Ain Raal¹, Valeriia Kokitko², Vira Odyntsova², Anne Orav³, Oleh Koshovyi^1,4,*

Phyton-International Journal of Experimental Botany, Vol.93, No.7, pp. 1365-1382, 2024, DOI:10.32604/phyton.2024.053754

Abstract Valeriana officinalis L. is a plant from the Caprifoliaceae family, which is widely distributed in various parts of the world, especially in Europe and Asia. All species of Valeriana are distinguished by their ability to synthesize essential oil, which has a powerful effect on the physiological and mental aspects of the human body. The aim was to study the qualitative and quantitative composition of essential oil from valerian roots, collected in different countries, using the gas chromatography method, and to establish marker compounds for valerian species. 13 samples of commercial roots with rhizomes of V. officinalis from nine… More >

Adel A. Rezk^1,2,*, Mohamed M. El-Malky³, Heba I. Mohamed^4,*, Hossam S. El-Beltagi^1,5

Phyton-International Journal of Experimental Botany, Vol.93, No.7, pp. 1733-1748, 2024, DOI:10.32604/phyton.2024.052739

Abstract Twenty-four rice genotypes were examined to assess genetic variability, heritability, and correlations for seven-grain quality traits, eight nutritional elements, and protein. ANOVA revealed significant differences for the quality traits studied. For every trait under study, the phenotypic coefficient of variation was higher than the correspondence genotypic coefficient of variation. Heritability in a broad sense varied from 29.75% for grain length to 98.31% for the elongation trait. Hulling percentage recovery had a highly significant positive correlation with milling and head rice percentage. Consequently, milling percentage had a highly positive correlation with head rice percentage. In amylose… More >

Pengcheng Li^1,2,#, Tianze Zhu^1,#, Yunyun Wang^1,2, Shuangyi Yin¹, Xinjie Zhu¹, Minggang Ji¹, Wenye Rui¹, Houmiao Wang¹, Zefeng Yang^1,2,*, Chenwu Xu^1,2,*

Phyton-International Journal of Experimental Botany, Vol.93, No.7, pp. 1441-1453, 2024, DOI:10.32604/phyton.2024.052219

Abstract The nutritional composition and overall quality of maize kernels are largely determined by the key chemical components: protein, oil, and starch. Nevertheless, the genetic basis underlying these nutritional quality traits during grain filling remains poorly understood. In this study, the concentrations of protein, oil, and starch were studied in 204 recombinant inbred lines resulting from a cross between DH1M and T877 at four different stages post-pollination. All the traits exhibited considerable phenotypic variation. During the grain-filling stage, the levels of protein and starch content generally increased, whereas oil content decreased, with significant changes observed between… More >

Yolotzin Apatzingán Palomino-Hermosillo¹, Ángel Elpidio Díaz-Jasso², Rosendo Balois-Morales¹, Verónica Alhelí Ochoa-Jiménez^1,3, Pedro Ulises Bautista-Rosales¹, Guillermo Berumen-Varela^1,*

Phyton-International Journal of Experimental Botany, Vol.93, No.7, pp. 1717-1732, 2024, DOI:10.32604/phyton.2024.052216

Abstract Soursop (Annona muricata L.) is a tropical fruit highly valued for its unique flavor, nutritional value, and health-promoting properties. The ripening process of soursop involves complex changes in gene expression and metabolite accumulation, which have been studied using various omics technologies. Transcriptome analysis has provided insights into the regulation of key genes involved in ripening, while metabolic compound analysis has revealed the presence of numerous bioactive compounds with potential health benefits. However, the integration of transcriptome and metabolite compound data has not been extensively explored in soursop. Therefore, in this paper, we present a comprehensive analysis… More >

Jiamin Huang^1,2, Ping Wu^2,*, Wangxin Li³, Jun Zhang², Yidong Xu²

Structural Durability & Health Monitoring, Vol.18, No.5, pp. 577-598, 2024, DOI:10.32604/sdhm.2024.050338

Abstract With the advent of the big data era and the rise of Industrial Revolution 4.0, digital twins (DTs) have gained significant attention in various industries. DTs offer the opportunity to combine the physical and digital worlds and aid the digital transformation of the civil engineering industry. In this paper, 605 documents obtained from the search were first analysed using CiteSpace for literature visualisation, and an author co-occurrence network, a keyword co-occurrence network, and a keyword clustering set were obtained. Next, through a literature review of 86 papers, this paper summarises the current status of DT More >

Tianzhe Jiao, Chaopeng Guo, Xiaoyue Feng, Yuming Chen, Jie Song^*

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1-35, 2024, DOI:10.32604/cmc.2024.053204

Abstract Multi-modal fusion technology gradually become a fundamental task in many fields, such as autonomous driving, smart healthcare, sentiment analysis, and human-computer interaction. It is rapidly becoming the dominant research due to its powerful perception and judgment capabilities. Under complex scenes, multi-modal fusion technology utilizes the complementary characteristics of multiple data streams to fuse different data types and achieve more accurate predictions. However, achieving outstanding performance is challenging because of equipment performance limitations, missing information, and data noise. This paper comprehensively reviews existing methods based on multi-modal fusion techniques and completes a detailed and in-depth analysis.… More >

Li Li^*, Qing Zhang, Youran Kong

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 801-818, 2024, DOI:10.32604/cmc.2024.051916

Abstract Due to the diversity and unpredictability of changes in malicious code, studying the traceability of variant families remains challenging. In this paper, we propose a GAN-EfficientNetV2-based method for tracing families of malicious code variants. This method leverages the similarity in layouts and textures between images of malicious code variants from the same source and their original family of malicious code images. The method includes a lightweight classifier and a simulator. The classifier utilizes the enhanced EfficientNetV2 to categorize malicious code images and can be easily deployed on mobile, embedded, and other devices. The simulator utilizes… More >

Mohamed Karray^1,*, Nesrine Triki^2,*, Mohamed Ksantini²

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 119-138, 2024, DOI:10.32604/cmc.2024.051562

Abstract Advanced Driver Assistance Systems (ADAS) technologies can assist drivers or be part of automatic driving systems to support the driving process and improve the level of safety and comfort on the road. Traffic Sign Recognition System (TSRS) is one of the most important components of ADAS. Among the challenges with TSRS is being able to recognize road signs with the highest accuracy and the shortest processing time. Accordingly, this paper introduces a new real time methodology recognizing Speed Limit Signs based on a trio of developed modules. Firstly, the Speed Limit Detection (SLD) module uses… More >

Chunhong Zeng, Kang Lu, Zhiqin He^*, Qinmu Wu

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1441-1456, 2024, DOI:10.32604/cmc.2024.051551

Abstract Personalized gait curves are generated to enhance patient adaptability to gait trajectories used for passive training in the early stage of rehabilitation for hemiplegic patients. The article utilizes the random forest algorithm to construct a gait parameter model, which maps the relationship between parameters such as height, weight, age, gender, and gait speed, achieving prediction of key points on the gait curve. To enhance prediction accuracy, an attention mechanism is introduced into the algorithm to focus more on the main features. Meanwhile, to ensure high similarity between the reconstructed gait curve and the normal one, More >

Yongguo Li, Yuanrong Wang, Jia Xie^*, Caiyin Xu, Kun Zhang

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 467-486, 2024, DOI:10.32604/cmc.2024.051426

Abstract To address the challenges of missed detections in water surface target detection using solely visual algorithms in unmanned surface vehicle (USV) perception, this paper proposes a method based on the fusion of visual and LiDAR point-cloud projection for water surface target detection. Firstly, the visual recognition component employs an improved YOLOv7 algorithm based on a self-built dataset for the detection of water surface targets. This algorithm modifies the original YOLOv7 architecture to a Slim-Neck structure, addressing the problem of excessive redundant information during feature extraction in the original YOLOv7 network model. Simultaneously, this modification simplifies… More >