Executive Self, Self-Esteem, and Negative Affectivity: Relations at the Phenotypic and Genotypic Level.

Complementary approaches examined the relations among executive self, self-esteem, and negative affectivity. A cross-sectional (N = 4,242) and a longitudinal (N = 158) study established that self-esteem mediated the relation between executive self and negative affectivity. A 3rd study (N = 878 twin pairs) replicated this pattern and examined genetic and environmental influences underlying all 3 phenotypes. Covariation among the 3 phenotypes reflected largely common genetic influences, although unique genetic effects explained variability in both executive self and negative affectivity. Executive self was influenced by shared environmental influences unique from those affecting self-esteem and negative affectivity. Nonshared environmental influences accounted for the majority of variance in each construct and were primarily unique to each. The unique genetic and nonshared environmental influences support the proposition that the executive self, self-esteem, and negative affectivity capture distinct and important differences between people. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Theoretical Correlations and Measured Correlations: Relating Recognition and Recall in Four Distributed Memory Models.

This article addresses the relation between item recognition and associative (cued) recall. Going beyond measures of performance on each task, the analysis focuses on the degree to which the contingency between successful recognition and successful recall of a studied item reflects the commonality of memory processes underlying the recognition and recall tasks. Specifically, 4 classes of distributed memory models are assessed for their ability to account for the relatively invariant correlation (≈ .5) between successive recognition and recall. Basic versions of each model either under- or overpredict the intertask correlation. Introducing variability in goodness-of-encoding and response criteria, as well as output encoding, enabled all 4 models to reproduce the moderate intertask correlation and the increase in correlation observed in 2 mixed-list experiments. This model-based analysis provides a general theoretical framework for interpreting contingencies between successive memory tests. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Parameterized fuzzy operators in fuzzy decision making

The basic operations of fuzzy sets, such as negation, intersection, and union, usually are computed by applying the one‐complement, minimum, and maximum operators to the membership functions of fuzzy sets. However, different decision agents may have different perceptions for these fuzzy operations. In this article, the concept of parameterized fuzzy operators will be introduced. A parameter α will be used to represent the degree of softness. The variance of α captures the differences of decision agents' subjective attitudes and characteristics, which result in their differing perceptions. The defined parameterized fuzzy operators also should satisfy the axiomatic requirements for the traditional fuzzy operators. A learning algorithm will be proposed to obtain the parameter α given a set of training data for each agent. In this article, the proposed parameterized fuzzy operators will be used in individual decision‐making problems. An example is given to show the concept and application of the parameterized fuzzy operators. © 2003 Wiley Periodicals, Inc.     

Detecting image orientation based on low-level visual content

Accurately and automatically detecting image orientation is of great importance in intelligent image processing. In this paper, we present automatic image orientation detection algorithms based on both the luminance (structural) and chrominance (color) low-level content features. The statistical learning support vector machines (SVMs) are used in our approach as the classifiers. The different sources of the extracted image features, as well as the binary classification nature of SVM, require our system to be able to integrate the outputs from multiple classifiers. Both static combiner (averaging) and trainable combiner (also based on SVMs) are proposed and evaluated in this work. Furthermore, two rejection options (regular and re-enforced ambiguity rejections) are employed to improve orientation detection accuracy by sieving out images with low confidence values during the classification. Large amounts of experiments have been conducted on a database of more than 14,000 images to validate our approaches. Discussions and future directions for this work are also addressed at the end of the paper.     

Opposing Effects of D? and D? Receptor Activation on Odor Discrimination Learning.

Dopaminergic modulation of cortical activity has been implicated in the formation of reward associations. There is abundant evidence for dopaminergic effects on olfactory processing. Using an olfactory discrimination task, the authors show that D? and D? dopamine receptors can regulate rats' olfactory discrimination capacities and that the effects of receptor activation functionally oppose one another. Injection of either the D? agonist SKF 38393 (10 mg/kg) or the D? antagonist spiperone (0.62 mg/kg) facilitated the discrimination of similar odorants but had no effect on the discrimination of dissimilar odorants, whereas both the D, antagonist SCH 23390 (0.025 mg/kg) and the D? agonist quinpirole (0.2 mg/kg) significantly impaired rats' ability to discriminate similar and dissimilar odorants. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The Power of the Brown v. Board of Education Decision: Theorizing Threats to Sustainability.

Interviews with African American and White American elders capture the immediate power of the Brown v. Board of Education (1954) decision and the biography of its impact over time. This article reviews the lived experience of the decision and theorizes 3 threats to sustainability that ruthlessly undermined the decision over time: (a) the unacknowledged and enormous sacrifice endured by the African American community in the name of desegregation; b) the violent and relentless resistance to the decision by government officials, educators, and many White community members; and (c) the dramatic shrinkage of the vision of Brown from the dismantling of White supremacy to a technical matter of busing. Implications are drawn for the study of desegregation and for the study of sustainability of social justice more broadly. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Parents' Personality and Infants' Temperament as Contributors to Their Emerging Relationship.

The authors examined the contributions of infant's temperament and parent's personality to their relationship. In Study 1, 102 infants, mothers, and fathers were studied when infants were 7 months; in Study 2, 112 infants and mothers were followed from 9 to 45 months. Infants' temperament (joy, fear, anger, and attention) was observed in standard temperament paradigms. Parents' personality measures encompassed the Big Five traits and Empathy in Study 1 and Mistrust, Manipulativeness, Aggression, Dependency, Entitlement, and Workaholism in Study 2. Parent-child relationship (shared positive affect and parental responsiveness in Studies 1 and 2 and parental tracking of the infant in Study 1) was observed in naturalistic contexts. In Study 1, mothers' Neuroticism, Empathy, and Conscientiousness and fathers' Agreeableness, Openness, and Extraversion related to the relationship with the infants. All measures of infant temperament also related to the emerging relationship. In Study 2, maternal Mistrust, Manipulativeness, Dependency, and Workaholism predicted the relationship with the child. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Age effects on social cognition: Faces tell a different story.

The authors administered social cognition tasks to younger and older adults to investigate age-related differences in social and emotional processing. Although slower, older adults were as accurate as younger adults in identifying the emotional valence (i.e., positive, negative, or neutral) of facial expressions. However, the age difference in reaction time was largest for negative faces. Older adults were significantly less accurate at identifying specific facial expressions of fear and sadness. No age differences specific to social function were found on tasks of self-reference, identifying emotional words, or theory of mind. Performance on the social tasks in older adults was independent of performance on general cognitive tasks (e.g., working memory) but was related to personality traits and emotional awareness. Older adults also showed more intercorrelations among the social tasks than did the younger adults. These findings suggest that age differences in social cognition are limited to the processing of facial emotion. Nevertheless, with age there appears to be increasing reliance on a common resource to perform social tasks, but one that is not shared with other cognitive domains. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

On Conducting Simultaneous Versus Sequential Engineering Activities in Risky R&D

We consider development projects in which the activities can be classified in two types: uncertainty resolving R&D efforts that accumulate in the form of knowledge to eventually give rise to a discovery; and routine technical investments which aim at improving the profitability of the project once the discovery has been made. The advantage of initiating routine preparatory activities prior to the achievement of a technological breakthrough in such projects, sometimes termed as 'concurrent engineering', is analyzed within a suitable dynamic optimization framework. The optimal double expenditure policy is compared with the conservative delayed investment policy, under which all the routine engineering activities are delayed until the risky R&D efforts culminate in a breakthrough. A criterion for the optimality of the latter policy is developed on the basis of the probability distribution of the discovery date. The application of the criterion is illustrated for a variety of specifications regarding the uncertainty associated with the R&D process. We find that simultaneous investment is the optimal policy for a large class of probability distributions. However, if the conditional probability of immediate discovery is always below some critical value, it is optimal to delay the preparatory activities until the discovery.     

Viscous Open Data: The Roles of Intermediaries in an Open Data Ecosystem

Open data have the potential to improve the governance of universities as public institutions. In addition, open data are likely to increase the quality, efficacy and efficiency of the research and analysis of higher education systems by providing a shared empirical base for critical interrogation and reinterpretation. Drawing on research conducted by the Emerging Impacts of Open Data in Developing Countries project, and using an ecosystems approach, this research paper considers the supply, demand and use of open data as well as the roles of intermediaries in the governance of South African public higher education. It shows that government's higher education database is a closed and isolated data source in the data ecosystem; and that the open data that are made available by government is inaccessible and rarely used. In contrast, government data made available by data intermediaries in the ecosystem are being used by key stakeholders. Intermediaries are found to play several important roles in the ecosystem: (i) they increase the accessibility and utility of data; (ii) they may assume the role of a “keystone species” in a data ecosystem; and (iii) they have the potential to democratize the impacts and use of open data. The article concludes that despite poor data provision by government, the public university governance open data ecosystem has evolved because intermediaries in the ecosystem have reduced the viscosity of government data. Further increasing the fluidity of government open data will improve access and ensure the sustainability of open data supply in the ecosystem.