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This paper constructs various measures of domestic and global uncertainty and provides a comprehensive study of their impacts on the Thai economy. Based on a small open economy VAR, global uncertainty delivers deeper and more long-lasting effects when compared to within-country ones. In addition, we find that uncertainty shocks first generate sudden and large declines for stock prices and foreign portfolio investment, before gradually affecting the real economy through investment and trade channels. There is also meaningful heterogeneity among different types of domestic uncertainty. While financial uncertainty matters most for the Thai economy overall, consumption demand largely responds to macroeconomic uncertainty, while economic policy and political uncertainty generates the most persistent effects on investment. Furthermore, fiscal policy uncertainty is a key driver of trade flows while monetary policy uncertainty plays an important role for capital markets.COVID-19 made considerable changes in the lifestyle of people, which have led to a rise in energy use in homes. So, this study investigated the relationship between COVID-19 and domestic hot water demands. For this purpose, a nondimensional and principal component analysis were conducted to find out the influencing factors using demand data before and after COVID-19 from our study site. Analysis showed that the COVID-19 outbreak affected the daily peak time and the amount of domestic hot water usage, the active case number of COVID-19 was a good indicator for correlating the changes in hot water demand and patterns. Based on this, a machine learning model with an artificial neural network was developed to predict hot water demand depending on the severity of COVID-19 and the relevant correlation was also derived. The model analysis showed that the increase in the number of active cases in the region affected the hot water demand increased at a certain rate and the maximum demand peak in morning during weekdays and weekends decreased. Furthermore, if the number of active cases reached more than 4000, the peak in morning moved to afternoon so that the energy use patterns of weekdays and weekends are assimilated.The Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) provides breastfeeding support and free formula to low-income participating infants in the U.S. Literature has consistently documented worse breastfeeding outcomes in WIC infants and children than in non-participants, although self-selection bias poses a challenge in examining the relationship between WIC participation and breastfeeding in low-income mother-child dyads. The WIC program adopted a comprehensive food package revision in 2009, the first one in four decades. Since that time, few national studies have examined the relationship between WIC participation and breastfeeding while controlling for the endogeneity of WIC participation with the propensity score method. This paper applied an instrumental variable (IV) approach on a large, nationally representative survey sample of children, the National Immunization Surveys (NIS), to examine the relationship between WIC participation and breastfeeding among children born between 2005 and 2014. We identified state Supplemental Nutrition Assistance Program (SNAP) enrollment rates and SNAP Policy Indices as valid IVs to address WIC participation endogeneity. Without the IVs, WIC participation had a significantly negative relationship with breastfeeding. Avacopan After addressing endogeneity using the IVs, the relationship became insignificant in the whole sample and in the subpopulations across race/ethnicity and child gender. The neutrality of WIC participation on breastfeeding is important for policy makers to understand in seeking to improve breastfeeding among WIC participants.The COVID-19 pandemic is one of the most pressing issues at present. A question which is particularly important for governments and policy makers is the following Does the virus spread in the same way in different countries? Or are there significant differences in the development of the epidemic? In this paper, we devise new inference methods that allow to detect differences in the development of the COVID-19 epidemic across countries in a statistically rigorous way. In our empirical study, we use the methods to compare the outbreak patterns of the epidemic in a number of European countries.The main objective of the article is twofold. On the one hand, it aims to offer a critical analysis of the different operationalizations of the concept of social exclusion at the international level, including reflection on widely used methods such as the "At risk of poverty or social exclusion" rate. On the other hand, it offers an empirically tested proposal of indicator aggregation for the measurement of social exclusion. The debate regarding the measurement of social exclusion has been widely addressed, but there are hardly any proposals that test different systems of indicator aggregation. The multiple correspondence analysis allows the implementation of a new approach for measuring the weights of the indicators, based on the distance to the integration point, which is understood as the absence of problems. The proposed new system shows an important potential to be extrapolated to the comparative measurement of social exclusion, also allowing the comparison of different social groups. The empirical reference used for the analysis is the Survey on Social Needs and Social Integration of the FOESSA Foundation for Spain 2018.It is imperative that image-guided intervention (IGI) systems provide accurate and precise navigation information to enable the user to trust the system and not place unwarranted confidence in the guidance capabilities of the system. Unfortunately, the actual error associated with the overall targeting capabilities of an IGI system is not readily known. Here we are primarily interested in the application of image-guided surgery in the context of renal interventions. We built a simulation pipeline to study the uncertainty propagation through an optically tracked IGI system to gain insight into the overall accuracy of the system. Our simulation pipeline models several stages, including stylus calibration, tool tracking, patient tracking, and image to patient registration. In the effort to realistically estimate tracking noise and user-associated fiducial localization error (FLE), we conducted several experiments using the optical tracking system. Our simulation suggested that a wider cone angle results in a more accurate tool calibration, which improves further with the collection of additional samples.

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