6,828 research outputs found
Spatial distribution of Chlorpyrifos and Endosulfan in USA coastal waters and the Great Lakes
Between 1994 and 1997, 258 tissue and 178 sediment samples were analyzed for chlorpyrifos throughout the coastal United States and the Great Lakes. Subsequently, 95 of
the 1997 tissue samples were reanalyzed for endosulfan. Tissue chlorpyrifos concentrations, which exceeded the 90th percentile, were found in coastal regions known to have high
agricultural use rates but also strongly correlated with sites near high population. The highest concentrations of endosulfans in contrast, were generally limited to agricultural regions of the country. Detections of chlorpyrifos at several Alaskan sites suggest an atmospheric
transport mechanism. Many Great Lakes sites had chlorpyrifos tissue concentrations above the 90th percentile which decreased with increasing distance from the Corn Belt region (Iowa, Indiana, Illinois, and Wisconsin) where most agriculturally applied chlorpyrifos is used. Correlation analysis suggests that fluvial discharge is the primary transport pathway on the Atlantic and Gulf of Mexico coasts for chlorpyrifos but not necessarily for endosulfans. (PDF contains 28 pages
Training a Spiking Neural Network with Equilibrium Propagation
Backpropagation is almost universally used to train artificial neural networks. However, there are several reasons that backpropagation could not be plausibly implemented by biological neurons. Among these are the facts that (1) biological neurons appear to lack any mechanism for sending gradients backwards across synapses, and (2) biological “spiking” neurons emit binary signals, whereas back-propagation requires that neurons communicate continuous values between one another. Recently, Scellier and Bengio [2017], demonstrated an alternative to backpropagation, called Equilibrium Propagation, wherein gradients are implicitly computed by the dynamics of the neural network, so that neurons do not need an internal mechanism for backpropagation of gradients. This provides an interesting solution to problem (1). In this paper, we address problem (2) by proposing a way in which Equilibrium Propagation can be implemented with neurons which are constrained to just communicate binary values at each time step. We show that with appropriate step-size annealing, we can converge to the same fixed-point as a real-valued neural network, and that with predictive coding, we can make this convergence much faster. We demonstrate that the resulting model can be used to train a spiking neural network using the update scheme from Equilibrium propagation
Dynamics and gravitational wave signature of collapsar formation
We perform 3+1 general relativistic simulations of rotating core collapse in the context of the collapsar model for long gamma-ray bursts. We employ a realistic progenitor, rotation based on results of stellar evolution calculations, and a simplified equation of state. Our simulations track self-consistently collapse, bounce, the postbounce phase, black hole formation, and the subsequent early hyperaccretion phase. We extract gravitational waves from the spacetime curvature and identify a unique gravitational wave signature associated with the early phase of collapsar formatio
Impact of an improved neutrino energy estimate on outflows in neutron star merger simulations
Binary neutron star mergers are promising sources of gravitational waves for
ground-based detectors such as Advanced LIGO. Neutron-rich material ejected by
these mergers may also be the main source of r-process elements in the
Universe, while radioactive decays in the ejecta can power bright
electromagnetic post-merger signals. Neutrino-matter interactions play a
critical role in the evolution of the composition of the ejected material,
which significantly impacts the outcome of nucleosynthesis and the properties
of the associated electromagnetic signal. In this work, we present a simulation
of a binary neutron star merger using an improved method for estimating the
average neutrino energies in our energy-integrated neutrino transport scheme.
These energy estimates are obtained by evolving the neutrino number density in
addition to the neutrino energy and flux densities. We show that significant
changes are observed in the composition of the polar ejecta when comparing our
new results with earlier simulations in which the neutrino spectrum was assumed
to be the same everywhere in optically thin regions. In particular, we find
that material ejected in the polar regions is less neutron rich than previously
estimated. Our new estimates of the composition of the polar ejecta make it
more likely that the color and timescale of the electromagnetic signal depend
on the orientation of the binary with respect to an observer's line-of-sight.
These results also indicate that important observable properties of neutron
star mergers are sensitive to the neutrino energy spectrum, and may need to be
studied through simulations including a more accurate, energy-dependent
neutrino transport scheme.Comment: 19p, 17 figures, Accepted by Phys.Rev.
The Influence of Thermal Pressure on Equilibrium Models of Hypermassive Neutron Star Merger Remnants
The merger of two neutron stars leaves behind a rapidly spinning hypermassive
object whose survival is believed to depend on the maximum mass supported by
the nuclear equation of state, angular momentum redistribution by
(magneto-)rotational instabilities, and spindown by gravitational waves. The
high temperatures (~5-40 MeV) prevailing in the merger remnant may provide
thermal pressure support that could increase its maximum mass and, thus, its
life on a neutrino-cooling timescale. We investigate the role of thermal
pressure support in hypermassive merger remnants by computing sequences of
spherically-symmetric and axisymmetric uniformly and differentially rotating
equilibrium solutions to the general-relativistic stellar structure equations.
Using a set of finite-temperature nuclear equations of state, we find that hot
maximum-mass critically spinning configurations generally do not support larger
baryonic masses than their cold counterparts. However, subcritically spinning
configurations with mean density of less than a few times nuclear saturation
density yield a significantly thermally enhanced mass. Even without decreasing
the maximum mass, cooling and other forms of energy loss can drive the remnant
to an unstable state. We infer secular instability by identifying approximate
energy turning points in equilibrium sequences of constant baryonic mass
parametrized by maximum density. Energy loss carries the remnant along the
direction of decreasing gravitational mass and higher density until instability
triggers collapse. Since configurations with more thermal pressure support are
less compact and thus begin their evolution at a lower maximum density, they
remain stable for longer periods after merger.Comment: 20 pages, 12 figures. Accepted for publication in Ap
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Developing theory-informed interventions to implement evidence into practice: a systematic approach using the Theoretical Domains Framework
Background: There is little systematic operational guidance about how best to develop complex interventions to reduce the gap between practice and evidence. This article is one in a series of articles documenting the development and use of the Theoretical Domains Framework (TDF) to advance the science of implementation research.
Methods: The intervention was developed considering three main components: theory, evidence, and practical issues. We used a four-step approach, consisting of guiding questions, to direct the choice of the most appropriate components of an implementation intervention: Who needs to do what, differently? Using a theoretical framework, which barriers and enablers need to be addressed? Which intervention components (behaviour change techniques and mode(s) of delivery) could overcome the modifiable barriers and enhance the enablers? And how can behaviour change be measured and understood?
Results: A complex implementation intervention was designed that aimed to improve acute low back pain management in primary care. We used the TDF to identify the barriers and enablers to the uptake of evidence into practice and to guide the choice of intervention components. These components were then combined into a cohesive intervention. The intervention was delivered via two facilitated interactive small group workshops. We also produced a DVD to distribute to all participants in the intervention group. We chose outcome measures in order to assess the mediating mechanisms of behaviour change.
Conclusions: We have illustrated a four-step systematic method for developing an intervention designed to change clinical practice based on a theoretical framework. The method of development provides a systematic framework that could be used by others developing complex implementation interventions. While this framework should be iteratively adjusted and refined to suit other contexts and settings, we believe that the four-step process should be maintained as the primary framework to guide researchers through a comprehensive intervention development process
Dynamics and Gravitational Wave Signature of Collapsar Formation
We perform 3+1 general relativistic simulations of rotating core collapse in the context of the collapsar model for long gamma-ray bursts. We employ a realistic progenitor, rotation based on results of stellar evolution calculations, and a simplified equation of state. Our simulations track self-consistently collapse, bounce, the postbounce phase, black hole formation, and the subsequent early hyperaccretion phase. We extract gravitational waves from the spacetime curvature and identify a unique gravitational wave signature associated with the early phase of collapsar formation
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