Qian Zhang¹, Lei Fu^1,2, Renzhou Chen³, Xu Zhan^4,*

CMC-Computers, Materials & Continua, Vol.87, No.2, 2026, DOI:10.32604/cmc.2026.074939 - 12 March 2026

Abstract Triply periodic minimal surface (TPMS) structures are widely utilized in engineering and biomedical fields owing to their superior mechanical and functional properties. However, limited by the current additive manufacturing (AM) techniques, insufficient wall thickness often leads to poor forming quality or even printing failure. Therefore, accurate prediction of wall thickness parameters during the design stage is essential. This study proposes a prediction approach for the wall thickness parameters of TPMS models by integrating a Convolutional Neural Network–Support Vector Regression (CNN-SVM) framework with Multiple Linear Regression (MLR). A total of 152 TPMS models were randomly generated,… More >

Anfeng Yang, Fei Kang, Wenjuan Bu^*

CMC-Computers, Materials & Continua, Vol.87, No.2, 2026, DOI:10.32604/cmc.2025.073979 - 12 March 2026

Abstract Large language models (LLMs) have demonstrated significant capabilities in semantic understanding and code generation. However, cybersecurity tasks often require prompting the adaptation of open-source models to this domain. Despite their effectiveness, large-parameter LLMs incur substantial memory usage and runtime costs during task inference and downstream fine-tuning for cybersecurity applications. In this study, we fine-tuned six LLMs with parameters under 4 billion using LoRA (Low-Rank Adaptation) on specific cybersecurity instruction datasets, employing evaluation metrics similar to Hackmentor. Results indicate that post-fine-tuning, smaller models achieved victory or parity rates up to 85% against larger models like Qwen-1.5-14B… More >

Luca Giammichele^*, Valerio D’Alessandro, Matteo Falone, Renato Ricci

Frontiers in Heat and Mass Transfer, Vol.24, No.1, 2026, DOI:10.32604/fhmt.2026.072535 - 28 February 2026

Abstract The airborne diffusion of saliva droplets during respiratory activities is one of the major factors in the spread of infections. During the COVID-19 pandemic, the use of protective face masks was essential to reduce the risk of infection and spread of SARS-CoV-2. The face mask is able to significantly reduce the saliva droplet emission in front of the person. However, the use of masks also produces a particle leakage towards the back of the person, which could increase the infection risk of people behind the subject. Most of the experimental investigations applied invasive and/or complex… More >

Wanqing Lin^1,2,*, Mohd Azrin Mohd Nasir¹, Suzila Binti Ismail¹

Journal of Psychology in Africa, Vol.36, No.1, pp. 143-152, 2026, DOI:10.32604/jpa.2026.073231 - 26 February 2026

Abstract This systematic review synthesizes empirical research on external risk factors for adolescent smartphone addiction. Scopus and Web of Science were searched for English peer-reviewed empirical articles from 2008 onward; 28 met inclusion criteria (excluding non-adolescents, generic internet addiction, non-empirical work, or non-English). Thematic synthesis organized findings into three external risk domains—family, school, and peers—considering cultural/contextual mechanisms. Family dynamics (parental phubbing, harsh parenting, dysfunction), school stressors, and adverse peer relationships were identified as accumulating, direct and indirect contributors to smartphone addiction. These operate within a techno-ecological framework, where digital technologies amplify vulnerabilities and create new pathways More >

Muhamad Hakimi Sahbudin¹, Noraain Mohamed Saraf^1,*, Saiful Aman Sulaiman¹, Abdul Rauf Abdul Rasam², Nafisah Khalid¹, Lau Chong Luh¹

Revue Internationale de Géomatique, Vol.35, pp. 101-120, 2026, DOI:10.32604/rig.2026.072359 - 24 February 2026

Abstract The integration of Light Detection and Ranging (LiDAR) technology into consumer electronics like smartphones has created new opportunities for the use of three-dimensional (3D) modelling, especially in the domains of infrastructure inspection and civil engineering. This paper presents the accuracy of a 3D bridge model generated using a smartphone LiDAR application in comparison with conventional surveying methods. In this study, LiDAR data were captured using an iPhone 13 Pro and processed to generate 3D models. The accuracy of the generated model was then validated against reference data obtained from a tacheometry survey, which served as… More >

Chiwan Ahn¹, Daehee Kim^2,*, Seongkeun Park^3,*

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.073330 - 10 February 2026

Abstract This paper proposes a deep learning-based 3D LiDAR perception framework designed for applications such as autonomous robots and vehicles. To address the high dependency on large-scale annotated data—an inherent limitation of deep learning models—this study introduces a hybrid perception architecture that incorporates expert-driven LiDAR processing techniques into the deep neural network. Traditional 3D LiDAR processing methods typically remove ground planes and apply distance- or density-based clustering for object detection. In this work, such expert knowledge is encoded as feature-level inputs and fused with the deep network, thereby mitigating the data dependency issue of conventional learning-based… More >

Nataliya Kazantseva^1,2,*, Nikolai Saharov¹, Denis Davydov^1,2, Nikolai Popov², Maxim Il’inikh¹

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2026.073078 - 10 February 2026

Abstract Because of the developed surface of the Triply Periodic Minimum Surface (TPMS) structures, polylactide (PLA) products with a TPMS structure are thought to be promising bio soluble implants with the potential for targeted drug delivery. For implants, mechanical properties are key performance characteristics, so understanding the deformation and failure mechanisms is essential for selecting the appropriate implant structure. The deformation and fracture processes in PLA samples with different interior architectures have been studied through computer simulation and experimental research. Two TPMS topologies, the Schwarz Diamond and Gyroid architectures, were used for the sample construction by… More >

Zeyu Wang¹, Jian-Hong Wang^1,*, Kuo-Chun Hsu^2,*

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.072881 - 10 February 2026

Abstract In daily life, keyword spotting plays an important role in human-computer interaction. However, noise often interferes with the extraction of time-frequency information, and achieving both computational efficiency and recognition accuracy on resource-constrained devices such as mobile terminals remains a major challenge. To address this, we propose a novel time-frequency dual-branch parallel residual network, which integrates a Dual-Branch Broadcast Residual module and a Time-Frequency Coordinate Attention module. The time-domain and frequency-domain branches are designed in parallel to independently extract temporal and spectral features, effectively avoiding the potential information loss caused by serial stacking, while enhancing information… More >

Zujun Ding, Shuaichao Wu, Chenliang Ji, Xinyu Feng, Yuanyuan Shi, Baolian Liu, Wan Chen, Qiuchan Bai, Hengrui Zhou, Hui Huang, Jie Ji^*

Energy Engineering, Vol.123, No.2, 2026, DOI:10.32604/ee.2025.068106 - 27 January 2026

Abstract In the quest to enhance energy efficiency and reduce environmental impact in the transportation sector, the recovery of waste heat from diesel engines has become a critical area of focus. This study provided an exhaustive thermodynamic analysis optimizing Organic Rankine Cycle (ORC) systems for waste heat recovery from diesel engines. The study assessed the performance of five candidate working fluids—R11, R123, R113, R245fa, and R141b—under a range of operating conditions, specifically varying overheat temperatures and evaporation pressures. The results indicated that the choice of working fluid substantially influences the system’s exergetic efficiency, net output power,… More >

Sha Hu^1,2,#, Wenjing Wang^1,#, Qianfang Hu^3,#, Rujuan Zheng^1,2, Qinghe Huang^1,2, Hui Shi^1,2, Xinyuan Ding^3,*, Wenjuan Wang^1,2,*, Zengyan Zhu^1,2,*

Oncology Research, Vol.34, No.2, 2026, DOI:10.32604/or.2025.068967 - 19 January 2026

Abstract Objectives: Acquired resistance to paclitaxel represents a critical barrier to the effective chemotherapy of non-small cell lung cancer (NSCLC). The present study aimed to elucidate the molecular and pharmacological mechanisms promoting paclitaxel resistance in NSCLC and to explore potential strategies for overcoming this resistance. Methods: Here, we report an integrated pharmacological and analytical approach to quantify paclitaxel disposition and overcome resistance in a A549/TAX cell model (paclitaxel-resistant A549 cells). Results: Cell counting kit-8 (CCK-8) assay, colony formation, and apoptosis assays confirmed that A549/TAX cells exhibited marked resistance to paclitaxel relative to parental A549 cells. Based on… More >