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  • Open Access

    ARTICLE

    Summer Warming Limited Bud Output Drives a Decline in Daughter Shoot Biomass through Reduced Photosynthetis of Parent Shoots in Leymus chinensis Seedlings

    Song Gao1, Ruocheng Xu2, Lin Li3, Jiao Wang2, Nian Liu2, Johannes M. H. Knops4, Junfeng Wang2,*

    Phyton-International Journal of Experimental Botany, Vol.93, No.7, pp. 1667-1675, 2024, DOI:10.32604/phyton.2024.051548

    Abstract Understanding how summer warming influences the parent and daughter shoot production in a perennial clonal grass is vital for comprehending the response of grassland productivity to global warming. Here, we conducted a simulated experiment using potted Leymus chinensis, to study the relationship between the photosynthetic activity of parent shoots and the production of daughter shoots under a whole (90 days) summer warming scenario (+3°C). The results showed that the biomass of parents and buds decreased by 25.52% and 33.45%, respectively, under warming conditions. The reduction in parent shoot biomass due to warming directly resulted from decreased… More >

  • Open Access

    ARTICLE

    Swarming Computational Efficiency to Solve a Novel Third-Order Delay Differential Emden-Fowler System

    Wajaree Weera1, Zulqurnain Sabir2, Muhammad Asif Zahoor Raja3, Sakda Noinang4, Thongchai Botmart1,*

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4833-4849, 2022, DOI:10.32604/cmc.2022.030888

    Abstract The purpose of this research is to construct an integrated neuro swarming scheme using the procedures of the artificial neural networks (ANNs) with the use of global search particle swarm optimization (PSO) along with the competent local search interior-point programming (IPP) called as ANN-PSOIPP. The proposed computational scheme is implemented for the numerical simulations of the third order nonlinear delay differential Emden-Fowler model (TON-DD-EFM). The TON-DD-EFM is based on two types along with the particulars of shape factor, delayed terms, and singular points. A merit function is performed using the optimization of PSOIPP to find More >

  • Open Access

    ARTICLE

    Swarming Computational Techniques for the Influenza Disease System

    Sakda Noinang1, Zulqurnain Sabir2, Gilder Cieza Altamirano3, Muhammad Asif Zahoor Raja4, Manuel Jesús Sànchez-Chero5, María-Verónica Seminario-Morales5, Wajaree Weera6,*, Thongchai Botmart6

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4851-4868, 2022, DOI:10.32604/cmc.2022.029437

    Abstract The current study relates to designing a swarming computational paradigm to solve the influenza disease system (IDS). The nonlinear system’s mathematical form depends upon four classes: susceptible individuals, infected people, recovered individuals and cross-immune people. The solutions of the IDS are provided by using the artificial neural networks (ANNs) together with the swarming computational paradigm-based particle swarm optimization (PSO) and interior-point scheme (IPA) that are the global and local search approaches. The ANNs-PSO-IPA has never been applied to solve the IDS. Instead a merit function in the sense of mean square error is constructed using More >

  • Open Access

    ARTICLE

    Swarming Computational Approach for the Heartbeat Van Der Pol Nonlinear System

    Muhammad Umar1, Fazli Amin1, Soheil Salahshour2, Thongchai Botmart3, Wajaree Weera3, Prem Junswang4,*, Zulqurnain Sabir1

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 6185-6202, 2022, DOI:10.32604/cmc.2022.027970

    Abstract The present study is related to design a stochastic framework for the numerical treatment of the Van der Pol heartbeat model (VP-HBM) using the feedforward artificial neural networks (ANNs) under the optimization of particle swarm optimization (PSO) hybridized with the active-set algorithm (ASA), i.e., ANNs-PSO-ASA. The global search PSO scheme and local refinement of ASA are used as an optimization procedure in this study. An error-based merit function is defined using the differential VP-HBM form as well as the initial conditions. The optimization of the merit function is accomplished using the hybrid computing performances of More >

  • Open Access

    ARTICLE

    Swarming Behavior of Harris Hawks Optimizer for Arabic Opinion Mining

    Diaa Salam Abd Elminaam1,2,*, Nabil Neggaz3, Ibrahim Abdulatief Ahmed4,5, Ahmed El Sawy Abouelyazed4

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 4129-4149, 2021, DOI:10.32604/cmc.2021.019047

    Abstract At present, the immense development of social networks allows generating a significant amount of textual data, which has facilitated researchers to explore the field of opinion mining. In addition, the processing of textual opinions based on the term frequency-inverse document frequency method gives rise to a dimensionality problem. This study aims to detect the nature of opinions in the Arabic language employing a swarm intelligence (SI)-based algorithm, Harris hawks algorithm, to select the most relevant terms. The experimental study has been tested on two datasets: Arabic Jordanian General Tweets and Opinion Corpus for Arabic. In More >

  • Open Access

    ARTICLE

    Improving Mechanical Properties of Vitrified Umbilical Arteries with Magnetic Warming

    Mengyuan Cao, Yi Xu*, Yilin Dong

    FDMP-Fluid Dynamics & Materials Processing, Vol.17, No.1, pp. 123-139, 2021, DOI:10.32604/fdmp.2021.011443

    Abstract The damage caused by thermal stress during rewarming vitrified biosamples is one of the major obstacles for clinical purposes. Magnetic warming is a highly effective approach to overcome this hurdle and can achieve rapid and spatially homogeneous heating. The current research investigates the effects of magnetic warming on the histological and biomechanical properties of the vitrified umbilical arteries (UAs) through experiments and simulation. The results of experiments show that, for the case of magnetic warming comparing with the conventional water bath, magnetic warming presents better preservation of extracellular matrix (ECM), collagen fibers, elastic fibers, and… More >

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