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  • Open Access

    ARTICLE

    Enhanced Efficiency of Solar-Assist Heat Pump Using Tracking PV/T Panel: A TRNSYS Simulation Study

    Ashna Abduljabbar Haji*, Ranj S. Abdullah*

    Energy Engineering, Vol.122, No.12, pp. 5111-5127, 2025, DOI:10.32604/ee.2025.073367 - 27 November 2025

    Abstract The hybrid photovoltaic solar-assisted heat pump are primarily used to generate electricity and provide thermal energy for heating applications. This study investigates the performance enhancement of a hybrid Photovoltaic Thermal Solar-Assisted Heat Pump (PV/T-SAHP) system integrated with a solar tracking mechanism. The system was simulated using TRNSYS to evaluate its monthly electrical output and coefficient of performance (COP) of the heat pump system over a year. The results showed a significant improvement in energy generation and efficiency compared to a conventional PV/T system without SAHP system. Overall, the solar tracking configuration of the PV/T-SAHP generated… More > Graphic Abstract

    Enhanced Efficiency of Solar-Assist Heat Pump Using Tracking PV/T Panel: A TRNSYS Simulation Study

  • Open Access

    ARTICLE

    ORTHRUS: A Model for a Decentralized and Fair Data Marketplace Supporting Two Types of Output

    Su Jin Shin1, Sang Uk Shin2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 2787-2819, 2025, DOI:10.32604/cmes.2025.072602 - 26 November 2025

    Abstract To reconstruct vehicle accidents, data from the time of the incident—such as pre-collision speed and collision point—is essential. This data is collected and generated through various sensors installed in the vehicle. However, it may contain sensitive information about the vehicle owner. Consequently, vehicle owners tend to be reluctant to provide their vehicle data due to concerns about personal information exposure. Therefore, extensive research has been conducted on secure vehicle data trading models. Existing models primarily utilize centralized approaches, leading to issues such as single points of failure, data leakage, and manipulation. To address these problems,… More >

  • Open Access

    ARTICLE

    Pik3cb Antagonizes LPS/ATP-Induced Inflammatory Activation in Cardiomyocytes by Inhibiting the PI3K/AKT/NF-κB/NLRP3 Signaling Axis

    Xuekun Shao1,#, Cheng Wang2,#,*, Mengru Zhang2, Yi Wang2, Zhuoya Qiu1, Wen Cai1, Ruiliang Zhu3, Ping Wang2,*

    BIOCELL, Vol.49, No.11, pp. 2181-2194, 2025, DOI:10.32604/biocell.2025.070859 - 24 November 2025

    Abstract Objectives: PI3K plays a pivotal role in the inflammatory response by modulating the production and release of inflammatory factors. Pik3cb is one of the subunits of PI3K, and its specific role in myocardium inflammation remains unelucidated. This study aimed to investigate the role of Pik3cb in the inflammatory response and to elucidate the underlying mechanism. Methods: An inflammation model was established using H9c2 cells treated with LPS and ATP, and Pik3cb expression was evaluated in this model system. Subsequently, an overexpression model was constructed by transfecting cells with a Pik3cb overexpression plasmid, after which the… More > Graphic Abstract

    Pik3cb Antagonizes LPS/ATP-Induced Inflammatory Activation in Cardiomyocytes by Inhibiting the PI3K/AKT/NF-<b>κ</b>B/NLRP3 Signaling Axis

  • Open Access

    ARTICLE

    Why Transformers Outperform LSTMs: A Comparative Study on Sarcasm Detection

    Palak Bari, Gurnur Bedi, Khushi Joshi, Anupama Jawale*

    Journal on Artificial Intelligence, Vol.7, pp. 499-508, 2025, DOI:10.32604/jai.2025.072531 - 17 November 2025

    Abstract This study investigates sarcasm detection in text using a dataset of 8095 sentences compiled from MUStARD and HuggingFace repositories, balanced across sarcastic and non-sarcastic classes. A sequential baseline model (LSTM) is compared with transformer-based models (RoBERTa and XLNet), integrated with attention mechanisms. Transformers were chosen for their proven ability to capture long-range contextual dependencies, whereas LSTM serves as a traditional benchmark for sequential modeling. Experimental results show that RoBERTa achieves 0.87 accuracy, XLNet 0.83, and LSTM 0.52. These findings confirm that transformer architectures significantly outperform recurrent models in sarcasm detection. Future work will incorporate multimodal More >

  • Open Access

    ARTICLE

    STPEIC: A Swin Transformer-Based Framework for Interpretable Post-Earthquake Structural Classification

    Xinrui Ma, Shizhi Chen*

    Structural Durability & Health Monitoring, Vol.19, No.6, pp. 1745-1767, 2025, DOI:10.32604/sdhm.2025.071148 - 17 November 2025

    Abstract The rapid and accurate assessment of structural damage following an earthquake is crucial for effective emergency response and post-disaster recovery. Traditional manual inspection methods are often slow, labor-intensive, and prone to human error. To address these challenges, this study proposes STPEIC (Swin Transformer-based Framework for Interpretable Post-Earthquake Structural Classification), an automated deep learning framework designed for analyzing post-earthquake images. STPEIC performs two key tasks: structural components classification and damage level classification. By leveraging the hierarchical attention mechanisms of the Swin Transformer (Shifted Window Transformer), the model achieves 85.4% accuracy in structural component classification and 85.1% More >

  • Open Access

    ARTICLE

    Systematic Analysis of Latent Fingerprint Patterns through Fractionally Optimized CNN Model for Interpretable Multi-Output Identification

    Mubeen Sabir1, Zeshan Aslam Khan2,*, Muhammad Waqar2, Khizer Mehmood1, Muhammad Junaid Ali Asif Raja3, Naveed Ishtiaq Chaudhary4, Khalid Mehmood Cheema5, Muhammad Asif Zahoor Raja4, Muhammad Farhan Khan6, Syed Sohail Ahmed7

    CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 807-855, 2025, DOI:10.32604/cmes.2025.068131 - 30 October 2025

    Abstract Fingerprint classification is a biometric method for crime prevention. For the successful completion of various tasks, such as official attendance, banking transactions, and membership requirements, fingerprint classification methods require improvement in terms of accuracy, speed, and the interpretability of non-linear demographic features. Researchers have introduced several CNN-based fingerprint classification models with improved accuracy, but these models often lack effective feature extraction mechanisms and complex multineural architectures. In addition, existing literature primarily focuses on gender classification rather than accurately, efficiently, and confidently classifying hands and fingers through the interpretability of prominent features. This research seeks to… More >

  • Open Access

    PROCEEDINGS

    AI-Assisted Generative Inverse Design of Heterogeneous Meta-Biomaterials Based on TPMS for Biomimetic Tissue Engineering

    Xiaolong Zhu, Feng Chen, Yuntian Chen, Wei Zhu, Xiaoxiao Han*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.3, pp. 1-1, 2025, DOI:10.32604/icces.2025.012584

    Abstract Human tissues and organs exhibit not only intricate anatomical architectures but also spatially heterogeneous distributions of elastic modulus—for example, between cancellous and cortical bone, across the epidermis, dermis, and subcutaneous layers, and between healthy and fibrotic liver tissues. Conventional biomaterials often fail to replicate such mechanical heterogeneity, thereby limiting their capacity to recreate biomimetic physiological microenvironments essential for applications like tissue regeneration and disease modeling. Meta-biomaterials, artificially engineered through the rational structural design of continuous materials, have emerged as a promising class of materials owing to their highly tunable mechanical and biological properties. These attributes… More >

  • Open Access

    ARTICLE

    Maximizing Wind Farm Power Output through Site-Specific Wake Model Calibration and Yaw Optimization

    Yang Liu1, Lifu Ding2,*, Zhenfan Yu1, Tannan Xiao2, Qiuyu Lu1, Ying Chen2, Weihua Wang1

    Energy Engineering, Vol.122, No.11, pp. 4365-4384, 2025, DOI:10.32604/ee.2025.068712 - 27 October 2025

    Abstract Wake effects in large-scale wind farms significantly reduce energy capture efficiency. Active Wake Control (AWC), particularly through intentional yaw misalignment of upstream turbines, has emerged as a promising strategy to mitigate these losses by redirecting wakes away from downstream turbines. However, the effectiveness of yaw-based AWC is highly dependent on the accuracy of the underlying wake prediction models, which often require site-specific adjustments to reflect local atmospheric conditions and turbine characteristics. This paper presents an integrated, data-driven framework to maximize wind farm power output. The methodology consists of three key stages. First, a practical simulation-assisted… More >

  • Open Access

    PROCEEDINGS

    Flow and Heat Transfer Performance of Porous Heat Exchanger Based on Conformal Geometry Design

    Yijin Zhang, Panding Wang*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.2, pp. 1-1, 2025, DOI:10.32604/icces.2025.011144

    Abstract As a type of porous material with high porosity and a large surface-area-to-volume ratio, triply periodic minimal surface (TPMS) structures divide space into two non-interconnected parts. This increases the contact area while maintaining full connectivity and smoothness, which helps reduce flow resistance, making it naturally suited for applications in heat exchange designs. The advancement of additive manufacturing (AM) technology has contributed to the development of TPMS-based heat exchangers. However, due to the complexity of fluid heat exchanger designs, developing effective representations, models, and optimization schemes for TPMS structures in multi-fluid heat exchange problems is very… More >

  • Open Access

    ARTICLE

    Research on Variable Condition Properties and Experimental Verification of a Variable Cross-Section Scroll Expander

    Junying Wei1, Guangxian Yin2, Jihao Zhang2, Wenwen Chang2, Chenrui Zhang2, Zhengyi Li1, Long Chang1, Minghan Peng3,*

    Frontiers in Heat and Mass Transfer, Vol.23, No.4, pp. 1185-1201, 2025, DOI:10.32604/fhmt.2025.067244 - 29 August 2025

    Abstract The scroll expander, as the core component of the micro-compressed air energy storage and power generation system, directly affects the output efficiency of the system. Meanwhile, the scroll profile plays a central role in determining the output performance of the scroll expander. In this study, in order to investigate the output characteristics of a variable cross-section scroll expander, numerical simulation and experimental studies were conducted by using Computational Fluid Dynamics (CFD) methods and dynamic mesh techniques. The impact of critical parameters on the output performance of the scroll expander was analyzed through the utilization of… More >

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