Graph Neural Network for spatiotemporal data: methods and applications

In the era of big data, there has been a surge in the availability of data containing rich spatial and temporal information, offering valuable insights into dynamic systems and processes for applications such as weather forecasting, natural disaster management, intelligent transport systems, and precision agriculture. Graph neural networks (GNNs) have emerged as a powerful tool for modeling and understanding data with dependencies to each other such as spatial and temporal dependencies. There is a large amount of existing work that focuses on addressing the complex spatial and temporal dependencies in spatiotemporal data using GNNs. However, the strong interdisciplinary nature of spatiotemporal data has created numerous GNNs variants specifically designed for distinct application domains. Although the techniques are generally applicable across various domains, cross-referencing these methods remains essential yet challenging due to the absence of a comprehensive literature review on GNNs for spatiotemporal data. This article aims to provide a systematic and comprehensive overview of the technologies and applications of GNNs in the spatiotemporal domain. First, the ways of constructing graphs from spatiotemporal data are summarized to help domain experts understand how to generate graphs from various types of spatiotemporal data. Then, a systematic categorization and summary of existing spatiotemporal GNNs are presented to enable domain experts to identify suitable techniques and to support model developers in advancing their research. Moreover, a comprehensive overview of significant applications in the spatiotemporal domain is offered to introduce a broader range of applications to model developers and domain experts, assisting them in exploring potential research topics and enhancing the impact of their work. Finally, open challenges and future directions are discussed

CpG Oligodeoxynucleotides Enhance the Efficacy of Adoptive Cell Transfer Using Tumor Infiltrating Lymphocytes by Modifying the Th1 Polarization and Local Infiltration of Th17 Cells

Adoptive cell transfer immunotherapy using tumor infiltrating lymphocytes (TILs) was an important therapeutic strategy against tumors. But the efficacy remains limited and development of new strategies is urgent. Recent evidence suggested that CpG-ODNs might be a potent candidate for tumor immunotherapy. Here we firstly reported that CpG-ODNs could significantly enhance the antitumor efficacy of adoptively transferred TILs in vivo accompanied by enhanced activity capacity and proliferation of CD8+ T cells and CD8+ T cells, as well as a Th1 polarization immune response. Most importantly, we found that CpG-ODNs could significantly elevate the infiltration of Th17 cells in tumor mass, which contributed to anti-tumor efficacy of TILs in vivo. Our findings suggested that CpG ODNs could enhance the anti-tumor efficacy of adoptively transferred TILs through modifying Th1 polarization and local infiltration of Th17 cells, which might provide a clue for developing a new strategy for ACT based on TILs

Mesangial cell: A hub in lupus nephritis

Lupus nephritis (LN) is a severe renal disease caused by the massive deposition of the immune complexes (ICs) in renal tissue, acting as one of the significant organ manifestations of systemic lupus erythematosus (SLE) and a substantial cause of death in clinical patients. As mesangium is one of the primary sites for IC deposition, mesangial cells (MCs) constantly undergo severe damage, resulting in excessive proliferation and increased extracellular matrix (ECM) production. In addition to playing a role in organizational structure, MCs are closely related to in situ immunomodulation by phagocytosis, antigen-presenting function, and inflammatory effects, aberrantly participating in the tissue-resident immune responses and leading to immune-mediated renal lesions. Notably, such renal-resident immune responses drive a second wave of MC damage, accelerating the development of LN. This review summarized the damage mechanisms and the in situ immune regulation of MCs in LN, facilitating the current drug research for exploring clinical treatment strategies

Formalization of Function Matrix Theory in HOL

Function matrices, in which elements are functions rather than numbers, are widely used in model analysis of dynamic systems such as control systems and robotics. In safety-critical applications, the dynamic systems are required to be analyzed formally and accurately to ensure their correctness and safeness. Higher-order logic (HOL) theorem proving is a promise technique to match the requirement. This paper proposes a higher-order logic formalization of the function vector and the function matrix theories using the HOL theorem prover, including data types, operations, and their properties, and further presents formalization of the differential and integral of function vectors and function matrices. The formalization is implemented as a library in the HOL system. A case study, a formal analysis of differential of quadratic functions, is presented to show the usefulness of the proposed formalization

Operational characteristics of mixed traffic flow under bi-directional environment using cellular automaton

Mixed traffic flow composed of autos and non-autos widely exists in developing countries and areas. To investigate the operational characteristics of the mixed traffic flow consisting of vehicles in different types (large vehicles, cas, and bicycles), we develop a cellular automaton model to replicate the travel behaviors on a bi-directional road segment with respect to the physical and mechanic ftures of différent vehicle types. By implementing the eesential parameters calibrated through the field data collection, a numerical study is carried out considering the variation in volume, density, and velocity with different compositions of mixed traffic flows. The primary findings include: the average velocity of traffic flow and total volume decrease 60% and 30% after incorporating 10% bicycles, respectively; the phenomenon of double-summit in terms of the total volume appears when the proportion of bicycle is beyond 60%; the maximal total volume starts to recover when the proportion of bicycle is higher than 10 %

The evolution of regional disparity and gravity center time-region shift for China's direct investment in Africa

This paper made quantitative analysis on the regional disparity of China's direct investment in Africa by means of Theil index which was used as a measurement for regional factor differences.Besides,it employed gravity center model to describe the time and region shift of China's direct investment in Africa,which were visualized with ArcGIS.Finally,it looked forward to the future trend of China's investment in Africa based on the research

Research on spatial structure of regional tourism resources——Taking Nanjing city as an example

The spatial structure of tourism resources can help to understand the spatial distribution characteristics of tourism resources,and then guide the tourism planning and improve the competitive advantage of tourism area.Based on the relevant data released by Jiangsu Provincial Tourism Bureau,taking advantage of the ArcGIS platform,the development and utilization of tourism resources and the problems in the spatial structure of tourism resources were analyzed by using the superiority index,Nearest Neighbor Index and Traffic Connectivity Index.The results show that:1) the spatial distribution of tourism resources in Nanjing is clustered;the distribution of the main urban area is relatively dense,and the resource level is higher;2) the spatial distribution of the traffic network between the tourist resources is in the middle and lower levels,and the traffic loops are poor and the accessibility is not high.The accessibility degree shows ‘center high,four weeks low’ and ‘east and west high,north and south low’.3)The resource of Nanjing tourism can be optimized by optimization of the transport network;by determining the core of tourism,clarifying the level of scenic spots;increasing the efforts of tourism development and developing tourism products in depth;integration of the tourism resources,construction of the clusters and zones of tourism resources;and other aspects

Acute Visual Impairment in a Patient with Parkinson’s Disease after Successful Bilateral Subthalamic Nucleus Deep Brain Stimulation with Low-Dose Levodopa: A Case Report

Background: Subthalamic nucleus deep brain stimulation (STN-DBS) is widely used for the treatment of primary motor symptoms in patients with Parkinson’s disease (PD). Further, recent evidence suggests that STN-DBS may relieve a few ophthalmic symptoms in PD, such as eye-blink rate and the flexibility of eye saccades. However, its exact effect on visual function remains unknown. Herein, we report the case of a patient with PD who underwent STN-DBS and experienced visual symptoms following levodopa reduction. Case presentation: A 63-year-old male patient with PD developed severe visual impairment after six months of high-frequency STN-DBS. His symptoms resolved after adjusting the levodopa dose prescribed to the patient. Conclusions: This case report suggests that DBS is beneficial in patients with PD in terms of eye-blink rate. However, the rapid reduction of medication after STN-DBS may lead to retinal atrophy and the shrinkage of vessel density in the ocular fundus. Thus, neurosurgeons should pay close attention to patients with visual symptoms when adjusting levodopa dosages