scholarly journals The Spatio-Temporal Characteristics and Influencing Factors of Covid-19 Spread in Shenzhen, China—An Analysis Based on 417 Cases

Author(s):  
Shirui Liu ◽  
Yaochen Qin ◽  
Zhixiang Xie ◽  
Jingfei Zhang

The global pandemic of COVID-19 has made it the focus of current attention. At present, the law of COVID-19 spread in cities is not clear. Cities have long been difficult areas for epidemic prevention and control because of the high population density, high mobility of people, and high frequency of contacts. This paper analyzed case information for 417 patients with COVID-19 in Shenzhen, China. The nearest neighbor index method, kernel density method, and the standard deviation ellipse method were used to analyze the spatio-temporal characteristics of the COVID-19 spread in Shenzhen. The factors influencing that spread were then explored using the multiple linear regression method. The results show that: (1) The development of COVID-19 epidemic situation in Shenzhen occurred in three stages. The patients showed significant hysteresis from the onset of symptoms to hospitalization and then to diagnosis. Prior to 27 January, there was a relatively long time interval between the onset of symptoms and hospitalization for COVID-19; the interval decreased thereafter. (2) The epidemic site (the place where the patient stays during the onset of the disease) showed an agglomeration in space. The degree of agglomeration constantly increased across the three time nodes of 31 January, 14 February, and 22 February. The epidemic sites formed a “core area” in terms of spatial distribution and spread along the “northwest–southeast” direction of the city. (3) Economic and social factors significantly impacted the spread of COVID-19, while environmental factors have not played a significant role.

1981 ◽  
Vol 20 (03) ◽  
pp. 169-173
Author(s):  
J. Wagner ◽  
G. Pfurtscheixer

The shape, latency and amplitude of changes in electrical brain activity related to a stimulus (Evoked Potential) depend both on the stimulus parameters and on the background EEG at the time of stimulation. An adaptive, learnable stimulation system is introduced, whereby the subject is stimulated (e.g. with light), whenever the EEG power is subthreshold and minimal. Additionally, the system is conceived in such a way that a certain number of stimuli could be given within a particular time interval. Related to this time criterion, the threshold specific for each subject is calculated at the beginning of the experiment (preprocessing) and adapted to the EEG power during the processing mode because of long-time fluctuations and trends in the EEG. The process of adaptation is directed by a table which contains the necessary correction numbers for the threshold. Experiences of the stimulation system are reflected in an automatic correction of this table. Because the corrected and improved table is stored after each experiment and is used as the starting table for the next experiment, the system >learns<. The system introduced here can be used both for evoked response studies and for alpha-feedback experiments.


2021 ◽  
Vol 24 (3) ◽  
pp. 5-8
Author(s):  
Kai Geissdoerfer ◽  
Mikołaj Chwalisz ◽  
Marco Zimmerling

Collaboration of batteryless devices is essential to their success in replacing traditional battery-based systems. Without significant energy storage, spatio-temporal fluctuations of ambient energy availability become critical for the correct functioning of these systems. We present Shepherd, a testbed for the batteryless Internet of Things (IoT) that can record and reproduce spatio-temporal characteristics of real energy environments to obtain insights into the challenges and opportunities of operating groups of batteryless sensor nodes.


Fluids ◽  
2018 ◽  
Vol 3 (3) ◽  
pp. 63 ◽  
Author(s):  
Thomas Meunier ◽  
Claire Ménesguen ◽  
Xavier Carton ◽  
Sylvie Le Gentil ◽  
Richard Schopp

The stability properties of a vortex lens are studied in the quasi geostrophic (QG) framework using the generalized stability theory. Optimal perturbations are obtained using a tangent linear QG model and its adjoint. Their fine-scale spatial structures are studied in details. Growth rates of optimal perturbations are shown to be extremely sensitive to the time interval of optimization: The most unstable perturbations are found for time intervals of about 3 days, while the growth rates continuously decrease towards the most unstable normal mode, which is reached after about 170 days. The horizontal structure of the optimal perturbations consists of an intense counter-shear spiralling. It is also extremely sensitive to time interval: for short time intervals, the optimal perturbations are made of a broad spectrum of high azimuthal wave numbers. As the time interval increases, only low azimuthal wave numbers are found. The vertical structures of optimal perturbations exhibit strong layering associated with high vertical wave numbers whatever the time interval. However, the latter parameter plays an important role in the width of the vertical spectrum of the perturbation: short time interval perturbations have a narrow vertical spectrum while long time interval perturbations show a broad range of vertical scales. Optimal perturbations were set as initial perturbations of the vortex lens in a fully non linear QG model. It appears that for short time intervals, the perturbations decay after an initial transient growth, while for longer time intervals, the optimal perturbation keeps on growing, quickly leading to a non-linear regime or exciting lower azimuthal modes, consistent with normal mode instability. Very long time intervals simply behave like the most unstable normal mode. The possible impact of optimal perturbations on layering is also discussed.


2021 ◽  
pp. 100058
Author(s):  
Theos Dieudonne Benimana ◽  
Naae Lee ◽  
Seungpil Jung ◽  
Woojoo Lee ◽  
Seung-sik Hwang

2021 ◽  
Vol 13 (8) ◽  
pp. 4203
Author(s):  
Bin Du ◽  
Ying Wang ◽  
Jiaxin He ◽  
Wai Li ◽  
Xiaohong Chen

Based on the fundamental concept of sustainable development, this study empirically analyzes the spatio-temporal characteristics, formation mechanisms and obstacle factors of the urban-rural integration of shrinking cities in China, from 2008 to 2018. The conclusions are as follows: the overall level of the urban-rural integration of shrinking cities in China is low; the internal differences of urban-rural integration are also small, and the changes are slow. Next, the space difference is high in the east and low in the west, high in the south and low in the north. Moreover, differences exist among different levels of urban agglomerations. Urban economic efficiency, urban resources and environment, urban social equity and rural economic efficiency are the main factors affecting the urban-rural integration of shrinking cities in China. Urban and rural economic efficiency are the two most prominent shortcomings that restrict the urban-rural integration of shrinking cities. The spatial resistance mode of each city is more than the two-system resistance; the main resistance of shrinking cities with a higher level of urban-rural integration also comes from the non-economic field. This study expands the research scope that up till now has ignored the discussion of urban-rural issues in the research of shrinking cities at home and abroad, and provides practical guidance for the sustainable development of shrinking cities in China.


2003 ◽  
Vol 46 (2) ◽  
pp. 291-301 ◽  
Author(s):  
Haikun JIANG ◽  
Shengli MA ◽  
Liu ZHANG ◽  
Wenhai CAO ◽  
Haifeng HOU

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