3,778 research outputs found
NuSTAR Tests of Sterile-Neutrino Dark Matter: New Galactic Bulge Observations and Combined Impact
We analyze two dedicated NuSTAR observations with exposure ks
located from the Galactic plane, one above and the other
below, to search for x-ray lines from the radiative decay of sterile-neutrino
dark matter. These fields were chosen to minimize astrophysical x-ray
backgrounds while remaining near the densest region of the dark matter halo. We
find no evidence of anomalous x-ray lines in the energy range 5--20 keV,
corresponding to sterile neutrino masses 10--40 keV. Interpreted in the context
of sterile neutrinos produced via neutrino mixing, these observations provide
the leading constraints in the mass range 10--12 keV, improving upon previous
constraints in this range by a factor . We also compare our results to
Monte Carlo simulations, showing that the fluctuations in our derived limit are
not dominated by systematic effects. An updated model of the instrumental
background, which is currently under development, will improve NuSTAR's
sensitivity to anomalous x-ray lines, particularly for energies 3--5 keV.Comment: 16 pages, 5 figures. Text updated to match published version in PRD.
Conclusions unchange
Bayesian spatio-temporal analysis and geospatial risk factors of Human Monocytic Ehrlichiosis
Citation: Raghavan RK, Neises D, Goodin DG, Andresen DA, Ganta RR (2014) Bayesian Spatio-Temporal Analysis and Geospatial Risk Factors of Human Monocytic Ehrlichiosis. PLoS ONE 9(7): e100850. doi:10.1371/journal.pone.0100850Variations in spatio-temporal patterns of Human Monocytic Ehrlichiosis (HME) infection in the state of Kansas, USA were examined and the relationship between HME relative risk and various environmental, climatic and socio-economic variables were evaluated. HME data used in the study was reported to the Kansas Department of Health and Environment between years 2005–2012, and geospatial variables representing the physical environment [National Land cover/Land use, NASA Moderate Resolution Imaging Spectroradiometer (MODIS)], climate [NASA MODIS, Prediction of Worldwide Renewable Energy (POWER)], and socio-economic conditions (US Census Bureau) were derived from publicly available sources. Following univariate screening of candidate variables using logistic regressions, two Bayesian hierarchical models were fit; a partial spatio-temporal model with random effects and a spatio-temporal interaction term, and a second model that included additional covariate terms. The best fitting model revealed that spatio-temporal autocorrelation in Kansas increased steadily from 2005–2012, and identified poverty status, relative humidity, and an interactive factor, ‘diurnal temperature range x mixed forest area’ as significant county-level risk factors for HME. The identification of significant spatio-temporal pattern and new risk factors are important in the context of HME prevention, for future research in the areas of ecology and evolution of HME, and as well as climate change impacts on tick-borne diseases
Socionic Multi-Agent Systems Based on Reflexive Petri Nets and Theories of Social Self-Organisation
This contribution summarises the core results of the transdisciplinary ASKO project, part of the German DFG's programme Sozionik, which combines sociologists' and computer scientists' skills in order to create improved theories and models of artificial societies. Our research group has (a) formulated a social theory, which is able to explain fundamental mechanisms of self-organisation in both natural and artificial societies, (b) modelled this in a mathematical way using a visual formalism, and (c) developed a novel multi-agent system architecture which is conceptually coherent, recursively structured (hence non-eclectic) and based on our social theory. The article presents an outline of both a sociological middle-range theory of social self-organisation in educational institutions, its formal, Petri net based model, including a simulation of one of its main mechanisms, and the multi-agent system architecture SONAR. It describes how the theory was created by a re-analysis of some grand social theories, by grounding it empirically, and finally how the theory was evaluated by modelling its concepts and statements.Multi-Agents Systems, Petri Nets, Self-Organisation, Social Theories
Learning fluid physics from highly turbulent data using sparse physics-informed discovery of empirical relations (SPIDER)
We show how a complete mathematical description of a complicated physical
phenomenon can be learned from observational data via a hybrid approach
combining three simple and general ingredients: physical assumptions of
smoothness, locality, and symmetry, a weak formulation of differential
equations, and sparse regression. To illustrate this, we extract a system of
governing equations describing flows of incompressible Newtonian fluids -- the
Navier-Stokes equation, the continuity equation, and the boundary conditions --
from numerical data describing a highly turbulent channel flow in three
dimensions. These relations have the familiar form of partial differential
equations, which are easily interpretable and readily provide information about
the relative importance of different physical effects as well as insight into
the quality of the data, serving as a useful diagnostic tool. The approach
described here is remarkably robust, yielding accurate results for very high
noise levels, and should thus be well-suited to experimental data
Virulence mismatches in index hosts shape the outcomes of cross-species transmission
Whether a pathogen entering a new host species results in a single infection or in onward transmission, and potentially an outbreak, depends upon the progression of infection in the index case. Although index infections are rarely observable in nature, experimental inoculations of pathogens into novel host species provide a rich and largely unexploited data source for meta-analyses to identify the host and pathogen determinants of variability in infection outcomes. We analyzed the progressions of 514 experimental cross-species inoculations of rabies virus, a widespread zoonosis which in nature exhibits both dead-end infections and varying levels of sustained transmission in novel hosts. Inoculations originating from bats rather than carnivores, and from warmer- to cooler-bodied species caused infections with shorter incubation periods that were associated with diminished virus excretion. Inoculations between distantly related hosts tended to result in shorter clinical disease periods, which are also expected to impede onward transmission. All effects were modulated by infection dose. Taken together, these results suggest that as host species become more dissimilar, increased virulence might act as a limiting factor preventing onward transmission. These results can explain observed constraints on rabies virus host shifts, describe a previously unrecognized role of host body temperature, and provide a potential explanation for host shifts being less likely between genetically distant species. More generally, our study highlights meta-analyses of experimental infections as a tractable approach to quantify the complex interactions between virus, reservoir, and novel host that shape the outcome of cross-species transmission
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