37,697 research outputs found
Ecological Modeling of Aedes aegypti (L.) Pupal Production in Rural Kamphaeng Phet, Thailand
Background - Aedes aegypti (L.) is the primary vector of dengue, the most important arboviral infection globally. Until an effective vaccine is licensed and rigorously administered, Ae. aegypti control remains the principal tool in preventing and curtailing dengue transmission. Accurate predictions of vector populations are required to assess control methods and develop effective population reduction strategies. Ae. aegypti develops primarily in artificial water holding containers. Release recapture studies indicate that most adult Ae. aegypti do not disperse over long distances. We expect, therefore, that containers in an area of high development site density are more likely to be oviposition sites and to be more frequently used as oviposition sites than containers that are relatively isolated from other development sites. After accounting for individual container characteristics, containers more frequently used as oviposition sites are likely to produce adult mosquitoes consistently and at a higher rate. To this point, most studies of Ae. aegypti populations ignore the spatial density of larval development sites. Methodology - Pupal surveys were carried out from 2004 to 2007 in rural Kamphaeng Phet, Thailand. In total, 84,840 samples of water holding containers were used to estimate model parameters. Regression modeling was used to assess the effect of larval development site density, access to piped water, and seasonal variation on container productivity. A varying-coefficients model was employed to account for the large differences in productivity between container types. A two-part modeling structure, called a hurdle model, accounts for the large number of zeroes and overdispersion present in pupal population counts. Findings - The number of suitable larval development sites and their density in the environment were the primary determinants of the distribution and abundance of Ae. aegypti pupae. The productivity of most container types increased significantly as habitat density increased. An ecological approach, accounting for development site density, is appropriate for predicting Ae. aegypti population levels and developing efficient vector control program
Helium, Oxygen, Proton, and Electron (HOPE) Mass Spectrometer for the Radiation Belt Storm Probes Mission
The HOPE mass spectrometer of the Radiation Belt Storm Probes (RBSP) mission (renamed the Van Allen Probes) is designed to measure the in situ plasma ion and electron fluxes over 4π sr at each RBSP spacecraft within the terrestrial radiation belts. The scientific goal is to understand the underlying physical processes that govern the radiation belt structure and dynamics. Spectral measurements for both ions and electrons are acquired over 1 eV to 50 keV in 36 log-spaced steps at an energy resolution ΔE FWHM/E≈15 %. The dominant ion species (H+, He+, and O+) of the magnetosphere are identified using foil-based time-of-flight (TOF) mass spectrometry with channel electron multiplier (CEM) detectors. Angular measurements are derived using five polar pixels coplanar with the spacecraft spin axis, and up to 16 azimuthal bins are acquired for each polar pixel over time as the spacecraft spins. Ion and electron measurements are acquired on alternate spacecraft spins. HOPE incorporates several new methods to minimize and monitor the background induced by penetrating particles in the harsh environment of the radiation belts. The absolute efficiencies of detection are continuously monitored, enabling precise, quantitative measurements of electron and ion fluxes and ion species abundances throughout the mission. We describe the engineering approaches for plasma measurements in the radiation belts and present summaries of HOPE measurement strategy and performance
TOWARDS A COMPREHENSIVE REGIONAL WATER POLICY MODEL FOR THE TEXAS HIGH PLAINS
A 19 county, 50-year dynamic economic optimization model of irrigated crop production is linked to a detailed hydrology model for purposes of improving policy estimates of economic cost and associated water saving of groundwater conservation management policies. Spatial and temporal desegregation, allows planners to target specific areas and improve the accuracy of benefit-cost policy estimates.Resource /Energy Economics and Policy,
Volatility forecasting
Volatility has been one of the most active and successful areas of research in time series econometrics and economic forecasting in recent decades. This chapter provides a selective survey of the most important theoretical developments and empirical insights to emerge from this burgeoning literature, with a distinct focus on forecasting applications. Volatility is inherently latent, and Section 1 begins with a brief intuitive account of various key volatility concepts. Section 2 then discusses a series of different economic situations in which volatility plays a crucial role, ranging from the use of volatility forecasts in portfolio allocation to density forecasting in risk management. Sections 3, 4 and 5 present a variety of alternative procedures for univariate volatility modeling and forecasting based on the GARCH, stochastic volatility and realized volatility paradigms, respectively. Section 6 extends the discussion to the multivariate problem of forecasting conditional covariances and correlations, and Section 7 discusses volatility forecast evaluation methods in both univariate and multivariate cases. Section 8 concludes briefly. JEL Klassifikation: C10, C53, G1
Multi-Messenger Gravitational Wave Searches with Pulsar Timing Arrays: Application to 3C66B Using the NANOGrav 11-year Data Set
When galaxies merge, the supermassive black holes in their centers may form
binaries and, during the process of merger, emit low-frequency gravitational
radiation in the process. In this paper we consider the galaxy 3C66B, which was
used as the target of the first multi-messenger search for gravitational waves.
Due to the observed periodicities present in the photometric and astrometric
data of the source of the source, it has been theorized to contain a
supermassive black hole binary. Its apparent 1.05-year orbital period would
place the gravitational wave emission directly in the pulsar timing band. Since
the first pulsar timing array study of 3C66B, revised models of the source have
been published, and timing array sensitivities and techniques have improved
dramatically. With these advances, we further constrain the chirp mass of the
potential supermassive black hole binary in 3C66B to less than using data from the NANOGrav 11-year data set. This
upper limit provides a factor of 1.6 improvement over previous limits, and a
factor of 4.3 over the first search done. Nevertheless, the most recent orbital
model for the source is still consistent with our limit from pulsar timing
array data. In addition, we are able to quantify the improvement made by the
inclusion of source properties gleaned from electromagnetic data to `blind'
pulsar timing array searches. With these methods, it is apparent that it is not
necessary to obtain exact a priori knowledge of the period of a binary to gain
meaningful astrophysical inferences.Comment: 14 pages, 6 figures. Accepted by Ap
Volatility Forecasting
Volatility has been one of the most active and successful areas of research in time series econometrics and economic forecasting in recent decades. This chapter provides a selective survey of the most important theoretical developments and empirical insights to emerge from this burgeoning literature, with a distinct focus on forecasting applications. Volatility is inherently latent, and Section 1 begins with a brief intuitive account of various key volatility concepts. Section 2 then discusses a series of different economic situations in which volatility plays a crucial role, ranging from the use of volatility forecasts in portfolio allocation to density forecasting in risk management. Sections 3, 4 and 5 present a variety of alternative procedures for univariate volatility modeling and forecasting based on the GARCH, stochastic volatility and realized volatility paradigms, respectively. Section 6 extends the discussion to the multivariate problem of forecasting conditional covariances and correlations, and Section 7 discusses volatility forecast evaluation methods in both univariate and multivariate cases. Section 8 concludes briefly.
Fast Simulation of Gaussian-Mode Scattering for Precision Interferometry
Understanding how laser light scatters from realistic mirror surfaces is
crucial for the design, com- missioning and operation of precision
interferometers, such as the current and next generation of gravitational-wave
detectors. Numerical simulations are indispensable tools for this task but
their utility can in practice be limited by the computational cost of
describing the scattering process. In this paper we present an efficient method
to significantly reduce the computational cost of optical simulations that
incorporate scattering. This is accomplished by constructing a near optimal
representation of the complex, multi-parameter 2D overlap integrals that
describe the scattering process (referred to as a reduced order quadrature). We
demonstrate our technique by simulating a near-unstable Fabry-Perot cavity and
its control signals using similar optics to those installed in one of the LIGO
gravitational-wave detectors. We show that using reduced order quadrature
reduces the computational time of the numerical simulation from days to minutes
(a speed-up of ) whilst incurring negligible errors. This
significantly increases the feasibility of modelling interferometers with
realistic imperfections to overcome current limits in state-of-the-art optical
systems. Whilst we focus on the Hermite-Gaussian basis for describing the
scattering of the optical fields, our method is generic and could be applied
with any suitable basis. An implementation of this reduced order quadrature
method is provided in the open source interferometer simulation software
Finesse.Comment: 15 pages, 11 figure
The what and where of adding channel noise to the Hodgkin-Huxley equations
One of the most celebrated successes in computational biology is the
Hodgkin-Huxley framework for modeling electrically active cells. This
framework, expressed through a set of differential equations, synthesizes the
impact of ionic currents on a cell's voltage -- and the highly nonlinear impact
of that voltage back on the currents themselves -- into the rapid push and pull
of the action potential. Latter studies confirmed that these cellular dynamics
are orchestrated by individual ion channels, whose conformational changes
regulate the conductance of each ionic current. Thus, kinetic equations
familiar from physical chemistry are the natural setting for describing
conductances; for small-to-moderate numbers of channels, these will predict
fluctuations in conductances and stochasticity in the resulting action
potentials. At first glance, the kinetic equations provide a far more complex
(and higher-dimensional) description than the original Hodgkin-Huxley
equations. This has prompted more than a decade of efforts to capture channel
fluctuations with noise terms added to the Hodgkin-Huxley equations. Many of
these approaches, while intuitively appealing, produce quantitative errors when
compared to kinetic equations; others, as only very recently demonstrated, are
both accurate and relatively simple. We review what works, what doesn't, and
why, seeking to build a bridge to well-established results for the
deterministic Hodgkin-Huxley equations. As such, we hope that this review will
speed emerging studies of how channel noise modulates electrophysiological
dynamics and function. We supply user-friendly Matlab simulation code of these
stochastic versions of the Hodgkin-Huxley equations on the ModelDB website
(accession number 138950) and
http://www.amath.washington.edu/~etsb/tutorials.html.Comment: 14 pages, 3 figures, review articl
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