ECONOMIC ISSUES ASSOCIATED WITH FOOD SAFETY

Food Consumption/Nutrition/Food Safety,

AN ECONOMETRIC MODEL OF THE MARKET FOR NEW ENGLAND GROUNDFISH

This paper develops an economic model of the New England groundfish market. A multi-sector, multi-level econometric model is estimated using data from 1970 to 1982. The parameters of the estimated model are used to characterize consumer demand for groundfish and related products. Retail and exvessel demands for fresh and frozen groundfish fillets are found to be highly elastic. Fresh fillets especially show high income elasticity of demand, reflecting their status as a luxury good. Only a very small and statistically weak relationship was found between the prices of imported groundfish and domestic exvessel prices indicating that proposals to assist the domestic industry via tariffs may be ineffectual.Marketing,

THE ECONOMICS OF IMPROVING FOOD SAFETY

Food Consumption/Nutrition/Food Safety,

MODELING THE COSTS OF FOOD SAFETY REGULATION

Food safety, regulatory costs, cost/benefit analysis, Food Consumption/Nutrition/Food Safety,

The Ambiguity of Simplicity

A system's apparent simplicity depends on whether it is represented classically or quantally. This is not so surprising, as classical and quantum physics are descriptive frameworks built on different assumptions that capture, emphasize, and express different properties and mechanisms. What is surprising is that, as we demonstrate, simplicity is ambiguous: the relative simplicity between two systems can change sign when moving between classical and quantum descriptions. Thus, notions of absolute physical simplicity---minimal structure or memory---at best form a partial, not a total, order. This suggests that appeals to principles of physical simplicity, via Ockham's Razor or to the "elegance" of competing theories, may be fundamentally subjective, perhaps even beyond the purview of physics itself. It also raises challenging questions in model selection between classical and quantum descriptions. Fortunately, experiments are now beginning to probe measures of simplicity, creating the potential to directly test for ambiguity.Comment: 7 pages, 6 figures, http://csc.ucdavis.edu/~cmg/compmech/pubs/aos.ht

Occam's Quantum Strop: Synchronizing and Compressing Classical Cryptic Processes via a Quantum Channel

A stochastic process's statistical complexity stands out as a fundamental property: the minimum information required to synchronize one process generator to another. How much information is required, though, when synchronizing over a quantum channel? Recent work demonstrated that representing causal similarity as quantum state-indistinguishability provides a quantum advantage. We generalize this to synchronization and offer a sequence of constructions that exploit extended causal structures, finding substantial increase of the quantum advantage. We demonstrate that maximum compression is determined by the process's cryptic order---a classical, topological property closely allied to Markov order, itself a measure of historical dependence. We introduce an efficient algorithm that computes the quantum advantage and close noting that the advantage comes at a cost---one trades off prediction for generation complexity.Comment: 10 pages, 6 figures; http://csc.ucdavis.edu/~cmg/compmech/pubs/oqs.ht

Information Accessibility and Cryptic Processes: Linear Combinations of Causal States

We show in detail how to determine the time-reversed representation of a stationary hidden stochastic process from linear combinations of its forward-time $\epsilon$-machine causal states. This also gives a check for the $k$-cryptic expansion recently introduced to explore the temporal range over which internal state information is spread.Comment: 6 pages, 9 figures, 2 tables; http://users.cse.ucdavis.edu/~cmg/compmech/pubs/iacplcocs.ht

Conditional exponents, entropies and a measure of dynamical self-organization

In dynamical systems composed of interacting parts, conditional exponents, conditional exponent entropies and cylindrical entropies are shown to be well defined ergodic invariants which characterize the dynamical selforganization and statitical independence of the constituent parts. An example of interacting Bernoulli units is used to illustrate the nature of these invariants.Comment: 6 pages Latex, 1 black and white and 2 color figures, replacement of damaged gif file

Macaques preferentially attend to visual patterns with higher fractal dimension contours.

Animals' sensory systems evolved to efficiently process information from their environmental niches. Niches often include irregular shapes and rough textures (e.g., jagged terrain, canopy outlines) that must be navigated to find food, escape predators, and master other fitness-related challenges. For most primates, vision is the dominant sensory modality and thus, primates have evolved systems for processing complicated visual stimuli. One way to quantify information present in visual stimuli in natural scenes is evaluating their fractal dimension. We hypothesized that sensitivity to complicated geometric forms, indexed by fractal dimension, is an evolutionarily conserved capacity, and tested this capacity in rhesus macaques (Macaca mulatta). Monkeys viewed paired black and white images of simulated self-similar contours that systematically varied in fractal dimension while their attention to the stimuli was measured using noninvasive infrared eye tracking. They fixated more frequently on, dwelled for longer durations on, and had attentional biases towards images that contain boundary contours with higher fractal dimensions. This indicates that, like humans, they discriminate between visual stimuli on the basis of fractal dimension and may prefer viewing informationally rich visual stimuli. Our findings suggest that sensitivity to fractal dimension may be a wider ability of the vertebrate vision system

Prediction, Retrodiction, and The Amount of Information Stored in the Present

We introduce an ambidextrous view of stochastic dynamical systems, comparing their forward-time and reverse-time representations and then integrating them into a single time-symmetric representation. The perspective is useful theoretically, computationally, and conceptually. Mathematically, we prove that the excess entropy--a familiar measure of organization in complex systems--is the mutual information not only between the past and future, but also between the predictive and retrodictive causal states. Practically, we exploit the connection between prediction and retrodiction to directly calculate the excess entropy. Conceptually, these lead one to discover new system invariants for stochastic dynamical systems: crypticity (information accessibility) and causal irreversibility. Ultimately, we introduce a time-symmetric representation that unifies all these quantities, compressing the two directional representations into one. The resulting compression offers a new conception of the amount of information stored in the present.Comment: 17 pages, 7 figures, 1 table; http://users.cse.ucdavis.edu/~cmg/compmech/pubs/pratisp.ht