Ennissampson3182

8%). this website The lack of space at home barrier was associated with age (OR = 2.56; CI 95% 1.05-6.02) and living in the capital (OR = 2.53; CI 95% 1.26-5.33). The barriers, taking care of children (OR = 3.75; CI 95% 1.37-10.2) and increased time spent on daily activities (OR = 2.20; CI 95% 1.02-4.74) were associated with living in the metropolitan region.

The lack of motivation, space at home, and professional instruction showed as being limiting factors to physical activity during the lockdown, indicating plans of action aimed at encouraging the practice of physical activity during a pandemic period.

The lack of motivation, space at home, and professional instruction showed as being limiting factors to physical activity during the lockdown, indicating plans of action aimed at encouraging the practice of physical activity during a pandemic period.The Covid-19 pandemic instills emotions that can be understood in the pathological sense of mental disorder and/or in the heuristic sense of a moral dimension. So what about this distinction in critical care and resuscitation services where caregivers are at the forefront of events? What to do with emotions? The objective of this work is to pose a medico-psychological and ethical perspective on these questions, starting from the hypothesis that emotions have a specific use during the pandemic. The first step will be to show that anguish and fear, although different from an epistemological point of view, arise from the same historical place, which is the discourse of the medical world with death. The awareness of the inevitable makes share the same need of the caregiver and the citizen of a psychic economy which will lead to differentiating two possible reactions to emotions one to face up and one to come to terms with. This psychic interlacing, inherent to the pandemic context, calls for critical care on a moral dimension related to the issue of abandonment of the human person and the poorly understood notion of "mass death". An answer to this difficulty would be found in the concept of "being-caregiver-close" but its application also supposes an ethical reflection on the outlets and the personal virtues.The year 2020 will certainly be remembered for the COVID-19 outbreak. First reported in Wuhan city of China back in December 2019, the number of people getting affected by this contagious virus has grown exponentially. Given the population density of India, the implementation of the mantra of the test, track, and isolate is not obtaining satisfactory results. A shortage of testing kits and an increasing number of fresh cases encouraged us to come up with a model that can aid radiologists in detecting COVID19 using chest Xray images. In the proposed framework the low level features from the Chest X-ray images are extracted using an ensemble of four pre-trained Deep Convolutional Neural Network (DCNN) architectures, namely VGGNet, GoogleNet, DenseNet, and NASNet and later on are fed to a fully connected layer for classification. The proposed multi model ensemble architecture is validated on two publicly available datasets and one private dataset. We have shown that our multi model ensemble architecture performs better than single classifier. On the publicly available dataset we have obtained an accuracy of 88.98% for three class classification and for binary class classification we report an accuracy of 98.58%. Validating the performance on private dataset we obtained an accuracy of 93.48%. The source code and the dataset are made available in the github linkhttps//github.com/sagardeepdeb/ensemble-model-for-COVID-detection.The purpose of this paper is to examine the effect of spatial proximity on financial contagion during the COVID-19 outbreak. We use the daily stock index series of Asian, American, and European countries from January 1, 2014 to January 30, 2021. Two groups of countries are considered the first includes China and geographically close countries, namely Taiwan, Hong Kong, Singapore, India, Australia, Indonesia, Malaysia, South Korea, Singapore, Vietnam and Russia. The second group includes countries that are geographically distant from China the United States, Brazil, Mexico, Argentina, Italy, France and Germany. Using local correlation measurement and polynomial regressions, we show that the spatial contagion effect exists between China and geographically distant countries. However, this effect is absent for geographically close countries (Taiwan, Vietnam and Hong Kong). These findings have strong implications for investors and present guidance for regulators and policymakers in understanding the true impact of the COVID-19 on financial markets.The current COVID-19 pandemics is a major threat to human populations. The disease has rapidly spread, causing mass hospitalization and the loss of millions of people mainly in urban areas which are hubs for contagion. At the same time, the social distancing practices required for containing the outbreak have caused an eruption of mental illnesses that include symptoms of depression, anxiety and stress. The severity of such mental distress is modulated by the context of media coverage and the information and guidelines from local health authorities. Different urban green infrastructures, such as gardens, parks, and green views can be important for mitigating mental distress during the pandemics. However, it is unclear whether some urban green infrastructures are more efficient than others in reducing mental distress or whether their effectiveness changes with the context. Here we assess the relative importance of different urban green infrastructures on the mental distress of residents of Rio de Janeiro, Brazil. We show that although urban parks and green views are important, home gardens are the most efficient in mitigating mental distress. This is likely related to the practice of self-isolation seen for the residents of Rio de Janeiro. Information on the efficiency of different urban green infrastructures in mitigating mental distress can be important to help guide programs to inform the public about the best practices for maintaining mental health during the current outbreak. This can also help planning cities that are more resilient to future pandemics.Although different studies have evaluated the positive impacts of the COVID-19 pandemic and lockdown measures on reducing noise pollution and traffic levels and improving air quality, how populations have perceived such changes in the natural environment has not been adequately evaluated. The present study provides a more in-depth exploration of human population perception of enhanced natural exposure (to animal life and nature sounds) and reduced harmful exposure (by improved air quality and reduced traffic volume) as a result of the COVID-19 pandemic lockdown. The data is drawn from 3,109 unselected adults who participated in the GreenCOVID survey from April to July 2020 in England, Ireland, and Spain. The findings suggest that the positive impacts to the natural environment as a result of the lockdown have been better received by the population in Spain and Ireland, in comparison to England. Participants who resided in urban areas had better perceived improvements in nature sounds, air quality, and traffic volume compared to those in rural areas. Older populations and those with lower smoking and alcohol consumption were found to perceive this improvement the most. Furthermore, the greater perception of improvements in environmental elements was also associated with better self-perceived health and improved wellbeing. In the binary logistic regression, living in Ireland or Spain, urban areas, female gender, older age, and good overall wellbeing were associated with a greater perception of improvements in the natural environment, while the factors most associated with a greater perception of reduced harmful exposure were living in Spain, had a good self-perceived health status and older age.Urban green infrastructure provides a range of experiences for people and various health benefits that support human well-being. To increase urban resilience, exceptional situations, such as the COVID-19 pandemic, are important to learn from. This study aims to understand how the residents in Turku, a middle-sized city in Finland, perceived their outdoor recreation changed and how nature contributed to their subjective well-being during the early phases of the COVID-19. Sites of outdoor recreation and associated ecosystem service benefits were gathered through a map-based survey. In addition, the contribution of nature on subjective well-being was measured through Likert scale statements and the perceived changes in outdoor recreation behaviour were measured through self-reported number of days and from responses to open survey questions. Data was analysed through quantitative, qualitative and spatial methods. The results show that nearly half of the respondents increased outdoor recreation and the majority o resilience of the city and its residents. Participatory mapping can capture the variety in resident's values and identify key recreation sites of multiple ecosystem service benefits.Given a discrete-time controlled bilinear systems with initial state x 0 and output function y i , we investigate the maximal output set Θ(Ω) = x 0 ∈ ℝ n , y i ∈ Ω, ∀ i ≥ 0 where Ω is a given constraint set and is a subset of ℝ p . Using some stability hypothesis, we show that Θ(Ω) can be determined via a finite number of inequations. Also, we give an algorithmic process to generate the set Θ(Ω). To illustrate our theoretical approach, we present some examples and numerical simulations. Moreover, to demonstrate the effectiveness of our approach in real-life problems, we provide an application to the SI epidemic model and the SIR model.Blackleg is an infectious disease of animals that is commonly caused by Clostridium chauvoei and characterized by localized muscle necrosis. In this study, proteome-mining and immunoinformatics approaches were applied to identify novel antigenic proteins and to construct a multi-epitope vaccine against C. chauvoei. All proteins of C. chauvoei strains were retrieved from the NCBI Microbial Genome Database containing both genomic and proteomic data of prokaryotes. The proteins were analyzed to exclude non-redundant sequences and to determine antigenic, virulent, and non-allergenic vaccine candidates through several online tools, resulting in seven protein candidates. Cytotoxic T and B cell epitopes of these proteins were evaluated through the tools present in the immune epitope database and the prioritized antigenic epitopes were then conjugated via appropriate linkers to construct the vaccine candidate. After the evaluation of physicochemical properties of the construct, the tertiary structure was modeled and refined through trRosetta and GalaxyRefine, respectively. The quality of the 3D structure was validated by ERRAT score, z-score, and Ramachandran plot and the construct was then docked with bovine Toll-like receptor 4 (TLR 4) using ClusPro. The docked complex was subjected to Molecular Mechanics/Generalized Born Surface Area in the HawkDock server and normal mode analysis in the iMODS simulation suite to assess the binding energy and stability of the complex, respectively. Overall, the vaccine construct was found stable and energetically feasible for bovine TLR 4 binding. Therefore, it can be used as a multi-epitope vaccine construct in clostridial vaccines to control the blackleg disease.

The online version contains supplementary material available at 10.1007/s10989-021-10279-9.

The online version contains supplementary material available at 10.1007/s10989-021-10279-9.