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At least 1,063 records · Page 59

MO-DE-207A-02: A Feature-Preserving Image Reconstruction Method for Improved Pancreaticlesion Classification in Diagnostic CT Imaging

Purpose: To develop a feature-preserving model based image reconstruction (MBIR) method that improves performance in pancreatic lesion classification at equal or reduced radiation dose. Methods: A set of pancreatic lesion models was created with both benign and premalignant lesion types. These two classes of lesions are distinguished by their fine internal structures; their delineation is therefore crucial to the task of pancreatic lesion classification. To reduce image noise while preserving the features of the lesions, we developed a MBIR method with curvature-based regularization. The novel regularization encourages formation of smooth surfaces that model both the exterior shape and the internal features of pancreatic lesions. Given that the curvature depends on the unknown image, image reconstruction or denoising becomes a non-convex optimization problem; to address this issue an iterative-reweighting scheme was used to calculate and update the curvature using the image from the previous iteration. Evaluation was carried out with insertion of the lesion models into the pancreas of a patient CT image. Results: Visual inspection was used to compare conventional TV regularization with our curvature-based regularization. Several penalty-strengths were considered for TV regularization, all of which resulted in erasing portions of the septation (thin partition) in a premalignant lesion. At matched noise variance (50% noise reduction in the patient stomach region), the connectivity of the septation was well preserved using the proposed curvature-based method. Conclusion: The curvature-based regularization is able to reduce image noise while simultaneously preserving the lesion features. This method could potentially improve task performance for pancreatic lesion classification at equal or reduced radiation dose. The result is of high significance for longitudinal surveillance studies of patients with pancreatic cysts, which may develop into pancreatic cancer. The Senior Author receives financial support from Siemens GmbH Healthcare.

60 APPLIED LIFE SCIENCES↗

Latent Variable Network Modeling

lvnm Is a library for fitting latent variable network models within the R programming language. The code focuses on the Stochastic Block Model, Weighted Stochastic Block Model, and Dynamic Stochastic Block Model. Features include simulation methods, estimation methods, diagnostic plots and anomaly detection routines for network data.

Dabbs, Beau↗

Enclosed Sydney Swirl Burner Experimental Data Set - Release 1.0

This submission includes a comprehensive data set for the NETL Enclosed Sydney Swirl Burner, generated between 2012 and 2014. The data set includes global parametric data and advanced diagnostic data for (3) flames of interest to CFD model validation. The submission includes a companion summary document describing the data and associated references.

Diagnostics↗

COVID-19 Testing R&D (Final Report)

Eleven Labs within the US Department of Energy (DOE), National Virtual Biotechnology Laboratory (NVBL), came together as a team to address significant R&D gaps in COVID-19 testing. Beginning in March 2020, the NVBL COVID Testing Team developed an R&D agenda, worked with DOE and other agencies to set priorities, and collaborated to deliver timely results. Priority was given to quick implementation as well as development of novel capabilities for immediate and evolving pandemic needs without placing additional burden on operational performers. Priority elements capitalized on DOE National Laboratory strengths and expertise. The Team delivered: testing and evaluation that enabled decisions on testing options, forwardleaning approaches to prepare for future scale-up needs, and models and experiments that supported prioritization of diagnostic and therapeutic candidates.

60 APPLIED LIFE SCIENCES↗

Non-Equilibrium Plasma Interactions with Biomaterials, Biological Solutions and Tissues

Cold atmospheric pressure plasma discharges offer an abundant source of reactive oxygen and nitrogen species (RONS) at room temperature enabling unique interactions with biomaterials, biological solutions and tissues. These interactions particularly with living matter are presently an important intellectual frontier in plasma science with promising potential applications ranging from human health care to advanced biomaterial processing. Exciting case studies have been reported that illustrate the huge potential of cold atmospheric plasma technology in wound healing and cancer treatment. The interaction of plasma with conducting and dielectric biomaterials such as tissue strongly influences the plasma properties. In turn this changes the impact of the plasma on the biomaterial. Particularly in the case of living matter, liquid based solutions are ubiquitous which complicates interfacial processes. The lack of insight into the underlying mechanisms of the interaction of plasma with wounds and tumors is currently a bottleneck for the further development of the technology and gives rise to many interesting scientific questions. This project was focused on plasma properties and kinetics during plasma-biomaterial interactions. Both DC pulsed and RF driven atmospheric pressure plasma jets, extensively used by the plasma community were studied. The bio-interfaces included hydrogel as a tissue model, (saline) solutions, bacteria and virus. Plasma diagnostics used include Thomson scattering, Rayleigh scattering, Raman scattering, (two-photon absorption) laser induced fluorescence, optical emission spectroscopy, absorption spectroscopy, molecular beam mass spectrometry and fast imaging allowing to determine electron densities and temperatures, ionic species, reactive species including radicals, gas temperatures, gas composition, electric fields and solution components transferred to the gas phase.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Millisecond Pulsar Origin of the Galactic Center Excess and Extended Gamma-Ray Emission from Andromeda: A Closer Look

A new measurement of a spatially extended gamma-ray signal from the center of the Andromeda galaxy (M31) has recently been published by the Fermi -LAT collaboration, reporting that the emission broadly resembles the so-called Galactic center excess (GCE) of the Milky Way (MW). The weight of the evidence is steadily accumulating on a millisecond pulsar (MSPs) origin for the GCE. These elements prompt us to compare these observations with what is, perhaps, the simplest model for an MSP population, which is solely obtained by rescaling of the MSP luminosity function that is determined in the local MW disk via the respective stellar mass of the systems. Remarkably, we find that without free fitting parameters, this model can account for both the energetics and the morphology of the GCE within uncertainties. For M31, the estimated luminosity due to primordial MSPs is expected to only contribute about a quarter of the detected emission, although a stronger contribution cannot be excluded given the large uncertainties. If correct, the model predicts that the M31 disk emission due to MSPs is not far below the present upper bound. We also discuss additional refinements of this simple model. Using the correlation between globular cluster gamma-ray luminosity and stellar encounter rate, we gauge the dynamical MSP formation in the bulge. This component is expected to contribute to the GCE only at a level of ≲5%, it could affect the signal's morphology. In conclusion, we also comment on the limitations of our model and on future perspectives for improved diagnostics.

79 ASTRONOMY AND ASTROPHYSICS↗

Evaluating seasonal and regional distribution of snowfall in regional climate model simulations in the Arctic

In this study, we investigate how the regional climate model HIRHAM5 reproduces the spatial and temporal distribution of Arctic snowfall when compared to CloudSat satellite observations during the examined period of 2007–2010. For this purpose, both approaches, i.e., the assessments of the surface snowfall rate (observation-to-model) and the radar reflectivity factor profiles (model-to-observation), are carried out considering spatial and temporal sampling differences. The HIRHAM5 model, which is constrained in its synoptic representation by nudging to ERA-Interim, represents the snowfall in the Arctic region well in comparison to CloudSat products. The spatial distribution of the snowfall patterns is similar in both identifying the southeastern coast of Greenland and the North Atlantic corridor as regions gaining more than twice as much snowfall as the Arctic average, defined here for latitudes between 66 and 81°N. Excellent agreement (difference less than 1%) in the Arctic-averaged annual snowfall rate between HIRHAM5 and CloudSat is found, whereas ERA-Interim reanalysis shows an underestimation of 45% and significant deficits in the representation of the snowfall rate distribution. From the spatial analysis, it can be seen that the largest differences in the mean annual snowfall rates are an overestimation near the coastlines of Greenland and other regions with large orographic variations as well as an underestimation in the northern North Atlantic Ocean. To a large extent, the differences can be explained by clutter contamination, blind zone or higher resolution of CloudSat measurements, but clearly HIRHAM5 overestimates the orographic-driven precipitation. The underestimation of HIRHAM5 within the North Atlantic corridor south of Svalbard is likely connected to a poor description of the marine cold air outbreaks which could be identified by separating snowfall into different circulation weather type regimes. By simulating the radar reflectivity factor profiles from HIRHAM5 utilizing the Passive and Active Microwave TRAnsfer (PAMTRA) forward-modeling operator, the contribution of individual hydrometeor types can be assessed. Looking at a latitude band at 72–73°N, snow can be identified as the hydrometeor type dominating radar reflectivity factor values across all seasons. The largest differences between the observed and simulated reflectivity factor values are related to the contribution of cloud ice particles, which is underestimated in the model, most likely due to the small sizes of the particles. The model-to-observation approach offers a promising diagnostic when improving cloud schemes, as illustrated by comparison of different schemes available for HIRHAM5.

54 ENVIRONMENTAL SCIENCES↗

High-beta effects and anomalous diffusion in plasmas expanding into magnetic fields

A metallic laser-produced plasma is allowed to expand transversely into an applied magnetic field, under conditions where the typical ion cyclotron radius is much larger, and the electron cyclotron radius much smaller, than the experimental dimensions. A stationary background plasma may also be present. Initially, the flow energy density exceeds (B squared/8 times pi), where B is the ambient magnetic field. Magnetic coil probes, Langmuir probes, and microwave diagnostics are used to study the plasma-field interaction. Field compression at the leading edge and field exclusion within the expanding plasma are seen. The diagnostic measurements and comparison with a theoretical model demonstrate plasma turbulence and anomalously high diffusion of field into the expanding plasma.

Koopman, D. W.↗

Comptonization in supercritical winds. I - Spectral evolution. II - Dynamics and observational diagnostics

The physics governing spectral evolution in steady, fully ionized, radiatively driven winds from compact objects is examined. A largely analytic theory is developed to describe the effects of diffusion, adiabatic cooling, and repeated Compton scattering on the emergent radiation spectrum. Analytic forms for the wind temperature profile are derived, and spectral solutions obtained by considering a modified, time-independent Kompaneets equation are presented subject to a variety of initial conditions. A probabilistic formalism which describes the effect of diffusion photons travelling beyond the trapping radius is developed to allow the calculation of spectra observed at infinity. The second paper focuses on the dynamics of supercritical winds and on observational diagnostics which may be used to constrain model parameters in the contexts of specific astrophysical systems, including X-ray burst sources and mass-losing quasars.

Becker, Peter A.↗

Diagnosis and sensor validation through knowledge of structure and function

The liquid oxygen expert system 'LES' is proposed as the first capable of diagnostic reasoning from sensor data, using model-based knowledge of structure and function to find the expected state of all system objects, including sensors. The approach is generally algorithmic rather than heuristic, and represents uncertainties as sets of possibilities. Functional relationships are inverted to determine hypothetical values for potentially faulty objects, and may include conditional functions not normally considered to have inverses.

Scarl, Ethan A.↗

Potential vorticity and layer thickness variations in the flow around Jupiter's Great Red Spot and White Oval BC

Using Voyager images, layer thickness variations in the flow around Jupiter's Great Red Spot (GRS) and White Oval BC were investigated by treating potential vorticity as a conserved tracer. Fluid trajectories around the GRS and the White Oval BC were calculated assuming the flow to be frictionless, adiabatic, hydrostatic, and steady in the reference frame of the vortex. The data obtained constitute a useful diagnostic which will help to differentiate between models of Jovian vortices. Implications of the observations were studied in the context of a one-layer quasi-geostrophic model in which a thin upper weather layer, which contains the vortex, is supported hydrostatically by a much deeper lower layer.

Dowling, Timothy E.↗

Graph-based real-time fault diagnostics

A real-time fault detection and diagnosis capability is absolutely crucial in the design of large-scale space systems. Some of the existing AI-based fault diagnostic techniques like expert systems and qualitative modelling are frequently ill-suited for this purpose. Expert systems are often inadequately structured, difficult to validate and suffer from knowledge acquisition bottlenecks. Qualitative modelling techniques sometimes generate a large number of failure source alternatives, thus hampering speedy diagnosis. In this paper we present a graph-based technique which is well suited for real-time fault diagnosis, structured knowledge representation and acquisition and testing and validation. A Hierarchical Fault Model of the system to be diagnosed is developed. At each level of hierarchy, there exist fault propagation digraphs denoting causal relations between failure modes of subsystems. The edges of such a digraph are weighted with fault propagation time intervals. Efficient and restartable graph algorithms are used for on-line speedy identification of failure source components.

Padalkar, S.↗

Rocket Ejector Studies for Application to RBCC Engines: An Integrated Experimental/CFD Approach

Recent interest in low cost, reliable access to space has generated increased interest in advanced technology approaches to space transportation systems. A key to the success of such programs lies in the development of advanced propulsion systems capable of achieving the performance and operations goals required for the next generation of space vehicles. One extremely promising approach involves the combination of rocket and air- breathing engines into a rocket-based combined-cycle engine (RBCC). A key element of that engine is the rocket ejector which is utilized in the zero to Mach two operating regime. Studies of RBCC engine concepts are not new and studies dating back thirty years are well documented in the literature. However, studies focused on the rocket ejector mode of the RBCC cycle are lacking. The present investigation utilizes an integrated experimental and computation fluid dynamics (CFD) approach to examine critical rocket ejector performance issues. In particular, the development of a predictive methodology capable of performance prediction is a key objective in order to analyze thermal choking and its control, primary/secondary pressure matching considerations, and effects of nozzle expansion ratio. To achieve this objective, the present study emphasizes obtaining new data using advanced optical diagnostics such as Raman spectroscopy and CFD techniques to investigate mixing in the rocket ejector mode. A new research facility for the study of the rocket ejector mode is described along with the diagnostic approaches to be used. The CFD modeling approach is also described along with preliminary CFD predictions obtained to date.

Pal, S.↗

Tumor-Initiating Cells and Methods of Use

Provided herein are an isolated or enriched population of tumor initiating cells derived from normal cells, cells susceptible to neoplasia, or neoplastic cells. Methods of use of the cells for screening for anti-hyperproliferative agents, and use of the cells for animal models of hyperproliferative disorders including metastatic cancer, diagnostic methods, and therapeutic methods are provided.

Hlatky, Lynn↗

The Pathway to a Safe and Effective Spaceflight Medication Formulary: Expert Review Panel Recommendations

Exploration spaceflight poses several challenges to the provision of a comprehensive medication formulary. This formulary must accommodate the size and space limitations of the spacecraft, while addressing individual medication needs and preferences of the crew, consequences of a degrading inventory over time, the inability to resupply used or expired medications, and the need to forecast the best possible medication candidates to treat conditions that may occur. The Exploration Medical Capability (ExMC) Element's Pharmacy Project Team has developed a research plan (RP) that is focused on evidence-based models and theories as well as new diagnostic tools, treatments, or preventive measures aimed to ensure an available, safe, and effective pharmacy sufficient to manage potential medical threats during exploration spaceflight. Here, we will discuss the ways in which the ExMC Pharmacy Project Team pursued expert evaluation and guidance, and incorporated acquired insight into an achievable research pathway, reflected in the revised RP.

Daniels, V. R.↗

The HadGEM3-GA7.1 radiative kernel: the importance of a well-resolved stratosphere

We present top-of-atmosphere and surface radiative kernels based on the atmospheric component (GA7.1) of the HadGEM3 general circulation model developed by the UK Met Office. We show that the utility of radiative kernels for forcing adjustments in idealised CO2 perturbation experiments is greatest where there is sufficiently high resolution in the stratosphere in both the target climate model and the radiative kernel. This is because stratospheric cooling to a CO2 perturbation continues to increase with height, and low-resolution or low-top kernels or climate model output are unable to fully resolve the full stratospheric temperature adjustment. In the sixth phase of the Coupled Model Intercomparison Project (CMIP6), standard atmospheric model data are available up to 1 hPa on 19 pressure levels, which is a substantial advantage compared to CMIP5. We show in the IPSL-CM6A-LR model where a full set of climate diagnostics are available that the HadGEM3-GA7.1 kernel exhibits linear behaviour and the residual error term is small, as well as from a survey of kernels available in the literature that in general low-top radiative kernels underestimate the stratospheric temperature response. The HadGEM3-GA7.1 radiative kernels are available at https://doi.org/10.5281/zenodo.3594673 (Smith, 2019).

radiative kernels↗