The impact of insufficient sleep on dietary choices and physical activity behaviors: evidence from a randomized cross-over trial by David L. Dickinson, Naomi Kakoschke, Sean P. A. Drummond

“…Furthermore, SR predicted reduced average hourly PA (p < .01), increased sedentary behaviors (p < .01), and more prolonged bouts of sitting (p < .01) for all participants. …”
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Differential Flight Responses of Sympatric Raptor Species to Weather Conditions and Extreme Temperature Events by Lara Naves‐Alegre, Hernán García‐Mayoral, Jon Morant, Juan Manuel Pérez‐García, Andreia Dias, Elvira Cano‐Montes, Ángel Sánchez, Víctor García‐Matarranz

“…Each species exhibited unique strategies and responsiveness to heatwaves, reflecting diverse adaptive capacities and behavioral flexibilities. Specifically, Bonelli's eagle displayed comparatively minor adjustments in its flight strategy during periods of extreme temperature, contrasting with the pronounced behavioral variations observed in the golden eagle. …”
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Machine learning models for predicting the risk of depressive symptoms in Chinese college students by Chengfu Yu, Xiangxuan Kong, Weijie Yu, Xingcan Ni, Jing Chen, Xiaoyan Liao

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A Prediction Method of Mobile User Preference Based on the Influence between Users by Yancui Shi, Jianhua Cao, Congcong Xiong, Xiankun Zhang

“…User preference will be impacted by other users. To accurately predict mobile user preference, the influence between users is introduced into the prediction model of user preference. …”
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Who is more inclined to reduce social media addictive tendency behaviors? Explanations based on sex and proactive personality by Jian Mao, Pei Chen, Jiajie He, Jiarong Chen, Yangang Nie

“…These results can help to increase the motivation of college students to reduce social media addictive tendency behaviors and further promote the improvement of social media addictive tendency behaviors.…”
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Predictive model of the relationship between social support, body image perception, and physical activity among university students by Xuejiao Gao, Xiaolin Wang, Chen Soon Chee, Shamsulariffin bin Samsudin, Muhammad Zarif Hassan, Luhong Ma, Pan Liu, Yuming Zhang

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Constructing a predictive model of negative academic emotions in high school students based on machine learning methods by Shumeng Ma, Ning Jia, Xiuchao Wei, Wanyi Zhang

“…We concluded that the most important factors for predicting high school students’ negative academic emotions are affect control, followed by ability attribution, luck attribution, background attribution, self-efficacy for learning behaviors, and self-efficacy for learning abilities. …”
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From interdependence to pro-environmental behavior: Development and validation of the Preference for Explanations in Terms of Interdependence (PETI) scale for children by Fantine Lisa Surret, Sofia Besomi, Margaux Chehab, Wojciech Świątkowski, Céline Buchs, Emilio Paolo Visintin, Fabrizio Butera

“…We argue that understanding social and natural phenomena in terms of interdependence could predict children's pro-environmental behaviors (PEBs). …”
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Care burden among Iranian family caregivers of patients with schizophrenia: the predictive role of quality of life and life satisfaction by Maede Esmaeeli, Seyedmohammad Mirhosseini, Seyedmohammad Mirhosseini, Somaye Minaei-Moghadam, Saeed Ghasempour, Mohammad Hasan Basirinezhad, Hossein Ebrahimi

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Predictive model for sarcopenia in chronic kidney disease: a nomogram and machine learning approach using CHARLS data by Renjie Lu, Shiyun Wang, Pinghua Chen, Fangfang Li, Fangfang Li, Pan Li, Qian Chen, Xuefei Li, Fangyu Li, Suxia Guo, Jinlin Zhang, Jinlin Zhang, Dan Liu, Zhijun Hu

“…Forty-nine variables encompassing socio-demographic, behavioral, health status, and biochemical factors were analyzed. …”
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Prognostic assessment of “psychiatrist-avoidant behavior” in patients with somatization disorders who applied to primary health care institutions by A. V. Vasileva, Yu. V. Bogushevskaya, A. I. Ivchenko

“…The purpose of this study is to develop a predictive model of the relationship between the duration of “psychiatrist-avoidant behavior” and clinical and psychological parameters in patients with somatization disorders. …”
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Predicting crude oil returns and trading position: evidence from news sentiment by Hail Jung, Daejin Kim

“…We study the effectiveness of textual information in predicting the returns of crude oil futures and understanding the behavior of market participants. …”
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Predicting financial default risks: A machine learning approach using smartphone data by Shinta Palupi, Gunawan, Ririn Kusdyawati, Richki Hardi, Rana Zabrina

“…This study leverages machine learning (ML) techniques to predict financial default risks using smartphone data, providing a novel approach to financial risk assessment. …”
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Machine learning-driven prediction model for cuproptosis-related genes in spinal cord injury: construction and experimental validation by Yimin Zhou, Xin Li, Zixiu Wang, Liqi Ng, Rong He, Chaozong Liu, Gang Liu, Xiao Fan, Xiaohong Mu, Yu Zhou, Yu Zhou

“…This study aimed to explore the relationship between SCI and cuproptosis and construct prediction models.MethodsGene expression data of SCI patient samples from the GSE151371 dataset were analyzed. …”
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Machine Learning-Based Anomaly Prediction for Proactive Monitoring in Data Centers: A Case Study on INFN-CNAF by Andrea Asperti, Gabriele Raciti, Elisabetta Ronchieri, Daniele Cesini

“…We evaluate several methods, including Long Short-Term Memory, Random Forest, and various neural networks, assessing their Accuracy and sensitivity in distinguishing normal from anomalous behaviors. The results demonstrate the effectiveness of these methods, not only in predicting anomalies but also in pinpointing critical areas within monitored metrics. …”
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Time series analysis for modeling and predicting confirmed cases of influenza a in Algeria by Djillali Seba, N. Benaklef, K. Belaide

“…This paper is dedicated to studying the distribution behavior and predicting confirmed cases of Influenza A within the Algerian context, a highly infectious dis- ease that causes widespread illness and deaths both in Algeria and globally. …”
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Machine Learning in E-Commerce: Trends, Applications, and Future Challenges by Elias Dritsas, Maria Trigka

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Thermal performance evaluation of water-based gel packs and insulating covers: A case study on raw milk preservation for local transport by Nattawut Chaomuang, Onrawee Laguerre, Denis Flick, Steven Duret

“…Comparative analysis revealed similar thermal behaviors for milk and water, enabling the extrapolation of results. …”
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Socioeconomic status and lifestyle as factors of multimorbidity among older adults in China: results from the China Health and Retirement Longitudinal Survey by Wei Gong, Wei Gong, Wei Gong, Xiaoxiao Hu, Huimin Cui, Huimin Cui, Yuxin Zhao, Yuxin Zhao, Hong Lin, Hong Lin, Hong Lin, Peng Sun, Peng Sun, Jianjun Yang, Jianjun Yang

“…While previous studies have highlighted the role of individual behaviors, the complex interaction between lifestyle factors and socioeconomic status (SES) in multimorbidity remains unclear.MethodsUsing nationally representative data from the China Health and Retirement Longitudinal Study (CHARLS), we developed predictive models to identify key determinants of multimorbidity among individuals aged ≥60 years. …”
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Machine learning-based e-commerce platform repurchase customer prediction model. by Cheng-Ju Liu, Tien-Shou Huang, Ping-Tsan Ho, Ping-Tsan Ho, Jui-Chan Huang, Ching-Tang Hsieh

“…This paper analyzes the shortcomings and challenges of traditional online shopping behavior prediction methods, and proposes an online shopping behavior analysis and prediction system. …”
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