A hierarchical Bayesian approach for identifying socioeconomic factors influencing self-rated health in Japan by Makoto Nakakita, Teruo Nakatsuma

“…Furthermore, we used the ancillary-sufficiency interweaving strategy (ASIS) algorithm to improve the efficiency of the MCMC method for the panel data logit model. …”
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Exercise-changed gut mycobiome as a potential contributor to metabolic benefits in diabetes prevention: an integrative multi-omics study by Yao Wang, Jiarui Chen, Yueqiong Ni, Yan Liu, Xiang Gao, Michael Andrew Tse, Gianni Panagiotou, Aimin Xu

“…Furthermore, a machine-learning algorithm built using baseline microbial signatures and clinical characteristics predicted exercise responsiveness in improvements of insulin sensitivity, with an area under the receiver operating characteristic (AUROC) of 0.91 (95% CI: 0.85–0.97) in the discovery cohort and of 0.79 (95% CI: 0.74–0.86) in the independent validation cohort (n = 30).Conclusions Our findings suggest that intense exercise training significantly remodels the human fungal microbiome composition. …”
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Development of model for identifying homologous recombination deficiency (HRD) status of ovarian cancer with deep learning on whole slide images by Ke Zhang, Youhui Qiu, Songwei Feng, Han Yin, Qi Liu, Yuxin Zhu, Haoyu Cui, Xiaoying Wei, Guoqing Wang, Xiangxue Wang, Yang Shen

“…Results The UNet + + algorithm segmented tumor regions with 81.8% accuracy, 85.9% recall, 83.8% dice score and 68.3% IoU. …”
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Research on Stability of Removal Function in Figuring Process of Mandrel of X-Ray-Focusing Mirror with Variable Curvature by Jiadai Xue, Yuhao Li, Mingyang Gao, Dongyun Gu, Yanlin Wu, Yanwen Liu, Yuxin Fan, Peng Zheng, Wentao Chen, Zhigao Chen, Zheng Qiao, Yuan Jin, Fei Ding, Yangong Wu, Bo Wang

“…This model predicts the compliance figuring process of variable-curvature symmetrical mandrels for X-ray grazing incidence mirrors by utilizing planar tool influence functions. …”
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Quantifying the chemical composition of weathering products of Hainan basalts with reflectance spectroscopy and its implications for Mars by Xing Wu, JiaCheng Liu, WeiChao Sun, Yang Liu, Joseph Michalski, Wei Tan, XiaoRong Qin, YongLiao Zou

“…We established a quantitative spectral model by combining the genetic algorithm and partial least squares regression (GA-PLSR) to predict the chemical properties (SiO2, Al2O3, Fe2O3) and index of laterization (IOL). …”
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An Observational Study on Flask Web Framework Questions on Stack Overflow (SO) by Luluh Albesher, Reem Alfayez

“…Afterward, we utilized the Latent Dirichlet Allocation (LDA) algorithm to identify Flask-related topics that are discussed within the set of the identified questions. …”
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Digitized Cursive Handwriting for Determining FMS in Early School-Age Children by Nurul Zainal Fanani, Ika Widiastuti, Khamid, Laszlo T. Koczy

“…In many countries, including Indonesia, teachers assess FMS by observing handwriting, often with the aid of an educational psychologist. However, this approach can be subjective and prone to observer bias. …”
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A numerical study on tread wear and fatigue damage of railway wheels subjected to anti-slip control by Yunfan Yang, Liang Ling, Jiacheng Wang, Wanming Zhai

“…This paper intends to investigate the impact of anti-slip control on wheel tread wear and fatigue damage under diverse wheel/rail friction conditions. To this end, a prediction model for wheel wear and fatigue damage evolution on account of a comprehensive vehicle-track interaction model is extended, where the wheel/rail non-Hertzian contact algorithm is used. …”
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Proposing a New Method for Customer Segmentation Based on Their Level of Loyalty and Defining Appropriate Strategies for Each Segment by Samira KHodabandehlou, Ali Akbar Niknafs

“…The obtained data have been analyzed using Clementine 14.2 software application using MLP and RBF neural networks as well as the K-means algorithm. The results of the study show that the proposed method provides the highest level of accuracy for predicting the customers’ loyalty. …”
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A novel re-entrant circular star-shaped auxetic honeycomb with enhanced energy absorption and anisotropic Poisson’s ratio by Danrong Shi, Zhuangzhuang Wang, Yongwei Li, Ruyuan Huo, Jin Zhang, Jianguo Cai

“…A multi-objective optimisation strategy was used by a Kriging surrogate model and NSGA-II algorithm to identify an optimal configuration with improved crashworthiness. …”
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An end-to-end deep learning solution for automated LiDAR tree detection in the urban environment by Julian R. Rice, G. Andrew Fricker, Jonathan Ventura

“…Specifically, we develop and train a novel PointNet-based neural network architecture to predict tree locations directly from LiDAR data augmented with multi-spectral imagery. …”
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Integrated Simulation Process Chain: From 3D Roll Forming Design to Crash Analysis by Sedlmaier Albert, Dietl Thomas, Abee André, Harrasser Johann, Pereira Miguel Sousa

“…This holistic approach enhances the fidelity of product performance predictions, offering a robust framework for optimizing forming processes and end-use structural integrity.…”
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Reinforcement Learning-Based Television White Space Database by Armie E. Pakzad, Raine Mattheus Manuel, Jerrick Spencer Uy, Xavier Francis Asuncion, Joshua Vincent Ligayo, Lawrence Materum

“…However, it is unclear if those databases have the prediction feature that gives TVWSDB the capability of decreasing the number of inquiries from SUs. …”
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Optimal Report Strategies for WBANs Using a Cloud-Assisted IDS by Shigen Shen, Keli Hu, Longjun Huang, Hongjie Li, Risheng Han, Qiying Cao

“…We afterward design a PBE-based algorithm to make the IDS-sensor decide when to report the monitored events. …”
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Inverse Identification of Constituent Elastic Parameters of Ceramic Matrix Composites Based on Macro–Micro Combined Finite Element Model by Sheng Huang, Le Rong, Zhuoqun Jiang, Yuriy V. Tokovyy

“…The inversion process of the constituent elastic parameters was established using the trust-region algorithm combined with an improved error function. …”
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Enhancement of joint quality for laser welded dissimilar material cell-to-busbar joints using meta model-based multi-objective optimization by Andreas Andersson Lassila, Tobias Andersson, Rohollah Ghasemi, Dan Lönn

“…In an meta model-based multi-objective optimization approach, the non-dominated sorting genetic algorithm II (NSGA-II) is used to efficiently search for trade-off solutions and the meta models are used for objective approximation. …”
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A model of feature extraction for well logging data based on graph regularized non-negative matrix factorization with optimal estimation by Kehong Yuan, Youlin Shang, Haixiang Guo, Yongsheng Dong, Zhonghua Liu

“…Abstract Reservoir oil-bearing recognition is the process of predicting reservoir types based on well logging data, which determines the accuracy of recognition. …”
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Modelling COVID-19 in the North American region with a metapopulation network and Kalman filter by Matteo Perini, Teresa K. Yamana, Marta Galanti, Jiyeon Suh, Roselyn Kaondera-Shava, Jeffrey Shaman

“…Background: Understanding the dynamics of infectious disease spread and predicting clinical outcomes are critical for managing large-scale epidemics and pandemics, such as COVID-19. …”
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Identification of Road Black Spots Based on the Sliding Window Optimization and Safety Performance Function Development by Shahin Shabani, Jalal Ayoubinejad, Nassir Baradaran Rahmanian

“…The optimization methodology employed in this study is as follows: Firstly, the road is segmented, and for each segment, different scenarios of window lengths are chosen using the Density-Based Spatial Clustering of Applications with Noise algorithm. Next, a Safety Performance Function is developed to calculate the predicted and expected number of crashes, as well as the Potential Safety Improvement, for each window movement across all selected scenarios within the segment. …”
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Deep Learning-Based Atmospheric Visibility Detection by Yawei Qu, Yuxin Fang, Shengxuan Ji, Cheng Yuan, Hao Wu, Shengbo Zhu, Haoran Qin, Fan Que

“…Furthermore, the paper addresses critical challenges in the field, including dataset quality, algorithm optimization, and practical application barriers, proposing future research directions, such as the development of large-scale, accurately labeled datasets, innovative learning strategies, and enhanced model interpretability. …”
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