Bayesian modelling of catch in a north-west Atlantic fishery

Summary. We model daily catches of fishing boats in the Grand Bank fishing grounds. We use data on catches per species for a number of vessels collected by the European Union in the context of the Northwest Atlantic Fisheries Organization. Many variables can be thought to influence the amount caught: a number of ship characteristics (such as the size of the ship, the fishing technique used and the mesh size of the nets) are obvious candidates, but one can also consider the season or the actual location of the catch. Our database leads to 28 possible regressors (arising from six continuous variables and four categorical variables, whose 22 levels are treated separately), resulting in a set of 177 million possible linear regression models for the log-catch. Zero observations are modelled separately through a probit model. Inference is based on Bayesian model averaging, using a Markov chain Monte Carlo approach. Particular attention is paid to the prediction of catches for single and aggregated ships.     

Choosing between Cox proportional hazards and logistic models for interval- censored data via bootstrap

This work develops a new methodology in order to discriminate models for interval- censored data based on bootstrap residual simulation by observing the deviance difference from one model in relation to another, according to Hinde (1992). Generally, this sort of data can generate a large number of tied observations and, in this case, survival time can be regarded as discrete. Therefore, the Cox proportional hazards model for grouped data (Prentice & Gloeckler, 1978) and the logistic model (Lawless, 1982) can be fitted by means of generalized linear models. Whitehead (1989) considered censoring to be an indicative variable with a binomial distribution and fitted the Cox proportional hazards model using complementary log-log as a link function. In addition, a logistic model can be fitted using logit as a link function. The proposed methodology arises as an alternative to the score tests developed by Colosimo et al. (2000), where such models can be obtained for discrete binary data as particular cases from the Aranda-Ordaz distribution asymmetric family. These tests are thus developed with a basis on link functions to generate such a fit. The example that motivates this study was the dataset from an experiment carried out on a flax cultivar planted on four substrata susceptible to the pathogen Fusarium oxysoprum . The response variable, which is the time until blighting, was observed in intervals during 52 days. The results were compared with the model fit and the AIC values.     

The effects of regulatory tools on organizational populations

One of the main activities of regulation is the control of market development by influencing the number of firms in an industry, their entry into an industry, and their exit from an industry. Population ecology is used as a framework for explaining both the direct and indirect effects of regulatory activity on entry, exit, and market structure. This framework is then used to derive specific propositions about regulatory effects on entry, exit, and market structure in the health maintenance organization industry.     

Ethnography, Cultural Change and Local Power

The author argues that despite the declaration for the end of ethnography by some North American scholars, ethnography is precisely what is needed for a more nuanced and complex understanding of cultural change. Using snippets of ethnographic observation from the Mexican state of Michoacan, the argument is made that neither "modernization" nor "globalization" are imposed from above, but are woven together with local processes to create institutions and practices which synthesize both the "traditional" and the "modern" in previously unimagined ways. Local people and processes are thus conceived of as dynamic partners in cultural change rather than passive subjects. Ethnography, then, is a fruitful means for uncovering how and the extent to which this is so.     

A Stochastic Model to Assess the Effect of Meat Inspection Practices on the Contamination of the Pig Carcasses

The objective of meat inspection is to promote animal and public health by preventing, detecting, and controlling hazards originating from animals. With the improvements of sanitary level in pig herds, the hazards profile has shifted and the inspection procedures no longer target major foodborne pathogens (i.e., not risk based). Additionally, carcass manipulations performed when searching for macroscopic lesions can lead to cross‐contamination. We therefore developed a stochastic model to quantitatively describe cross‐contamination when consecutive carcasses are submitted to classic inspection procedures. The microbial hazard used to illustrate the model was Salmonella, the data set was obtained from Brazilian slaughterhouses, and some simplifying assumptions were made. The model predicted that due to cross‐contamination during inspection, the prevalence of contaminated carcass surfaces increased from 1.2% to 95.7%, whereas the mean contamination on contaminated surfaces decreased from 1 logCFU/cm² to ?0.87 logCFU/cm², and the standard deviations decreased from 0.65 to 0.19. These results are explained by the fact that, due to carcass manipulations with hands, knives, and hooks, including the cutting of contaminated lymph nodes, Salmonella is transferred to previously uncontaminated carcasses, but in small quantities. These small quantities can easily go undetected during sampling. Sensitivity analyses gave insight into the model performance and showed that the touching and cutting of lymph nodes during inspection can be an important source of carcass contamination. The model can serve as a tool to support discussions on the modernization of pig carcass inspection.     

Classes of protection in urban forest fragments are effectiveless in structuring butterfly assemblages: landscape and forest structure are far better predictors

Urbanization is a major cause of biodiversity loss and disconnection between people and nature. For this reason, the creation and maintenance of green areas as part of the urban landscape is a common practice in cities around the world. These green areas are generally a result of particular public policies regarding how these areas can be accessed, maintained, and how they are connected to other natural fragments in the city. In an effort to investigate aspects of the ecology of such green areas of the city of Curitiba, southern Brazil, the present study measured distinct parameters of the structure of butterfly assemblages from 19 forest fragments of distinct classes of protection, testing the influence of different policies (protection category) on butterfly assemblages. Comparatively, we also tested the predictive power of landscape variables (at distinct scales) and fragment quality (e.g. diameter at breast height, density of vegetation) using Generalized Linear Models (GLMs). Overall, 14,596 individuals belonging to 412 butterfly species were recorded, but values of species diversity and composition are very heterogeneous, indicating that the protection categories do not significantly interfere with the structure of the butterfly assemblages. More important than the protection category is the forest fragment quality and landscape connectivity. Our models showed that degraded fragments tend to present a specific butterfly composition, whereas the more urbanized landscape have poor butterfly species richness. These results reinforce the importance of implementing public policies that prioritize the conservation of the quality of forest fragments in every class of protection, as well as the conservation of forest fragments throughout the urban landscape.

     

Misestimating Betting Behavior: The Role of Negative Asymmetries in Emotional Self Prediction

This paper addresses the role of negative asymmetries in emotional self-prediction by looking at the extent to which individuals misestimate their own betting behavior in sequential gambles. In a series of three experimental studies, we demonstrate that losses lead to higher than planned bets whereas bets are on average carried over after gains. Such asymmetric deviations from the plan emerge (1) when monetary and non-monetary incentives are used, and (2) when participants face fair and unfair gambles. The asymmetry is based on people’s inability to predict how much the negative emotions generated by a bad experience (e.g. the loss) will influence them to put more effort (e.g. bet more) than planned in an attempt to re-establish a homeostatic state in the prospect of a good experience (e.g. winning).     

The Ruins of the New Argentina: Peronism and the Remaking of San Juan after the 1944 Earthquake

Ted Robert Gurr, Rogues, Rebels, and Reformers. A Political History of Urban Crime and Conflict (1977), xii+192 (Sage, Beverly Hills and London, £7.50)     

Managing Logistics in Regional Banknote Supply Chain Under Security Concerns

We study the logistics problem faced by Regional Branches (RBs) of a central bank in managing the currency supply under security concerns. While making banknote supply decisions to Sub‐Branches (SBs), the management of RB must achieve two goals simultaneously: (i) guarantee that each SB has sufficient inventories of all denominations of banknotes to satisfy the demands from all commercial banks within its service area, and (ii) control the annual spending on this banknote supply operation. Due to security concerns, the following methods are implemented in the process of transporting banknotes: (i) the capacity of a cash truck is limited by the total face value (instead of the physical space) of banknotes, and (ii) empty decoy trucks are deployed along with the trucks filled with banknotes. After deriving a polynomial‐time strategy to guarantee an optimal solution for the special Bin‐Packing Problem faced in this study, we provide an exact formulation for the RB's supply planning problem. We also propose several polynomial‐time algorithms for deriving either optimal or near‐optimal solutions for the problem under different settings. Using the weekly demand data obtained from the central bank, we verify the performance of our algorithms, and analyze the impacts of changes in these features and in the fleet capacity on the total cost incurred by an RB under various scenarios.     

An F-type test for detecting departure from monotonicity in a functional linear model

When studying associations between a functional covariate and scalar response using a functional linear model (FLM), scientific knowledge may indicate possible monotonicity of the unknown parameter curve. In this context, we propose an F-type test of monotonicity, based on a full versus reduced nested model structure, where the reduced model with monotonically constrained parameter curve is nested within an unconstrained FLM. For estimation under the unconstrained FLM, we consider two approaches: penalised least-squares and linear mixed model effects estimation. We use a smooth then monotonise approach to estimate the reduced model, within the null space of monotone parameter curves. A bootstrap procedure is used to simulate the null distribution of the test statistic. We present a simulation study of the power of the proposed test, and illustrate the test using data from a head and neck cancer study.