Women Counselor Educators: Strategies for Success in Academia

In order to achieve gender equity in the academy, it is necessary to understand how traditional gender roles impact university practices and policies. In this session, the impact of gender norms on women counselor educators’ teaching, research, and service responsibilities will be explored. Results from recent studies on this topic will be provided. Strategies for successfully navigating the academic culture will be discussed. Ethical responsibilities related to the recruitment and retention of a diverse faculty will be considered. Advocacy activities designed to promote equity in academia will be recommended

Spinnability and characteristics of polyvinylidene fluoride (PVDF)-based bicomponent fibers with a carbon nanotube (CNT) modified polypropylene core for piezoelectric applications

Biodiesel production has received considerable attention in the recent past as a nonpolluting fuel. However, this assertion has been based on its biodegradability and reduction in exhaust emissions. Assessments of water and soil biodiesel pollution are still limited. Spill simulation with biodiesel and their diesel blends in soils were carried out, aiming at analyzing their cytotoxic and genotoxic potentials. While the cytotoxicity observed may be related to diesel contaminants, the genotoxic and mutagenic effects can be ascribed to biodiesel pollutants. Thus, taking into account that our data stressed harmful effects on organisms exposed to biodiesel-polluted soils, the designation of this biofuel as an environmental-friendly fuel should be carefully reviewed to assure environmental quality. (C) 2011 Elsevier B.V. All rights reserved

Feature enhancement of reverberant speech by distribution matching and non-negative matrix factorization

This paper describes a novel two-stage dereverberation feature enhancement method for noise-robust automatic speech recognition. In the first stage, an estimate of the dereverberated speech is generated by matching the distribution of the observed reverberant speech to that of clean speech, in a decorrelated transformation domain that has a long temporal context in order to address the effects of reverberation. The second stage uses this dereverberated signal as an initial estimate within a non-negative matrix factorization framework, which jointly estimates a sparse representation of the clean speech signal and an estimate of the convolutional distortion. The proposed feature enhancement method, when used in conjunction with automatic speech recognizer back-end processing, is shown to improve the recognition performance compared to three other state-of-the-art techniques