The 55th College Training Detachment of the Army Air Corps Program On the Gettysburg College Campus, 1943-1944

The 55th College Training Detachment of the Air Force Cadet Program came to Gettysburg College in 1943. It was a separate program designed to provide educated officers for the Air Corps in the United States Army. These trainees would not only learn military drill, physical training, medical aid and flight skills, but they would also study physics, math, English, history, and geography. They were taught by members of the Gettysburg College staff and housed on campus, in dorms and fraternity houses.Their presence on campus was a constant reminder for regular students that the country was in the midst of a war

MS-062: George Hay Kain Papers, Class of 1897

The collection consists of 46 of George Hay Kain’s letters to his college girlfriend, A. Marjorie Zug, a student at the Women’s College of Baltimore. His letters include commentary on various aspects of college life, including classes, assignments, faculty, fraternity events, sports, commencement, class days, the Preparatory School, and the college publications. The letters date from 1896-1898. Special Collections and College Archives Finding Aids are discovery tools used to describe and provide access to our holdings. Finding aids include historical and biographical information about each collection in addition to inventories of their content. More information about our collections can be found on our website http://www.gettysburg.edu/special_collections/collections/.https://cupola.gettysburg.edu/findingaidsall/1057/thumbnail.jp

A Quantum Random Walk Search Algorithm

Quantum random walks on graphs have been shown to display many interesting properties, including exponentially fast hitting times when compared with their classical counterparts. However, it is still unclear how to use these novel properties to gain an algorithmic speed-up over classical algorithms. In this paper, we present a quantum search algorithm based on the quantum random walk architecture that provides such a speed-up. It will be shown that this algorithm performs an oracle search on a database of $N$ items with $O(\sqrt{N})$ calls to the oracle, yielding a speed-up similar to other quantum search algorithms. It appears that the quantum random walk formulation has considerable flexibility, presenting interesting opportunities for development of other, possibly novel quantum algorithms.Comment: 13 pages, 3 figure

Fraud Dataset Benchmark and Applications

Standardized datasets and benchmarks have spurred innovations in computer vision, natural language processing, multi-modal and tabular settings. We note that, as compared to other well researched fields, fraud detection has unique challenges: high-class imbalance, diverse feature types, frequently changing fraud patterns, and adversarial nature of the problem. Due to these, the modeling approaches evaluated on datasets from other research fields may not work well for the fraud detection. In this paper, we introduce Fraud Dataset Benchmark (FDB), a compilation of publicly available datasets catered to fraud detection FDB comprises variety of fraud related tasks, ranging from identifying fraudulent card-not-present transactions, detecting bot attacks, classifying malicious URLs, estimating risk of loan default to content moderation. The Python based library for FDB provides a consistent API for data loading with standardized training and testing splits. We demonstrate several applications of FDB that are of broad interest for fraud detection, including feature engineering, comparison of supervised learning algorithms, label noise removal, class-imbalance treatment and semi-supervised learning. We hope that FDB provides a common playground for researchers and practitioners in the fraud detection domain to develop robust and customized machine learning techniques targeting various fraud use cases

Projective simulation for artificial intelligence

We propose a model of a learning agent whose interaction with the environment is governed by a simulation-based projection, which allows the agent to project itself into future situations before it takes real action. Projective simulation is based on a random walk through a network of clips, which are elementary patches of episodic memory. The network of clips changes dynamically, both due to new perceptual input and due to certain compositional principles of the simulation process. During simulation, the clips are screened for specific features which trigger factual action of the agent. The scheme is different from other, computational, notions of simulation, and it provides a new element in an embodied cognitive science approach to intelligent action and learning. Our model provides a natural route for generalization to quantum-mechanical operation and connects the fields of reinforcement learning and quantum computation.Comment: 22 pages, 18 figures. Close to published version, with footnotes retaine

Improving our understanding of metal implant failures: Multiscale chemical imaging of exogenous metals in ex-vivo biological tissues

Biological exposures to micro- and nano-scale exogenous metal particles generated as a consequence of in-service degradation of orthopaedic prosthetics can result in severe adverse tissues reactions. However, individual reactions are highly variable and are not easily predicted, due to in part a lack of understanding of the speciation of the metal-stimuli which dictates cellular interactions and toxicity. Investigating the chemistry of implant derived metallic particles in biological tissue samples is complicated by small feature sizes, low concentrations and often a heterogeneous speciation and distribution. These challenges were addressed by developing a multi-scale two-dimensional X-ray absorption spectroscopic (XAS) mapping approach to discriminate sub-micron changes in particulate chemistry within ex-vivo tissues associated with failed CoCrMo total hip replacements (THRs). As a result, in the context of THRs, we demonstrate much greater variation in Cr chemistry within tissues compared with previous reports. Cr compounds including phosphate, hydroxide, oxide, metal and organic complexes were observed and correlated with Co and Mo distributions. This variability may help explain the lack of agreement between biological responses observed in experimental exposure models and clinical outcomes. The multi-scale 2D XAS mapping approach presents an essential tool in discriminating the chemistry in dilute biological systems where speciation heterogeneity is expected. Significance: Metal implants are routinely used in healthcare but may fail following degradation in the body. Although specific implants can be identified as ‘high-risk’, our analysis of failures is limited by a lack of understanding of the chemistry of implant metals within the peri-prosthetic milieu. A new approach to identify the speciation and variability in speciation at sub-micron resolution, of dilute exogenous metals within biological tissues is reported; applied to understanding the failure of metallic (CoCrMo) total-hip-replacements widely used in orthopedic surgery. Much greater variation in Cr chemistry was observed compared with previous reports and included phosphate, hydroxide, oxide, metal and organic complexes. This variability may explain lack of agreement between biological responses observed in experimental exposure models and clinical outcomes

Coronary heart disease policy models: a systematic review

BACKGROUND: The prevention and treatment of coronary heart disease (CHD) is complex. A variety of models have therefore been developed to try and explain past trends and predict future possibilities. The aim of this systematic review was to evaluate the strengths and limitations of existing CHD policy models. METHODS: A search strategy was developed, piloted and run in MEDLINE and EMBASE electronic databases, supplemented by manually searching reference lists of relevant articles and reviews. Two reviewers independently checked the papers for inclusion and appraisal. All CHD modelling studies were included which addressed a defined population and reported on one or more key outcomes (deaths prevented, life years gained, mortality, incidence, prevalence, disability or cost of treatment). RESULTS: In total, 75 articles describing 42 models were included; 12 (29%) of the 42 models were micro-simulation, 8 (19%) cell-based, and 8 (19%) life table analyses, while 14 (33%) used other modelling methods. Outcomes most commonly reported were cost-effectiveness (36%), numbers of deaths prevented (33%), life-years gained (23%) or CHD incidence (23%). Among the 42 models, 29 (69%) included one or more risk factors for primary prevention, while 8 (19%) just considered CHD treatments. Only 5 (12%) were comprehensive, considering both risk factors and treatments. The six best-developed models are summarised in this paper, all are considered in detail in the appendices. CONCLUSION: Existing CHD policy models vary widely in their depth, breadth, quality, utility and versatility. Few models have been calibrated against observed data, replicated in different settings or adequately validated. Before being accepted as a policy aid, any CHD model should provide an explicit statement of its aims, assumptions, outputs, strengths and limitations

Common Variants at 9p21 and 8q22 Are Associated with Increased Susceptibility to Optic Nerve Degeneration in Glaucoma

Optic nerve degeneration caused by glaucoma is a leading cause of blindness worldwide. Patients affected by the normal-pressure form of glaucoma are more likely to harbor risk alleles for glaucoma-related optic nerve disease. We have performed a meta-analysis of two independent genome-wide association studies for primary open angle glaucoma (POAG) followed by a normal-pressure glaucoma (NPG, defined by intraocular pressure (IOP) less than 22 mmHg) subgroup analysis. The single-nucleotide polymorphisms that showed the most significant associations were tested for association with a second form of glaucoma, exfoliation-syndrome glaucoma. The overall meta-analysis of the GLAUGEN and NEIGHBOR dataset results (3,146 cases and 3,487 controls) identified significant associations between two loci and POAG: the CDKN2BAS region on 9p21 (rs2157719 [G], OR = 0.69 [95%CI 0.63–0.75], p = 1.86×10−18), and the SIX1/SIX6 region on chromosome 14q23 (rs10483727 [A], OR = 1.32 [95%CI 1.21–1.43], p = 3.87×10−11). In sub-group analysis two loci were significantly associated with NPG: 9p21 containing the CDKN2BAS gene (rs2157719 [G], OR = 0.58 [95% CI 0.50–0.67], p = 1.17×10−12) and a probable regulatory region on 8q22 (rs284489 [G], OR = 0.62 [95% CI 0.53–0.72], p = 8.88×10−10). Both NPG loci were also nominally associated with a second type of glaucoma, exfoliation syndrome glaucoma (rs2157719 [G], OR = 0.59 [95% CI 0.41–0.87], p = 0.004 and rs284489 [G], OR = 0.76 [95% CI 0.54–1.06], p = 0.021), suggesting that these loci might contribute more generally to optic nerve degeneration in glaucoma. Because both loci influence transforming growth factor beta (TGF-beta) signaling, we performed a genomic pathway analysis that showed an association between the TGF-beta pathway and NPG (permuted p = 0.009). These results suggest that neuro-protective therapies targeting TGF-beta signaling could be effective for multiple forms of glaucoma