Hyeon-Sik Choi¹, Min Kyu Kim¹, Jiuk Shin², Thomas H.-K. Kang^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.074029 - 29 January 2026

Abstract Unbonded post-tensioned (PT) concrete systems are widely used in safety-critical structures, yet modeling practices for prestress implementation and tendon-concrete interaction remain inconsistent. This study investigates the effects of sheath (duct) implementation and confinement assumptions through nonlinear finite element analysis. Four modeling cases were defined, consisting of an explicit sheath without tendon-concrete confinement (S) and three no-sheath variants with different confinement levels (X, N, A). One-way beams and two-way panels were analyzed, and panel blast responses were validated against experimental results. In both beams and panels, average initial stress levels were similar across models, through local More >

Shaoping Xiao^1,*, Zhaoan Wang¹, Junchao Li², Caden Noeller¹, Jiefeng Jiang³, Jun Wang⁴

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-62, 2026, DOI:10.32604/cmc.2025.072146 - 09 December 2025

Abstract The integration of human factors into artificial intelligence (AI) systems has emerged as a critical research frontier, particularly in reinforcement learning (RL), where human-AI interaction (HAII) presents both opportunities and challenges. As RL continues to demonstrate remarkable success in model-free and partially observable environments, its real-world deployment increasingly requires effective collaboration with human operators and stakeholders. This article systematically examines HAII techniques in RL through both theoretical analysis and practical case studies. We establish a conceptual framework built upon three fundamental pillars of effective human-AI collaboration: computational trust modeling, system usability, and decision understandability. Our… More >

Sabina-Cristiana Necula^*, Napoleon-Alexandru Sireteanu

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-34, 2026, DOI:10.32604/cmc.2025.070861 - 09 December 2025

Abstract Modern business information systems face significant challenges in managing heterogeneous data sources, integrating disparate systems, and providing real-time decision support in complex enterprise environments. Contemporary enterprises typically operate 200+ interconnected systems, with research indicating that 52% of organizations manage three or more enterprise content management systems, creating information silos that reduce operational efficiency by up to 35%. While attention mechanisms have demonstrated remarkable success in natural language processing and computer vision, their systematic application to business information systems remains largely unexplored. This paper presents the theoretical foundation for a Hierarchical Attention-Based Business Information System (HABIS)… More >

Mintao Xu^1,#, Zichao Jin^1,#, Yangyang Tian¹, Jingcheng Zhang^1,*, Huiqin Ma¹, Yujin Jing¹, Jiangxing Wu², Jing Zhai²

Phyton-International Journal of Experimental Botany, Vol.94, No.12, pp. 4059-4078, 2025, DOI:10.32604/phyton.2025.074422 - 29 December 2025

Abstract The frequent outbreaks of crop diseases pose a serious threat to global agricultural production and food security. Data-driven forecasting models have emerged as an effective approach to support early warning and management, yet the lack of user-friendly tools for model development remains a major bottleneck. This study presents the Multi-Scenario Crop Disease Forecasting Modeling System (MSDFS), an open-source platform that enables end-to-end model construction-from multi-source data ingestion and feature engineering to training, evaluation, and deployment-across four representative scenarios: static point-based, static grid-based, dynamic point-based, and dynamic grid-based. Unlike conventional frameworks, MSDFS emphasizes modeling flexibility, allowing… More >

Luke Patrick O’Connor¹, Alexander Jordan Henry², Wendy Michelle Novicoff³, Marwan Ali², Adam Seth Baumgarten⁴, Nicolas Martin Ortiz^2,*

Canadian Journal of Urology, Vol.32, No.6, pp. 621-626, 2025, DOI:10.32604/cju.2025.065217 - 30 December 2025

Abstract Background: Postoperative pain management after penile prosthesis (PP) has traditionally required opioid medication. Recently, urologic prosthetic surgeons have sought to establish opioid-free protocols (OFP) and/or opioid-reduced protocols (ORP) for PP postoperative pain management. We sought to investigate the adoption patterns of OFP/ORP among surgeons who perform PP surgery and identify barriers to implementation. Methods: A 13-question confidential survey was sent to members of the Sexual Medicine Society of North America (SMSNA) and the Society of Urologic Prosthetic Surgeons (SUPS) via email. The survey was administered via Qualtrics. A t-test was used to analyze survey responses. Results:… More >

Edward Danso Ansong^*, Simon Bonsu Osei^*, Raphael Adjetey Adjei

Journal of Cyber Security, Vol.7, pp. 533-564, 2025, DOI:10.32604/jcs.2025.061821 - 11 December 2025

Abstract The surge in identity fraud, driven by the rapid adoption of mobile money, internet banking, and e-services during the COVID-19 pandemic, underscores the need for robust cybersecurity solutions. Zero-Knowledge Proofs (ZKPs) enable secure identity verification by allowing individuals to prove possession of a National ID card without revealing sensitive information. This study implements a ZKP-based identity verification system using Camenisch-Lysyanskaya (CL) signatures, reducing reliance on complex trusted setup ceremonies. While a trusted issuer is still required, as assumed in this work, our approach eliminates the need for broader system-wide trusted parameters. We evaluate the system’s More >

Beth Steinberg^1,*, Yulia Mulugeta¹, Catherine Quatman-Yates², Maeghan Williams², Anvitha Gogineni¹, Maryanna Klatt¹

International Journal of Mental Health Promotion, Vol.27, No.9, pp. 1237-1264, 2025, DOI:10.32604/ijmhp.2025.067232 - 30 September 2025

Abstract Background: Community-based first responders face high levels of workplace stressors that can profoundly impact their physical and mental health. Mindfulness-based interventions have shown promise in decreasing stress and increasing psychological resilience; however, implementation is difficult due to unpredictability of the job, department culture, and generational preferences. The objective of this qualitative study was to identify and enhance understanding of the specific needs and potential barriers and facilitators for the implementation of mindfulness-based programming for community-based first responders. Methods: A phenomenological qualitative study design was used to gain insights into the lived experiences of first responders… More >

Anshul Pandey, Sachin Kumar^*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 3251-3286, 2025, DOI:10.32604/cmes.2025.067858 - 30 September 2025

Abstract The phase field model can coherently address the relatively complex fracture phenomenon, such as crack nucleation, branching, deflection, etc. The model has been extensively implemented in the finite element package Abaqus to solve brittle fracture problems in recent studies. However, accurate numerical analysis typically requires fine meshes to model the evolving crack path effectively. A broad region must be discretized without prior knowledge of the crack path, further augmenting the computational expenses. In this proposed work, we present an automated framework utilizing a posteriori error-indicator (MISESERI) to demarcate and sufficiently refine the mesh along the… More >

Ruigang Zhang^1,*, Qihui Yan², Jialiang Wang¹, Hao Wang¹, Jie Sun², Junjiao Shi²

Energy Engineering, Vol.122, No.9, pp. 3609-3624, 2025, DOI:10.32604/ee.2025.066880 - 26 August 2025

Abstract As the core facility of offshore wind power systems, the structural safety of offshore booster stations directly impacts the stable operation of entire wind farms. With the global energy transition toward green and low-carbon goals, offshore wind power has emerged as a key renewable energy source, yet its booster stations face harsh marine environments, including persistent wave impacts, salt spray corrosion, and equipment-induced vibrations. Traditional monitoring methods relying on manual inspections and single-dimensional sensors suffer from critical limitations: low efficiency, poor real-time performance, and inability to capture millinewton-level stress fluctuations that signal early structural fatigue.… More >

Ayoub Mhaouch^1,*, Wafa Gtifa², Turke Althobaiti³, Hamzah Faraj⁴, Mohsen Machhout¹

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5637-5663, 2025, DOI:10.32604/cmc.2025.065525 - 30 July 2025

Abstract In medical imaging, accurate brain tumor classification in medical imaging requires real-time processing and efficient computation, making hardware acceleration essential. Field Programmable Gate Arrays (FPGAs) offer parallelism and reconfigurability, making them well-suited for such tasks. In this study, we propose a hardware-accelerated Convolutional Neural Network (CNN) for brain cancer classification, implemented on the PYNQ-Z2 FPGA. Our approach optimizes the first Conv2D layer using different numerical representations: 8-bit fixed-point (INT8), 16-bit fixed-point (FP16), and 32-bit fixed-point (FP32), while the remaining layers run on an ARM Cortex-A9 processor. Experimental results demonstrate that FPGA acceleration significantly outperforms the… More >