Shuai Zhao, Zhiwei Zhang^*, Junkai Wang, Ye Yuan, Guoren Wang

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.073315 - 12 January 2026

Abstract With the development of sharded blockchains, high cross-shard rates and load imbalance have emerged as major challenges. Account partitioning based on hashing and real-time load faces the issue of high cross-shard rates. Account partitioning based on historical transaction graphs is effective in reducing cross-shard rates but suffers from load imbalance and limited adaptability to dynamic workloads. Meanwhile, because of the coupling between consensus and execution, a target shard must receive both the partitioned transactions and the partitioned accounts before initiating consensus and execution. However, we observe that transaction partitioning and subsequent consensus do not require… More >

Ruikang Ma^1,2, Ziying Huang¹, Zexiu Zhang³, Ruohui Lu⁴, Menghan Li¹, Zhiyi Luo³, Mengni Li⁵, Pengyue Zhang³, Xiaohong Lin³, Guozhuang Zhang^1,*, Linlin Dong^1,*

Phyton-International Journal of Experimental Botany, Vol.94, No.11, pp. 3721-3748, 2025, DOI:10.32604/phyton.2025.072062 - 01 December 2025

Abstract Dendrobium officinale (DO) is a well-recognized medicinal and edible plant with a long history of application in traditional medicinal practices across China and Southeast Asia. Recent studies have demonstrated that DO is abundant in diverse bioactive compounds, including polysaccharides (DOP), flavonoids, alkaloids, and bibenzyls thought to exert a range of pharmacological effects, such as anti-tumor and immunomodulatory effects. However, our comprehensive understanding of two key aspects—pharmacological functions and biosynthetic mechanisms—of DO’s major constituents remains limited, especially when considered within the clinical contexts of traditional use. To address this gap, this study reviews DO’s historical applications, clinical effects, and… More > Graphic Abstract

Kinzah Noor¹, Agbotiname Lucky Imoize^2,*, Michael Adedosu Adelabu³, Cheng-Chi Lee^4,5,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 1575-1664, 2025, DOI:10.32604/cmes.2025.073200 - 26 November 2025

Abstract The envisioned 6G wireless networks demand advanced Multiple Access (MA) schemes capable of supporting ultra-low latency, massive connectivity, high spectral efficiency, and energy efficiency (EE), especially as the current 5G networks have not achieved the promised 5G goals, including the projected 2000 times EE improvement over the legacy 4G Long Term Evolution (LTE) networks. This paper provides a comprehensive survey of Artificial Intelligence (AI)-enabled MA techniques, emphasizing their roles in Spectrum Sensing (SS), Dynamic Resource Allocation (DRA), user scheduling, interference mitigation, and protocol adaptation. In particular, we systematically analyze the progression of traditional and modern… More > Graphic Abstract

Bin Zhang¹, En-Cheng Liou^2,*, Yi-Chih Tung³, Muhammad Usman^2,4, Chiung-An Chen^2,4, Chao-Shun Yang^2,4

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 2551-2571, 2025, DOI:10.32604/cmes.2025.072471 - 26 November 2025

Abstract Indoor localization is a fundamental requirement for future 6G Intelligent Sensing and Communication (ISAC) systems, enabling precise navigation in environments where Global Positioning System (GPS) signals are unavailable. Existing methods, such as map-based navigation or site-specific fingerprinting, often require intensive data collection and lack generalization capability across different buildings, thereby limiting scalability. This study proposes a cross-site, map-free indoor localization framework that uses low-frequency sub-1 GHz radio signals and a Transformer-based neural network for robust positioning without prior environmental knowledge. The Transformer’s self-attention mechanisms allow it to capture spatial correlations among anchor nodes, facilitating accurate… More >

Mengting Huang, Meiting Lu, Li Yang, Jiwen Long, Li Zhou^*

Journal of Renewable Materials, Vol.13, No.10, pp. 2077-2090, 2025, DOI:10.32604/jrm.2025.02025-0122 - 22 October 2025

Abstract Peach gum polysaccharide (PGP), a readily available natural polysaccharide, boasts substantial potential across diverse applications, yet its practical utility is severely limited by its vulnerability to bacterial growth and limited antioxidant activity. Herein, we introduced a simple and effective method to enhance the antibacterial and antioxidant properties of PGP by conjugating it with salicylic acid (SA). Cytotoxicity evaluation results confirmed that the resulting PGP-SA retains the excellent biocompatibility of PGP. Notably, PGP-SA demonstrates outstanding antibacterial activity against both Gram-positive (S. aureus) and Gram-negative (E. coli) bacteria, outperforming non-modified PGP. Its antibacterial mechanism is hypothesized to stem from… More > Graphic Abstract

Livanshee Gupta¹, Nouha Haoudi^2,3,*, Lanjelina Oinam¹, Ananya Mahajan¹, Sonia Morya^1,*

Phyton-International Journal of Experimental Botany, Vol.94, No.9, pp. 2669-2700, 2025, DOI:10.32604/phyton.2025.065058 - 30 September 2025

Abstract The trends of consuming or using eco-friendly, biodegradable products due to the change in the lifestyle of the people have led to the exploration of new sources from plants or animals. Seed mucilage (SeM) is an underexplored component of plants that can be brought into play to deal with such problems. Mucilage, a viscous polysaccharide that can be obtained when seeds like chia, flax, garden cress, and tomato get hydrated and form a slimy, gel-like substance around the seed coat, can be utilized due to its unique characteristics. It has been used in developing many… More >

Naif Almusallam^1,*, Junaid Qayyum^2,3

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 3653-3687, 2025, DOI:10.32604/cmc.2025.067220 - 23 September 2025

Abstract This paper proposes a novel hybrid fraud detection framework that integrates multi-stage feature selection, unsupervised clustering, and ensemble learning to improve classification performance in financial transaction monitoring systems. The framework is structured into three core layers: (1) feature selection using Recursive Feature Elimination (RFE), Principal Component Analysis (PCA), and Mutual Information (MI) to reduce dimensionality and enhance input relevance; (2) anomaly detection through unsupervised clustering using K-Means, Density-Based Spatial Clustering (DBSCAN), and Hierarchical Clustering to flag suspicious patterns in unlabeled data; and (3) final classification using a voting-based hybrid ensemble of Support Vector Machine (SVM),… More >

Amal Al-Rasheed¹, Hashim Ali^2,*, Rahim Khan^2,*, Aamir Saeed³

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 3419-3436, 2025, DOI:10.32604/cmc.2025.065156 - 23 September 2025

Abstract In the domain of Electronic Medical Records (EMRs), emerging technologies are crucial to addressing longstanding concerns surrounding transaction security and patient privacy. This paper explores the integration of smart contracts and blockchain technology as a robust framework for securing sensitive healthcare data. By leveraging the decentralized and immutable nature of blockchain, the proposed approach ensures transparency, integrity, and traceability of EMR transactions, effectively mitigating risks of unauthorized access and data tampering. Smart contracts further enhance this framework by enabling the automation and enforcement of secure transactions, eliminating reliance on intermediaries and reducing the potential for… More >

Jiao Li, Xiaoyu Song^*

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5239-5254, 2025, DOI:10.32604/cmc.2025.065504 - 30 July 2025

Abstract The long transaction latency and low throughput of blockchain are the key challenges affecting the large-scale adoption of blockchain technology. Sharding technology is a primary solution by divides the blockchain network into multiple independent shards for parallel transaction processing. However, most existing random or modular schemes fail to consider the transactional relationships between accounts, which leads to a high proportion of cross-shard transactions, thereby increasing the communication overhead and transaction confirmation latency between shards. To solve this problem, this paper proposes a blockchain sharding algorithm based on account degree and frequency (DFSA). The algorithm takes… More >

Bo Li, Xiaoying Yang^*, Zhijie Pei, Xin Yang, Yaqi Wu

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3649-3672, 2025, DOI:10.32604/cmc.2025.066267 - 03 July 2025

Abstract It is well known that the kit completeness of parts processed in the previous stage is crucial for the subsequent manufacturing stage. This paper studies the flexible job shop scheduling problem (FJSP) with the objective of material kitting, where a material kit is a collection of components that ensures that a batch of components can be ready at the same time during the product assembly process. In this study, we consider completion time variance and maximum completion time as scheduling objectives, continue the weighted summation process for multiple objectives, and design adaptive weighted summation parameters… More >