The U.S. Department of Energy’s (DOE) commitment to assuring the health and safety of its workers includes the conduct of illness and injury surveillance activities that provide an early warning system to detect health problems among workers. The Illness and Injury Surveillance Program monitors illnesses and health conditions that result in an absence, occupational injuries and illnesses, and disabilities and deaths among current workers.

This project presents the outcome of an effort made by a consortium of six universities in the State of New York to develop a Center for Advanced technology (CAT) in the emerging field of Nano-Bio-Molecular Information Technology. The effort consists of activities such as organization of the NYNBIT incubator, collaborative research projects, development of courses, an educational program for high schools, and commercial start-up programs.

A introduction to particle filtering is discussed starting with an overview of Bayesian inference from batch to sequential processors. Once the evolving Bayesian paradigm is established, simulation-based methods using sampling theory and Monte Carlo realizations are discussed. Here the usual limitations of nonlinear approximations and non-gaussian processes prevalent in classical nonlinear processing algorithms (e.g. Kalman filters) are no longer a restriction to perform Bayesian inference. It is shown how the underlying hidden or state variables are easily assimilated into this Bayesian construct. Importance sampling methods are then discussed and shown how they can be extended to sequential solutions implemented using Markovian state-space models as a natural evolution. With this in mind, the idea of a particle filter, which is a discrete representation of a probability distribution, is developed and shown how it can be implemented using sequential importance sampling/resampling methods. Finally, an application is briefly discussed comparing the performance of the particle filter designs with classical nonlinear filter implementations.

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In 2000, a Cooperative Research and Development Agreement (CRADA) was undertaken between the Oak Ridge National Laboratory (ORNL) and the Special Metals Corporation (SMC) to determine the mechanical property response of the IN740 alloy to help establish thermo-mechanical processing parameters for the use of this alloy in supercritical and ultra-critical boiler tubes with the potential for other end uses. SMC had developed an alloy, commercially known as INCONEL alloy 740, which exhibited various beneficial physical, mechanical, and chemical properties. As part of SMC's on-going efforts to optimize this alloy for targeted boiler applications there was a need to develop an understanding of the thermo-mechanical response of the material, characterize the resulting microstructure from this processing, and possibly, utilize models to develop the appropriate processing scheme for this product.

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The general goal of this report is to diminish concentrations of metals/radionuclide in groundwaters of contaminated sites to below MCL values through reduction to lower solubility species.

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Effective environmental management of DOE sites requires reliable prediction of reactive transport phenomena. A central issue in prediction of subsurface reactive transport is the impact of multiscale physical, chemical, and biological heterogeneity. Heterogeneity manifests itself through incomplete mixing of reactants at scales below those at which concentrations are explicitly defined (i.e., the numerical grid scale). This results in a mismatch between simulated reaction processes (formulated in terms of average concentrations) and actual processes (controlled by local concentrations). At the field scale, this results in apparent scale-dependence of model parameters and inability to utilize laboratory parameters in field models. Accordingly, most field modeling efforts are restricted to empirical estimation of model parameters by fitting to field observations, which renders extrapolation of model predictions beyond fitted conditions unreliable. The objective of this project is to develop a theoretical and computational framework for (1) connecting models of coupled reactive transport from pore-scale processes to field-scale bioremediation through a hierarchy of models that maintain crucial information from the smaller scales at the larger scales; and (2) quantifying the uncertainty that is introduced by both the upscaling process and uncertainty in physical parameters. One of the challenges of addressing scale-dependent effects of coupled processes in …

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The Environmental Molecular Sciences laboratory (EMSL) is a national scientific user facility operated by the Pacific Northwest National Laboratory (PNNL) for the U.S. Department of Energy's Office of Biological and Environmental Research. Located in Richland, Washington, EMSL offers researchers a comprehensive array of cutting-edge capabilities unmatched anywhere else in the world and access to the expertise of over 300 resident users--all at one location. EMSL's resources are available on a peer-reviewed proposal basis and are offered at no cost if research results are shared in the open literature. Researchers are encouraged to submit a proposal centered around one of EMSL's four Science Themes, which represent growing areas of research: (1) Geochemistry/Biogeochemistry and Subsurface Science; (2) Atmospheric Aerosol Chemistry; (3) Biological Interactions and Dynamics; and (4) Science of Interfacial Phenomena. To learn more about EMSL, visit www.emsl.pnl.gov.

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In this paper we report on strangeness measurements in p+p, Au+Au and Cu+Cu collisions at different energies in the STAR detector at RHIC. We will focus on two momentum regions in particular: Firstly we look at strangeness enhancement in A+A collisions with respect to p+p. These yields are dominated by low transverse momentum. We compare the enhancements from Au+Au and Cu+Cu data at {radical}s{sub NN} = 200 GeV with Pb+Pb data at {radical}s{sub NN} = 17.2 GeV and find that the enhancement does not scale with N{sub part} as expected, but rather scales with N{sub part}{sup 1/3}, where N{sub part} represents the number of participants; We then examine {Lambda}/K{sub S}{sup 0} ratios at intermediate transverse momentum in both Au+Au and Cu+Cu data where we find a greater enhancement in Cu+Cu compared to Au+Au data when we compare integrated ratios between 1.5 < p{sub T} < 3.5 GeV/c.

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Soft X-ray imager mirrors have been designed, calibrated and fabricated at Lawrence Livermore National Laboratory and characterized at the Advanced Light Source for their performance between 200 and 1300 eV. The mirrors are coated with a multilayer coating consisting of 70 bilayers of W/ SiC. The mirrors are to reflect at 22.5 deg from grazing angle at 1.50 nm wavelength and the width of the reflectivity peak should be at least 1.3%. Also, the mirrors should be non-reflective elsewhere. Our multilayer design was optimized to satisfy these requirements. The coating is very challenging since the individual layer thicknesses need to be less than 1 nm thick and reproducibility from layer to layer is crucial. To minimize the second harmonic peak we designed a multilayer with {Gamma} = 0.5 (W and SiC layer thicknesses are the same). This way we end up with a mirror that has only the 1st and 3rd harmonic peak as shown in Figure 1. To suppress reflectivity outside the first peak we used our novel approach, an antireflective coating. Modeling predicted substantial reduction in reflectivity, especially for lower energies as shown in Figure 1. The experimental results of the soft x-ray imager mirror as measured at …

In this paper we report on electron beam lifetime measurements as a function of scraper position, RF voltage and bunch fill pattern in SPEAR3. We then outline development of an empirical, macroscopic model using the beam-loss rate equation. By identifying the dependence of loss coefficients on accelerator and beam parameters, a numerically-integrating simulator can be constructed to compute beam decay with time. In a companion paper, the simulator is used to train a parametric, non-linear dynamics model for the system [1].

Pillar detector is an innovative solid state device structure that leverages advanced semiconductor fabrication technology to produce a device for thermal neutron detection. State-of-the-art thermal neutron detectors have shortcomings in achieving simultaneously high efficiency, low operating voltage while maintaining adequate fieldability performance. By using a 3-dimensional silicon PIN diode pillar array filled with isotopic boron 10, ({sup 10}B) a high efficiency device is theoretically possible. The fabricated pillar structures reported in this work are composed of 2 {micro}m diameter silicon pillars with a 4 {micro}m pitch and pillar heights of 6 and 12 {micro}m. The pillar detector with a 12 {micro}m height achieved a thermal neutron detection efficiency of 7.3% at 2V.

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Knowledge of the thermophysical properties of materials at extreme pressure and temperature conditions is essential for improving our understanding of many planetary and detonation processes. Significant gaps in what is known about the behavior of materials at high density and high temperature exist, largely due to the limitations and dangers of performing experiments at the necessary extreme conditions. Modeling these systems through the use of equations of state and particle-based simulation methods significantly extends the range of pressures and temperatures that can be safely studied. The reliability of such calculations depends on the accuracy of the models used. Here we present an assessment of the united-atom version of the TraPPE (Transferable Potentials for Phase Equilibria) force field and single-site exp-6 representations for methane, methanol, oxygen, and ammonia at extreme conditions. As shown by Monte Carlo simulations in the isobaric-isothermal ensemble, the TraPPE models, despite being parameterized to the vapor-liquid coexistence curve (i.e. relatively mild conditions), perform remarkably well in the high pressure/high temperature regime. The single-site exp-6 models can fit experimental data in the high pressure/temperature regime very well, but the parameters are less transferable to ambient conditions.