H. A. Ahmed, M. Y. Ali, S. S. Hamood, A. N. Abd^*

Chalcogenide Letters, Vol.22, No.1, pp. 11-22, 2025, DOI:10.15251/CL.2025.221.11

Abstract As a potential substitute for antibiotics, cadmium sulfide and zinc oxide nano-particles (CdS and ZnO NPs) were created using laser ablation and a straightforward chemical process, respectively. Target of cadmium sulfide, deionized water, zinc nitrate, and sodium hydroxide were used as precursors. Different characterization techniques were used to characterize the CdS and ZnO NPs. X-ray diffraction was used to confirm that the CdS and ZnO had polycrystalline structures with average crystalline sizes of 54.16 nm and 29.23 nm, respectively. The ZnO particles were densely packed 2D curved nanopetals with a diameter of 51.65 nm, whereas… More >

Sheikh Showkat Ahmad¹, Chandni Garg¹, Dalia Fouad², Islam Abdulrahim Alredah³, Sandeep Kaur⁴, Satwinderjeet Kaur^1,*

Phyton-International Journal of Experimental Botany, Vol.94, No.11, pp. 3401-3426, 2025, DOI:10.32604/phyton.2025.067984 - 01 December 2025

Abstract The Tragopogon dubius is traditionally used to treat many ailments, consumed as a vegetable, and utilized as fodder for livestock. Tragopogon dubius, found in the Kashmir Himalayas, is the least explored for its bioactivity properties and has a unique geographical location. This study is the first attempt to investigate the antioxidant, anticancer, and genoprotective properties of the aqueous extracts from the leaves (AQ-TrDL) and stems (AQ-TrDS) of this plant. AQ-TrDL and AQ-TrDS demonstrated significant amounts of phenolic and flavonoid contents. GC-HRMS identified various phytochemicals belonging to different classes, like carboxylic acids, fatty acid derivatives, phenols, and triterpenoids.… More >

Yihang Tang¹, Jing Li¹, Wentao Xu¹, Yao Xiao¹, Jiayi Deng¹, Ge Rong¹, Jin Zhao², Song Xu¹, Man Zhou^1,*, Zhongyu Li^3,*

Journal of Renewable Materials, Vol.13, No.10, pp. 1993-2041, 2025, DOI:10.32604/jrm.2025.02025-0065 - 22 October 2025

Abstract Natural fibers, as a typical renewable and biodegradable material, have shown great potential for many applications (e.g., catalysis, hydrogel, biomedicine) in recent years. Recently, the growing importance of natural fibers in these photo-driven applications is reflected by the increasing number of publications. The utilization of renewable materials in photo-driven applications not only contributes to mitigating the energy crisis but also facilitates the transition of society toward a low-carbon economy, thus enabling harmonious coexistence between humans and the environment within the context of sustainable development. This paper provides an overview of the recent advances of natural… More > Graphic Abstract

Kaiyang Li¹, Renjing Li¹, Hui Wang², Naiqiang Zhang^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.1, pp. 1-1, 2025, DOI:10.32604/icces.2025.012643

Abstract Zn is a promising biomedical implant for its good biocompatibility, moderate mechanical strength, and suitable degradation rate. As a novel fabricating method, Additive Manufacturing (AM) could prepare biomedical Zn by raw powder deposition, melting, and molten pool solidification in a layer-by-layer pattern, which favors the customized shape and well-controlled geometry of the final product. Meanwhile, the rapid heating and solidification from AM often induces unique structural changes compared with traditional fabrication techniques, thus subsequently affecting the degradation behavior. Still, setting up the correlations among AM fabrication, structural changes and degradation behavior of Zn remains a… More >

Batyrkhan Omarov^1,2,3,4,*

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 2195-2253, 2025, DOI:10.32604/cmc.2025.064799 - 23 September 2025

Abstract Deep learning now underpins many state-of-the-art systems for biomedical image and signal processing, enabling automated lesion detection, physiological monitoring, and therapy planning with accuracy that rivals expert performance. This survey reviews the principal model families as convolutional, recurrent, generative, reinforcement, autoencoder, and transfer-learning approaches as emphasising how their architectural choices map to tasks such as segmentation, classification, reconstruction, and anomaly detection. A dedicated treatment of multimodal fusion networks shows how imaging features can be integrated with genomic profiles and clinical records to yield more robust, context-aware predictions. To support clinical adoption, we outline post-hoc explainability More >

Majid Harouni^1,*, Vishakha Goyal¹, Gabrielle Feldman¹, Sam Michael², Ty C. Voss¹

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 331-366, 2025, DOI:10.32604/cmc.2025.067915 - 29 August 2025

Abstract Semantic segmentation plays a foundational role in biomedical image analysis, providing precise information about cellular, tissue, and organ structures in both biological and medical imaging modalities. Traditional approaches often fail in the face of challenges such as low contrast, morphological variability, and densely packed structures. Recent advancements in deep learning have transformed segmentation capabilities through the integration of fine-scale detail preservation, coarse-scale contextual modeling, and multi-scale feature fusion. This work provides a comprehensive analysis of state-of-the-art deep learning models, including U-Net variants, attention-based frameworks, and Transformer-integrated networks, highlighting innovations that improve accuracy, generalizability, and computational More >

Arun Kumar¹, Revanasiddappa Moolemane¹, Thulasi Rajendran², Suresh Babu Naidu Krishna^3,4,*

Journal of Renewable Materials, Vol.13, No.7, pp. 1315-1346, 2025, DOI:10.32604/jrm.2025.02024-0050 - 22 July 2025

Abstract In the past two decades, nanocellulose has become an innovative material with unique properties. This substance has exceptional mechanical strength, an extensive surface area, and biodegradability. Collaborative integration of nanocellulose offers a more environmentally friendly solution to the current limitations by substituting carbon. Due to its versatility, nanocellulose is commonly employed in various industrial sectors, including paints, adhesives, paper production, and biodegradable polymers. Such versatility enables the creation of customized structures for potential use in emulsion and dispersion applications. Given its biocompatibility and nontoxicity, nanocellulose is particularly well-suited for biomedical purposes such as tissue engineering, More > Graphic Abstract

Ali Mohammad Alqudah¹, Zahra Moussavi^1,2,*

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 3753-3841, 2025, DOI:10.32604/cmc.2025.063643 - 19 May 2025

Abstract This review presents a comprehensive technical analysis of deep learning (DL) methodologies in biomedical signal processing, focusing on architectural innovations, experimental validation, and evaluation frameworks. We systematically evaluate key deep learning architectures including convolutional neural networks (CNNs), recurrent neural networks (RNNs), transformer-based models, and hybrid systems across critical tasks such as arrhythmia classification, seizure detection, and anomaly segmentation. The study dissects preprocessing techniques (e.g., wavelet denoising, spectral normalization) and feature extraction strategies (time-frequency analysis, attention mechanisms), demonstrating their impact on model accuracy, noise robustness, and computational efficiency. Experimental results underscore the superiority of deep learning… More >

Chaichawin Chavapradit¹, Wonnop Visessanguan², Suwan Panjanapongchai¹, Anil Kumar Anal^1,*

Journal of Renewable Materials, Vol.13, No.3, pp. 553-582, 2025, DOI:10.32604/jrm.2025.058857 - 20 March 2025

Abstract The growing population and industrialization have led to significant production in agro-industrial sectors, resulting in large amounts of agro-industrial residues often left untreated, posing potential environmental issues. Therefore, finding effective ways to utilize these bio-based residues is crucial. One promising approach is to use these low- or no-value agro-industrial wastes as raw materials for producing renewable biomaterials, including proteins and peptides. Research has extensively explored peptide extraction using plant and animal-based agro-industrial residue. Due to lower processing costs and beneficial bioactive properties, peptides derived from waste could replace synthetic peptides and those extracted from food More >

Hariharasakthisudhan Ponnarengan^1,*, Sivakumar Rajendran², Vikas Khalkar³, Gunapriya Devarajan⁴, Logesh Kamaraj⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.1, pp. 1-48, 2025, DOI:10.32604/cmes.2024.056605 - 17 December 2024

Abstract The purpose of this review is to explore the intersection of computational engineering and biomedical science, highlighting the transformative potential this convergence holds for innovation in healthcare and medical research. The review covers key topics such as computational modelling, bioinformatics, machine learning in medical diagnostics, and the integration of wearable technology for real-time health monitoring. Major findings indicate that computational models have significantly enhanced the understanding of complex biological systems, while machine learning algorithms have improved the accuracy of disease prediction and diagnosis. The synergy between bioinformatics and computational techniques has led to breakthroughs in More >