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Similarities and Differences between ICME-driven Shocks Observed by VEX (∼0.72 au) and WIND (∼1.0 au)
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Phenome-wide association studies between SERINC2 and neuropsychiatric disorders
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Cardiovascular outcomes in long COVID-19: a systematic review and meta-analysis
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ViT-Based Face Diagnosis Images Analysis for Schizophrenia Detection
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Microbial-Induced Carbonate Precipitation for Strengthening Soft Clay
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Spatial distribution and influencing factors of secondhand smoke exposure in Chinese healthcare facilities: a cross-sectional survey
Published 2024-12-01“…The regions with the lowest exposure rates were Shanghai city and Beijing city (exposure rates between 0% and 5%), and the region with the highest exposure rate was Jiangxi province (exposure rate between 25% and 30%). …”
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Osteoarthritis and Degree of Fatigue are Associated with Pain Levels in Patients with Fibromyalgia Syndrome: A Cross-Sectional Study of 394 Patients
Published 2025-01-01“…Zihan Wang,1,2,* Tianyi Lan,1,2,* Yuqiao Zhang,1,2 Zijia Guo,3 Hongwei Yu,4 Guiyao Sun,5 Zhitian Wang,6 Zeran Yan,1 Qingwen Tao,1 Yuan Xu1 1Traditional Chinese Medicine Department of Rheumatism, China-Japan Friendship Hospital, Beijing, People’s Republic of China; 2Graduate School, Beijing University of Chinese Medicine, Beijing, People’s Republic of China; 3Graduate School, Inner Mongolia Medical University, Hohhot, People’s Republic of China; 4Department of Radiology, China-Japan Friendship Hospital, Beijing, People’s Republic of China; 5Department of Orthopedics, Shuangqiao Hospital, Beijing, People’s Republic of China; 6Science Faculty, University of Auckland, Auckland, New Zealand*These authors contributed equally to this workCorrespondence: Qingwen Tao; Yuan Xu, Email taoqg1@sina.com; xuyuan2004020@163.comObjective: To observe how osteoarthritis (OA) and degree of fatigue affect are associated with pain levels in patients with fibromyalgia syndrome (FMS).Methods: A cross-sectional study was conducted involving FMS patients. …”
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A Framework for the Land Use Change Dynamics Model Compatible with RCMs
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Learning Coupled Meteorological Characteristics Aids Short-Term Photovoltaic Interval Prediction Methods
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