scholarly journals Autocatalytic Model for Covid-19 Progression in a Country

2020 ◽  
Author(s):  
Anatoly Chernyshev
Keyword(s):  
Population Density ◽  
Ambient Temperature ◽  
Computational Model ◽  
Moving Average ◽  
Kinetic Constants ◽  
Published Data ◽  
Policy Makers ◽  
Linear Fitting ◽  
Autocatalytic Model ◽  
Containment Measures

AbstractHerewith we present a computational model for the forecasting of cumulative diagnosed cases of Covid-19 pneumonia within a country. The only explicit parameter of the model is the population density. The implicit parameter is a moving average ambient temperature, currently integrated into the kinetic constants. Other finer details pertaining to the mechanism of the pathogen SARS-CoV-2 spread within a given region are implicitly manifested in the exponent parameters derived from the non-linear fitting of the published data on Covid-19 occurrence. The performance of the model is demonstrated on a few selected countries, and on the Diamond Princess cruising ship outbreak. The model might be used as an aiding tool for the policy makers regarding the decisions on the containment measures and quarantine regime required.

scholarly journals Biomimetic Urban and Architectural Design: Illustrating and Leveraging Relationships between Ecosystem Services

Biomimetics ◽  
2020 ◽  
Vol 6 (1) ◽  
pp. 2
Author(s):  
Maibritt Pedersen Zari
Keyword(s):  
Ecosystem Services ◽  
Urban Design ◽  
Urban Areas ◽  
Architectural Design ◽  
Urban Environments ◽  
Published Data ◽  
Ecological Knowledge ◽  
Policy Makers ◽  
Spatial Design ◽  
Key Barrier

Redesigning and retrofitting cities so they become complex systems that create ecological and cultural–societal health through the provision of ecosystem services is of critical importance. Although a handful of methodologies and frameworks for considering how to design urban environments so that they provide ecosystem services have been proposed, their use is not widespread. A key barrier to their development has been identified as a lack of ecological knowledge about relationships between ecosystem services, which is then translated into the field of spatial design. In response, this paper examines recently published data concerning synergetic and conflicting relationships between ecosystem services from the field of ecology and then synthesises, translates, and illustrates this information for an architectural and urban design context. The intention of the diagrams created in this research is to enable designers and policy makers to make better decisions about how to effectively increase the provision of various ecosystem services in urban areas without causing unanticipated degradation in others. The results indicate that although targets of ecosystem services can be both spatially and metrically quantifiable while working across different scales, their effectiveness can be increased if relationships between them are considered during design phases of project development.

scholarly journals Simulation of P2X-mediated calcium signaling in microglia

2018 ◽  
Author(s):  
Ben Chun ◽  
Bradley D. Stewart ◽  
Darin Vaughan ◽  
Adam D. Bachstetter ◽  
Peter M. Kekenes-Huskey
Keyword(s):  
Computational Model ◽  
Purinergic Receptor ◽  
Receptor Activation ◽  
Quantitative Model ◽  
Published Data ◽  
Transcriptional Responses ◽  
Extracellular Adenosine ◽  
Wide Range ◽  
Intracellular Ca

AbstractMicroglia function is orchestrated through highly-coupled signaling pathways that depend on calcium (Ca2+). In response to extracellular adenosine triphosphate (ATP), transient increases in intracellular Ca2+ driven through the activation of purinergic receptors, P2X and P2Y, are sufficient to promote cytokine synthesis and potentially their release. While steps comprising the pathways bridging purinergic receptor activation with transcriptional responses have been probed in great detail, a quantitative model for how these steps collectively control cytokine production has not been established. Here we developed a minimal computational model that quantitatively links extracellular stimulation of two prominent ionotropic puriner-gic receptors, P2X4 and P2X7, with the graded production of a gene product, namely the tumor necrosis factor α (TNFα) cytokine. In addition to Ca2+ handling mechanisms common to eukaryotic cells, our model includes microglia-specific processes including ATP-dependent P2X4 and P2X7 activation, activation of NFAT transcription factors, and TNFα production. Parameters for this model were optimized to reproduce published data for these processes, where available. With this model, we determined the propensity for TNFα production in microglia, subject to a wide range of ATP exposure amplitudes, frequencies and durations that the cells could encounter in vivo. Furthermore, we have investigated the extent to which modulation of the signal transduction pathways influence TNFα production. Our key findings are that TNFα production via P2X4 is maximized at low ATP when subject to high frequency ATP stimulation, whereas P2X7 contributes most significantly at millimolar ATPranges. Given that Ca2+ homeostasis in microglia is profoundly important to its function, this computational model provides a quantitative framework to explore hypotheses pertaining to microglial physiology.

scholarly journals Regional quality of living in Europe

REGION ◽  
2015 ◽  
Vol 2 (2) ◽  
pp. 1 ◽  
Author(s):  
Piet Lagas ◽  
Frank Van Dongen ◽  
Frank Van Rijn ◽  
Hans Visser
Keyword(s):  
Population Density ◽  
Capital City ◽  
Gdp Per Capita ◽  
European Regions ◽  
Policy Makers ◽  
The North ◽  
City Regions ◽  
Quality Of Living ◽  
Per Capita

This article sets out the conceptual framework and results of Regional Quality of Living indicators that were developed in order to benchmark European NUTS2 regions. Nine non-business-related indicators are constructed to support the goal of policy makers to improve the attractiveness of regions and cities for people or companies to settle in, and by doing so create economic growth. Each of the constructed indicators represents a pillar of the Quality of Living. The highest indicator scores are found for regions within Switzerland, Sweden, Norway and the Netherlands. Some countries show a wide divergence between regional scores. The southern regions of Italy and Spain, for example, have significantly lower scores than those in the north. In addition, capital city regions have better RQI scores. A positive correlation was found between the average RQI scores and both GDP per capita and weighted population density. Compared to GDP per capita, weighted population density has a modest influence on the RQI score. The European regions are divided into 11 clusters, based upon GDP per capita and weighted population density in order to benchmark a region with its peers.

scholarly journals Growth, instability and forecast of marine products export from India

2016 ◽  
Vol 63 (4) ◽  
Author(s):  
Apu Das ◽  
Nalini Ranjan Kumar ◽  
Prathvi Rani
Keyword(s):  
Moving Average ◽  
Export Performance ◽  
Arima Model ◽  
South East Asia ◽  
Arima Models ◽  
Policy Makers ◽  
Increasing Trend ◽  
Marine Products ◽  
Auto Regressive ◽  
Instability Indices

This paper analysed growth and instability in export of marine products from India with an attempt to forecast the total export quantity of marine products from the country. The compound growth rates and instability indices of marine products export from India were estimated for major importing countries viz., Japan, USA, European Union, South-east Asia and Middle East; as more than 80% of the marine products export from India destines to these markets. The study revealed high compound growth rate and low instability in case of selected countries. The study also revealed that India’s marine products export concentrated mainly to those countries, which were falling in less desirable or least desirable category which has affected export performance of the country. Forecast of India’s marine products export was done by fitting univariate Auto Regressive Integrated Moving Average (ARIMA) models. ARIMA (1, 1, 0) was found suitable for modelling marine products export from India. The results of ARIMA model indicated increasing trend in export of Indian marine products. This calls for serious attention by policy makers to identify competitive and stable market destinations for marine products export which could help in harnessing the potential of marine products export from India.

scholarly journals Integrated experimental-computational analysis of a liver-islet microphysiological system for human-centric diabetes research

2021 ◽  
Author(s):  
Belén Casas ◽  
Liisa Vilén ◽  
Sophie Bauer ◽  
Kajsa Kanebratt ◽  
Charlotte Wennberg Huldt ◽  
...  
Keyword(s):  
Glucose Metabolism ◽  
Computational Model ◽  
In Silico ◽  
Experimental Results ◽  
Published Data ◽  
Diabetes Research ◽  
Glucose Response ◽  
High Blood Glucose

Microphysiological systems (MPS) are powerful tools for emulating human physiology and replicating disease progression in vitro. MPS could be better predictors of human outcome than current animal models, but mechanistic interpretation and in vivo extrapolation of the experimental results remain significant challenges. Here, we address these challenges using an integrated experimental-computational approach. This approach allows for in silico representation and predictions of glucose metabolism in a previously reported MPS with two organ compartments (liver and pancreas) connected in a closed loop with circulating medium. We developed a computational model describing glucose metabolism over 15 days of culture in the MPS. The model was calibrated on an experiment-specific basis using data from seven experiments, where single-liver or liver-islet cultures were exposed to both normal and hyperglycemic conditions resembling high blood glucose levels in diabetes. The calibrated models reproduced the fast (i.e. hourly) variations in glucose and insulin observed in the MPS experiments, as well as the long-term (i.e. over weeks) decline in both glucose tolerance and insulin secretion. We also investigated the behavior of the system under hypoglycemia by simulating this condition in silico, and the model could correctly predict the glucose and insulin responses measured in new MPS experiments. Last, we used the computational model to translate the experimental results to humans, showing good agreement with published data of the glucose response to a meal in healthy subjects. The integrated experimental-computational framework opens new avenues for future investigations toward disease mechanisms and the development of new therapies for metabolic disorders.

Spatial Model Approach for Deforestation

2013 ◽  
pp. 1901-1912
Author(s):  
Lilik B. Prasetyo ◽  
Chandra Irawadi Wijaya ◽  
Yudi Setiawan
Keyword(s):  
Population Density ◽  
Rural Areas ◽  
Forest Cover ◽  
Positive Impact ◽  
Forest Loss ◽  
Road Density ◽  
Policy Makers ◽  
Explanatory Variables ◽  
The Government ◽  
Negative Impacts

Java is very densely populated since it is inhabited by more than 60% of the total population of Indonesia. Based on data from the Ministry of Forestry, forest loss between 2000-2005 in Java was about 800,000 hectares. Regardless of the debate on whether the different methodologies of forest inventory applied in 2005 have resulted in an underestimation of the figure of forest loss or not, the decrease of forest cover in Java is obvious and needs immediate response. Spatial modeling of the deforestation will assist the policy makers in understanding this process and in taking it into consideration, when decisions are made on the issue. Moreover, the results can be used as data input to solve environmental problems resulting from deforestation. The authors of this chapter modeled the deforestation in Java by using logistic regression. Percentage of deforested area was considered as the response variable, whilst biophysical and socioeconomic factors, that explain the current spatial pattern in deforestation, were assigned as explanatory variables. Furthermore, the authors predicted the future deforestation process, and then, for the case of Java, it was validated with the actual deforestation derived from MODIS satellite imageries from 2000 to 2008. Results of the study showed that the impacts of population density, road density, and slope are significant. Population density and road density have negative impacts on deforestation, while slope has positive impact. Deforestation on Java Island tends to occur in remote areas with limited access, low density population and relatively steep slopes. Implication of the model is that the government should pay more attention to remote rural areas and develop good access to accelerate and create alternative non agricultural jobs in order to reduce pressure on the forest.

Spatial Model Approach for Deforestation

2011 ◽  
pp. 376-387 ◽  
Author(s):  
Lilik B. Prasetyo ◽  
Chandra Irawadi Wijaya ◽  
Yudi Setiawan
Keyword(s):  
Population Density ◽  
Rural Areas ◽  
Forest Cover ◽  
Positive Impact ◽  
Forest Loss ◽  
Road Density ◽  
Policy Makers ◽  
Explanatory Variables ◽  
The Government ◽  
Negative Impacts

Java is very densely populated since it is inhabited by more than 60% of the total population of Indonesia. Based on data from the Ministry of Forestry, forest loss between 2000-2005 in Java was about 800,000 hectares. Regardless of the debate on whether the different methodologies of forest inventory applied in 2005 have resulted in an underestimation of the figure of forest loss or not, the decrease of forest cover in Java is obvious and needs immediate response. Spatial modeling of the deforestation will assist the policy makers in understanding this process and in taking it into consideration, when decisions are made on the issue. Moreover, the results can be used as data input to solve environmental problems resulting from deforestation. The authors of this chapter modeled the deforestation in Java by using logistic regression. Percentage of deforested area was considered as the response variable, whilst biophysical and socioeconomic factors, that explain the current spatial pattern in deforestation, were assigned as explanatory variables. Furthermore, the authors predicted the future deforestation process, and then, for the case of Java, it was validated with the actual deforestation derived from MODIS satellite imageries from 2000 to 2008. Results of the study showed that the impacts of population density, road density, and slope are significant. Population density and road density have negative impacts on deforestation, while slope has positive impact. Deforestation on Java Island tends to occur in remote areas with limited access, low density population and relatively steep slopes. Implication of the model is that the government should pay more attention to remote rural areas and develop good access to accelerate and create alternative non agricultural jobs in order to reduce pressure on the forest.

scholarly journals Age-stratified discrete compartment model of the COVID-19 epidemic with application to Switzerland

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Fadoua Balabdaoui ◽  
Dirk Mohr
Keyword(s):  
Infected Individual ◽  
Compartment Model ◽  
Policy Makers ◽  
Modern Health Care ◽  
Containment Measures ◽  
To Come ◽  
Second Wave ◽  
Important Basis ◽  
Day By Day ◽  
Model Based Analysis

AbstractCompartmental models enable the analysis and prediction of an epidemic including the number of infected, hospitalized and deceased individuals in a population. They allow for computational case studies on non-pharmaceutical interventions thereby providing an important basis for policy makers. While research is ongoing on the transmission dynamics of the SARS-CoV-2 coronavirus, it is important to come up with epidemic models that can describe the main stages of the progression of the associated COVID-19 respiratory disease. We propose an age-stratified discrete compartment model as an alternative to differential equation based S-I-R type of models. The model captures the highly age-dependent progression of COVID-19 and is able to describe the day-by-day advancement of an infected individual in a modern health care system. The fully-identified model for Switzerland not only predicts the overall histories of the number of infected, hospitalized and deceased, but also the corresponding age-distributions. The model-based analysis of the outbreak reveals an average infection fatality ratio of 0.4% with a pronounced maximum of 9.5% for those aged ≥ 80 years. The predictions for different scenarios of relaxing the soft lockdown indicate a low risk of overloading the hospitals through a second wave of infections. However, there is a hidden risk of a significant increase in the total fatalities (by up to 200%) in case schools reopen with insufficient containment measures in place.

scholarly journals PEMODELAN JUMLAH TINDAK KRIMINALITAS DI PROVINSI JAWA TIMUR DENGAN ANALISIS REGRESI SPATIAL AUTOREGRESSIVE AND MOVING AVERAGE

2018 ◽  
Vol 7 (4) ◽  
pp. 346
Author(s):  
NI MADE LASTI LISPANI ◽  
I WAYAN SUMARJAYA ◽  
I KOMANG GDE SUKARSA
Keyword(s):  
Population Density ◽  
Regression Model ◽  
Average Length ◽  
Moving Average ◽  
Spatial Regression ◽  
Higher Order ◽  
Spatial Effect ◽  
Spatial Regression Model ◽  
Spatial Autoregressive ◽  
Total Average

One of spatial regression model is spatial autoregressive and moving average (SARMA) which assumes that there is a spatial effect on dependent variable and error. SARMA can analyze the spatial effect on the higher order. The purpose of this research is to estimate the model of the total crime in East Java along with factors that affect it. The results show that the model can describe total crime in East Java is SARMA(0,1). The factors that influence the total crime  are population density (), poverty total (), average length of education at every regency/city and error from the neigbors.

scholarly journals Stringent containment measures without complete city lockdown to achieve low incidence and mortality across two waves of COVID-19 in Hong Kong

2020 ◽  
Vol 5 (10) ◽  
pp. e003573
Author(s):  
Martin C S Wong ◽  
Rita W Y Ng ◽  
Ka Chun Chong ◽  
Christopher K C Lai ◽  
Junjie Huang ◽  
...  
Keyword(s):  
Hong Kong ◽  
Moving Average ◽  
Linear Regression Analysis ◽  
Leisure Activities ◽  
Multiple Linear Regression Analysis ◽  
Mitigation Strategies ◽  
Incidence And Mortality ◽  
Containment Measures ◽  
Epidemiological Characteristics ◽  
Second Wave

IntroductionAn international city, Hong Kong, in proximity to the first epicentre of COVID- 19, experienced two epidemic waves with different importation pressure. We compared the epidemiological features of patients with COVID-19 in the context of containment policies between the first and second waves.MethodsWe retrieved information on the first 1038 cases detected in Hong Kong (23 January to 25 April 2020) to analyse the epidemiological characteristics including age/gender-specific incidence, clustering, reproduction number (Rt) and containment delay; in relation to the containment measures implemented. Factors associated with containment delay were evaluated by multiple linear regression analysis with age, gender, epidemic wave and infection source as covariates. A time series of 5-day moving average was plotted to examine the changes across the two epidemic waves.ResultsThe incidence and mortality (135.5 and 0.5 per 1 000 000 population) was among the lowest in the world. Aggressive escalation of border control correlated with reductions in Rt from 1.35 to 0.57 and 0.92 to 0.18, and aversions of 450 and 1650 local infections during the first and second waves, respectively. Implementing COVID-19 tests for overseas returners correlated with an upsurge of asymptomatic case detection, and shortened containment delay in the second wave. Medium-sized cluster events in the first wave were family gatherings, whereas those in the second wave were leisure activities among youngsters. Containment delay was associated with older age (adjusted OR (AOR)=1.01, 95% CI 1.00 to 1.02, p=0.040), male gender (AOR=1.41, 95% CI 1.02 to 1.96, p=0.039) and local cases (AOR=11.18, 95% CI 7.43 to 16.83, p<0.001), and with significant improvement in the second wave compared with the first wave (average: 6.8 vs 3.7 days). A higher incidence rate was observed for males, raising possibility of gender predilection in susceptibility of developing symptoms.ConclusionPrompt and stringent all-round containment strategies represent successful measures in pandemic control. These findings could inform formulation and implementation of pandemic mitigation strategies.

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