Gender differences in career decision making: The content and structure of preferences.

To identify possible sources of the observed differences in the career choices of women and men, three facets of career preferences were examined: the relative importance attributed to career-related aspects, the within-aspect preferences (i.e., desirable characteristics of occupations), and the structure of aspects derived from these within-aspect preferences. The career-related preferences of 2,000 young adults who were in the process of making their career decisions were analyzed. These career-related preferences were elicited during their dialogues with a computer-assisted career guidance system. The analyses revealed (a) only small gender differences in the relative importance of the aspects, (b) considerable gender differences in the within-aspect preferences, and (c) certain gender differences in the structure of aspects. The findings and their possible theoretical and practical implications are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Unsupervised image-set clustering using an information theoretic framework.

In this paper, we combine discrete and continuous image models with information-theoretic-based criteria for unsupervised hierarchical image-set clustering. The continuous image modeling is based on mixture of Gaussian densities. The unsupervised image-set clustering is based on a generalized version of a recently introduced information-theoretic principle, the information bottleneck principle. Images are clustered such that the mutual information between the clusters and the image content is maximally preserved. Experimental results demonstrate the performance of the proposed framework for image clustering on a large image set. Information theoretic tools are used to evaluate cluster quality. Particular emphasis is placed on the application of the clustering for efficient image search and retrieval.     

Modeling Temperature in Coupled Electrical and Thermal Simulations of the Electroconsolidation® Process

Electroconsolidation® is a process for densifying complex-shaped parts by using electrically conductive particulate solids as a pressure-transmitting medium. The part is immersed in a bed of the particulate medium contained in a die chamber. Sintering temperature is achieved by resistive heating of the medium while applying compaction pressure. The process is capable of ultrahigh temperatures and short cycle times and offers the potential for low processing costs.

Control of the process and selection of process conditions require knowledge of the temperatures within the die. Temperature gradients exist because of the high heating rate and because of variations of density and electrical resistivity of the medium due to the presence of the part. Direct measurement of temperature with thermocouples or other conventional means is impractical because of the high temperatures, high currents, and high pressures that are involved. Therefore, a computer model was developed to predict temperature as a function of time and applied voltage for any location in the die. The computer model is composed of three parts: a geometrical model to approximate the density and resistivity variations in the medium, a finite-element model to calculate the rate of resistive heating within each element, and a finite-difference model to calculate the temperature distribution based on solution of the heat-transfer equations. Predicted temperatures have been shown to be in excellent agreement with measurements, and numerical simulation provided encouraging consistency and reasonably accurate predictions of temperature profiles within the die. The model demonstrated the feasibility of a new process to achieve simultaneous application of pressure and heat to powder densification in Electroconsolidation.     

Psychosocial factors among members of religious and secular kibbutzim

Mortality in 11 secular kibbutzim between 1970 and 1985 was nearly twice that of 11 matched religious kibbutzim. A cross-sectional study was undertaken in 1991 in 10 of these settlements, 5 religious and 5 secular, to determine whether differences in risk factors could explain the unequal survival. These comprised physical, physiologic and biochemical measurements, health-relevant behaviors and psychosocial variables. This report addresses the psychosocial aspect of the study, which included assessment of sense of coherence, hostility, satisfaction with self, work-related stress, social supports and social contacts using self-administered questionnaires. The response rate among the sample of men and women, aged 35-64 years, was 76% (437 respondents, 208 men and 229 women). Analysis of variance and logistic regression (the latter comparing the upper or lower fourths of the distribution vs. the rest) were used. Religious kibbutz members reported a higher sense of coherence (odds ratio = 1.58, 95% CI 1.02 to 2.46) and a lower level of hostility (odds ratio = 0.49, 95% CI 0.33 to 0.75) than their secular counterparts. Findings for satisfaction with self and work-related stress were inconsistent; there were significant interactions between religious affiliation, sex and age. Younger women reported less satisfaction with self and higher work-related stress than the other age-sex groups in both types of kibbutz. There was no difference in social support or frequency of social contact between religious and secular kibbutzim. Voluntary work was more frequent among the religious kibbutzim. The findings are consistent with an interpretation that Jewish religious observance may enhance the formation of certain protective personality characteristics. Membership in a cohesive religious kibbutz community may increase host resistance to stressors and thereby promote overall well-being and a positive health status. This could reflect an interplay of individual and collective attributes of religion.     

Mosaic organization of DNA nucleotides

Long-range power-law correlations have been reported recently for DNA sequences containing noncoding regions. We address the question of whether such correlations may be a trivial consequence of the known mosaic structure ("patchiness") of DNA. We analyze two classes of controls consisting of patchy nucleotide sequences generated by different algorithms--one without and one with long-range power-law correlations. Although both types of sequences are highly heterogenous, they are quantitatively distinguishable by an alternative fluctuation analysis method that differentiates local patchiness from long-range correlations. Application of this analysis to selected DNA sequences demonstrates that patchiness is not sufficient to account for long-range correlation properties.     

Long-range correlation properties of coding and noncoding DNA sequences: GenBank analysis

An open question in computational molecular biology is whether long-range correlations are present in both coding and noncoding DNA or only in the latter. To answer this question, we consider all 33301 coding and all 29453 noncoding eukaryotic sequences--each of length larger than 512 base pairs (bp)--in the present release of the GenBank to dtermine whether there is any statistically significant distinction in their long-range correlation properties. Standard fast Fourier transform (FFT) analysis indicates that coding sequences have practically no correlations in the range from 10 bp to 100 bp (spectral exponent beta=0.00 +/- 0.04, where the uncertainty is two standard deviations). In contrast, for noncoding sequences, the average value of the spectral exponent beta is positive (0.16 +/- 0.05) which unambiguously shows the presence of long-range correlations. We also separately analyze the 874 coding and the 1157 noncoding sequences that have more than 4096 bp and find a larger region of power-law behavior. We calculate the probability that these two data sets (coding and noncoding) were drawn from the same distribution and we find that it is less than 10(-10). We obtain independent confirmation of these findings using the method of detrended fluctuation analysis (DFA), which is designed to treat sequences with statistical heterogeneity, such as DNA's known mosaic structure ("patchiness") arising from the nonstationarity of nucleotide concentration. The near-perfect agreement between the two independent analysis methods, FFT and DFA, increases the confidence in the reliability of our conclusion.     

Generalized Lévy-walk model for DNA nucleotide sequences

We propose a generalized Lévy walk to model fractal landscapes observed in noncoding DNA sequences. We find that this model provides a very close approximation to the empirical data and explains a number of statistical properties of genomic DNA sequences such as the distribution of strand-biased regions (those with an excess of one type of nucleotide) as well as local changes in the slope of the correlation exponent alpha. The generalized Lévy-walk model simultaneously accounts for the long-range correlations in noncoding DNA sequences and for the apparently paradoxical finding of long subregions of biased random walks (length lj) within these correlated sequences. In the generalized Lévy-walk model, the lj are chosen from a power-law distribution P(lj) varies as lj(-mu). The correlation exponent alpha is related to mu through alpha = 2-mu/2 if 2 < mu < 3. The model is consistent with the finding of "repetitive elements" of variable length interspersed within noncoding DNA.     

An unsupervised data projection that preserves the cluster structure

In this paper we propose a new unsupervised dimensionality reduction algorithm that looks for a projection that optimally preserves the clustering data structure of the original space. Formally we attempt to find a projection that maximizes the mutual information between data points and clusters in the projected space. In order to compute the mutual information, we neither assume the data are given in terms of distributions nor impose any parametric model on the within-cluster distribution. Instead, we utilize a non-parametric estimation of the average cluster entropies and search for a linear projection and a clustering that maximizes the estimated mutual information between the projected data points and the clusters. The improved performance is demonstrated on both synthetic and real world examples.     

Limits to the evolution of dispersal kernels under rapid fragmentation

Adaptive evolution of dispersal strategies is one mechanism by which species can respond to rapid environmental changes. However, under rapid anthropogenic fragmentation, the evolution of dispersal may be limited, and species may be unable to adequately adapt to fragmented landscapes. Here, we develop a spatially explicit model to investigate the evolution of dispersal kernels under various combinations of fragmentation dynamics and initial conditions. We also study the consequences of modelling an evolutionary process in which dispersal phenotypes continuously and gradually shift in phenotype space in a manner corresponding to a polygenic underlying genetic architecture. With rapid fragmentation rates, we observed the emergence of long-term transient states in which dispersal strategies are not well suited to fragmented landscapes. We also show that the extent and length of these transient states depend on the pre-fragmentation dispersal strategy of the species, as well as on the rate of the fragmentation process leading to the fragmented landscape. In an increasingly fragmented world, understanding the ability of populations to adapt, and the effects that rapid fragmentation has on the evolution of dispersal, is critical for an informed assessment of species viability in the Anthropocene.