Media, Law, and the Gay/Trans Panic Defense

The gay/trans panic defense is a legal strategy that is used to try to lower the sentence of a defendant in cases of assault, claiming that certain actions were justified because an individual had “deceived” them as a result of their sexual or gender orientation. We analyze how cultural perceptions of gay/trans panic shape the way we understand the legitimacy of this legal defense. We look at this in two ways: first, we are using a media analysis to examine how gay/trans panic is represented in film and television to understand how it becomes culturally legitimized. Second, we conduct a survey to gather data about how people from different parts of the United States understand the defense, and gauge if there is a correlation between certain beliefs that they hold and their sympathy towards the defense. We anticipate that political and geographic differences may correlate with perceptions of the defense\u27s legitimacy, given the fact that it is still permissible in many states and has led to lighter sentencing of aggressors.https://orb.binghamton.edu/research_days_posters_2021/1029/thumbnail.jp

Evaluation of the cutaneous microbiome in psoriasis

Psoriasis, a highly prevalent disease of humans of unknown cause, is a chronic inflammatory disorder primarily involving skin, with distinctive clinical characteristics. With the newly developed tools that facilitate microbiome research, it now is possible to assess whether the cutaneous microbiome plays a role in the pathogenesis of this disorder. Preliminary data from our studies suggest that the cutaneous microbiome in psoriasis is complex and possibly different from normal. To deal with this complexity, we propose to examine the cutaneous microbiome in relation to psoriasis with explorations at several taxonomic and informatic levels. Our overall objective is to examine how changes in the normal cutaneous microbiome contributes to the pathogenesis of psoriasis. Since causality is complex and often difficult to prove, our overall hypothesis is that there are alterations in the cutaneous microbiome in areas of skin affected by psoriasis in comparison with the range observed in clinically unaffected areas, or in healthy persons. We also hypothesize that the characteristics of the microbiome may affect clinical responses to the immunomodulatory agents used to treat psoriasis. An alternative hypothesis is that effective treatment of psoriasis with systemic immunomodulatory agents will not substantially affect the disordered microbial ecosystem. Such observations would provide evidence for the roles of the microbiota in this disorder. Since an important consideration in microbiome research is the optimal level (e.g. phylum, genus, species, strain, gene) at which to examine a scientific question, and we are not yet certain what are the optimal levels for psoriasis, this also will be examined. Our studies of psoriasis should allow development of both approaches and tools that will have general utility for microbiome research. To test our hypothesis, we propose the following specific aims: 1. To understand the cutaneous microbiome species composition overlaying psoriatic lesions; 2. To investigate differences in metagenome content for psoriatic lesions compared to normal skin; 3. To identify differences in the transcriptional profiles of the microbiome and the host between normal skin and psoriatic lesions using high-throughput sequencing; and 4. To estimate the effects of systemic immunomodulatory therapy for psoriasis on microbiome composition. In total, these studies should help us understand the role of the microbiome in psoriasis pathogenesis

The Governor Architecture: Avoiding Catastrophic Forgetting in Robot Learning

The governor architecture is a new method for avoiding catatrophic forgetting in neural networks that is particularly useful in online robot learn- ing. The governor architecture uses a categorizer to identify events and excise long sequences of repetitive data that cause catastrophic forgetting in neural networks trained on robot-based tasks. We examine the performance of several variations of the governor architecture on a number of re- lated localization tasks using a simulated robot. The results show that governed networks perform far better than ungoverned networks. Governored networks are able to reliably and robustly prevent catastrophic forgetting in robot learning tasks

The Governor Architecture: Avoiding Catastrophic Forgetting in Robot Learning

The governor architecture is a new method for avoiding catatrophic forgetting in neural networks that is particularly useful in online robot learn- ing. The governor architecture uses a categorizer to identify events and excise long sequences of repetitive data that cause catastrophic forgetting in neural networks trained on robot-based tasks. We examine the performance of several variations of the governor architecture on a number of re- lated localization tasks using a simulated robot. The results show that governed networks perform far better than ungoverned networks. Governored networks are able to reliably and robustly prevent catastrophic forgetting in robot learning tasks