Changes in Functional Connectivity Associated with Treatment Gains in Aphasia

NIDCD/NIH (F31 NRSA grant 1F31DC011220-01A1); Boston University Sargent College (Dudley Allen Sargent Research Award

A Comparison of Clustering Techniques for Malware Analysis

In this research, we apply clustering techniques to the malware detection problem. Our goal is to classify malware as part of a fully automated detection strategy. We compute clusters using the well-known �-means and EM clustering algorithms, with scores obtained from Hidden Markov Models (HMM). The previous work in this area consists of using HMM and �-means clustering technique to achieve the same. The current effort aims to extend it to use EM clustering technique for detection and also compare this technique with the �-means clustering

Sex trafficking of girls and women : Evidence from Anantapur district, Andhra Pradesh

A crucial gap in the trafficking literature from India is the dearth of primary data and micro studies that could be used for vulnerability mapping of the source areas and addressing the identified risk factors. The present paper is a small attempt to contribute to plugging the gap in the context of Andhra Pradesh, identified as a hot spot in the trafficking literature. This paper is based on case studies of 78 women who had been trafficked from their places of origin in Anantapur district in Andhra Pradesh to metropolitan cities across India and who have since returned to their homes. The paper attempted to identify the individual and family circumstances that contribute to the causes of trafficking, to highlight in particular the gendered vulnerabilities that set these women up for trafficking, and to capture the process of the trafficking experience. The findings of the study are located in the dynamic interplay of the social structural context and specificities of the district that contribute to causes of trafficking and the individual circumstances and agency of the women. The case studies reported in this paper are a pointer to the compelling urgency of interventions that will go beyond the forced / voluntary divide in trafficking and sex work.Andhra Pradesh, India, trafficking

Semantic Complexity In Treatment Of Naming Deficits In Aphasia: Evidence From Well-Defined Categories

Purpose: Our previous work on manipulating typicality of category exemplars during treatment of naming deficits has shown that training atypical examples generalizes to untrained typical examples but not vice versa. In contrast to natural categories that consist of fuzzy boundaries, well-defined categories (e.g., shapes) have rigid category boundaries. Whether these categories illustrate typicality effects similar to natural categories is under debate. The present study addressed this question in the context of treatment for naming deficits in aphasia. Methods: Using a single-subject experiment design, 3 participants with aphasia received a, semantic feature treatment to improve naming of either typical or atypical items of shapes, while generalization was tested to untrained items of the category. Results: For 2 of the 3 participants, training naming of atypical examples of shapes resulted in improved naming of untrained typical examples. Training typical examples in 1 participant did not improve naming of atypical examples. All 3 participants, however, showed weak acquisition trends. Conclusions: Results of the present study show equivocal support for manipulating typicality as a treatment variable within well-defined categories. Instead, these results indicate that acquisition and generalization effects within well-defined categories such as shapes are overshadowed by their inherent abstractness.Communication Sciences and Disorder