Weidong Li^1,2, Zh Yeng Chong³, Yaqing Mao^4,*, Wanying Zhang⁴, Wei Xu³, Mingwei Li⁵, Yiyun Wang⁶, Huaxia Xiong⁴

International Journal of Mental Health Promotion, Vol.27, No.2, pp. 161-177, 2025, DOI:10.32604/ijmhp.2025.059090 - 03 March 2025

Abstract Background: The Teaching Personal and Social Responsibility (TPSR) model in physical education (PE) has been shown to promote Social and emotional competence (SEC). However, the underlying mechanisms through which TPSR enhances SEC, particularly in university students within the Chinese context, remain unclear. This study aims to explore the effects of TPSR and the mediating roles of self-efficacy and grit in improving SEC. Methods: 71 Chinese university students were in the TPSR group, and 39 in the Traditional Teaching Model (TTM) control group, assessed before and after a 14-week intervention. The Adapted Social and Emotional Competence… More >

Xiaowen Wan¹, Wenbin Sheng¹, Rong Huang¹, Cheng Zeng¹, Xu Zhou^2,*, Yuan Wu³, Xiaohui Cao¹, Xiaoke Chen¹

International Journal of Mental Health Promotion, Vol.27, No.2, pp. 215-229, 2025, DOI:10.32604/ijmhp.2025.059074 - 03 March 2025

Abstract Background: As the digital age progresses, fear of missing out (FoMO) is becoming increasingly common, and the impact factor of FOMO needs to be further investigated. This study aims to explore the relationship between psychological security (PS) and FoMO by analyzing the mediating role of social networking addiction (SNA) and the moderating role of social self-efficacy (SSE). Methods: We collected a sample of 1181 college students (with a mean age of 19.67 ± 1.38 years) from five universities in a province of mainland China through cluster sampling. Data were gathered using the psychological security questionnaire… More >

Khalid Jamil¹, Wahab Khan¹, Bilal Khan², Sarwar Shah Khan^2,*

Digital Engineering and Digital Twin, Vol.3, pp. 1-16, 2025, DOI:10.32604/dedt.2025.058943 - 28 February 2025

Abstract Brain tumors are one of the deadliest cancers, partly because they’re often difficult to detect early or with precision. Standard Magnetic Resonance Imaging (MRI) imaging, though essential, has limitations, it can miss subtle or early-stage tumors, which delays diagnosis and affects patient outcomes. This study aims to tackle these challenges by exploring how machine learning (ML) can improve the accuracy of brain tumor identification from MRI scans. Motivated by the potential for artificial intillegence (AI) to boost diagnostic accuracy where traditional methods fall short, we tested several ML models, with a focus on the K-Nearest More >

LI SUN^1,#, SHICHAO ZHUO^2,#, XIAOXIN LI², HUSHENG KONG³, WEIWEI DU³, CHONG ZHOU⁴, JUNXING HUANG^1,*

Oncology Research, Vol.33, No.3, pp. 641-651, 2025, DOI:10.32604/or.2024.050057 - 28 February 2025

Abstract Background: Cisplatin (DDP) has been used in the treatment of various human cancers. However, DDP alone lacks efficacy in treating triple-negative breast cancer (TNBC), and its clinical application is often hampered by side effects. Astragalus polysaccharide (APS) is one of the active components extracted from Astragalus membranaceus and has gained attention for its various biological properties. This research is aimed to evaluate the effectiveness of a combination of APS and DDP on TNBC and explore the potential mechanisms. Methods: The efficacy and mechanisms of single or combined treatment were evaluated using Cell Counting Kit-8 (CCK8) assay, Annexin… More >

Mohd Anjum¹, Naoufel Kraiem², Hong Min^3,*, Ashit Kumar Dutta⁴, Yousef Ibrahim Daradkeh⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.1, pp. 357-384, 2025, DOI:10.32604/cmes.2024.057889 - 17 December 2024

Abstract Machine learning (ML) is increasingly applied for medical image processing with appropriate learning paradigms. These applications include analyzing images of various organs, such as the brain, lung, eye, etc., to identify specific flaws/diseases for diagnosis. The primary concern of ML applications is the precise selection of flexible image features for pattern detection and region classification. Most of the extracted image features are irrelevant and lead to an increase in computation time. Therefore, this article uses an analytical learning paradigm to design a Congruent Feature Selection Method to select the most relevant image features. This process… More >

Joshua Winograd^1,*, John Lama^1,*, Alia Codelia-Anjum², Naeem Bhojani³, Dean S. Elterman⁴, Kevin C. Zorn^3,5, Eric Margolis⁶, Jamin Brahmbhatt⁷, Ricardo Gonzalez⁸, Bilal Chughtai²

Canadian Journal of Urology, Vol.31, No.6, pp. 12053-12059, 2024

Abstract Introduction: Benign prostatic hyperplasia (BPH) is a prevalent condition affecting a significant portion of the male population, leading to secondary lower urinary tract symptoms (LUTS). Alternative therapies such as phytotherapy using Lipidosterolic extract of Serenoa repens (LSESR USPlus) are commonly used. However, the efficacy of LSESr remains controversial due to conflicting data. We sought to determine the effect of a standardized USP-verified Saw Palmetto extract on male LUTS secondary to BPH.
Materials and methods: In this prospective single arm trial, we investigated the efficacy of a standardized USP-verified Saw Palmetto extract in treating male LUTS secondary to More >

Xiaofeng Wang^1,#, Xingwei Chen^2,#, Shilin Wang¹, Xia Li¹, Zhongyuan Lu¹, Wenlong Wang¹, Xu Wang^1,*

Congenital Heart Disease, Vol.19, No.5, pp. 489-498, 2024, DOI:10.32604/chd.2024.054441 - 31 December 2024

Abstract Objective: Pulmonary hypertension is a crucial factor affecting the recovery after Glenn procedure. This study explores the effects of intravenous treprostinil on hemodynamic status and hospital postoperative recovery under different administration strategies. Methods: We retrospectively included pediatric patients admitted to Fuwai Hospital from 2019 to 2022 who underwent the Glenn procedure and had intraoperative measurements of mean pulmonary artery pressure (mPAP) >15 mmHg postoperatively. Patients with non-anatomical single ventricle physiology undergoing the Glenn procedure and those requiring postoperative extracorporeal membrane oxygenation were excluded. Due to the standardized use of treprostinil in our center starting in… More >

Honggang Liu¹, Xiaobing Lu^2,*, Bin Chen¹, Xu Wang¹, Miaoyue Xia^3,4,*

International Journal of Mental Health Promotion, Vol.26, No.12, pp. 997-1007, 2024, DOI:10.32604/ijmhp.2024.057771 - 31 December 2024

Abstract Background: With the widespread adoption of synchronous online instruction, concerns have arisen regarding teachers’ professional functioning in this new context. While previous studies have extensively explored teacher psychology, the control-value theory (CVT) provides additional insights into teachers’ experiences. As limited research has specifically addressed the psychological experiences of primary school teachers in online teaching settings, this study investigated the relationships among teachers’ online self-efficacy, anxiety, and engagement through the CVT framework. Methods: This study employed a quantitative research design, conducting a questionnaire survey of 1037 Chinese primary school teachers recruited through convenience and snowball sampling.… More >

Peichao Xie^1,#, Kexu Chen^1,#, Yuxuan Ji¹, Qi Wang¹, Kaiyun Li^1,*, Fanlu Jia¹, Ting Peng²

International Journal of Mental Health Promotion, Vol.26, No.11, pp. 887-895, 2024, DOI:10.32604/ijmhp.2024.056305 - 28 November 2024

Abstract Background: Coping self-efficacy can help individuals mitigate the adverse emotional impacts of stress, anxiety, and other negative emotions, and it also influences individuals’ academic performance, including school adjustment and academic burnout. It is an important factor affecting the mental health of adolescents. However, there is no measurement tool specifically designed for adolescent populations in China. Therefore, the purpose of this study is to assess the applicability of the Coping Self-Efficacy Scale (CSES) among Chinese adolescents. Methods: In September 2023, this study collected data through online questionnaires and ultimately conducted item analysis, exploratory factor analysis, confirmatory… More >

Grace Gau¹, Minerva Singh^2,3,*

Revue Internationale de Géomatique, Vol.33, pp. 427-443, 2024, DOI:10.32604/rig.2024.055752 - 11 October 2024

Abstract This study examines how socio-economic characteristics predict flood risk in London, England, using machine learning algorithms. The socio-economic variables considered included race, employment, crime and poverty measures. A stacked generalization (SG) model combines random forest (RF), support vector machine (SVM), and XGBoost. Binary classification issues employ RF as the basis model and SVM as the meta-model. In multiclass classification problems, RF and SVM are base models while XGBoost is meta-model. The study utilizes flood risk labels for London areas and census data to train these models. This study found that SVM performs well in binary… More >