Zheng Liu^1,#, Xuhong Yan^2,#, Guicheng Liu¹, Jingyi Zhang¹, Xujun Yu³, Degui Chang^1,*, Liang Dong^3,*

Canadian Journal of Urology, Vol.32, No.5, pp. 385-400, 2025, DOI:10.32604/cju.2025.068136 - 30 October 2025

Abstract Late-onset hypogonadism (LOH), characterized by the intersection of aging and androgen deficiency, impacts the health of approximately 2%−39% of middle-aged and elderly men, underscoring the need for comprehensive research. Animal models, serving as analogs of human diseases, are indispensable for investigating disease mechanisms and facilitating drug development. However, the diverse array of animal models utilized for LOH research has led to a lack of standardized modeling approaches and evaluation systems, potentially impeding progress in understanding the pathogenesis and therapeutic development. In this paper, we summarize and compile the characteristics, methods, and evaluation systems of rodent More >

Andrea Panunzio¹, Rossella Orlando¹, Federico Greco^2,3, Giovanni Mazzucato⁴, Floriana Luigina Rizzo¹, Serena Domenica D’Elia¹, Antonio Benito Porcaro⁵, Alessandro Antonelli⁵, Alessandro Tafuri^1,6,*

Canadian Journal of Urology, Vol.32, No.5, pp. 375-384, 2025, DOI:10.32604/cju.2025.066140 - 30 October 2025

Abstract Background: The Barthel Index (BI) measures the level of patient independence in activities of daily living. This review aims to summarize current evidence on the use of the BI in urology, highlighting its potential as a tool for assessing patients prior to surgery. Materials and methods: A comprehensive search of PubMed, Scopus, and Web of Science databases was conducted for studies evaluating the BI in patients undergoing urologic surgery, following Systematic Review and Meta-analyses (PRISMA) guidelines. The BI was investigated both as a descriptor of baseline or postoperative health status and a prognostic indicator. A qualitative… More >

Dimindra Karki^*, Ghizlane Yaakoubi, Beth Edelblute, Ahmed Aboumohamed^*

Canadian Journal of Urology, Vol.32, No.5, pp. 501-507, 2025, DOI:10.32604/cju.2025.063294 - 30 October 2025

Abstract Background: Epithelioid angiomyolipoma (EAML) is an uncommon renal tumor variant with histologic and radiologic features that can mimic renal cell carcinoma (RCC) on imaging due to the paucity of fat compared to the classic AML. EAML may exhibit aggressive behavior, including local invasion, recurrence, and distant metastases to the liver, lungs, and lymph nodes. Although recent reports suggest that up to one-third of EAML cases may behave malignantly, variability in diagnostic criteria and limited case series contribute to uncertainty regarding its true clinical course. Case Description: This case report describes a 19-year-old female presenting with an… More >

Hsiao-Chun Han¹, Der-Chen Huang^1,*, Chin-Ling Chen^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 67-126, 2025, DOI:10.32604/cmes.2025.070944 - 30 October 2025

Abstract This study presents a systematic review of applications of artificial intelligence (abbreviated as AI) and blockchain in supply chain provenance traceability and legal forensics cover five sectors: integrated circuits (abbreviated as ICs), pharmaceuticals, electric vehicles (abbreviated as EVs), drones (abbreviated as UAVs), and robotics—in response to rising trade tensions and geopolitical conflicts, which have heightened concerns over product origin fraud and information security. While previous literature often focuses on single-industry contexts or isolated technologies, this review comprehensively surveys these sectors and categorizes 116 peer-reviewed studies by application domain, technical architecture, and functional objective. Special attention More >

Zhengzheng Cao^1,2,3, Fangxu Guo¹, Wenqiang Wang^2,3,4,*, Feng Du^2,3,4, Zhenhua Li^2,3,4, Shuaiyang Zhang¹, Qixuan Wang¹, Yongzhi Zhai¹

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.10, pp. 2419-2442, 2025, DOI:10.32604/fdmp.2025.070624 - 30 October 2025

Abstract With the depletion of shallow mineral resources, mining operations are extending to greater depths and larger scales, increasing the risk of water inrush disasters, particularly from confined aquifers intersected by faults. This paper reviews the current state of research on fault-induced water inrushes in mining faces, examining the damage characteristics and permeability of fractured floor rock, the mechanical behavior of faults under mining stress, and the mechanisms driving water inrush. Advances in prevention technologies, risk assessment, and prediction methods are also summarized. Research shows that damage evolution in fractured floor rock, coupled with fluid-solid interactions,… More > Graphic Abstract

Mir Majid Etghani¹, Homayoun Boodaghi^2,*

Energy Engineering, Vol.122, No.11, pp. 4385-4474, 2025, DOI:10.32604/ee.2025.070668 - 27 October 2025

Abstract Energy system optimization has become crucial for enhancing efficiency and environmental sustainability. This comprehensive review examines the synergistic application of Artificial Neural Networks (ANN) and Taguchi methods in optimizing diverse energy systems. While previous reviews have focused on these methods separately, this paper presents the first integrated analysis of both approaches across multiple energy applications. We systematically analyze their implementation in: Internal combustion engines, Thermal energy storage systems, Solar energy systems, Wind and tidal turbines, Heat exchangers, and hybrid energy systems. Our findings reveal that ANN models consistently achieve prediction accuracies exceeding 90% when compared More > Graphic Abstract

Xin Wen^1,2,3, Siru Chen¹, Kechen Song^2,3,4,*, Han Yu^2,3,*, Xingjie Li^2,3, Ling Zhong¹

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 4173-4201, 2025, DOI:10.32604/cmc.2025.070906 - 23 October 2025

Abstract With the growing demand for higher product quality in manufacturing, X-ray non-destructive testing has found widespread application not only in industrial quality control but also in a wide range of industrial applications, owing to its unique capability to penetrate materials and reveal both internal and surface defects. This paper presents a systematic review of recent advances and current applications of X-ray-based defect detection in industrial components. It begins with an overview of the fundamental principles of X-ray imaging and typical inspection workflows, followed by a review of classical image processing methods for defect detection, segmentation,… More >

Shengjia Chang, Baojiang Cui^*, Shaocong Feng

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 4345-4374, 2025, DOI:10.32604/cmc.2025.070195 - 23 October 2025

Abstract Binary Code Similarity Detection (BCSD) is vital for vulnerability discovery, malware detection, and software security, especially when source code is unavailable. Yet, it faces challenges from semantic loss, recompilation variations, and obfuscation. Recent advances in artificial intelligence—particularly natural language processing (NLP), graph representation learning (GRL), and large language models (LLMs)—have markedly improved accuracy, enabling better recognition of code variants and deeper semantic understanding. This paper presents a comprehensive review of 82 studies published between 1975 and 2025, systematically tracing the historical evolution of BCSD and analyzing the progressive incorporation of artificial intelligence (AI) techniques. Particular… More >

Inam Ullah Khan¹, Fida Muhammad Khan^1,*, Zeeshan Ali Haider¹, Fahad Alturise^2,*

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 4307-4344, 2025, DOI:10.32604/cmc.2025.070189 - 23 October 2025

Abstract The rapid expansion of the Internet of Things (IoT) has introduced significant security challenges due to the scale, complexity, and heterogeneity of interconnected devices. The current traditional centralized security models are deemed irrelevant in dealing with these threats, especially in decentralized applications where the IoT devices may at times operate on minimal resources. The emergence of new technologies, including Artificial Intelligence (AI), blockchain, edge computing, and Zero-Trust-Architecture (ZTA), is offering potential solutions as it helps with additional threat detection, data integrity, and system resilience in real-time. AI offers sophisticated anomaly detection and prediction analytics, and… More >

Imran Ahmed^1,#, Misbah Ahmad^2,3,#, Gwanggil Jeon^4,5,*

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 4237-4273, 2025, DOI:10.32604/cmc.2025.068319 - 23 October 2025

Abstract The rapid convergence of Information and Communication Technologies (ICT), driven by advancements in 5G/6G networks, cloud computing, Artificial Intelligence (AI), and the Internet of Things (IoT), is reshaping modern digital ecosystems. As massive, distributed data streams are generated across edge devices and network layers, there is a growing need for intelligent, privacy-preserving AI solutions that can operate efficiently at the network edge. Federated Learning (FL) enables decentralized model training without transferring sensitive data, addressing key challenges around privacy, bandwidth, and latency. Despite its benefits in enhancing efficiency, real-time analytics, and regulatory compliance, FL adoption faces… More >