Vehicle trajectory clustering based on dynamic representation learning of internet of vehicles

With the widely used Internet of Things, 5G, and smart city technologies, we are able to acquire a variety of vehicle trajectory data. These trajectory data are of great significance which can be used to extract relevant information in order to, for instance, calculate the optimal path from one position to another, detect abnormal behavior, monitor the traffic flow in a city, and predict the next position of an object. One of the key technology is to cluster vehicle trajectory. However, existing methods mainly rely on manually designed metrics which may lead to biased results. Meanwhile, the large scale of vehicle trajectory data has become a challenge because calculating these manually designed metrics will cost more time and space. To address these challenges, we propose to employ network representation learning to achieve accurate vehicle trajectory clustering. Specifically, we first construct the k-nearest neighbor-based internet of vehicles in a dynamic manner. Then we learn the low-dimensional representations of vehicles by performing dynamic network representation learning on the constructed network. Finally, using the learned vehicle vectors, vehicle trajectories are clustered with machine learning methods. Experimental results on the real-word dataset show that our method achieves the best performance compared against baseline methods. © 2000-2011 IEEE. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Feng Xia” is provided in this record*

Presynaptic CRF1 Receptors Mediate the Ethanol Enhancement of GABAergic Transmission in the Mouse Central Amygdala

Corticotropin-releasing factor (CRF) is a 41-amino-acid neuropeptide involved in stress responses initiated from several brain areas, including the amygdala formation. Research shows a strong relationship between stress, brain CRF, and excessive alcohol consumption. Behavioral studies suggest that the central amygdala (CeA) is significantly involved in alcohol reward and dependence. We recently reported that the ethanol augmentation of GABAergic synaptic transmission in rat CeA involves CRF1 receptors, because both CRF and ethanol significantly enhanced the amplitude of evoked GABAergic inhibitory postsynaptic currents (IPSCs) in CeA neurons from wild-type (WT) and CRF2 knockout (KO) mice, but not in neurons of CRF1 KO mice. The present study extends these findings using selective CRF receptor ligands, gene KO models, and miniature IPSC (mIPSC) analysis to assess further a presynaptic role for the CRF receptors in mediating ethanol effects in the CeA. In whole-cell patch recordings of pharmacologically isolated GABAAergic IPSCs from slices of mouse CeA, both CRF and ethanol augmented evoked IPSCs in a concentration-dependent manner, with low EC50s. A CRF1 (but not CRF2) KO construct and the CRF1-selective nonpeptide antagonist NIH-3 (LWH-63) blocked the augmenting effect of both CRF and ethanol on evoked IPSCs. Furthermore, the new selective CRF1 agonist stressin1, but not the CRF2 agonist urocortin 3, also increased evoked IPSC amplitudes. Both CRF and ethanol decreased paired-pulse facilitation (PPF) of evoked IPSCs and significantly enhanced the frequency, but not the amplitude, of spontaneous miniature GABAergic mIPSCs in CeA neurons of WT mice, suggesting a presynaptic site of action. The PPF effect of ethanol was abolished in CeA neurons of CRF1 KO mice. The CRF1 antagonist NIH-3 blocked the CRF- and ethanol-induced enhancement of mIPSC frequency in CeA neurons. These data indicate that presynaptic CRF1 receptors play a critical role in permitting or mediating ethanol enhancement of GABAergic synaptic transmission in CeA, via increased vesicular GABA release, and thus may be a rational target for the treatment of alcohol abuse and alcoholism

Allylic oxidation of olefins with a manganese-based metal-organic framework

Selective oxidation of olefins to α,β-unsaturated ketones under mild reaction conditions have attracted considerable interest, since α,β-unsaturated ketones can serve to be synthetic precursors for various downstream chemical products. The major challenges inherently with this chemical oxidation are chem-, regio-selectivity as well as environmental concerns, i.e. catalyst recycle, safety and cost. Using atmospheric oxygen as an environmental friendly oxidant, we found that a metal-organic framework (MOF) constructed with Mn and tetrazolate ligand (CPF-5) showed good activity and selectivity for the allylic oxidation of olefins to α,β-unsaturated ketones. Under the optimized condition, we could achieve 98% conversion of cyclohexene and 87% selectivity toward cyclohexanone. The combination of a substoichiometric amount of TBHP (tert-butylhydroperoxide) and oxygen not only provides a cost effective oxidation system but significantly enhances the selectivity to α,β-unsaturated ketones, outperforming most reported oxidation methods. This catalytic system is heterogeneous in nature, and CPF-5 could be reused at least five times without a significant decrease in its catalytic activity and selectivity

Automatic method for individual parcellation of manganese-enhanced magnetic resonance imaging of rat brain

AimsTo construct an automatic method for individual parcellation of manganese-enhanced magnetic resonance imaging (MEMRI) of rat brain with high accuracy, which could preserve the inherent voxel intensity and Regions of interest (ROI) morphological characteristics simultaneously.Methods and resultsThe transformation relationship from standardized space to individual space was obtained by firstly normalizing individual image to the Paxinos space and then inversely transformed. On the other hand, all the regions defined in the atlas image were separated and resaved as binary mask images. Then, transforming the mask images into individual space via the inverse transformations and reslicing using the 4th B-spline interpolation algorithm. The boundary of these transformed regions was further refined by image erosion and expansion operator, and finally combined together to generate the individual parcellations. Moreover, two groups of MEMRI images were used for evaluation. We found that the individual parcellations were satisfied, and the inherent image intensity was preserved. The statistical significance of case-control comparisons was further optimized.ConclusionsWe have constructed a new automatic method for individual parcellation of rat brain MEMRI images, which could preserve the inherent voxel intensity and further be beneficial in case-control statistical analyses. This method could also be extended to other imaging modalities, even other experiments species. It would facilitate the accuracy and significance of ROI-based imaging analyses

Effects of Sublethal Concentrations of Chlorpyrifos on Olfactory Learning and Memory Performances in Two Bee Species, Apis mellifera and Apis cerana

Chlorpyrifos is a widely used organophosphorus insecticide. The acute oral 24 h median lethal dose (LD50) value of chlorpyrifos in Apis mellifera and in Apis cerana was estimated to assess differential acute chlorpyrifos toxicity in both bee species. The LD50 values of chlorpyrifos in A. mellifera and in A. cerana are 103.4 ng/bee and 81.8 ng/bee, respectively, which suggests that A. cerana bees are slightly more sensitive than A. mellifera bees to the toxicity of chlorpyrifos. Doses half the acute LD50 of chlorpyrifos were selected to study behavioral changes in both bee species using proboscis extension response assay. A. mellifera foragers treated with chlorpyrifos showed significantly lower response to the 10% sucrose solution compared to control bees after 2, 24 and 48 h. Chlorpyrifos significantly impaired the olfactory learning abilities and 2 h memory retention of forager bees regardless of honey bee species, which may affect the foraging success of bees exposed to chlorpyrifos

Identification of genes related to high royal jelly production in the honey bee (Apis mellifera) using microarray analysis

China is the largest royal jelly producer and exporter in the world, and high royal jelly-yielding strains have been bred in the country for approximately three decades. However, information on the molecular mechanism underlying high royal jelly production is scarce. Here, a cDNA microarray was used to screen and identify differentially expressed genes (DEGs) to obtain an overview on the changes in gene expression levels between high and low royal jelly producing bees. We developed a honey bee gene chip that covered 11,689 genes, and this chip was hybridised with cDNA generated from RNA isolated from heads of nursing bees. A total of 369 DEGs were identified between high and low royal jelly producing bees. Amongst these DEGs, 201 (54.47%) genes were up-regulated, whereas 168 (45.53%) were down-regulated in high royal jelly-yielding bees. Gene ontology (GO) analyses showed that they are mainly involved in four key biological processes, and pathway analyses revealed that they belong to a total of 46 biological pathways. These results provide a genetic basis for further studies on the molecular mechanisms involved in high royal jelly production.This work was supported by National Natural Science Foundation of China (No.30571409), Educational and scientific research program for young and middle-aged instructor of Fujian province (No.JAT160161) and the earmarked fund for Modern Agro-industry Technology Research System (No.CARS-45-KXJ3

Facile Fabrication of Hierarchical MOF–Metal Nanoparticle Tandem Catalysts for the Synthesis of Bioactive Molecules

Multifunctional metal–organic frameworks (MOFs) that possess permanent porosity are promising catalysts in organic transformation. Herein, we report the construction of a hierarchical MOF functionalized with basic aliphatic amine groups and polyvinylpyrrolidone-capped platinum nanoparticles (Pt NPs). The postsynthetic covalent modification of organic ligands increases basic site density in the MOF and simultaneously introduces mesopores to create a hierarchically porous structure. The multifunctional MOF is capable of catalyzing a sequential Knoevenagel condensation–hydrogenation–intramolecular cyclization reaction. The unique selective reduction of the nitro group to intermediate hydroxylamine by Pt NPs supported on MOF followed by intramolecular cyclization with a cyano group affords an excellent yield (up to 92%) to the uncommon quinoline N-oxides over quinolines. The hierarchical MOF and polyvinylpyrrolidone capping agent on Pt NPs synergistically facilitate the enrichment of substrates and thus lead to high activity in the reduction–intramolecular cyclization reaction. The bioactivity assay indicates that the synthesized quinoline N-oxides evidently inhibit the proliferation of lung cancer cells. Our findings demonstrate the feasibility of MOF-catalyzed direct synthesis of bioactive molecules from readily available compounds under mild conditions

Asymptotic Spreading Speed for the Weak Competition System with a Free Boundary

This paper is concerned with a diffusive Lotka-Volterra type competition system with a free boundary in one space dimension. Such a system may be used to describe the invasion of a new species into the habitat of a native competitor, and its long-time dynamical behavior can be described by a spreading-vanishing dichotomy. The main purpose of this paper is to determine the asymptotic spreading speed of the invading species when its spreading is successful, which involves two systems of traveling wave type equations