Who's Got Your Six? Ramifications of the Court's Refusal to Define "Incident to Service" in the Feres Doctrine on Military Sexual Assault Survivors

Article published in the Michigan State Law Review

The Effects of a Prescribed Burn on Small Mammals in an Ohio Tallgrass Prairie

Prescribed burning is used on prairies for increased prairie health and to manage the communities of organisms that rely on the prairie’s natural resources. Small mammals are also affected by the burning of prairies. Previous research by Chance in 1986 and Cook in 1950 has established that burning decreases the small mammal capture rates in the burned area because of the habitat loss and rapid change of habitat post-burn that stresses the animals and leads to lower reproductive levels (Chance, 1986). Other studies by Francl and Small also showed that small mammal populations did not return to pre-burn numbers even after 16 months of evaluation (Francl, K. E., & Small, C. J., 2013). We hypothesize that small mammal populations will decrease in the prairie after burning because of a lack of habitat and food source and that they will emigrate from the burning site to nearby prairie or similar habitat. We will use baited Sherman live traps placed at 25 meter intervals in order to estimate the various small mammal populations in each of the observed habitats. We will plot the capture locations on a map of the area in order to track how stress affects the shift of population density

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Genetic Origins of Mercury Resistance in Great Salt Lake Microorganisms

Extremophiles are a diverse group of organisms, typically Bacteria and Archaea, that can inhabit extreme environments, such as geysers, deserts, and saline lakes. Their abilities to withstand extremely dry, hot, salinic, acidic, and mercuric conditions have made these microorganisms admirable astrobiological models for life on other planets1

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Open-World Object Manipulation using Pre-trained Vision-Language Models

For robots to follow instructions from people, they must be able to connect the rich semantic information in human vocabulary, e.g. "can you get me the pink stuffed whale?" to their sensory observations and actions. This brings up a notably difficult challenge for robots: while robot learning approaches allow robots to learn many different behaviors from first-hand experience, it is impractical for robots to have first-hand experiences that span all of this semantic information. We would like a robot's policy to be able to perceive and pick up the pink stuffed whale, even if it has never seen any data interacting with a stuffed whale before. Fortunately, static data on the internet has vast semantic information, and this information is captured in pre-trained vision-language models. In this paper, we study whether we can interface robot policies with these pre-trained models, with the aim of allowing robots to complete instructions involving object categories that the robot has never seen first-hand. We develop a simple approach, which we call Manipulation of Open-World Objects (MOO), which leverages a pre-trained vision-language model to extract object-identifying information from the language command and image, and conditions the robot policy on the current image, the instruction, and the extracted object information. In a variety of experiments on a real mobile manipulator, we find that MOO generalizes zero-shot to a wide range of novel object categories and environments. In addition, we show how MOO generalizes to other, non-language-based input modalities to specify the object of interest such as finger pointing, and how it can be further extended to enable open-world navigation and manipulation. The project's website and evaluation videos can be found at https://robot-moo.github.io/Comment: Accepted at the 7th Conference on Robot Learning (CoRL 2023

What WorX: Measuring the impact of faith-based service and social justice programs on Catholic youth

The Center for FaithJustice (CFJ) offers innovative programs that engage youth in faith, service, and social justice. With the Indiana University Lilly Family School of Philanthropy at IUPUI, they developed a survey to evaluate their programs and measure their longitudinal impact on alumni in those three focus areas. This report will offer related insights on youth engagement and suggest how CFJ’s programs relate to larger trends of youth disaffiliation within the Catholic Church. This study examines survey results from alumni and parents of alumni of CFJ’s youth programs, which are collectively called the “WorX” programs. These include curricula for middle school students (ServiceworX), high school students (JusticeworX, New Jersey Service Project/NJSP, MercyworX, and CommunityworX), young adults (LeaderworX), and adults (FaithJustice Fellows and adult volunteers). The results of this study focused on CFJ’s three core areas of interest: faith, service, and social justice

Frontiers in Precision Medicine IV: Artificial Intelligence, Assembling Large Cohorts, and the Population Data Revolution

Large cohort studies and more recently electronic medical records (EMR) are being used to collect massive amounts of genetic information. Implementation of artificial intelligence has become increasingly necessary to interpret this data with the goal of augmenting patient care. While it is impossible to predict what the future holds, policy makers are challenged to create guiding principles and responsibly roll out these new technologies. On March 22, 2019, the University of Utah hosted its fourth annual Precision Medicine Symposium focusing on artificial intelligence, assembling large cohorts, and the population data revolution. The symposium brought together experts in medicine, science, law and ethics to discuss and debate these emerging issues