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  • Open Access

    REVIEW

    In vitro Mutagenesis for the Improvement of Agave Genus

    Sugey Vásquez-Hernández, Joaquín Adolfo Montes-Molina*, Federico Antonio Gutiérrez-Miceli, Sheila Jazmín Reyes-Zambrano, Carlos Alberto Lecona-Guzmán*

    Phyton-International Journal of Experimental Botany, Vol.92, No.7, pp. 2065-2078, 2023, DOI:10.32604/phyton.2023.028784

    Abstract Biotechnological techniques provide a viable alternative to help improve and increase the production of plant species of agricultural and economic importance, which have been affected over the years by climate change, increasing their susceptibility to pests and/or diseases, generating losses in production as well as a decrease in their regenerative and genetic diversity. The application of biotechnological techniques such as in vitro mutagenesis offers a viable option for the generation of crops that are resistant to the different factors caused by abiotic and biotic stress. In vitro mutagenesis has been used in an efficient way to generate genetic changes in… More >

  • Open Access

    ARTICLE

    The correlation of miRNA expression and tumor mutational burden in uterine corpus endometrial carcinoma

    YANYA CHEN1,#, HONGYUAN WU2,#, RUISI ZHOU5,#, HELING DONG4, XUEFANG ZHANG2, XUEWEI WU1, WENSHAN CHEN1, YANTING YOU5,*, YIFEN WU3,*

    BIOCELL, Vol.47, No.6, pp. 1353-1364, 2023, DOI:10.32604/biocell.2023.027346

    Abstract Background: The relationship between microRNA (miRNA) expression patterns and tumor mutation burden (TMB) in uterine corpus endometrial carcinoma (UCEC) was investigated in this study. Methods: The UCEC dataset from The Cancer Genome Atlas (TCGA) database was used to identify the miRNAs that differ in expression between high TMB and low TMB sample sets. The total sample sets were divided into a training set and a test set. TMB levels were predicted using miRNA-based signature classifiers developed by Lasso Cox regression. Test sets were used to validate the classifier. This study investigated the relationship between a miRNA-based signature classifier and three… More >

  • Open Access

    ARTICLE

    Short-Term Prediction of Photovoltaic Power Generation Based on LMD Permutation Entropy and Singular Spectrum Analysis

    Wenchao Ma*

    Energy Engineering, Vol.120, No.7, pp. 1685-1699, 2023, DOI:10.32604/ee.2023.025404

    Abstract The power output state of photovoltaic power generation is affected by the earth's rotation and solar radiation intensity. On the one hand, its output sequence has daily periodicity; on the other hand, it has discrete randomness. With the development of new energy economy, the proportion of photovoltaic energy increased accordingly. In order to solve the problem of improving the energy conversion efficiency in the grid-connected optical network and ensure the stability of photovoltaic power generation, this paper proposes the short-term prediction of photovoltaic power generation based on the improved multi-scale permutation entropy, local mean decomposition and singular spectrum analysis algorithm.… More >

  • Open Access

    ARTICLE

    Multi-Strategy Boosted Spider Monkey Optimization Algorithm for Feature Selection

    Jianguo Zheng, Shuilin Chen*

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3619-3635, 2023, DOI:10.32604/csse.2023.038025

    Abstract To solve the problem of slow convergence and easy to get into the local optimum of the spider monkey optimization algorithm, this paper presents a new algorithm based on multi-strategy (ISMO). First, the initial population is generated by a refracted opposition-based learning strategy to enhance diversity and ergodicity. Second, this paper introduces a non-linear adaptive dynamic weight factor to improve convergence efficiency. Then, using the crisscross strategy, using the horizontal crossover to enhance the global search and vertical crossover to keep the diversity of the population to avoid being trapped in the local optimum. At last, we adopt a Gauss-Cauchy… More >

  • Open Access

    ARTICLE

    Implementation of Hybrid Particle Swarm Optimization for Optimized Regression Testing

    V. Prakash*, S. Gopalakrishnan

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2575-2590, 2023, DOI:10.32604/iasc.2023.032122

    Abstract Software test case optimization improves the efficiency of the software by proper structure and reduces the fault in the software. The existing research applies various optimization methods such as Genetic Algorithm, Crow Search Algorithm, Ant Colony Optimization, etc., for test case optimization. The existing methods have limitations of lower efficiency in fault diagnosis, higher computational time, and high memory requirement. The existing methods have lower efficiency in software test case optimization when the number of test cases is high. This research proposes the Tournament Winner Genetic Algorithm (TW-GA) method to improve the efficiency of software test case optimization. Hospital Information… More >

  • Open Access

    ARTICLE

    Novel Metrics for Mutation Analysis

    Savas Takan1,*, Gokmen Katipoglu2

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 2075-2089, 2023, DOI:10.32604/csse.2023.036791

    Abstract A measure of the “goodness” or efficiency of the test suite is used to determine the proficiency of a test suite. The appropriateness of the test suite is determined through mutation analysis. Several Finite State Machine (FSM) mutants are produced in mutation analysis by injecting errors against hypotheses. These mutants serve as test subjects for the test suite (TS). The effectiveness of the test suite is proportional to the number of eliminated mutants. The most effective test suite is the one that removes the most significant number of mutants at the optimal time. It is difficult to determine the fault… More >

  • Open Access

    ARTICLE

    An Improved Reptile Search Algorithm Based on Cauchy Mutation for Intrusion Detection

    Salahahaldeen Duraibi*

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 2509-2525, 2023, DOI:10.32604/csse.2023.036119

    Abstract With the growth of the discipline of digital communication, the topic has acquired more attention in the cybersecurity medium. The Intrusion Detection (ID) system monitors network traffic to detect malicious activities. The paper introduces a novel Feature Selection (FS) approach for ID. Reptile Search Algorithm (RSA)—is a new optimization algorithm; in this method, each agent searches a new region according to the position of the host, which makes the algorithm suffers from getting stuck in local optima and a slow convergence rate. To overcome these problems, this study introduces an improved RSA approach by integrating Cauchy Mutation (CM) into the… More >

  • Open Access

    ARTICLE

    An Improved Bald Eagle Search Algorithm with Cauchy Mutation and Adaptive Weight Factor for Engineering Optimization

    Wenchuan Wang1,*, Weican Tian1, Kwok-wing Chau2, Yiming Xue1, Lei Xu3, Hongfei Zang1

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1603-1642, 2023, DOI:10.32604/cmes.2023.026231

    Abstract The Bald Eagle Search algorithm (BES) is an emerging meta-heuristic algorithm. The algorithm simulates the hunting behavior of eagles, and obtains an optimal solution through three stages, namely selection stage, search stage and swooping stage. However, BES tends to drop-in local optimization and the maximum value of search space needs to be improved. To fill this research gap, we propose an improved bald eagle algorithm (CABES) that integrates Cauchy mutation and adaptive optimization to improve the performance of BES from local optima. Firstly, CABES introduces the Cauchy mutation strategy to adjust the step size of the selection stage, to select… More >

  • Open Access

    REVIEW

    Advances in Targeted Therapy Against Driver Mutations and Epigenetic Alterations in Non-Small Cell Lung Cancer

    Jiajian Shi1, Yuchen Chen1,*, Chentai Peng1, Linwu Kuang2, Zitong Zhang1, Yangkai Li2,*, Kun Huang1

    Oncologie, Vol.24, No.4, pp. 613-648, 2022, DOI:10.32604/oncologie.2022.027545

    Abstract The incidence and mortality of lung cancer rank top three of all cancers worldwide. Accounting for 85% of the total number of lung cancer, non-small cell lung cancer (NSCLC) is an important factor endangering human health. Recently, targeted therapies against driver mutations and epigenetic alterations have made encouraging advances that benefit NSCLC patients. Druggable driver mutations, which mainly occur in EGFR, KRAS, MET, HER2, ALK, ROS1, RET and BRAF, have been identified in more than a quarter of NSCLC patients. A series of highly selective mutant targeting inhibitors, such as EGFR tyrosine kinase inhibitors and KRAS inhibitors, have been well… More >

  • Open Access

    ARTICLE

    Al-Biruni Earth Radius (BER) Metaheuristic Search Optimization Algorithm

    El-Sayed M. El-kenawy1,2, Abdelaziz A. Abdelhamid3,4, Abdelhameed Ibrahim5, Seyedali Mirjalili6,7, Nima Khodadad8, Mona A. Al duailij9, Amel Ali Alhussan9,*, Doaa Sami Khafaga9

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1917-1934, 2023, DOI:10.32604/csse.2023.032497

    Abstract Metaheuristic optimization algorithms present an effective method for solving several optimization problems from various types of applications and fields. Several metaheuristics and evolutionary optimization algorithms have been emerged recently in the literature and gained widespread attention, such as particle swarm optimization (PSO), whale optimization algorithm (WOA), grey wolf optimization algorithm (GWO), genetic algorithm (GA), and gravitational search algorithm (GSA). According to the literature, no one metaheuristic optimization algorithm can handle all present optimization problems. Hence novel optimization methodologies are still needed. The Al-Biruni earth radius (BER) search optimization algorithm is proposed in this paper. The proposed algorithm was motivated by… More >

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