Green Arrow vs. Hawkeye

It was during the twentieth annual Secre

Advanced Computing Systems for Scientific Research

An advanced computing system was constructed at Bridgewater State University to provide students access to computing machines tailored to the purpose of computational scientific research. This paper provides an overview of the construction, design, capability, and future potential of the computing system. Project Reasoning During the course of projects utilizing a numerical weather prediction (NWP) model, it became evident that the desktop computing machines provided to students in computer labs were not capable of yielding results in a reasonable amount of time for non-standard applications. The standard configuration of computers in the Conant Science and Mathematics Center at Bridgewater State University is sufficient for the majority of student purposes; however, these standard computers become insufficient for more comprehensive applications. Because of this insufficiency, it became necessary to seek better performing computer systems to support research applications. Project Execution To increase the computational power of computing systems on campus, two distinct steps were taken. The first step was the upgrade of a standard desktop computer. This upgrade provided a single desktop machine with superior computing capability to the standard machines available to students. The second step was the construction of a Linux computer cluster from several networked previous generation machines

Patterns of Drinking Among the Deaf

Thirty-nine White deaf persons functioning normally within the general hearing community were surveyed on a variety of factors concerning their use of alcohol, and compared to the data from two comparable hearing samples reported previously in the literature. No significant differences were found between the deaf and heharing samples on patterns of drinking or other parameters of alcohol use. Heavier alcohol use among the deaf correlated significantly with reported frequency of driving after having drunk too much, age of having had first drink, ever having been drunk, feeling guilt over drinking too much, and others criticizing the respondent for drinking behavior. Heavier use also tended to be correlated with attendance at an all-deaf school. Implications of the findings of similar drinking patterns for the deaf and the hearing are discussed in terms of the lack of specific rehabilitation facilities for the deaf, along with possible reasons for the lack of use by deaf clients of alcohol rehabilitation agencies in the community

Using Sequential Mixed Methods to Evaluate the Contribution of Absorptive Capacity (ACAP)

How might Absorptive Capacity (ACAP) (Cohen & Levinthal 1990,,Song et al. 2018) contribute to indigenous firm innovation and growth and how might the effects of this construct be evaluated at both firm and policy level? This paper demonstrates how a mixed methods research design and data analysis strategy can address the research question outlined above. Within the ‘mixed methods’ research genre, the design approach argued for here is for a ‘sequential mixed methods research’ approach. This is where one methodology is followed sequentially by another to add robustness to the overall findings from a study. The approach can also be described as a multi-phase research design depending on the number and type of research techniques utilised. Adopting this methodology however allows for data triangulation possibilities as the combination of archival data (secondary) and interview data (primary) gives complementary perspectives on the same proprietary dataset of cases (n=20)(Eisenhardt1989). Combining this triangulation of data with the proposed methodological triangulation can further strengthen the internal validity of the overall findings in the study. The data analysis strategy suggested here employs firstly an exploratory cross – case analysis (Yin 2018), using thematic coding (Saldana 2013) to identify the underlying ACAP mechanisms at play. This is then followed sequentially by a Qualitative Comparative Analysis (Rihoux and Ragin 2009). QCA is a data analysis technique which is used for determining which logical conclusions a data set supports. This proposed research design is applicable to complex research settings where a study can deliver findings on the ‘contribution’ of mechanisms underpinning ACAP (Cordero & Ferreira 2019), to the innovation and growth performance of the firm rather than assigning precise ‘attribution’ or impact measures to individual factors or variables

Measuring outcomes of importance to women with stress urinary incontinence

The definitive version is available at www.interscience.wiley.comPeer reviewedPostprin

Search for Gamma-ray Emission from Dark Matter Annihilation in the Large Magellanic Cloud with the Fermi Large Area Telescope

At a distance of 50 kpc and with a dark matter mass of $\sim10^{10}$ M$_{\odot}$, the Large Magellanic Cloud (LMC) is a natural target for indirect dark matter searches. We use five years of data from the Fermi Large Area Telescope (LAT) and updated models of the gamma-ray emission from standard astrophysical components to search for a dark matter annihilation signal from the LMC. We perform a rotation curve analysis to determine the dark matter distribution, setting a robust minimum on the amount of dark matter in the LMC, which we use to set conservative bounds on the annihilation cross section. The LMC emission is generally very well described by the standard astrophysical sources, with at most a $1-2\sigma$ excess identified near the kinematic center of the LMC once systematic uncertainties are taken into account. We place competitive bounds on the dark matter annihilation cross section as a function of dark matter particle mass and annihilation channel.Comment: 33 pages, 22 figures Version 2: minor corrections and clarifications after journal peer review proces

Search for Gamma-ray Emission from Dark Matter Annihilation in the Small Magellanic Cloud with the Fermi Large Area Telescope

The Small Magellanic Cloud (SMC) is the second-largest satellite galaxy of the Milky Way and is only 60 kpc away. As a nearby, massive, and dense object with relatively low astrophysical backgrounds, it is a natural target for dark matter indirect detection searches. In this work, we use six years of Pass 8 data from the Fermi Large Area Telescope to search for gamma-ray signals of dark matter annihilation in the SMC. Using data-driven fits to the gamma-ray backgrounds, and a combination of N-body simulations and direct measurements of rotation curves to estimate the SMC DM density profile, we found that the SMC was well described by standard astrophysical sources, and no signal from dark matter annihilation was detected. We set conservative upper limits on the dark matter annihilation cross section. These constraints are in agreement with stronger constraints set by searches in the Large Magellanic Cloud and approach the canonical thermal relic cross section at dark matter masses lower than 10 GeV in the $b\bar{b}$ and $\tau^+\tau^-$ channels.Comment: 17 pages, 11 figures. Accepted by PR

Species' traits predict phenological responses to climate change in butterflies

How do species' traits help identify which species will respond most strongly to future climate change? We examine the relationship between species' traits and phenology in a well-established model system for climate change, the U.K. Butterfly Monitoring Scheme (UKBMS). Most resident U.K. butterfly species have significantly advanced their dates of first appearance during the past 30 years. We show that species with narrower larval diet breadth and more advanced overwintering stages have experienced relatively greater advances in their date of first appearance. In addition, species with smaller range sizes have experienced greater phenological advancement. Our results demonstrate that species' traits can be important predictors of responses to climate change, and they suggest that further investigation of the mechanisms by which these traits influence phenology may aid in understanding species' responses to current and future climate change