(In)Human Anatomies: Constructions of Whiteness and Otherness in the Fiction of H.P. Lovecraft

In the fiction of H.P. Lovecraft - one of the most significant horror writers of the twentieth century, and an acknowledged white supremacist - racialized configurations Otherness are used to construct and inspire horror. At the same time, these racist and racializing narratives function to destabilize the privileged category whiteness, transgressing its boundaries, revealing its vulnerabilities, and disrupting its coherent self-construction

Automated Location of Bird Roosts Using NEXRAD Data and Image Segmentation

Weather surveillance radars can effectively detect flying animals, such as groups of birds, bats, and insects. Further, these radars are demonstrably useful for detecting the existence of certain bird roosting locations, particularly those of many species of swallows. The roosts appear on radar as distinctive rings of high reflectivity. Detecting and locating bird roosts have a variety of applications from ecological conservation to wind farm placement and air traffic control. In this thesis, I first detect the presence of a roost in NEXt Generation Weather RADar (NEXRAD) images of purple martin and tree swallow roosts and improve upon Chilson et al. (2019)'s work by altering the network architecture and data preprocessing. Because determining the exact locations of bird roosts is more useful than detection, I also use image segmentation to attempt to locate roosts. I apply a standard U-Net, which shows promising results for determining roost location, achieving a true positive rate of around 0.80 and true negative rate of around 0.85. To increase performance, the dataset is augmented 32 times its original size through a variety of image transformations

Exploring the Effect of Chicano Studies Courses on Student Success at CSU Channel Islands

California State University, Channel Islands (CSUCI) has long embraced the ideal of access to education while seeking to provide high quality degrees for its students. The success of obtaining Hispanic-Serving Institutions grants has been helpful in providing resources for programs offering educational interventions for both Hispanic students and for those from other backgrounds. We have seen anecdotal evidence that Hispanic students who enroll in Chicano Studies courses tend to find community and consequently success. In this project, we use the enormous storehouse of CSUCI data to explore the effectiveness of specific Chicano Studies courses on student success. We apply regression analysis, hypothesis tests for proportions, t-tests, and tests of independence to investigate the quantitative evidence for what we have seen anecdotally

Measuring Interventional Robustness in Reinforcement Learning

Recent work in reinforcement learning has focused on several characteristics of learned policies that go beyond maximizing reward. These properties include fairness, explainability, generalization, and robustness. In this paper, we define interventional robustness (IR), a measure of how much variability is introduced into learned policies by incidental aspects of the training procedure, such as the order of training data or the particular exploratory actions taken by agents. A training procedure has high IR when the agents it produces take very similar actions under intervention, despite variation in these incidental aspects of the training procedure. We develop an intuitive, quantitative measure of IR and calculate it for eight algorithms in three Atari environments across dozens of interventions and states. From these experiments, we find that IR varies with the amount of training and type of algorithm and that high performance does not imply high IR, as one might expect.Comment: 17 pages, 13 figure

Modeling Seven Years of Event Horizon Telescope Observations with Radiatively Inefficient Accretion Flow Models

An initial three-station version of the Event Horizon Telescope, a millimeter-wavelength very-long baseline interferometer, has observed Sagittarius A* (Sgr A*) repeatedly from 2007 to 2013, resulting in the measurement of a variety of interferometric quantities. Of particular importance, there is now a large set of closure phases, measured over a number of independent observing epochs. We analyze these observations within the context of a realization of semi-analytic radiatively inefficient disk models, implicated by the low luminosity of Sgr A*. We find a broad consistency among the various observing epochs and between different interferometric data types, with the latter providing significant support for this class of models of Sgr A*. The new data significantly tighten existing constraints on the spin magnitude and its orientation within this model context, finding a spin magnitude of $a=0.10^{+0.30+0.56}_{-0.10-0.10}$, an inclination with respect to the line of sight of $\theta={60^\circ}^{+5^\circ+10^\circ}_{-8^\circ-13^\circ}$, and a position angle of $\xi={156^\circ}^{+10^\circ+14^\circ}_{-17^\circ-27^\circ}$ east of north. These are in good agreement with previous analyses. Notably, the previous $180^\circ$ degeneracy in the position angle has now been conclusively broken by the inclusion of the closure phase measurements. A reflection degeneracy in the inclination remains, permitting two localizations of the spin vector orientation, one of which is in agreement with the orbital angular momentum of the infrared gas cloud G2 and the clockwise disk of young stars. This possibly supports a relationship between Sgr A*'s accretion flow and these larger-scale features.Comment: 16 pages, 11 figures, accepted to Ap

Aminoglycosides for Intra-Abdominal Infection: Equal to the Challenge?

Background: Aminoglycosides, combined with antianaerobic agents, have been used widely for the treatment of intra-abdominal infection. However, some prospective randomized controlled trials and other data suggested that aminoglycosides were less efficacious than newer comparators for the treatment of these infections. We therefore performed a meta-analysis of all prospective randomized controlled trials utilizing aminoglycosides to reevaluate the efficacy of these agents for the treatment of intra-abdominal infection. Methods: Published English-language prospective randomized controlled trials comparing aminoglycosides with other agents for treatment of intra-abdominal infection were identified by MEDLINE search. For each study, data were collected regarding the number of patients enrolled and evaluated, their basic demographic characteristics, the sources of the intra-abdominal infections, the number of failures as determined by the study investigators, quality score, and the use of serum drug concentrations to monitor aminoglycoside therapy. These data were combined to calculate odds ratios for risk of therapeutic failure, which were assessed for significance using Chi-square analysis. Results: Forty-seven prospective randomized controlled trials comparing aminoglycosides to other agents were identified. These were published between 1981 and 2000, and included a total of 5,182 evaluable patients. Analysis of all studies combined revealed an odds ratio that slightly, but significantly, favored the comparators. After excluding six trials using comparators that lacked accepted antianaerobic efficacy, the odds ratio more strongly favored comparators. Trials published since 1990 also notably favored comparators. Analyzing results by quality score or the use of aminoglycoside monitoring did not alter these findings. Conclusions: In this meta-analysis, aminoglycosides were less efficacious than newer comparators for the treatment of intra-abdominal infection. Given the well-known toxicities of these agents, we conclude that they should not be used as first-line therapy for these infections

From policy to patient : using a socio-ecological framework to explore the factors influencing safe practice in UK primary care

Background: The recent and rapid changes in the model of primary care delivery have led to an increased focus on patient safety in what is one of the most diverse and complex healthcare settings. However, previous initiatives have failed to deliver the expected improvements, leading to calls for a better understanding of how a range of personal and contextual factors influence the decisions and behaviours of individual care providers. Methods: The socio-ecological framework, successfully used in public health settings to interpret the complex influences on individual behaviours, enabled a post-hoc deductive analysis of a series of semi-structured interviews conducted with clinical staff and senior managers at a range of practices across five geographically diverse regions in England to explore their perspectives on the factors that influence safe practice. Results: The five levels of the socio-ecological framework successfully helped unpick the myriad influences on safe primary care practice, including, at the Individual level, assumptions of responsibility and previous experience; at the Interpersonal, equitable communication in support of a team ethos; at the Organisational, the physical infrastructure, size and complexity of the practice; at the Community, the health profile and literacy of patients; and at the Policy, meeting the demands of competing local and national governing bodies. Conclusions: Coherent, realistic and achievable goals are needed for improving patient safety in primary care addressing personal, organisational and environmental factors. Such goals and the tools and interventions designed to meet them must therefore be sympathetic to the demands on resources and the characteristics of patients, staff, and their organisations. Using the framework to interpret our findings provided much needed insight into the impact of these varying influences, and highlights the importance of recognising and communicating the relationship between specific contextual factors and the ability of individual providers to provide safe primary care

Automated detection of bird roosts using NEXRAD radar data and Convolutional neural networks

Although NEXRAD radars have proven to be an effective tool for detecting airborne animals, detecting biological phenomena in radar images often involves a manual, time‐ consuming data‐extraction process. This paper focuses on applying machine learning to automatically find radar data that snapshots large aggregations of birds (specifically Purple Martins and Tree Swallows) as they depart en masse from roosting sites. These aggregations are evident in radar images as rings of elevated reflectivity that appear early in the morning as birds depart from roost sites. Our goal was to develop an algorithm that could determine whether an individual radar image contained at least one Purple Martin or Tree Swallow roost. We use a dataset of known roost locations to train three machine learning algorithms that employed (1) a traditional Artificial Neural Network (ANN), (2) a sophisticated preexisting Convolutional Neural Network (CNN) called Inception‐v3, and (3) a shallow CNN built from scratch. The resulting programs were all effective at finding bird roosts, with both the shallow CNN and the Inception‐v3 network making correct determinations about 90 per cent of the time with an AUC above .9. To the best of our knowledge, this study is the first to apply neural networks in the analysis of bird roosts in radar imagery, and these analytical tools offer new avenues of research into the ecology and behavior of flying animals, with practical applications to wind farm placement, air traffic administration and wildlife conservation. The NEXRAD radar network offers a tremendous archive of continental‐scale data and has the potential to capture entire vertebrate populations. We apply existing machine learning models to a new dataset which constitutes a valuable approach to extracting information from this archive.The funding from the NSF-DGE-1545261 grant helped make this research possible. We thank Sandra Pletschet for her time spent collecting the roost data and Dr. Phillip Chilson for his advice on the project. Some of the computing for this project was performed at the OU Supercomputing Center for Education & Research (OSCER) at the University of Oklahoma (OU). Article processing charges for this publication funded in part by the University of Oklahoma Libraries Open Access Fund.Ye