Global dynamics of a vector-host epidemic model with age of infection by Yan-Xia Dang, Zhi-Peng Qiu, Xue-Zhi Li, Maia Martcheva

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Transparency Enhances Positive Perceptions of Social Artificial Intelligence by Ying Xu, Nora Bradford, Radhika Garg

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Whatsapp Addiction Affecting Students at Politeknik Sultan Mizan Zainal Abidin by Noor Rulhanim Binti Mohamad Ariffin, Norhafiza Binti Idris

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Training Program to Modify Manual Wheelchairs to Simplified Power Wheelchairs for Community Dwelling Elderly People and Caregivers by Suchitporn Lersilp, Supawadee Putthinoi, Theeratorn Lersilp, Kewalin Panyo, Autchariya Punyakaew

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Teacher reward challenges and student academic performance in selected secondary schools in Luwero district. by Auk, Timothy, Sekiwu, Denis, Edoru, John Michael

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Ecotourism and Poverty Reduction in Uganda. A Case Study of Batwa Communities in Kisoro District. by Kukundakwe, Obadiah

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Doença de chagas e seus vetores: Conhecer para prevenir! by Flavia dos Santos, Jairo Torres Magalhães-Junior, Ianei de Oliveira Carneiro, Ellenise Elsa Emidio Bicalho, Maurício dos Santos Conceição, Carlos Roberto Franke

“…Keywords: Health in Education; University Teaching-Research-Extension; Triatomines; Trypanosoma cruzi …”
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Microwave-Assisted Synthesized ZnO@APTES Quantum Dots Exhibits Potent Antibacterial Efficacy Against Methicillin-Resistant Staphylococcus aureus Without Inducing Resistance by Du F, Niu J, Hong Y, Fang X, Geng Z, Liu J, Xu F, Liu T, Chen Q, Zhai J, Miao B, Liu S, Zhang Y, Chen Z

“…Fangyuan Du,1,* Jingqi Niu,1,* Yu Hong,1 Xue Fang,2 Zhihui Geng,1 Jing Liu,1 Fangqi Xu,1 Tingshu Liu,1 Qifan Chen,1 Jingbo Zhai,3 Beiliang Miao,4 Shiwei Liu,4 Yi Zhang,1 Zeliang Chen1 1Key Laboratory of Livestock Infectious Diseases, Ministry of Education, and Key Laboratory of Ruminant Infectious Disease Prevention and Control (East), Ministry of Agriculture and Rural Affairs, College of Animal Science and Veterinary Medicine, Shenyang Agricultural University, Shenyang, 110866, People’s Republic of China; 2College of Animal Husbandry & Veterinary Medicine, Jinzhou Medical University, Jinzhou, 121001, People’s Republic of China; 3Key Laboratory of Zoonose Prevention and Control at Universities of Inner Mongolia Autonomous Region, Medical College, Inner Mongolia Minzu University, Tongliao, 028000, People’s Republic of China; 4Department of Nephrology and Endocrinology, Wangjing Hospital, Chinese Academy of Chinese Medical Science, Beijing, 100102, People’s Republic of China*These authors contributed equally to this workCorrespondence: Yi Zhang; Zeliang Chen, Key Laboratory of Livestock Infectious Diseases, Ministry of Education, and Key Laboratory of Ruminant Infectious Disease Prevention and Control (East), Ministry of Agriculture and Rural Affairs, College of Animal Science and Veterinary Medicine, Shenyang Agricultural University, 120 Dongling Road, Shenyang, 110866, Liaoning, People’s Republic of China, Email 2005500042@syau.edu.cn; chenzliang5@mail.sysu.edu.cnBackground: Antibiotic resistance of many bacteria, including Methicillin-resistant Staphylococcus aureus (MRSA), has become a major threat to global health. …”
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Attitudes Toward Psychotherapeutic Treatment and Health Literacy in a Large Sample of the General Population in Germany: Cross-Sectional Study by Rebekka Schröder, Tim Hamer, Ralf Suhr, Lars König

“…Pearson correlations (age), ANOVAs (level of education and subjective social status), and t tests (experience with psychotherapy, gender, and migration background) were used to analyze how these relate to attitudes toward psychotherapy. …”
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Komparasi Machine Learning Berbasis Pso Untuk Prediksi Tingkat Keberhasilan Belajar Berbasis E-Learning by Elin Panca Saputra, Siti Nurajizah, Mawadatul Maulidah, Nadiyah Hidayati, Taufik Rahman

“…Abstract   The development of the field of technology has a very fast development aspect. our research has the aim of transmitting knowledge about machine learning which has become so popularly used until now, in this study how to get attribute selection features and get predictive results from learning at universities or educational institutions that apply learning by distance learning methods or e-learning. …”
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Coronary Heart Disease Risk Prediction Model Based on Machine Learning by YUE Haitao, HE Chanchan, CHENG Yuyou, ZHANG Sencheng, WU You, MA Jing

“…Conclusion This study not only confirmed known factors affecting CHD but also identified potential impacts of self-assessed health level, income level, and education level on CHD. The performance of the five algorithms was significantly enhanced after employing two data balancing methods. …”
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Analysis of factors causing delays in seeking medical attention and its relationship with short-term prognosis in patient with acute ischemic stroke (急性缺血性脑卒中患者延迟就医原因与短期预后相关性分析)... by PENG Hong (彭红), CHEN Xiangyang (陈向阳), ZHANG Xiuliang (张修亮)

“…It is required to enhance the public health education about identification of stroke signs. …”
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KORELASI BODY MASS INDEX (BMI) DENGAN VO2MAX PADA ATLET SEMI-PROFESIONAL FUTSAL KOTA BLITAR by Lawrenza Berliana Dwi Saputri, Trinovandhi Setyawan, Muhammad Nidomuddin, Hari Pamungkas, Shoffurijal Agyanur, Ashari Husen

“…JOSSAE (Journal of Sport Science and Education), 8(2), 129–136. https://doi.org/10.26740/jossae.v8n2.p129-136 Pedro, R. …”
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Association between Helicobacter pylori Infection and Diabetes: A Cross-Sectional Study in China by Sailimai Man, Yuan Ma, Cheng Jin, Jun Lv, Mingkun Tong, Bo Wang, Liming Li, Yi Ning

“…After adjustment of age, sex, family history of diabetes, smoking, education, stroke, coronary heart disease, BMI, SBP, TG, HDL-C, and LDL-C, multivariate logistic regression analysis found no association between H. pylori infection and diabetes (OR 1.02, 95% CI 0.88-1.18). …”
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Sociodemographic factors associated with prenatal care utilization in Arkansas, United States by Pearl A. McElfish, Aaron Caldwell, Donya Watson, Jonathan Langner, Jennifer Callaghan-Koru, Austin Porter, Don E. Willis, Jennifer A. Andersen, Nicola L. Hawley, James P. Selig, Amir Forati, Maria R. Alcala, Lanita White, Enrique Gomez-Pomar, Clare C. Brown

“…Summary statistics were computed, and adjusted rates ratios were calculated adjusting for maternal age, maternal education, and parity for payer, race/ethnicity, and rural/urban residence. …”
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Strategies for diversification of economic activities in villages of Saqez city using SWOC method and QSPM matrix by ahadollah fatahi, afsaneh ahmadi, vahid riahi, hamid jalalian

“…The key factors of the migration and exodus of elite educated to Tehran and neighboring provinces, climate change and increasing natural hazards such as floods and droughts are the most important external barriers affecting the diversification of economic activities in the villages of the study area. …”
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Current applications and challenges in large language models for patient care: a systematic review by Felix Busch, Lena Hoffmann, Christopher Rueger, Elon HC van Dijk, Rawen Kader, Esteban Ortiz-Prado, Marcus R. Makowski, Luca Saba, Martin Hadamitzky, Jakob Nikolas Kather, Daniel Truhn, Renato Cuocolo, Lisa C. Adams, Keno K. Bressem

“…Abstract Background The introduction of large language models (LLMs) into clinical practice promises to improve patient education and empowerment, thereby personalizing medical care and broadening access to medical knowledge. …”
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Evidence-Based Practice in Primary Care Occupational Therapy: A Cross-Sectional Survey in Sweden by Ann-Charlotte Lindström, Susanne Bernhardsson

“…The findings suggest that education measures need to be taken to address the identified shortcomings.…”
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A serosurvey study of hand, foot and mouth disease in healthy children aged 6 to 71 months old in West Bandung and Bandung Region, Indonesia by Rodman Tarigan Girsang, Kusnandi Rusmil, Eddy Fadlyana, Budi Setiabudiawan, Riyadi Adrizain, Rizky Perdana Mulyadi, Arief Budiman, Rona Kania Utami, Behesti Zahra Mardiah, Muhammad Gilang Dwi Putra, Frizka Primadewi Fulendry, Dinda Tiaraningrum Nashsyah, Hadyana Sukandar

“…Child age, sex, nutritional status, height/age, immunisation status, parental income, and father’s and mother’s educations were not statistically related in rural and urban areas (p > 0.05) because the rate of IgG EV71 seropositivity was very high. …”
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Correlates of access to sanitation facilities and benefits received from the Swachh Bharat Mission in India: analysis of cross-sectional data from the 2018 National Sample Survey by Pradeep Kumar, Sayeed Unisa, Srayasi Prakash, Preeti Dhillon

“…Limited and unimproved facilities decreased significantly (p<0.001) with increase in economic status, although poor and less educated households received the maximum benefit from the Swachh Bharat Mission.Conclusion The mission has been successful in increasing access overall; however, many people continue to lack access to improved sanitation and there remains a need to follow up poor and rural households to determine their usage of and the current state of their sanitation facilities.…”
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