Notes

The actual circadian rest-activity pattern states mental fall amid mild-moderate Alzheimer's disease sufferers.
The predicted concentrations were slightly lower and less dispersed than the observed ones. Consistent with observed pollution records, prediction maps exhibited higher concentration over the road network, industrial areas, and the eastern quadrants of the city. Lastly, results of a corresponding study of PM in summer 2010 and winter 2011 were considered. While the small size of the 2010-2011 sample hampered a multi-temporal analysis, we cautiously note comparable seasonal patterns and consistent association with land use variables for both PM fine fractions over the 5-year interval.There is no denying the fact that, for a developing country like Bangladesh, the economic consequences of lockdown for containing COVID-19 pandemic can be far reaching affecting livelihoods of millions of households. Given that the share of food consumption expenditure to total expenditure is higher in the lower income groups of Bangladesh, this shock is expected to directly affect affordability of consumption of basic food items of these households. Using nationally representative household survey data of Bangladesh, and while following the Feasible Generalized Least Square method, this paper attempts to examine food poverty, food consumption inequality along with vulnerability to food poverty of households and explores the importance of different socio-demographic and environmental factors in this connection. Our estimation reflects that, greater percentage of households with young children or with elderly people are found to suffer high food vulnerability. In addition, households in environmentally endangered regions e.g. drought prone areas or river erosion affected places are more food vulnerable than those in other parts of the country. Certain occupation groups e.g. day labourer and self-employed are found to be highly vulnerable to food poverty while according to our decomposition analysis of food consumption inequality, area of residence (urban vs. rural) is expected to cause sizable inequality in food consumption. This study can therefore, help in identifying food vulnerable households for government's social protection programs and COVID-19 incentive packages, and thereby can contribute towards designing effective poverty reduction strategies.The manuscript presents a bragging-based ensemble forecasting model for predicting the number of incidences of a disease based on past occurrences. The objectives of this research work are to enhance accuracy, reduce overfitting, and handle overdrift; the proposed model has shown promising results in terms of error metrics. The collated dataset of the diseases is collected from the official government site of Hong Kong from the year 2010 to 2019. The preprocessing is done using log transformation and z score transformation. The proposed ensemble model is applied, and its applicability to a specific disease dataset is presented. The proposed ensemble model is compared against the ensemble models, namely dynamic ensemble for time series, arbitrated dynamic ensemble, and random forest using different error metrics. The proposed model shows the reduced value of MAE (mean average error) by 27.18%, 3.07%, 11.58%, 13.46% for tuberculosis, dengue, food poisoning, and chickenpox, respectively. The comparison drawn between the proposed model and the existing models shows that the proposed ensemble model gives better accuracy in the case of all the four-disease datasets.This study investigated the perceived health care needs, unmet health need, and barriers to health care in 224 rural-dwelling adolescents. A cross-sectional, descriptive design was used to survey adolescents attending a public high school in a low-resource, rural Indiana community. One in five adolescents reported an unmet health need. The most common barriers to health care were related to access, apathy, anxiety, and parenting issues. Implications include confidentiality protocols in family healthcare practices, school-based health centers, and intervention research targeting adolescents' communication skills and healthcare consumer skills.World Health Organization (WHO) stated COVID-19 as a pandemic in March 2020. Since then, 26,795,847 cases have been reported worldwide, and 878,963 lost their lives due to the illness by September 3, 2020. Prediction of the COVID-19 pandemic will enable policymakers to optimize the use of healthcare system capacity and resource allocation to minimize the fatality rate. In this research, we design a novel hybrid reinforcement learning-based algorithm capable of solving complex optimization problems. We apply our algorithm to several well-known benchmarks and show that the proposed methodology provides quality solutions for most complex benchmarks. Besides, we show the dominance of the offered method over state-of-the-art methods through several measures. selleck chemicals Moreover, to demonstrate the suggested method's efficiency in optimizing real-world problems, we implement our approach to the most recent data from Quebec, Canada, to predict the COVID-19 outbreak. Our algorithm, combined with the most recent mathematical model for COVID-19 pandemic prediction, accurately reflected the future trend of the pandemic with a mean square error of 6.29E-06. Furthermore, we generate several scenarios for deepening our insight into pandemic growth. We determine essential factors and deliver various managerial insights to help policymakers making decisions regarding future social measures.The aim of this paper is to investigate the impact of Brexit on the dependence between European financial markets. We use the Diebold and Yilmaz (2009, 2012) approach to better map the relationship between the three main European markets and we propose an Optimal portfolio weighting to gain insights into the portfolio design dynamics in the period between 2013 and 2019, in particular any changes due to uncertainty surrounding Brexit. First, the findings show that between September 2015 and September 2016, the high level of volatility and spillover confirms the strong degree of market integration, with uncertainty surrounding the referendum outcome having a clear impact on the three main European markets. Second, the direction of spillover in the pre-Brexit period was from the UK market to the French and German markets in anticipation of uncertainty regarding the outcome of the referendum and the period immediately following it. Third, only the conditional correlation between the pair (CAC40-FTSE100) is characterized by an asymmetric effect.
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