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

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

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

Magnetic Order in YBa2_2Cu3_3O6+x_{6+x} Superconductors

Polarized and unpolarized neutron diffraction has been used to search for magnetic order in YBa$_2$Cu$_3$O$_{6+x}$ superconductors. Most of the measurements were made on a high quality crystal of YBa$_2$Cu$_3$O$_{6.6}$. 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 $a$-$b$ 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 $d$-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 YBa$_2$Cu$_3$O$_{7}$ show no signal while a small magnetic intensity is found in YBa$_2$Cu$_3$O$_{6.45}$ 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