Inclusion of Fresh Pork Pancreas in Raw Pork Meat-Based Diets for African Wildcats (Felis silvestris tristrami) does not Impact Macronutrient Digestibility

Apparent total tract macronutrient digestibility was evaluated in 4 African wildcats (Felis silvestris tristrami) fed beef or pork-based raw meat diets. Diets were formulated to meet nutrient requirements of cats (NRC, 2006). Cats were fed isocaloric amounts of either control (standard beef raw diet) or pork-based raw diets containing 0, 3, or 5% added raw pancreas, in four 14-day periods. Protein digestibility was higher for pork diets compared with beef and inclusion up to 5% fresh pancreas did not increase macronutrient digestibility in healthy animals. Raw pork can be fed to exotic felids as a viable alternative to standard beef-based zoological formulations

A linear theory for control of non-linear stochastic systems

We address the role of noise and the issue of efficient computation in stochastic optimal control problems. We consider a class of non-linear control problems that can be formulated as a path integral and where the noise plays the role of temperature. The path integral displays symmetry breaking and there exist a critical noise value that separates regimes where optimal control yields qualitatively different solutions. The path integral can be computed efficiently by Monte Carlo integration or by Laplace approximation, and can therefore be used to solve high dimensional stochastic control problems.Comment: 5 pages, 3 figures. Accepted to PR

Algorithms for identification and categorization

The main features of a family of efficient algorithms for recognition and classification of complex patterns are briefly reviewed. They are inspired in the observation that fast synaptic noise is essential for some of the processing of information in the brain.Comment: 6 pages, 5 figure

Update on biomarkers to monitor clinical efficacy response during and post treatment in allergen immunotherapy

Allergen immunotherapy (AIT) is an immune modulating treatment for allergic diseases. Although highly effective, some patients do not respond to the treatment. To date there are no surrogate biomarkers that are predictive of the clinical response to AIT. More and more is known about the underlying immunological mechanism involved in AIT. Through modulation of both innate and adaptive immune responses, involving reduced ILC2 and enhanced Treg and Breg induction and functionality, along with induction of IgG4 antibody production which have the capacity to inhibit both allergen-induced basophil responsiveness and CD23-mediated IgE-facilitated allergen presentation, the result is an immune skewing towards a more balanced Type I response. So far, however there is not a clear correlation with the observed immunological changes and predictive correlates of clinical efficacy. The most promising biomarker of successful AIT is IgE-FAB as a reflection of functional IgG4. Cellular responses and cytokine analysis gives a great deal of insight into the mechanisms of AIT but may not represent useful or indeed reliable biomarkers in a clinical setting. There is a need for more research for confirmation and interpretation of the possible association with biomarkers and clinical response to AIT

Path integrals and symmetry breaking for optimal control theory

This paper considers linear-quadratic control of a non-linear dynamical system subject to arbitrary cost. I show that for this class of stochastic control problems the non-linear Hamilton-Jacobi-Bellman equation can be transformed into a linear equation. The transformation is similar to the transformation used to relate the classical Hamilton-Jacobi equation to the Schr\"odinger equation. As a result of the linearity, the usual backward computation can be replaced by a forward diffusion process, that can be computed by stochastic integration or by the evaluation of a path integral. It is shown, how in the deterministic limit the PMP formalism is recovered. The significance of the path integral approach is that it forms the basis for a number of efficient computational methods, such as MC sampling, the Laplace approximation and the variational approximation. We show the effectiveness of the first two methods in number of examples. Examples are given that show the qualitative difference between stochastic and deterministic control and the occurrence of symmetry breaking as a function of the noise.Comment: 21 pages, 6 figures, submitted to JSTA

Barriers and facilitators perceived by physicians when using prediction models in practice

Objectives Prediction models may facilitate risk-based management of health care conditions. In a large cluster-randomized trial, presenting calculated risks of postoperative nausea and vomiting (PONV) to physicians (assistive approach) increased risk-based management of PONV. This increase did not improve patient outcome - that is, PONV incidence. This prompted us to explore how prediction tools guide the decision-making process of physicians. Study Design and Setting Using mixed methods, we interviewed eight physicians to understand how predicted risks were perceived by the physicians and how they influenced decision making. Subsequently, all 57 physicians of the trial were surveyed for how the presented risks influenced their perceptions. Results Although the prediction tool made physicians more aware of PONV prevention, the physicians reported three barriers to use predicted risks in their decision making. PONV was not considered an outcome of utmost importance; decision making on PONV prophylaxis was mostly intuitive rather than risk based; prediction models do not weigh benefits and risks of prophylactic drugs. Conclusion Combining probabilistic output of the model with their clinical experience may be difficult for physicians, especially when their decision-making process is mostly intuitive. Adding recommendations to predicted risks (directive approach) was considered an important step to facilitate the uptake of a prediction tool

How Multidisciplinary is Gamification Research? : Results from a Scoping Review

Gamification has been repeatedly framed as an emerging multidisciplinary research field. However, it is unclear how multidisciplinary the field actually is. To answer this question, this paper presents initial results of a broader scoping review of gamification research published between 2010 and 2016. Close to 2,000 peer-reviewed English-language journal and conference papers were identified across 11 databases and categorized by discipline. Results indicate an explosive growth of literature peaking in 2015. Early on, Information and Computing Science dominated the field, to be overtaken by the sum of other disciplines in 2013, education, economics and tourism in specific. This indicates that gamification was initially a field within computer science and HCI and has only recently become truly multi-disciplinary

Survey propagation at finite temperature: application to a Sourlas code as a toy model

In this paper we investigate a finite temperature generalization of survey propagation, by applying it to the problem of finite temperature decoding of a biased finite connectivity Sourlas code for temperatures lower than the Nishimori temperature. We observe that the result is a shift of the location of the dynamical critical channel noise to larger values than the corresponding dynamical transition for belief propagation, as suggested recently by Migliorini and Saad for LDPC codes. We show how the finite temperature 1-RSB SP gives accurate results in the regime where competing approaches fail to converge or fail to recover the retrieval state