Seo Yeon Shin¹, Nu Ri Song¹, Sa Rang Choi¹, Ki Min Kim¹, Jae Hee Byun¹, Su Jung Kim², Dai Hyun Jung², Seong Sim Kim², Seong Ju Park², So Jeong Chu², Kyung Mok Park^1,*

BIOCELL, Vol.49, No.8, pp. 1435-1448, 2025, DOI:10.32604/biocell.2025.065199 - 29 August 2025

Abstract Background: The efficient transdermal delivery of biologically active molecules remains a major challenge because of the structural barrier of the stratum corneum, which limits the penetration of large or hydrophilic molecules. Low-molecular-weight protamine (LMWP) has a structure similar to that of the HIV TAT protein-derived peptide and is a representative cell-penetrating peptide (CPP) used to increase cell permeability. However, protamine has been reported to have many toxicities and side effects. Objectives: We developed human-derived low-molecular-weight protamine (hLMWP), which is based on fish-derived LMWP but designed using human protein sequences to improve safety and functionality. As… More > Graphic Abstract

Fang-Yie Leu¹, Kun-Lin Tsai^2,*, Li-Woei Chen³, Deng-Yao Yao², Jian-Fu Tsai², Ju-Wei Zhu², Guo-Wei Wang²

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 1937-1957, 2025, DOI:10.32604/cmc.2025.068486 - 29 August 2025

Abstract With the rapid development of Cloud-Edge-End (CEE) computing, the demand for secure and lightweight communication protocols is increasingly critical, particularly for latency-sensitive applications such as smart manufacturing, healthcare, and real-time monitoring. While traditional cryptographic schemes offer robust protection, they often impose excessive computational and energy overhead, rendering them unsuitable for use in resource-constrained edge and end devices. To address these challenges, in this paper, we propose a novel lightweight encryption framework, namely Dynamic Session Key Allocation with Time-Indexed Ascon (DSKA-TIA). Built upon the NIST-endorsed Ascon algorithm, the DSKA-TIA introduces a time-indexed session key generation mechanism… More >

Ying Zhou¹, Jiayang Yuan¹, Zhengtao Shu¹, Mengli Ye¹, Liang Gao¹, Qiong Wang^2,*

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 557-580, 2025, DOI:10.32604/cmc.2025.067761 - 29 August 2025

Abstract Simultaneously, reducing an acoustic metamaterial’s weight and sound pressure level is an important but difficult topic. Considering the law of mass, traditional lightweight acoustic metamaterials make it difficult to control noise efficiently in real-life applications. In this study, a novel optimization-driven design scheme is developed to obtain lightweight acoustic metamaterials with a strong sound insulation capability for additive manufacturing. In the proposed design scheme, a topology optimization method for an acoustic metamaterial in the acoustic-solid interaction system is implemented to obtain an initial cross-sectional topology of the acoustic microstructure during the conceptual design phase. Then, More >

Hao Sun^1,2, Di Cai¹, Dae-Ki Kang^2,*

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 1675-1692, 2025, DOI:10.32604/cmc.2025.067675 - 29 August 2025

Abstract Accurately identifying crop pests and diseases ensures agricultural productivity and safety. Although current YOLO-based detection models offer real-time capabilities, their conventional convolutional layers involve high computational redundancy and a fixed receptive field, making it challenging to capture local details and global semantics in complex scenarios simultaneously. This leads to significant issues like missed detections of small targets and heightened sensitivity to background interference. To address these challenges, this paper proposes a lightweight adaptive detection network—StarSpark-AdaptiveNet (SSANet), which optimizes features through a dual-module collaborative mechanism. Specifically, the StarNet module utilizes Depthwise separable convolutions (DW-Conv) and dynamic… More >

Zhenxiang He^*, Rulin Wu, Xinyuan Wang

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 1631-1651, 2025, DOI:10.32604/cmc.2025.067252 - 29 August 2025

Abstract With the continuous advancement of steganographic techniques, the task of image steganalysis has become increasingly challenging, posing significant obstacles to the fields of information security and digital forensics. Although existing deep learning methods have achieved certain progress in steganography detection, they still encounter several difficulties in real-world applications. Specifically, current methods often struggle to accurately focus on steganography sensitive regions, leading to limited detection accuracy. Moreover, feature information is frequently lost during transmission, which further reduces the model’s generalization ability. These issues not only compromise the reliability of steganography detection but also hinder its applicability… More >

Chuanchuan Wang^1,2, Ahmad Sufril Azlan Mohamed^2,*, Xiao Yang ², Hao Zhang ², Xiang Li¹, Mohd Halim Bin Mohd Noor ²

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 855-874, 2025, DOI:10.32604/cmc.2025.066343 - 29 August 2025

Abstract Classroom behavior recognition is a hot research topic, which plays a vital role in assessing and improving the quality of classroom teaching. However, existing classroom behavior recognition methods have challenges for high recognition accuracy with datasets with problems such as scenes with blurred pictures, and inconsistent objects. To address this challenge, we proposed an effective, lightweight object detector method called the RFNet model (YOLO-FR). The YOLO-FR is a lightweight and effective model. Specifically, for efficient multi-scale feature extraction, effective feature pyramid shared convolutional (FPSC) was designed to improve the feature extract performance by leveraging convolutional… More >

Fathe Jeribi^1,2, Ayesha Siddiqa^3,*, Hareem Kibriya⁴, Ali Tahir¹, Nadim Rana¹

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 955-982, 2025, DOI:10.32604/cmc.2025.065853 - 29 August 2025

Abstract Wound classification is a critical task in healthcare, requiring accurate and efficient diagnostic tools to support clinicians. In this paper, we investigated the effectiveness of the YOLO11n model in classifying different types of wound images. This study presents the training and evaluation of a lightweight YOLO11n model for automated wound classification using the AZH dataset, which includes six wound classes: Background (BG), Normal Skin (N), Diabetic (D), Pressure (P), Surgical (S), and Venous (V). The model’s architecture, optimized through experiments with varying batch sizes and epochs, ensures efficient deployment in resource-constrained environments. The model’s architecture… More >

Xian Yu, Jianxun Zhang^*, Siran Tian, Xiaobao He

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 1883-1897, 2025, DOI:10.32604/cmc.2025.065529 - 29 August 2025

Abstract In recent years, diffusion models have achieved remarkable progress in image generation. However, extending them to text-to-video (T2V) generation remains challenging, particularly in maintaining semantic consistency and visual quality across frames. Existing approaches often overlook the synergy between high-level semantics and low-level texture information, resulting in blurry or temporally inconsistent outputs. To address these issues, we propose Dual Consistency Training (DCT), a novel framework designed to jointly optimize semantic and texture consistency in video generation. Specifically, we introduce a multi-scale spatial adapter to enhance spatial feature extraction, and leverage the complementary strengths of CLIP and More >

Aylin Altınbay^1,2, Ceren Özsaltık², Mohammadreza Nofar^2,*

Journal of Renewable Materials, Vol.13, No.8, pp. 1605-1621, 2025, DOI:10.32604/jrm.2025.02025-0048 - 22 August 2025

Abstract Interfacial compatibilization is essential to generate compatible blend structures with synergistically enhanced properties. However, the effect of molecular structure on the reactivity of compatibilizers is not properly known. This study investigates the compatibilization effect of multifunctional, epoxy-based Joncryl chain extender in blends of polylactide (PLA) and polybutylene adipate-co-terephthalate (PBAT) using PLA with varying D-lactide contents and molecular weights. These PLAs were high molecular weight amorphous PLA (aPLA) with D-content of 12 mol% and semi-crystalline PLA (scPLA) grades with D-contents below 1.5 mol% at both high (h) and low (l) molecular weights. The reactivity of Joncryl… More >

Nurul A. Asram¹, Eran S. S. Md Sadek^2,*

Revue Internationale de Géomatique, Vol.34, pp. 619-637, 2025, DOI:10.32604/rig.2025.065667 - 06 August 2025

Abstract Landslides are a frequent geomorphological hazard in tropical regions, particularly where steep terrain and high precipitation coincide. This study evaluates landslide susceptibility in the Jelapang area of Perak, Malaysia, using Shannon Entropy-weighted bivariate models (i.e., Frequency Ratio, Information Value, and Weight of Evidence), in comparison with Logistic Regression. Seven conditioning factors were selected based on their geomorphological relevance and tested for multicollinearity: slope gradient, slope aspect, curvature, vegetation cover, lineament density, terrain ruggedness index, and flow accumulation. Each model generated susceptibility maps, which were validated using Receiver Operating Characteristic curves and Area Under the Curve… More >