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DOE OSTI2018

Characterizing the Impact of Soft Errors Affecting Floating-point ALUs using RTL-level Fault Injection

Strategies to detect, correct, or mitigate the impact of soft errors rely on errors-injection experiments. For efficient evaluation, such experiments typically inject errors in software by sampling errors from a candidate distribution. Most often, these strategies randomly select and flip one bit in the output of an instruction. While single-bit flips might constitute a meaningful model for errors affecting hardware, the appropriateness of this model for software-based errors has not been studied. In this paper, we study the manifestation of errors in the output registers due to errors affecting candidate instructions executed by floating point ALUs. We inject single-bit flips into the RTL descriptions of floating point ALUs and analyze the differences between anticipated and observed outputs when executing floating-point addition, subtraction, multiplication, and division. We choose the operands for these instructions randomly and from operands observed in five benchmarks. We observe a rich distribution of errors in the output and analyze their implications for software-based fault-injection campaigns.

Subasi, Omer↗

DOE OSTI2019

Geometric Estimation of Multivariate Dependency

This paper proposes a geometric estimator of dependency between a pair of multivariate random variables. The proposed estimator of dependency is based on a randomly permuted geometric graph (the minimal spanning tree) over the two multivariate samples. This estimator converges to a quantity that we call the geometric mutual information (GMI), which is equivalent to the Henze–Penrose divergence. between the joint distribution of the multivariate samples and the product of the marginals. The GMI has many of the same properties as standard MI but can be estimated from empirical data without density estimation; making it scalable to large datasets. The proposed empirical estimator of GMI is simple to implement, involving the construction of an minimal spanning tree (MST) spanning over both the original data and a randomly permuted version of this data. We establish asymptotic convergence of the estimator and convergence rates of the bias and variance for smooth multivariate density functions belonging to a Hölder class. We demonstrate the advantages of our proposed geometric dependency estimator in a series of experiments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2016

TEM Characterization of U-Mo Irradiated with High-Energy Xe Ions

U-Mo alloys (with 7-10 wt.% Mo) with a low U-235 enrichment (< 20%) have been developed to be used in high-performance research and test reactors, replacing the current highly enriched uranium (HEU) fuels. A number of in-pile irradiation tests of U-Mo fuels show that drastic microstructural changes occurred during reactor irradiation, including the formation of U-Mo-Al interaction products and large gas-filled pores. These microstructural changes might lead to breakaway swelling and deterioration of plate mechanical integrity. Hence, it is critical to understand the underlying mechanisms of these microstructural changes in order to improve the irradiation behavior of UMo fuels. Heavy ion irradiation was employed in this study to investigate separate effects of the irradiation behavior of U-Mo fuels. 1.7 mm diameter disks punched out from UMo/ Al dispersion fuel mini-plates were irradiated with 84 MeV Xe ions at the ATLAS accelerator at Argonne National Laboratory (ANL). This particular ion source was selected for two reasons: (1) to simulate the irradiation response of the fuel to fission fragment bombardments, and (2) to study fission gas behavior, as fission gas bubble formation and growth is the primary cause of U-Mo fuel swelling. The ion-irradiated samples have been characterized with scanning electron microscopy (SEM). This study focuses on the characterization of the samples using transmission electron microscopy (TEM). With the high magnification details, microstructures in U-Mo along the ion penetration depth were revealed. The U-7Mo/Al dispersion fuel sample irradiated with 84 MeV Xe ions to a dose of 2.9 x 10{sup 17} ions/cm{sup 3} was characterized using TEM. The TEM results exhibit that the sample microstructure varies along the ion penetration depth. Near the sample surface (zone A) is a layer of nano-crystalline U-Mo-Al interdiffusion product. After passing through zone A, the Xe ions resided in zone B, where gas bubbles formed in U-Mo. TEM images of this region displayed that large gas bubbles formed on grain boundaries and high-density nano-bubbles lay inside grains. The random distribution of intragranular bubbles indicates that the irradiation conditions of this sample cannot lead to gas bubble superlattice formation. Outside of the Xe penetration depth (zone C), significant amount of α-uranium precipitates were identified. The fact that no α-uranium precipitates were found in zone B suggests that the dose rate in this irradiation is sufficient to facilitate a phase reversal by means of a displacement spike mechanism. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS1980

Aliasing and blurring in 2-D sampled imagery

The quality of image reconstructions from discrete data suffers not only from the blurring of spatial detail caused by limitations in the spatial frequency response of electrooptical systems, but also from the aliasing generated if spatial detail has been undersampled. Previous studies have observed that reasonable spot intensity profiles and photosensor aperture shapes of equivalent size result in about equal blurring but that some profiles and shapes suppress aliasing better than others. This paper presents quantitative results of the magnitude of aliasing and blurring as a function of random radiance fields typical for natural scenes and of spatial responses and sampling intervals typical for TV cameras and optical-mechanical scanners. These results indicate that aliasing may often be a larger source of degradation than either blurring or electronic noise.

Huck, F. O.↗

DOE OSTI2026

Accelerating multicanonical sampling with irreversibility

Flat-histogram Monte Carlo simulations are well-established, robust methods to perform random walks in a physical observable or parameter space, making them suitable for finding ground states or studying phase transitions in complex systems in statistical physics. However, their efficiency can be limited by the time to attain the desired flat distribution, which is generally unknown prior to the simulations. In particular, they might suffer from slowing down towards the end of a simulation due to the diffusive nature of random walks. In this work we apply irreversibility to the multicanonical Monte Carlo method via the lifting approach to alleviate this behavior. We achieve a 2–4 times speedup in ground-state search for a two-dimensional (2D) Ising model, and up to an order of magnitude of speedup for finding the ground-state energy in an Edwards–Anderson spin glass, compared to traditional multicanonical sampling. In conclusion, the round-trip times between ground states show a narrower distribution and are significantly shorter compared to the reversible counterpart, suggesting that a lower convergence time with a smaller time variance is feasible.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2017

Seroprevalence of Herpes Simplex Virus type-2 (HSV-2) among pregnant women who participated in a national HIV surveillance activity in Haiti

Background: Herpes simplex virus type 2 (HSV-2), one the most common causes of genital ulcers, appears to increase both the risk of HIV acquisition and HIV transmission. HSV-2/HIV co-infection among pregnant women may increase the risk of perinatal transmission of HIV. This study describes rates of HSV-2 among pregnant women in Haiti and HSV-2 test performance in this population. Methods: Unlinked residual serum specimens from the 2012 National HIV and Syphilis Sentinel Surveillance Survey among pregnant women in Haiti were tested using two commercial kits (Focus HerpeSelect, Kalon) for HSV-2 antibodies. We evaluated rates of HSV-2 seropositivity and HSV-2/HIV co-infection, associations between HSV-2 and demographic characteristics using multivariable Cox proportional hazards modeling, and HSV-2 test performance in this population. Results: Serum samples from 1000 pregnant women (all 164 HIV positive and 836 random HIV negative) were selected. The overall weighted prevalence of HSV-2 was 31.4% (95% CI: 27.7–35.4) and the prevalence of HIV-positivity among HSV2 positive pregnant women was five times higher than the prevalence among HSV-2 negative women (4.8% [95% CI: 3. 9–6.0] vs. 0.9% [95% CI: 0.6–1.3], respectively). Factors significantly associated with HSV-2 positivity were HIV-positivity (PR: 2.27 [95% CI: 1.94–2.65]) and older age (PRs: 1.41 [95% CI: 1.05–1.91] for 20–24 years, 1.71 [95% CI:1.13–2.60] for 30– 34 years, and 1.55 [95% CI: 1.10–2.19] for 35 years or greater]), while rural residence was negatively associated with HSV2 positivity (PR 0.83 [95% CI: 0.69–1.00]), after controlling for other covariables. For this study a conservative Focus index cutoff of 3.5 was used, but among samples with a Focus index value ≥2.5, 98.4% had positive Kalon tests. Conclusion: The prevalence of HSV-2 is relatively high among pregnant women in Haiti. Public health interventions to increase access to HSV-2 screening in antenatal services are warranted.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1987

Detection of signals by weighted integrate-and-dump filter

A Weighted Integrate and Dump Filter (WIDF) is presented that results in reducing those losses in telemetry symbol signal to noise ratio (SNR) which occur in digital Integrate and Dump Filters (IDFs) when the samples are not phase locked to the input data symbol clock. The Minimum Mean Square Error (MMSE) criterion is used to derive a set of weights for approximating the analog integrate and dump filter, which is the matched filter for detection of signals in additive white Gaussian noise. This new digital matched filter results in considerable performance improvement compared to unweighted digital matched filters. An example is presented for a sampling rate of four times the symbol rate. As the sampling offset (or phase) varies with respect to the data symbol boundaries, the output SNR varies 1 dB for an unweighted IDF, but only 0.3 dB for the optimum WIDF, averaged over random data patterns. This improvement in performance relative to unweighted IDF means that significantly lower sampling and processing rates can be used for given telemetry symbol rates, resulting in reduced system cost.

Sadr, R.↗

DOE OSTI2016

Implementing an Accurate and Rapid Sparse Sampling Approach for Low-Dose Atomic Resolution STEM Imaging

Aberration correction for scanning transmission electron microscopes (STEM) has dramatically increased spatial image resolution for beam-stable materials, but it is the sample stability rather than the microscope that often limits the practical resolution of STEM images. To extract physical information from images of beam sensitive materials it is becoming clear that there is a critical dose/dose-rate below which the images can be interpreted as representative of the pristine material, while above it the observation is dominated by beam effects. Here we describe an experimental approach for sparse sampling in the STEM and in-painting image reconstruction in order to reduce the electron dose/dose-rate to the sample during imaging. By characterizing the induction limited rise-time and hysteresis in scan coils, we show that sparse line-hopping approach to scan randomization can be implemented that optimizes both the speed of the scan and the amount of the sample that needs to be illuminated by the beam. The dose and acquisition time for the sparse sampling is shown to be effectively decreased by factor of 5x relative to conventional acquisition, permitting imaging of beam sensitive materials to be obtained without changing the microscope operating parameters. As a result, the use of sparse line-hopping scan to acquire STEM images is demonstrated with atomic resolution aberration corrected Z-contrast images of CaCO 3 , a material that is traditionally difficult to image by TEM/STEM because of dose issues.

36 MATERIALS SCIENCE↗

DOE OSTI2018

An Efficient Algorithm for Automatic Structure Optimization in X-ray Standing-Wave Experiments

We present that x-ray standing-wave photoemission experiments involving multilayered samples are emerging as unique probes of the buried interfaces that are ubiquitous in current device and materials research. Such data require for their analysis a structure optimization process comparing experiment to theory that is not straightforward. In this work, we present a new computer program for optimizing the analysis of standing-wave data, called SWOPT, that automates this trial-and-error optimization process. The program includes an algorithm that has been developed for computationally expensive problems: so-called black-box simulation optimizations. It also includes a more efficient version of the Yang X-ray Optics Program (YXRO) [Yang, S.-H., Gray, A.X., Kaiser, A.M., Mun, B.S., Sell, B.C., Kortright, J.B., Fadley, C.S., J. Appl. Phys. 113, 1 (2013)] which is about an order of magnitude faster than the original version. Human interaction is not required during optimization. We tested our optimization algorithm on real and hypothetical problems and show that it finds better solutions significantly faster than a random search approach. The total optimization time ranges, depending on the sample structure, from minutes to a few hours on a modern laptop computer, and can be up to 100x faster than a corresponding manual optimization. Finally, these speeds make the SWOPT program a valuable tool for realtime analyses of data during synchrotron experiments.

36 MATERIALS SCIENCE↗

NASA NTRS2003

Evaluation of Treadmill Exercise in a Lower Body Negative Pressure Chamber as a Countermeasure for Weightlessness-Induced Bone Loss: a Bed Rest Study with Identical Twins

Counteracting bone loss is required for future space exploration. We evaluated the ability of treadmill exercise in a LBNP chamber to counteract bone loss in a 30-day bed rest study. Eight pairs of identical twins were randomly assigned to sedentary control or exercise groups. Exercise within LBNP decreased the bone resorption caused by bed rest and may provide a countermeasure for spaceflight. INTRODUCTION: Bone loss is one of the greatest physiological challenges for extended-duration space missions. The ability of exercise to counteract weightlessness-induced bone loss has been studied extensively, but to date, it has proven ineffective. We evaluated the effectiveness of a combination of two countermeasures-treadmill exercise while inside a lower body negative pressure (LBNP) chamber-on bone loss during a 30-day bed rest study. MATERIALS AND METHODS: Eight pairs of identical twins were randomized into sedentary (SED) or exercise/LBNP (EX/LBNP) groups. Blood and urine samples were collected before, several times during, and after the 30-day bed rest period. These samples were analyzed for markers of bone and calcium metabolism. Repeated measures ANOVA was used to determine statistical significance. Because identical twins were used, both time and group were treated as repeated variables. RESULTS: Markers of bone resorption were increased during bed rest in samples from sedentary subjects, including the collagen cross-links and serum and urinary calcium concentrations. For N-telopeptide and deoxypyridinoline, there were significant (p < 0.05) interactions between group (SED versus EX/LBNP) and phase of the study (sample collection point). Pyridinium cross-links were increased above pre-bed rest levels in both groups, but the EX/LBNP group had a smaller increase than the SED group. Markers of bone formation were unchanged by bed rest in both groups. CONCLUSIONS: These data show that this weight-bearing exercise combined with LBNP ameliorates some of the negative effects of simulated weightlessness on bone metabolism. This protocol may pave the way to counteracting bone loss during spaceflight and may provide valuable information about normal and abnormal bone physiology here on Earth.

Twin Study↗

DOE OSTI2021

Preventing Failures By Dataset Shift Detection in Safety-Critical Graph Applications

Dataset shift refers to the problem where the input data distribution may change over time (e.g., between training and test stages). Since this can be a critical bottleneck in several safety-critical applications such as healthcare, drug-discovery, etc., dataset shift detection has become an important research issue in machine learning. Though several existing efforts have focused on image/video data, applications with graph-structured data have not received sufficient attention. Therefore, in this paper, we investigate the problem of detecting shifts in graph structured data through the lens of statistical hypothesis testing. Specifically, we propose a practical two-sample test based approach for shift detection in large-scale graph structured data. Our approach is very flexible in that it is suitable for both undirected and directed graphs, and eliminates the need for equal sample sizes. Using empirical studies, we demonstrate the effectiveness of the proposed test in detecting dataset shifts. We also corroborate these findings using real-world datasets, characterized by directed graphs and a large number of nodes.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Reassessing the MCNP Random Number Generator

Random number generators are integral components to Monte Carlo codes. They provide the pseudorandom number sequence used to actually sample the distributions of interest. As a result, they are one of the most important components to the software. The current recommended MCNP random number generator is a 63-bit linear congruential generator (LCG). This generator is quite fast, but it has some drawbacks. First, it only has a period of 2 63 . Due to the necessarily non-optimal usage of random numbers to ensure parallel reproducibility, this amount is too few to guarantee random number sequences are not reused in all configurations the code runs under. As simulation size increases, users will need to be aware of the limitations of the generator and tune configuration variables to best suit their simulations, or they will need to assume that reuse is not negatively affecting their answers. Neither of these are optimal. Second, small LCGs are fairly weak in bit generation quality, and this can have an unknown impact on the quality of the simulation. This paper is an investigation into whether or not more modern random number generators can supersede the current ones. The goal is to find a generator that is similar or superior in speed to the LCGs, has a state space large enough to make strong guarantees about random number reuse, and passes all modern random number test suites. If such a generator is found, it would eliminate the need for the user to even be aware of the limitations of the random number generator and would simplify the use of the code. This paper will be broken into several parts. Sec. 2 will discuss the evolution of the random number generator within the MCNP code. Sec. 3 will go over what a Monte Carlo code needs from a generator to be reproducible and portable and how the current generator behaves in that light. Sec. 4 goes through how each generator was tested. Finally, Sec. 5 will discuss improvements that could be made to the code.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2019

Informative Path Planning for Mapping Radiation

This project involves making measurements of contaminated areas using portable radiation detectors and small robots. Tasks involve operating detectors and small robots, combining data acquisition for the two systems, and automating the systems. The end result is a radiation map of contamination areas. Localization of radioactive sources and mapping of contamination distribution is essential when responding to emergencies, or when dealing with cleanup efforts. Radiation maps are used for situational awareness and for establishing a safe perimeter. However, it may be hazardous or impossible for humans to safely enter the site and survey the area. Informative Path Planning (IPP) is used to design a path for a robotic sensor platform to gather the most information about the radiation distribution while operating under the set of constraints given by the dynamics of the robot and other requirements such as minimizing the overall mission time. The key challenge for IPP is the tight coupling in multiple layers of decisions: Selection of locations to visit; Allocation of sensors to those locations; Processing of information gathered. Given a robot equipped with a basic gamma detector and Lidar sensor, how can we efficiently explore an unknown environment in such a way that we can satisfy the robot's constraints while simultaneously maximizing the accuracy of the map and minimizing the total runtime? This work presents a systematic procedure for IPP and environmental mapping that: Selects the best locations at which to sample; Finds the best path for robots; Estimates the measurement value at unknown locations using a Gaussian Process regression framework. Given a set of points where radiation measurements were taken, we are utilizing a Gaussian Process Regression with a Matern kernel to reconstruct the shape of the underlying ground truth. Mapping is done via the Robot Operating System's OpenSlam Gmapping package, which creates a 2D occupancy grid map. Simulated trials were run with a radiation source placed at random locations, and allowing the robot to select and move towards 20 samples at separate locations, as well as sampling along the path while moving. The simulated sensor model assumed an efficiency of 0.3, collection time of 1 second. Various weighting schemes were tested and compared. Quantitative evaluations often favored exploitation-heavy weighting schemes where μ was emphasized, with the Root Mean Squared Error (RMSE) quickly tending towards 2, whereas qualitative comparisons would favor exploration-biased schemes with greater weight on σ. The difference comes from operators often favoring knowing the general location of a source, rather than the exact properties of a source. Weighting of the path-length π often reduced the quality of the regression as less exploration occurred, however this may be deemed a worthwhile trade-off under certain circumstances, such as with sensitive robots. Successfully developed a methodology for informative path-planning for a robot to efficiently gather information and create a map of radiation. In the future, we would like to focus on: Hardware trials with integration of the robot platform and the IPP software; More refined sensor and environmental modeling; Multiple robot platforms.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Geographic source attribution of honey by strontium isotope analyses: Latvia and India measurements compared to model predictions in a feasibility study

Strontium isotope ratios ( 87 Sr/ 86 Sr) can be used to determine the geographic origin of agricultural products. Here, in this study, we measured the 87 Sr/ 86 Sr of honey samples from Richland, WA, USA, Latvia, and India, and compared the results to published 87 Sr/ 86 Sr from surrounding areas and values predicted based upon a random forest isoscape model (Bataille et al., 2020). While the 87 Sr/ 86 Sr of the honey samples compared well with previously published data, the model did not accurately predict the 87 Sr/ 86 Sr of the honey samples, demonstrating that further refinement of the model would be beneficial. Because Sr cycling in terrestrial ecosystems is complex, the 87 Sr/ 86 Sr of honey is likely to reflect several sources (e.g., nectar, surface water, dust) and may change over time. In order to accurately predict the 87 Sr/ 86 Sr of honey, models must consider local geology, ecology, and bee behavior. Additional research examining how Sr is incorporated into honey is needed to inform models.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1982

Some karyological observations on plants grown in space

Experiments were conducted to assess whether cell division in a plant root would be affected by prolonged exposure to microgravity. Root materials from sunflower, oat, and mung bean plants grown on STS-2 and STS-3 were utilized for the experiments. It is found that all oat, sunflower, and mung seedlings showed a reduced number of cells in division as they went through their first cell division cycle on earth when compared to their ground controls. A significant number of oat, mung, and sunflower plantlets exhibited random root orientation and the lack of strictly orthotropic growth of their shoot systems in the flight samples. In addition, it is found that the mung roots were apparently least affected in terms of their cytology despite the fact that their roots were often randomly oriented.

Krikorian, A. D.↗

DOE OSTI2024

Barium stars as tracers of s -process nucleosynthesis in AGB stars

Barium (Ba) stars help to verify asymptotic giant branch (AGB) star nucleosynthesis models since they experienced pollution from an AGB binary companion and thus their spectra carry the signatures of the slow neutron capture process (s process). For a large number (180) of Ba stars, we searched for AGB stellar models that match the observed abundance patterns. We aim to uncover any systematic deviations of the sample abundances from the predictions of the nucleosynthesis models. We employed three machine learning algorithms as classifiers: a Random Forest method, developed for this work, and the two classifiers used in our previous study. Compared to that work, we also expanded our observational sample with 11 Ba stars available in the supersolar metallicity range. We studied the statistical behaviour of the different s-process elements in the observational sample to investigate if the AGB models systematically under- or overpredict the abundances observed in the Ba stars and show the results in the form of violin plots of the residuals between spectroscopic abundances and model predictions. We inspected the correlations between the observed [Fe/H], the s-process elemental abundances, and the residuals. We employed the [Zr/Fe] and [Nb/Fe] abundances as a thermometer to constrain the operational temperature that rules the production of these elements in the sample stars, assuming a steady-state s process. We also investigated the mass distribution of the identified polluter AGB stars and the behaviour of the δ parameter, which describes the fraction of accreted AGB material relative to the Ba star envelope. We find a significant trend in the residuals that implies an underproduction of the elements just after the first s-process peak (Nb, Mo, and Ru) in the models relative to the observations. This may originate from a neutron-capture process (e.g. the intermediate neutron-capture process, i process) not yet included in the AGB models of metallicity from solar to roughly 1/5 solar, corresponding to the range of the Ba stars. Correlations are found between the residuals of these peculiar elements, suggesting a common origin for the deviations from the models. In addition, there is a weak metallicity dependence of the residuals of these elements. The s-process temperatures derived with the [Zr/Fe] – [Nb/Fe] thermometer have an unrealistic value for the majority of our stars. The most likely explanation is that at least a fraction of these elements are not produced in a steady-state s process, and instead may be due to processes not included in the AGB models. The mass distribution of the identified models confirms that our sample of Ba stars was polluted by low-mass AGB stars (< 4 M ⊙ ). Most of the matching AGB models require low accreted mass, but a few systems with high accreted mass are needed to explain the observations.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Adaptive sampling quasi-Newton methods for zeroth-order stochastic optimization

Here, we consider unconstrained stochastic optimization problems with no available gradient information. Such problems arise in settings from derivative-free simulation optimization to reinforcement learning. We propose an adaptive sampling quasi-Newton method where we estimate the gradients using finite differences of stochastic function evaluations within a common random number framework. We develop modified versions of a norm test and an inner product quasi-Newton test to control the sample sizes used in the stochastic approximations and provide global convergence results to the neighborhood of a locally optimal solution. We present numerical experiments on simulation optimization problems to illustrate the performance of the proposed algorithm. When compared with classical zeroth-order stochastic gradient methods, we observe that our strategies of adapting the sample sizes significantly improve performance in terms of the number of stochastic function evaluations required.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1994

An IUE survey of interstellar H I Ly alpha absorption. 2: Interpretations

We present an analysis of interstellar neutral hydrogen column densities obtained from archival Ly alpha absorption line data toward the complete sample of B2 and hotter stars observed at high spectral resolution with the IUE satellite. The full sample includes 554 stars and more than doubles the number of lines of sight previously observed. Many of the B2 and B1.5 stars exhibit contamination from stellar Ly alpha absorption, and were excluded from the subsequent analysis. The final working sample includes 393 stars. We present statistical averages for a number of quantities derived for the sample. The stars range in distance from 0.12 to 11 kpc with an average distance of 2.1 kpc. Values for average sight-line density range from 0.017 to 8.62 atoms cm(exp -3), with an overall average of 0.23 atoms cm(exp -3). Neutral hydrogen and dust are well correlated, with N(H I)/E(B - V) = 4.93 x 10(exp 21) cm(exp -2) mag(exp -1), and N(H I)/E(Bump) = 2.17 x 10(exp 21) cm(exp -2) mag(exp -1). There is an increase in the H I to dust ratios for the densest sight lines. Evidently, the H I to dust ratios in dense clouds are higher than in the lower density medium between the clouds and in interarm directions. The effect is probably an indication of dust modification in the dense clouds. The H I to dust ratios are approx. 17% smaller for the sight lines to O stars compared to the ratios found toward B stars. We have identified sight lines with anomalously large and small values of N(H I)/E(B - V) and H(H I)/E(Bump). Some of these sight lines are well-known examples of peculiar extinction (i.e., HD 147933 and HD 37061 (NU Ori)). Others are less well known and may provide important new examples of regions with highly modified dust. The number of stars with anomalously low H I to dust ratios is disproportionately larger than the number of stars with anomalously high H I to dust ratios. The distribution of the gas away form the Galactic plane for the sample of objects is complex. For the subset of 375 stars whose lines of sight have a statistically low probablility of intersecting a large cloud, the distribution may be roughly approximated by an exponential density distribution, with a midplane density of 0.366 atoms cm(exp -3), a scale height of 195 pc, and a random logarithmic scattering parameter sigma (sub p) of 0.159 dex. For the same sample of stars, interstellar dust is found to be confined closer to the plane than the H I, with (E(B - V)/r)(sub 0) = 0.257 mag kpc(exp -1), scale height h = 152 pc, and sigma(sub p) = 0.263 dex. The dust distribution is more inhomogeneous than the gas distribution. The observed distribution of H I away from the Galactic plane can also be fitted with a two-component exponential model including the effects of patchiness. Unfortunately, the foreground contamination produced by the cloudy and more confined component of H I makes it difficult to estimate the scale height of the extended component without invoking an independent estimate of its midplane density. Assuming n(sub 2)(0) = 0.16 cm(exp -3) from the Copernicus satellite H I/H(sub 2) survey, we obtain n(sub 1)(0) = 0.247 cm(exp -3), h(sub 1) = 73 PC, and h(sub 2) + 357 pc.

Diplas, Athanassios↗