Cloud computing has gained significant recognition due to its ability to provide a broad range of online services and applications.Nevertheless,existing commercial cloud computing models demonstrate an appropriate des...Cloud computing has gained significant recognition due to its ability to provide a broad range of online services and applications.Nevertheless,existing commercial cloud computing models demonstrate an appropriate design by concentrating computational assets,such as preservation and server infrastructure,in a limited number of large-scale worldwide data facilities.Optimizing the deployment of virtual machines(VMs)is crucial in this scenario to ensure system dependability,performance,and minimal latency.A significant barrier in the present scenario is the load distribution,particularly when striving for improved energy consumption in a hypothetical grid computing framework.This design employs load-balancing techniques to allocate different user workloads across several virtual machines.To address this challenge,we propose using the twin-fold moth flame technique,which serves as a very effective optimization technique.Developers intentionally designed the twin-fold moth flame method to consider various restrictions,including energy efficiency,lifespan analysis,and resource expenditures.It provides a thorough approach to evaluating total costs in the cloud computing environment.When assessing the efficacy of our suggested strategy,the study will analyze significant metrics such as energy efficiency,lifespan analysis,and resource expenditures.This investigation aims to enhance cloud computing techniques by developing a new optimization algorithm that considers multiple factors for effective virtual machine placement and load balancing.The proposed work demonstrates notable improvements of 12.15%,10.68%,8.70%,13.29%,18.46%,and 33.39%for 40 count data of nodes using the artificial bee colony-bat algorithm,ant colony optimization,crow search algorithm,krill herd,whale optimization genetic algorithm,and improved Lévy-based whale optimization algorithm,respectively.展开更多
The leaves of Bt (Bacillus thuringiensis) transgenic poplar (Populus nigra L.) and CpTI (Cowpea trypsin inhibitor) transgenic poplar ((P. tomentosa×P. bolleana)×P. Tomentosa) were taken to feed the 4th-5th-i...The leaves of Bt (Bacillus thuringiensis) transgenic poplar (Populus nigra L.) and CpTI (Cowpea trypsin inhibitor) transgenic poplar ((P. tomentosa×P. bolleana)×P. Tomentosa) were taken to feed the 4th-5th-instar larvae of American white moth (Hyphantria cunea (Drury)) for determination of the activities of the protective enzyme system inside larvae’s body. The physiological and biochemical effects of the transgenic poplars on the larvae were studied. The results showed that the two kinds of transgenic poplars had similar effects on the protective enzyme system in the midgut of larvae. The activities of superoxide dismutase, catalase, and peroxidase in midgut of the larvae increased gradually, reached the highest value at a certain time, and then decreased suddenly. For the larvae that were fed with the leaves of Bt transgenic poplar, the peak value of superoxide dismutase and catalase presented at the time of 24-h feeding, while the peak of peroxidase took place at the time of 12-h feeding. The activities of these protective enzymes for the larvae that were fed with leaves of CpTI transgenic poplar peaked 12 h later than that of those fed with leaves of Bt transgenic poplar. The comparison of activities of the protective enzymes was also carried out between the larvae with different levels of intoxication. It was found that the activities of protective enzyme of the seriously intoxicant larvae were higher than that of the lightly intoxicant larvae. This difference was more obvious in the group treated with CpTI transgenic poplar.展开更多
针对新能源渗透率提升带来的电压稳定风险,同时考虑柔性互联装置逐步在电力系统试点应用的背景,提出一种考虑电压稳定的含智能储能软开关(soft open point with energy storage system integration,E-SOP)配电系统分布式电源双层规划模...针对新能源渗透率提升带来的电压稳定风险,同时考虑柔性互联装置逐步在电力系统试点应用的背景,提出一种考虑电压稳定的含智能储能软开关(soft open point with energy storage system integration,E-SOP)配电系统分布式电源双层规划模型。首先,分析电压稳定指标及E-SOP的作用机理。其次,基于拉丁超立方采样和经K-medoids算法融合的改进同步回代缩减法得到典型概率日场景。然后,建立含E-SOP接入的双层规划模型,上层模型以年综合费用最小为目标,对风电、光伏等设备进行选址定容;下层模型以电压稳定性、网络损耗、平均电压偏移等为目标,实施含E-SOP的有功无功协同优化。最后,采用改进飞蛾扑火算法进行模型求解。经IEEE 33节点配电系统算例分析,其结果表明,该模型能有效提高配电系统的经济性和实时运行的电压稳定性,验证了求解算法的优越性。展开更多
基金This work was supported in part by the Natural Science Foundation of the Education Department of Henan Province(Grant 22A520025)the National Natural Science Foundation of China(Grant 61975053)the National Key Research and Development of Quality Information Control Technology for Multi-Modal Grain Transportation Efficient Connection(2022YFD2100202).
文摘Cloud computing has gained significant recognition due to its ability to provide a broad range of online services and applications.Nevertheless,existing commercial cloud computing models demonstrate an appropriate design by concentrating computational assets,such as preservation and server infrastructure,in a limited number of large-scale worldwide data facilities.Optimizing the deployment of virtual machines(VMs)is crucial in this scenario to ensure system dependability,performance,and minimal latency.A significant barrier in the present scenario is the load distribution,particularly when striving for improved energy consumption in a hypothetical grid computing framework.This design employs load-balancing techniques to allocate different user workloads across several virtual machines.To address this challenge,we propose using the twin-fold moth flame technique,which serves as a very effective optimization technique.Developers intentionally designed the twin-fold moth flame method to consider various restrictions,including energy efficiency,lifespan analysis,and resource expenditures.It provides a thorough approach to evaluating total costs in the cloud computing environment.When assessing the efficacy of our suggested strategy,the study will analyze significant metrics such as energy efficiency,lifespan analysis,and resource expenditures.This investigation aims to enhance cloud computing techniques by developing a new optimization algorithm that considers multiple factors for effective virtual machine placement and load balancing.The proposed work demonstrates notable improvements of 12.15%,10.68%,8.70%,13.29%,18.46%,and 33.39%for 40 count data of nodes using the artificial bee colony-bat algorithm,ant colony optimization,crow search algorithm,krill herd,whale optimization genetic algorithm,and improved Lévy-based whale optimization algorithm,respectively.
文摘The leaves of Bt (Bacillus thuringiensis) transgenic poplar (Populus nigra L.) and CpTI (Cowpea trypsin inhibitor) transgenic poplar ((P. tomentosa×P. bolleana)×P. Tomentosa) were taken to feed the 4th-5th-instar larvae of American white moth (Hyphantria cunea (Drury)) for determination of the activities of the protective enzyme system inside larvae’s body. The physiological and biochemical effects of the transgenic poplars on the larvae were studied. The results showed that the two kinds of transgenic poplars had similar effects on the protective enzyme system in the midgut of larvae. The activities of superoxide dismutase, catalase, and peroxidase in midgut of the larvae increased gradually, reached the highest value at a certain time, and then decreased suddenly. For the larvae that were fed with the leaves of Bt transgenic poplar, the peak value of superoxide dismutase and catalase presented at the time of 24-h feeding, while the peak of peroxidase took place at the time of 12-h feeding. The activities of these protective enzymes for the larvae that were fed with leaves of CpTI transgenic poplar peaked 12 h later than that of those fed with leaves of Bt transgenic poplar. The comparison of activities of the protective enzymes was also carried out between the larvae with different levels of intoxication. It was found that the activities of protective enzyme of the seriously intoxicant larvae were higher than that of the lightly intoxicant larvae. This difference was more obvious in the group treated with CpTI transgenic poplar.
文摘针对新能源渗透率提升带来的电压稳定风险,同时考虑柔性互联装置逐步在电力系统试点应用的背景,提出一种考虑电压稳定的含智能储能软开关(soft open point with energy storage system integration,E-SOP)配电系统分布式电源双层规划模型。首先,分析电压稳定指标及E-SOP的作用机理。其次,基于拉丁超立方采样和经K-medoids算法融合的改进同步回代缩减法得到典型概率日场景。然后,建立含E-SOP接入的双层规划模型,上层模型以年综合费用最小为目标,对风电、光伏等设备进行选址定容;下层模型以电压稳定性、网络损耗、平均电压偏移等为目标,实施含E-SOP的有功无功协同优化。最后,采用改进飞蛾扑火算法进行模型求解。经IEEE 33节点配电系统算例分析,其结果表明,该模型能有效提高配电系统的经济性和实时运行的电压稳定性,验证了求解算法的优越性。
