Bias for Vocalic Over Consonantal Information in 6‐Month‐Olds

Human languages rely on the ability to learn and produce an indefinite number of words by combining consonants and vowels in a lawful manner. The categorization of speech representations into consonants and vowels is evidenced by the tendency of adult speakers, attested in many languages, to use consonants and vowels for different tasks. Consonants are favored in lexical tasks, while vowels are favored to learn structural regularities. Recent results suggest that this specialization is already observable at 12 months of age in Italian participants. Here, we investigated the representations of younger infants. In a series of anticipatory looking experiments, we showed that Italian 6‐month‐olds rely more on vowels than on consonants when learning the predictions made by individual words (Experiment 1) and are better at generalizing a structure when it is implemented over vowels than when it is implemented over consonants (Experiments 2 and 3). Until 6 months of age, infants thus show a general vocalic bias, which contrasts with the specialization previously observed at 12 months. These results suggest the format of speech representations changes during the second semester of life.     

On the Smoothness of Projections in Statistical Models

Here we examine the existence of the projection of a probability measure in a parametric statistical model. Once, in a general framework, the existence of the projection is established, we consider the problem from a statistical point of view, modeling a parametric statistical model as a convenient manifold.     

A classification updating procedure motivated by high-content screening data

The current paradigm for the identification of candidate drugs within the pharmaceutical industry typically involves the use of high-throughput screens. High-content screening (HCS) is the term given to the process of using an imaging platform to screen large numbers of compounds for some desirable biological activity. Classification methods have important applications in HCS experiments, where they are used to predict which compounds have the potential to be developed into new drugs. In this paper, a new classification method is proposed for batches of compounds where the rule is updated sequentially using information from the classification of previous batches. This methodology accounts for the possibility that the training data are not a representative sample of the test data and that the underlying group distributions may change as new compounds are analysed. This technique is illustrated on an example data set using linear discriminant analysis, k-nearest neighbour and random forest classifiers. Random forests are shown to be superior to the other classifiers and are further improved by the additional updating algorithm in terms of an increase in the number of true positives as well as a decrease in the number of false positives.     

Desegregation in Higher Education: An Examination of Traditionally Black and White Institutions*

Using the data collection techniques of historical analysis, secondary analysis of EEO-6 records, mailed questionnaires, and personal interviews, race relations among trustees, administrators, and faculty in the southeastern United States were examined during the late 1970s and early 1980s. The conclusion that blacks at traditionally white institutions (TWI) (1) had more tenuous job status, (2) experienced less job satisfaction, (3) experienced greater degrees of institutional alienation, and (4) more often stated a need for affirmative action programs than did their white colleagues at the same institution will surprise no one. Similar patterns and perceptions were found for whites at traditionally black institutions (TBI) where whites were in the “minority.” Although whites at TBIs remained members of the societal majority group as traditionally defined in the sociology of intergroup relations, their position and perceptions within specific TBIs were remarkably similar to the experience of black professionals at TWIs. Some implications for policy are drawn.     

The evaluation of a mind/body intervention to reduce psychological distress and perceived stress in college students

The authors examined the effect of a 6-week mind/body intervention on college students' psychological distress, anxiety, and perception of stress. One hundred twenty-eight students were randomly assigned to an experimental group (n = 63) or a waitlist control group (n = 65). The experimental group received 6 90-minute group-training sessions in the relaxation response and cognitive behavioral skills. The Symptom Checklist-90-Revised, Spielberger State-Trait Anxiety Inventory, and the Perceived Stress Scale were used to assess the students' psychological state before and after the intervention. Ninety students (70% of the initial sample) completed the postassessment measure. Significantly greater reductions in psychological distress, state anxiety, and perceived stress were found in the experimental group. This brief mind/body training may be useful as a preventive intervention for college students, according to the authors, who called for further research to determine whether the observed treatment effect can be sustained over a longer period of time.     

Crooked men and straightened women: images of homosexuality across race in two women's magazines, 1986-1995

Images of traditional sexuality, across race, prevail in mass media, especially in women's magazines. While omitting less traditional sexual practices for the most part, New Woman and Essence magazines construct the image of a bisexual male who threatens the heterosexual woman and the legitimate heterosexual couple. These women's magazines also redefine homosexual activity, suggesting women who experience homosexual inclinations are really engaging in normal heterosexual behavior.     

Benefits of community meetings in the corporate setting after the suicide of a coworker

When an employee commits suicide, his or her coworkers are confronted unexpectedly with issues related to the sudden traumatic death. Being inundated with questions, grappling with acceptance of the loss, and exploring how this could have happened are factors that can complicate the bereavement process and delay a return to workplace homeostasis. Understanding the dynamics and issues related to grief and bereavement after sudden traumatic death potentially can accelerate the recovery process and promote restoration of workforce normalcy for employees and organizations. This can be significantly important to corporate managers and administrators who must maintain ongoing productivity despite such disruption, while promoting adaptive coping for their employees.     

Bayesian approach to the inverse problem in a light scattering application

In this article, static light scattering (SLS) measurements are processed to estimate the particle size distribution of particle systems incorporating prior information obtained from an alternative experimental technique: scanning electron microscopy (SEM). For this purpose we propose two Bayesian schemes (one parametric and another non-parametric) to solve the stated light scattering problem and take advantage of the obtained results to summarize some features of the Bayesian approach within the context of inverse problems. The features presented in this article include the improvement of the results when some useful prior information from an alternative experiment is considered instead of a non-informative prior as it occurs in a deterministic maximum likelihood estimation. This improvement will be shown in terms of accuracy and precision in the corresponding results and also in terms of minimizing the effect of multiple minima by including significant information in the optimization. Both Bayesian schemes are implemented using Markov Chain Monte Carlo methods. They have been developed on the basis of the Metropolis–Hastings (MH) algorithm using Matlab^® and are tested with the analysis of simulated and experimental examples of concentrated and semi-concentrated particles. In the simulated examples, SLS measurements were generated using a rigorous model, while the inversion stage was solved using an approximate model in both schemes and also using the rigorous model in the parametric scheme. Priors from SEM micrographs were also simulated and experimented, where the simulated ones were obtained using a Monte Carlo routine. In addition to the presentation of these features of the Bayesian approach, some other topics will be discussed, such as regularization and some implementation issues of the proposed schemes, among which we remark the selection of the parameters used in the MH algorithm.