scholarly journals System inference for the spatio-temporal evolution of infectious diseases: Michigan in the time of COVID-19

2020 ◽  
Vol 66 (5) ◽  
pp. 1153-1176 ◽  
Author(s):  
Z. Wang ◽  
X. Zhang ◽  
G. H. Teichert ◽  
M. Carrasco-Teja ◽  
K. Garikipati
Keyword(s):  
Infectious Diseases ◽  
Temporal Evolution ◽  
Spatio Temporal

scholarly journals Correction to: System inference for the spatio-temporal evolution of infectious diseases: Michigan in the time of COVID-19

2020 ◽  
Vol 66 (5) ◽  
pp. 1177-1177 ◽  
Author(s):  
Z. Wang ◽  
X. Zhang ◽  
G. H. Teichert ◽  
M. Carrasco-Teja ◽  
K. Garikipati
Keyword(s):  
Infectious Diseases ◽  
Temporal Evolution ◽  
Spatio Temporal

Spatio-temporal evolution and dynamic origin of Jurassic-Cretaceous magmatism in the South China Block

2021 ◽  
Vol 217 ◽  
pp. 103605
Author(s):  
Xianzhi Cao ◽  
Nicolas Flament ◽  
Sanzhong Li ◽  
R. Dietmar Müller
Keyword(s):  
South China ◽  
Temporal Evolution ◽  
South China Block ◽  
The South ◽  
Spatio Temporal ◽  
Cretaceous Magmatism

scholarly journals Spatio-temporal evolution and influencing mechanism of the COVID-19 epidemic in Shandong province, China

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jinlong Shi ◽  
Xing Gao ◽  
Shuyan Xue ◽  
Fengqing Li ◽  
Qifan Nie ◽  
...  
Keyword(s):  
Prevention And Control ◽  
Temporal Evolution ◽  
Geographical Location ◽  
Shandong Province ◽  
Control Measures ◽  
Middle Aged ◽  
Health Crisis ◽  
Aged People ◽  
Spatio Temporal ◽  
And Control

AbstractThe novel coronavirus pneumonia (COVID-19) outbreak that emerged in late 2019 has posed a severe threat to human health and social and economic development, and thus has become a major public health crisis affecting the world. The spread of COVID-19 in population and regions is a typical geographical process, which is worth discussing from the geographical perspective. This paper focuses on Shandong province, which has a high incidence, though the first Chinese confirmed case was reported from Hubei province. Based on the data of reported confirmed cases and the detailed information of cases collected manually, we used text analysis, mathematical statistics and spatial analysis to reveal the demographic characteristics of confirmed cases and the spatio-temporal evolution process of the epidemic, and to explore the comprehensive mechanism of epidemic evolution and prevention and control. The results show that: (1) the incidence rate of COVID-19 in Shandong is 0.76/100,000. The majority of confirmed cases are old and middle-aged people who are infected by the intra-province diffusion, followed by young and middle-aged people who are infected outside the province. (2) Up to February 5, the number of daily confirmed cases shows a trend of “rapid increase before slowing down”, among which, the changes of age and gender are closely related to population migration, epidemic characteristics and intervention measures. (3) Affected by the regional economy and population, the spatial distribution of the confirmed cases is obviously unbalanced, with the cluster pattern of “high–low” and “low–high”. (4) The evolution of the migration pattern, affected by the geographical location of Wuhan and Chinese traditional culture, is dominated by “cross-provincial” and “intra-provincial” direct flow, and generally shows the trend of “southwest → northeast”. Finally, combined with the targeted countermeasures of “source-flow-sink”, the comprehensive mechanism of COVID-19 epidemic evolution and prevention and control in Shandong is revealed. External and internal prevention and control measures are also figured out.

scholarly journals Adjoint-based direct data assimilation of GNSS time series for optimizing frictional parameters and predicting postseismic deformation following the 2003 Tokachi-oki earthquake

2020 ◽  
Vol 72 (1) ◽  
Author(s):  
Masayuki Kano ◽  
Shin’ichi Miyazaki ◽  
Yoichi Ishikawa ◽  
Kazuro Hirahara
Keyword(s):  
Time Series ◽  
Data Assimilation ◽  
Evaluation Method ◽  
Temporal Evolution ◽  
Recovery Process ◽  
Postseismic Deformation ◽  
Coseismic Slip ◽  
Megathrust Earthquakes ◽  
Spatio Temporal ◽  
Gnss Time Series

Abstract Postseismic Global Navigation Satellite System (GNSS) time series followed by megathrust earthquakes can be interpreted as a result of afterslip on the plate interface, especially in its early phase. Afterslip is a stress release process accumulated by adjacent coseismic slip and can be considered a recovery process for future events during earthquake cycles. Spatio-temporal evolution of afterslip often triggers subsequent earthquakes through stress perturbation. Therefore, it is important to quantitatively capture the spatio-temporal evolution of afterslip and related postseismic crustal deformation and to predict their future evolution with a physics-based simulation. We developed an adjoint data assimilation method, which directly assimilates GNSS time series into a physics-based model to optimize the frictional parameters that control the slip behavior on the fault. The developed method was validated with synthetic data. Through the optimization of frictional parameters, the spatial distributions of afterslip could roughly (but not in detail) be reproduced if the observation noise was included. The optimization of frictional parameters reproduced not only the postseismic displacements used for the assimilation, but also improved the prediction skill of the following time series. Then, we applied the developed method to the observed GNSS time series for the first 15 days following the 2003 Tokachi-oki earthquake. The frictional parameters in the afterslip regions were optimized to A–B ~ O(10 kPa), A ~ O(100 kPa), and L ~ O(10 mm). A large afterslip is inferred on the shallower side of the coseismic slip area. The optimized frictional parameters quantitatively predicted the postseismic GNSS time series for the following 15 days. These characteristics can also be detected if the simulation variables can be simultaneously optimized. The developed data assimilation method, which can be directly applied to GNSS time series following megathrust earthquakes, is an effective quantitative evaluation method for assessing risks of subsequent earthquakes and for monitoring the recovery process of megathrust earthquakes.

scholarly journals Glimpse: A Gaze-Based Measure of Temporal Salience

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3099
Author(s):  
V. Javier Traver ◽  
Judith Zorío ◽  
Luis A. Leiva
Keyword(s):  
Visual Attention ◽  
Computational Models ◽  
Temporal Evolution ◽  
Temporal Consistency ◽  
Visual Salience ◽  
Temporal Dimension ◽  
Spatial Perspective ◽  
Spatio Temporal ◽  
Scoring Algorithms ◽  
Over Time

Temporal salience considers how visual attention varies over time. Although visual salience has been widely studied from a spatial perspective, its temporal dimension has been mostly ignored, despite arguably being of utmost importance to understand the temporal evolution of attention on dynamic contents. To address this gap, we proposed Glimpse, a novel measure to compute temporal salience based on the observer-spatio-temporal consistency of raw gaze data. The measure is conceptually simple, training free, and provides a semantically meaningful quantification of visual attention over time. As an extension, we explored scoring algorithms to estimate temporal salience from spatial salience maps predicted with existing computational models. However, these approaches generally fall short when compared with our proposed gaze-based measure. Glimpse could serve as the basis for several downstream tasks such as segmentation or summarization of videos. Glimpse’s software and data are publicly available.

A geographical analysis of the first wave of Covid-19 with reference to highland and lowland regions of India

2021 ◽  
Vol 67 (3) ◽  
pp. 263-281
Author(s):  
Bindhy Wasini Pandey ◽  
◽  
Yuvraj Singh ◽  
Usha Rani ◽  
Roosen Kumar ◽  
...  
Keyword(s):  
Infectious Diseases ◽  
Temporal Pattern ◽  
Regional Disparity ◽  
Healthcare Facilities ◽  
Indian Himalayan Region ◽  
Pollution Levels ◽  
Extensive Coverage ◽  
The World ◽  
Spatio Temporal

The issue of health has become a major concern in recent years as a result of extensive coverage of media reporting outbreaks of diseases and the spread of deadly infectious diseases around the world. There has been a growing concern over the accessibility and affordability of healthcare facilities. The spread of the ongoing pandemic COVID-19 has been felt all over the world. However, the rate of infection varies across certain regions of the world. There exists intra-regional disparity as well. Recent research shows that there are latitudinal and altitudinal variations in the spread of the COVID-19. This paper studies variation of infection COVID-19 across the highlands of the Indian Himalayan Region (IHR) and the lowland areas in India. The paper also examines the role of geographical spaces in the spread of coronavirus in these regions. The study indicates that place-based effects (altitude, temperature, pollution levels, etc.) on health can be seen in a variety of ways; therefore, locational issues are very important for addressing health questions. The paper also analyses the Spatio-temporal pattern of the COVID-19 pandemic in the study area to understand the nature of the disease in different locations.

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