Learning Rich Geographical Representations: Predicting Colorectal Cancer Survival in the State of Iowa

Neural networks are capable of learning rich, nonlinear feature representations shown to be beneficial in many predictive tasks. In this work, we use these models to explore the use of geographical features in predicting colorectal cancer survival curves for patients in the state of Iowa, spanning the years 1989 to 2012. Specifically, we compare model performance using a newly defined metric -- area between the curves (ABC) -- to assess (a) whether survival curves can be reasonably predicted for colorectal cancer patients in the state of Iowa, (b) whether geographical features improve predictive performance, and (c) whether a simple binary representation or richer, spectral clustering-based representation perform better. Our findings suggest that survival curves can be reasonably estimated on average, with predictive performance deviating at the five-year survival mark. We also find that geographical features improve predictive performance, and that the best performance is obtained using richer, spectral analysis-elicited features.Comment: 8 page

HNPCC (Lynch Syndrome): Differential Diagnosis, Molecular Genetics and Management - a Review

HNPCC (Lynch syndrome) is the most common form of hereditary colorectal cancer (CRC), wherein it accounts for between 2-7 percent of the total CRC burden. When considering the large number of extracolonic cancers integral to the syndrome, namely carcinoma of the endometrium, ovary, stomach, hepatobiliary system, pancreas, small bowel, brain tumors, and upper uroepithelial tract, these estimates of its frequency are likely to be conservative. The diagnosis is based upon its natural history in concert with a comprehensive cancer family history inclusive of all anatomic sites. In order for surveillance and management to be effective and, indeed, lifesaving, among these high-risk patients, the linchpin to cancer control would be the physician, who must be knowledgeable about hereditary cancer syndromes, their molecular and medical genetics, genetic counseling, and, most importantly, the natural history of the disorders, so that the entirety of this knowledge can be melded to highly-targeted management

The Helicopter Antenna Radiation Prediction Code (HARP)

The first nine months effort in the development of a user oriented computer code, referred to as the HARP code, for analyzing the radiation from helicopter antennas is described. The HARP code uses modern computer graphics to aid in the description and display of the helicopter geometry. At low frequencies the helicopter is modeled by polygonal plates, and the method of moments is used to compute the desired patterns. At high frequencies the helicopter is modeled by a composite ellipsoid and flat plates, and computations are made using the geometrical theory of diffraction. The HARP code will provide a user friendly interface, employing modern computer graphics, to aid the user to describe the helicopter geometry, select the method of computation, construct the desired high or low frequency model, and display the results

Mid-Infrared Ethane Emission on Neptune and Uranus

We report 8- to 13-micron spectral observations of Neptune and Uranus from the NASA Infrared Telescope Facility spanning more than a decade. The spectroscopic data indicate a steady increase in Neptune's mean atmospheric 12-micron ethane emission from 1985 to 2003, followed by a slight decrease in 2004. The simplest explanation for the intensity variation is an increase in stratospheric effective temperature from 155 +/- 3 K in 1985 to 176 +/- 3 K in 2003 (an average rate of 1.2 K/year), and subsequent decrease to 165 +/- 3 K in 2004. We also detected variation of the overall spectral structure of the ethane band, specifically an apparent absorption structure in the central portion of the band; this structure arises from coarse spectral sampling coupled with a non-uniform response function within the detector elements. We also report a probable direct detection of ethane emission on Uranus. The deduced peak mole fraction is approximately an order of magnitude higher than previous upper limits for Uranus. The model fit suggests an effective temperature of 114 +/- 3 K for the globally-averaged stratosphere of Uranus, which is consistent with recent measurements indicative of seasonal variation.Comment: Accepted for publication in ApJ. 16 pages, 10 figures, 2 table

Setting priorities to inform assessment of care homes’ readiness to participate in healthcare innovation: a systematic mapping review and consensus process

© 2020 The Author(s). This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly citedOrganisational context is known to impact on the successful implementation of healthcare initiatives in care homes. We undertook a systematic mapping review to examine whether researchers have considered organisational context when planning, conducting, and reporting the implementation of healthcare innovations in care homes. Review data were mapped against the Alberta Context Tool, which was designed to assess organizational context in care homes. The review included 56 papers. No studies involved a systematic assessment of organisational context prior to implementation, but many provided post hoc explanations of how organisational context affected the success or otherwise of the innovation. Factors identified to explain a lack of success included poor senior staff engagement, non-alignment with care home culture, limited staff capacity to engage, and low levels of participation from health professionals such as general practitioners (GPs). Thirty-five stakeholders participated in workshops to discuss findings and develop questions for assessing care home readiness to participate in innovations. Ten questions were developed to initiate conversations between innovators and care home staff to support research and implementation. This framework can help researchers initiate discussions about health-related innovation. This will begin to address the gap between implementation theory and practice.Peer reviewe

Leveraging OpenStack and Ceph for a Controlled-Access Data Cloud

While traditional HPC has and continues to satisfy most workflows, a new generation of researchers has emerged looking for sophisticated, scalable, on-demand, and self-service control of compute infrastructure in a cloud-like environment. Many also seek safe harbors to operate on or store sensitive and/or controlled-access data in a high capacity environment. To cater to these modern users, the Minnesota Supercomputing Institute designed and deployed Stratus, a locally-hosted cloud environment powered by the OpenStack platform, and backed by Ceph storage. The subscription-based service complements existing HPC systems by satisfying the following unmet needs of our users: a) on-demand availability of compute resources, b) long-running jobs (i.e., $> 30$ days), c) container-based computing with Docker, and d) adequate security controls to comply with controlled-access data requirements. This document provides an in-depth look at the design of Stratus with respect to security and compliance with the NIH's controlled-access data policy. Emphasis is placed on lessons learned while integrating OpenStack and Ceph features into a so-called "walled garden", and how those technologies influenced the security design. Many features of Stratus, including tiered secure storage with the introduction of a controlled-access data "cache", fault-tolerant live-migrations, and fully integrated two-factor authentication, depend on recent OpenStack and Ceph features.Comment: 7 pages, 5 figures, PEARC '18: Practice and Experience in Advanced Research Computing, July 22--26, 2018, Pittsburgh, PA, US

An Improved Approximate Consensus Algorithm in the Presence of Mobile Faults

This paper explores the problem of reaching approximate consensus in synchronous point-to-point networks, where each pair of nodes is able to communicate with each other directly and reliably. We consider the mobile Byzantine fault model proposed by Garay '94 -- in the model, an omniscient adversary can corrupt up to $f$ nodes in each round, and at the beginning of each round, faults may "move" in the system (i.e., different sets of nodes may become faulty in different rounds). Recent work by Bonomi et al. '16 proposed a simple iterative approximate consensus algorithm which requires at least $4f+1$ nodes. This paper proposes a novel technique of using "confession" (a mechanism to allow others to ignore past behavior) and a variant of reliable broadcast to improve the fault-tolerance level. In particular, we present an approximate consensus algorithm that requires only $\lceil 7f/2\rceil + 1$ nodes, an $\lfloor f/2 \rfloor$ improvement over the state-of-the-art algorithms. Moreover, we also show that the proposed algorithm is optimal within a family of round-based algorithms