occurrence and development of myocardial hypertrophy, which was further validated by vivo model. …”
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Deciphering the efficiency of preoperative systemic-immune inflammation related markers in predicting oncological outcomes of upper tract urothelial carcinoma patients after radica... by Nouha Setti Boubaker, Bilel Saidani, Ahmed Saadi, Seif Mokadem, Zeineb Naimi, Lotfi Kochbati, Haroun Ayed, Marouen Chakroun, Mohamed Riadh Ben Slama

“…Univariate and multivariate survival analysis were performed using general linear models to identify risk factors for prognosis. …”
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Attention-Guided Residual Spatiotemporal Network with Label Regularization for Fault Diagnosis with Small Samples by Yanlong Xu, Liming Zhang, Ling Chen, Tian Tan, Xiaolong Wang, Hongguang Xiao

“…Subsequently, a residual module is introduced to address the vanishing gradient problem of the model in deep network structures. In addition, LSTM is used to realize spatiotemporal feature fusion. …”
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Detecting intrusions in cloud-based ensembles: evaluating voting and stacking methods with machine learning classifiers by Khawla Ali Maodah, Sharaf Alhomdy, Fursan Thabit

“…Furthermore, it is shown via feature selection methods (Random Forest, Gain Information, and Manual Selection) that the ensemble model performs consistently even when feature sets are smaller.DiscussionThese findings highlight how both individual and group Machine learning approaches may be used to improve Intrusion detection systems for cloud infrastructures, providing implementation flexibility according to threat landscapes and computing limitations.…”
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Detection of failures in HV surge arrester using chaos pattern with deep learning neural network by Chun‐Chun Hung, Meng‐Hui Wang, Shiue‐Der Lu, Cheng‐Chien Kuo

“…The Partial Discharge (PD) test was initially performed on six HV surge arrester fault models. The Discrete Wavelet Transform (DWT) was performed for filtering the PD signals. …”
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Identification of Earthquake Precursors Origin and AI Framework for Automatic Classification for One of These Precursors by Ghada Ali, Lotfy Samy, Omar M. Saad, Ali G. Hafez, El-Sayed Hasaneen, Kamal AbdElrahman, Ibrahim Salah, Mohammed S. Fnais, Hamed Nofel, Ahmed M. Mohamed

“…The current study also introduces this automatic classification by developing various machine learning (ML) and Convolutional Neural Network (CNN) models to highlight the features characterizing each pattern. …”
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Algorithms Facilitating the Observation of Urban Residential Vacancy Rates: Technologies, Challenges and Breakthroughs by Binglin Liu, Weijia Zeng, Weijiang Liu, Yi Peng, Nini Yao

“…Deep learning algorithms can automatically learn feature representation, perform well in processing large amounts of high-dimensional and complex data, and can effectively deal with the challenges brought by various data sources, but the training process is complex and the computational cost is high. …”
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Deep Learning-Based Surface Temperature Prediction for a Porous Radiant Burner Using Thermocouple-Calibrated Thermal Infrared Images by Hao-Yu Hsieh, Shenqyang Shy, Wei-Wun Wang, Yung-Chien Chou

“…All models exhibit stable and high prediction performance, achieving R2 values above 0.85 on the test set, thereby confirming the effectiveness and robustness of the proposed framework. …”
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