Individual and household willingness to pay for public goods

The issue of whether willingness to pay (WTP) for the benefits generated by a public good should be elicited on an individual or on a household basis is addressed. Differences between individual and household WTP may arise when members of the household are mutually altruistic. It is shown that, for general specifications of altruism, household WTP is less than the sum of household members' individual WTP. Implications for the choice between household and individual measures of WTP are considered, and issues in the elicitation of household WTP are addressed.

Stochastic structure and individual-tree growth models

The majority of past and current individual-tree growth modelling methodologies have failed to characterise and incorporate structured stochastic components. Rather, they have relied on deterministic predictions or have added an unstructured random component to predictions. In particular, spatial stochastic structure has been neglected, despite being present in most applications of individual-tree growth models. Spatial stochastic structure (also called spatial dependence or spatial autocorrelation) eventuates when spatial influences such as competition and micro-site effects are not fully captured in models. Temporal stochastic structure (also called temporal dependence or temporal autocorrelation) eventuates when a sequence of measurements is taken on an individual-tree over time, and variables explaining temporal variation in these measurements are not included in the model. Nested stochastic structure eventuates when measurements are combined across sampling units and differences among the sampling units are not fully captured in the model. This review examines spatial, temporal, and nested stochastic structure and instances where each has been characterised in the forest biometry and statistical literature. Methodologies for incorporating stochastic structure in growth model estimation and prediction are described. Benefits from incorporation of stochastic structure include valid statistical inference, improved estimation efficiency, and more realistic and theoretically sound predictions. It is proposed in this review that individual-tree modelling methodologies need to characterise and include structured stochasticity. Possibilities for future research are discussed. (C) 2001 Elsevier Science B.V. All rights reserved.

Analyses of Individual and Organizational Competences Associated with Knowledge Management Practice

The research analyzed critical aspects of the knowledge management process based on the analyses of knowledge, abilities and attitudes required to individual knowledge workers and to organizations responsible for the management process. In the present work a characterization of the knowledge management process was developed and information and knowledge wokers defined. Competence concept was discussed and specialists gave opinions about critical competences to knowledge management process. The opinions were organized and analyzed by the Delphi method. The results aggregate to the management context by discussing an extremely important resource to organizations - knowledge - and because they support its management process. The research identified wide critical aspects that are compatible with current organizational challenges, directing the process management to important themes as: the worker able to create, the organization able to convert individual knowledge into organizational knowledge, knowledge sharing while still tacit, the maximization organizational knowledge use, information and knowledge generation and preservation, among others important topics to be observed by knowledge workers and by administrators responsible for the knowledge management process.

Individual differences in motivated social cognition: The case of self-serving information processing

Three experiments examined the hypothesis that people show consistency in motivated social cognitive processing across self-serving domains. Consistent with this hypothesis, Experiment 1 revealed that people who rated a task at which they succeeded as more important than a task at which they failed also cheated on a series of math problems, but only when they could rationalize their cheating as unintentional. Experiment 2 replicated this finding and demonstrated that a self-report measure of self-deception did not predict this rationalized cheating. Experiment 3 replicated Experiments 1 and 2 and ruled out several alternative explanations. These experiments suggest that people who show motivated processing in ego-protective domains also show motivated processing in extrinsic domains. These experiments also introduce a new measurement procedure for differentiating between intentional versus rationalized cheating.

Hyperplane navigation: A method to set individual scores in fMRI group datasets

Recent studies have demonstrated that spatial patterns of fMRI BOLD activity distribution over the brain may be used to classify different groups or mental states. These studies are based on the application of advanced pattern recognition approaches and multivariate statistical classifiers. Most published articles in this field are focused on improving the accuracy rates and many approaches have been proposed to accomplish this task. Nevertheless, a point inherent to most machine learning methods (and still relatively unexplored in neuroimaging) is how the discriminative information can be used to characterize groups and their differences. In this work, we introduce the Maximum Uncertainty Linear Discrimination Analysis (MLDA) and show how it can be applied to infer groups` patterns by discriminant hyperplane navigation. In addition, we show that it naturally defines a behavioral score, i.e., an index quantifying the distance between the states of a subject from predefined groups. We validate and illustrate this approach using a motor block design fMRI experiment data with 35 subjects. (C) 2008 Elsevier Inc. All rights reserved.

Individual risk prediction of nodal and distant metastasis for patients with typical bronchial carcinoid tumors

Objective: Bronchial typical carcinoid tumors are tow-grade malignancies. However, metastases are diagnosed in some patients. Predicting the individual risk of these metastases to determine patients eligible for a radical lymphadenectomy and patients to be followed-up because of distant metastasis risk is relevant. Our objective was to screen for predictive criteria of bronchial typical carcinoid tumor aggressiveness based on a logistic regression model using clinical, pathological and biomolecular data. Methods: A multicenter retrospective cohort study, including 330 consecutive patients operated on for bronchial typical carcinoid tumors and followed-up during a period more than 10 years in two university hospitals was performed. Selected data to predict the individual risk for both nodal and distant metastasis were: age, gender, TNM staging, tumor diameter and location (central/peripheral), tumor immunostaining index of p53 and Ki67, Bcl2 and the extracellular density of neoformed microvessels and of collagen/elastic extracellular fibers. Results: Nodal and distant metastasis incidence was 11% and 5%, respectively. Univariate analysis identified all the studied biomarkers as related to nodal metastasis. Multivariate analysis identified a predictive variable for nodal metastasis: neo angiogenesis, quantified by the neoformed pathological microvessels density. Distant metastasis was related to mate gender. Discussion: Predictive models based on clinical and biomolecular data could be used to predict individual risk for metastasis. Patients under a high individual risk for lymph node metastasis should be considered as candidates to mediastinal lymphadenectomy. Those under a high risk of distant metastasis should be followed-up as having an aggressive disease. Conclusion: Individual risk prediction of bronchial typical carcinoid tumor metastasis for patients operated on can be calculated in function of biomolecular data. Prediction models can detect high-risk patients and help surgeons to identify patients requiring radical lymphadenectomy and help oncologists to identify those as having an aggressive disease requiring prolonged follow-up. (C) 2008 European Association for Cardio-Thoracic Surgery. Published by Elsevier B.V. All rights reserved.

Individual vulnerability to escalated aggressive behavior by a low dose of alcohol: decreased serotonin receptor mRNA in the prefrontal cortex of male mice

Low to moderate doses of alcohol consumption induce heightened aggressive behavior in some, but not all individuals. Individual vulnerability for this nonadaptive behavior may be determined by an interaction of genetic and environmental factors with the sensitivity of alcohol`s effects on brain and behavior. We used a previously established protocol for alcohol oral self-administration and characterized alcohol-heightened aggressive (AHA) mice as compared with alcohol non-heightened (ANA) counterparts. A week later, we quantified mRNA steady state levels of several candidate genes in the serotonin [5-hydroxytryptamine (5-HT)] system in different brain areas. We report a regionally selective and significant reduction of all 5-HT receptor subtype transcripts, except for 5-HT(3), in the prefrontal cortex of AHA mice. Comparable gene expression profile was previously observed in aggressive mice induced by social isolation or by an anabolic androgenic steroid. Additional change in the 5-HT(1B) receptor transcripts was seen in the amygdala and hypothalamus of AHA mice. In both these areas, 5-HT(1B) mRNA was elevated when compared with ANA mice. In the hypothalamus, AHA mice also showed increased transcripts for 5-HT(2A) receptor. In the midbrain, 5-HT synthetic enzyme, 5-HT transporter and 5-HT receptors mRNA levels were similar between groups. Our results emphasize a role for postsynaptic over presynaptic 5-HT receptors in mice which showed escalated aggression after the consumption of a moderate dose of alcohol. This gene expression profile of 5-HT neurotransmission components in the brain of mice may suggest a vulnerability trait for alcohol-heightened aggression.