Modeling Community Evolution Characteristics of Dynamic Networks with Evolutionary Bayesian Nonnegative Matrix Factorization by Wei Yu, Xiaoming Li, Huaming Wu, Xue Chen, Minghu Tang, Yang Yu, Wenjun Wang

“…This leads to inaccurate results of temporal community structure analysis with a two-step strategy. Fortunately, a few approaches take the evolution characteristics into account for modeling temporal community structures. …”
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Impacts of Changes in Oasis Farmland Patterns on Carbon Storage in Arid Zones—A Case Study of the Xinjiang Region by Shanshan Meng, Jianli Ding, Jinjie Wang, Shuang Zhao, Zipeng Zhang

“…This research integrates the PLUS and InVEST models to calculate the carbon effects resulting from the spatiotemporal changes in farmland distribution in Xinjiang. …”
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Application of the hierarchical model of intrinsic and extrinsic motivation in the context of exercise: a systematic review by Bernardo Viveiros, Miguel Jacinto, Miguel Jacinto, Raúl Antunes, Raúl Antunes, Rui Matos, Rui Matos, Nuno Amaro, Nuno Amaro, Luís Cid, Luís Cid, Nuno Couto, Nuno Couto, Diogo Monteiro, Diogo Monteiro

“…Seven studies were considered for analysis and subjected to a methodological quality assessment The results showed that the variables that make up the social factors (e.g., supportive/thwarting behaviors) tend to be associated with satisfaction of basic psychological needs (BPN) (r = 0.51, p < 0.01; r = −0.73, p < 0.01) and with frustration of BPN (r = −0.39, p < 0.01; r = 0.78, p < 0. 01), BPN satisfaction and frustration tend to be associated with autonomous forms of motivation (r = 0.57, p < 0.01; r = −0.63, p < 0.01) and controlled forms of motivation (r = −0.76, p < 0.01; r = 0.46, p < 0.01) and autonomous and controlled forms of motivation are associated with behavioral consequences (e.g., intention) (r = 0.19, p < 0.01; r = −0.17, p < 0.01). …”
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Exploring T-cell metabolism in tuberculosis: development of a diagnostic model using metabolic genes by Shoupeng Ding, Chunxiao Huang, Jinghua Gao, Chun Bi, Yuyang Zhou, Zihan Cai

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Impact of New Mobility Solutions on Travel Behaviour and Its Incorporation into Travel Demand Models by Ada Garus, Borja Alonso, Maria Alonso Raposo, Biagio Ciuffo, Luigi dell’Olio

“…An overview and comparison of relevant studies implementing activity or trip-based demand models and other methodologies are presented. The analysis shows that the results of the different studies heavily depend on the extent to which behavioural changes are considered. …”
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VEGF-C — a biomarker of renal injury in the experimental model of intra-abdominal hypertension by V. V. Iakovlev, A. V. Badaeva, E. I. Ivanova, L. O. Severgina, L. D. Maltseva, O. L. Morozova

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A Novel Learning-Based MPC Method via Basic-Residual Cooperative Model by Yuesheng Liu, Zhongxian Xu, Ning He, Lile He, Fuan Cheng

“…The proposed method significantly enhances the model adaptability and computational efficiency of nonlinear dynamic systems, such as autonomous vehicles and robots.…”
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Constructing a predictive model for acute mastitis in lactating women based on machine learning by Liujing Zhu, Zuyan Huang, Yan Chen, Guangqiu Li, Liwen Liu

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Simulation Modeling of Energy Efficiency of Electric Dump Truck Use Depending on the Operating Cycle by Aleksey F. Pryalukhin, Boris V. Malozyomov, Nikita V. Martyushev, Yuliia V. Daus, Vladimir Y. Konyukhov, Tatiana A. Oparina, Ruslan G. Dubrovin

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Research on Traffic Accident Severity Level Prediction Model Based on Improved Machine Learning by Jiming Tang, Yao Huang, Dingli Liu, Liuyuan Xiong, Rongwei Bu

“…Decision tree, XGBoost, and random forest algorithms, respectively, were applied for the secondary prediction. The analysis results show that the improved machine learning model is significantly superior to a single model in the overall performance. …”
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Elucidating postoperative dynamics in tractional retinal detachment: a systematic review and meta-analysis of structural and functional outcomes following diabetic vitrectomy, incl... by Miguel A. Quiroz-Reyes, Erick A. Quiroz-Gonzalez, Miguel A. Quiroz-Gonzalez, Virgilio Lima-Gomez

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MMAgentRec, a personalized multi-modal recommendation agent with large language model by Xiaochen Xiao

“…We conducted extensive evaluations to assess the effectiveness of our proposed model, including an ablation study, comparison with state-of-the-art methods, and performance analysis on multiple datasets. …”
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Development and validation of a prediction model based on a nomogram for tuberculous pleural effusion by Suli Liu, Suli Liu, Yao Yang, Yao Yang, Dongmei Wang, Lijuan Gao, Lijuan Gao, Jiangyue Qin, Jiangyue Qin, Yanqiu Wu, Yanqiu Wu, Diandian Li, Diandian Li, Xiaohua Li, Mei Chen, Hao Wang, Hao Wang, Yongchun Shen, Yongchun Shen, Fuqiang Wen, Fuqiang Wen, Fangying Chen

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Analysis and validation of serum biomarkers in brucellosis patients through proteomics and bioinformatics by Xiao Li, Bo Wang, Xiaocong Li, Juan He, Yue Shi, Rui Wang, Dongwei Li, Ding Haitao, Ding Haitao

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Modeling the distribution of the invasive snail Physella acuta in China: Implications for ecological and economic impact by Yingxuan Yin, Anyuan Xu, Xiaowen Pan, Qing He, Aoxun Wu, Linya Huang, Yinjuan Wu, Xuerong Li

“…Methods: Global distribution data of P. acuta were collected and screened using “ENMtool”; environmental variables were screened based on contribution of environmental variables, jackknife test and variable correlation analysis using MaxEnt 3.4.1 and GraphPad Prism 8; “kuenm” package in R 4.0.4 software was used to calculate and adjust model parameters; the optimized MaxEnt model was used to predict the potential distribution range of P. acuta in China under different climate scenarios; ArcGIS 10.7 was used to process and visualize the results. …”
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An intelligent dashboard framework for healthcare data analysis and disease outbreak prediction by B. Divya Prabha, P. S. S. Akilashri

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A study on the risk prediction model for venous thromboembolism in orthopedic inpatients based on machine learning by Bo Zhang, Yumei Qin, Liandi Jiu, Chunming Qin, Jiangbo Wang, Haiqing Zhao

“…ObjectiveTo construct a venous thromboembolism (VTE) risk prediction model for orthopedic inpatients using machine learning modeling techniques, identify high-risk patients, and optimize clinical interventions.MethodsThis study involved a retrospective analysis of 286 orthopedic inpatients from Nanxishan Hospital of Guangxi Zhuang Autonomous Region (The Second People’s Hospital of Guangxi Zhuang Autonomous Region) from January 1, 2022 to December 31, 2022. …”
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Predictive Modeling for Fetal Health: A Comparative Study of PCA, LDA, and KPCA for Dimensionality Reduction by Ariana Deyaneira Jimenez-Narvaez, Victor David Casa Vaca, Jonathan Javier Loor-Duque, Isidro Rafael Amaro Martin, Ivan Galo Reyes-Chacon, Paulina Vizcaino, Manuel Eugenio Morocho-Cayamcela

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Optimized Offloading in Vehicular Edge Computing: A Game Theoretic Analysis by Abdelkarim Ait Temghart, Mbarek Marwan, Mohamed Baslam

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Analysis of the speed and curvature of the trajectory in the problem of pursuing a set of targets by A. A. Dubanov

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