The situation of plants on the slope can reflect the effect of vegetation restoration during the process of artificial vegetation recovery.Taking the typical damaged slope of Wenchuan earthquake area as the research o...The situation of plants on the slope can reflect the effect of vegetation restoration during the process of artificial vegetation recovery.Taking the typical damaged slope of Wenchuan earthquake area as the research object,through observing the vegetation situation of deserted slope,the results show that compositae plants and gramineous plants are suitable for being pioneer plants and dominant in community; during the vegetation succession,many compositae and gramineous species invade,but there is no magaphanerophytes invading; as time goes by,the herbaceous species and diversity increase gradually,so the ecosystem becomes more stable and the gradient is important for the vegetation restoration.展开更多
Waste collection is an important part of waste management system.Transportation costs and carbon emissions can be greatly reduced by proper vehicle routing.Meanwhile,each vehicle can work again after achieving its cap...Waste collection is an important part of waste management system.Transportation costs and carbon emissions can be greatly reduced by proper vehicle routing.Meanwhile,each vehicle can work again after achieving its capacity limit and unloading the waste.For this,an energy-efficient multi-trip vehicle routing model is established for municipal solid waste collection,which incorporates practical factors like the limited capacity,maximum working hours,and multiple trips of each vehicle.Considering both economy and environment,fixed costs,fuel costs,and carbon emission costs are minimized together.To solve the formulated model effectively,contribution-based adaptive particle swarm optimization is proposed.Four strategies named greedy learning,multi-operator learning,exploring learning,and exploiting learning are specifically designed with their own searching priorities.By assessing the contribution of each learning strategy during the process of evolution,an appropriate one is selected and assigned to each individual adaptively to improve the searching efficiency of the algorithm.Moreover,an improved local search operator is performed on the trips with the largest number of waste sites so that both the exploiting ability and the convergence accuracy of the algorithm are improved.Performance of the proposed algorithm is tested on ten waste collection instances,which include one real-world case derived from the Green Ring Company of Jiangbei New District,Nanjing,China,and nine synthetic instances with increasing scales generated from the commonly-used capacitated vehicle routing problem benchmark datasets.Comparisons with five state-of-the-art algorithms show that the proposed algorithm can obtain a solution with a higher accuracy for the constructed model.展开更多
Understanding the connection between brain and behavior in animals requires precise monitoring of their behaviors in three-dimensional(3-D)space.However,there is no available three-dimensional behavior capture system ...Understanding the connection between brain and behavior in animals requires precise monitoring of their behaviors in three-dimensional(3-D)space.However,there is no available three-dimensional behavior capture system that focuses on rodents.Here,we present MouseVenue3D,an automated and low-cost system for the efficient capture of 3-D skeleton trajectories in markerless rodents.We improved the most time-consuming step in 3-D behavior capturing by developing an automatic calibration module.Then,we validated this process in behavior recognition tasks,and showed that 3-D behavioral data achieved higher accuracy than 2-D data.Subsequently,MouseVenue3D was combined with fast high-resolution miniature two-photon microscopy for synchronous neural recording and behavioral tracking in the freely-moving mouse.Finally,we successfully decoded spontaneous neuronal activity from the 3-D behavior of mice.Our findings reveal that subtle,spontaneous behavior modules are strongly correlated with spontaneous neuronal activity patterns.展开更多
基金Supported by The Balanced Fertilization Technology of the Main Fast-growing Trees in Sichuan Province(JB201412)
文摘The situation of plants on the slope can reflect the effect of vegetation restoration during the process of artificial vegetation recovery.Taking the typical damaged slope of Wenchuan earthquake area as the research object,through observing the vegetation situation of deserted slope,the results show that compositae plants and gramineous plants are suitable for being pioneer plants and dominant in community; during the vegetation succession,many compositae and gramineous species invade,but there is no magaphanerophytes invading; as time goes by,the herbaceous species and diversity increase gradually,so the ecosystem becomes more stable and the gradient is important for the vegetation restoration.
基金This work was supported by the Guangdong Provincial Key Laboratory(No.2020B121201001)National Natural Science Foundation of China(NSFC)(Nos.61502239 and 62002148)+1 种基金Natural Science Foundation of Jiangsu Province of China(No.BK20150924)Shenzhen Science and Technology Program(No.KQTD2016112514355531).
文摘Waste collection is an important part of waste management system.Transportation costs and carbon emissions can be greatly reduced by proper vehicle routing.Meanwhile,each vehicle can work again after achieving its capacity limit and unloading the waste.For this,an energy-efficient multi-trip vehicle routing model is established for municipal solid waste collection,which incorporates practical factors like the limited capacity,maximum working hours,and multiple trips of each vehicle.Considering both economy and environment,fixed costs,fuel costs,and carbon emission costs are minimized together.To solve the formulated model effectively,contribution-based adaptive particle swarm optimization is proposed.Four strategies named greedy learning,multi-operator learning,exploring learning,and exploiting learning are specifically designed with their own searching priorities.By assessing the contribution of each learning strategy during the process of evolution,an appropriate one is selected and assigned to each individual adaptively to improve the searching efficiency of the algorithm.Moreover,an improved local search operator is performed on the trips with the largest number of waste sites so that both the exploiting ability and the convergence accuracy of the algorithm are improved.Performance of the proposed algorithm is tested on ten waste collection instances,which include one real-world case derived from the Green Ring Company of Jiangbei New District,Nanjing,China,and nine synthetic instances with increasing scales generated from the commonly-used capacitated vehicle routing problem benchmark datasets.Comparisons with five state-of-the-art algorithms show that the proposed algorithm can obtain a solution with a higher accuracy for the constructed model.
基金the Key Area R&D Program of Guangdong Province,China(2018B030338001 and 2018B030331001)the National Key R&D Program of China(2018YFA0701403)+11 种基金the National Natural Science Foundation of China(31500861,31630031,91732304,and 31930047)Chang Jiang Scholars Program,the International Big Science Program Cultivating Project of the Chinese Academy of Science(CAS172644KYS820170004)the Strategic Priority Research Program of the CAS(XDB32030100)the Youth Innovation Promotion Association of the CAS(2017413)the CAS Key Laboratory of Brain Connectome and Manipulation(2019DP173024)Shenzhen Government Basic Research Grants(JCYJ20170411140807570,JCYJ20170413164535041)the Science,Technology and Innovation Commission of Shenzhen Municipality(JCYJ20160429185235132)a Helmholtz-CAS Joint Research grant(GJHZ1508)Guangdong Provincial Key Laboratory of Brain Connectome and Behavior(2017B030301017)the Ten Thousand Talent Program,the Guangdong Special Support Program,Key Laboratory of Shenzhen Institute of Advanced Technology(2019DP173024)the Shenzhen Key Science and Technology Infrastructure Planning Project(ZDKJ20190204002).
文摘Understanding the connection between brain and behavior in animals requires precise monitoring of their behaviors in three-dimensional(3-D)space.However,there is no available three-dimensional behavior capture system that focuses on rodents.Here,we present MouseVenue3D,an automated and low-cost system for the efficient capture of 3-D skeleton trajectories in markerless rodents.We improved the most time-consuming step in 3-D behavior capturing by developing an automatic calibration module.Then,we validated this process in behavior recognition tasks,and showed that 3-D behavioral data achieved higher accuracy than 2-D data.Subsequently,MouseVenue3D was combined with fast high-resolution miniature two-photon microscopy for synchronous neural recording and behavioral tracking in the freely-moving mouse.Finally,we successfully decoded spontaneous neuronal activity from the 3-D behavior of mice.Our findings reveal that subtle,spontaneous behavior modules are strongly correlated with spontaneous neuronal activity patterns.
