Sowon Lee¹, Boyoung Kim^1,*, Chung Kil Park^2,*

International Journal of Mental Health Promotion, Vol.26, No.4, pp. 251-260, 2024, DOI:10.32604/ijmhp.2024.048803

Abstract This study explored how mental health professionals collaborate with peer supporters with mental disabilities in a community mental health institution. From January 19 to February 23, 2021, three 60 min interviews were conducted with six mental health professionals working at a Korean community center. The results were qualitatively analyzed and divided into four themes and eight categories. The four themes were the perceptions of and challenges in working with peer supporters with mental disabilities, conflict and confusion about working with peer supporters, forming partnerships with peer supporters, and policy support for peer supporters’ job security. Participants reported vague anxiety about… More >

Yanjing Cao¹, Chenchen Xu^1,2, Qi Li¹, Shan Lu^1,2,*, Jing Xiao^1,*

International Journal of Mental Health Promotion, Vol.26, No.4, pp. 261-269, 2024, DOI:10.32604/ijmhp.2024.043729

Abstract Background: Valid and reliable measures of depressive symptoms are crucial for understanding risk factors, outcomes, and interventions across rural and urban settings. Despite this need, the longitudinal invariance of these measures over time remains understudied. This research explores the structural components of the Center for Epidemiological Studies Depression Scale (CES-D) and examines its consistency across various living environments and temporal stability in a cohort of Chinese teenagers. Method: In the initial phase, 1,042 adolescents furnished demographic details and undertook the CES-D assessment. After a three-month interval, 967 of these participants repeated the CES-D evaluation. The study employed Confirmatory factor analysis… More >

Fenglan Wang^#, Zhenyuan Cai^#, Zhimei Li, Shilong Zhang, Honghui Luo, Qing Wu, Hanhan Xia, Yanhong Guo^*

Phyton-International Journal of Experimental Botany, Vol.93, No.4, pp. 819-830, 2024, DOI:10.32604/phyton.2024.049150

Abstract FLOWERING LOCUS T (FT) is an important factor for integrating flowering signals through the photoperiod pathway, which significantly promotes flowering. Most chrysanthemum varieties are short-day plants, sensitive to the photoperiod, which limits their ornamental and annual production supply. In this study, we aim to analyze the nutrients and flowering-related genes of chrysanthemums with different photoperiod types and to clone and verify the function of the flowering-related gene CmFT. We found that the formation of floral buds requires the accumulation of starch while consuming soluble sugars and the expression patterns of flowering-related genes GIGANTEA (GI), CONSTANS (CO), and FT in C.morifolium… More >

Jiaqi Lang¹, Mingyan Ye¹, Ya Luo¹, Yueheng Wang¹, Zhifen Shi^1,2, Xiaotian Kong^1,3, Xuan Li¹, Nong Zhou^1,*

Phyton-International Journal of Experimental Botany, Vol.93, No.4, pp. 789-806, 2024, DOI:10.32604/phyton.2024.049088

Abstract This study aimed to examine the effects of inoculating Fritillaria taipaiensis P.Y.Li leaves with different strains of potassium-solubilizing bacteria (KSB), or combinations thereof, focusing on aspects of photosynthesis and physiological and biochemical characteristics. At present, some studies have only studied the rhizosphere microbial community characteristics of F. taipaiensis and have not discussed the effects of different microbial species on the growth promotion of F. taipaiensis. This paper will start from the perspective of potassium-solubilizing bacteria to conduct an in-depth study. Seed cultivation commenced at the base with three different KSBs in early October 2022. The growth of F. taipaiensis leaves… More >

Nugroho Agung Pambudi^1,2,4,*, Andrew Chapman, Alfan Sarifudin^1,3, Desita Kamila Ulfa⁴, Iksan Riva Nanda⁵

Energy Engineering, Vol.121, No.5, pp. 1143-1159, 2024, DOI:10.32604/ee.2024.047555

Abstract One of the impacts of the Fukushima disaster was the shutdown of all nuclear power plants in Japan, reaching zero production in 2015. In response, the country started importing more fossil energy including coal, oil, and natural gas to fill the energy gap. However, this led to a significant increase in carbon emissions, hindering the efforts to reduce its carbon footprint. In the current situation, Japan is actively working to balance its energy requirements with environmental considerations, including the utilization of hydrogen fuel. Therefore, this paper aims to explore the feasibility and implications of using hydrogen power plants as a… More >

Lingjie Zhao, Cong Li^*

Energy Engineering, Vol.121, No.5, pp. 1363-1380, 2024, DOI:10.32604/ee.2024.046918

Abstract The Miller cycle is a program that effectively reduces NO_x emissions from marine diesel engines by lowering the maximum combustion temperature in the cylinder, thereby reducing NO_x emissions. To effectively investigate the impact of Miller cycle optimum combustion performance and emission capability under high load conditions, this study will perform a one-dimensional simulation of the performance of a marine diesel engine, as well as a three-dimensional simulation of the combustion in the cylinder. A 6-cylinder four-stroke single-stage supercharged diesel engine is taken as the research object. The chassis dynamometer and other related equipment are used to build the test system,… More >

Dong Pan¹, Xu Gui¹, Jiayin Xu¹, Yuming Shen¹, Haoran Xu², Yinghao Ma^2,*

Energy Engineering, Vol.121, No.5, pp. 1309-1328, 2024, DOI:10.32604/ee.2024.046464

Abstract With the increasing urgency of the carbon emission reduction task, the generation expansion planning process needs to add carbon emission risk constraints, in addition to considering the level of power adequacy. However, methods for quantifying and assessing carbon emissions and operational risks are lacking. It results in excessive carbon emissions and frequent load-shedding on some days, although meeting annual carbon emission reduction targets. First, in response to the above problems, carbon emission and power balance risk assessment indicators and assessment methods, were proposed to quantify electricity abundance and carbon emission risk level of power planning scenarios, considering power supply regulation… More >

Yuancong Chai, Yuefei Zhu^*, Wei Lin, Ding Li

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1223-1243, 2024, DOI:10.32604/cmc.2024.049904

Abstract With the increasing proportion of encrypted traffic in cyberspace, the classification of encrypted traffic has become a core key technology in network supervision. In recent years, many different solutions have emerged in this field. Most methods identify and classify traffic by extracting spatiotemporal characteristics of data flows or byte-level features of packets. However, due to changes in data transmission mediums, such as fiber optics and satellites, temporal features can exhibit significant variations due to changes in communication links and transmission quality. Additionally, partial spatial features can change due to reasons like data reordering and retransmission. Faced with these challenges, identifying… More >

Aodi Liu, Na Wang^*, Xuehui Du, Dibin Shan, Xiangyu Wu, Wenjuan Wang

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1705-1726, 2024, DOI:10.32604/cmc.2024.049011

Abstract Big data resources are characterized by large scale, wide sources, and strong dynamics. Existing access control mechanisms based on manual policy formulation by security experts suffer from drawbacks such as low policy management efficiency and difficulty in accurately describing the access control policy. To overcome these problems, this paper proposes a big data access control mechanism based on a two-layer permission decision structure. This mechanism extends the attribute-based access control (ABAC) model. Business attributes are introduced in the ABAC model as business constraints between entities. The proposed mechanism implements a two-layer permission decision structure composed of the inherent attributes of… More >

Khaled Soliman^1,*, Mohamed Sobh², Ayman M. Bahaa-Eldin²

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1419-1439, 2024, DOI:10.32604/cmc.2024.048883

Abstract The continuous development of cyberattacks is threatening digital transformation endeavors worldwide and leads to wide losses for various organizations. These dangers have proven that signature-based approaches are insufficient to prevent emerging and polymorphic attacks. Therefore, this paper is proposing a Robust Malicious Executable Detection (RMED) using Host-based Machine Learning Classifier to discover malicious Portable Executable (PE) files in hosts using Windows operating systems through collecting PE headers and applying machine learning mechanisms to detect unknown infected files. The authors have collected a novel reliable dataset containing 116,031 benign files and 179,071 malware samples from diverse sources to ensure the efficiency… More >