Zhukui Tan¹, Xiaoyong Cao^2,*, Qihui Feng¹, Dong Liu², Xiayu Chen³, Fei Chen²

Energy Engineering, Vol.123, No.5, 2026, DOI:10.32604/ee.2026.078440 - 27 April 2026

Abstract The rapid integration of photovoltaic (PV) generation and energy storage systems has significantly increased the operational complexity of low-voltage direct current (LVDC) distribution networks in zero-carbon parks. Under highly variable operating conditions, conventional DC protection schemes relying on fixed overcurrent thresholds often suffer from maloperation or failure to trip, particularly during fluctuations in PV power, load switching, and changes in network topology. To address these challenges, this paper proposes an adaptive DC protection strategy based on an artificial neural network (ANN)-driven dynamic threshold optimization mechanism. The proposed method replaces static protection settings with an adaptive… More > Graphic Abstract

Hongsheng Su, Dan Li^*, Yuwei Du

Energy Engineering, Vol.123, No.5, 2026, DOI:10.32604/ee.2025.072397 - 27 April 2026

Abstract When the three-phase grid-connected inverter system is in operation, there are problems of significant switching losses and power losses. At the same time, if the switching frequency is not fixed, it will lead to problems such as a high content of low-order harmonics in the current on the grid side. This paper takes the three-phase grid-connected inverter as the research object and proposes a solution. Establish a mathematical model for the inverter system and analyze the transformation relationships of relevant electrical quantities across different coordinate systems. First, the paper proposes an improved three-vector model predictive… More >

Benjamin Heckelmann^#, Jannis Duhn^#, Rüdiger Braun^*

Oncology Research, Vol.34, No.5, 2026, DOI:10.32604/or.2026.075028 - 22 April 2026

Abstract Pancreatic ductal adenocarcinoma (PDAC) is currently the third leading cancer-related cause of death worldwide and is forecasted to become the second leading cause in the United States by 2030. Despite the development of multimodal treatment regimens, 5-year overall survival remained as low as 12%. Several efforts have been made to account for different aspects of heterogeneous tumor biology in PDAC, aiming to enable treatment stratification of defined subtypes. Besides targeting specific mutations, the definition of molecular (transcriptional) subtypes has gained substantial interest regarding response prediction and treatment stratification. Despite numerous advances in the field of… More >

Muhammad Mukhtar^1,2, Farizah Yunus¹, Ahmad Shukri Mohd Noor^1,*, Zulfiqar Ali³, Muhammad Junaid^4,*, Mehmood Ahmed⁴

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.076246 - 09 April 2026

Abstract The increasing adoption of 5G cellular networks has introduced significant challenges for network operators. The main challenge lies in the management of seamless handoff (HO), which occurs owing to the rapid expansion of equipment, data, and network complexity. To address this challenge, a model named optimal HO management deep learning neural network (OHMDLNN) is proposed. The model is trained on network activity data, and it uses KPIs (key performance indicators) and system-level parameters to make HO decisions. As demonstrated in the article, OHMDLNN is successful in analyzing the effect and interdependence of KPIs from both… More >

M. Mohsin Raza^1,#, Muhammad Umair^1,#, Imran Arshad Choudhry¹, Muhammad Qasim¹, Muhammad Tahir Naseem^2,*, Mamoona Naveed Asghar³, Daniel Gavilanes^4,5,6,7, Manuel Masias Vergara^4,8,9, Imran Ashraf^10,*

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.3, 2026, DOI:10.32604/cmes.2025.074164 - 30 March 2026

Abstract Over the past decade, the landscape of cybersecurity has been increasingly shaped by the growing sophistication and frequency of malware attacks. Traditional detection techniques, while still in use, often fall short when confronted with modern threats that use advanced evasion strategies. This systematic review critically examines recent developments in malware detection, with a particular emphasis on the role of artificial intelligence (AI) and machine learning (ML) in enhancing detection capabilities. Drawing on literature published between 2019 and 2025, this study reviews 105 peer-reviewed contributions from prominent digital libraries including IEEE Xplore, SpringerLink, ScienceDirect, and ACM… More >

Zimin Zhu^*, Yu Duan, Jian Ma, Xiaoyun Wang, Xiaoyu Deng, Xiaofang Wu

Energy Engineering, Vol.123, No.4, 2026, DOI:10.32604/ee.2026.072166 - 27 March 2026

Abstract When the converter bus voltage of a voltage source converter-based high voltage direct current (VSC-HVDC) system drops below a certain predetermined threshold, the system enters low-voltage ride-through (LVRT) mode to avoid overcurrent and potential equipment failure, during which it operates as a controlled current source. The influence mechanism of LVRT control strategies on short-circuit current and overall system stability remains not yet fully and systematically investigated. First, this paper provides an overview of several LVRT strategies for VSC-HVDC systems and examines their effects on short-circuit current contribution. Next, it analyzes in detail the mechanisms through… More >

Hongyu Xu^1,*, Xiaofeng Liu¹, Zhao Li¹, Shuai Zhang², Jintao Cui¹, Zongshuai Zhou¹, Longlong Chen¹, Mengen Zhang¹

CMC-Computers, Materials & Continua, Vol.87, No.2, 2026, DOI:10.32604/cmc.2026.075413 - 12 March 2026

Abstract In two-scale topology optimization, enhancing the connectivity between adjacent microstructures is crucial for achieving the collaborative optimization of micro-scale performance and macro-scale manufacturability. This paper proposes a two-scale concurrent topology optimization strategy aimed at improving the interface connection strength. This method employs a parametric approach to explicitly divide the micro-design domain into a “boundary connection region” and a “free design domain” at the initial stage of optimization. The boundary connection region is used to generate a connection layer that enhances the interface strength, while the free design domain is not constrained by this layer, thus… More >

Richard Mathenge^*, Catherine Mukunga, Ephantus Mwangi

Journal of Cyber Security, Vol.8, pp. 129-151, 2026, DOI:10.32604/jcs.2026.077183 - 11 March 2026

Abstract The rapid digitization of microfinance institutions (MFIs) has strengthened financial inclusion but has simultaneously increased exposure to phishing attacks and other cybersecurity threats driven by organizational, technical, and human vulnerabilities. Grounded in socio-technical systems theory, this systematic analysis evaluates AI-based mitigation strategies, with particular emphasis on gated recurrent unit (GRU) architectures. It compares them with Transformer and LSTM models. GRUs are prioritized due to their computational efficiency and suitability for low-resource environments typical of digital MFIs. Following PRISMA 2020 guidelines, 32 empirical studies published between January 2012 and April 2025 were analyzed from the Web… More >

Mingwei Zhan^1,#, Zhaokai Zhou^2,#, Jianpeng Zhang^3,#, Xin Wang⁴, Canxuan Li⁵, Bochen Pan⁶, Zhanyang Luo⁷, Wenjie Shi⁸, Yongjie Wang⁹, Minglun Li¹⁰, Weizhuo Wang^11,*, Run Shi^12,*, Jingyu Zhu^1,13,*

Canadian Journal of Urology, Vol.33, No.1, pp. 35-49, 2026, DOI:10.32604/cju.2026.076084 - 28 February 2026

Abstract Artificial intelligence (AI) is transforming the diagnostic landscape of malignant tumors in the urinary system, including prostate cancer, bladder cancer, and renal cell carcinoma (RCC). By integrating imaging, pathology, and molecular data, AI enhances the precision and reproducibility of tumor detection, grading, and risk stratification. In prostate cancer, AI-assisted multiparametric Magnetic resonance imaging (MRI) and digital pathology systems improve lesion localization and Gleason scoring. For bladder cancer, deep learning-based cystoscopy and radiomics models from Computed tomography/magnetic resonance imaging (CT/MRI) enable real-time lesion segmentation and non-invasive biomarker prediction, such as Programmed Cell Death-Ligand 1 (PD-L1) expression. More >

Bara Barakat^1,*, Bilal Al-Absi¹, Boris Hadaschik², Christian Rehme², Samer Schakaki³, Joerg Bauer¹

Canadian Journal of Urology, Vol.33, No.1, pp. 105-116, 2026, DOI:10.32604/cju.2026.071284 - 28 February 2026

Abstract Background: Artificial intelligence (AI)-assisted three-dimensional (3D) surgical platforms, integrated with augmented reality, have the potential to improve intraoperative anatomical recognition and provide surgeons with an immersive, dynamic operating environment during uro-oncological procedures. This review aims to examine the current applications of AI in robotic uro-oncology, with a particular focus on its role in facilitating intraoperative navigation during complex surgeries. Methods: A systematic literature search was performed across PubMed, the National Library of Medicine, MEDLINE, the Cochrane Central Register of Controlled Trials (CENTRAL), ClinicalTrials.gov, and Google Scholar to identify relevant studies published up to July 2025.… More >