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  • Open Access

    ARTICLE

    Belowground Bud Bank Is Insensitive to Short-Term Nutrient Addition in the Meadow Steppe of Inner Mongolia

    Jin Tao1, Jiatai Tian1, Dongmei Li1, Jinlei Zhu2, Qun Ma3, Zhiming Zhang1, Jungang Chen4, Yipeng Liu5, Jianqiang Qian1,*

    Phyton-International Journal of Experimental Botany, Vol.93, No.6, pp. 1129-1141, 2024, DOI:10.32604/phyton.2024.051405

    Abstract Human activities and industrialization have significantly increased soil nutrients, such as nitrogen (N) and phosphorus (P), profoundly impacting the composition and structure of plant community, as well as the ecosystem functions, especially in nutrient-limited ecosystems. However, as the key propagule pool of perennial grasslands, how belowground bud bank and its relationship with aboveground vegetation respond to short-term changes in soil nutrients was still unclear. In this study, we conducted a short-term (2021–2022) soil fertilization experiment with N addition (10 g N m yr) and P addition (5 g N m yr) in the meadow steppe… More >

  • Open Access

    ARTICLE

    Performance Improvement through Novel Adaptive Node and Container Aware Scheduler with Resource Availability Control in Hadoop YARN

    J. S. Manjaly, T. Subbulakshmi*

    Computer Systems Science and Engineering, Vol.47, No.3, pp. 3083-3108, 2023, DOI:10.32604/csse.2023.036320

    Abstract The default scheduler of Apache Hadoop demonstrates operational inefficiencies when connecting external sources and processing transformation jobs. This paper has proposed a novel scheduler for enhancement of the performance of the Hadoop Yet Another Resource Negotiator (YARN) scheduler, called the Adaptive Node and Container Aware Scheduler (ANACRAC), that aligns cluster resources to the demands of the applications in the real world. The approach performs to leverage the user-provided configurations as a unique design to apportion nodes, or containers within the nodes, to application thresholds. Additionally, it provides the flexibility to the applications for selecting and… More >

  • Open Access

    ARTICLE

    Predicting Resource Availability in Local Mobile Crowd Computing Using Convolutional GRU

    Pijush Kanti Dutta Pramanik1, Nilanjan Sinhababu2, Anand Nayyar3,4,*, Mehedi Masud5, Prasenjit Choudhury1

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5199-5212, 2022, DOI:10.32604/cmc.2022.019630

    Abstract In mobile crowd computing (MCC), people’s smart mobile devices (SMDs) are utilized as computing resources. Considering the ever-growing computing capabilities of today’s SMDs, a collection of them can offer significantly high-performance computing services. In a local MCC, the SMDs are typically connected to a local Wi-Fi network. Organizations and institutions can leverage the SMDs available within the campus to form local MCCs to cater to their computing needs without any financial and operational burden. Though it offers an economical and sustainable computing solution, users’ mobility poses a serious issue in the QoS of MCC. To… More >

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