A cross-country comparison of alcohol,tobacco, and marijuana use among youth who are employed,in school or out of the labor force and school (OLFS)

Labor force and school attachment may influence alcohol, tobacco, and marijuana use in the US and Canada. Differences in social welfare provision, which provide protections for individuals with insecure attachments to the labor force or education, may in turn impact the behavior and health of youth in these countries. Yet, there is little research to understand the health consequences for youth of being out of the labor force and school (OLFS). Data of 25–29 year old participants of the National Longitudinal Survey of Youth (year 2010) and the Canadian Community Health Survey (2009–2010) were used to examine differences in substance use by labor force and school attachment. Logistic regression suggests that OLFS in the US and Canada were less likely to report alcohol uptake and more likely to use tobacco compared to employed youth. Unemployment was differentially associated with substance use behaviors by country. Country of residence and subsequent exposure to social welfare policy does not appear to impact substance use behaviors among OLFS. However, associations of unemployment and gender by country indicates differences in substance use behavior. More research should seek to understand factors that influence alcohol, tobacco, and marijuana use among OLFS and unemployed youth.     

Combining Quantitative Risk Assessment of Human Health,Food Waste,and Energy Consumption: The Next Step in the Development of the Food Cold Chain?

The preservation of perishable food via refrigeration in the supply chain is essential to extend shelf life and provide consumers with safe food. However, electricity consumed in refrigeration processes has an economical and an environmental impact. This study focuses on the cold chain of cooked ham, including transport, cold room in supermarket, display cabinet, transport by consumer, and domestic refrigerator, and aims to predict the risk for human health associated with Listeria monocytogenes, the amount of food wasted due to the growth of spoilage bacteria, and the electrical consumption to maintain product temperature through the cold chain. A set of eight intervention actions were tested to evaluate their impact on the three criteria. Results show that the modification of the thermostat of the domestic refrigerator has a high impact on food safety and food waste and a limited impact on the electrical consumption. Inversely, the modification of the airflow rate in the display cabinet has a high impact on electrical consumption and a limited impact on food safety and food waste. A cost–benefit analysis approach and two multicriteria decision analysis methods were used to rank the intervention actions. These three methodologies show that setting the thermostat of the domestic refrigerator to 4 °C presents the best compromise between the three criteria. The impact of decisionmaker preferences (criteria weight) and limitations of these three approaches are discussed. The approaches proposed by this study may be useful in decision making to evaluate global impact of intervention actions in issues involving conflicting outputs.     

Transactions with God: Market,Moralities and Agency in the Worship of the Goddess of the Treasury in Northern Vietnam

This article explores the complex moral choices of those who have negotiated the encounter between marketisation and distinctive religious traditions within and beyond Asia. I focus on the dramatic rise in the worship of the Goddess of the Treasury in northern Vietnam since the onset of marketisation. She is believed to possess a special power: to grant those who borrow a sum from her symbolic treasury the same amount as real profit and actual wealth through earthly business activities. I show that the Goddess's rise does not reflect the universalising effects of marketisation, but instead how Vietnamese religious ideas of faithfulness and sincerity continue to inform worshippers’ choices as active moral agents. Rather than robotic doers of market principles or passive followers of ‘superstitious’ beliefs in rejection of market changes, worshippers are creative actors who innovatively employ traditional moralities in novel ways to meet their present-day quest for economic prosperity.     

Layer Sampling

Layer sampling is an algorithm for generating variates from a non-normalized multidimensional distribution p( · ). It empirically constructs a majorizing function for p( · ) from a sequence of layers. The method first selects a layer based on the previous variate. Next, a sample is drawn from the selected layer, using a method such as Rejection Sampling. Layer sampling is regenerative. At regeneration times, the layers may be adapted to increase mixing of the Markov chain. Layer sampling may also be used to estimate arbitrary integrals, including normalizing constants.     

Understanding the Hastings Algorithm

The Hastings algorithm is a key tool in computational science. While mathematically justified by detailed balance, it can be conceptually difficult to grasp. Here, we present two complementary and intuitive ways to derive and understand the algorithm. In our framework, it is straightforward to see that the celebrated Metropolis–Hastings algorithm has the highest acceptance probability of all Hastings algorithms.     

Bounding Poorly Characterized Risks: A Lung Cancer Example

For diseases with more than one risk factor, the sum of probabilistic estimates of the number of cases caused by each individual factor may exceed the total number of cases observed, especially when uncertainties about exposure and dose response for some risk factors are high. In this study, we outline a method of bounding the fraction of lung cancer fatalities not due to specific well-studied causes. Such information serves as a "reality check" for estimates of the impacts of the minor risk factors, and, as such, complements the traditional risk analysis. With lung cancer as our example, we allocate portions of the observed lung cancer mortality to known causes (such as smoking, residential radon, and asbestos fibers) and describe the uncertainty surrounding those estimates. The interactions among the risk factors are also quantified, to the extent possible. We then infer an upper bound on the residual mortality due to "other" causes, using a consistency constraint on the total number of deaths, the maximum uncertainty principle, and the mathematics originally developed of imprecise probabilities.     

Access to social protection among people with disabilities: Evidence from Viet Nam

Although people with disabilities are frequently targeted as key beneficiaries of social protection, little is known on their access to existing programmes. This study uses mixed methods to explore participation in disability‐targeted and non‐targeted social protection programmes in Viet Nam, particularly in the district of Cam Le. In this district, social assistance and health insurance coverage among people with disabilities was 53 per cent and 96 per cent respectively. However, few accessed employment‐linked social insurance and other disability‐targeted benefits (e.g. vocational training, transportation discounts). Factors affecting access included the accessibility of the application process, disability assessment procedures, awareness and the perceived utility of programmes, and attitudes on disability and social protection.     

Does greater household wealth make young children perform better? The case of Vietnam

Our study examines factors affecting children's cognitive ability in Vietnam for the period 2006–2016. We find that conditional wealth has a positive association with the cognitive capacity of 15-year-old children, manifested in all three methods of measurement: vocabulary points, math scores and reading comprehension scores in Vietnamese. Notably, the finding implies that improving household wealth after the children's first 1,000 days still plays an important role in the cognitive development of 5–12-year-olds. Also, it suggests that using conditional wealth enables us to capture the impact of economic shocks, thereby having a significant effect on the cognitive ability of children.     

Nonparametric regression in a statistical modified Helmholtz equation using the Fourier spectral regularization

In this paper, we deal with the Cauchy problem for the modified Helmholtz equation. We consider two models of data: the bounded variance model and the i.i.d. model. The trigonometric estimators of nonparametric regression is applied to solve the problem. In addition, the general forms of regularization parameter corresponding to the pointwise mean squared error and the mean integrated squared error are discussed in detail. The minimax rate convergence corresponding to the bounded variance model is also presented. In the i.i.d. model, we construct the asymptotic confidence interval for the solution of the problem. Finally, we give some numerical experiments and discuss the obtained results.