5,787 research outputs found
Impact of time to appropriate therapy on mortality in patients with vancomycin-intermediate Staphylococcus aureus infection
Despite the increasing incidence of vancomycin-intermediate Staphylococcus aureus (VISA) infections, few studies have examined the impact of delay in receipt of appropriate antimicrobial therapy on outcomes in VISA patients. We examined the effects of timing of appropriate antimicrobial therapy in a cohort of patients with sterile-site methicillin-resistant S. aureus (MRSA) and VISA infections. In this single-center, retrospective cohort study, we identified all patients with MRSA or VISA sterile-site infections from June 2009 to February 2015. Clinical outcomes were compared according to MRSA/VISA classification, demographics, comorbidities, and antimicrobial treatment. Thirty-day all-cause mortality was modeled with Kaplan-Meier curves. Multivariate logistic regression analysis (MVLRA) was used to determine odds ratios for mortality. We identified 354 patients with MRSA (n = 267) or VISA (n = 87) sterile-site infection. Fifty-five patients (15.5%) were nonsurvivors. Factors associated with mortality in MVLRA included pneumonia, unknown source of infection, acute physiology and chronic health evaluation (APACHE) II score, solid-organ malignancy, and admission from skilled care facilities. Time to appropriate antimicrobial therapy was not significantly associated with outcome. Presence of a VISA infection compared to that of a non-VISA S. aureus infection did not result in excess mortality. Linezolid use was a risk for mortality in patients with APACHE II scores of ≥14. Our results suggest that empirical vancomycin use in patients with VISA infections does not result in excess mortality. Future studies should (i) include larger numbers of patients with VISA infections to confirm the findings presented here and (ii) determine the optimal antibiotic therapy for critically ill patients with MRSA and VISA infections
Comparing compact binary parameter distributions I: Methods
Being able to measure each merger's sky location, distance, component masses,
and conceivably spins, ground-based gravitational-wave detectors will provide a
extensive and detailed sample of coalescing compact binaries (CCBs) in the
local and, with third-generation detectors, distant universe. These
measurements will distinguish between competing progenitor formation models. In
this paper we develop practical tools to characterize the amount of
experimentally accessible information available, to distinguish between two a
priori progenitor models. Using a simple time-independent model, we demonstrate
the information content scales strongly with the number of observations. The
exact scaling depends on how significantly mass distributions change between
similar models. We develop phenomenological diagnostics to estimate how many
models can be distinguished, using first-generation and future instruments.
Finally, we emphasize that multi-observable distributions can be fully
exploited only with very precisely calibrated detectors, search pipelines,
parameter estimation, and Bayesian model inference
Characterizing Entanglement Sources
We discuss how to characterize entanglement sources with finite sets of
measurements. The measurements do not have to be tomographically complete, and
may consist of POVMs rather than von Neumann measurements. Our method yields a
probability that the source generates an entangled state as well as estimates
of any desired calculable entanglement measures, including their error bars. We
apply two criteria, namely Akaike's information criterion and the Bayesian
information criterion, to compare and assess different models (with different
numbers of parameters) describing entanglement-generating devices. We discuss
differences between standard entanglement-verificaton methods and our present
method of characterizing an entanglement source.Comment: This submission, together with the next one, supersedes
arXiv:0806.416
Information criteria for efficient quantum state estimation
Recently several more efficient versions of quantum state tomography have
been proposed, with the purpose of making tomography feasible even for
many-qubit states. The number of state parameters to be estimated is reduced by
tentatively introducing certain simplifying assumptions on the form of the
quantum state, and subsequently using the data to rigorously verify these
assumptions. The simplifying assumptions considered so far were (i) the state
can be well approximated to be of low rank, or (ii) the state can be well
approximated as a matrix product state. We add one more method in that same
spirit: we allow in principle any model for the state, using any (small) number
of parameters (which can, e.g., be chosen to have a clear physical meaning),
and the data are used to verify the model. The proof that this method is valid
cannot be as strict as in above-mentioned cases, but is based on
well-established statistical methods that go under the name of "information
criteria." We exploit here, in particular, the Akaike Information Criterion
(AIC). We illustrate the method by simulating experiments on (noisy) Dicke
states
The complex network of global cargo ship movements
Transportation networks play a crucial role in human mobility, the exchange
of goods, and the spread of invasive species. With 90% of world trade carried
by sea, the global network of merchant ships provides one of the most important
modes of transportation. Here we use information about the itineraries of
16,363 cargo ships during the year 2007 to construct a network of links between
ports. We show that the network has several features which set it apart from
other transportation networks. In particular, most ships can be classified in
three categories: bulk dry carriers, container ships and oil tankers. These
three categories do not only differ in the ships' physical characteristics, but
also in their mobility patterns and networks. Container ships follow regularly
repeating paths whereas bulk dry carriers and oil tankers move less predictably
between ports. The network of all ship movements possesses a heavy-tailed
distribution for the connectivity of ports and for the loads transported on the
links with systematic differences between ship types. The data analyzed in this
paper improve current assumptions based on gravity models of ship movements, an
important step towards understanding patterns of global trade and bioinvasion.Comment: 7 figures Accepted for publication by Journal of the Royal Society
Interface (2010) For supplementary information, see
http://www.icbm.de/~blasius/publications.htm
Probability Models for Degree Distributions of Protein Interaction Networks
The degree distribution of many biological and technological networks has
been described as a power-law distribution. While the degree distribution does
not capture all aspects of a network, it has often been suggested that its
functional form contains important clues as to underlying evolutionary
processes that have shaped the network. Generally, the functional form for the
degree distribution has been determined in an ad-hoc fashion, with clear
power-law like behaviour often only extending over a limited range of
connectivities. Here we apply formal model selection techniques to decide which
probability distribution best describes the degree distributions of protein
interaction networks. Contrary to previous studies this well defined approach
suggests that the degree distribution of many molecular networks is often
better described by distributions other than the popular power-law
distribution. This, in turn, suggests that simple, if elegant, models may not
necessarily help in the quantitative understanding of complex biological
processes.
On designing observers for time-delay systems with nonlinear disturbances
This is the post print version of the article. The official published version can be obtained from the link below - Copyright 2002 Taylor & Francis LtdIn this paper, the observer design problem is studied for a class of time-delay nonlinear systems. The system under consideration is subject to delayed state and non-linear disturbances. The time-delay is allowed to be time-varying, and the non-linearities are assumed to satisfy global Lipschitz conditions. The problem addressed is the design of state observers such that, for the admissible time-delay as well as non-linear disturbances, the dynamics of the observation error is globally exponentially stable. An effective algebraic matrix inequality approach is developed to solve the non-linear observer design problem. Specifically, some conditions for the existence of the desired observers are derived, and an explicit expression of desired observers is given in terms of some free parameters. A simulation example is included to illustrate the practical applicability of the proposed theory.The work of Z. Wang was supported in part by the University of Kaiserslautern of Germany and the Alexander von Humboldt Foundation of Germany
Winter Conditions Influence Biological Responses of Migrating Hummingbirds
Conserving biological diversity given ongoing environmental changes requires the knowledge of how organisms respond biologically to these changes; however, we rarely have this information. This data deficiency can be addressed with coordinated monitoring programs that provide field data across temporal and spatial scales and with process-based models, which provide a method for predicting how species, in particular migrating species that face different conditions across their range, will respond to climate change. We evaluate whether environmental conditions in the wintering grounds of broad-tailed hummingbirds influence physiological and behavioral attributes of their migration. To quantify winter ground conditions, we used operative temperature as a proxy for physiological constraint, and precipitation and the normalized difference vegetation index (NDVI) as surrogates of resource availability. We measured four biological response variables: molt stage, timing of arrival at stopover sites, body mass, and fat. Consistent with our predictions, we found that birds migrating north were in earlier stages of molt and arrived at stopover sites later when NDVI was low. These results indicate that wintering conditions impact the timing and condition of birds as they migrate north. In addition, our results suggest that biologically informed environmental surrogates provide a valuable tool for predicting how climate variability across years influences the animal populations
Continental-scale patterns of pathogen prevalence: a case study on the corncrake
Pathogen infections can represent a substantial threat to wild populations, especially those already limited in size. To determine how much variation in the pathogens observed among fragmented populations is caused by ecological factors, one needs to examine systems where host genetic diversity is consistent among the populations, thus controlling for any potentially confounding genetic effects. Here, we report geographic variation in haemosporidian infection among European populations of corncrake. This species now occurs in fragmented populations, but there is little genetic structure and equally high levels of genetic diversity among these populations. We observed a longitudinal gradient of prevalence from western to Eastern Europe negatively correlated with national agricultural yield, but positively correlated with corncrake census population sizes when only the most widespread lineage is considered. This likely reveals a possible impact of local agriculture intensity, which reduced host population densities in Western Europe and, potentially, insect vector abundance, thus reducing the transmission of pathogens. We conclude that in the corncrake system, where metapopulation dynamics resulted in variations in local census population sizes, but not in the genetic impoverishment of these populations, anthropogenic activity has led to a reduction in host populations and pathogen prevalence
Ecological Effects of Fear: How Spatiotemporal Heterogeneity in Predation Risk Influences Mule Deer Access to Forage in a Sky‐Island System
Forage availability and predation risk interact to affect habitat use of ungulates across many biomes. Within sky‐island habitats of the Mojave Desert, increased availability of diverse forage and cover may provide ungulates with unique opportunities to extend nutrient uptake and/or to mitigate predation risk. We addressed whether habitat use and foraging patterns of female mule deer (Odocoileus hemionus) responded to normalized difference vegetation index (NDVI), NDVI rate of change (green‐up), or the occurrence of cougars (Puma concolor). Female mule deer used available green‐up primarily in spring, although growing vegetation was available during other seasons. Mule deer and cougar shared similar habitat all year, and our models indicated cougars had a consistent, negative effect on mule deer access to growing vegetation, particularly in summer when cougar occurrence became concentrated at higher elevations. A seemingly late parturition date coincided with diminishing NDVI during the lactation period. Sky‐island populations, rarely studied, provide the opportunity to determine how mule deer respond to growing foliage along steep elevation and vegetation gradients when trapped with their predators and seasonally limited by aridity. Our findings indicate that fear of predation may restrict access to the forage resources found in sky islands
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