Scale and Nature of Sulcification Patterns

Sulci are surface folds commonly seen in strained soft elastomers and form via a strongly subsubcriticalcritical, yet scale-free instability. Treating the threshold for nonlinear instability as a nonlinear critical point, we explain the nature of sulcus patterns in terms of the scale and translation symmetries which are broken by the formation of an isolated, small sulcus. Our perturbative theory and simulations show that sulcus formation in a thick, compressed slab can arise either as a supercritical or as a weakly subcritical bifurcation relative to this nonlinear critical point, depending on the boundary conditions. An infinite number of competing, equilibrium patterns simultaneously emerge at this critical point, but the one selected has the lowest energy. We give a simple, physical explanation for the formation of these sulcification patterns using an analogy to a solid-solid phase transition with a finite energy of transformation.Comment: 4 pages, 2 figures; new title and abstract; clarification of the role of pre-stress following Eq. 5. Revised and updated to agree with published versio

Cosmological Argument: A Pragmatic Defense

We formulate a sort of "generic" cosmological argument, i.e., a cosmological argument that shares premises (e.g., "contingent, concretely existing entities have a cause") with numerous versions of the argument. We then defend each of the premises by offering pragmatic arguments for them. We show that an endorsement of each premise will lead to an increase in expected utility; so in the absence of strong evidence that the premises are false, it is rational to endorse them. Therefore, it is rational to endorse the cosmological argument, and so rational to endorse theism. We then consider possible objection

An overview on the role and potential of forage production on lowland organic livestock farms

This report was presented at the UK Organic Research 2002 Conference of the Colloquium of Organic Researchers (COR). This paper outlines some of the factors influencing the level of forage production on organic lowland farms. Optimal forage production is achieved by maintaining soil fertility, providing a balance between N-fixing and N-demanding crops and producing sufficient quantities of quality feed to meet the requirements of the organic livestock enterprise. A key objective for organic systems is to increase the efficiency of forage production by improving the nutrient input/output balance of the wholefarm system. Improving forage quality reduces the requirement for external feed sources, leading to increased self-sufficiency in the wholefarm system. Legumes provide the main source of nitrogen for forage production with energy shortage and an erratic supply of protein the main limiting factors in the provision of balanced diets from home-grown crops

Prediction of infectious disease epidemics via weighted density ensembles

Accurate and reliable predictions of infectious disease dynamics can be valuable to public health organizations that plan interventions to decrease or prevent disease transmission. A great variety of models have been developed for this task, using different model structures, covariates, and targets for prediction. Experience has shown that the performance of these models varies; some tend to do better or worse in different seasons or at different points within a season. Ensemble methods combine multiple models to obtain a single prediction that leverages the strengths of each model. We considered a range of ensemble methods that each form a predictive density for a target of interest as a weighted sum of the predictive densities from component models. In the simplest case, equal weight is assigned to each component model; in the most complex case, the weights vary with the region, prediction target, week of the season when the predictions are made, a measure of component model uncertainty, and recent observations of disease incidence. We applied these methods to predict measures of influenza season timing and severity in the United States, both at the national and regional levels, using three component models. We trained the models on retrospective predictions from 14 seasons (1997/1998 - 2010/2011) and evaluated each model's prospective, out-of-sample performance in the five subsequent influenza seasons. In this test phase, the ensemble methods showed overall performance that was similar to the best of the component models, but offered more consistent performance across seasons than the component models. Ensemble methods offer the potential to deliver more reliable predictions to public health decision makers.Comment: 20 pages, 6 figure

Dominance of extreme statistics in a prototype many-body Brownian ratchet

Many forms of cell motility rely on Brownian ratchet mechanisms that involve multiple stochastic processes. We present a computational and theoretical study of the nonequilibrium statistical dynamics of such a many-body ratchet, in the specific form of a growing polymer gel that pushes a diffusing obstacle. We find that oft-neglected correlations among constituent filaments impact steady-state kinetics and significantly deplete the gel's density within molecular distances of its leading edge. These behaviors are captured quantitatively by a self-consistent theory for extreme fluctuations in filaments' spatial distribution.Comment: 5 pages with 3 figures + 20 pages of Supplementary Material with 2 figures. Updated to agree with published version; published as a Communication in J. Chem. Phy

Restricted Opportunities, Personal Choices, Ineffective Policies: What Explains Food Insecurity in Oregon?

This study examines the extent to which household demographics, local economic and social conditions, and federal food security programs explain the likelihood of household food insecurity in Oregon. Between 1999 and 2001, Oregon had the highest average rate of hunger in the nation and ranked in the top five states with respect to food insecurity. Statistical analyses using a multivariate logit model reveal that food insecurity is influenced by much more than demographics and individual choices. County-level factors such as residential location (urban versus rural) and housing costs significantly affect the likelihood that families will be food insecure.food insecurity, food stamps, hunger, rural residence, Food Security and Poverty,