Analysis of Spatial Travel Association Rules for Rail Transit Based on AFC and POI Data

In order to explore the spatial distribution rules and causes of urban rail transit passenger travel, this paper mines the spatial 1-frequent itemset and 2-frequent itemsets of weekdays and weekends metro passenger travel based on Apriori algorithm using the continuous week of Automatic Fare Collection System (AFC) swipe card. At the same time, the K-Means algorithm is used to cluster the subway stations and explore the causes of association rules by combining the Point of Interest (POI) data of the same period within the radiation range of the subway stations. The study shows that the spatial distribution pattern of inbound and outbound passenger flow of Shanghai rail transit is consistent between weekdays and weekends, and the outbound passenger flow is more concentrated than the inbound passenger flow, and the significance of weekends is higher; the spatial distribution of metro stations is "circled"; the analysis of the high-lift association rules show that a large passenger flow group centered on the type 3 station is formed in the spatial location, and the passenger flow within the group is mainly commuter flow with separation of employment and residence. The association rule mining of metro passenger travel data is beneficial to understanding the spatial distribution pattern and causes of metro ridership, which can provide reference for rail network planning and operation management

Pyrene-based aggregation-induced emission luminogens and their applications

"Unity is force"-Aesop. It is a common phenomenon that traditional chromophores exhibit high fluorescence in dilute solutions, yet luminescence is quenched at high concentrations or in the aggregate state, i.e. "aggregation-caused quenching" (ACQ). Tang reported the unusual photophysical observation that luminogens can exhibit weak or no fluorescence in solution, yet they are highly emissive in the aggregate or solid state; this is defined as aggregation-induced emission (AIE). The discovery of AIE helped solve the ACQ effect in traditional luminophores. Pyrene is an important polycyclic aromatic hydrocarbon (PAH), which exhibits very different photophysical behavior in solution versus the aggregate state, and the ACQ effect has played a dominant role in pyrene chemistry. The ACQ effect is harmful for some practical applications and is a challenge in organic light-emitting diodes (OLEDs) and light-emitting electrochemical cells, for which the effect is more severe in the solid state. Thus, how to overcome the ACQ effect observed in pyrene chemistry still remains a challenge. In this review, we discuss how following basic AIE mechanisms such as the restriction of intramolecular motion (RIM), excited-state intramolecular proton transfer (ESIPT), and twisted intramolecular charge transfer (TICT), can transform pyrene-based ACQ luminogens to AIE luminogens with excellent optical properties. Furthermore, prospective applications of pyrene-based AIEgens are discussed, as is the potential for designing new organic functional materials

Software for doing computations in graded Lie algebras

We introduce the Macaulay2 package GradedLieAlgebras for doing computations in graded Lie algebras presented by generators and relations.Comment: 5 page

Constructing high-order functional connectivity network based on central moment features for diagnosis of autism spectrum disorder

The sliding-window-based dynamic functional connectivity network (D-FCN) has been becoming an increasingly useful tool for understanding the changes of brain connectivity patterns and the association of neurological diseases with these dynamic variations. However, conventional D-FCN is essentially low-order network, which only reflects the pairwise interaction pattern between brain regions and thus overlooking the high-order interactions among multiple brain regions. In addition, D-FCN is innate with temporal sensitivity issue, i.e., D-FCN is sensitive to the chronological order of its subnetworks. To deal with the above issues, we propose a novel high-order functional connectivity network framework based on the central moment feature of D-FCN. Specifically, we firstly adopt a central moment approach to extract multiple central moment feature matrices from D-FCN. Furthermore, we regard the matrices as the profiles to build multiple high-order functional connectivity networks which further capture the higher level and more complex interaction relationships among multiple brain regions. Finally, we use the voting strategy to combine the high-order networks with D-FCN for autism spectrum disorder diagnosis. Experimental results show that the combination of multiple functional connectivity networks achieves accuracy of 88.06%, and the best single network achieves accuracy of 79.5%

Quantitative and functional post-translational modification proteomics reveals that TREPH1 plays a role in plant thigmomorphogenesis

Plants can sense both intracellular and extracellular mechanical forces and can respond through morphological changes. The signaling components responsible for mechanotransduction of the touch response are largely unknown. Here, we performed a high-throughput SILIA (stable isotope labeling in Arabidopsis)-based quantitative phosphoproteomics analysis to profile changes in protein phosphorylation resulting from 40 seconds of force stimulation in Arabidopsis thaliana. Of the 24 touch-responsive phosphopeptides identified, many were derived from kinases, phosphatases, cytoskeleton proteins, membrane proteins and ion transporters. TOUCH-REGULATED PHOSPHOPROTEIN1 (TREPH1) and MAP KINASE KINASE 2 (MKK2) and/or MKK1 became rapidly phosphorylated in touch-stimulated plants. Both TREPH1 and MKK2 are required for touch-induced delayed flowering, a major component of thigmomorphogenesis. The treph1-1 and mkk2 mutants also exhibited defects in touch-inducible gene expression. A non-phosphorylatable site-specific isoform of TREPH1 (S625A) failed to restore touch-induced flowering delay of treph1-1, indicating the necessity of S625 for TREPH1 function and providing evidence consistent with the possible functional relevance of the touch-regulated TREPH1 phosphorylation. Bioinformatic analysis and biochemical subcellular fractionation of TREPH1 protein indicate that it is a soluble protein. Altogether, these findings identify new protein players in Arabidopsis thigmomorphogenesis regulation, suggesting that protein phosphorylation may play a critical role in plant force responses

Methods for Extremely Sparse-Angle Proton Tomography

Proton radiography is a widely-fielded diagnostic used to measure magnetic structures in plasma. The deflection of protons with multi-MeV kinetic energy by the magnetic fields is used to infer their path-integrated field strength. Here, the use of tomographic methods is proposed for the first time to lift the degeneracy inherent in these path-integrated measurements, allowing full reconstruction of spatially resolved magnetic field structures in three dimensions. Two techniques are proposed which improve the performance of tomographic reconstruction algorithms in cases with severely limited numbers of available probe beams, as is the case in laser-plasma interaction experiments where the probes are created by short, high-power laser pulse irradiation of secondary foil targets. The methods are equally applicable to optical probes such as shadowgraphy and interferometry [M. Kasim et al. Phys. Rev. E 95, 023306 (2017)], thereby providing a disruptive new approach to three dimensional imaging across the physical sciences and engineering disciplines.Comment: 11 pages, 6 figures, companion article to arXiv:2103.1126

Retrieve Anyone: A General-purpose Person Re-identification Task with Instructions

Human intelligence can retrieve any person according to both visual and language descriptions. However, the current computer vision community studies specific person re-identification (ReID) tasks in different scenarios separately, which limits the applications in the real world. This paper strives to resolve this problem by proposing a new instruct-ReID task that requires the model to retrieve images according to the given image or language instructions.Our instruct-ReID is a more general ReID setting, where existing ReID tasks can be viewed as special cases by designing different instructions. We propose a large-scale OmniReID benchmark and an adaptive triplet loss as a baseline method to facilitate research in this new setting. Experimental results show that the baseline model trained on our OmniReID benchmark can improve +0.5%, +3.3% mAP on Market1501 and CUHK03 for traditional ReID, +2.1%, +0.2%, +15.3% mAP on PRCC, VC-Clothes, LTCC for clothes-changing ReID, +12.5% mAP on COCAS+ real2 for clothestemplate based clothes-changing ReID when using only RGB images, +25.5% mAP on COCAS+ real2 for our newly defined language-instructed ReID. The dataset, model, and code will be available at https://github.com/hwz-zju/Instruct-ReID

HumanBench: Towards General Human-centric Perception with Projector Assisted Pretraining

Human-centric perceptions include a variety of vision tasks, which have widespread industrial applications, including surveillance, autonomous driving, and the metaverse. It is desirable to have a general pretrain model for versatile human-centric downstream tasks. This paper forges ahead along this path from the aspects of both benchmark and pretraining methods. Specifically, we propose a \textbf{HumanBench} based on existing datasets to comprehensively evaluate on the common ground the generalization abilities of different pretraining methods on 19 datasets from 6 diverse downstream tasks, including person ReID, pose estimation, human parsing, pedestrian attribute recognition, pedestrian detection, and crowd counting. To learn both coarse-grained and fine-grained knowledge in human bodies, we further propose a \textbf{P}rojector \textbf{A}ssis\textbf{T}ed \textbf{H}ierarchical pretraining method (\textbf{PATH}) to learn diverse knowledge at different granularity levels. Comprehensive evaluations on HumanBench show that our PATH achieves new state-of-the-art results on 17 downstream datasets and on-par results on the other 2 datasets. The code will be publicly at \href{https://github.com/OpenGVLab/HumanBench}{https://github.com/OpenGVLab/HumanBench}.Comment: Accepted to CVPR202