Modeling Cholinesterase Activity for Human Dietary Risk Assessment of Carbamate Insecticides

This article demonstrates statistical models to quantify the interaction between a carbamate insecticide and acetylcholinesterase. Carbamates are a class of chemicals that inhibit the activity of acetylcholinesterase in humans, an enzyme involved in the regulation of the neurotransmitter acetylcholine. Following exposure to a carbamate insecticide, we specifically address (1) if acetylcholinesterase activity recovers to its level of preexposure activity; (2) the level of inhibition of acetylcholinesterase activity; (3) the recovery time of acetylcholinesterase activity to its preexposure level for a typical individual; and (4) the upper percentiles of the recovery time of acetycholinesterase activity across individuals. A nonlinear mixed-effects model is fitted to data from a repeated measures experiment conducted with human volunteers randomly assigned to a control and four dose groups. Repeated measurements were taken prior to exposure and at 1, 2, 4, 6, 8, and 21 hours after exposure to the carbamate aldicarb. It was found that full recovery did occur. Inhibition at 1 hour was estimated with maximum inhibition most likely occurring prior to 1-hour postexposure. In addition, recovery was rapid even for sensitive individuals. Given this information, the potential effect from exposure to a carbamate consumed in the diet during a day can be quantitatively assessed.     

Hitting the Target…but Missing the Point: Resolving the Paradox of Strategic Transition

Many firms are undertaking a strategic shift from cost leadership (through process management) to differentiation based on radical product innovation. Success in such transitions has been mixed, as have findings on the role of performance measurement and management in the process. This study explores the challenges of managing this transition, with specific focus on the role of performance metrics. Conventional wisdom indicates that top management can use metrics - measures, standards and rewards - to communicate new directions and priorities. Based on findings reported in this paper, this approach is found to be potentially fatally flawed when applied to a situation where both the corporate goals and the means of achieving these goals have changed. Using detailed data drawn from a multi-level analysis of a major international corporation undertaking such a strategic shift, this study explores the process by which metrics are formed and deployed, and the impact of this process on the ability of the firm to successfully achieve the change. Using measures such as the percentage of sales from new products, top management in the case study had the impression that the strategy was being successfully carried out by the various operating divisions. However, radical innovation (the desired result) had been replaced by incremental innovation. This study identifies the reasons for this situation. A major finding is that the performance measurement and management system can both allow and conceal this failure. Firms trying to significantly change their strategic directions must change their selection of performance metrics to focus less on the intended outcomes and more on the means by which these outcomes are to be achieved.     

A quadratic lower bound for Rocchio’s similarity-based relevance feedback algorithm with a fixed query updating factor

Rocchio’s similarity-based relevance feedback algorithm, one of the most important query reformation methods in information retrieval, is essentially an adaptive supervised learning algorithm from examples. In practice, Rocchio’s algorithm often uses a fixed query updating factor. When this is the case, we strengthen the linear Ω(n) lower bound obtained by Chen and Zhu (Inf. Retr. 5:61–86, 2002) and prove that Rocchio’s algorithm makes Ω(k(n−k)) mistakes in searching for a collection of documents represented by a monotone disjunction of k relevant features over the n-dimensional binary vector space {0,1} ⁿ , when the inner product similarity measure is used. A quadratic lower bound is obtained when k is linearly proportional to n. We also prove an O(k(n−k)³) upper bound for Rocchio’s algorithm with the inner product similarity measure in searching for such a collection of documents with a constant query updating factor and a zero classification threshold.     

Education as a social agreement

This article shows that the main hypotheses used in the economic literature to explain the existence of low-skill traps are not necessary. In particular, if we relax two strong assumptions, those of perfect information in the labor market and individual homogeneity, less-developed countries may remain caught in a poverty trap even when there are not intergenerational or intertemporal spillovers, intersectoral complementarities, increasing returns to scale or credit market imperfections. Due to the lack of coordination among workers, the role played by some institutions such as universities or unions in escaping the trap becomes crucial. A numerical calibration of the model supports our conclusions.     

Modelling state anxiety in a medical setting: The mediating role of embarrassment

Abstract

Little research has been conducted on the relationship between state anxiety and embarrassment in a medical setting. In the prcsent study, several personality and situational variables were examined as antecedents of state anxiety. A total of 277 patients who had come for an examination either as a response to a melanoma screening programme or due to a dermatological complaint participated in the study. Results showed that purpose of patient visit, physician's recommendation, trait anxiety, and embarrassment, were each correlated with state anxiety. Furthermore, using mediated regression analysis as well as structural equations, embarrassment was found to mediate between the above antecedents and state anxiety. The authors proposed a model linking all the variables and identifying their paths. Theoretical and practical considerations of the findings are discussed.