To explore the spatial heterogeneity of plankton communities in a deep artificial lake （Songhua Lake, China）, samples were collected at seven sites. Samples were investigated by denaturing gradient gel electrophores...To explore the spatial heterogeneity of plankton communities in a deep artificial lake （Songhua Lake, China）, samples were collected at seven sites. Samples were investigated by denaturing gradient gel electrophoresis （DGGE） analysis of the PCR-amplified 16S and 18S rRNA genes and specific bands were sequenced. Cluster analysis of the DGGE profiles revealed that all of the samples grouped into two distinct clusters, in accordance with sampling site; while in each cluster, the divergence of sub-clusters correlated with sampling depth. Sequence analysis of selected dominant DGGE bands revealed that most sequenced phylotypes （84%） exhibited 〉97% similarity to the closest sequences in GenBank, and were affiliated with ten common freshwater plankton phyla （Proteobacteria, Actinobacteria, Bacteroidetes, Cyanobacteria, Bacillariophyta, Pyrrophyta, Cryptophyta, Ciliophora, Stramenopiles, and Rotifera）. Several of these groups are also found worldwide, indicating the cosmopolitan distribution of the phylotypes. The relationships between DGGE patterns and environmental factors were analyzed by redundancy analysis （RDA）. The results suggested that, total nitrogen, nitrate, nitrite, temperature were strongly correlated with the variation ammonia, and CODMn concentrations, and water in plankton composition.展开更多
Smart homes can provide complementary information to assist home service robots.We present a robotic misplaced item finding(MIF)system,which uses human historical trajectory data obtained in a smart home environment.F...Smart homes can provide complementary information to assist home service robots.We present a robotic misplaced item finding(MIF)system,which uses human historical trajectory data obtained in a smart home environment.First,a multi-sensor fusion method is developed to localize and track a resident.Second,a path-planning method is developed to generate the robot movement plan,which considers the knowledge of the human historical trajectory.Third,a real-time object detector based on a convolutional neural network is applied to detect the misplaced item.We present MIF experiments in a smart home testbed and the experimental results verify the accuracy and efficiency of our solution.展开更多
基金Supported by the National Natural Science Foundation of China(No.51178090)the National Key Technology R&D Program of China(No.2012BAJ21B02-02)the National Water Pollution Control and Management Technology Major Projects(No.2009ZX07106-001)
文摘To explore the spatial heterogeneity of plankton communities in a deep artificial lake （Songhua Lake, China）, samples were collected at seven sites. Samples were investigated by denaturing gradient gel electrophoresis （DGGE） analysis of the PCR-amplified 16S and 18S rRNA genes and specific bands were sequenced. Cluster analysis of the DGGE profiles revealed that all of the samples grouped into two distinct clusters, in accordance with sampling site; while in each cluster, the divergence of sub-clusters correlated with sampling depth. Sequence analysis of selected dominant DGGE bands revealed that most sequenced phylotypes （84%） exhibited 〉97% similarity to the closest sequences in GenBank, and were affiliated with ten common freshwater plankton phyla （Proteobacteria, Actinobacteria, Bacteroidetes, Cyanobacteria, Bacillariophyta, Pyrrophyta, Cryptophyta, Ciliophora, Stramenopiles, and Rotifera）. Several of these groups are also found worldwide, indicating the cosmopolitan distribution of the phylotypes. The relationships between DGGE patterns and environmental factors were analyzed by redundancy analysis （RDA）. The results suggested that, total nitrogen, nitrate, nitrite, temperature were strongly correlated with the variation ammonia, and CODMn concentrations, and water in plankton composition.
基金Project supported by the Basic Public Research Program of Zhejiang Province,China(No.LGF18F030001)the Open Research Project of the State Key Laboratory of Industrial Control Technology,Zhejiang University,China(No.ICT1800414)
文摘Smart homes can provide complementary information to assist home service robots.We present a robotic misplaced item finding(MIF)system,which uses human historical trajectory data obtained in a smart home environment.First,a multi-sensor fusion method is developed to localize and track a resident.Second,a path-planning method is developed to generate the robot movement plan,which considers the knowledge of the human historical trajectory.Third,a real-time object detector based on a convolutional neural network is applied to detect the misplaced item.We present MIF experiments in a smart home testbed and the experimental results verify the accuracy and efficiency of our solution.
