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At least 487 records · Page 27

A Monte-Carlo Model for the Formation of Radiation-induced Chromosomal Aberrations

Purpose: To simulate radiation-induced chromosome aberrations in mammalian cells (e.g., rings, translocations, and dicentrics) and to calculate their frequency distributions following exposure to DNA double strand breaks (DSBs) produced by high-LET ions. Methods: The interphase genome was assumed to be comprised of a collection of 2 kbp rigid-block monomers following the random-walk geometry. Additional details for the modeling of chromosomal structure, such as chromosomal domains and chromosomal loops, were included. A radial energy profile for heavy ion tracks was used to simulate the high-LET pattern of induced DSBs. The induced DSB pattern depended on the ion charge and kinetic energy, but always corresponded to the DSB yield of 25 DSBs/cell/Gy. The sum of all energy contributions from Poisson-distributed particle tracks was taken to account for all possible one-track and multi-track effects. The relevant output of the model was DNA fragments produced by DSBs. The DSBs, or breakpoints, were defined by (x, y, z, l) positions, where x, y, z were the Euclidian coordinates of a DSB, and where l was the relative position along the genome. Results: The code was used to carry out Monte Carlo simulations for DSB rejoinings at low doses. The resulting fragments were analyzed to estimate the frequencies of specific types of chromosomal aberrations. Histograms for relative frequencies of chromosomal aberrations and P.D.F.s (probability density functions) of a given aberration type were produced. The relative frequency of dicentrics to rings was compared to empirical data to calibrate rejoining probabilities. Of particular interest was the predicted distribution of ring sizes, irrespective of their frequencies relative to other aberrations. Simulated ring sizes were . 4 kbp, which are far too small to be observed experimentally (i.e., by microscopy) but which, nevertheless, are conjectured to exist. Other aberrations, for example, inversions, translocations, as well as multi-centrics were also recorded. Conclusion: High-LET DNA damage affects the frequencies of chromosomal aberrations. The ratio of rings to dicentrics is correct for the genomic size cut-offs corresponding to available experimental data. The present work predicts a relative abundance of small rings following irradiation by heavy ions.

Ponomarev, Artem L.↗

FUNSTAT and statistical image representations

General ideas of functional statistical inference analysis of one sample and two samples, univariate and bivariate are outlined. ONESAM program is applied to analyze the univariate probability distributions of multi-spectral image data.

Parzen, E.↗

Unsaturated Comptonization of isotropic photon spectra by relativistic electrons

The multiple scattering approach for evaluating the transformation of an arbitrary soft photon spectrum as a result of unsaturated Compton scatterings in a medium of relativistic electrons is explored. The medium is assumed to be infinite and spatially homogeneous but may be time-dependent, and the photons are isotropic. It is shown that the distortion of a radiation spectrum can be described analytically in a compact form using the Fourier transform of the single-scattering probability. In the nonrelativistic case, the validity of the known analytical results derived from the Kompaneets (1957) equation is extended to arbitrary electron distribution functions and photon spectra. For relativistic electrons, simple expressions are obtained for the total energy that is transferred from the electrons to the photons and for the distortion in the Rayleigh-Jeans regime of a blackbody spectrum. It is demonstrated that the treatment applies to Comptonization in a relativistic jet and that Comptonization of very soft trapped photons by semirelativistic electrons in an expanding medium leads naturally to a log Gaussian spectrum, of the form observed in blazars.

Loeb, Abraham↗

Incorporation of spatial information in Bayesian image reconstruction - The maximum residual likelihood criterion

We have developed a new figure of merit, a 'maximum-residual-likelihood' (MRL) statistic, for the goodness of fit for Bayesian image restoration which explicitly incorporates spatial information. The MRL constraint provides a natural means of incorporating the prior knowledge that the residuals contain no spatial structure through the autocorrelation function of the residuals. We demonstrate that this statistic follows a Chi-square distribution and that forcing this statistic to have its most probable value leads to a restored image whose residuals are consistent with the noise model. Our numerical experiments suggest that image restoration using the MRL statistic alone is numerically robust and produces results which are independent of the initial guess for the restored image. However, we caution that using the MRL statistic without an image prior can result in overresolution in low SNR portions of the image.

Pina, R. K.↗

Statistics of highly magnified gravitational images in clusters of galaxies. I - Implications for the clusters. II - Implications for the sources

A study is presently conducted of the probability distribution of observing images of background galaxies that are gravitationally lensed in the form of elongated arcs by clusters of galaxies, as a function of arc width, curvature radius, and the elongation's orientation. An upper limit is obtained on the size of the cores which is smaller than cluster core radii obtained for the gas from the X-ray surface brightness. It is argued that lensing clusters tend to be elongated along the line of sight; projection effects will enhance surface density. In the second part of this work, it is shown that the number of arcs expected in lensing clusters is primarily dependent on the angular size of the sources, since lower magnification is required to generate an arc of fixed length for a larger source.

Miralda-Escude, Jordi↗

Large-amplitude auroral electric fields measured with DE 1

A large fraction of the available electric field data from the plasma wave instrument (PWI) on the Dynamics Explorer (DE) 1 satellite has recently been searched for events with large-amplitude electric fields. The magnitude and distribution of these peak events as functions of altitude have been determined. The largest amplitudes were found between 1.4 and 2.5 RE and the probability of finding large electric fields was greatest in the range of 1.5 to 1.7 RE. However, when the measured electric field values are 'mapped' to the Earth's surface in order to account for the geometry of the geomagnetic field lines, then the mapped values always increase with increasing altitude. This radial dependence is considered to be evidence for magnetic field-aligned electric fields. The largest electric field that was detected with the DE 1 instrument had a magnitude exceeding 840 mV/m and was found at 1.45 R(E). This field appears to be associated with a low-frequency wave. At subauroral latitudes the average mapped electric field is nearly constant with altitude, as it should be where there are no magnetic field-aligned potential drops. Within auroral latitudes the average value of the mapped electric field increases as altitude increases. The largest gradients are found between 1.3 and 2 R(E).

Weimer, D. R.↗

Quantifying Uncertainties in the Thermo-Mechanical Properties of Particulate Reinforced Composites

The present paper reports results from a computational simulation of probabilistic particulate reinforced composite behavior. The approach consists use of simplified micromechanics of particulate reinforced composites together with a Fast Probability Integration (FPI) technique. Sample results are presented for a Al/SiC(sub p)(silicon carbide particles in aluminum matrix) composite. The probability density functions for composite moduli, thermal expansion coefficient and thermal conductivities along with their sensitivity factors are computed. The effect of different assumed distributions and the effect of reducing scatter in constituent properties on the thermal expansion coefficient are also evaluated. The variations in the constituent properties that directly effect these composite properties are accounted for by assumed probabilistic distributions. The results show that the present technique provides valuable information about the scatter in composite properties and sensitivity factors, which are useful to test or design engineers.

Mital, Subodh K.↗

"Novel Techniques in Non-Stationary Analysis of Rotorcraft Vibration Signitures"

This research effort produced new methods to analyze the performance of linear predictors that track non-stationary processes. Specifically, prediction methods have been applied to the vibration pattern of rotorcraft drivetrains. This analysis is part or a larger rotorcraft Health and Usage Monitoring System (HUMS) that can diagnose immediate failures of the subsystems, as indicated by abrupt change in the vibration signature, and prognosticate future health, by examining the vibration patterns against long-term trends. This problem is described by a earlier joint paper co-authored by members of the funding agency and the recipient institutions prior to this grant effort. Specific accomplishments under this grant include the following: (1) Definition of a framework for analysis of non-stationary time-series estimation using the coefficients of an adaptive filter. (2) Description of a novel method of combining short-term predictor error and long-term regression error to analyze the performance of a non-stationary predictor. (3) Formulation of a multi-variate probability density function that quantifies the performance of a adaptive predictor by using the short- and long-term error variables in a Gamma function distribution. and (4) Validation of the mathematical formulations with empirical data from NASA flight tests and simulated data to illustrate the utility beyond the domain of vibrating machinery.

Meng, Teresa↗

Improving Project Management with Simulation and Completion Distribution Functions

Despite the critical importance of project completion timeliness, management practices in place today remain inadequate for addressing the persistent problem of project completion tardiness. A major culprit in late projects is uncertainty, which most, if not all, projects are inherently subject to. This uncertainty resides in the estimates for activity durations, the occurrence of unplanned and unforeseen events, and the availability of critical resources. In response to this problem, this research developed a comprehensive simulation based methodology for conducting quantitative project completion time risk analysis. It is called the Project Assessment by Simulation Technique (PAST). This new tool enables project stakeholders to visualize uncertainty or risk, i.e. the likelihood of their project completing late and the magnitude of the lateness, by providing them with a completion time distribution function of their projects. Discrete event simulation is used within PAST to determine the completion distribution function for the project of interest. The simulation is populated with both deterministic and stochastic elements. The deterministic inputs include planned project activities, precedence requirements, and resource requirements. The stochastic inputs include activity duration growth distributions, probabilities for events that can impact the project, and other dynamic constraints that may be placed upon project activities and milestones. These stochastic inputs are based upon past data from similar projects. The time for an entity to complete the simulation network, subject to both the deterministic and stochastic factors, represents the time to complete the project. Repeating the simulation hundreds or thousands of times allows one to create the project completion distribution function. The Project Assessment by Simulation Technique was demonstrated to be effective for the on-going NASA project to assemble the International Space Station. Approximately $500 million per month is being spent on this project, which is scheduled to complete by 2010. NASA project stakeholders participated in determining and managing completion distribution functions produced from PAST. The first result was that project stakeholders improved project completion risk awareness. Secondly, using PAST, mitigation options were analyzed to improve project completion performance and reduce total project cost.

Cates, Grant R.↗

High-accuracy computation of Delta V magnitude probability densities - Preliminary remarks

This paper describes an algorithm for the high accuracy computation of some statistical quantities of the magnitude of a random trajectory correction maneuver (TCM). The trajectory correction velocity increment Delta V is assumed to be a three-component random vector with each component being a normally distributed random scalar having a possibly nonzero mean. Knowledge of the statitiscal properties of the magnitude of a random TCM is important in the planning and execution of maneuver strategies for deep-space missions such as Galileo. The current algorithm involves the numerical integration of a set of differential equations. This approach allows the computation of density functions for specific Delta V magnitude distributions to high accuracy without first having to generate large numbers of random samples. Possible applications of the algorithm to maneuver planning, planetary quarantine evaluation, and guidance success probability calculations are described.

Chadwick, C.↗

A Framework for Parametric and Predictive Uncertainty Quantification in the E3SM Land Model: Assessing Site and Observable Generalizability

Quantifying parametric uncertainty using observations from individual sites provides a critical foundation for Earth system modeling, serving as a necessary first step before scaling up to regional or global applications. This study introduces a novel computational framework designed to enhance model predictability by reducing parametric uncertainty and assessing site and observable generalizability using various observational constraints. The framework integrates five components: Model Simulation, Statistical Emulation, Global Sensitivity Analysis (GSA), Model Calibration, and Model Prediction. Using the E3SM land model, we simulated site-level land-atmosphere carbon and energy fluxes from 2003 to 2007 across five evergreen needleleaf FLUXNET sites, perturbing 26 vegetation-related model parameters. Gaussian process emulators were employed to expedite GSA and model calibration. Four critical parameters that strongly influence selected land-atmosphere fluxes were identified by GSA. Bayesian approaches were used to infer parameter probability distributions leveraging synthetic data and FLUXNET observations. The results reveal that posterior parameter distributions vary significantly across different sites and observables within the same plant functional type. Probabilistic predictions indicate that parameters calibrated at one site can enhance predictive accuracy at other sites, although site heterogeneity may sometimes outweigh parametric uncertainty. Additionally, the probabilistic predictions demonstrate that calibration for one variable can also improve predictability for other variables, thereby maximizing predictive capabilities with limited observations. This framework provides a powerful approach for reducing parametric uncertainty in Earth system models and deepening our understanding of carbon dynamics and energy cycles. Its adaptability makes it a valuable tool for broader applications in Earth system modeling.

54 ENVIRONMENTAL SCIENCES↗

Radar modeling of space diversity associated with slant path rain attenuation at variable path angles, frequencies, and drop size distributions

Single and joint terminal slant path attenuation statistics at frequencies of 28.56 and 19.04 GHz were derived from radar data. Statistics were independently obtained for path angles of 20, 45, and 90 deg, in order to examine how path angle influences both single terminal and joint probability distributions. A prediction technique is demonstrated to work well for calculating both single and joint terminal distributions at other path angles. Diversity gains and autocorrelation function dependence on site spacing were determined employing the radar modeling results.

Goldhirsh, J.↗

Measurement of Attenuation with Airborne and Ground-Based Radar in Convective Storms Over Land and Its Microphysical Implications

Observations by the airborne X-band Doppler radar (EDOP) and the NCAR S-band polarimetric (S-POL) radar from two field experiments are used to evaluate the Surface ref'ercnce technique (SRT) for measuring the path integrated attenuation (PIA) and to study attenuation in deep convective storms. The EDOP, flying at an altitude of 20 km, uses a nadir beam and a forward pointing beam. It is found that over land, the surface scattering cross-section is highly variable at nadir incidence but relatively stable at forward incidence. It is concluded that measurement by the forward beam provides a viable technique for measuring PIA using the SRT. Vertical profiles of peak attenuation coefficient are derived in vxo deep convective storms by the dual-wavelength method. Using the measured Doppler velocity, the reflectivities at. the two wavelengths, the differential reflectivity and the estimated attenuation coefficients, it is shown that: supercooled drops and dry ice particles probably co-existed above the melting level in regions of updraft, that water-coated partially melted ice particles probably contributed to high attenuation below the melting level, and that the data are not readil~ explained in terms of a gamma function raindrop size distribution.

Tian, Lin↗

Ulysses Observations of Alfven and Magnetosonic Waves at High Latitude

Ulysses observations provide a unique opportunity to study diverse problems related to Alfven and magnetosonic waves. The large amplitude of the Alfven waves influences the distribution functions of the spiral angle, the azimuthal field component and, possibly, the radial component such that their averages are not equal to their most probable values.

Alfven and Magnetosonic Waves Ulysses↗

Probabilistic #D data fusion for multiresolution surface generation

In this paper we present an algorithm for adaptive resolution integration of 3D data collected from multiple distributed sensors. The input to the algorithm is a set of 3D surface points and associated sensor models. Using a probabilistic rule, a surface probability function is generated that represents the probability that a particular volume of space contains the surface. The surface probability function is represented using an octree data structure; regions of space with samples of large conariance are stored at a coarser level than regions of space containing samples with smaller covariance. The algorithm outputs an adaptive resolution surface generated by connecting points that lie on the ridge of surface probability with triangles scaled to match the local discretization of space given by the algorithm, we present results from 3D data generated by scanning lidar and structure from motion.

3D data fusion multiresolution surface generation ↗

Time-Dependent Satellite Explosion Probabilities for Long-Term Orbital Debris Environment Modeling

On-orbit accidental explosions are a significant contributor to the growth of the orbital debris population. Certain types of satellites have been seen to exhibit different behaviors and timelines of explosions. Recent assessments of on-orbit explosions for three categories of satellites – Russian Sistema Obespecheniya Zapuska (SOZ, Proton 4th stage attitude and ullage motors) units, spacecraft, and rocket bodies – suggest that on-orbit explosions can be modeled using a continuous, time-dependent probability of explosion. This paper discusses the methodology for developing a time-dependent probability of explosion as a function of the satellite’s orbital lifetime based on historical explosions. The SOZ units are found to be best modeled by a modified Gaussian probability distribution, with the peak probability of explosion occurring around 10.4 years on-orbit. Spacecraft and rocket bodies both exhibit exponentially decaying explosion probabilities, with rocket bodies showing fast-, medium-, and slow-time modes of decay. Total cumulative probabilities of explosion are approximately 57% for SOZ units, 4% for spacecraft, and 2% for rocket bodies. Examples of implementation in a simulation of the orbital debris environment using NASA's long-term evolutionary model are given, showing the overall explosion behavior over two centuries is significantly different from that using a previously implemented constant-probability type-dependent explosion rate model and provides a better representation of the historical explosion record.

Alyssa P Manis↗

Granulometric characteristics of lunar surface material from the Sea of Fertility

The particle size distributions in the 1-1000 micrometer range along the length of the core of lunar surface material returned by Luna 16 were recorded by electrical impulse as well as sieve methods. The measurements are represented in the form of cumulative functions of the logarithm of size versus the logarithm of particle number, and also as the logarithm of size versus particle mass on a probability scale. The former functions at all depths consist of the super-positioning of two straight lines with slopes from 2.10 to 4.05. The second functions are near linear, which together with the closeness of the calculated asymmetries of the distribution to zero and the nearness of the calculated excess of the distributions to unity indicate the closeness of the recorded distributions to the logarithmically normal law. This agrees with the assumption that regolith particles were formed in a process of intensive mechanical grinding.

Stakheyev, Y. I.↗

A probabilistic fracture mechanics approach for structural reliability assessment of space flight systems

A probabilistic fracture mechanics approach for predicting the failure life distribution due to subcritical crack growth is presented. A state-of-the-art crack propagation method is used in a Monte Carlo simulation to generate a distribution of failure lives. The crack growth failure model expresses failure life as a function of stochastic parameters including environment, loads, material properties, geometry, and model specification errors. A stochastic crack growth rate model that considers the uncertainties due to scatter in the data and mode misspecification is proposed. The rationale for choosing a particular type of probability distribution for each stochastic input parameter and for specifying the distribution parameters is presented. The approach is demonstrated through a probabilistic crack growth failure analysis of a welded tube in the Space Shuttle Main Engine. A discussion of the results from this application of the methodology is given.

Sutharshana, S.↗