Feng Wei^*, Zhao Chen, Yin Wang, Dongqing Liu, Xun Zhang, Zhao Zhou

CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 5325-5341, 2025, DOI:10.32604/cmc.2025.058802 - 06 March 2025

Abstract The integration of artificial intelligence (AI) with advanced power technologies is transforming energy system management, particularly through real-time data monitoring and intelligent decision-making driven by Artificial Intelligence Generated Content (AIGC). However, the openness of power system channels and the resource-constrained nature of power sensors have led to new challenges for the secure transmission of power data and decision instructions. Although traditional public key cryptographic primitives can offer high security, the substantial key management and computational overhead associated with these primitives make them unsuitable for power systems. To ensure the real-time and security of power data… 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 >

Amine Batbat^1,2, Mohamed El Fadili³, Naoufal El Hachlafi^4,*, Amine Elbouzidi^5,*, Chaymae Hmimen⁶, Hiba Yahyaoui^2,7, Samir Jeddi⁶, Abdellatif Benbouazza², Kawtar Fikri-Benbrahim⁶, Mohamed Addi⁵, Samiah Hamad Al-Mijalli⁸, Khaoula Habbadi², Hassane Greche¹

Phyton-International Journal of Experimental Botany, Vol.94, No.2, pp. 481-501, 2025, DOI:10.32604/phyton.2025.059841 - 06 March 2025

Abstract This study highlights the regulatory potential antibacterial and antiradical of Origanum elongatum essential oil (EO), an endemic medicinal plant of Morocco used for its various properties. The chemical composition of the EO was characterized using gas chromatography-mass spectrometry (GC-MS). The antibacterial activity against different agricultural phytopathogens was determined by disc diffusion and microatmosphere methods, as well as by the determination of minimum inhibitory concentrations (MIC) and minimum bactericidal concentration (MBC), while the antioxidant activity was evaluated by DPPH and FRAP assays. To complement the experimental analyses, a molecular docking approach was used to predict and elucidate… More >

Baoquan Liu^1,3, Xi Chen^2,3, Qingjun Yuan^2,3, Degang Li^2,3, Chunxiang Gu^2,3,*

CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 3179-3201, 2025, DOI:10.32604/cmc.2024.059688 - 17 February 2025

Abstract With the emphasis on user privacy and communication security, encrypted traffic has increased dramatically, which brings great challenges to traffic classification. The classification method of encrypted traffic based on GNN can deal with encrypted traffic well. However, existing GNN-based approaches ignore the relationship between client or server packets. In this paper, we design a network traffic topology based on GCN, called Flow Mapping Graph (FMG). FMG establishes sequential edges between vertexes by the arrival order of packets and establishes jump-order edges between vertexes by connecting packets in different bursts with the same direction. It not… More >

Xinlu Zong^*, Fan Yu, Zhen Chen, Xue Xia

CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 3517-3537, 2025, DOI:10.32604/cmc.2024.057494 - 17 February 2025

Abstract Accurate traffic flow prediction has a profound impact on modern traffic management. Traffic flow has complex spatial-temporal correlations and periodicity, which poses difficulties for precise prediction. To address this problem, a Multi-head Self-attention and Spatial-Temporal Graph Convolutional Network (MSSTGCN) for multiscale traffic flow prediction is proposed. Firstly, to capture the hidden traffic periodicity of traffic flow, traffic flow is divided into three kinds of periods, including hourly, daily, and weekly data. Secondly, a graph attention residual layer is constructed to learn the global spatial features across regions. Local spatial-temporal dependence is captured by using a More >

Samiah Hamad Al-Mijalli¹, Hanae Naceiri Mrabti², Amine Elbouzidi^3,*, Naglaa S. Ashmawy^4,5, Amine Batbat⁶, Emad M. Abdallah⁷, Wafa Laaboudi⁸, Mohammed Aladhadh⁹, Fahad M. Alshabrmi¹⁰, Sulaiman Mohammed Alnasser¹¹, Mohamed Addi³, Naoufal El Hachlafi¹²

Phyton-International Journal of Experimental Botany, Vol.94, No.1, pp. 209-227, 2025, DOI:10.32604/phyton.2025.060438 - 24 January 2025

Abstract Thymus serpyllum L., often known as wild thyme, has been used since ancient times due to its multifaceted culinary and medicinal attributes. It is usually utilized in folk medicine to manage different health issues. This work aimed to investigate the chemical composition and biological characteristics of T. serpyllum essential oil (EO), including its antimicrobial, antioxidant, and anti-inflammatory capabilities. Moreover, we have prompted an in-silico simulation to reveal the underlying mode of action of these properties. The chemical characterization of T. serpyllum (EO) by Gas Chromatography-Mass Spectrometry (GC-MS) indicated sabinene (17.33%), terpinen-4-ol (11.73%), phellandral (13.18%), and thymol (10.54%) as main… More >

Fayez Althobaiti¹, Hadeer Darwish^1,*, Raghad Alruqayb¹, Saqer S. Alotaibi¹, Fahad E. Alharthi², Ibrahim Jafri¹, Sarah Awwadh Altalhi¹, Ghadi Alsharif^3,4, Hussam Awwadh E Althagafi⁵, Hesham Noureldeen⁶, Sarah Alharthi⁷, Jawaher Albaqami², Najla Amin T. Al Kashgry², Ahmed Noureldeen²

Phyton-International Journal of Experimental Botany, Vol.94, No.1, pp. 181-198, 2025, DOI:10.32604/phyton.2025.059387 - 24 January 2025

Abstract The interest in using the Datura stramonium plant is due to its natural products, which are used in many pharmaceutical industries. The objective of the current study was to assess the therapeutic and cytotoxic effects of the D. stramonium plant on two types of human cancer cell models (MCF7 and HT29) in vitro. A soxhlet apparatus was used to obtain methanolic extract from dried plant leaves. The recovered crude, after the solvent had evaporated, was then dispersed at varied concentrations of extract 100, 50, 20, and 0.0 µg/mL and tested to see how the cells responded. Also,… More >

YARU DU^1,2,#, ZHIHUI PEI^1,3,#, SHUQIN HU⁴, CHUANWEN LIAO¹, SHUHAO LIU^1,*

Oncology Research, Vol.33, No.2, pp. 309-325, 2025, DOI:10.32604/or.2024.058273 - 16 January 2025

Abstract Objectives: KH-type splicing regulatory protein (KHSRP) is an RNA-binding protein involved in several cellular processes, including nuclear splicing, mRNA localization, and cytoplasmic degradation. While KHSRP’s role has been studied in other cancers, its specific involvement in gastric cancer remains poorly understood. This study aims to explore KHSRP expression in gastric cancer and its potential effects on tumor progression and immune response. Methods: KHSRP expression in gastric cancer tissues and normal tissues was analyzed using data from The Cancer Genome Atlas (TCGA) database. The correlation between KHSRP expression, patient survival, and immune response was also assessed.… More >

ZHENGYANG ZHOU^1,#, LEI QIAO^1,#, TONGTONG WANG¹, WEN PAN¹, JINGJING DUAN¹, HAIYANG ZHANG², TING DENG¹, YI BA^1,*, YI HE^1,*

Oncology Research, Vol.33, No.2, pp. 327-345, 2025, DOI:10.32604/or.2024.050431 - 16 January 2025

Abstract Background: Patients with gastric cancer (GC) are prone to lymph node metastasis (LNM), which is an important factor for recurrence and poor prognosis of GC. Nowadays, more and more studies have confirmed that exosomes can participate in tumor lymphangiogenesis. An in-depth exploration of the pathological mechanism in the process of LNM in GC may provide effective targets and improve the diagnosis and treatment effect. Materials and Methods: We used sequencing analysis of collected serum to screen out exo-miRNA related to LNM in GC. ELISA, qRT-PCR, Western Blot, RNA pull-down assay, Transwell assay, animal experiments, and other… More > Graphic Abstract

Ange Chen, Chengdong Wu^*, Chuanjiang Leng

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 173-191, 2025, DOI:10.32604/cmc.2024.059284 - 03 January 2025

Abstract Previous multi-view 3D human pose estimation methods neither correlate different human joints in each view nor model learnable correlations between the same joints in different views explicitly, meaning that skeleton structure information is not utilized and multi-view pose information is not completely fused. Moreover, existing graph convolutional operations do not consider the specificity of different joints and different views of pose information when processing skeleton graphs, making the correlation weights between nodes in the graph and their neighborhood nodes shared. Existing Graph Convolutional Networks (GCNs) cannot extract global and deep-level skeleton structure information and view… More >