Yamixa Delgado^1,*, Caliani Gaytan¹, Naydi Perez², Eric Miranda³, Bryan Colón Morales¹, Mónica Santos¹

Congenital Heart Disease, Vol.19, No.1, pp. 19-31, 2024, DOI:10.32604/chd.2024.046339

Abstract Background: Given the pervasive issues of obesity and diabetes both in Puerto Rico and the broader United States, there is a compelling need to investigate the intricate interplay among body mass index (BMI), pregestational, and gestational maternal diabetes, and their potential impact on the occurrence of congenital heart defects (CHD) during neonatal development. Methods: Using the comprehensive System of Vigilance and Surveillance of Congenital Defects in Puerto Rico, we conducted a focused analysis on neonates diagnosed with CHD between 2016 and 2020. Our assessment encompassed a range of variables, including maternal age, gestational age, BMI, pregestational diabetes, gestational diabetes, hypertension,… More >

Abdullah B. Alansare^*

International Journal of Mental Health Promotion, Vol.26, No.1, pp. 11-20, 2024, DOI:10.32604/ijmhp.2023.044656

Abstract Emerging evidence suggests the existence of ‘paradoxical’ relationships between domain-specific sedentary behavior (SB) and health outcomes. This study assessed the associations of total and domain-specific SB, by pattern, with symptoms of mental disorders in Saudi adults. Participants (n = 554) completed a web-based survey between January 18th, 2023 and February 5th, 2023. Total SB was measured by using the Sedentary Behavior Questionnaire. Total SB was then partitioned into leisure, occupational, and commuting SB during weekdays and on weekend days. Symptoms of mental disorders including symptoms of depression, anxiety, and stress were evaluated by using the DASS-21 questionnaire. Adjusted linear regressions… More >

Yulan Yu^1,2, Rassamee Chotipanvithayakul³, Hujiao Kuang⁴, Wit Wichaidit^3,*, Chonghua Wan^1,2,*

International Journal of Mental Health Promotion, Vol.25, No.12, pp. 1343-1351, 2023, DOI:10.32604/ijmhp.2023.043446

Abstract Adverse childhood experiences (ACEs) can negatively affect mental health, whereas character strengths seem to be positively correlated with mental health. Detailed information on the history of ACEs among university students in China and the extent which mental health is associated with ACEs and character strengths can contribute to the needed empirical evidence for relevant stakeholders. Objectives of this study are 1) to estimate the prevalence of ACEs among undergraduate students in Southern China; and 2) to assess the extent which mental health outcomes (positive growth, well-being, and depression) are associated with ACEs and character strengths among undergraduate students in Southern… More >

Yajun Liang^1,2,#, Juyun Zheng^1,#, Junduo Wang^1,#, Zhaolong Gong¹, Zhiqiang Li³, Ling Min⁴, Zeliang Zhang², Zhiwei Sang², Yanying Qu², Xueyuan Li^1,*, Quanjia Chen^2,*

Phyton-International Journal of Experimental Botany, Vol.92, No.12, pp. 3345-3357, 2023, DOI:10.32604/phyton.2023.028755

Abstract Upland cotton (Gossypium hirsutum) is the most important plant producing natural fibers for the textile industry. In this study, we first investigated the phenotypic variation of seven agronomic traits of 273 diverse cotton accessions in the years 2017 and 2018, which were from 18 geographical regions. We found large variations among the traits in different geographical regions and only half of the traits in either years 2017 or 2018 followed a normal distribution. We then genotyped the collection with 81,612 high quality SNPs. Phylogenetic tree and population structure revealed a diverse genetic structure of the core collection, and geographical diversification… More >

Nadeem Malik^1,*, Saud Altaf¹, Muhammad Usman Tariq², Ashir Ahmed³, Muhammad Babar⁴

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1599-1615, 2023, DOI:10.32604/cmc.2023.040455

Abstract The severity of traffic accidents is a serious global concern, particularly in developing nations. Knowing the main causes and contributing circumstances may reduce the severity of traffic accidents. There exist many machine learning models and decision support systems to predict road accidents by using datasets from different social media forums such as Twitter, blogs and Facebook. Although such approaches are popular, there exists an issue of data management and low prediction accuracy. This article presented a deep learning-based sentiment analytic model known as Extra-large Network Bi-directional long short term memory (XLNet-Bi-LSTM) to predict traffic collisions based on data collected from… More >

ZHONGXIANG TANG^1,2, LILI WANG^1,2, GUOJUN WU^1,2, LING QIN^1,2,*, YURONG TAN^1,2,*

BIOCELL, Vol.47, No.11, pp. 2503-2516, 2023, DOI:10.32604/biocell.2023.031565

Abstract Background: Non-small cell lung cancer (NSCLC) has a poor prognosis with a low 5-year survival rate. Lung adenocarcinoma (LUAD) accounts for 50%. Facio-genital dysplasia-5 (FGD5), a member of a subfamily of Rho GTP-GDP exchange factors, may be a good molecular biomarker for diagnosis and prognosis. Objective: To explore the clinical application of FGD5, the study was designed to investigate the prognosis value of FGD5 expression and its correlation with immune infiltrates in LUAD patients. Methods: Through the Wilcoxon signed-rank test and logistic regression, the correlation between clinical characteristics and FGD5 expression was analyzed. Kaplan–Meier plotter analysis, Cox regression, and a… More > Graphic Abstract

Firas Abedi¹, Hayder M. A. Ghanimi², Abeer D. Algarni³, Naglaa F. Soliman^3,*, Walid El-Shafai^4,5, Ali Hashim Abbas⁶, Zahraa H. Kareem⁷, Hussein Muhi Hariz⁸, Ahmed Alkhayyat⁹

Computer Systems Science and Engineering, Vol.47, No.3, pp. 2791-2814, 2023, DOI:10.32604/csse.2023.038762

Abstract Data mining plays a crucial role in extracting meaningful knowledge from large-scale data repositories, such as data warehouses and databases. Association rule mining, a fundamental process in data mining, involves discovering correlations, patterns, and causal structures within datasets. In the healthcare domain, association rules offer valuable opportunities for building knowledge bases, enabling intelligent diagnoses, and extracting invaluable information rapidly. This paper presents a novel approach called the Machine Learning based Association Rule Mining and Classification for Healthcare Data Management System (MLARMC-HDMS). The MLARMC-HDMS technique integrates classification and association rule mining (ARM) processes. Initially, the chimp optimization algorithm-based feature selection (COAFS)… More >

Océane Phanatzis^1,2,*, Rébecca Ratel^1,2, Isabelle Barcos^1,2, Marie Daspas³, Emmanuelle Clairembault³, François Alla^1,2

Psycho-Oncologie, Vol.17, No.3, pp. 133-145, 2023, DOI:10.32604/po.2023.044916

Abstract Objectif : L’objectif de cet article est d’exposer les composantes interventionnelles et contextuelles d’un accompagnement au sevrage tabagique dans le cadre des soins oncologiques de support (SOS) délivrés par une association, qui soit viable en contexte français et efficace, et de décrire le processus de recherche partenariale dans lequel elles ont été élaborées. Méthodes : L’intervention a été développée à partir d’un ensemble de données recueillies lors d’une étude de viabilité à la mise en place d’une offre de sevrage tabagique au sein de la Ligue Contre le Cancer Gironde, une revue de la portée sur les interventions probantes et… More >

Hao Yao¹, Shuzhen Chen^2,*

International Journal of Mental Health Promotion, Vol.25, No.9, pp. 1053-1065, 2023, DOI:10.32604/ijmhp.2023.028844

Abstract In the context of the COVID-19 pandemic and under the pressure of high competitiveness for higher education in China, junior high school students’ mental health is facing greater challenges. Understanding the time allocation of study and sleep is necessary for developing effective prevention and treatment programs. Based on a survey of 31,057 junior high school students in 47 junior high schools in Gansu Province, mainland China, the study analyzed the associations of time spent on study and sleep with anxiety and depressive symptoms among junior high school students through chi-square test, ANOVA, logistic regression model and threshold regression model. It… More >

BIOCELL, Vol.47, Suppl.2, pp. 1-35, 2023

Abstract This article has no abstract. More >