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At least 1,639 records · Page 91

Using the concordance of in vitro and in vivo data to evaluate extrapolation assumptions

Linking in vitro bioactivity and in vivo toxicity on a dose basis enables the use of highthroughput in vitro assays as an alternative to traditional animal studies. In this study, we evaluated assumptions in the use of a high-throughput, physiologically based toxicokinetic (PBTK) model to relate in vitro bioactivity and rat in vivo toxicity data. The fraction unbound in plasma (fup) and intrinsic hepatic clearance (Clint) were measured for rats (for 67 and 77 chemicals, respectively), combined with fup and Clint literature data for 97 chemicals, and incorporated in the PBTK model. Of these chemicals, 84 had corresponding in vitro ToxCast bioactivity data and in vivo toxicity data. For each possible comparison of in vitro and in vivo endpoint, the concordance between the in vivo and in vitro data was evaluated by a regression analysis. For a base set of assumptions, the PBTK results were more frequently better associated than either the results from a “random” model parameterization or direct comparison of the “untransformed” values of AC50 and dose (performed best in 51%, 28%, and 21% of cases, respectively). We also investigated several assumptions in the application of PBTK for IVIVE, including clearance and internal dose selection. One of the better assumptions sets–restrictive clearance and comparing free in vivo venous plasma concentration with free in vitro concentration–outperformed the random and untransformed results in 71% of the in vitro-in vivo endpoint comparisons. These results demonstrate that applying PBTK improves our ability to observe the association between in vitro bioactivity and in vivo toxicity data in general. This suggests that potency values from in vitro screening should be transformed using in vitro-in vivo extrapolation (IVIVE) to build potentially better machine learning and other statistical models for predicting in vivo toxicity in humans

59 BASIC BIOLOGICAL SCIENCES↗

Evaluation of Impinging Stream Vortex Chamber Concepts for Liquid Rocket Engine Applications

To pursue technology developments for future launch vehicles, NASA/Marshall Space Flight Center (MSFC) is examining vortex chamber concepts for liquid rocket engine applications. Past studies indicated that the vortex chamber schemes potentially have a number of advantages over conventional chamber methods. Due to the nature of the vortex flow, relatively cooler propellant streams tend to flow along the chamber wall. Hence, the thruster chamber can be operated without the need of any cooling techniques. This vortex flow also creates strong turbulence, which promotes the propellant mixing process. Consequently, the subject chamber concepts not only offer system simplicity, but also enhance the combustion performance. Test results have shown that chamber performance is markedly high even at a low chamber length-to-diameter ratio (LD). This incentive can be translated to a convenience in the thrust chamber packaging. Variations of the vortex chamber concepts have been introduced in the past few decades. These investigations include an ongoing work at Orbital Technologies Corporation (ORBITEC). By injecting the oxidizer tangentially at the chamber convergence and fuel axially at the chamber head end, Knuth et al. were able to keep the wall relatively cold. A recent investigation of the low L/D vortex chamber concept for gel propellants was conducted by Michaels. He used both triplet (two oxidizer orifices and one fuel orifice) and unlike impinging schemes to inject propellants tangentially along the chamber wall. Michaels called the subject injection scheme an Impinging Stream Vortex Chamber (ISVC). His preliminary tests showed that high performance, with an Isp efficiency of 9295, can be obtained. MSFC and the U. S. Army are jointly investigating an application of the ISVC concept for the cryogenic oxygen/hydrocarbon propellant system. This vortex chamber concept is currently tested with gel propellants at AMCOM at Redstone Arsenal, Alabama. A version of this concept for the liquid oxygen (LOX) hydrocarbon fuel (RP-1) system has been derived from the one for the gel propellant. An unlike impinging injector was employed to deliver the propellants to the chamber. MSFC is also conducting an alternative injection scheme, called the chasing injector, associated with this vortex chamber concept. In this injection technique, both propellant jets and their impingement point are in the same chamber cross-sectional plane. Long duration tests (approximately up to 15 seconds) will be conducted on the ISVC to study the thermal effects. This paper will report the progress of the subject efforts at NASA Marshall Space Flight Center. Thrust chamber performance and thermal wall compatibility will be evaluated. The chamber pressures, wall temperatures, and thrust will be measured as appropriate. The test data will be used to validate CFD models, which, in turn, will be used to design the optimum vortex chambers. Measurements in the previous tests showed that the chamber pressures vary significantly with radius. This is due to the existence of the vortices in the chamber flow field. Hence, the combustion efficiency may not be easily determined from chamber pressure. For this project, measured thrust data will be collected. The performance comparison will be in terms of specific impulse efficiencies. In addition to the thrust measurements, several pressure and temperature readings at various locations on the chamber head faceplate and the chamber wall will be made. The first injector and chamber were designed and fabricated based on the available data and experience gained during gel propellant system tests by the U.S. Army. The alternate injector for the ISVC was also fabricated. Hot-fire tests of the vortex chamber are about to start and are expected to complete in February of 2003 at the TS115 facility of MSFC.

Trinh, Huu P.↗

Big bang nucleosynthesis - The standard model and alternatives

The standard homogeneous-isotropic calculation of the big bang cosmological model is reviewed, and alternate models are discussed. The standard model is shown to agree with the light element abundances for He-4, H-2, He-3, and Li-7 that are available. Improved observational data from recent LEP collider and SLC results are discussed. The data agree with the standard model in terms of the number of neutrinos, and provide improved information regarding neutron lifetimes. Alternate models are reviewed which describe different scenarios for decaying matter or quark-hadron induced inhomogeneities. The baryonic density relative to the critical density in the alternate models is similar to that of the standard model when they are made to fit the abundances. This reinforces the conclusion that the baryonic density relative to critical density is about 0.06, and also reinforces the need for both nonbaryonic dark matter and dark baryonic matter.

Schramm, David N.↗

The Structural Basis for Partitioning of the XRCC1/DNA Ligase III-alpha BRCT-mediated Dimer Complexes

The ultimate step common to almost all DNA repair pathways is the ligation of the nicked intermediate to form contiguous double-stranded DNA. In the mammalian nucleotide and base excision repair pathways, the ligation step is carried out by ligase III-{alpha}. For efficient ligation, ligase III-{alpha} is constitutively bound to the scaffolding protein XRCC1 through interactions between the C-terminal BRCT domains of each protein. Although structural data for the individual domains has been available, no structure of the complex has been determined and several alternative proposals for this interaction have been advanced. Interpretation of the models is complicated by the formation of homodimers that, depending on the model, may either contribute to, or compete with heterodimer formation. We report here the structures of both homodimer complexes as well as the heterodimer complex. Structural characterization of the heterodimer formed from a longer XRCC1 BRCT domain construct, including residues comprising the interdomain linker region, revealed an expanded heterodimer interface with the ligase III-{alpha} BRCT domain. This enhanced linker-mediated binding interface plays a significant role in the determination of heterodimer/homodimer selectivity. These data provide fundamental insights into the structural basis of BRCT-mediated dimerization, and resolve questions related to the organization of this important repair complex.

59 BASIC BIOLOGICAL SCIENCES↗

Plasmon-enhanced phonon and ionized impurity scattering in doped silicon

Historically, two microscopic electron scattering calculation methods have been used to fit macroscopic electron mobility data in n-type silicon. The first method was performed using a static system that included long-range electron-plasmon scattering; however, the well-known Born approximation fails in this case when dealing with electron-impurity scattering. In the second method, sophisticated numerical simulations were developed around plasmon-excited potential fluctuations and successfully reproduced the mobility data at room temperature. In this paper, we propose a third method as an alternative to the first method. First, using a fluctuating system, which was characterized on the basis of our recently experimentally extracted plasmon-excited potential fluctuations, the microscopic calculations reveal enhanced short-range scattering of electrons by phonons and ionized impurities due to increased electron temperature and increased screening length, respectively. The increased hot electron population makes the Born approximation hold, which eases the overall calculation task substantially. Then, we return to the static system while incorporating plasmon-enhanced impurity scattering. The resulting macroscopic electron mobility shows fairly good agreement with data over wide ranges of temperatures (200–400 K) and doping concentrations (10{sup 15}–10{sup 20 }cm{sup −3}). Application of the proposed method to strained silicon is also demonstrated.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Energy Return on Investment – Fuel Recycle

This report provides a methodology and requisite data to assess the potential Energy Return On Investment (EROI) for nuclear fuel cycle alternatives, and applies that methodology to a limited set of used fuel recycle scenarios. This paper is based on a study by Lawrence Livermore National Laboratory and a parallel evaluation by AREVA Federal Services LLC, both of which were sponsored by the DOE Fuel Cycle Technologies (FCT) Program. The focus of the LLNL effort was to develop a methodology that can be used by the FCT program for such analysis that is consistent with the broader energy modeling community, and the focus of the AREVA effort was to bring industrial experience and operational data into the analysis. This cooperative effort successfully combined expertise from the energy modeling community with expertise from the nuclear industry. Energy Return on Investment is one of many figures of merit on which investment in a new energy facility or process may be judged. EROI is the ratio of the energy delivered by a facility divided by the energy used to construct, operate and decommission that facility. While EROI is not the only criterion used to make an investment decision, it has been shown that, in technologically advanced societies, energy supplies must exceed a minimum EROI. Furthermore, technological history shows a trend towards higher EROI energy supplies. EROI calculations have been performed for many components of energy technology: oil wells, wind turbines, photovoltaic modules, biofuels, and nuclear reactors. This report represents the first standalone EROI analysis of nuclear fuel reprocessing (or recycling) facilities.

02 PETROLEUM↗

Probing High-Temperature Amine Chemistry: Is the Reaction NH 3 + NH 2 ⇌ N 2 H 3 + H 2 Important?

The reaction NH 3 + NH 2 ⇌ N 2 H 3 + H 2 (R1) has been identified as a key step to explain experimental results for pyrolysis and oxidation of ammonia. However, no direct experimental or theoretical evidence for the reaction has been reported. In the present work, the reaction was studied by ab initio theory and by reinterpretation of experimental data. We could not locate a transition state for R1 occurring as a direct process, but alternative mechanisms yielded an upper bound to k 1 of 1.5 × 10 13 exp(–58.9 kcal mol –1 /RT) cm 3 mol –1 s –1 over 1000–2500 K, several orders of magnitude lower than values applied in modeling. Consistent with the theoretical work, re-evaluation of NH 3 pyrolysis data supported a very low value of k 1 . However, this finding opens up a novel unresolved issue. Current kinetic models cannot capture the NH 3 oxidation behavior in a number of laminar flow reactor and jet-stirred reactor experiments without adopting an improbably high value for k 1 . Furthermore, important oxidation steps might be underestimated or missing from mechanisms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Could Blobs Fuel Storage-Based Convergence between HPC and Big Data?

The increasingly growing data sets processed on HPC platforms raise major challenges for the underlying storage layer. A promising alternative to POSIX-IO- compliant file systems are simpler blobs (binary large objects), or object storage systems. Such systems offer lower overhead and better performance at the cost of largely unused features such as file hierarchies or permissions. Similarly, blobs are increasingly considered for replacing distributed file systems for big data analytics or as a base for storage abstractions such as key-value stores or time-series databases. This growing interest in such object storage on HPC and big data platforms raises the question: Are blobs the right level of abstraction to enable storage-based convergence between HPC and Big Data? In this paper we study the impact of blob-based storage for real-world applications on HPC and cloud environments. The results show that blobbased storage convergence is possible, leading to a significant performance improvement on both platforms

Matri, Pierre↗

Atmospheric Soundings from AIRS/AMSU in Partial Cloud Cover

Simultaneous use of AIRS/AMSU-A observations allow for the determination of accurate atmospheric soundings under partial cloud cover conditions. The methodology involves the determination of the radiances AIRS would have seen if the AIRS fields of view were clear, called clear column radiances, and use of these radiances to infer the atmospheric and surface conditions giving rise to these clear column radiances. Susskind et al. demonstrate via simulation that accurate temperature soundings and clear column radiances can be derived from AIRS/AMSU-A observations in cases of up to 80% partial cloud cover, with only a small degradation in accuracy compared to that obtained in clear scenes. Susskind and Atlas show that these findings hold for real AIRS/AMSU-A soundings as well. For data assimilation purposes, this small degradation in accuracy is more than offset by a significant increase in spatial coverage (roughly 50% of global cases were accepted, compared to 3.6% of the global cases being diagnosed as clear), and assimilation of AIRS temperature soundings in partially cloudy conditions resulted in a larger improvement in forecast skill than when AIRS soundings were assimilated only under clear conditions. Alternatively, derived AIRS clear column radiances under partial cloud cover could also be used for data assimilation purposes. Further improvements in AIRS sounding methodology have been made since the results shown in Susskind and Atlas . A new version of the AIRS/AMSU-A retrieval algorithm, Version 4.0, was delivered to the Goddard DAAC in February 2005 for production of AIRS derived products, including clear column radiances. The major improvement in the Version 4.0 retrieval algorithm is with regard to a more flexible, parameter dependent, quality control. Results are shown of the accuracy and spatial distribution of temperature-moisture profiles and clear column radiances derived from AIRS/AMSU-A as a function of fractional cloud cover using the Version 4.0 algorithm. Use of the Version 4.0 AIRS temperature profiles increased the positive forecast impact arising from AIRS retrievals relative to what was shown in Susskind and Atlas .

Susskind, Joel↗

Preventing Data Ambiguity in Infectious Diseases with Four-Dimensional and Personalized Evaluations

Background Diagnostic errors can occur, in infectious diseases, when anti-microbial immune responses involve several temporal scales. When responses span from nanosecond to week and larger temporal scales, any pre-selected temporal scale is likely to miss some (faster or slower) responses. Hoping to prevent diagnostic errors, a pilot study was conducted to evaluate a four-dimensional (4D) method that captures the complexity and dynamics of infectious diseases. Methods Leukocyte-microbial-temporal data were explored in canine and human (bacterial and/or viral) infections, with: (i) a non-structured approach, which measures leukocytes or microbes in isolation; and (ii) a structured method that assesses numerous combinations of interacting variables. Four alternatives of the structured method were tested: (i) a noise reduction oriented version, which generates a single (one data point-wide) line of observations; (ii) a version that measures complex, three-dimensional (3D) data interactions; (iii) a non-numerical version that displays temporal data directionality (arrows that connect pairs of consecutive observations); and (iv) a full 4D (single line-, complexity-, directionality based) version. Results In all studies, the non-structured approach revealed non-interpretable (ambiguous) data: observations numerically similar expressed different biological conditions, such as recovery and lack of recovery from infections. Ambiguity was also found when the data were structured as single lines. In contrast, two or more data subsets were distinguished and ambiguity was avoided when the data were structured as complex, 3D, single lines and, in addition, temporal data directionality was determined. The 4D method detected, even within one day, changes in immune profiles that occurred after antibiotics were prescribed. Conclusions Infectious disease data may be ambiguous. Four-dimensional methods may prevent ambiguity, providing earlier, in vivo, dynamic, complex, and personalized information that facilitates both diagnostics and selection or evaluation of anti-microbial therapies.

59 BASIC BIOLOGICAL SCIENCES↗

Crop identification technology assessment for remote sensing (CITARS). Volume 6: Data processing at the laboratory for applications of remote sensing

The results of classifications and experiments for the crop identification technology assessment for remote sensing are summarized. Using two analysis procedures, 15 data sets were classified. One procedure used class weights while the other assumed equal probabilities of occurrence for all classes. Additionally, 20 data sets were classified using training statistics from another segment or date. The classification and proportion estimation results of the local and nonlocal classifications are reported. Data also describe several other experiments to provide additional understanding of the results of the crop identification technology assessment for remote sensing. These experiments investigated alternative analysis procedures, training set selection and size, effects of multitemporal registration, spectral discriminability of corn, soybeans, and other, and analyses of aircraft multispectral data.

Bauer, M. E.↗

Analyzing School Bus Electrification in Richmond, Virginia

School buses are an essential component of the transportation infrastructure, serving as a lifeline for students across the globe. However, the widespread use of diesel school buses has raised concerns about the health impact on millions of students exposed to harmful emissions daily. Recognizing this issue, school districts worldwide are urgently seeking cleaner energy alternatives. Electric school buses emerge as an environmentally friendly and sustainable option, fostering a healthier environment for both students and communities. However, school bus electrification faces the challenges of high upfront cost, cumbersome charging management, and constraints from power grids. To help school bus operators address those challenges, this study presents a data-driven analysis for school bus electrification. This study considered a real-world school bus system in Richmond, VA, and developed a mathematical programming model to analyze the system design, charging strategies, and charging load profiles for the electrification scenario. The study evaluated different charging strategies based on model outcomes, aiming to optimize efficiency and effectiveness. Ultimately, this research generated electric school bus charging demand profiles under various scenarios, shedding light on the feasibility and implications of transitioning to electric-powered school buses.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Multiresolution With Super-Compact Wavelets

The solution data computed from large scale simulations are sometimes too big for main memory, for local disks, and possibly even for a remote storage disk, creating tremendous processing time as well as technical difficulties in analyzing the data. The excessive storage demands a corresponding huge penalty in I/O time, rendering time and transmission time between different computer systems. In this paper, a multiresolution scheme is proposed to compress field simulation or experimental data without much loss of important information in the representation. Originally, the wavelet based multiresolution scheme was introduced in image processing, for the purposes of data compression and feature extraction. Unlike photographic image data which has rather simple settings, computational field simulation data needs more careful treatment in applying the multiresolution technique. While the image data sits on a regular spaced grid, the simulation data usually resides on a structured curvilinear grid or unstructured grid. In addition to the irregularity in grid spacing, the other difficulty is that the solutions consist of vectors instead of scalar values. The data characteristics demand more restrictive conditions. In general, the photographic images have very little inherent smoothness with discontinuities almost everywhere. On the other hand, the numerical solutions have smoothness almost everywhere and discontinuities in local areas (shock, vortices, and shear layers). The wavelet bases should be amenable to the solution of the problem at hand and applicable to constraints such as numerical accuracy and boundary conditions. In choosing a suitable wavelet basis for simulation data among a variety of wavelet families, the supercompact wavelets designed by Beam and Warming provide one of the most effective multiresolution schemes. Supercompact multi-wavelets retain the compactness of Haar wavelets, are piecewise polynomial and orthogonal, and can have arbitrary order of approximation. The advantages of the multiresolution algorithm are that no special treatment is required at the boundaries of the interval, and that the application to functions which are only piecewise continuous (internal boundaries) can be efficiently implemented. In this presentation, Beam's supercompact wavelets are generalized to higher dimensions using multidimensional scaling and wavelet functions rather than alternating the directions as in the 1D version. As a demonstration of actual 3D data compression, supercompact wavelet transforms are applied to a 3D data set for wing tip vortex flow solutions (2.5 million grid points). It is shown that high data compression ratio can be achieved (around 50:1 ratio) in both vector and scalar data set.

Lee, Dohyung↗

Algorithms in Diffraction Profile Analysis

This chapter introduces several approaches to crystallographic structure refinement from diffraction profile data including the Rietveld method, global optimization methods, and Bayesian modeling. First, the Rietveld method and related nonlinear least squares approaches to analyzing diffraction profiles are briefly discussed. We then review the most common algorithms within global optimization as alternative methods of structure solution: grid search, simulated annealing, and genetic algorithms. As the Rietveld method is the standard tool for analyzing diffraction profile data, we catalogue its challenges and limitations. A Bayesian approach to diffraction profile analysis is presented as an alternative, along with several sampling algorithms including Gibbs sampling, variants of Metropolis sampling, Hamiltonian Monte Carlo, and approximate Bayesian computing. These sampling algorithms are applied to the fitting of a neutron diffraction profile from a National Institute of Standards and Technology silicon standard reference material, and their results are compared.

Singh, Susheela↗

Stacked filters: learning to filter by structure

We present Stacked Filters, a new probabilistic filter which is fast and robust similar to query-agnostic filters (such as Bloom and Cuckoo filters), and at the same time brings low false positive rates and sizes similar to classifier-based filters (such as Learned Filters). The core idea is that Stacked Filters incorporate workload knowledge about frequently queried non-existing values. Instead of learning, they structurally incorporate that knowledge using hashing and several sequenced filter layers, indexing both data and frequent negatives. Stacked Filters can also gather workload knowledge on-the-fly and adaptively build the filter. We show experimentally that for a given memory budget, Stacked Filters achieve end-to-end query throughput up to 130x better than the best alternative for a workload, either query-agnostic or classifier-based filters, and depending on where data is (SSD or HDD).

Computer Science↗

A fast two-stage algorithm for non-negative matrix factorization in smoothly varying data

This article reports the study of algorithms for non-negative matrix factorization (NMF) in various applications involving smoothly varying data such as time or temperature series diffraction data on a dense grid of points. Utilizing the continual nature of the data, a fast two-stage algorithm is developed for highly efficient and accurate NMF. In the first stage, an alternating non-negative least-squares framework is used in combination with the active set method with a warm-start strategy for the solution of subproblems. In the second stage, an interior point method is adopted to accelerate the local convergence. The convergence of the proposed algorithm is proved. The new algorithm is compared with some existing algorithms in benchmark tests using both real-world data and synthetic data. Furthermore, the results demonstrate the advantage of the algorithm in finding high-precision solutions.

interior point method↗

Optimal identification using inconsistent modal data

This work examines techniques under the general approach of optimal-update identification which produce optimally adjusted, or updated, property matrices (i.e., mass, stiffness and damping matrices) to more closely match the structure modal response. For practical applications, the techniques must perform when the modal response is inconsistent with other constraints on the desired model. An alternate view of the optimal-update problem is presented that leads to new techniques for addressing inconsistent data. Viewpoints used for previously published techniques are also examined to explore issues in optimal-update identification.

Smith, Suzanne Weaver↗

SAMBA: Sparse Approximation of Moment-Based Arbitrary Polynomial Chaos

A new arbitrary Polynomial Chaos (aPC) method is presented for moderately high-dimensional problems characterised by limited input data availability. The proposed methodology improves the algorithm of aPC and extends the method, that was previously only introduced as tensor product expansion, to moderately high-dimensional stochastic problems. The fundamental idea of aPC is to use the statistical moments of the input random variables to develop the polynomial chaos expansion. This approach provides the possibility to propagate continuous or discrete probability density functions and also histograms (data sets) as long as their moments exist, are finite and the determinant of the moment matrix is strictly positive. For cases with limited data availability, this approach avoids bias and fitting errors caused by wrong assumptions. In this work, an alternative way to calculate the aPC is suggested, which provides the optimal polynomials, Gaussian quadrature collocation points and weights from the moments using only a handful of matrix operations on the Hankel matrix of moments. It can therefore be implemented without requiring prior knowledge about statistical data analysis or a detailed understanding of the mathematics of polynomial chaos expansions. The extension to more input variables suggested in this work, is an anisotropic and adaptive version of Smolyak's algorithm that is solely based on the moments of the input probability distributions. It is referred to as SAMBA (PC), which is short for Sparse Approximation of Moment-Based Arbitrary Polynomial Chaos. It is illustrated that for moderately high-dimensional problems (up to 20 different input variables or histograms) SAMBA can significantly simplify the calculation of sparse Gaussian quadrature rules. SAMBA's efficiency for multivariate functions with regard to data availability is further demonstrated by analysing higher order convergence and accuracy for a set of nonlinear test functions with 2, 5 and 10 different input distributions or histograms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗