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NASA NTRS2016

Source Data Impacts on Epistemic Uncertainty for Launch Vehicle Fault Tree Models

Launch vehicle systems are designed and developed using both heritage and new hardware. Design modifications to the heritage hardware to fit new functional system requirements can impact the applicability of heritage reliability data. Risk estimates for newly designed systems must be developed from generic data sources such as commercially available reliability databases using reliability prediction methodologies, such as those addressed in MIL-HDBK-217F. Failure estimates must be converted from the generic environment to the specific operating environment of the system in which it is used. In addition, some qualification of applicability for the data source to the current system should be made. Characterizing data applicability under these circumstances is crucial to developing model estimations that support confident decisions on design changes and trade studies. This paper will demonstrate a data-source applicability classification method for suggesting epistemic component uncertainty to a target vehicle based on the source and operating environment of the originating data. The source applicability is determined using heuristic guidelines while translation of operating environments is accomplished by applying statistical methods to MIL-HDK-217F tables. The paper will provide one example for assigning environmental factors uncertainty when translating between operating environments for the microelectronic part-type components. The heuristic guidelines will be followed by uncertainty-importance routines to assess the need for more applicable data to reduce model uncertainty.

Al Hassan, Mohammad↗

DOE OSTI2017

Stereotactic Body Radiation Therapy and the Influence of Chemotherapy on Overall Survival for Large (≥5 Centimeter) Non-Small Cell Lung Cancer

Purpose: Stereotactic body radiation therapy (SBRT) for ≥5 cm lesions is poorly defined, largely owing to the low sample sizes in existing studies. The present analysis examined the SBRT outcomes and assessed the effect of chemotherapy in this population. Methods and Materials: The National Cancer Data Base was queried for primary non-small cell lung cancer ≥5 cm treated with SBRT (≤10 fractions). Patient, tumor, and treatment parameters were extracted. The primary outcome was overall survival (OS). Statistical methods involved Kaplan-Meier analysis and multivariable Cox proportional hazards modeling. Results: From 2004 to 2012, data from 201 patients were analyzed. The median follow-up was 41.1 months. The median tumor size was 5.5 cm (interquartile range 5.0-6.0), with cT2a, cT2b, and cT3 disease in 24.9%, 53.2%, and 21.9%, respectively. The median total SBRT dose and fractionation was 50 Gy in 4 fractions, and 92.5% of the patients underwent SBRT with ≤5 fractions. The median OS was 25.1 months. Of the 201 patients, 15% received chemotherapy. The receipt of chemotherapy was associated with longer OS (median 30.6 vs 23.4 months; P=.027). On multivariable analysis, worse OS was seen with increasing age (hazard ratio [HR] 1.03; P=.012), poorly differentiated tumors (HR 2.06; P=.049), and T3 classification (HR 2.13; P=.005). On multivariable analysis, chemotherapy remained independently associated with improved OS (HR 0.57; P=.039). Conclusions: SBRT has utility in the setting of tumors ≥5 cm, with chemotherapy associated with improved OS in this subset. These hypothesis-generating data now raise the necessity of performing prospective analyses to determine whether chemotherapy confers outcome benefits after SBRT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

NASA NTRS1992

Statistical Approach To Extraction Of Texture In SAR

Improved statistical method of extraction of textural features in synthetic-aperture-radar (SAR) images takes account of effects of scheme used to sample raw SAR data, system noise, resolution of radar equipment, and speckle. Treatment of speckle incorporated into overall statistical treatment of speckle, system noise, and natural variations in texture. One computes speckle auto-correlation function from system transfer function that expresses effect of radar aperature and incorporates range and azimuth resolutions.

Rignot, Eric J.↗

DOE OSTI2021

Grid-based minimization at scale: Feldman-Cousins corrections for light sterile neutrino search

High Energy Physics (HEP) experiments generally employ sophisticated statistical methods to present results in searches of new physics. In the problem of searching for sterile neutrinos, likelihood ratio tests are applied to short-baseline neutrino oscillation experiments to construct confidence intervals for the parameters of interest. The test statistics of the form Δχ2 is often used to form the confidence intervals, however, this approach can lead to statistical inaccuracies due to the small signal rate in the region-of-interest. In this paper, we present a computational model for the computationally expensive Feldman-Cousins corrections to construct a statistically accurate confidence interval for neutrino oscillation analysis. The program performs a grid-based minimization over oscillation parameters and is written in C++. Our algorithms make use of vectorization through Eigen3, yielding a single-core speed-up of 350 compared to the original implementation, and achieve MPI data parallelism by employing DIY. We demonstrate the strong scaling of the application at High-Performance Computing (HPC) sites. We utilize HDF5 along with HighFive to write the results of the calculation to file.

Wospakrik, Marianette↗

DOE OSTI2017

Creating a Face from a DNA Sample

The idea of creating a recognizable face from a sample of DNA is moving closer to reality as Oak Ridge National Laboratory (ORNL) researchers employ a novel statistical representation of the face and a genome-wide association study (GWAS) to relate facial characteristics to genetic mutations. The reduction in cost of DNA sequencing and genotyping technology is leading to the availability of massive datasets of human genome sequences and human genotypes representing mutational variation among people. These large-scale data provide for the first time the potential to correlate an individual’s specific genetic code with their physical appearance. Using a specialized statistical method for representing the entire 3D shape of faces, ORNL researchers performed a GWAS to discover associations between genetic mutations and aspects of face shape. Data from 3,556 subjects resulted in the discovery of a very large set of statistically significant associations, which is strong evidence for the viability of predicting faces from DNA.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Quantitative methods and modeling to assess COVID–19–interrupted in vivo pharmacokinetic bioequivalence studies with two reference batches

The coronavirus disease 2019 (COVID-19) has presented unprecedented challenges to the generic drug development, including interruptions in bioequivalence (BE) studies. Per guidance published by the US Food and Drug Administration (FDA) during the COVID-19 public health emergency, any protocol changes or alternative statistical analysis plan for COVID-19-interrupted BE study should be accompanied with adequate justifications and not lead to biased equivalence determination. In this study, we used a modeling and simulation approach to assess the potential impact of study outcomes when two different batches of a Reference Standard (RS) were to be used in an in vivo pharmacokinetic BE study due to the RS expiration during the COVID-19 pandemic. Simulations were performed with hypothetical drugs under two scenarios: (1) uninterrupted study using a single batch of an RS, and (2) interrupted study using two batches of an RS. The acceptability of BE outcomes was evaluated by comparing the results obtained from interrupted studies with those from uninterrupted studies. The simulation results demonstrated that using a conventional statistical approach to evaluate BE for COVID-19-interrupted studies may be acceptable based on the pooled data from two batches. An alternative statistical method which includes a “batch” effect to the mixed effects model may be used when a significant “batch” effect was found in interrupted four-way crossover studies. However, such alternative method is not applicable for interrupted two-way crossover studies. Overall, the simulated scenarios are only for demonstration purpose, the acceptability of BE outcomes for the COVID19-interrupted studies could be case-specific.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

coloring v.1.0

SAND2024-02435O The software coloring allows applications written in the C++ language to generate publication-quality 2D plots. Its functionality is similar to Microsoft Excel's chart functionality or the Python language's matplotlib package. The value of coloring is that it is written purely in C++ and thus can be compiled on systems where Python is not available and linked into high performance computing software. For drawing shapes onto an image, coloring uses the mathematical definition of quadratic Bezier splines and uses Newton's method to search for the closest point on a spline to a given query point. This is then used to do accurate sub-pixel sampling to get clean, non-pixelated images. For working with the actual plot data, coloring has basic statistical methods such as finding maxima and minima as well as axis scaling such as logarithms. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Ibanez, Daniel↗

NASA NTRS1981

Estimation of trends

The application of statistical methods to recorded ozone measurements. The effects of a long term depletion of ozone at magnitudes predicted by the NAS is harmful to most forms of life. Empirical prewhitening filters the derivation of which is independent of the underlying physical mechanisms were analyzed. Statistical analysis performs a checks and balances effort. Time series filters variations into systematic and random parts, errors are uncorrelated, and significant phase lag dependencies are identified. The use of time series modeling to enhance the capability of detecting trends is discussed.

Source record↗

NASA NTRS1982

On the detection of other planetary systems by astrometric techniques

A quantitative method for astrometrically detecting perturbations induced in a star's motion by the presence of a planetary object is described. A periodogram is defined, wherein signals observed from a star show exactly periodic variations, which can be extracted from observational data using purely statistical methods. A detection threshold is defined for the frequency of occurrence of some detectable signal, e.g., the Nyquist frequency. Possible effects of a stellar orbital eccentricity and multiple companions are discussed, noting that assumption of a circular orbit assures the spectral purity of the signal described. The periodogram technique was applied to 12 yr of astrometric data from the U.S. Naval Observatory for three stars with low mass stellar companions. Periodic perturbations were confirmed. A comparison of the accuracy of different astrometric systems shows that the detection accuracy of a system is determined by the measurement accuracy and the number of observations, although the detection efficiency can be maximized by minimizing the number of data points for the case when observational errors are proportional to the square root of the number of data points. It is suggested that a space-based astrometric telescope is best suited to take advantage of the method.

Black, D. C.↗

DOE OSTI2026

Emerging anomaly detection techniques for electronic health records: A survey

Background Anomaly detection in electronic health records (EHRs) is a cornerstone of biomedical informatics, with direct implications for patient safety, clinical decision-making, and the prevention of healthcare fraud. Once guided primarily by simple rule-based methods, the field has advanced rapidly, driven by increased computing power, richer and more detailed health data, and the rise of machine learning and deep learning techniques. The objective of this paper is to provide a comprehensive overview of modern approaches to detecting anomalies in EHRs, outlining their strengths, limitations, and relevance to key healthcare challenges. We review traditional statistical methods alongside newer ML- and DL-based strategies and hybrid models, with particular attention to how these techniques support transparency and build clinical trust. Methods This paper presents a thorough and critical survey through systematic review (PRISMA-based) of the latest anomaly detection strategies in time-sequence data domains within electronic health record systems. Results We explore a broad spectrum of methodologies, including statistical models, supervised and unsupervised learning approaches, hybrid frameworks, and state-of-the-art ML-based techniques that collectively advance the precision and scalability of detecting anomalies in complex clinical datasets. In addition to mapping current capabilities, we address the enduring challenges that hinder widespread implementation and provide a forward-looking perspective on the future of anomaly detection in the data-rich landscape of modern healthcare. Summary The advancement in AI-based approaches is reported along with the basic principles of the individual approaches and their applicability. The increased availability of high-quality data, advancements in DL approaches, and enhanced computation power are leading to more frequent adaptation of DL-based approaches. Emerging DL-based approaches that have been adapted in other domains or recently applied in the EHR domain are also discussed in detail. Although DL-based approaches can improve model predictions by incorporating comorbidities, their application is limited in low-frequency data domains (e.g., when the total available data remains in the single digits). Therefore, the user must carefully consider the application based on data availability.

Anomaly detection↗

NASA NTRS1989

Periodicity in extinction and the problem of catastrophism in the history of life

The hypothesis that extinction events have recurred periodically over the last quarter billion years is greatly strengthened by new data on the stratigraphic ranges of marine animal genera. In the interval from the Permian to Recent, these data encompass some 13,000 generic extinctions, providing a more sensitive indicator of species-level extinctions than previously used familial data. Extinction time series computed from the generic data display nine strong peaks that are nearly uniformly spaced at 26 Ma intervals over the last 270 Ma. Most of these peaks correspond to extinction events recognized in more detailed, if limited, biostratigraphic studies. These new data weaken or negate most arguments against periodicity, which have involved criticisms of the taxonomic data base, sampling intervals, chronometric time scales, and statistical methods used in previous analyses. The criticisms are reviewed in some detail and various new calculations and simulations, including one assessing the effects of paraphyletic taxa, are presented. Although the new data strengthen the case for periodicity, they offer little new insight into the deriving mechanism behind the pattern. However, they do suggest that many of the periodic events may not have been catastrophic, occurring instead over several stratigraphic stages or substages.

NASA Discipline Number 52-40↗

DOE OSTI2015

Applying compressive sensing to TEM video: A substantial frame rate increase on any camera

One of the main limitations of imaging at high spatial and temporal resolution during in-situ transmission electron microscopy (TEM) experiments is the frame rate of the camera being used to image the dynamic process. While the recent development of direct detectors has provided the hardware to achieve frame rates approaching 0.1 ms, the cameras are expensive and must replace existing detectors. In this paper, we examine the use of coded aperture compressive sensing (CS) methods to increase the frame rate of any camera with simple, low-cost hardware modifications. The coded aperture approach allows multiple sub-frames to be coded and integrated into a single camera frame during the acquisition process, and then extracted upon readout using statistical CS inversion. Here we describe the background of CS and statistical methods in depth and simulate the frame rates and efficiencies for in-situ TEM experiments. Depending on the resolution and signal/noise of the image, it should be possible to increase the speed of any camera by more than an order of magnitude using this approach.

36 MATERIALS SCIENCE↗

NASA NTRS1982

Contingency in visual scanning of cockpit traffic displays

A statistical method to identify reliable, repetitive scanning patterns in the positions of visual fixations has been developed and applied to data from 8 airline pilots who monitored cockpit displays of traffic information (CDTI). Their fixational transition patterns between points of interest on the display showed deterministic, statistical dependencies generally associated with symbols predicting future aircraft position. These dependencies constitute deviations from stratified random sampling of the visual information on the display, confirm the importance of future aircraft position information for the use of CDTI, and provide objective support for the existence of 'scanpaths' in visual fixation patterns.

Ellis, S. R.↗

NASA NTRS1977

Characteristics of fragments

Methods used to estimate initial fragment velocities from various types of accidental explosions, geometry of vessel, or explosion source are reported. In addition, fragmentation ranges and impact conditions, using initial velocities as inputs, are discussed. Several classes of accidental explosions and fragment mass distribution predicted by statistical methods are included. Computer program techniques are summarized.

Source record↗

DOE OSTI2019

Tumor-Infiltrating Lymphocytes in a Contemporary Cohort of Women with Ductal Carcinoma In Situ (DCIS)

Background: Growing evidence suggests that the tumor immune microenvironment influences breast cancer development and prognosis. Density of tumor-infiltrating lymphocytes (TILs) within invasive breast cancer is correlated with response to therapy, especially in triple-negative disease. The clinical relevance and outcomes of TILs within ductal carcinoma in situ (DCIS) are less understood. Methods: Our institutional database of 668 patients with pure DCIS from 2010 to 2018 was queried. TILs were evaluated by International TILs Working Group guidelines. Percentage of TILs was assessed from the densest focus (hotspot) in one high-power field of stroma touching the basement membrane. Statistical methods included cluster analyses (to define sparse versus dense TILs), logistic, and Cox regression models. Results: Sixty-nine patients with DCIS and TILs were evaluated, of whom 54 (78%) were treated by breast-conserving surgery. Thirteen (19%) patients had ipsilateral recurrence. Each recurrence (n = 13) was matched to four controls (n = 56) based on date of surgery. Median follow-up was 6.7 years. TILs were defined as sparse (< 45%) or dense (≥ 45%). Dense TILs were associated with younger age (p = 0.045), larger tumor size (p < 0.001), high nuclear grade (p = 0.010), comedo histology (p = 0.033), necrosis (p = 0.027), estrogen receptor (ER) negativity (p = 0.037), and ipsilateral recurrence (p = 0.001). Nine patients with dense TILs had mean time to recurrence of 73.5 months compared with four patients with sparse TILs with mean time to recurrence of 97.9 months (p = 0.003). Conclusions: Dense TILs were significantly associated with age, tumor size, nuclear grade, comedo histology, necrosis, and ER status and was a significant predictor of recurrence in patients with pure DCIS.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

NASA NTRSDate not supplied

Continuous Habitable Zones: Pairing a GCM and Bayesian Framework to Predict Habitable Zone Evolution

In the near-future, new space telescopes like JWST, LUVOIR, and HabEx will begin attempting to explore the properties of atmospheres of potentially habitable planets. This will require a significant amount of time and resources for even a single planet, which makes it essential to prioritize observations by those most-likely to have detectable life. Here we present a statistical method to estimate the probabilities that specific exoplanets have been continuously in the habitable zone of their host stars for more than 2 billion years, the approximate time it took life on Earth to significantly increase the oxygen content of the atmosphere. We introduce the use of statistics of an ensemble of 3D planetary general circulation models to estimate these probabilities, replacing prior 1D model estimates.

habitable planets↗

NASA NTRSDate not supplied

Pairing a GCM and Bayesian Framework to Predict Habitable Zone Evolution

habitable planets↗

DOE OSTI2016

High-Resolution, Non-Invasive Imaging of Upper Vocal Tract Articulators Compatible with Human Brain Recordings

A complete neurobiological understanding of speech motor control requires determination of the relationship between simultaneously recorded neural activity and the kinematics of the lips, jaw, tongue, and larynx. Many speech articulators are internal to the vocal tract, and therefore simultaneously tracking the kinematics of all articulators is nontrivial-especially in the context of human electrophysiology recordings. Here, we describe a noninvasive, multi-modal imaging system to monitor vocal tract kinematics, demonstrate this system in six speakers during production of nine American English vowels, and provide new analysis of such data. Classification and regression analysis revealed considerable variability in the articulator-to-acoustic relationship across speakers. Non-negative matrix factorization extracted basis sets capturing vocal tract shapes allowing for higher vowel classification accuracy than traditional methods. Statistical speech synthesis generated speech from vocal tract measurements, and we demonstrate perceptual identification. We demonstrate the capacity to predict lip kinematics from ventral sensorimotor cortical activity. These results demonstrate a multi-modal system to non-invasively monitor articulator kinematics during speech production, describe novel analytic methods for relating kinematic data to speech acoustics, and provide the first decoding of speech kinematics from electrocorticography. These advances will be critical for understanding the cortical basis of speech production and the creation of vocal prosthetics.

60 APPLIED LIFE SCIENCES↗