INCLUDING SOFT INFORMATION IN EISs

Although much of executive decision making is based on soft information—opinions, predictions, news, and even rumors—executive information systems (EISs) have only recently begun to augment factual data with such information. A study of current use of soft information in EISs yields 15 propositions designed to help EIS developers determine what kinds of soft information are most valuable and how best to capture and deliver this information.     

Effects of long-term vocabulary instruction on lexical access and reading comprehension.

To examine the relationship between knowledge of word meanings and semantic processes, 27 4th-grade children were taught 104 words over a 5-mo period. Following instruction, Ss performed tasks designed to require semantic processes ranging from single word semantic decisions to simple sentence verification and memory for connected text. On all these tasks, instructed Ss performed at a significantly higher level than controls matched on pre-instruction vocabulary knowledge and comprehension. Thus, instructed Ss gave evidence both of learning word meanings taught by the program and of being able to process instructed words more efficiently in tasks more reflective of comprehension. Implications for vocabulary instruction and the role of individual word meanings in comprehension are discussed. (18 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Denial, anxiety, locus of control, and discrepancy between aspirations and achievements as components of depression.

Reformulated a number of clinical observations about depression to test them empirically, using multiple regression equations. Ss were 547 men in Army basic training. Psychological measures included the Depression subscale of the Cornell Medical Index, Rotter's Internal-External Control Scale, the Institute for Personality and Ability Testing Anxiety Scale, N. Hahn's denial measure, and the Cantril Self-Anchoring Striving Scale. Depression was negatively correlated with denial and positively correlated with anxiety, locus of control, and the discrepancy between aspirations and achievements (discontent). Locus of control was positively correlated with discontent and anxiety and negatively correlated with denial. There were interaction effects between locus of control and discontent, between locus of control and anxiety, and between anxiety and denial when these terms were regressed on depression. (34 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Prototypic typology and the Borderline Personality Disorder.

Based on interview data from 76 18–45 yr old outpatients, the implications of a prototypic rather than a classical model of personality-disorder classification were demonstrated for DSM-III Axis II Borderline Personality Disorder (BPD). Heterogeneity of membership is described, and conditional probabilities are used to demonstrate the relative efficiency of single diagnostic criteria and combinations of criteria and the degree of overlap among BPD and other personality disorders. The conditional probability approach can be used to determine empirically the covariation of symptoms and to link the study of prototypicality to the individual patient rather than to the group. (17 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Relational learning of a size concept.

Administered relational size problems in the context of ordinal series to 72 4-5 yr olds. Solution was facilitated when Ss were directed to locate a terminal member (the smallest) of the series. In contrast, Ss who were instructed to locate a nonterminal member without prior designation of a terminal member were unable to achieve solution of the problem. Age- and sex-related differences in performance were observed as well as differences associated with stimulus arrangements and stimulus sizes. The outcomes are discussed in terms of composite task demands. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Effect of government actions on technological innovation for SO2 control

The relationship between government actions and innovation in environmental control technology is important for the design of cost-effective policies to achieve environmental goals. This paper examines such relationships for the case of sulfur dioxide control technology for U.S. coal-fired power plants. The study employs several complementary research methods, including analyses of key government actions, technology patenting activity, technology performance and cost trends, knowledge transfer activities, and expert elicitations. Our results indicate that government regulation appears to be a greater stimulus to inventive activity than government-sponsored research support alone, and that the anticipation of regulation also spurs inventive activity. Regulatory stringency focuses this activity along particular technical pathways and is a key factor in creating markets for environmental technologies. We also find that with greater technology adoption, both new and existing systems experience notable efficiency improvements and capital cost reductions. The important role of government in fostering knowledge transfer via technical conferences and other measures is also seen as an important factor in promoting environmental technology innovation.     

Blind deblurring of spiral CT images

To discriminate fine anatomical features in the inner ear, it has been desirable that spiral computed tomography (CT) may perform beyond their current resolution limits with the aid of digital image processing techniques. In this paper, we develop a blind deblurring approach to enhance image resolution retrospectively without complete knowledge of the underlying point spread function (PSF). An oblique CT image can be approximated as the convolution of an isotropic Gaussian PSF and the actual cross section. Practically, the parameter of the PSF is often unavailable. Hence, estimation of the parameter for the underlying PSF is crucially important for blind image deblurring. Based on the iterative deblurring theory, we formulate an edge-to-noise ratio (ENR) to characterize the image quality change due to deblurring. Our blind deblurring algorithm estimates the parameter of the PSF by maximizing the ENR, and deblurs images. In the phantom studies, the blind deblurring algorithm reduces image blurring by about 24%, according to our blurring residual measure. Also, the blind deblurring algorithm works well in patient studies. After fully automatic blind deblurring, the conspicuity of the submillimeter features of the cochlea is substantially improved.     

Genomic mining for complex disease traits with “random chemistry”

Our rapidly growing knowledge regarding genetic variation in the human genome offers great potential for understanding the genetic etiology of disease. This, in turn, could revolutionize detection, treatment, and in some cases prevention of disease. While genes for most of the rare monogenic diseases have already been discovered, most common diseases are complex traits, resulting from multiple gene–gene and gene-environment interactions. Detecting epistatic genetic interactions that predispose for disease is an important, but computationally daunting, task currently facing bioinformaticists. Here, we propose a new evolutionary approach that attempts to hill-climb from large sets of candidate epistatic genetic features to smaller sets, inspired by Kauffman’s “random chemistry” approach to detecting small auto-catalytic sets of molecules from within large sets. Although the algorithm is conceptually straightforward, its success hinges upon the creation of a fitness function able to discriminate large sets that contain subsets of interacting genetic features from those that don’t. Here, we employ an approximate and noisy fitness function based on the ReliefF data mining algorithm. We establish proof-of-concept using synthetic data sets, where individual features have no marginal effects. We show that the resulting algorithm can successfully detect epistatic pairs from up to 1,000 candidate single nucleotide polymorphisms in time that is linear in the size of the initial set, although success rate degrades as heritability declines. Research continues into seeking a more accurate fitness approximator for large sets and other algorithmic improvements that will enable us to extend the approach to larger data sets and to lower heritabilities.