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 >

Qi Lu^1,2, Longfei Jin², Cuiling Tong³, Feng Liu², Bei Huang², Dejian Zhang^1,2,*

Phyton-International Journal of Experimental Botany, Vol.93, No.4, pp. 661-679, 2024, DOI:10.32604/phyton.2024.049733

Abstract A Plant Biostimulant is any substance or microorganism applied to plants to enhance nutrition efficiency, abiotic stress tolerance, and/or crop quality traits, regardless of its nutrient content. The application of Plant biostimulants (PBs) in production can reduce the application of traditional pesticides and chemical fertilizers and improve the quality and yield of crops, which is conducive to the sustainable development of agriculture. An in-depth understanding of the mechanism and effect of various PBs is very important for how to apply PBs reasonably and effectively in the practice of crop production. This paper summarizes the main classification of PBs; The growth… More >

Xin Zou¹, Jieyu Zhang¹, Ting Cheng¹, Yangyang Guo¹, Xiao Han¹, Han Liu¹, Yuxing Qin¹, Jie Li², Dabing Xiang^1,*

Phyton-International Journal of Experimental Botany, Vol.93, No.4, pp. 699-712, 2024, DOI:10.32604/phyton.2024.048469

Abstract To mitigate the wastage of seed resources and reduce the usage of pesticides and fertilizers, seed coating agents have gained popularity. This study employs single-factor and multi-index orthogonal experimental design methods to investigate the seed coating formula and physical properties of Tartary buckwheat. The specific effects of each component on Tartary buckwheat seed germination are analyzed. The findings reveal that the seed coating agent formulated with 1.5% polyvinyl alcohol, 0.15% sodium alginate, 0.2% op-10, 0.1% polyacrylamide, 8% colorant, 3% ammonium sulfate, 1% potassium dihydrogen phosphate, and 0.15% carbendazim exhibits the most effective coating. It demonstrates optimal physical properties and promotes… 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 >

Xiang Lin^1,*, Jian Fang¹, Ming Zhang¹, Kuang Yin¹, Yan Tian¹, Yingfei Guo², Qianggang Wang²

Energy Engineering, Vol.121, No.5, pp. 1127-1141, 2024, DOI:10.32604/ee.2024.046861

Abstract Efforts to protect electric power systems from faults have commonly relied on the use of ultra-high frequency (UHF) antennas for detecting partial discharge (PD) as a common precursor to faults. However, the effectiveness of existing UHF antennas suffers from a number of challenges such as limited bandwidth, relatively large physical size, and low detection sensitivity. The present study addresses these issues by proposing a compact microstrip patch antenna with fixed dimensions of 100 mm × 100 mm × 1.6 mm. The results of computations yield an optimized antenna design consisting of 2nd-order Hilbert fractal units positioned within a four-layer serpentine… More > Graphic Abstract

Chenglian Ma¹, Rui Han¹, Zhao An^2,*, Tianyu Hu², Meizhu Jin²

Energy Engineering, Vol.121, No.5, pp. 1245-1261, 2024, DOI:10.32604/ee.2024.046644

Abstract Precise forecasting of solar power is crucial for the development of sustainable energy systems. Contemporary forecasting approaches often fail to adequately consider the crucial role of weather factors in photovoltaic (PV) power generation and encounter issues such as gradient explosion or disappearance when dealing with extensive time-series data. To overcome these challenges, this research presents a cutting-edge, multi-stage forecasting method called D-Informer. This method skillfully merges the differential transformation algorithm with the Informer model, leveraging a detailed array of meteorological variables and historical PV power generation records. The D-Informer model exhibits remarkable superiority over competing models across multiple performance metrics,… More > Graphic Abstract

Yingkai Dong^1,2, Chaohe Chen^2,*, Guangyan Jia², Lidai Wang³, Jian Bai¹

Energy Engineering, Vol.121, No.5, pp. 1173-1193, 2024, DOI:10.32604/ee.2024.046432

Abstract This study investigates the heat dissipation mechanism of the insulation layer and other plane insulation layers in the polar drilling rig system. Combining the basic theory of heat transfer with the environmental requirements of polar drilling operations and the characteristics of polar drilling processes, we analyze the factors that affect the insulation effect of the drilling rig system. These factors include the thermal conductivity of the insulation material, the thickness of the insulation layer, ambient temperature, and wind speed. We optimize the thermal insulation material of the polar drilling rig system using a steady-state method to measure solid thermal conductivity.… More >

Le Zou¹, Linsong Hu¹, Yifan Wang¹, Zhize Wu², Xiaofeng Wang^1,*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 927-941, 2024, DOI:10.32604/cmc.2024.048889

Abstract Depth estimation is an important task in computer vision. Collecting data at scale for monocular depth estimation is challenging, as this task requires simultaneously capturing RGB images and depth information. Therefore, data augmentation is crucial for this task. Existing data augmentation methods often employ pixel-wise transformations, which may inadvertently disrupt edge features. In this paper, we propose a data augmentation method for monocular depth estimation, which we refer to as the Perpendicular-Cutdepth method. This method involves cutting real-world depth maps along perpendicular directions and pasting them onto input images, thereby diversifying the data without compromising edge features. To validate the… More >

Yushan Yin¹, Witold Pedrycz^1,2, Zhiwu Li^1,*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 623-650, 2024, DOI:10.32604/cmc.2024.048787

Abstract Utilizing granular computing to enhance artificial neural network architecture, a new type of network emerges—the granular neural network (GNN). GNNs offer distinct advantages over their traditional counterparts: The ability to process both numerical and granular data, leading to improved interpretability. This paper proposes a novel design method for constructing GNNs, drawing inspiration from existing interval-valued neural networks built upon NNNs. However, unlike the proposed algorithm in this work, which employs interval values or triangular fuzzy numbers for connections, existing methods rely on a pre-defined numerical network. This new method utilizes a uniform distribution of information granularity to granulate connections with… More >

Sapiah Sakri¹, Shakila Basheer¹, Zuhaira Muhammad Zain¹, Nurul Halimatul Asmak Ismail^2,*, Dua’ Abdellatef Nassar¹, Manal Abdullah Alohali¹, Mais Ayman Alharaki¹

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1157-1185, 2024, DOI:10.32604/cmc.2024.048051

Abstract Background: Sepsis, a potentially fatal inflammatory disease triggered by infection, carries significant health implications worldwide. Timely detection is crucial as sepsis can rapidly escalate if left undetected. Recent advancements in deep learning (DL) offer powerful tools to address this challenge. Aim: Thus, this study proposed a hybrid CNNBDLSTM, a combination of a convolutional neural network (CNN) with a bi-directional long short-term memory (BDLSTM) model to predict sepsis onset. Implementing the proposed model provides a robust framework that capitalizes on the complementary strengths of both architectures, resulting in more accurate and timelier predictions. Method: The sepsis prediction method proposed here utilizes… More >