Learning Gaussian Mixture Representations for Tensor Time Series Forecasting

Tensor time series (TTS) data, a generalization of one-dimensional time series on a high-dimensional space, is ubiquitous in real-world scenarios, especially in monitoring systems involving multi-source spatio-temporal data (e.g., transportation demands and air pollutants). Compared to modeling time series or multivariate time series, which has received much attention and achieved tremendous progress in recent years, tensor time series has been paid less effort. Properly coping with the tensor time series is a much more challenging task, due to its high-dimensional and complex inner structure. In this paper, we develop a novel TTS forecasting framework, which seeks to individually model each heterogeneity component implied in the time, the location, and the source variables. We name this framework as GMRL, short for Gaussian Mixture Representation Learning. Experiment results on two real-world TTS datasets verify the superiority of our approach compared with the state-of-the-art baselines.Comment: 9 pages, 5 figures, published to IJCAI 202

Application of Image Processing and Three-Dimensional Data Reconstruction Algorithm Based on Traffic Video in Vehicle Component Detection

Vehicle detection is one of the important technologies in intelligent video surveillance systems. Owing to the perspective projection imaging principle of cameras, traditional two-dimensional (2D) images usually distort the size and shape of vehicles. In order to solve these problems, the traffic scene calibration and inverse projection construction methods are used to project the three-dimensional (3D) information onto the 2D images. In addition, a vehicle target can be characterized by several components, and thus vehicle detection can be fulfilled based on the combination of these components. The key characteristics of vehicle targets are distinct during a single day; for example, the headlight brightness is more significant at night, while the vehicle taillight and license plate color are much more prominent in the daytime. In this paper, by using the background subtraction method and Gaussian mixture model, we can realize the accurate detection of target lights at night. In the daytime, however, the detection of the license plate and taillight of a vehicle can be fulfilled by exploiting the background subtraction method and the Markov random field, based on the spatial geometry relation between the corresponding components. Further, by utilizing Kalman filters to follow the vehicle tracks, detection accuracy can be further improved. Finally, experiment results demonstrate the effectiveness of the proposed methods

On the Measurements of Individual Particle Properties Via Compression and Crushing

An experimental study is presented to measure the elastic, yielding, and crushing properties of individual particles under compression using substrates made of aluminum alloy, stainless steel, and sapphire. Carefully selected, highly spherical individual Ottawa sand particles of 0.75-1.1 mm in nominal diameter were compressed between two smooth substrates, and the load-deformation curves were analyzed by Hertz elastic contact theory to derive their reduced modulus and Young\u27s modulus as well as yielding and crushing strengths, which vary significantly with the type of substrate materials. Further analysis of the yielding and plastic deformation at the particle-substrate contact shows that the yield strength or hardness of the substrate materials dominates the local contact behavior and hence affects the measured apparent yielding and crushing strengths. The two softer substrates (aluminum alloy and stainless steel) actually lead to underestimated apparent shear yield strengths of quartz particles by 60.4% and 54.2%, respectively, which are actually the yielding of substrates, while the true particle yielding occurs in the sapphire-particle contact. Moreover, the two softer substrates cause much overestimated crushing strengths of the quartz particles by 50.4% and 36.4%, respectively. Selection of inappropriate substrate materials and inappropriate interpretation of the particle-substrate contact can lead to significant errors in the measured yielding and crushing strengths. It is recommended that single particle compression testing uses substrates with yield strength greater than that of the tested particles and result interpretation also considers the elastic and yielding behaviors of the substrates. (C) 2021 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences. Production and hosting by Elsevier B.V

Spatio-Temporal Adaptive Embedding Makes Vanilla Transformer SOTA for Traffic Forecasting

With the rapid development of the Intelligent Transportation System (ITS), accurate traffic forecasting has emerged as a critical challenge. The key bottleneck lies in capturing the intricate spatio-temporal traffic patterns. In recent years, numerous neural networks with complicated architectures have been proposed to address this issue. However, the advancements in network architectures have encountered diminishing performance gains. In this study, we present a novel component called spatio-temporal adaptive embedding that can yield outstanding results with vanilla transformers. Our proposed Spatio-Temporal Adaptive Embedding transformer (STAEformer) achieves state-of-the-art performance on five real-world traffic forecasting datasets. Further experiments demonstrate that spatio-temporal adaptive embedding plays a crucial role in traffic forecasting by effectively capturing intrinsic spatio-temporal relations and chronological information in traffic time series.Comment: Accepted as CIKM2023 Short Pape

Fabrication Process Simulation of a PEM Fuel Cell Catalyst Layer and Its Microscopic Structure Characteristics

The catalyst layers (CLs) in proton exchange membrane fuel cells (PEMFCs) are porous composites of complex microstructures of the building blocks, i.e., Pt nano-particles, carbonaceous substrates and Nafion ionomers. It is important to understand the factors that control the microstructure formation in the fabrication process. A coarse-grained molecular dynamics (CG-MD) method is employed to investigate the fabrication process of CLs, which depends on the type and amount of components and also the type of the dispersion medium (ethylene glycol, isopropanol or hexanol) used during ink preparation of the catalyst-coated membranes (CCMs). The dynamical behaviors of all the components are outlined and analyzed following the fabrication steps. In addition, the Pt nano-particle size distribution is evaluated and compared with the labor testing. Furthermore, the primary pore size distributions in the final formations of three cases are shown and compared with the experiments. The sizes of the reconstructed agglomerates are also considered on the effect of solvent polarity. (C) 2012 The Electrochemical Society. [DOI: 10.1149/2.064203jes] All rights reserved

Single and composite damage mechanisms of soil polyethylene/polyvinyl chloride microplastics to the photosynthetic performance of soybean (Glycine max [L.] merr.)

IntroductionAdverse impacts of soil microplastics (MPs, diameter<5 mm) on vegetative growth and crop production have been widely reported, however, the single and composite damage mechanisms of polyethylene (PE) /polyvinyl chloride (PVC) microplastics (MPs) induced photosynthesis inhibition are still rarely known.MethodsIn this study, two widely distributed MPs, PE and PVC, were added to soils at a dose of 7% (dry soil) to examine the single and composite effects of PE-MPs and PVC-MPs on the photosynthetic performance of soybean.ResultsResults showed PE-MPs, PVC-MPs and the combination of these two contaminants increased malondialdehyde (MDA) content by 21.8-97.9%, while decreased net photosynthesis rate (Pn) by 11.5-22.4% compared to those in non-stressed plants, PVC MPs caused the most severe oxidative stress, while MPs stress resulted in Pn reduction caused by non-stomatal restriction. The reason for this is the single and composite MPs stress resulted in a 6% to 23% reduction in soybean PSII activity RCs reaction centers, along with negative effects on soybean PSII energy uptake, capture, transport, and dissipation. The presence of K-band and L-band also represents an imbalance in the number of electrons on the donor and acceptor side of PSII and a decrease in PSII energy transfer. Similarly, PVC single stress caused greater effects on soybean chloroplast PSII than PE single stress and combined stresses.DiscussionPE and PVC microplastic stress led to oxidative stress in soybean, which affected the structure and function of photosynthetic PSII in soybean, ultimately leading to a decrease in net photosynthetic rate in soybean

The site conditions of the Guo Shou Jing Telescope

The weather at Xinglong Observing Station, where the Guo Shou Jing Telescope (GSJT) is located, is strongly affected by the monsoon climate in north-east China. The LAMOST survey strategy is constrained by these weather patterns. In this paper, we present a statistics on observing hours from 2004 to 2007, and the sky brightness, seeing, and sky transparency from 1995 to 2011 at the site. We investigate effects of the site conditions on the survey plan. Operable hours each month shows strong correlation with season: on average there are 8 operable hours per night available in December, but only 1-2 hours in July and August. The seeing and the sky transparency also vary with seasons. Although the seeing is worse in windy winters, and the atmospheric extinction is worse in the spring and summer, the site is adequate for the proposed scientific program of LAMOST survey. With a Monte Carlo simulation using historical data on the site condition, we find that the available observation hours constrain the survey footprint from 22h to 16h in right ascension; the sky brightness allows LAMOST to obtain the limit magnitude of V = 19.5mag with S/N = 10.Comment: 10 pages, 8 figures, accepted for publication in RA

Association of Traffic-Related Air Pollution with Children’s Neurobehavioral Functions in Quanzhou, China

http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000270874101349&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Public, Environmental & Occupational HealthSCI(E)CPCI-S(ISTP)06S228-S2292

Root hairs facilitate rice root penetration into compacted layers

Compacted soil layers adversely affect rooting depth and access to deeper nutrient and water resources, thereby impacting climate resilience of crop production and global food security. Root hair plays well-known roles in facilitating water and nutrient acquisition. Here, we report that root hair also contributes to root penetration into compacted layers. We demonstrate that longer root hair, induced by elevated auxin response during a root compaction response, improves the ability of rice roots to penetrate harder layers. This compaction-induced auxin response in the root hair zone is dependent on the root apex-expressed auxin synthesis gene OsYUCCA8 (OsYUC8), which is induced by compaction stress. This auxin source for root hair elongation relies on the auxin influx carrier AUXIN RESISTANT 1 (OsAUX1), mobilizing this signal from the root apex to the root hair zone. Mutants disrupting OsYUC8 and OsAUX1 genes exhibit shorter root hairs and weaker penetration ability into harder layers compared with wild type (WT). Root-hair-specific mutants phenocopy these auxin-signaling mutants, as they also exhibit an attenuated root penetration ability. We conclude that compaction stress upregulates OsYUC8-mediated auxin biosynthesis in the root apex, which is subsequently mobilized to the root hair zone by OsAUX1, where auxin promotes root hair elongation, improving anchorage of root tips to their surrounding soil environment and aiding their penetration ability into harder layers