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  • Open Access

    ARTICLE

    YOLO-SIFD: YOLO with Sliced Inference and Fractal Dimension Analysis for Improved Fire and Smoke Detection

    Mariam Ishtiaq1,2, Jong-Un Won1,2,*

    CMC-Computers, Materials & Continua, Vol.82, No.3, pp. 5343-5361, 2025, DOI:10.32604/cmc.2025.061466 - 06 March 2025

    Abstract Fire detection has held stringent importance in computer vision for over half a century. The development of early fire detection strategies is pivotal to the realization of safe and smart cities, inhabitable in the future. However, the development of optimal fire and smoke detection models is hindered by limitations like publicly available datasets, lack of diversity, and class imbalance. In this work, we explore the possible ways forward to overcome these challenges posed by available datasets. We study the impact of a class-balanced dataset to improve the fire detection capability of state-of-the-art (SOTA) vision-based models and proposeMore >

  • Open Access

    ARTICLE

    A Dynamic Prediction Approach for Wire Icing Thickness under Extreme Weather Conditions Based on WGAN-GP-RTabNet

    Mingguan Zhao1,2,*, Xinsheng Dong1,2, Yang Yang1,2, Meng Li1,2, Hongxia Wang1,2, Shuyang Ma1,2, Rui Zhu3, Xiaojing Zhu3

    CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 2091-2109, 2025, DOI:10.32604/cmes.2025.059169 - 27 January 2025

    Abstract Ice cover on transmission lines is a significant issue that affects the safe operation of the power system. Accurate calculation of the thickness of wire icing can effectively prevent economic losses caused by ice disasters and reduce the impact of power outages on residents. However, under extreme weather conditions, strong instantaneous wind can cause tension sensors to fail, resulting in significant errors in the calculation of icing thickness in traditional mechanics-based models. In this paper, we propose a dynamic prediction model of wire icing thickness that can adapt to extreme weather environments. The model expands… More >

  • Open Access

    ARTICLE

    KHSRP promotes cancer stem cell maintenance, tumorigenesis, and suppresses anti-tumor immunity in gastric cancer

    YARU DU1,2,#, ZHIHUI PEI1,3,#, SHUQIN HU4, CHUANWEN LIAO1, SHUHAO LIU1,*

    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 >

  • Open Access

    ARTICLE

    Bilevel Optimal Scheduling of Island Integrated Energy System Considering Multifactor Pricing

    Xin Zhang*, Mingming Yao, Daiwen He, Jihong Zhang, Peihong Yang, Xiaoming Zhang

    Energy Engineering, Vol.122, No.1, pp. 349-378, 2025, DOI:10.32604/ee.2024.057676 - 27 December 2024

    Abstract In this paper, a bilevel optimization model of an integrated energy operator (IEO)–load aggregator (LA) is constructed to address the coordinate optimization challenge of multiple stakeholder island integrated energy system (IIES). The upper level represents the integrated energy operator, and the lower level is the electricity-heat-gas load aggregator. Owing to the benefit conflict between the upper and lower levels of the IIES, a dynamic pricing mechanism for coordinating the interests of the upper and lower levels is proposed, combined with factors such as the carbon emissions of the IIES, as well as the lower load… More > Graphic Abstract

    Bilevel Optimal Scheduling of Island Integrated Energy System Considering Multifactor Pricing

  • Open Access

    PROCEEDINGS

    Mechanics of Freezing-Empowered Self-Catapulting of Water Droplets

    Haimin Yao1,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.31, No.3, pp. 1-1, 2024, DOI:10.32604/icces.2024.012649

    Abstract Despite the remarkable progress of anti-icing and deicing technologies in the past decades, it remains a grand challenge to dislodge freezing water from a solid surface without consuming external energy. Herein, we propose a strategy to dislodge freezing water from solid surfaces just by leveraging its volume expansion resulting from the phase change from water to ice. The implementation of this energy-saving strategy relies on a simple micropillar-based gadget on the surface, termed freezing-empowered droplet catapult (FEDC), whereby the work done by the volume expansion of a freezing droplet accreted on it can be harvested… More >

  • Open Access

    PROCEEDINGS

    Series-Parallel Machine Learning-Generated Five-Site Water Models for Ice Ih and Liquid: TIP5P-BG and TIP5P-BGT

    Jian Wang1,*, Haitao Hei1, Yonggang Zheng1, Hongwu Zhang1, Hongfei Ye1

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.3, pp. 1-2, 2024, DOI:10.32604/icces.2024.010916

    Abstract Icing is a ubiquitous phenomenon in nature and widely observed in the micro/nanoconfinement, e.g., two-dimensional ice growth on Au surface, nanoconfinement-induced phase change, nanodroplet freezing on surface, etc. These complicated and abstruse processes and behaviours demand deep understanding from the microscale level by the aid of molecular dynamics (MD) simulation [1]. However, it is still a great challenge to accurately describe the ice and liquid water simultaneously with the present water models [1,2]. In response to this, we propose a series-parallel machine learning (ML) approach consisting of classification back-propagation neural network (BPNN), parallel regression BPNNs… More >

  • Open Access

    REVIEW

    Spliceosome-mediated RNA trans-splicing: a strategy for Huntington’s disease gene therapy

    QINGYANG ZHANG, SHUXIAN HUANG, DAN WENG*

    BIOCELL, Vol.48, No.10, pp. 1443-1453, 2024, DOI:10.32604/biocell.2024.053794 - 02 October 2024

    Abstract Huntington’s disease (HD) is a debilitating neurodegenerative disorder caused by an abnormal expansion of CAG repeats (Cytosine, Adenine, Guanine) in the huntingtin gene (HTT). This mutation leads to the production of a mutant huntingtin protein, resulting in neuronal dysfunction and cell death. Current treatments primarily focus on symptomatic relief and do not address the underlying genetic cause. This review explores spliceosome-mediated RNA trans-splicing (SMaRT) therapy as an innovative and potential approach for HD treatment. SMaRT leverages the cell’s natural splicing machinery to correct mutant mRNA, thereby reducing toxic protein levels while restoring functional protein production. We More >

  • Open Access

    ARTICLE

    EV Charging Station Load Prediction in Coupled Urban Transportation and Distribution Networks

    Benxin Li*, Xuanming Chang

    Energy Engineering, Vol.121, No.10, pp. 3001-3018, 2024, DOI:10.32604/ee.2024.051332 - 11 September 2024

    Abstract The increasingly large number of electric vehicles (EVs) has resulted in a growing concern for EV charging station load prediction for the purpose of comprehensively evaluating the influence of the charging load on distribution networks. To address this issue, an EV charging station load prediction method is proposed in coupled urban transportation and distribution networks. Firstly, a finer dynamic urban transportation network model is formulated considering both nodal and path resistance. Then, a finer EV power consumption model is proposed by considering the influence of traffic congestion and ambient temperature. Thirdly, the Monte Carlo method… More > Graphic Abstract

    EV Charging Station Load Prediction in Coupled Urban Transportation and Distribution Networks

  • Open Access

    ARTICLE

    Influence of Surface Ice Roughness on the Aerodynamic Performance of Wind Turbines

    Xin Guan1,2,*, Mingyang Li1, Shiwei Wu1, Yuqi Xie1, Yongpeng Sun1

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.9, pp. 2029-2043, 2024, DOI:10.32604/fdmp.2024.049499 - 23 August 2024

    Abstract The focus of this research was on the equivalent particle roughness height correction required to account for the presence of ice when determining the performances of wind turbines. In particular, two icing processes (frost ice and clear ice) were examined by combining the FENSAP-ICE and FLUENT analysis tools. The ice type on the blade surfaces was predicted by using a multi-time step method. Accordingly, the influence of variations in icing shape and ice surface roughness on the aerodynamic performance of blades during frost ice formation or clear ice formation was investigated. The results indicate that More >

  • Open Access

    ARTICLE

    CoopAI-Route: DRL Empowered Multi-Agent Cooperative System for Efficient QoS-Aware Routing for Network Slicing in Multi-Domain SDN

    Meignanamoorthi Dhandapani*, V. Vetriselvi, R. Aishwarya

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2449-2486, 2024, DOI:10.32604/cmes.2024.050986 - 08 July 2024

    Abstract The emergence of beyond 5G networks has the potential for seamless and intelligent connectivity on a global scale. Network slicing is crucial in delivering services for different, demanding vertical applications in this context. Next-generation applications have time-sensitive requirements and depend on the most efficient routing path to ensure packets reach their intended destinations. However, the existing IP (Internet Protocol) over a multi-domain network faces challenges in enforcing network slicing due to minimal collaboration and information sharing among network operators. Conventional inter-domain routing methods, like Border Gateway Protocol (BGP), cannot make routing decisions based on performance,… More >

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