BIOCELL, Vol.48, Suppl.3, pp. 1-15, 2024

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BIOCELL, Vol.48, Suppl.2, pp. 1-71, 2024

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Oncology Research Editorial Office

Oncology Research, Vol.32, No.8, pp. 1381-1381, 2024, DOI:10.32604/or.2024.055035

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Deema Mohammed Alsekait^1,*, Asif Nawaz², Ayman Nabil³, Mehwish Bukhari², Diaa Salama AbdElminaam^3,4,5,6,*

Computer Systems Science and Engineering, Vol.48, No.4, pp. 1031-1054, 2024, DOI:10.32604/csse.2024.051847

Abstract The article describes a novel method for sentiment analysis and requirement elicitation from social media feedback, leveraging advanced machine learning techniques. This innovative approach automates the extraction and classification of user requirements by analyzing sentiment in data gathered from social media platforms such as Twitter and Facebook. Utilizing APIs (Application Programming Interface) for data collection and Graph-based Neural Networks (GNN) for feature extraction, the proposed model efficiently processes and analyzes large volumes of unstructured user-generated content. The preprocessing pipeline includes data cleaning, normalization, and tokenization, ensuring high-quality input for the sentiment analysis model. By classifying… More >

Yue Wan, Nan Jiang^*, Ziyu Liu

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 3017-3034, 2024, DOI:10.32604/cmes.2024.051101

Abstract The Social Internet of Things (SIoT) integrates the Internet of Things (IoT) and social networks, taking into account the social attributes of objects and diversifying the relationship between humans and objects, which overcomes the limitations of the IoT’s focus on associations between objects. Artificial Intelligence (AI) technology is rapidly evolving. It is critical to build trustworthy and transparent systems, especially with system security issues coming to the surface. This paper emphasizes the social attributes of objects and uses hypergraphs to model the diverse entities and relationships in SIoT, aiming to build an SIoT hypergraph generation… More >

Meng Zhang^1,2, Xiangyang Luo^1,2,*, Ningbo Huang²

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2513-2532, 2024, DOI:10.32604/cmes.2024.050517

Abstract Geolocating social media users aims to discover the real geographical locations of users from their publicly available data, which can support online location-based applications such as disaster alerts and local content recommendations. Social relationship-based methods represent a classical approach for geolocating social media. However, geographically proximate relationships are sparse and challenging to discern within social networks, thereby affecting the accuracy of user geolocation. To address this challenge, we propose user geolocation methods that integrate neighborhood geographical distribution and social structure influence (NGSI) to improve geolocation accuracy. Firstly, we propose a method for evaluating the homophily… More >

Yuanqing He^*, Xinyue Yu, Yu Xia, Yanhua Cao

International Journal of Mental Health Promotion, Vol.26, No.6, pp. 463-474, 2024, DOI:10.32604/ijmhp.2024.051909

Abstract Background: Teacher burnout is a serious issue in the field of education, particularly in early childhood education, where teachers face high levels of work stress and emotional labor, leading to emotional exhaustion and job burnout. However, past research has not sufficiently explored the mechanisms of social skills, empathy, and mindfulness in mitigating teacher burnout. Therefore, this study aims to investigate the relationship between preschool teachers’ social skills, empathy, and mindfulness with job burnout, in order to provide theoretical basis and practical guidance for reducing teacher burnout. Methods: This research utilized a convenience sampling approach to… More >

Yun-Jung Choi¹, Heewon Song^2,*

International Journal of Mental Health Promotion, Vol.26, No.6, pp. 475-480, 2024, DOI:10.32604/ijmhp.2024.050824

Abstract During the rapid spread of COVID-19, first responders are at risk of being exposed to COVID-19 due to their role in providing first aid and responding to an unspecified number of people. This uncertainty can have adverse mental health effects, such as increased anxiety and fear. This study aimed to investigate the degree of association between fear of COVID-19, obsession with COVID-19, and post-traumatic stress disorder (PTSD) in emergency rescue firefighters. The participants were 150 emergency rescue firefighters working in Region S, Korea. They filled out self-report questionnaires: The data obtained through the Fear of… More >

Yuetan Wang^1,2,*, Xianle Yan^1,2, Lili Liu^1,2, Xiran Lu^1,2, Lan Luo^1,2, Xiaobin Ding^1,2,*

International Journal of Mental Health Promotion, Vol.26, No.6, pp. 429-438, 2024, DOI:10.32604/ijmhp.2024.050445

Abstract Social anxiety (SA) is a prevalent mental health issue among adolescents, and vulnerable narcissism (VN) can exacerbate this condition. This study aims to investigate the impact of vulnerable narcissism on social anxiety in adolescents, specifically focusing on the mediating effects of self-concept clarity (SCC) and self-esteem (SE) in the relationship between vulnerable narcissism and social anxiety. Through cluster sampling, a questionnaire survey was conducted among 982 students from three secondary schools in two provinces. The data was analyzed using structural equation modeling (SEM). The results revealed that there was a significant negative correlation between vulnerable More >

Shuai Lv^1,2, Zhaojun Chen^2,3, Jian Mao⁴, Hui Wang^2,5,*, Peibo Wu², Yujuan Hai¹

International Journal of Mental Health Promotion, Vol.26, No.6, pp. 491-498, 2024, DOI:10.32604/ijmhp.2024.048917

Abstract Objectives: To explore the relationship between college students’ self-esteem (SE) and their social phobia (SP), as well as the mediating role of fear of negative evaluation (FNE) and the moderating effect of perfectionism. Methods: A convenience sampling survey was carried out for 1020 college students from Shandong Province of China, utilizing measures of college students’ self-esteem, fear of negative evaluation, perfectionism, and social phobia. Data analysis was performed using the SPSS PROCESS macro. Results: (1) college students’ self-esteem significantly and negatively predicts their social phobia (β = −0.31, t = −10.10, p < 0.001); (2) fear of More >