Conditional and syllogistic deductive tasks dissociate functionally during premise integration.

Deduction allows us to draw consequences from previous knowledge. Deductive reasoning can be applied to several types of problem, for example, conditional, syllogistic, and relational. It has been assumed that the same cognitive operations underlie solutions to them all; however, this hypothesis remains to be tested empirically. We used event-related fMRI, in the same group of subjects, to compare reasoning-related activity associated with conditional and syllogistic deductive problems. Furthermore, we assessed reasoning-related activity for the two main stages of deduction, namely encoding of premises and their integration. Encoding syllogistic premises for reasoning was associated with activation of BA 44/45 more than encoding them for literal recall. During integration, left fronto-lateral cortex (BA 44/45, 6) and basal ganglia activated with both conditional and syllogistic reasoning. Besides that, integration of syllogistic problems additionally was associated with activation of left parietal (BA 7) and left ventro-lateral frontal cortex (BA 47). This difference suggests a dissociation between conditional and syllogistic reasoning at the integration stage. Our finding indicates that the integration of conditional and syllogistic reasoning is carried out by means of different, but partly overlapping, sets of anatomical regions and by inference, cognitive processes. The involvement of BA 44/45 during both encoding (syllogisms) and premise integration (syllogisms and conditionals) suggests a central role in deductive reasoning for syntactic manipulations and formal/linguistic representations.

Causality and endogeneity: Problems and solutions

Most leadership and management researchers ignore one key design and estimation problem rendering parameter estimates uninterpretable: Endogeneity. We discuss the problem of endogeneity in depth and explain conditions that engender it using examples grounded in the leadership literature. We show how consistent causal estimates can be derived from the randomized experiment, where endogeneity is eliminated by experimental design. We then review the reasons why estimates may become biased (i.e., inconsistent) in non-experimental designs and present a number of useful remedies for examining causal relations with non-experimental data. We write in intuitive terms using nontechnical language to make this chapter accessible to a large audience.

Optimal public rationing and price response

We study optimal public rationing of an indivisible good and private sector price responses. Consumers differ in their wealth and costs of provisions. Due to a limited budget, some consumers must be rationed. Public rationing determines the characteristics of consumers who seek supply from the private sector, where a firm sets prices based on consumers' cost information and in response to the rationing rule. We consider two information regimes. In the first, the public supplier rations consumers according to their wealth information. In equilibrium, the public supplier must ration both rich and poor consumers. Supplying all poor consumers would leave only rich consumers in the private market, and the firm would react by setting a high price. Rationing some poor consumers is optimal, and implements price reduction in the private market. In the second information regime, the public supplier rations consumers according to consumers' wealth and cost information. In equilibrium, consumers are allocated the good if and only if their costs are below a threshold. Wealth information is not used. Rationing based on cost results in higher equilibrium total consumer surplus than rationing based on wealth. [Authors]

Caution on the storage of waters and aqueous solutions in plastic containers for hydrogen and oxygen stable isotope analysis

RATIONALE The choice of containers for storage of aqueous samples between their collection, transport and water hydrogen (2H) and oxygen (18O) stable isotope analysis is a topic of concern for a wide range of fields in environmental, geological, biomedical, food, and forensic sciences. The transport and separation of water molecules during water vapor or liquid uptake by sorption or solution and the diffusive transport of water molecules through organic polymer material by permeation or pervaporation may entail an isotopic fractionation. An experiment was conducted to evaluate the extent of such fractionation. METHODS Sixteen bottle-like containers of eleven different organic polymers, including low and high density polyethylene (LDPE and HDPE), polypropylene (PP), polycarbonate (PC), polyethylene terephthalate (PET), and perfluoroalkoxy-Teflon (PFA), of different wall thickness and size were completely filled with the same mineral water and stored for 659?days under the same conditions of temperature and humidity. Particular care was exercised to keep the bottles tightly closed and prevent loss of water vapor through the seals. RESULTS Changes of up to +5 parts per thousand for d2H values and +2.0 parts per thousand for d18O values were measured for water after more than 1?year of storage within a plastic container, with the magnitude of change depending mainly on the type of organic polymer, wall thickness, and container size. The most important variations were measured for the PET and PC bottles. Waters stored in glass bottles with Polyseal (TM) cone-lined PP screw caps and thick-walled HDPE or PFA containers with linerless screw caps having an integrally molded inner sealing ring preserved their original d2H and d18O values. The carbon, hydrogen, and oxygen stable isotope compositions of the organic polymeric materials were also determined. CONCLUSIONS The results of this study clearly show that for precise and accurate measurements of the water stable isotope composition in aqueous solutions, rigorous sampling and storage procedures are needed both for laboratory standards and for unknown samples. Copyright (c) 2012 John Wiley & Sons, Ltd.

Advancing hypoxic training in team sports: from intermittent hypoxic training to repeated sprint training in hypoxia.

Over the past two decades, intermittent hypoxic training (IHT), that is, a method where athletes live at or near sea level but train under hypoxic conditions, has gained unprecedented popularity. By adding the stress of hypoxia during 'aerobic' or 'anaerobic' interval training, it is believed that IHT would potentiate greater performance improvements compared to similar training at sea level. A thorough analysis of studies including IHT, however, leads to strikingly poor benefits for sea-level performance improvement, compared to the same training method performed in normoxia. Despite the positive molecular adaptations observed after various IHT modalities, the characteristics of optimal training stimulus in hypoxia are still unclear and their functional translation in terms of whole-body performance enhancement is minimal. To overcome some of the inherent limitations of IHT (lower training stimulus due to hypoxia), recent studies have successfully investigated a new training method based on the repetition of short (<30 s) 'all-out' sprints with incomplete recoveries in hypoxia, the so-called repeated sprint training in hypoxia (RSH). The aims of the present review are therefore threefold: first, to summarise the main mechanisms for interval training and repeated sprint training in normoxia. Second, to critically analyse the results of the studies involving high-intensity exercises performed in hypoxia for sea-level performance enhancement by differentiating IHT and RSH. Third, to discuss the potential mechanisms underpinning the effectiveness of those methods, and their inherent limitations, along with the new research avenues surrounding this topic.

Detection of Optimal Models in Parameter Space with Support Vector Machines

The paper proposes an approach aimed at detecting optimal model parameter combinations to achieve the most representative description of uncertainty in the model performance. A classification problem is posed to find the regions of good fitting models according to the values of a cost function. Support Vector Machine (SVM) classification in the parameter space is applied to decide if a forward model simulation is to be computed for a particular generated model. SVM is particularly designed to tackle classification problems in high-dimensional space in a non-parametric and non-linear way. SVM decision boundaries determine the regions that are subject to the largest uncertainty in the cost function classification, and, therefore, provide guidelines for further iterative exploration of the model space. The proposed approach is illustrated by a synthetic example of fluid flow through porous media, which features highly variable response due to the parameter values' combination.