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899) and specificity (0.889). The NPV of all three models exceeded 97%, while their PPV values were relatively low, resulting in 0.381 for LR, 0.402 for LR-5, and 0.432 for GBDT. Regarding severe and critically severe cases, the GBDT model also performed the best with a fivefold AUC of 0.918. In the external validation test of the LR-5 model using 72 cases of COVID-19 from Brunei, leukomonocyte (%) turned to show the highest fivefold AUC (0.917), followed by urea (0.867), age (0.826), and SPO2 (0.704). The findings confirm that the mortality prediction performance of the GBDT is better than the LR models in confirmed cases of COVID-19. The performance comparison seems independent of disease severity.

The online version contains supplementary material available at(10.1007/s00521-020-05592-1).

The online version contains supplementary material available at(10.1007/s00521-020-05592-1).The increasing popularity of social media platforms has simplified the sharing of news articles that have led to the explosion in fake news. With the emergence of fake news at a very rapid rate, a serious concern has produced in our society because of enormous fake content dissemination. The quality of the news content is questionable and there exists a necessity for an automated tool for the detection. Existing studies primarily focus on utilizing information extracted from the news content. We suggest that user-based engagements and the context related group of people (echo-chamber) sharing the same opinions can play a vital role in the fake news detection. Hence, in this paper, we have focused on both the content of the news article and the existence of echo chambers in the social network for fake news detection. Standard factorization methods for fake news detection have limited effectiveness due to their unsupervised nature and primarily employed with traditional machine learning models. To design an eff potential use of the technique for classifying fake news.Australia's economy abruptly entered into a recession due to the COVID-19 pandemic of 2020. Related labour market shocks on Australian residents have been substantial due to business closures and social distancing restrictions. Government measures are in place to reduce flow-on effects to people's financial situations, but the extent to which Australian residents suffering these shocks experience lower levels of financial wellbeing, including associated implications for inequality, is unknown. Using novel data we collected from 2078 Australian residents during April to July 2020, we show that experiencing a labour market shock during the pandemic is associated with a 29% lower level of perceived financial wellbeing, on average. Unconditional quantile regressions indicate that lower levels of financial wellbeing are present across the entire distribution, except at the very top. Distribution analyses indicate that the labour market shocks are also associated with higher levels of inequality in financial wellbeing. Financial counselling and support targeted at people who experience labour market shocks could help them to manage financial commitments and regain financial control during periods of economic uncertainty.Urbanization of global populations with augmented and convenient living standards of people are driving towards techno-enabled and sustainable smart cities in the future. With this, technology plays a key role in making the existing cities smart and intelligent in a way that the citizens are being served better and safer. Over the past 1-decade, the application of Artificial Intelligence (AI) in different sectors like Environment, Education, Healthcare, etc. is well-supporting the idea of Global Digitalization and Smart Cities. In this paper, we highlight and discuss the multiple sectors where the AI approach is expected to grow to make a Global Smart City. Further, the paper contributes to presenting the AI approach for urban and rural India using AI-enabled drones. For Urban India, we discuss how and where the AI can be used to make urban India smart and sustainable. Lastly, the paper contributes to exposing the challenges faced by rural India and giving a wholesome approach to integrating AI into different sectors for rural enhancement and upliftment.It is well documented that foreign investment inflows are deterred by host taxes. What is less clear, however, is the degree to which these aggregate changes are driven by firm choices at the extensive (whether to invest) or intensive (how much to invest) margins. Further, there is little evidence on the way in which these two margins are affected by firm and home-country characteristics. We contribute by examining firm-level cross-border investments during 2007-2015 into Europe from a broad group of home countries at both investment margins. Similar to the existing single-country studies, we find that taxes operate primarily on the extensive margin. Building on those results, we delve further and find significant variation across firms with small investors from high-tax home countries especially sensitive to host taxation.This paper studies the role of the tax on mobile capital in labor markets with matching frictions and the effects of such frictions on inefficiency of capital taxation. Firms acquire capital and create vacancies, and workers apply for firms. Due to matching frictions, vacancies may not be filled, and workers may not be employed. Firms' investment in capital, wages and market tightness are determined in a way that a firm's profit and a worker's utility are jointly maximized. In addition, the return to capital net of the tax is equalized across jurisdictions, as capital moves between jurisdictions. An increase in the capital tax of a jurisdiction alters firms' capital investment, wages and market tightness of the jurisdiction. In particular, it decreases employment and wages of the jurisdiction, providing an explanation for why policymakers of a jurisdiction provide incentives such as tax cuts for mobile capital. More capital increases the wages only when workers are employed and hence have higher incomes, decreasing the benefit of more capital for risk-averse workers and reducing the incentives of a jurisdiction to lower the tax and attract capital. The equilibrium capital tax thus may be too low or too high relative to the efficient level, and capital is taxed even with the head tax.The current study investigates a novel redox technology based on synthetic franklinite-like zinc-ferrite nanomaterial with magnetic properties and redox nature for potential use in water treatment. Physicochemical characterization revealed the nanoscale size and AB2O4 spinel configuration of the zinc-ferrite nanomaterial. The redox activity of nanoparticles was tested for degradation of diclofenac (DCF) pharmaceutical in water, without any added external oxidants and under dark experimental conditions. Results revealed ~90% degradation in DCF (10 μM) within 2 min of reaction using 0.17 g/L Zn1.0Fe2.0O4. Degradation of DCF was due to chemical reduction by surface electrons on zinc-ferrite and oxidation by oxygen-based radicals. Three byproducts from reduction route and eight from oxidation pathways were identified in the reaction system. Reaction pathways were suggested based on the identified byproducts. TPX-0005 Results demonstrated the magnetic zinc-ferrite is a standalone technology that has a great promise for rapid degradation of organic contaminants, such as DCF in water.We consider a real-time emergency medical service (EMS) vehicle patient transportation problem in which vehicles are assigned to patients so they can be transported to hospitals during an emergency. The objective is to minimize the total travel time of all vehicles while satisfying two types of time window constraints. The first requires each EMS vehicle to arrive at a patient's location within a specified time window. The second requires the vehicle to arrive at the designated hospital within another time window. We allow an EMS vehicle to serve up to two patients instead of just one. The problem is shown to be NP-complete. We, therefore, develop a simulated annealing (SA) heuristic for efficient solution in real-time. A column generation algorithm is developed for determining a tight lower bound. Numerical results show that the proposed SA heuristic provides high-quality solutions in much less CPU time, when compared to the general-purpose solver. Therefore, it is suitable for implementation in a real-time decision support system, which is available via a web portal (www.rtdss.org).

The global crisis caused by the outbreak of severe acute respiratory syndrome caused by the SARS-CoV-2 virus, better known as COVID-19, brought the need to improve the population's immunity. The foods rich in polysaccharides with immunomodulation properties are among the most highly rated to be used as immune response modulators. Thus, the use of polysaccharides obtained from food offers an innovative strategy to prevent serious side effects of viral infections.

This review revisits the current studies on the pathophysiology of SARS-CoV-2, its characteristics, target cell interactions, and the possibility of using polysaccharides from functional foods as activators of the immune response. Several natural foods are explored for the possibility of being used to obtain polysaccharides with immunomodulatory potential. And finally, we address expectations for the use of polysaccharides in the development of potential therapies and vaccines.

The negative consequences of the SARS-CoV-2 pandemic across the worl In addition, they can be used safely, as they have no toxic effects, are biocompatible and biodegradable. Finally, these biopolymers can still be used in the development of new therapies and vaccines.Understanding and improving the public risk perception have become an important element in the management of flood risk. In China, the risk government is of so-called nationwide catastrophe response mode which is different from the widely adopted "bottom up" risk governance mode in the Western countries. Such a particular mode may make Chinese people perceive risk in a different way from people in other countries. Hence, a further discussion of risk perception is of great value in China. This paper presents a case study on the public perception of flood hazard and flood risk in a city prone to floods. The relationship between risk perception and exposure was examined by spatial analysis. Meanwhile, inferential testing with chi-squared tests was undertaken regarding experience, social trust, and protective behaviors. Our results suggest that (1) the relationship between exposure and risk perception of people in Nanjing is positive and statistically significant, (2) flood experience was strongly related to risk perception, (3) trust showed a significant relationship to risk perception, and (4) people who have perceived the probability of floods and associated loss of life have a higher willingness to take more protective measures. These findings will help local government to develop effective flood risk communication strategies for improving public awareness creation, emergency response and preparedness.Rapid damage assessment of natural disasters is essential for the fast recovery and strategic post-disaster reconstructions. In the present study, National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) day/night band (DNB)-extracted night-time lights (NTL) data were explored for damage assessment caused by extremely severe cyclonic storm 'AMPHAN' that struck one of the most populous regions in India. link2 The disaster impact was measured on two parameters population and crop land area, where NTL density and population density were found to be strongly correlated (r 2 > 0.8). link3 From power outage intensity, three 'crisis zones' indicating the severity of cyclone damage were identified. Finally, the assessment found that the total affected population and crop land area were nearly 70% and 66%, respectively, of the study area. Therefore, NPP-VIIRS DNB image-based rapid damage assessment is potentially a useful tool for generating first hand information about the physical damages caused by extreme events.