Yuan Yuan¹, Yanfei Yang^2,*

Journal of Psychology in Africa, Vol.35, No.4, pp. 541-548, 2025, DOI:10.32604/jpa.2025.069551 - 17 August 2025

Abstract This study examined the impact of teacher-student relationship quality on students’ risk of bullying victimization and the mediating roles of student-student relationships and student engagement in this relationship. A total of 656 Chinese junior high school students (females = 361, mean age = 13.75, SD = 0.98) completed validated measures of teacher-student relationship quality, student-student relationship quality, student engagement, and bullying victimization. Regression analysis results indicated that higher teacher-student relationship quality predicted a lower risk of student bullying victimization. Serial mediating effect testing of the student-student relationship quality and student engagement revealed that these factors More >

Hamed Yousefzadeh Eini, Mohammad Hossein Sabouri, Mojtaba Babaelahi^*

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.7, pp. 1771-1788, 2025, DOI:10.32604/fdmp.2025.066747 - 31 July 2025

Abstract Heat Recovery Ventilators (HRVs) are essential for improving indoor air quality (IAQ) and reducing energy consumption in residential buildings situated in cold climates. This study considers the efficiency and performance optimization of HRVs under cold climatic conditions, where conventional ventilation systems increase heat loss. A comprehensive numerical model was developed using COMSOL Multiphysics, integrating fluid dynamics, heat transfer, and solid mechanics to evaluate the thermal efficiency and structural integrity of an HRV system. The methodology employed a detailed geometry with tetrahedral elements, temperature-dependent material properties, and coupled governing equations solved under Tehran-specific boundary conditions. A More >

Yunfeng Zhang, Dong Hu^*, Yuan Liu

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.7, pp. 1641-1655, 2025, DOI:10.32604/fdmp.2025.065820 - 31 July 2025

Abstract To address the challenges of poor surface quality and high energy consumption in marble cutting, this study introduces an auxiliary abrasive jet cutting technology enhanced by the use of polyacrylamide (PAM) as a drag-reducing additive. The effects of feed rate (50–300 mm/min), polymer concentration (0–0.5 g/L), and nozzle spacing (4–12 mm) on kerf width and surface roughness are systematically investigated through an orthogonal experimental design. Results reveal that feed rate emerges as the most significant factor (p < 0.01), followed by PAM concentration and nozzle spacing. The optimal set of parameters, comprising a 200 mm/min feed More >

Mingjie Huang^1,*, Yaping Pan², Jing Shen¹

Journal of Psychology in Africa, Vol.35, No.3, pp. 369-376, 2025, DOI:10.32604/jpa.2025.068057 - 31 July 2025

Abstract The present study examined the role of emotional balance and the moderating role of rumination in the relationship between psychological inflexibility and sleep quality among college students. Participants were 837 Chinese college students (females = 52%, mean age = 18.89, SD = 0.93 years). They completed the Multidimensional Psychological Inflexibility Scale (MPIS), Affect Balance Scale (ABS), Ruminative Response Scale (RRS), Pittsburgh Sleep Quality Index (PSQI). We utilized moderated-mediation analysis to explore the mechanism of action among variables. Emotional balance mediated the relationship between psychological inflexibility and sleep quality, and rumination moderated the direct effect of… 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 >

Issah Zabsonre Alhassan^1,2,*, Gaddafi Abdul-Salaam¹, Michael Asante¹, Yaw Marfo Missah¹, Alimatu Sadia Shirazu¹

Journal of Cyber Security, Vol.7, pp. 165-196, 2025, DOI:10.32604/jcs.2025.063529 - 07 July 2025

Abstract Pseudorandom number generators (PRNGs) are foundational to modern cryptography, yet existing approaches face critical trade-offs between cryptographic security, computational efficiency, and adaptability to emerging threats. Traditional PRNGs (e.g., Mersenne Twister, LCG) remain widely used in low-security applications despite vulnerabilities to predictability attacks, while machine learning (ML)-driven and chaos-based alternatives struggle to balance statistical robustness with practical deployability. This study systematically evaluates traditional, chaos-based, and ML-driven PRNGs to identify design principles for next-generation systems capable of meeting the demands of high-security environment like blockchain and IoT. Using a framework that quantifies cryptographic robustness (via NIST SP… More >

Weili Liu¹, Fayi Hao¹, Jiangping Yuan^1,2,*

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 1951-1979, 2025, DOI:10.32604/cmc.2025.065836 - 03 July 2025

Abstract Additive manufacturing (AM) and Three-dimensional (3D) printing build complex structures layer by layer, greatly expanding design possibilities. Traditional thermoplastics like Polylactic Acid (PLA), Acrylonitrile Butadiene Styrene (ABS), and Polyethylene Terephthalate Glycol (PETG) are widely used in 3D printing, but their non-renewable nature and limited biodegradability have driven research into plant fiber-based materials. These materials, mainly cellulose and lignin, come from sources like wood and agricultural waste, offering renewability, biodegradability, and biocompatibility. This paper reviews recent advances in plant fiber-based materials for 3D printing, covering their development from raw materials to applications. It highlights the sources,… More >

Ziyang Wang¹, Lian Duan^1,2,*, Lei Kuang¹, Haibo Zhou¹, Ji’an Duan¹

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 2587-2604, 2025, DOI:10.32604/cmc.2025.065648 - 03 July 2025

Abstract The packaging quality of coaxial laser diodes (CLDs) plays a pivotal role in determining their optical performance and long-term reliability. As the core packaging process, high-precision laser welding requires precise control of process parameters to suppress optical power loss. However, the complex nonlinear relationship between welding parameters and optical power loss renders traditional trial-and-error methods inefficient and imprecise. To address this challenge, a physics-informed (PI) and data-driven collaboration approach for welding parameter optimization is proposed. First, thermal-fluid-solid coupling finite element method (FEM) was employed to quantify the sensitivity of welding parameters to physical characteristics, including… More >

Duc Cuong Pham¹, Tien Duc Ngo², Hoai Nam Vu^1,3,*

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 2959-2974, 2025, DOI:10.32604/cmc.2025.064672 - 03 July 2025

Abstract Air quality estimation assesses the pollution level in the air, supports public health warnings, and is a valuable tool in environmental management. Although air sensors have proven helpful in this task, sensors are often expensive and difficult to install, while cameras are becoming more popular and accessible, from which images can be collected as data for deep learning models to solve the above task. This leads to another problem: several labeled images are needed to achieve high accuracy when deep-learning models predict air quality. In this research, we have three main contributions: (1) Collect and… More >

Nisa Nacar Çıkan^*

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.3, pp. 3279-3327, 2025, DOI:10.32604/cmes.2025.065442 - 30 June 2025

Abstract This study addresses the critical challenge of reconfiguration in unbalanced power distribution networks (UPDNs), focusing on the complex 123-Bus test system. Three scenarios are investigated: (1) simultaneous power loss reduction and voltage profile improvement, (2) minimization of voltage and current unbalance indices under various operational cases, and (3) multi-objective optimization using Pareto front analysis to concurrently optimize voltage unbalance index, active power loss, and current unbalance index. Unlike previous research that oftensimplified system components, this work maintains all equipment, including capacitor banks, transformers, and voltage regulators, to ensure realistic results. The study evaluates twelve metaheuristic More >