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At least 1,783 records · Page 99

Agent-Based Model of Combined Community- and Jail-Based Take-Home Naloxone Distribution

Importance Opioid-related overdose accounts for almost 80 000 deaths annually across the US. People who use drugs leaving jails are at particularly high risk for opioid-related overdose and may benefit from take-home naloxone (THN) distribution. Objective To estimate the population impact of THN distribution at jail release to reverse opioid-related overdose among people with opioid use disorders. Design, Setting, and Participants This study developed the agent-based Justice-Community Circulation Model (JCCM) to model a synthetic population of individuals with and without a history of opioid use. Epidemiological data from 2014 to 2020 for Cook County, Illinois, were used to identify parameters pertinent to the synthetic population. Twenty-seven experimental scenarios were examined to capture diverse strategies of THN distribution and use. Sensitivity analysis was performed to identify critical mediating and moderating variables associated with population impact and a proxy metric for cost-effectiveness (ie, the direct costs of THN kits distributed per death averted). Data were analyzed between February 2022 and March 2024. Intervention Modeled interventions included 3 THN distribution channels: community facilities and practitioners; jail, at release; and social network or peers of persons released from jail. Main Outcomes and Measures The primary outcome was the percentage of opioid-related overdose deaths averted with THN in the modeled population relative to a baseline scenario with no intervention. Results Take-home naloxone distribution at jail release had the highest median (IQR) percentage of averted deaths at 11.70% (6.57%-15.75%). The probability of bystander presence at an opioid overdose showed the greatest proportional contribution (27.15%) to the variance in deaths averted in persons released from jail. The estimated costs of distributed THN kits were less than $\$$15 000 per averted death in all 27 scenarios. Conclusions and Relevance This study found that THN distribution at jail release is an economical and feasible approach to substantially reducing opioid-related overdose mortality. Training and preparation of proficient and willing bystanders are central factors in reaching the full potential of this intervention.

Tatara, Eric [Argonne National Laboratory (ANL), A↗

Coverage, repulsion, and reactivity of hydrogen on High-Entropy alloys

Modeling hydrogen evolution reaction (HER) activity probability on IrPdPtRhRu(1 1 1) high-entropy alloys. Determining hydrogen coverages based on ligand effects and generalized hydrogen–hydrogen repulsion. The rate of H 2 formation is highly impacted by the level of hydrogen coverage on the catalyst surface. In search of optimal catalytic properties high-entropy alloys (HEA) are promising candidates that utilize the compositional space of multiple elements. Based on simulations of HEA model (1 1 1) surfaces with a range of hydrogen coverages, distributions of binding energies are used to construct a framework that approximates the probability that adsorbed hydrogen may lead to the formation of H 2 as a function of applied potential. By optimizing the alloy compositions for the highest activity probability at given potentials the best and most efficient catalyst candidates for HER can be identified. Treating hydrogen–hydrogen repulsion effects and binding energy separately, we find that the repulsion is larger for HEAs than for pure metals. Differing isotherm slopes in the mean adsorption and desorption energies demonstrate a possible hysteresis for hydrogen adsorption on HEAs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The use of prior probabilities in maximum likelihood classification of remotely sensed data

Possibilities for the improvement of classification accuracies by the use of prior information about the expected distribution of classes in the maximum likelihood classification of remote sensing data are examined. The modification of the maximum likelihood decision rule to take into account one or several sets of probabilities for the occurrence of classes which probabilities are based on independent knowledge of the area surveyed is demonstrated. It is then shown that the use of prior probabilities is sufficiently versatile so as to allow the prior weighting of output classes based on their anticipated sizes as well as the merging of continuously varying measurements with discrete collateral information data sets and the construction of time-sequential classification systems in which an earlier classification modifies the outcome of a latter one.

Strahler, A. H.↗

The statistics of gravitational lenses - The distributions of image angular separations and lens redshifts

An analytical calculation is presented which determines the probability that the light from a distant quasar can be lensed by objects in a different redshift range. Three types of information are used to make the calculation: (1) the physical properties of the intervening scattering lenses; (2) the intrinsic properties of the quasars and (3) the selection procedures by which the quasar samples are acquired. A series of differential equations is given in which the probability is derived, and a number of recommendations are offered with respect to VLA and Space Telescope observations of quasars lensed in this way.

Turner, E. L.↗

Probabilistic Prediction of Lifetimes of Ceramic Parts

ANSYS/CARES/PDS is a software system that combines the ANSYS Probabilistic Design System (PDS) software with a modified version of the Ceramics Analysis and Reliability Evaluation of Structures Life (CARES/Life) Version 6.0 software. [A prior version of CARES/Life was reported in Program for Evaluation of Reliability of Ceramic Parts (LEW-16018), NASA Tech Briefs, Vol. 20, No. 3 (March 1996), page 28.] CARES/Life models effects of stochastic strength, slow crack growth, and stress distribution on the overall reliability of a ceramic component. The essence of the enhancement in CARES/Life 6.0 is the capability to predict the probability of failure using results from transient finite-element analysis. ANSYS PDS models the effects of uncertainty in material properties, dimensions, and loading on the stress distribution and deformation. ANSYS/CARES/PDS accounts for the effects of probabilistic strength, probabilistic loads, probabilistic material properties, and probabilistic tolerances on the lifetime and reliability of the component. Even failure probability becomes a stochastic quantity that can be tracked as a response variable. ANSYS/CARES/PDS enables tracking of all stochastic quantities in the design space, thereby enabling more precise probabilistic prediction of lifetimes of ceramic components.

Nemeth, Noel N.↗

Public Risk Assessment Program

The Public Entry Risk Assessment (PERA) program addresses risk to the public from shuttle or other spacecraft re-entry trajectories. Managing public risk to acceptable levels is a major component of safe spacecraft operation. PERA is given scenario inputs of vehicle trajectory, probability of failure along that trajectory, the resulting debris characteristics, and field size and distribution, and returns risk metrics that quantify the individual and collective risk posed by that scenario. Due to the large volume of data required to perform such a risk analysis, PERA was designed to streamline the analysis process by using innovative mathematical analysis of the risk assessment equations. Real-time analysis in the event of a shuttle contingency operation, such as damage to the Orbiter, is possible because PERA allows for a change to the probability of failure models, therefore providing a much quicker estimation of public risk. PERA also provides the ability to generate movie files showing how the entry risk changes as the entry develops. PERA was designed to streamline the computation of the enormous amounts of data needed for this type of risk assessment by using an average distribution of debris on the ground, rather than pinpointing the impact point of every piece of debris. This has reduced the amount of computational time significantly without reducing the accuracy of the results. PERA was written in MATLAB; a compiled version can run from a DOS or UNIX prompt.

Mendeck, Gavin↗

Radar Cross Section of Orbital Debris Objects

This discussion is concerned with the radar-data analysis and usage involved in the building of model orbital debris (OD) populations in the near-Earth environment, focusing on radar cross section (RCS). While varying with radar wavelength, physical dimension, material composition, overall shape and structure, the RCS of an irregular object is also strongly dependent on its spatial orientation. The historical records of observed RCSs for cataloged OD objects in the Space Surveillance Network are usually distributed over an RCS range, forming respective characteristic patterns. The National Aeronautics and Space Administration (NASA) Size Estimation Model provides an empirical probability-density function of RCS as a function of “effective diameter” (or “characteristic length”), which makes it feasible to predict possible RCS distributions for a given model OD population and to link data with model from a statistical perspective. The discussion also includes application of the widely used method of moments (MoM) and the Generalized Multi-particle Mie-solution (GMM) in the prediction of the RCS of arbitrarily shaped objects. Theoretical calculation results for an aluminum cube are compared with corresponding experimental measurements.

Xu, Yu-Lin↗

Risk Assessment of Bone Fracture During Space Exploration Missions to the Moon and Mars

The possibility of a traumatic bone fracture in space is a concern due to the observed decrease in astronaut bone mineral density (BMD) during spaceflight and because of the physical demands of the mission. The Bone Fracture Risk Module (BFxRM) was developed to quantify the probability of fracture at the femoral neck and lumbar spine during space exploration missions. The BFxRM is scenario-based, providing predictions for specific activities or events during a particular space mission. The key elements of the BFxRM are the mission parameters, the biomechanical loading models, the bone loss and fracture models and the incidence rate of the activity or event. Uncertainties in the model parameters arise due to variations within the population and unknowns associated with the effects of the space environment. Consequently, parameter distributions were used in Monte Carlo simulations to obtain an estimate of fracture probability under real mission scenarios. The model predicts an increase in the probability of fracture as the mission length increases and fracture is more likely in the higher gravitational field of Mars than on the moon. The resulting probability predictions and sensitivity analyses of the BFxRM can be used as an engineering tool for mission operation and resource planning in order to mitigate the risk of bone fracture in space.

Lewandowski, Beth E.↗

Risk Assessment of Bone Fracture During Space Exploration Missions to the Moon and Mars

The possibility of a traumatic bone fracture in space is a concern due to the observed decrease in astronaut bone mineral density (BMD) during spaceflight and because of the physical demands of the mission. The Bone Fracture Risk Module (BFxRM) was developed to quantify the probability of fracture at the femoral neck and lumbar spine during space exploration missions. The BFxRM is scenario-based, providing predictions for specific activities or events during a particular space mission. The key elements of the BFxRM are the mission parameters, the biomechanical loading models, the bone loss and fracture models and the incidence rate of the activity or event. Uncertainties in the model parameters arise due to variations within the population and unknowns associated with the effects of the space environment. Consequently, parameter distributions were used in Monte Carlo simulations to obtain an estimate of fracture probability under real mission scenarios. The model predicts an increase in the probability of fracture as the mission length increases and fracture is more likely in the higher gravitational field of Mars than on the moon. The resulting probability predictions and sensitivity analyses of the BFxRM can be used as an engineering tool for mission operation and resource planning in order to mitigate the risk of bone fracture in space.

Lewandowski, Beth E.↗

Photoionization of the diffuse interstellar medium and galactic halo by OB associtations

Assuming smoothly varying H I distributions in te Galactic disk, we have calculated the geometry of diffuse II regions due to OB associations in the Galactic plane. Near the solar circle, OB associations with a Lyman continuum (Lyc) photon luminosity Psi(sub Lyc) = 3.3 x 10(exp 7) cm(exp -2) s(exp -1), produce H II regions that are density bounded in the vertical direction (H II chimneys) allowing Lyc to escape the gaseous disk and penetrate into the Galactic halo. We provide analytic formulae for the Lyc escape fraction as functions of S(sub 0) O-star catalog of Garmany and a new Lyc stellar stellar Lyc stellar flux calibration, we find a production rate of Lyc photons by OB associations within 2.5 kpc of Psi(sub Lyc) = 3.3 x 10(exp 7) cm(exp -2) s(exp -1). Integrating the fraction of Lyc photons that escape the disk over our adopted luminosity function of OB associations, we estimate that approximately 7% of the ionizing photons, or Phi(sub Lyc) = 2.3 x 10(exp 6) cm(exp -2) s(exp -1), escape each side of the H I disk layer and penetrate the diffuse ionized medium ('Reynolds layer'). This flux is sufficient to explain the potoionization of this, although we have not constructed a model for the observed H-alpha emission and pulsar dispersion measures that is fully consistent with the absorption rate of Lyc in the H II layer. Since our quiescent model does not account for the effects of dynamic chimneys and superbubbles, which should enhance Lyc escape, we conclude the O stars are the probable source of ionizing radiation for the Reynolds layer. For a random distribution of OB associations throughout the disk, the Lyc flux is nearly uniform for heights Z is greater than approximately 0.8 kpc above the midplane.

Dove, James B.↗

Boost-phase discrimination research

The final report describes the combined work of the Computational Chemistry and Aerothermodynamics branches within the Thermosciences Division at NASA Ames Research Center directed at understanding the signatures of shock-heated air. Considerable progress was made in determining accurate transition probabilities for the important band systems of NO that account for much of the emission in the ultraviolet region. Research carried out under this project showed that in order to reproduce the observed radiation from the bow shock region of missiles in their boost phase it is necessary to include the Burnett terms in the constituent equation, account for the non-Boltzmann energy distribution, correctly model the NO formation and rotational excitation process, and use accurate transition probabilities for the NO band systems. This work resulted in significant improvements in the computer code NEQAIR that models both the radiation and fluid dynamics in the shock region.

Langhoff, Stephen R.↗

Plasma turbulence in the downstream ionosheath of Venus

Observations made by the Pioneer Venus Orbiter plasma analyzer and the plasma wave instrument in the Venus ionosheath are compared. Large increases in plasma wave turbulence levels appear to be connected with changing plasma distributions and interpenetrating plasma beams. Some of these plasma waves are identified as Doppler - shifted ion acoustic waves due to beam/beam interactions, but it is noted that different forms of instabilities are probably also operative. The changes in the temperature, intensity and energy of the peak in the PVO plasma distributions are similar to those observed by Venera 10 closer to the planet and appear to be evidence for rarefaction and compression in the downstream ionosheath. Some of the changes in the PVO plasma distributions may be related to the presence of a second ion population or the acceleration of protons.

Intriligator, D. S.↗

Redundancy: How Many Unreliable Spares are Needed for High Reliability and Confidence on a Time Limited Mission?

This paper investigates the number of redundant units needed to achieve high reliability with high confidence. The approach applies to the case where the unit failure rate is too high for a single unit to provide the required reliability over the mission duration. To achieve high reliability, the design then uses N redundant units, one operating unit and N – 1 spares. If the unit failure rate is f, the mission length is L, and f * L is small (not the case assumed here), the unit failure probability over the mission duration is F1 = f * L << 1. In this case, the probability that all N units will fail is FN = F1N, and the needed N = LN(FN)/LN(F1). For the case of large f * L assumed here, F1 = f * L > 1, and F1 is the expected number of failures during the mission. The needed redundancy, N, to achieve the specified N unit reliability, FN, can be computed using the cumulative Poisson distribution with mean equal to F1. The number of spares, N - 1, is increased until the probability - that the total number of failures will be less than N -1 - achieves the required reliability. The confidence that this reliability can be achieved can be computed using the cumulative Poisson distribution or the chi-square distribution. Since the measured unit failure rate, f, has some uncertainty, the confidence that the rate is not lower than the actual failure rate and the required reliability is not overestimated is about 50%. Adding more redundant units increases the confidence that the required reliability, FN, will be achieved. For a fixed number of redundant units, the expected reliability and confidence can be traded off, since lower reliability goals have higher confidence in being achieved. Both the required reliability and confidence can be specified initially and the needed number of redundant units computed using the measured failure rate. The unit failure rate is determined by initial reliability growth testing to remove design errors and to better estimate the final constant failure rate. Reducing the failure rate and reducing its variance both reduce the number of redundant units needed for the required reliability and confidence. Since the total cost is the sum of the costs of the units and of the testing, there is an optimum test time that produces minimum cost.

Harry W. Jones↗

Monte Carlo analysis of lobular gas-surface scattering in tubes applied to thermal transpiration

A model of rarefied gas flow in tubes was developed which combines a lobular distribution with diffuse reflection at the wall. The model with Monte Carlo techniques was used to explain previously observed deviations in the free molecular thermal transpiration ratio which suggest molecules can have a greater tube transmission probability in a hot-to-cold direction than in a cold-to-hot direction. The model yields correct magnitudes of transmission probability ratios for helium in Pyrex tubing (1.09 to 1.14), and some effects of wall-temperature distribution, tube surface roughness, tube dimensions, gas temperature, and gas molecular mass.

Smith, J. D.↗

Application of the Bootstrap Statistical Method in Deriving Vibroacoustic Specifications

This paper discusses the Bootstrap Method for specification of vibroacoustic test specifications. Vibroacoustic test specifications are necessary to properly accept or qualify a spacecraft and its components for the expected acoustic, random vibration and shock environments seen on an expendable launch vehicle. Traditionally, NASA and the U.S. Air Force have employed methods of Normal Tolerance Limits to derive these test levels based upon the amount of data available, and the probability and confidence levels desired. The Normal Tolerance Limit method contains inherent assumptions about the distribution of the data. The Bootstrap is a distribution-free statistical subsampling method which uses the measured data themselves to establish estimates of statistical measures of random sources. This is achieved through the computation of large numbers of Bootstrap replicates of a data measure of interest and the use of these replicates to derive test levels consistent with the probability and confidence desired. The comparison of the results of these two methods is illustrated via an example utilizing actual spacecraft vibroacoustic data.

Hughes, William O.↗

Fault diagnosis and fault tolerant control for T-S fuzzy stochastic distribution systems subject to sensor and actuator faults

The problem of fault diagnosis (FD) and fault tolerant control (FTC) for a class of Takagi-Sugeno (T-S) fuzzy stochastic distribution control (SDC) systems subject to sensor and actuator faults is discussed in this paper. First, fuzzy logic models are used to approximate the output probability density function (PDF). Next, an adaptive augmented state/fault diagnosis observer is proposed to estimate the system state, sensor and the actuator faults simultaneously. New expected weights based on the sensor fault estimation information and a PI-type fuzzy feedback fault tolerant (FT) controller are designed to compensate the effect of sensor fault and actuator fault simultaneously. When the sensor fault occurs, the expected objective is redesigned to compensate the sensor fault. Meanwhile, the PI controller can compensate the effect of actuator fault, and the output PDF of the system can still track the desired PDF after the fault occurs. Finally, an example of quality distribution control in chemical reaction process is given to confirm the effectiveness of the algorithm.

42 ENGINEERING↗

The density distribution and physical origins of intermittency in supersonic, highly magnetized turbulence with diverse modes of driving

The probability density function (PDF) of the logarithmic density contrast, s = ln (ρ/ρ 0 ), with gas density ρ and mean density ρ 0 , for hydrodynamical supersonic turbulence is well known to have significant non-Gaussian (intermittent) features that monotonically increase with the turbulent Mach number, M. By studying the mass- and volume-weighted s-PDF for an ensemble of 36 sub-to-trans-Alfvenic mean-field, supersonic, isothermal turbulence simulations with different modes of driving, relevant to molecular gas in the cool interstellar medium, we show that a more intricate picture emerges for the non-Gaussian nature of s. Using four independent measures of the non-Gaussian components, we find hydrodynamical-like structure in the highly magnetized plasma for M≲4. However, for M≳4, the non-Gaussian signatures disappear, leaving approximately Gaussian s-statistics – exactly the opposite of hydrodynamical turbulence in the high-M limit. We also find that the non-Gaussian components of the PDF increase monotonically with more compressive driving modes. To understand the M≲4 non-Gaussian features, we use one-dimensional pencil beams to explore the dynamics along and across the large-scale magnetic field, B 0 . Here we discuss kinetic, density, and magnetic field fluctuations from the pencil beams, and identify physical sources of non-Gaussian components to the PDF as single, strong shocks coupled to fast magnetosonic compressions that form along B 0 . We discuss the Gaussianization of the M≳4 s-fields through the lens of two phenomenologies: the self-similarity of the s-field and homogenization of the dynamical time-scales between the over- and underdense regions in the compressible gas.

79 ASTRONOMY AND ASTROPHYSICS↗

Visualizing Time-Varying Distribution Data in EOS Application

In this research, we have developed several novel visualization methods for spatial probability density function data. Our focus has been on 2D spatial datasets, where each pixel is a random variable, and has multiple samples which are the results of experiments on that random variable. We developed novel clustering algorithms as a means to reduce the information contained in these datasets; and investigated different ways of interpreting and clustering the data.

Shen, Han-Wei↗