Motor learning is the process of improving task execution according to some measure of performance. This can be divided into skill learning, a model-free process, and adaptation, a model-based process. Prior studies have indicated that adaptation results from two complementary learning systems with parallel organization. This report attempted to answer the question of whether a similar interaction leads to savings, a model-free process that is described as faster relearning when experiencing something familiar. This was tested in a two-week reaching task conducted on a robotic arm capable of perturbing movements. The task was designed so that the two sessions differed in their history of errors. By measuring the change in the learning rate, the savings was determined at various points. The results showed that the history of errors successfully modulated savings. Thus, this supports the notion that the two complementary systems interact to develop savings. Additionally, this report was part of a larger study that will explore the organizational structure of the complementary systems as well as the neural basis of this motor learning.

The goal of this study was to compare and contrast the discriminatory experiences of women in policing. Through this comparison, the deeper goal was to investigate the levels of discrimination throughout the ranks of Policewomen and the potential ramifications that might have had on their careers. Surveys were administered to female police officers. In order for a case study to be performed, 19 responses were collected. The survey consisted of 8 demographic and 8 long response questions. The demographic questions asked for age, ethnicity, state of birth, education level, officer ranking, career outlook, current marital status, and number of children. The long response questions include their positive and negative attributes about their career, their inspiration for pursuing their career in law enforcement, and if they have ever been discriminated against based on sex. The findings in the research gathered on police women within the rank of officer indicate varying levels of discrimination. The discrimination does not only happen from those inside the work place but from the community; the people officers are protecting. In conclusion, there is still great discrimination female officers face by both the community they serve and the department they serve with. This has ramifications on their ability to not only do their job in the moment but also move up throughout their departments.

Significant health inequalities exist between different castes and ethnic communities in India, and identifying the roots of these inequalities is of interest to public health research and policy. Research on caste-based health inequalities in India has historically focused on general, government-defined categories, such as “Scheduled Castes,” “Scheduled Tribes,” and “Other Backward Classes.” This method obscures the diversity of experiences, indicators of well-being, and health outcomes between castes, tribes, and other communities in the “scheduled” category. This study analyzes data on 699,686 women from 4,260 castes, tribes and communities in the 2015-2016 Demographic and Health Survey of India to: (1) examine the diversity within and overlap between general, government-defined community categories in both wealth, infant mortality, and education, and (2) analyze how infant mortality is related to community category membership and socioeconomic status (measured using highest level of education and household wealth). While there are significant differences between general, government-defined community categories (e.g., scheduled caste, backward class) in both wealth and infant mortality, the vast majority of variation between communities occurs within these categories. Moreover, when other socioeconomic factors like wealth and education are taken into account, the difference between general, government-defined categories reduces or disappears. These findings suggest that focusing on measures of education and wealth at the household level, rather than general caste categories, may more accurately target those individuals and households most at risk for poor health outcomes. Further research is needed to explain the mechanisms by which discrimination affects health in these populations, and to identify sources of resilience, which may inform more effective policies.