4,963 research outputs found
Finding the signal in the noise: Could social media be utilized for early hospital notification of multiple casualty events?
IntroductionDelayed notification and lack of early information hinder timely hospital based activations in large scale multiple casualty events. We hypothesized that Twitter real-time data would produce a unique and reproducible signal within minutes of multiple casualty events and we investigated the timing of the signal compared with other hospital disaster notification mechanisms.MethodsUsing disaster specific search terms, all relevant tweets from the event to 7 days post-event were analyzed for 5 recent US based multiple casualty events (Boston Bombing [BB], SF Plane Crash [SF], Napa Earthquake [NE], Sandy Hook [SH], and Marysville Shooting [MV]). Quantitative and qualitative analysis of tweet utilization were compared across events.ResultsOver 3.8 million tweets were analyzed (SH 1.8 m, BB 1.1m, SF 430k, MV 250k, NE 205k). Peak tweets per min ranged from 209-3326. The mean followers per tweeter ranged from 3382-9992 across events. Retweets were tweeted a mean of 82-564 times per event. Tweets occurred very rapidly for all events (<2 mins) and represented 1% of the total event specific tweets in a median of 13 minutes of the first 911 calls. A 200 tweets/min threshold was reached fastest with NE (2 min), BB (7 min), and SF (18 mins). If this threshold was utilized as a signaling mechanism to place local hospitals on standby for possible large scale events, in all case studies, this signal would have preceded patient arrival. Importantly, this threshold for signaling would also have preceded traditional disaster notification mechanisms in SF, NE, and simultaneous with BB and MV.ConclusionsSocial media data has demonstrated that this mechanism is a powerful, predictable, and potentially important resource for optimizing disaster response. Further investigated is warranted to assess the utility of prospective signally thresholds for hospital based activation
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Elevated plasma levels of TIMP-3 are associated with a higher risk of acute respiratory distress syndrome and death following severe isolated traumatic brain injury.
BackgroundComplications after injury, such as acute respiratory distress syndrome (ARDS), are common after traumatic brain injury (TBI) and associated with poor clinical outcomes. The mechanisms driving non-neurologic organ dysfunction after TBI are not well understood. Tissue inhibitor of matrix metalloproteinase-3 (TIMP-3) is a regulator of matrix metalloproteinase activity, inflammation, and vascular permeability, and hence has plausibility as a biomarker for the systemic response to TBI.MethodsIn a retrospective study of 182 patients with severe isolated TBI, we measured TIMP-3 in plasma obtained on emergency department arrival. We used non-parametric tests and logistic regression analyses to test the association of TIMP-3 with the incidence of ARDS within 8 days of admission and in-hospital mortality.ResultsTIMP-3 was significantly higher among subjects who developed ARDS compared with those who did not (median 2810 pg/mL vs. 2260 pg/mL, p=0.008), and significantly higher among subjects who died than among those who survived to discharge (median 2960 pg/mL vs. 2080 pg/mL, p<0.001). In an unadjusted logistic regression model, for each SD increase in plasma TIMP-3, the odds of ARDS increased significantly, OR 1.5 (95% CI 1.1 to 2.1). This association was only attenuated in multivariate models, OR 1.4 (95% CI 1.0 to 2.0). In an unadjusted logistic regression model, for each SD increase in plasma TIMP-3, the odds of death increased significantly, OR 1.7 (95% CI 1.2 to 2.3). The magnitude of this association was greater in a multivariate model adjusted for markers of injury severity, OR 1.9 (95% CI 1.2 to 2.8).DiscussionTIMP-3 may play an important role in the biology of the systemic response to brain injury in humans. Along with clinical and demographic data, early measurements of plasma biomarkers such as TIMP-3 may help identify patients at higher risk of ARDS and death after severe isolated TBI.Level of evidenceIII
First principles based atomistic modeling of phase stability in PMN-xPT
We have performed molecular dynamics simulations using a shell model
potential developed by fitting first principles results to describe the
behavior of the relaxor-ferroelectric (1-x)PbMg1/3Nb2/3O3-xPbTiO3 (PMN-xPT) as
function of concentration and temperature, using site occupancies within the
random site model. In our simulations, PMN is cubic at all temperatures and
behaves as a polar glass. As a small amount of Ti is added, a weak polar state
develops, but structural disorder dominates, and the symmetry is rhombohedral.
As more Ti is added the ground state is clearly polar and the system is
ferroelectric, but with easy rotation of the polarization direction. In the
high Ti content region, the solid solution adopts ferroelectric behavior
similar to PT, with tetragonal symmetry. The ground state sequence with
increasing Ti content is R-MB-O-MC-T. The high temperature phase is cubic at
all compositions. Our simulations give the slope of the morphotropic phase
boundaries, crucial for high temperature applications. We find that the phase
diagram PMN-xPT can be understood within the random site model.Comment: 27 pages, 9 figure
Issues and Opportunities in Exotic Hadrons
The last few years have been witness to a proliferation of new results concerning heavy exotic hadrons. Experimentally, many new signals have been discovered that could be pointing towards the existence of tetraquarks, pentaquarks, and other exotic configurations of quarks and gluons. Theoretically, advances in lattice field theory techniques place us at the cusp of understanding complex coupled-channel phenomena, modelling grows more sophisticated, and effective field theories are being applied to an ever greater range of situations. It is thus an opportune time to evaluate the status of the field. In the following, a series of high priority experimental and theoretical issues concerning heavy exotic hadrons is presented
Scattering polarization of hydrogen lines from electric-induced atomic alignment
We consider a gas of hydrogen atoms illuminated by a broadband, unpolarized
radiation with zero anisotropy. In the absence of external fields, the atomic
J-levels are thus isotropically populated. While this condition persists in the
presence of a magnetic field, we show instead that electric fields can induce
the alignment of those levels. We also show that this electric alignment cannot
occur in a two-term model of hydrogen (e.g., if only the Ly-alpha transition is
excited), or if the level populations are distributed according to Boltzmann's
law.Comment: 10 pages, 4 figures. Accepted by J.Phys.B: At.Mol.Opt.Phy
Bott periodicity and stable quantum classes
We use Bott periodicity to relate previously defined quantum classes to
certain "exotic Chern classes" on . This provides an interesting
computational and theoretical framework for some Gromov-Witten invariants
connected with cohomological field theories. This framework has applications to
study of higher dimensional, Hamiltonian rigidity aspects of Hofer geometry of
, one of which we discuss here.Comment: prepublication versio
Identification of complex metabolic states in critically injured patients using bioinformatic cluster analysis
IntroductionAdvances in technology have made extensive monitoring of patient physiology the standard of care in intensive care units (ICUs). While many systems exist to compile these data, there has been no systematic multivariate analysis and categorization across patient physiological data. The sheer volume and complexity of these data make pattern recognition or identification of patient state difficult. Hierarchical cluster analysis allows visualization of high dimensional data and enables pattern recognition and identification of physiologic patient states. We hypothesized that processing of multivariate data using hierarchical clustering techniques would allow identification of otherwise hidden patient physiologic patterns that would be predictive of outcome.MethodsMultivariate physiologic and ventilator data were collected continuously using a multimodal bioinformatics system in the surgical ICU at San Francisco General Hospital. These data were incorporated with non-continuous data and stored on a server in the ICU. A hierarchical clustering algorithm grouped each minute of data into 1 of 10 clusters. Clusters were correlated with outcome measures including incidence of infection, multiple organ failure (MOF), and mortality.ResultsWe identified 10 clusters, which we defined as distinct patient states. While patients transitioned between states, they spent significant amounts of time in each. Clusters were enriched for our outcome measures: 2 of the 10 states were enriched for infection, 6 of 10 were enriched for MOF, and 3 of 10 were enriched for death. Further analysis of correlations between pairs of variables within each cluster reveals significant differences in physiology between clusters.ConclusionsHere we show for the first time the feasibility of clustering physiological measurements to identify clinically relevant patient states after trauma. These results demonstrate that hierarchical clustering techniques can be useful for visualizing complex multivariate data and may provide new insights for the care of critically injured patients
Limitations on the principle of stationary phase when it is applied to tunneling analysis
Using a recently developed procedure - multiple wave packet decomposition -
here we study the phase time formulation for tunneling/reflecting particles
colliding with a potential barrier. To partially overcome the analytical
difficulties which frequently arise when the stationary phase method is
employed for deriving phase (tunneling) time expressions, we present a
theoretical exercise involving a symmetrical collision between two identical
wave packets and an one-dimensional rectangular potential barrier. Summing the
amplitudes of the reflected and transmitted waves - using a method we call
multiple peak decomposition - is shown to allow reconstruction of the scattered
wave packets in a way which allows the stationary phase principle to be
recovered.Comment: 17 pages, 2 figure
Large dust particles in disks around T Tauri stars
We present 7-mm continuum observations of 14 low-mass pre-main-sequence stars
in the Taurus-Auriga star-forming region obtained with the Very Large Array
with ~1.5" resolution and ~0.3 mJy rms sensitivity. For 10 objects, the
circumstellar emission has been spatially resolved. The large outer disk radii
derived suggest that the emission at this wavelength is mostly optically thin.
The millimetre spectral energy distributions are characterised by spectral
indices alpha = 2.3 to 3.2. After accounting for contribution from free-free
emission and corrections for optical depth, we determine dust opacity indices
beta in the range 0.5 to 1.6, which suggest that millimetre-sized dust
aggregates are present in the circumstellar disks. Four of the sources with
beta > 1 may be consistent with submicron-sized dust as found in the
interstellar medium. Our findings indicate that dust grain growth to
millimetre-sized particles is completed within less than 1 Myr for the majority
of circumstellar disks.Comment: 11 pages, 4 figure
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