Taste and Visual Influences on Hispanic Consumers' Preferences and Willingness-to-Pay for Pasture-Fed Beef

Experimental Economics methods are used to determine Hispanic consumers’ sensory acceptance of pasture-fed beef and evaluate visual and taste influences on their overall preferences and willingness-to-pay (WTP). Two hundred and thirty-one Hispanic consumers in four experimental sites in Virginia participated in a laboratory experimental procedure where they visually examined and tasted pasture-fed and conventionally produced grain-fed beef, and then participated in a non-hypothetical Multiple Price Lists (MPL) experiment to determine their WTP. Hispanic consumers perceived significant differences between pasture-fed and grain-fed beef’s appearance and taste. Visual and taste acceptances are closely correlated to and significantly influence overall preferences. More than fifty percent of Hispanic consumers prefer pasture-fed beef and the majority of them consistently are willing to pay a price premium. Approximately, half consumers who generally prefer pasture-fed beef consistently consider the appearance and taste of pasture-fed beef more favorable but another half of them indicated discrepant visual and taste acceptances. Nevertheless, this inconsistency doesn’t lead to a lower WTP for pasture-fed beef.Pasture-Fed Beef, Experimental Economics, Multiple Price Lists, Preference, Willingness-to-pay, Agribusiness, Consumer/Household Economics, Demand and Price Analysis, Food Consumption/Nutrition/Food Safety, Livestock Production/Industries, Marketing,

Comment on "Atomic Scale Structure and Chemical Composition across Order-Disorder Interfaces"

Interfaces have long been known to be the key to many mechanical and electric properties. To nickel base superalloys which have perfect creep and fatigue properties and have been widely used as materials of turbine blades, interfaces determine the strengthening capacities in high temperature. By means of high resolution scanning transmission electron microscopy (HRSTEM) and 3D atom probe (3DAP) tomography, Srinivasan et al. proposed a new point that in nickel base superalloys there exist two different interfacial widths across the {\gamma}/{\gamma}' interface, one corresponding to an order-disorder transition, and the other to the composition transition. We argue about this conclusion in this comment

Flux-dynamics associated with the Second Magnetisation Peak in iron-pnictide Ba_{1-x}K_xFe_2As_2

We report on isofield magnetic relaxation data on a single crystal of $Ba_{1-x}K_xFe_2As_2$ with superconducting transition temperature $T_c$= 32.7 K which exhibit the so called fish-tail effect. A surface map of the superconducting transition temperature shows that the superconducting properties are close to homogeneous across the sample. Magnetic relaxation data, M(t), was used to obtain the activation energy U(M) in order to study different vortex dynamics regimes. Results of this analysis along with time dependent measurements as a function of field and temperature extended to the reversible region of some M(H) curves demonstrate that the irreversibility as well the second magnetization peak position, $H_p(T)$, are time dependent and controlled by plastic motion of the vortex state. In the region delimited by a characteristic field Hon (well below $H_p$), and $H_p$, the vortex dynamics is controlled by collective pinning. For fields below Hon the activation energy, $U_0$, increases with field as expected for collective pinning, but the pinning mechanism is likely to be in the single vortex limit.Comment: 8 pages, 8 figures, one tabl

Multi-Channel Stochastic Variational Inference for the Joint Analysis of Heterogeneous Biomedical Data in Alzheimer's Disease

The joint analysis of biomedical data in Alzheimer's Disease (AD) is important for better clinical diagnosis and to understand the relationship between biomarkers. However, jointly accounting for heterogeneous measures poses important challenges related to the modeling of the variability and the interpretability of the results. These issues are here addressed by proposing a novel multi-channel stochastic generative model. We assume that a latent variable generates the data observed through different channels (e.g., clinical scores, imaging, ...) and describe an efficient way to estimate jointly the distribution of both latent variable and data generative process. Experiments on synthetic data show that the multi-channel formulation allows superior data reconstruction as opposed to the single channel one. Moreover, the derived lower bound of the model evidence represents a promising model selection criterion. Experiments on AD data show that the model parameters can be used for unsupervised patient stratification and for the joint interpretation of the heterogeneous observations. Because of its general and flexible formulation, we believe that the proposed method can find important applications as a general data fusion technique.Comment: accepted for presentation at MLCN 2018 workshop, in Conjunction with MICCAI 2018, September 20, Granada, Spai