Tolerance spaces and behavior

Tolerance spaces used in human behavior model

Identification of control strategies to manage microbiological risks in typical pork products

Starting from 2009 a pilot project has been implemented by a local veterinary service of the Veneto region of Italy (AZ-ULSS 8) in collaboration with IZSVe (Istituto Zooprofilattico Sperimentale delle Venezie) with the aim of identifying control measures based on own-checks and official controls in order to manage microbiological risks related to traditional pork fermented sausages (Italian salami end soppresse) consumption. According to the data obtained a control strategy based on microbiological tests performed by the Competent Authority (CA) and the monitoring of the weight decrease in sausages by the food business operator (FBO) has been implemented for 2010-2011 production season

Functional Brain Imaging Predicts Public Health Campaign Success

Mass media can powerfully affect health decision-making. Pre-testing through focus groups or surveys is a standard, though inconsistent, predictor of effectiveness. Converging evidence demonstrates that activity within brain systems associated with self-related processing can predict individual behavior in response to health messages. Preliminary evidence also suggests that neural activity in small groups can forecast population-level campaign outcomes. Less is known about the psychological processes that link neural activity and population-level outcomes, or how these predictions are affected by message content. We exposed 50 smokers to antismoking messages and used their aggregated neural activity within a ‘self-localizer’ defined region of medial prefrontal cortex to predict the success of the same campaign messages at the population level (n = 400 000 emails). Results demonstrate that: (i) independently localized neural activity during health message exposure complements existing self-report data in predicting population-level campaign responses (model combined R2 up to 0.65) and (ii) this relationship depends on message content—self-related neural processing predicts outcomes in response to strong negative arguments against smoking and not in response to compositionally similar neutral images. These data advance understanding of the psychological link between brain and large-scale behavior and may aid the construction of more effective media health campaigns

Surface-modified polysulfone membranes: aqueous phase oxidation via persulfate radical

Peer reviewed: YesNRC publication: Ye

Constraint Based Diagnosis Algorithms For Multiprocessors

Constraint-based diagnosis algorithms for multiprocessors A. Petri, P. Urban, J. Altmann, M. Dal Cin, E. Selenyi, K. Tilly, A. Pataricza In the latest years, new ideas appeared in system level diagnosis of multiprocessor systems. In contrary to the traditional diagnosis models (like PMC, BGM, etc.) which use strictly graph-oriented methods to determine the faulty components in a system, these new theories prefer AI-based algorithms, especially CSP methods. Syndrome decoding, the basic problem of self-diagnosis, can be easily transformed into constraints between the state of the tester and the tested components. Therefore, the diagnosis algorithm can be derived from a special constraint solving algorithm. The "benign" nature of the constraints (all their variables, representing the fault states of the components, have a very limited domain; the constraints are simple and similar to each other) reduces the algorithm's complexity so it can be converted to a powerful distributed diagnosis method with a minimal overhead. Experimental algorithms (using both centralized and distributed approach) were implemented for a Parsytec GC massively parallel multiprocessor system

Genome-Wide Analysis of Subependymomas Shows Underlying Chromosomal Copy Number Changes Involving Chromosomes 6, 7, 8 and 14 in a Proportion of Cases

Subependymomas (SE) are slow-growing brain tumors that tend to occur within the ventricles of middle-aged and elderly adults. The World Health Organization classifies these tumors within the ependymoma group. Previous limited analysis of this tumor type had not revealed significant underlying cytogenetic abnormalities