Classification of primary glomerulonephritis using machine learning models: a focus on IgA nephropathy prediction by Zhengbiao Hu, Shuangshan Bu, Kai Wang, Qianqian Cao, Huanhuan Zheng, Jie Yang, Shanshan Chen, Yuemeng Wu, Wenkai Ren, Chenlei He

“…In this study, multiple machine learning algorithms were used to develop a non-invasive and improved model for the diagnosis of IgAN. …”
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ECONOMIC ASPECTS OF APPLICATION OF THE RUSSIAN BIOSIMILAR OMALIZUMAB IN PATIENTS WITH ATOPIC BRONCHIAL ASTHMA OF MODERATE TO SEVERE CLINICAL COURSES by V. S. Krysanova, E. D. Ermolaeva, T. N. Ermolaeva, M. V. Davydovskaya, K. A. Kokushkin

“…They made it possible to improve the control of the disease. A number of original genetically engineered biological drugs, such as benralizumab, reslizumab, dupilumab, mepolizumab and omalizumab, are currently registered in Russia. …”
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A Novel Framework for Automated Grid Generation and CFD Simulation of Complex Geometries by Chunguang XU, Xin OUYANG, Jie CHEN, Jun LIU

“…This framework integrated body-fitted grids that accommodate intersecting grid lines, the flexible-node finite difference method (FN-FDM) designed for unordered point clouds, and a universal algorithm for freestream preservation (discrete equivalence equation and its discrete rule, DEER). …”
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An Ensemble Learning-Based Predictive Parameterization Approach for Permanent Magnet Synchronous Machines by Sema Nur Ipek, Nur Bekiroglu, Murat Taskiran

“…Six machine learning models-Multilayer Perceptron (MLP), Cascade Forward Neural Network (CFNN), Layer Recurrent Neural Network (LRNN), Transformer-like Network (TRF), Decision Tree (DT), and Support Vector Regression (SVR)–were evaluated in the first stage of the study. …”
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Spatiotemporal Analysis of Multi-UAV Persistent Search and Retrieval with Stochastic Target Appearance by Ryan Day, John L. Salmon

“…This research builds on a case study developed in a previous case study of multi-UAV PSR-STA. …”
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Current status and outlook of UWB radar personnel localization for mine rescue by ZHENG Xuezhao, MA Jiawen, HUANG Yuan, LI Qiang, REN Jing, LIU Yu

“…Key challenges in mine rescue scenarios are identified: ① significant localization errors and limited effective detection range in thick, heterogeneous, and discontinuous media; ② weakened radar echoes and severe clutter interference under Non-Line-of-Sight (NLOS) conditions, leading to low-precision micro-motion target detection and large real-time errors for dynamic targets; ③ signal interference and occlusion effects among multiple targets degrading localization accuracy. …”
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Prediction of Graduate Career Relevance Based on Academic and Non-Academic Aspects using Machine Learning by Muhammad Yusuf Luthfi Ijlal, Arif Setiawan, Diana Laily Fithri

“…The findings from the variable analysis and classification model can be utilized in developing a career alignment prediction system and as a basis for decision-making in strategies to improve graduate quality in line with labor market needs.…”
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Churn prediction for SaaS company with machine learning by Hugo Eduardo Sanches, Ayslan Trevizan Possebom, Linnyer Beatrys Ruiz Aylon

“…Design/methodology/approach – Through a preprocessing and normalization of data, seven machine learning algorithms were applied. …”
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Low Complexity CS/CB Techniques for Aerial Assisted Cellular Network With Imperfect CSI by Sheila N. Mugala, Jonathan Serugunda, Dorothy K. Okello

“…The beamforming algorithms are zero forcing beamforming (ZFBF), block diagonalization using singular value decomposition (BD SVD) and block diagonalization using Householder transformation (BD HH). …”
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ON THE SIMULATION OF MODES ОF ELECTRIC POWER SYSTEMS WITH FACTS by E. D. Halilov

“…The dependences of flows and power losses on the control parameter of FACTS devices have been derived.…”
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Mechanistic Learning for Predicting Survival Outcomes in Head and Neck Squamous Cell Carcinoma by Kevin Atsou, Anne Auperin, Jôel Guigay, Sébastien Salas, Sebastien Benzekry

“…ABSTRACT We employed a mechanistic learning approach, integrating on‐treatment tumor kinetics (TK) modeling with various machine learning (ML) models to address the challenge of predicting post‐progression survival (PPS)—the duration from the time of documented disease progression to death—and overall survival (OS) in Head and Neck Squamous Cell Carcinoma (HNSCC). …”
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Innovative Expert-Based Tools for Spatiotemporal Shallow Landslides Mapping: Field Validation of the GOGIRA System and Ex-MAD Framework in Western Greece by Michele Licata, Francesco Seitone, Efthimios Karymbalis, Konstantinos Tsanakas, Giandomenico Fubelli

“…DNC enables fully digital surveys, minimizing errors and delivering real-time, spatially accurate data to experts on site. …”
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The Emerging Role of Computed Tomography Coronary Angiography in the Left Main Stem Percutaneous Coronary Intervention by Asad Shabbir, Abdelrahman Attia, Nikkole Marie Weber, Mustafa Alhassan, Monika Radike, Conor M Lane, Apurva Bhavana Challa, Malgorzata Wamil

“…Recent technological advancements, including detailed multiplanar and three-dimensional (3D) reconstructions, CT-derived fractional flow reserve (CTFFR), and the integration of artificial intelligence (AI) algorithms, have expanded the capabilities of CTCA. …”
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Free-space terabit/s coherent optical links via platicon frequency microcombs by Wenting Wang, Hao Liu, Jiagui Wu, James F. McMillan, Dong IL Lee, Futai Hu, Wenzheng Liu, Jinghui Yang, Hangbo Yang, Abhinav Kumar Vinod, Yahya H. Ezzeldin, Christina Fragouli, Mingbin Yu, Patrick Guo-Qiang Lo, Dim-Lee Kwong, Devin S. Kahrs, Ninghua Zhu, Chee Wei Wong

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Comprehensive Risk Assessment of Power Grids Using Fuzzy Bayesian Networks Through Expert Elicitation: A Technical Analysis by Yasir Mahmood, Nof Yasir, Nita Yodo, Ying Huang, Di Wu, Roy A. McCann

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Automated noise modelling using a triangulated terrain model by Nadine Hobeika, Laurens van Rijssel, Maarit Prusti, Constantijn Dinklo, Denis Giannelli, Balázs Dukai, Arnaud Kok, Rob van Loon, René Nota, Jantien Stoter

“…These 3D polylines are semi-automatically generated to meet the highly demanding computing performance of simulation software. …”
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Machine learning for predicting resistance spot weld quality in automotive manufacturing by Nuttapong Chuenmee, Nattachai Phothi, Kontorn Chamniprasart, Sorada Khaengkarn, Jiraphon Srisertpol

“…The research highlights that the proposed methodology, particularly leveraging XGBoost, achieves a notable prediction accuracy of 97.1% when applied to unseen data.…”
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Unsignalized intersection vehicle platoon formation scheduling method based on mixed traffic by Junfeng Jiang, Yikang Rui, Bin Ran

“…In this context, the virtual platoon of lining vehicles into a one-dimensional virtual queue is based on a fully automated driving environment. …”
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Mechanical Response Analysis of Existing Metro Stations Caused by Large-sectionRectangular Interchange Passage CloselyUnderpassing by WU Jun, ZHANG Jiabing, SUN Houqiang, DU Yu, TENG Lirong

“…It is necessary to investigate the deformation and disturbance situation on the existing station caused by the newly built station closely under-passing. …”
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Assessment of Blind-Spots and Multi-Path Effects at Indoor Positioning by Multilateration by N. Doğan, Ö. H. Bettemir

“…Moreover, an algorithm for the detection of multipath is proposed and tested by simulation. …”
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