1,217 research outputs found
Absolute Calibration of a 200 MeV Proton Polarimeter for Use with the Brookhaven Linac
This work was supported by the National Science Foundation Grant NSF PHY 81-14339 and by Indiana Universit
The association of cognitive and somatic depressive symptoms with depression recognition and outcomes after myocardial infarction
BACKGROUND: Among patients with acute myocardial infarction (AMI), depression is both common and under-recognized. The association of different manifestations of depression, somatic and cognitive, with depression recognition and long-term prognosis is poorly understood. METHODS AND RESULTS: Depression was confirmed in 481 AMI patients enrolled from 21 sites during their index hospitalization with a Patient Health Questionnaire (PHQ-9) score ≥10. Within the PHQ-9, separate somatic and cognitive symptom scores were derived and the independent association between these domains and the clinical recognition of depression, as documented in the medical records, was evaluated. In a separate multisite AMI registry of 2,347 patients, the association between somatic and cognitive depressive symptoms and 4-year all-cause mortality and 1-year all-cause rehospitalization was evaluated. Depression was clinically recognized in 29% (n=140) of patients. Cognitive depressive symptoms (Relative Risk [RR] per Standard Deviation [SD] increase=1.14; 95% confidence interval [CI] 1.03–1.26; p=0.01) were independently associated with depression recognition, while the association for somatic symptoms and recognition (RR=1.04; 95% CI 0.87–1.26; p=0.66) was not significant. However, unadjusted Cox regression analyses found that only somatic depressive symptoms were associated with 4-year mortality (Hazard Ratio [HR] per SD increase=1.22; 95% confidence interval [CI] 1.08–1.39) or 1-year rehospitalization (HR=1.22; 95%CI 1.11–1.33) while cognitive manifestations were not (HR for mortality=1.01; 95%CI 0.89–1.14; HR for rehospitalization=1.01; 95%CI 0.93–1.11). After multivariable adjustment, the association between somatic symptoms and rehospitalization persisted (HR=1.16; 95% CI:1.06–1.27; p=0.01) but was attenuated for mortality (HR=1.07; 95% CI:0.94–1.21; p=0.30). CONCLUSIONS: Depression after AMI was recognized in fewer than 1 in 3 patients. Although cognitive symptoms were associated with recognition of depression, somatic symptoms were associated with long-term outcomes. Comprehensive screening and treatment of both somatic and cognitive symptoms may be necessary to optimize depression recognition and treatment in AMI patients
BeepTrace: Blockchain-enabled Privacy-preserving Contact Tracing for COVID-19 Pandemic and Beyond
The outbreak of COVID-19 pandemic has exposed an urgent need for effective contact tracing solutions through mobile phone applications to prevent the infection from spreading further. However, due to the nature of contact tracing, public concern on privacy issues has been a bottleneck to the existing solutions, which is significantly affecting the uptake of contact tracing applications across the globe. In this paper, we present a blockchain-enabled privacy-preserving contact tracing scheme: BeepTrace, where we propose to adopt blockchain bridging the user/patient and the authorized solvers to desensitize the user ID and location information. Compared with recently proposed contact tracing solutions, our approach shows higher security and privacy with the additional advantages of being battery friendly and globally accessible. Results show viability in terms of the required resource at both server and mobile phone perspectives. Through breaking the privacy concerns of the public, the proposed BeepTrace solution can provide a timely framework for authorities, companies, software developers and researchers to fast develop and deploy effective digital contact tracing applications, to conquer COVID-19 pandemic soon. Meanwhile, the open initiative of BeepTrace allows worldwide collaborations, integrate existing tracing and positioning solutions with the help of blockchain technology
Mental models of high reliability systems
Reliable performance in complex systems is determined in part by the ade quacy with which mental models of the system capture accurately the dimen sions of system coupling and system complexity. Failure to register coupling and complexity leads the observer to intervene into an imagined technology that does not exist and to convert opportunities for error into actual errors. To decrease the frequency with which this conversion occurs, people can make their models more complex or the systems they monitor less complex. Neither type of change is as daunting as it may appear, and this is illustrated by an analysis of the mental model and system design associated with the invasion of Grenada.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68652/2/10.1177_108602668900300203.pd
Magnetic Order in YBaCuO Superconductors
Polarized and unpolarized neutron diffraction has been used to search for
magnetic order in YBaCuO superconductors. Most of the
measurements were made on a high quality crystal of YBaCuO. It
is shown that this crystal has highly ordered ortho-II chain order, and a sharp
superconducting transition. Inelastic scattering measurements display a very
clean spin-gap and pseudogap with any intensity at 10 meV being 50 times
smaller than the resonance intensity. The crystal shows a complicated magnetic
order that appears to have three components. A magnetic phase is found at high
temperatures that seems to stem from an impurity with a moment that is in the
- plane, but disordered on the crystal lattice. A second ordering occurs
near the pseudogap temperature that has a shorter correlation length than the
high temperature phase and a moment direction that is at least partly along the
c-axis of the crystal. Its moment direction, temperature dependence, and Bragg
intensities suggest that it may stem from orbital ordering of the -density
wave (DDW) type. An additional intensity increase occurs below the
superconducting transition. The magnetic intensity in these phases does not
change noticeably in a 7 Tesla magnetic field aligned approximately along the
c-axis. Searches for magnetic order in YBaCuO show no signal
while a small magnetic intensity is found in YBaCuO that is
consistent with c-axis directed magnetic order. The results are contrasted with
other recent neutron measurements.Comment: 11 pages with 10 figure
Northern Ireland farm-level management factors for prolonged bovine tuberculosis herd breakdowns.
Publication history: Accepted - 16 September 2020; Published online - 28 September 2020This study determined farm management factors associated with long-duration bovine tuberculosis (bTB) breakdowns disclosed in the period 23 May 2016 to 21 May 2018; a study area not previously subject to investigation in Northern Ireland. A farm-level epidemiological investigation (n = 2935) was completed when one or more Single Intradermal Comparative Cervical Test (SICCT) reactors or when one or more confirmed (positive histological and/or bacteriological result) lesion at routine slaughter were disclosed. A case-control study design was used to construct an explanatory set of management factors associated with long-duration bTB herd breakdowns; with a case (n = 191) defined as an investigation into a breakdown of 365 days or longer. Purchase of infected animal(s) had the strongest association as the most likely source of infection for long-duration bTB herd breakdowns followed by badgers and then cattle-to-cattle contiguous herd spread. However, 73.5% (95% CI 61.1–85.9%) of the herd type contributing to the purchase of infection source were defined as beef fattening herds. This result demonstrates two subpopulations of prolonged bTB breakdowns, the first being beef fattening herds with main source continuous purchase of infected animals and a second group of primary production herds (dairy, beef cows and mixed) with risk from multiple sources
Modeling what we sample and sampling what we model: challenges for zooplankton model assessment
Zooplankton are the intermediate trophic level between phytoplankton and fish, and are an important component of carbon and nutrient cycles, accounting for a large proportion of the energy transfer to pelagic fishes and the deep ocean. Given zooplankton's importance, models need to adequately represent zooplankton dynamics. A major obstacle, though, is the lack of model assessment. Here we try and stimulate the assessment of zooplankton in models by filling three gaps. The first is that many zooplankton observationalists are unfamiliar with the biogeochemical, ecosystem, size-based and individual-based models that have zooplankton functional groups, so we describe their primary uses and how each typically represents zooplankton. The second gap is that many modelers are unaware of the zooplankton data that are available, and are unaccustomed to the different zooplankton sampling systems, so we describe the main sampling platforms and discuss their strengths and weaknesses for model assessment. Filling these gaps in our understanding of models and observations provides the necessary context to address the last gap—a blueprint for model assessment of zooplankton. We detail two ways that zooplankton biomass/abundance observations can be used to assess models: data wrangling that transforms observations to be more similar to model output; and observation models that transform model outputs to be more like observations. We hope that this review will encourage greater assessment of zooplankton in models and ultimately improve the representation of their dynamics
Transverse spin dependence of pp total cross‐sections
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/87331/2/72_1.pd
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