A comparison of generalized multinomial logit, random parameters logit, wtp-space and latent class models to studying consumers' preferences for animal welfare

The European societies are requiring that animals to be raised as closely as possible to their natural conditions. The growing concerns about animal welfare is resulting in continuous modifications of regulations and policies that led to ban of a number of intensive farming methods. The European authorities consider the pig welfare as a priority issue. They are studying to ban surgical pig castration by 2018, which may seriously affect markets and consumers due to boar tainted-meat. This study analysed consumers’ preferences and acceptance regarding an alternative to castration of high-level boar-taint frankfurter sausages. Non-hypothetical discrete choice experiments was applied by creating a real shopping scenario before and after tasting the products. Data were collected for a sample of 150 consumers from the metropolitan area of Madrid, Spain. Different modelling approaches (Generalized Multinomial Logit-GMNL, Random Parameters Logit-RPL, WTP-space and Latent Class-LC models) were applied to figure out which model have the best goodness of fit. Results showed the appropriateness of the proposed alternative by using a new flavour as a masking strategy. When consumers tasted the products, they showed their willingness to pay a premium for this flavour. The WTP space model showed the best goodness of fit in terms of likelihood, Akaike information criterion and McFadden Pseudo R2. Furthermore, the degree of randomness identified by the scale parameter is also estimated. Uncertainty in selection decreased significantly after the sensory experiencePostprint (published version

Neural simulation of a system that learns representations of sensory experience

The pyriform cortex forms stable representations of smells to allow their subsequent recognition. Clustering systems are shown to perform a similar function, so they provide a guide to understanding the operation of the pyriform. A neural model of a sample of pyriform cortex was built that adheres to most known biological constraints, including learning by long-term potentiation. Results of early simulations suggest some interesting properties. The effort has implications for the knowledge representations used in artificial intelligence work

Bayesian Learning Models of Pain: A Call to Action

Learning is fundamentally about action, enabling the successful navigation of a changing and uncertain environment. The experience of pain is central to this process, indicating the need for a change in action so as to mitigate potential threat to bodily integrity. This review considers the application of Bayesian models of learning in pain that inherently accommodate uncertainty and action, which, we shall propose are essential in understanding learning in both acute and persistent cases of pain

Leveraging Sensory Data in Estimating Transformer Lifetime

Transformer lifetime assessments plays a vital role in reliable operation of power systems. In this paper, leveraging sensory data, an approach in estimating transformer lifetime is presented. The winding hottest-spot temperature, which is the pivotal driver that impacts transformer aging, is measured hourly via a temperature sensor, then transformer loss of life is calculated based on the IEEE Std. C57.91-2011. A Cumulative Moving Average (CMA) model is subsequently applied to the data stream of the transformer loss of life to provide hourly estimates until convergence. Numerical examples demonstrate the effectiveness of the proposed approach for the transformer lifetime estimation, and explores its efficiency and practical merits.Comment: 2017 North American Power Symposium (NAPS), Morgantown, WV, 17-19 Sep. 201

Neuronal Distortions of Reward Probability without Choice

Reward probability crucially determines the value of outcomes. A basic phenomenon, defying explanation by traditional decision theories, is that people often overweigh small and underweigh large probabilities in choices under uncertainty. However, the neuronal basis of such reward probability distortions and their position in the decision process are largely unknown. We assessed individual probability distortions with behavioral pleasantness ratings and brain imaging in the absence of choice. Dorsolateral frontal cortex regions showed experience dependent overweighting of small, and underweighting of large, probabilities whereas ventral frontal regions showed the opposite pattern. These results demonstrate distorted neuronal coding of reward probabilities in the absence of choice, stress the importance of experience with probabilistic outcomes and contrast with linear probability coding in the striatum. Input of the distorted probability estimations to decision-making mechanisms are likely to contribute to well known inconsistencies in preferences formalized in theories of behavioral economics

Diagnostic, demographic, memory quality, and cognitive variables associated with acute stress disorder in children and adolescents

To date, no studies have investigated factors associated with acute stress disorder (ASD) in children and adolescents. Relationships between ASD and a number of demographic, trauma, cognitive, and trauma memory variables were therefore investigated in a sample (N=93) of children and adolescents involved in assaults and motor vehicle accidents. Several cognitive variables and the quality of trauma memories, but not demographic or trauma variables, were correlated with ASD and also mediated the relationship between peritraumatic threat and ASD. Finally, nosological analyses comparing ASD with indexes of posttraumatic stress disorder in the month posttrauma revealed little support for the dissociation mandate that uniquely characterizes ASD. The results are discussed with respect to assessment and treatment for the acute traumatic stress responses of children and young people

On the neural computation of utility

The rewarding effect produced by electrical stimulation of the lateral hypothalamus can compete and summate with gustatory rewards. However, physiological manipulations, such as sodium depletion and the accumulation of an energy-rich solution in the gut, can alter the rewarding impact of the gustatory stimuli without producing substantial changes in the rewarding effect of the electrical stimulation. On the basis of their competition and summation, it is argued that the artificial and natural rewards are evaluated in a common currency, represented in an aggregate firing-rate code. Such a code would make it possible for the synchronous, spatially contiguous pattern of neural firing induced by the electrode to simulate a signal normally produced by asynchronous, spatially distributed activity. It is suggested that a unidimensional code of this sort is employed to represent the utility of a goal object. In order for physiological feedback to alter the utility of one natural reward, such as sucrose, without changing the utility of a second natural reward, such as a salt solution, the physiological feedback signals must enter into the computation of utility at a stage of processing in which the representations of the two natural rewards are distinct. However, orderly choice between such rewards implies that their utilities are expressed ultimately in a common neural currency. That physiological feedback alters the rewarding effects of the gustatory stimuli suggests that the physiological feedback signals modulate the value of such natural stimuli at a stage of processing prior to their translation into a common currency. In contrast, physiological feedback would fail to alter the rewarding effect of the electrical stimulation if the electrically evoked signal is injected at a later stage processing, a stage in which different rewards are represented in a common currency. In this view, the signal injected by the electrical stimulation mimics the utility of a natural stimulus but not its sensory quality