Extracellular Vesicles: A Novel Target for Exercise-Mediated Reductions in Type 2 Diabetes and Cardiovascular Disease Risk by Natalie Z. M. Eichner, Uta Erdbrügger, Steven K. Malin

“…However, only about 40–50% of this CVD risk reduction is accounted for by adiposity, hyperglycemia, hypertension, and dyslipidemia. …”
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Sirtuin1 mitigation of calcium oxalate nephropathy via enhancing itaconate abundance through reduction of histone trimethylation by Xiangyang Yao, Haoran Liu, Chen Duan, Yangjun Zhang, Xiaoliang Wu, Bo Li, Sheng Li, Yan Gong, Tongzu Liu, Xinghuan Wang, Hua Xu

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Correction: Risk prediction models for stress urinary incontinence after pelvic organ prolapse (POP) surgery: a systematic review and meta-analysis by Bi Jun Yu, Hao Chong He, Li Wang, Han Mei Shao, Ying Min Liu, Xiao Ying Yan, Jian Liu

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Comparative physiological and transcriptomic analyses identify computationally predicted key genes and regulatory pathways in non-heading Chinese cabbage under heat stress by Wei Liu, Zhangyang Dai, Jingyi Jia, Xiaofeng Li, Hongfang Zhu, Xianzhao Kan, Bo Zhu

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Preliminary feasibility of mindfulness in motion to improve physiological biomarkers of wellbeing in healthcare providers during dayshift hours by Justin J. Merrigan, Maryanna Klatt, Catherine Quatman-Yates, Angela Emerson, Jamie Kronenberg, Morgan Orr, Jacqueline Caputo, Kayla Daniel, Anne-Marie Duchemin, Beth Steinberg, Joshua A. Hagen

Subjects: “…Mindfulness based stress reduction…”
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Ambient temperature and wet bulb globe temperature outperform heat index in predicting hydration status and heat perception in a semi-arid environment by Lilian Baker, Hannah Jacobson, Amanda McGrosky, Elena Hinz, Faith Wambua, Alison Sherwood, Tiffany-Chrissy Mbeng, Rosemary Nzunza, David R. Braun, Emmanuel Ndiema, Herman Pontzer, Asher Y. Rosinger

“…These associations were stronger among children than adults.Conclusion In a hot, semi-arid climate, ambient temperature and WBGT accurately predict human water needs and heat stress, with children more vulnerable to dehydration. …”
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Geophysical characterization methods for sweet spots in shale oil: A case study of Niuzhuang Subsag in Shengli Oilfield by ZHANG Qiang, WANG Jing, ZHOU Haiting, LÜ Shichao

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The analysis of the progressive local failure process of the Longquan Reservoir dam based on the global-local dynamic strength reduction method by Xin Qu, Fangfang Diao, Cheng Li, Xingqian Xu, Zihan Wang, Shuai Hao

“…Combining this model with the global-local dynamic strength reduction method, the progressive local failure process of the dam under heavy rain conditions was simulated. …”
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Generalizable deep learning models for predicting laboratory earthquakes by Chonglang Wang, Kaiwen Xia, Wei Yao, Chris Marone

“…With fine-tuning, CNN models trained on one lab fault configuration predict time to failure and shear stress for another configuration at varying fault slip rates. …”
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Identification and characterization of forced degradation products of lumateperone tosylate by LC-HRMS, GC-MS, NMR, and in silico toxicity prediction by Nehal Bhatt, Devendra Sonaje, Vijiaya Madhyanapu Golla, Rahul Khemchandani, Roshitha K. R, Arun Kumar Gupta, Gananadhamu Samanthula

“…This study presents a detailed forced degradation profiling of lumateperone under stress conditions to develop a stability-indicating method capable of separating degradation products (DP-1 to DP-11), followed by their identification and characterization using hyphenated analytical techniques. …”
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A dataset of psychological emotional expressions relating to depression, anxiety and stress for Malay language model trainingOSF by Ruhaila Maskat, Nor Hapiza Mohd Ariffin, Nurul Akhmal Dzulkefli

“…The dataset can benefit research works in the areas of emotional speech recognition, emotional intelligence understanding and emotional prediction. The dataset consists of raw and pre-processed posts which include normalized and tokenized words suitable for training Malay Large Language Models and predictive analytics.…”
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Cardiovascular risk and stress in employees of a higher education institution by Eugênio Barbosa de Melo Júnior, Jayne Ramos Araujo Moura, Sâmia Suély Leal Borges, Açucena Leal de Araújo, Jackson Júnior Vieira de Castro, Ana Roberta Vilarouca da Silva

“…Objective: to analyze the association between high levels of stress and the frequency of cardiovascular risk factors in employees of a higher education institution. …”
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Cardiovascular risk and stress in employees of a higher education institution by Eugênio Barbosa de Melo Júnior, Jayne Ramos Araujo Moura, Sâmia Suély Leal Borges, Açucena Leal de Araújo, Jackson Júnior Vieira de Castro, Ana Roberta Vilarouca da Silva

“…Objective: to analyze the association between high levels of stress and the frequency of cardiovascular risk factors in employees of a higher education institution. …”
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Data From Early Childhood Educators’ Work and Stress Study by Randi A. Bates, Jaclyn M. Dynia, Bailey E. Martin

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job stress, education and work ability among refinery workers by S Safari, E Habibi, H Dehghan, B Mahaki, A Hassanzadeh

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Examining the after-school study burden of Chinese secondary school students following burden reduction policies: a sociological analysis by Yunfang Ran, Xi Wu, Yitao Wang, Zhiying Zhou, Yuan Yin

“…Findings This study found that burden reduction policies have brought some relief to student participants due to tailored assignments, learning support, and diversified after-school programs, although the pressure remained high. …”
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Educational Stress and Artificial Intelligence Tools: A Study of International Students’ Experiences in Spanish Higher Education by Aida Mehrad, Mohammad Hossein Tahriri Zangeneh, Meriem Bouzedif, Neema George Rweramila

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Prediction of instability of formwork concrete pier based on big data machine learning for secondary mining without coal pillar mining by Yanhui Zhu, Ye Tian, Peilin Gong, Kang Yi, Tong Zhao

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Predicting potato plant vigor from the seed tuber properties by Elisa Atza, Rob Klooster, Falko Hofstra, Frank van der Werff, Hans van Doorn, Neil Budko

“…At the same time, for the variety that appeared to be less sensitive to environmental stresses, we obtained cross-field and cross-year vigor predictions correlating up to $$80\%$$ with the measurements. …”
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Genetic Programming-Based Prediction Model for Microseismic Data by Man Wang, Hongwei Zhou, Dongming Zhang, Yingwei Wang, Weihang Du, Beichen Yu

“…The results showed that the actual seismic and energy data of the working faces exhibited good agreement with those predicted by the prediction formulas. The high energy and seismic distribution were caused by the mining stress at the edge of working faces due to the excavation and unloading effect of the surface, and the energy and seismic evolution predicted by GP could also show this phenomenon well.…”
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