The Effect of Food Deserts on the Body Mass Index of Elementary School Children

Families in low-income neighborhoods sometimes lack access to supermarkets that provide a broad range of healthy foods. We investigate whether these so called "food deserts" play a role in childhood obesity using a statewide panel data set of Arkansas elementary schoolchildren. We use fixed-effects panel data regression models to estimate the average food desert effect. We next compare children who left (entered) food deserts to children who were always (never) in food deserts and homogenize samples for those whose food desert status changed as a result of a change in residence and those whose status changed only as a consequence of the entry or exit of a supermarket. We present evidence that exposure to food deserts is associated with higher z-scores for body mass index. On average, this is in the neighborhood of 0.04 standard deviations. The strongest evidence and largest association is among urban students and especially those that transition into food deserts from non-deserts. Our food desert estimates are similar in magnitude to findings reported in earlier work on diet and lifestyle interventions targeting similarly aged schoolchildren. That said, we are unable to conclude that the estimated food desert effect is causal because many of the transitions into or out of food deserts result from a change in residence, an event that is endogenous to the child's household. However, there is evidence that food deserts are a risk indicator and that food desert areas may be obesogenic in ways that other low-income neighborhoods are not

An acreage response model for Arkansas rice farms

In recent years, market forces have signaled a strong demand for rice as well as other Arkansas crops. However, high fuel, fertilizer, and chemical costs have negatively impacted farm income, and these input costs are widely known to impact planting decisions of farmers. The goal of this study is to develop and estimate an acreage response model for rice. The model is used to compute acreage response elasticities and provides insight into roles that input costs and crop prices play in acreage decisions made by producers. Economic theory predicts that prices for important inputs such as fuels and fertilizers as well as the relative prices of rice and soybeans will impact acreage decisions. Soybean prices are expected to be important because most of the machinery needed to produce rice and soybeans is the same and these crops are already used commonly in rotation. Results of the study show that crop price variables do indeed play a significant role in producer planning. Short- and long-run own-price acreage response elasticities are estimated to be 0.69 and 1.19, respectively. Soybean prices have the expected negative impact on rice acreage with a cross-price elasticity of -0.33 in the short run and -0.57 in the long run. On the other hand, the expected economic impacts of input prices on rice acreage were not supported by the results. Estimated relationships were negative, as would be predicted by economic theory, but were not statistically significant

Dirac model of electronic transport in graphene antidot barriers

In order to use graphene for semiconductor applications, such as transistors with high on/off ratios, a band gap must be introduced into this otherwise semimetallic material. A promising method of achieving a band gap is by introducing nanoscale perforations (antidots) in a periodic pattern, known as a graphene antidot lattice (GAL). A graphene antidot barrier (GAB) can be made by introducing a 1D GAL strip in an otherwise pristine sheet of graphene. In this paper, we will use the Dirac equation (DE) with a spatially varying mass term to calculate the electronic transport through such structures. Our approach is much more general than previous attempts to use the Dirac equation to calculate scattering of Dirac electrons on antidots. The advantage of using the DE is that the computational time is scale invariant and our method may therefore be used to calculate properties of arbitrarily large structures. We show that the results of our Dirac model are in quantitative agreement with tight-binding for hexagonal antidots with armchair edges. Furthermore, for a wide range of structures, we verify that a relatively narrow GAB, with only a few antidots in the unit cell, is sufficient to give rise to a transport gap

Electronic and optical properties of graphene antidot lattices: Comparison of Dirac and tight-binding models

The electronic properties of graphene may be changed from semimetallic to semiconducting by introducing perforations (antidots) in a periodic pattern. The properties of such graphene antidot lattices (GALs) have previously been studied using atomistic models, which are very time consuming for large structures. We present a continuum model that uses the Dirac equation (DE) to describe the electronic and optical properties of GALs. The advantages of the Dirac model are that the calculation time does not depend on the size of the structures and that the results are scalable. In addition, an approximation of the band gap using the DE is presented. The Dirac model is compared with nearest-neighbour tight-binding (TB) in order to assess its accuracy. Extended zigzag regions give rise to localized edge states, whereas armchair edges do not. We find that the Dirac model is in quantitative agreement with TB for GALs without edge states, but deviates for antidots with large zigzag regions.Comment: 15 pages, 7 figures. Accepted by Journal of Physics: Condensed matte

An Optimization Model for Winery Capacity Use

An optimization model to sequence wine flow through the production process is developed. The model is formulated as a mixed integer program and accounts for winemaking specifications, market conditions, grape availability, and tank capacity. An empirical example is provided to demonstrate results and uses of the model.Agribusiness,

Radiation effects in MOS integrated circuits

High energy electron irradiation effects on field effect transistors in integrated circuit device

SALES RESPONSES TO RECALLS FOR LISTERIA MONOCYTOGENES: EVIDENCE FROM BRANDED READY-TO-EAT MEATS

Empirical models are used to measure sales losses experienced by frankfurter brands following a recall for a foodborne pathogen. Recalled brands experience a 22 to 27 percent sales decline after a recall. Brand recovery occurs within 4 to 5 months after a recall. Non-recalled brands do not experience sales losses.Food Consumption/Nutrition/Food Safety,

Scaling behavior of spin transport in hydrogenated graphene

We calculate the spin transport of hydrogenated graphene using the Landauer-B\"uttiker formalism with a spin-dependent tight-binding Hamiltonian. The advantages of using this method is that it simultaneously gives information on sheet resistance and localization length as well as spin relaxation length. Furthermore, the Landauer-B\"uttiker formula can be computed very efficiently using the recursive Green's function technique. Previous theoretical results on spin relaxation time in hydrogenated graphene have not been in agreement with experiments. Here, we study magnetic defects in graphene with randomly aligned magnetic moments, where interference between spin-channels is explicitly included. We show that the spin relaxation length and sheet resistance scale nearly linearly with the impurity concentration. Moreover, the spin relaxation mechanism in hydrogenated graphene is Markovian only near the charge neutrality point or in the highly dilute impurity limit