Mujeebu Rehman¹, Qinghua Liu¹, Ali Ghulam², Tariq Ahmad³, Jawad Khan^4,*, Dildar Hussain^5,*, Yeong Hyeon Gu⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 779-805, 2025, DOI:10.32604/cmes.2025.067412 - 30 October 2025

Abstract Identifying druggable proteins, which are capable of binding therapeutic compounds, remains a critical and resource-intensive challenge in drug discovery. To address this, we propose CEL-IDP (Comparison of Ensemble Learning Methods for Identification of Druggable Proteins), a computational framework combining three feature extraction methods Dipeptide Deviation from Expected Mean (DDE), Enhanced Amino Acid Composition (EAAC), and Enhanced Grouped Amino Acid Composition (EGAAC) with ensemble learning strategies (Bagging, Boosting, Stacking) to classify druggable proteins from sequence data. DDE captures dipeptide frequency deviations, EAAC encodes positional amino acid information, and EGAAC groups residues by physicochemical properties to generate… More >

Sy-Yu Shiau^*, Shuting Ni, Yanli Yu, Songling Cai, Wenbo Huang

Phyton-International Journal of Experimental Botany, Vol.94, No.10, pp. 3047-3060, 2025, DOI:10.32604/phyton.2025.070289 - 29 October 2025

Abstract Consumers are increasingly demanding natural colorants that are safe and offer health benefits. In addition to their ornamental characteristics, Kanzan cherry (KC) blossoms present a promising source of red-hued natural colorants and functional bioactive substances. This research utilized distilled water to extract KC petals (KCP) and their ground powders (KCPP) under varying temperatures (30°C–90°C) and times (30–180 min). The total monomeric anthocyanins (TMAC) and total phenolics (TPC) in the extracts were evaluated via the pH differential and Folin–Ciocalteu methods. Antioxidant capacities were assessed by DPPH free radical scavenging ability and reducing power. Results indicated that… More >

Diyar Wirya Omar Ameenulhakeem^*, Osman Nuri Uçan

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 5671-5702, 2025, DOI:10.32604/cmc.2025.070422 - 23 October 2025

Abstract Face antispoofing has received a lot of attention because it plays a role in strengthening the security of face recognition systems. Face recognition is commonly used for authentication in surveillance applications. However, attackers try to compromise these systems by using spoofing techniques such as using photos or videos of users to gain access to services or information. Many existing methods for face spoofing face difficulties when dealing with new scenarios, especially when there are variations in background, lighting, and other environmental factors. Recent advancements in deep learning with multi-modality methods have shown their effectiveness in… More >

Tiren Huang, Chong Luo, Xu Li^*

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 5847-5865, 2025, DOI:10.32604/cmc.2025.067986 - 23 October 2025

Abstract Automatic pancreas segmentation in CT scans is crucial for various medical applications including early disease detection, treatment planning and therapeutic evaluation. However, the pancreas’s small size, irregular morphology, and low contrast with surrounding tissues make accurate pancreas segmentation still a challenging task. To address these challenges, we propose a novel RPMS-DSAUnet for accurate automatic pancreas segmentation in abdominal CT images. First, a Residual Pyramid Squeeze Attention module enabling hierarchical multi-resolution feature extraction with dynamic feature weighting and selective feature reinforcement capabilities is integrated into the backbone network, enhancing pancreatic feature extraction and improving localization accuracy.… More >

Hafiza Saima Gul^1,2,*, Mumtaz Hussain¹, Tayyaba Sanaullah³, Habib-ur-Rehman Athar², Ibrahim Al-Ashkar⁴, Muhammad Kamran⁵, Mohammed Antar⁶, Ayman El Sabagh^7,*

Phyton-International Journal of Experimental Botany, Vol.94, No.9, pp. 2893-2909, 2025, DOI:10.32604/phyton.2025.058816 - 30 September 2025

Abstract The low efficiency of phytoextraction of lead (Pb) from agricultural fields poses a significant agricultural challenge. Organic chelating agents can influence Pb bioavailability in soil, affecting its uptake, transport, and toxicity in plants. This study aimed to assess the impact of citric acid (CA) and diethylenetriaminepentaacetic acid (DTPA) on chelate-assisted phytoextraction of Pb and its effect on growth and physiology of two cultivars (07001; 07002) of mung bean (Vigna radiata). The cultivars of mung bean were exposed to 60 mg·L⁻¹ lead chloride (PbCl₂) solution, with or without the addition of 300 mg·L⁻¹ CA or 500 mg·L⁻¹ DTPA, until… More >

Weiqiang Xin^1,2,3,#, Zheng Wang^4,#, Xi Chen^1,5, Yufeng Tang¹, Bing Li¹, Chunwei Tian^2,5,*

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 2837-2849, 2025, DOI:10.32604/cmc.2025.069784 - 23 September 2025

Abstract Deep convolutional neural networks (CNNs) have demonstrated remarkable performance in video super-resolution (VSR). However, the ability of most existing methods to recover fine details in complex scenes is often hindered by the loss of shallow texture information during feature extraction. To address this limitation, we propose a 3D Convolutional Enhanced Residual Video Super-Resolution Network (3D-ERVSNet). This network employs a forward and backward bidirectional propagation module (FBBPM) that aligns features across frames using explicit optical flow through lightweight SPyNet. By incorporating an enhanced residual structure (ERS) with skip connections, shallow and deep features are effectively integrated,… More >

Hazem Farah¹, Akram Bennour^1,*, Hama Soltani¹, Mouaaz Nahas², Rashiq Rafiq Marie³, Mohammed Al-Sarem^3,4,*

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 3335-3348, 2025, DOI:10.32604/cmc.2025.067226 - 23 September 2025

Abstract This study presents an advanced method for post-mortem person identification using the segmentation of skeletal structures from chest X-ray images. The proposed approach employs the Attention U-Net architecture, enhanced with gated attention mechanisms, to refine segmentation by emphasizing spatially relevant anatomical features while suppressing irrelevant details. By isolating skeletal structures which remain stable over time compared to soft tissues, this method leverages bones as reliable biometric markers for identity verification. The model integrates custom-designed encoder and decoder blocks with attention gates, achieving high segmentation precision. To evaluate the impact of architectural choices, we conducted an… More >

Asmat Ullah¹, Yar Muhammad^1,*, Bakht Zada¹, Korhan Cengiz², Nikola Ivković^3,*, Mario Konecki³, Abid Yahya⁴

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 3767-3786, 2025, DOI:10.32604/cmc.2025.067145 - 23 September 2025

Abstract Low visibility conditions, particularly those caused by fog, significantly affect road safety and reduce drivers’ ability to see ahead clearly. The conventional approaches used to address this problem primarily rely on instrument-based and fixed-threshold-based theoretical frameworks, which face challenges in adaptability and demonstrate lower performance under varying environmental conditions. To overcome these challenges, we propose a real-time visibility estimation model that leverages roadside CCTV cameras to monitor and identify visibility levels under different weather conditions. The proposed method begins by identifying specific regions of interest (ROI) in the CCTV images and focuses on extracting specific… More >

Huan Zeng, Jianxun Zhang^*, Hongji Chen, Xinwei Zhu

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 3879-3896, 2025, DOI:10.32604/cmc.2025.066803 - 23 September 2025

Abstract Semantic segmentation in street scenes is a crucial technology for autonomous driving to analyze the surrounding environment. In street scenes, issues such as high image resolution caused by a large viewpoints and differences in object scales lead to a decline in real-time performance and difficulties in multi-scale feature extraction. To address this, we propose a bilateral-branch real-time semantic segmentation method based on semantic information distillation (BSDNet) for street scene images. The BSDNet consists of a Feature Conversion Convolutional Block (FCB), a Semantic Information Distillation Module (SIDM), and a Deep Aggregation Atrous Convolution Pyramid Pooling (DASP). More >

Wohua He, Fangji Wu, Haoqun Hong^*

Journal of Renewable Materials, Vol.13, No.9, pp. 1707-1763, 2025, DOI:10.32604/jrm.2025.02025-0005 - 22 September 2025

Abstract Under the background of the current energy crisis and environmental pollution, the development of green and sustainable materials has become particularly urgent. As one of the most abundant natural polymers on earth, cellulose has attracted wide attention due to its green recycling, sustainable development, degradability, and low cost. Therefore, cellulose and its derivatives were used as the starting point for comprehensive analysis. First, the basic structural properties of cellulose were discussed, and then the extraction and utilization methods of cellulose were reviewed, including Sodium Hydroxide based solvent system, N, N-Dimethylacetamide/Lithium Chloride System, N-Methylmorpholine-N-Oxide (NMMO) system, More > Graphic Abstract