The Effect Demographics Have On The Demand For Orange Juice

This paper investigates how the demand for orange juice is affected by the demographics of consumers. There are many variables in the orange juice demand equation and demographics are only one. Demographic variables are important in determining the tastes and preferences of different regions. The data that has been collected is weekly data over a two year period of time. The seemingly unrelated regression method will be used to examine the data. This project will be beneficial to orange juice advertising firms and companies that sell orange juice.Food Consumption/Nutrition/Food Safety, Marketing,

On the ranking of the disease susceptibility locus in family-based candidate gene studies: a simulation-based analysis

The ranking of the p-value of the true causal single nucleotide polymorphism in the ordered list of individual SNP p-values is an important factor for achieving success in the ultimate objective of association studies - identifying deleterious genetic variants. Thus, we undertake a study to assess the implications of complex, multimarker correlation structure, sample size and disease models on the ranking of the causal SNP. We carry out an extensive family-based candidate gene simulation study to analyze the position of the disease susceptibility locus in the complete list of individual SNP p-values ordered according to their statistical significance. We simulate data based on the haplotype distributions of ten randomly selected genes extracted from the HapMap database, various sample sizes (600,1000 and 2000) that current association studies employ, and disease models that mimic the characteristics of complex human disorders. We conclude that the average ranking of the causal SNP for sample sizes 600, 100 and 200 of 10.97, 9.65, and 8.34 are dramatically distant from the most significant and intuitively appropriate top position. This result is even more pronounced for genes with high average correlation and large number of common SNPs. Moreover, the gain of the DSL ranking when comparing sample sizes 600 to 1000 and 1000 to 2000, averaged over disease models, causal SNPs and genes, was approximately 1.3. These outcomes both reveal the importance of the sample size and quantify the magnitude required to unequivocally determine the identity of the DSL in family-based candidate gene studies. Our results show the overwhelming importance of large sample sizes in the localization of deleterious SNPs even under simple disease models. These conclusions possess pronounced importance for the design and result interpretation of candidate gene, next generation high-density genome-wide association studies, as well as for the construction and implementation of association tests based on the distribution of the most significant (minimum p-value) test statistics

Bifurcated polarization rotation in bismuth-based piezoelectrics

ABO3 perovskite-type solid solutions display a large variety of structural and physical properties, which can be tuned by chemical composition or external parameters such as temperature, pressure, strain, electric, or magnetic fields. Some solid solutions show remarkably enhanced physical properties including colossal magnetoresistance or giant piezoelectricity. It has been recognized that structural distortions, competing on the local level, are key to understanding and tuning these remarkable properties, yet, it remains a challenge to experimentally observe such local structural details. Here, from neutron pair-distribution analysis, a temperature-dependent 3D atomic-level model of the lead-free piezoelectric perovskite Na0.5Bi0.5TiO3 (NBT) is reported. The statistical analysis of this model shows how local distortions compete, how this competition develops with temperature, and, in particular, how different polar displacements of Bi3+ cations coexist as a bifurcated polarization, highlighting the interest of Bi-based materials in the search for new lead-free piezoelectrics

Imaging Sources with Fast and Slow Emission Components

We investigate two-proton correlation functions for reactions in which fast dynamical and slow evaporative proton emission are both present. In such cases, the width of the correlation peak provides the most reliable information about the source size of the fast dynamical component. The maximum of the correlation function is sensitive to the relative yields from the slow and fast emission components. Numerically inverting the correlation function allows one to accurately disentangle fast dynamical from slow evaporative emission and extract details of the shape of the two-proton source.Comment: 13 pages, 4 figure

Thermal processing and interactions of ethyl formate in model astrophysical ices containing water and ethanol

Temperature programmed desorption (TPD) and reflection absorption infrared spectroscopy (RAIRS) have been used to investigate the interactions between ethyl formate and water and ethyl formate and ethanol in model astrophysical ices adsorbed on a graphitic model grain surface. Experiments show that the ethyl formate forms hydrogen bonds to both water and ethanol via the oxygen lone pairs. This leads to the observation of shifts in the vibrational wavenumber of the C=O and C-O-C modes of ethyl formate, which can potentially be used to identify the environment of this complex organic molecule in astronomical observations. TPD data show that the interaction of ethyl formate with water is stronger than that with ethanol, with an additional species being observed in the TPD spectrum corresponding to the desorption of ethyl formate directly bonded to the water ice surface. The desorption energy of ethyl formate adsorbed on water ice was found to be 48.5 kJ mol-1, compared to 43.2 kJ mol-1 for pure ethyl formate monolayers. Ethyl formate also traps in water ice, and undergoes volcano desorption at the water amorphous to crystalline phase transition temperature. In contrast to the water, ethanol has very little effect on the desorption of ethyl formate, with the two species behaving independently even in a co-deposited ice

Exposure-Lag-Response in Longitudinal Studies: Application of Distributed-Lag Nonlinear Models in an Occupational Cohort.

Prolonged exposures can have complex relationships with health outcomes, as timing, duration, and intensity of exposure are all potentially relevant. Summary measures such as cumulative exposure or average intensity of exposure may not fully capture these relationships. We applied penalized and unpenalized distributed-lag nonlinear models (DLNMs) with flexible exposure-response and lag-response functions in order to examine the association between crystalline silica exposure and mortality from lung cancer and nonmalignant respiratory disease in a cohort study of 2,342 California diatomaceous earth workers followed during 1942-2011. We also assessed associations using simple measures of cumulative exposure assuming linear exposure-response and constant lag-response. Measures of association from DLNMs were generally higher than those from simpler models. Rate ratios from penalized DLNMs corresponding to average daily exposures of 0.4 mg/m3 during lag years 31-50 prior to the age of observed cases were 1.47 (95% confidence interval (CI): 0.92, 2.35) for lung cancer mortality and 1.80 (95% CI: 1.14, 2.85) for nonmalignant respiratory disease mortality. Rate ratios from the simpler models for the same exposure scenario were 1.15 (95% CI: 0.89, 1.48) and 1.23 (95% CI: 1.03, 1.46), respectively. Longitudinal cohort studies of prolonged exposures and chronic health outcomes should explore methods allowing for flexibility and nonlinearities in the exposure-lag-response

Assessing the quantity of pulmonary edema in critically ill children

Measuring extravascular lung water may be useful for predicting outcome in adults with acute lung injury. The present commentary briefly reviews the potential role and limitations of extravascular lung water measurement in critically ill children