Riwa Mahai¹, Rongpeng Liu¹, Xiaolang Du¹, Zejing Mu¹, Xiaoyun Wang^1,*, Jun Yuan^2,*

Phyton-International Journal of Experimental Botany, Vol.93, No.6, pp. 1203-1219, 2024, DOI:10.32604/phyton.2024.051559

Abstract Rosaceae represents a vast and complex group of species, with its classification being intricate and contentious. The taxonomic placement of many species within this family has been a subject of ongoing debate. The study utilized the Illumina platform to sequence 19 plant species from 10 genera in the Rosaceae. The cp genomes, varying in size from 153,366 to 159,895 bp, followed the typical quadripartite organization consisting of a large single-copy (LSC) region (84,545 to 87,883 bp), a small single-copy (SSC) region (18,174 to 19,259 bp), and a pair of inverted repeat (IR) regions (25,310 to… More >

Zhengfeng Lai, Dongmei Lian, Shaoping Zhang, Yudong Ju, Bizhen Lin, Yunfa Yao, Songhai Wu, Jianji Hong, Zhou Li^*

Phyton-International Journal of Experimental Botany, Vol.93, No.6, pp. 1143-1158, 2024, DOI:10.32604/phyton.2024.051207

Abstract The cytokinin oxidase/dehydrogenase (CKX) enzyme is essential for controlling the fluctuating levels of endogenous cytokinin (CK) and has a significant impact on different aspects of plant growth and development. Nonetheless, there is limited knowledge about CKX genes in tomato (Solanum lycopersicum L.). Here we performed genome-wide identification and analysis of nine SlCKX family members in tomatoes using bioinformatics tools. The results revealed that nine SlCKX genes were unevenly distributed on five chromosomes (Chr.1, Chr.4, Chr.8, Chr.10, and Chr.12). The amino acid length, isoelectric points, and molecular weight of the nine SlCKX proteins ranged from 453 to 553, 5.77… More >

Mengdong An¹, Weiyuan Zhong¹, Wei Xu², Xiuli Wang^1,*

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.6, pp. 1331-1349, 2024, DOI:10.32604/fdmp.2023.046604

Abstract The reactor coolant pump (RCP) rotor seizure accident is defined as a short-time seizure of the RCP rotor. This event typically leads to an abrupt flow decrease in the corresponding loop and an ensuing reactor and turbine trip. The significant reduction of core coolant flow while the reactor is being operated at full load can have very negative consequences. This potentially dangerous event is typically characterized by a complex transient behavior in terms of flow conditions and energy transformation, which need to be analyzed and understood. This study constructed transient flow and rotational speed mathematical More > Graphic Abstract

Lihui Ma^1,*, Zhuo Han¹, Wei Li¹, Guangfeng Qi¹, Ran Cheng², Yuanyuan Wang¹, Xiangran Mi³, Xiaohan Zhang¹, Yunfei Li¹

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.6, pp. 1381-1392, 2024, DOI:10.32604/fdmp.2024.046405

Abstract When a gas-liquid two-phase flow (GLTPF) enters a parallel separator through a T-junction, it generally splits unevenly. This phenomenon can seriously affect the operation efficiency and safety of the equipment located downstream. In order to investigate these aspects and, more specifically, the so-called bias phenomenon (all gas and liquid flowing to one pipe, while the other pipe is a liquid column that fluctuates up and down), laboratory experiments were carried out by using a T-junction connected to two parallel vertical pipes. Moreover, a GLTPF prediction model based on the principle of minimum potential energy was… More >

Aneel Manan¹, Pu Zhang^1,*, Shoaib Ahmad², Jawad Ahmad²

Journal of Polymer Materials, Vol.41, No.1, pp. 15-44, 2024, DOI:10.32604/jpm.2024.053859

Abstract Fiber-reinforced polymer (FRP) bars are gaining popularity as an alternative to steel reinforcement due to their advantages such as corrosion resistance and high strength-to-weight ratio. However, FRP has a lower modulus of elasticity compared to steel. Therefore, special attention is required in structural design to address deflection related issues and ensure ductile failure. This research explores the use of machine learning algorithms such as gene expression programming (GEP) to develop a simple and effective equation for predicting the elastic modulus of hybrid fiber-reinforced polymer (HFPR) bars. A comprehensive database of 125 experimental results of HFPR… More >

Jiahui Liu^1,2, Lang Li^1,2,*, Di Li^1,2, Yu Ou^1,2

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4641-4657, 2024, DOI:10.32604/cmc.2024.051613

Abstract Correlation power analysis (CPA) combined with genetic algorithms (GA) now achieves greater attack efficiency and can recover all subkeys simultaneously. However, two issues in GA-based CPA still need to be addressed: key degeneration and slow evolution within populations. These challenges significantly hinder key recovery efforts. This paper proposes a screening correlation power analysis framework combined with a genetic algorithm, named SFGA-CPA, to address these issues. SFGA-CPA introduces three operations designed to exploit CPA characteristics: propagative operation, constrained crossover, and constrained mutation. Firstly, the propagative operation accelerates population evolution by maximizing the number of correct bytes… More >

Hailing Yang¹, Suoping Li^1,2,*, Duo Peng²

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 5273-5294, 2024, DOI:10.32604/cmc.2024.050869

Abstract To address the problems of network congestion and spectrum resources shortage in multi-user large-scale scenarios, this paper proposes a twice random access OFDMA-NOMA-RA protocol combining the advantages of orthogonal frequency division multiple access (OFDMA) and non-orthogonal multiple access (NOMA). The idea of this protocol is that OFMDA is used to divide the entire frequency field into multiple orthogonal resource units (RUs), and NOMA is used on each RU to enable more users to access the channel and improve spectrum efficiency. Based on the protocol designed in this paper, in the case of imperfect successive interference… More >

Ahmed Redha Mahlous^*

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4781-4803, 2024, DOI:10.32604/cmc.2024.050821

Abstract Smart agriculture modifies traditional farming practices, and offers innovative approaches to boost production and sustainability by leveraging contemporary technologies. In today’s world where technology is everything, these technologies are utilized to streamline regular tasks and procedures in agriculture, one of the largest and most significant industries in every nation. This research paper stands out from existing literature on smart agriculture security by providing a comprehensive analysis and examination of security issues within smart agriculture systems. Divided into three main sections—security analysis, system architecture and design and risk assessment of Cyber-Physical Systems (CPS) applications—the study delves… More >

Adel Assiri¹, Abdu Gumaei^2,*, Faisal Mehmood^3,*, Touqeer Abbas⁴, Sami Ullah⁵

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4219-4236, 2024, DOI:10.32604/cmc.2024.050781

Abstract Modern technological advancements have made social media an essential component of daily life. Social media allow individuals to share thoughts, emotions, and ideas. Sentiment analysis plays the function of evaluating whether the sentiment of the text is positive, negative, neutral, or any other personal emotion to understand the sentiment context of the text. Sentiment analysis is essential in business and society because it impacts strategic decision-making. Sentiment analysis involves challenges due to lexical variation, an unlabeled dataset, and text distance correlations. The execution time increases due to the sequential processing of the sequence models. However,… More >

Xin Xiong¹, Jing Zhang¹, Sanli Yi¹, Chunwu Wang², Ruixiang Liu³, Jianfeng He^1,*

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4659-4681, 2024, DOI:10.32604/cmc.2024.050528

Abstract The analysis of microstates in EEG signals is a crucial technique for understanding the spatiotemporal dynamics of brain electrical activity. Traditional methods such as Atomic Agglomerative Hierarchical Clustering (AAHC), K-means clustering, Principal Component Analysis (PCA), and Independent Component Analysis (ICA) are limited by a fixed number of microstate maps and insufficient capability in cross-task feature extraction. Tackling these limitations, this study introduces a Global Map Dissimilarity (GMD)-driven density canopy K-means clustering algorithm. This innovative approach autonomously determines the optimal number of EEG microstate topographies and employs Gaussian kernel density estimation alongside the GMD index for… More >