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  • Open Access

    ARTICLE

    Integrative Analysis of Transcriptome and Phenolic Compounds Profile Provides Insights into the Quality of Soursop (Annona muricata L.) Fruit

    Yolotzin Apatzingán Palomino-Hermosillo1, Ángel Elpidio Díaz-Jasso2, Rosendo Balois-Morales1, Verónica Alhelí Ochoa-Jiménez1,3, Pedro Ulises Bautista-Rosales1, Guillermo Berumen-Varela1,*

    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 >

  • Open Access

    REVIEW

    Organ Abscission in Plants: With Special Emphasis on Bell Pepper

    Ramiro Reyes-Castro1, Héctor G. Núñez-Palenius1,*, Juan I. Valiente-Banuet2, María E. Sosa-Morales1, Blanca E. Orosco-Alcalá1, Rafael Guzmán-Mendoza1, Graciela M. L. Ruiz-Aguilar1, Rogelio Costilla-Salazar1

    Phyton-International Journal of Experimental Botany, Vol.93, No.7, pp. 1467-1484, 2024, DOI:10.32604/phyton.2024.051644

    Abstract Bell pepper (Capsicum annuum L.), along with potato and tomato, is one of the three most cultivated vegetables in the world. Bell pepper is worldwide accepted due to its characteristics of color, smell, flavor, and texture. Bell pepper is also considered a nutritious food due to its vitamin and antioxidant contents. In Mexico, bell pepper production has a high value because it is grown for the international markets, particularly the United States of America. Nevertheless, the abscission of flowers and fruits is a factor that limits the yield, hinders the planning of activities, and causes a More >

  • Open Access

    ARTICLE

    Study of a Hydraulic Jump in an Asymmetric Trapezoidal Channel with Different Sluice Gates

    Bouthaina Debabeche1,2,*, Sonia Cherhabil3

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.7, pp. 1499-1516, 2024, DOI:10.32604/fdmp.2024.047403

    Abstract In this study, the main properties of the hydraulic jump in an asymmetric trapezoidal flume are analyzed experimentally, including the so-called sequent depths, characteristic lengths, and efficiency. In particular, an asymmetric trapezoidal flume with a length of 7 m and a width of 0.304 m is considered, with the bottom of the flume transversely inclined at an angle of m = 0.296 and vertical lateral sides. The corresponding inflow Froude number is allowed to range in the interval (1.40 < F1 < 6.11). The properties of this jump are compared to those of hydraulic jumps More >

  • Open Access

    ARTICLE

    Detecting XSS with Random Forest and Multi-Channel Feature Extraction

    Qiurong Qin, Yueqin Li*, Yajie Mi, Jinhui Shen, Kexin Wu, Zhenzhao Wang

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 843-874, 2024, DOI:10.32604/cmc.2024.051769

    Abstract In the era of the Internet, widely used web applications have become the target of hacker attacks because they contain a large amount of personal information. Among these vulnerabilities, stealing private data through cross-site scripting (XSS) attacks is one of the most commonly used attacks by hackers. Currently, deep learning-based XSS attack detection methods have good application prospects; however, they suffer from problems such as being prone to overfitting, a high false alarm rate, and low accuracy. To address these issues, we propose a multi-stage feature extraction and fusion model for XSS detection based on… More >

  • Open Access

    ARTICLE

    An Improved Iterated Greedy Algorithm for Solving Rescue Robot Path Planning Problem with Limited Survival Time

    Xiaoqing Wang1, Peng Duan1,*, Leilei Meng1,*, Kaidong Yang2

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 931-947, 2024, DOI:10.32604/cmc.2024.050612

    Abstract Effective path planning is crucial for mobile robots to quickly reach rescue destination and complete rescue tasks in a post-disaster scenario. In this study, we investigated the post-disaster rescue path planning problem and modeled this problem as a variant of the travel salesman problem (TSP) with life-strength constraints. To address this problem, we proposed an improved iterated greedy (IIG) algorithm. First, a push-forward insertion heuristic (PFIH) strategy was employed to generate a high-quality initial solution. Second, a greedy-based insertion strategy was designed and used in the destruction-construction stage to increase the algorithm’s exploration ability. Furthermore,… More >

  • Open Access

    ARTICLE

    Classified VPN Network Traffic Flow Using Time Related to Artificial Neural Network

    Saad Abdalla Agaili Mohamed*, Sefer Kurnaz

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 819-841, 2024, DOI:10.32604/cmc.2024.050474

    Abstract VPNs are vital for safeguarding communication routes in the continually changing cybersecurity world. However, increasing network attack complexity and variety require increasingly advanced algorithms to recognize and categorize VPN network data. We present a novel VPN network traffic flow classification method utilizing Artificial Neural Networks (ANN). This paper aims to provide a reliable system that can identify a virtual private network (VPN) traffic from intrusion attempts, data exfiltration, and denial-of-service assaults. We compile a broad dataset of labeled VPN traffic flows from various apps and usage patterns. Next, we create an ANN architecture that can… More >

  • Open Access

    ARTICLE

    A Multi-Strategy-Improved Northern Goshawk Optimization Algorithm for Global Optimization and Engineering Design

    Liang Zeng1,2, Mai Hu1, Chenning Zhang1, Quan Yuan1, Shanshan Wang1,2,*

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1677-1709, 2024, DOI:10.32604/cmc.2024.049717

    Abstract Optimization algorithms play a pivotal role in enhancing the performance and efficiency of systems across various scientific and engineering disciplines. To enhance the performance and alleviate the limitations of the Northern Goshawk Optimization (NGO) algorithm, particularly its tendency towards premature convergence and entrapment in local optima during function optimization processes, this study introduces an advanced Improved Northern Goshawk Optimization (INGO) algorithm. This algorithm incorporates a multifaceted enhancement strategy to boost operational efficiency. Initially, a tent chaotic map is employed in the initialization phase to generate a diverse initial population, providing high-quality feasible solutions. Subsequently, after… More >

  • Open Access

    ABSTRACT

    Abstracts of the XLIII ANNUAL MEETING of ROSARIO SOCIETY OF BIOLOGY

    BIOCELL, Vol.48, Suppl.3, pp. 1-15, 2024

    Abstract This article has no abstract. More >

  • Open Access

    ABSTRACT

    Abstracts of the XLI Annual Meeting of Cuyo Biology Society

    BIOCELL, Vol.48, Suppl.2, pp. 1-71, 2024

    Abstract This article has no abstract. More >

  • Open Access

    ARTICLE

    Microarray Gene Expression Classification: An Efficient Feature Selection Using Hybrid Swarm Intelligence Algorithm

    Punam Gulande*, R. N. Awale

    Computer Systems Science and Engineering, Vol.48, No.4, pp. 937-952, 2024, DOI:10.32604/csse.2024.046123

    Abstract The study of gene expression has emerged as a vital tool for cancer diagnosis and prognosis, particularly with the advent of microarray technology that enables the measurement of thousands of genes in a single sample. While this wealth of data offers invaluable insights for disease management, the high dimensionality poses a challenge for multiclass classification. In this context, selecting relevant features becomes essential to enhance classification model performance. Swarm Intelligence algorithms have proven effective in addressing this challenge, owing to their ability to navigate intricate, non-linear feature-class relationships. This paper introduces a novel hybrid swarm More >

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