Xincong Shi^1,2, Yuze Ji^3,*, Xinrui Wang³, Ruimin Tian³, Chao Zhang²

Energy Engineering, Vol.122, No.3, pp. 1199-1220, 2025, DOI:10.32604/ee.2025.061586 - 07 March 2025

Abstract With the development of integrated power and gas distribution systems (IPGS) incorporating renewable energy sources (RESs), coordinating the restoration processes of the power distribution system (PS) and the gas distribution system (GS) by utilizing the benefits of RESs enhances service restoration. In this context, this paper proposes a coordinated service restoration framework that considers the uncertainty in RESs and the bi-directional restoration interactions between the PS and GS. Additionally, a coordinated service restoration model is developed considering the two systems’ interdependency and the GS’s dynamic characteristics. The objective is to maximize the system resilience index… More >

Xin Liu^1,*, Meng Sun¹, Bo Lin², Shibo Gu¹

Energy Engineering, Vol.122, No.3, pp. 1053-1072, 2025, DOI:10.32604/ee.2025.060489 - 07 March 2025

Abstract Long-term petroleum production forecasting is essential for the effective development and management of oilfields. Due to its ability to extract complex patterns, deep learning has gained popularity for production forecasting. However, existing deep learning models frequently overlook the selective utilization of information from other production wells, resulting in suboptimal performance in long-term production forecasting across multiple wells. To achieve accurate long-term petroleum production forecast, we propose a spatial-geological perception graph convolutional neural network (SGP-GCN) that accounts for the temporal, spatial, and geological dependencies inherent in petroleum production. Utilizing the attention mechanism, the SGP-GCN effectively captures… More >

Bernard Bayangbe^1,*, Ababacar Thiam^1,2, El hadji I. Cissé², Kory Faye¹

Energy Engineering, Vol.122, No.3, pp. 943-969, 2025, DOI:10.32604/ee.2025.060273 - 07 March 2025

Abstract Concentrating Solar Power (CSP) is one of the most promising solar technologies for sustainable power generation in countries with high solar potential, like Chad. Identifying suitable sites is of great importance for deploying solar power plants. This work focuses on the identification of potential sites for the installation of solar power plants in Chad as well as a comparative analysis using the Analytical Hierarchy Process (AHP), Fuzzy Analytical Hierarchy Process (FAHP), and Full Consistency Method (FUCOM). The results show that 35% of the Chadian territory, i.e., an area of 449,400 km², is compatible with the implementation… More >

Xiuyun Liu¹, Jixia Sun², Feng Ming³, Minxiao Liu^2,*, Xinyu Wang², Yingjie Zhang^2,*

Phyton-International Journal of Experimental Botany, Vol.94, No.2, pp. 379-391, 2025, DOI:10.32604/phyton.2025.060726 - 06 March 2025

Abstract To study the main aroma components of Phalaenopsis orchid and their relationship with colors, 10 fragrant cultivars with different colors, like pink, rose, yellow, and purple, were used as samples in this experiment. Headspace-gas chromatography-mass spectrometry was used to determine the main components of floral fragrance and analyze the correlation between floral color and fragrance. The results showed that the main aroma components of the 10 fragrant cultivars of Phalaenopsis were alcohols, alkenes, esters, and benzene ring compounds, and the main aroma components of different cultivars were diverse. The main aroma components of yellow fragrant flowers… More >

Valentina Spanic^1,*, Zvonimir Lalic², Ivica Berakovic¹, Luka Drenjancevic², Goran Jukic², Ivan Varnica²

Phyton-International Journal of Experimental Botany, Vol.94, No.2, pp. 317-330, 2025, DOI:10.32604/phyton.2025.058201 - 06 March 2025

Abstract Enhanced grain yield is achieved in barley by developing varieties incorporating grain yield-related and morphological traits derived from different varieties. The evaluation of 28 morphological characteristics of 422 barley varieties was carried out to assess their changes over time from 1973 to 2023. Most barley yield improvement seems to have been achieved by changes in morphological traits where modern varieties out-yielded older varieties for more than 30% (from 1973 to 2023). According to the Pareto chart, the length of the first segment of the rachis was found to be the most important parameter that changed… More >

Jun Zhang^1,2,#,*, Junqiao Guo^3,#

International Journal of Mental Health Promotion, Vol.27, No.2, pp. 193-214, 2025, DOI:10.32604/ijmhp.2025.058022 - 03 March 2025

Abstract Background: The academic community is increasingly interested in understanding the mechanisms through which gratitude influences coping strategies. In addition, the role of gratitude in fostering long-term resilience and mental health outcomes has garnered significant attention. This study explores the mechanisms through which gratitude affects problem-focused coping strategies and emotion-focused coping strategies by constructing models involving gratitude, perceived social support, self-esteem, and problem-focused coping strategies, as well as models involving gratitude, perceived social support, self-esteem, and emotion-focused coping strategies. Methods: A longitudinal survey was conducted on 1666 Chinese university students using highly reliable and valid scales,… More >

Akash Kumar Gartia, S. Chakraverty^*

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 2405-2455, 2025, DOI:10.32604/cmes.2025.061039 - 03 March 2025

Abstract This review explores multi-directional functionally graded (MDFG) nanostructures, focusing on their material characteristics, modeling approaches, and mechanical behavior. It starts by classifying different types of functionally graded (FG) materials such as conventional, axial, bi-directional, and tri-directional, and the material distribution models like power-law, exponential, trigonometric, polynomial functions, etc. It also discusses the application of advanced size-dependent theories like Eringen’s nonlocal elasticity, nonlocal strain gradient, modified couple stress, and consistent couple stress theories, which are essential to predict the behavior of structures at small scales. The review covers the mechanical analysis of MDFG nanostructures in nanobeams,… More > Graphic Abstract

Ramadan Abdul-Rashid¹, Mohd Amiruddin Abd Rahman^1,*, Kar Tim Chan¹, Arun Kumar Sangaiah^2,3,4

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.3, pp. 2585-2616, 2025, DOI:10.32604/cmes.2025.060548 - 03 March 2025

Abstract This study proposes a novel time-synchronization protocol inspired by stochastic gradient algorithms. The clock model of each network node in this synchronizer is configured as a generic adaptive filter where different stochastic gradient algorithms can be adopted for adaptive clock frequency adjustments. The study analyzes the pairwise synchronization behavior of the protocol and proves the generalized convergence of the synchronization error and clock frequency. A novel closed-form expression is also derived for a generalized asymptotic error variance steady state. Steady and convergence analyses are then presented for the synchronization, with frequency adaptations done using least More >

Lingling Zhang^1,2, Hualing Wang³, Yawen Liu², Ling Li^2,*, Jianping Xiong^1,4,*

BIOCELL, Vol.49, No.2, pp. 253-267, 2025, DOI:10.32604/biocell.2025.061585 - 28 February 2025

Abstract Objective: Anillin (ANLN) is considered an oncogene in various cancers, but its effect on cervical cancer remains poorly understood. Hence, this study aimed to describe the action of ANLN on cervical cancer development and investigate the potential mechanism. Methods: Analysis of ANLN expression and its association with survival in carcinoma and endocervical adenocarcinoma (CESC) patients based on GEO and UALCAN databases. The tumor and adjacent normal tissues of 100 cervical cancer cases were harvested to detect the ANLN expression and explore its relationship with patient survival. Cell proliferation, apoptosis, migration, and invasion were measured by… More >

Ali Hasan Dakheel^1,*, Mohammed Raheem Mohammed¹, Zainab Ali Abd Alhuseen¹, Wassan Adnan Hashim^2,3

Intelligent Automation & Soft Computing, Vol.40, pp. 195-220, 2025, DOI:10.32604/iasc.2025.061622 - 28 February 2025

Abstract The prediction of pregnancy-related hazards must be accurate and timely to safeguard mother and fetal health. This study aims to enhance risk prediction in pregnancy with a novel deep learning model based on a Long Short-Term Memory (LSTM) generator, designed to capture temporal relationships in cardiotocography (CTG) data. This methodology integrates CTG signals with demographic characteristics and utilizes preprocessing techniques such as noise reduction, normalization, and segmentation to create high-quality input for the model. It uses convolutional layers to extract spatial information, followed by LSTM layers to model sequences for superior predictive performance. The overall More >