Melvinsun0359

We discuss these findings and the relationship between government action and residents' response.The distributions of bat species in Qatar have not previously been recorded. We conducted the first nation-wide survey of bats in Qatar. Based on sonogram analysis, we identified Asellia tridens, Otonycteris hemprichii, and Pipistrellus kuhlii. The most commonly recorded species was Asellia tridens, the only species recorded in the northern half of the country. Contrary to our prediction, the likelihood of recording bats was not higher in the northern half of the country where there are many irrigated farms. The distributions of the bat species may result from differences in human land use and disturbance, and from the distance to the main body of the Arabian Peninsula. A key habitat feature for Asellia tridens and Otonycteris hemprichii may be the presence of roosting sites in less disturbed sinkholes/caves, which are therefore crucial for bat conservation.While degraded trust and cohesion within a country are often shown to have large socio-economic impacts, they can also have dramatic consequences when compliance is required for collective survival. #link# We illustrate this point in the context of the COVID-19 crisis. Policy responses all over the world aim to reduce social interaction and limit contagion. Using data on human mobility and political trust at regional level in Europe, we examine whether the compliance to these containment policies depends on the level of trust in policy makers prior to the crisis. Using a double difference approach around the time of lockdown announcements, we find that high-trust regions decrease their mobility related to non-necessary activities significantly more than low-trust regions. We also exploit country and time variation in treatment using the daily strictness of national policies. The efficiency of policy stringency in terms of mobility reduction significantly increases with trust. The trust effect is nonlinear and increases with the degree of stringency. We assess how the impact of trust on mobility potentially translates in terms of mortality growth rate.Independent Component Analysis (ICA) offers an effective data-driven approach for blind source extraction encountered in many signal and image processing problems. Although many ICA methods have been developed, they have received relatively little attention in the statistics literature, especially in terms of rigorous theoretical investigation for statistical inference. The current paper aims at narrowing this gap and investigates the statistical sampling properties of the colorICA (cICA) method. The cICA incorporates the correlation structure within sources through parametric time series models in the frequency domain and outperforms several existing ICA alternatives numerically. We establish the consistency and asymptotic normality of the cICA estimates, which then enables statistical inference based on the estimates. These asymptotic properties are further validated using simulation studies.This paper evaluates the impact of COVID-19 media coverage in mitigating its spread in China during the early phase of the pandemic. We construct a provincial-level dataset on COVID-19 and link it with population mobility data, among other control variables, to estimate how media coverage mitigates the spread of COVID-19. Seemingly unrelated regressions are used to examine the simultaneous impact of media coverage on the number of new cases and close contacts. The results show that the effect of media coverage on COVID-19 transmission in China had an inverse-U curvature and was mediated by within- and across-province population mobility. find more indicate that COVID-19 media coverage in China was associated with a potential reduction of 394,000 cases and 1.4 million close contacts during January 19 and February 29, 2020. Our results also provide strong support for the use of contact tracing in mitigating COVID-19 transmission.A negative correlation between the final ceiling of the logistic curve and its slope, established long time ago via a simulation study, motivated this closer look at flattening the curve of COVID-19. The diffusion of the virus is analyzed with S-shaped logistic-curve fits on the 25 countries most affected in which the curve was more than 95% completed at the time of the writing (mid-May 2020.) A negative correlation observed between the final number of infections and the slope of the logistic curve corroborates the result obtained long time ago via an extensive simulation study. There is both theoretical arguments and experimental evidence for the existence of such correlations. The flattening of the curve results in a retardation of the curve's midpoint, which entails an increase in the final number of infections. It is possible that more lives are lost at the end by this process. Our analysis also permits evaluation of the various governments' interventions in terms of rapidity of response, efficiency of the actions taken (the amount of flattening achieved), and the number of days by which the curve was delayed. Not surprisingly, early decisive response-such as countrywide lockdown-proves to be the optimum strategy among the countries studied.This paper describes a framework using disruptive technologies for COVID-19 analysis. Disruptive technologies include high-tech and emerging technologies such as AI, industry 4.0, IoT, Internet of Medical Things (IoMT), big data, virtual reality (VR), Drone technology, and Autonomous Robots, 5 G, and blockchain to offer digital transformation, research and development and service delivery. Disruptive technologies are essential for Industry 4.0 development, which can be applied to many disciplines. In this paper, we present a framework that uses disruptive technologies for COVID-19 analysis. The proposed framework restricts the spread of COVID-19 outbreaks, ensures the safety of the healthcare teams and maintains patients' physical and psychological healthcare conditions. The framework is designed to deal with the severe shortage of PPE for the medical team, reduce the massive pressure on hospitals, and track recovered patients to treat COVID-19 patients with plasma. The study provides oversight for governments on how to adopt technologies to reduce the impact of unprecedented outbreaks for COVID-19.