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.     

Dynamic reliability models with conditional proportional hazards

A dynamic approach to the stochastic modelling of reliability systems is further explored. This modelling approach is particularly appropriate for load-sharing, software reliability, and multivariate failure-time models, where component failure characteristics are affected by their degree of use, amount of load, or extent of stresses experienced. This approach incorporates the intuitive notion that when a set of components in a coherent system fail at a certain time, there is a jump from one structure function to another which governs the residual lifetimes of the remaining functioning components, and since the component lifetimes are intrinsically affected by the structure function which they constitute, then at such a failure time there should also be a jump in the stochastic structure of the lifetimes of the remaining components. For such dynamically-modelled systems, the stochastic characteristics of their jump times are studied. These properties of the jump times allow us to obtain the properties of the lifetime of the system. In particular, for a Markov dynamic model, specific expressions for the exact distribution functions of the jump times are obtained for a general coherent system, a parallel system, and a series-parallel system. We derive a new family of distribution functions which describes the distributions of the jump times for a dynamically-modelled system.     

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.     

Self‐Construal,Career Decision Self‐Efficacy,and Perceived Barriers Predict Mexican American Women's Life Satisfaction

This study used the social cognitive theory of well‐being (SCTW; Lent, 2004 ) to examine the role of career decision self‐efficacy (CDSE), perceived educational barriers, and independent self‐construal on the life satisfaction of 176 Mexican American college women. A 3‐step hierarchical regression analysis indicated that independent self‐construal, CDSE, and fewer perceived educational barriers significantly predicted greater life satisfaction among Mexican American college women above and beyond the influence of socioeconomic status and generational status. These findings are consistent with SCTW and highlight the need for counselors and researchers to be aware of the role that self‐construal, CDSE, and perceived educational barriers can have on Mexican American women's life satisfaction. Implications for practice at the secondary‐school and university levels are discussed.     

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.     

Utilization of Mixed Distributions in the Calculation of Polarization: The Case of Spain

Social Indicators Research - This study analyzes the evolution of salary polarization in the Spanish labor market. The paper proposes the use of mixed distributions to examine the consequences of...     

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.

     

Social Entrepreneur: Same or Different from the Rest?

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - A social business responds to social problems usually ignored by institutions, mobilizing resources and generating...