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DOE OSTI2016

SU-F-R-22: Malignancy Classification for Small Pulmonary Nodules with Radiomics and Logistic Regression

Purpose: We conducted a retrospective study of Radiomics research for classifying malignancy of small pulmonary nodules. A machine learning algorithm of logistic regression and open research platform of Radiomics, IBEX (Imaging Biomarker Explorer), were used to evaluate the classification accuracy. Methods: The training set included 100 CT image series from cancer patients with small pulmonary nodules where the average diameter is 1.10 cm. These patients registered at Chang Gung Memorial Hospital and received a CT-guided operation of lung cancer lobectomy. The specimens were classified by experienced pathologists with a B (benign) or M (malignant). CT images with slice thickness of 0.625 mm were acquired from a GE BrightSpeed 16 scanner. The study was formally approved by our institutional internal review board. Nodules were delineated and 374 feature parameters were extracted from IBEX. We first used the t-test and p-value criteria to study which feature can differentiate between group B and M. Then we implemented a logistic regression algorithm to perform nodule malignancy classification. 10-fold cross-validation and the receiver operating characteristic curve (ROC) were used to evaluate the classification accuracy. Finally hierarchical clustering analysis, Spearman rank correlation coefficient, and clustering heat map were used to further study correlation characteristics among different features. Results: 238 features were found differentiable between group B and M based on whether their statistical p-values were less than 0.05. A forward search algorithm was used to select an optimal combination of features for the best classification and 9 features were identified. Our study found the best accuracy of classifying malignancy was 0.79±0.01 with the 10-fold cross-validation. The area under the ROC curve was 0.81±0.02. Conclusion: Benign nodules may be treated as a malignant tumor in low-dose CT and patients may undergo unnecessary surgeries or treatments. Our study may help radiologists to differentiate nodule malignancy for low-dose CT.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Validating the galaxy and quasar catalog-level blinding scheme for the DESI 2024 analysis

In the era of precision cosmology, ensuring the integrity of data analysis through blinding techniques is paramount — a challenge particularly relevant for the Dark Energy Spectroscopic Instrument (DESI). DESI represents a monumental effort to map the cosmic web, with the goal to measure the redshifts of tens of millions of galaxies and quasars. Given the data volume and the impact of the findings, the potential for confirmation bias poses a significant challenge. To address this, we implement and validate a comprehensive blind analysis strategy for DESI Data Release 1 (DR1), tailored to the specific observables DESI is most sensitive to: Baryonic Acoustic Oscillations (BAO), Redshift-Space Distortion (RSD) and primordial non-Gaussianities (PNG). We carry out the blinding at the catalog level, implementing shifts in the redshifts of the observed galaxies to blind for BAO and RSD signals and weights to blind for PNG through a scale-dependent bias. We validate the blinding technique on mocks as well as on data by applying a second blinding layer to perform a series of sanity checks; the latter allows probing complexities in real data not captured in mocks. We find that the blinding strategy alters the data vector in a controlled way, and the BAO and RSD analysis choices are robust to blinding. The successful validation of the blinding strategy paves the way for the unblinded DESI DR1 analysis, alongside future blind analyses with DESI and other surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Network Models of Active Degradation Mechanisms and Pathways for Service Life Prediction of Indoor and Outdoor PV Modules

ct: PV service lifetime prediction (SLP) enables accurate calculation of levelized cost of energy (LCOE), which is crucial to rationalizing PV investment and installation. However, SLP is challeging since PV reliability in the field is affected by many combined factors, including various environmental stresses and module quality. In order to map out the active degradation mechanisms and pathways that best resemble real world conditions, we introduce the framework of a study protocol and use network models fitted to data, to enable analysis and SLP of complex PV systems with multiple active degradation mechanisms. The study protocol is the experimental design, including module variants and different exposure conditions, selection of evaluation methods, time-series data acquisition and training of network models to these data. We present SLP of minimodules in the lab and PV systems in the field. For lab SLP, minimodules with 8 variants based on manufacturer, architecture, and encapsulation were prepared and aged in modified damp heat with or without full spectrum light exposure. Stepwise I-V and Suns-Voc data acquisition tracks changes in electrical properties including Rs,IV, Isc,IV, Vmp,PIV providing insights into power loss of minimodules. Network structural equation modeling (netSEM) was utilized to construct degradation pathway models that identify active degradation mechanisms and predict power loss over time. For field SLP, datastreams of Pmp values and I-V curve datastreams of two types of modules installed in three distinctly different Köppen-Geiger climate zones for 9 years were acquired. With power loss modes corresponding to uniform current loss (ΔPIsc), recombination (ΔPVoc), series resistance (ΔPRs), and current mismatch (ΔPImis) determined, the performance loss rates (PLR) were determined using PVplr. We show how to establish a study protocol framework to ensure appropriate parametric variations and valid data collection from the variants of your complex systems. Then the data-driven netSEM model fitting provides a comprehensive mapping of multiple active degradation mechanisms, and accurate service life prediction.

network model, degradation, photovoltaic, solar↗

NASA NTRS2016

Preparation for Cassini Grand Finale - Validation of Saturn Ring Heating in TSS

Thermal analysis of spacecraft at Saturn have previously been restricted to three environmental heat fluxes: solar, Saturn planet IR, and Saturn planet albedo. Heat flux from Saturn’s rings were not available in any commercially available thermal analysis tools. While preparing for the Cassini Grand Finale, during which Cassini will travel extremely close to the rings of Saturn, it was determined the existing thermal model required updating to accurately predict heat fluxes from the rings. This is particularly important for Cassini’s Visual and Infrared Mapping Spectrometer infrared spectrometer (VIMS-IR), as it is cooled by a passive radiator which operates below the temperature of Saturn’s rings. This paper discusses the validation of the heat flux from solar, Saturn, and Saturn’s rings in Spacedesign’s Thermal Synthesizer System (TSS). The incorporation of heating from Saturn’s rings also led to the use of SPICE geometry to ensure accurate spacecraft positioning and pointing. Thermal model results are compared against historical heating events as well as predictive Grand Finale sequences.

Swanson, Kirsten S.↗

DOE OSTI2012

BAYESIAN ANGULAR POWER SPECTRUM ANALYSIS OF INTERFEROMETRIC DATA

We present a Bayesian angular power spectrum and signal map inference engine which can be adapted to interferometric observations of anisotropies in the cosmic microwave background (CMB), 21 cm emission line mapping of galactic brightness fluctuations, or 21 cm absorption line mapping of neutral hydrogen in the dark ages. The method uses Gibbs sampling to generate a sampled representation of the angular power spectrum posterior and the posterior of signal maps given a set of measured visibilities in the uv-plane. We use a mock interferometric CMB observation to demonstrate the validity of this method in the flat-sky approximation when adapted to take into account arbitrary coverage of the uv-plane, mode-mode correlations due to observations on a finite patch, and heteroschedastic visibility errors. The computational requirements scale as O(n{sub p} log n{sub p}) where n{sub p} measures the ratio of the size of the detector array to the inter-detector spacing, meaning that Gibbs sampling is a promising technique for meeting the data analysis requirements of future cosmology missions.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Monitoring water quality in the lower Kansas River using remote sensing

Abstract We demonstrate how to combine remote sensing data from satellite imagery (Sentinel‐2) with in situ water quality gauging (USGS Super Gages and the Gybe hyperspectral radiometer) to create spatially dense maps of water quality parameters (chlorophyll‐a concentration, turbidity, and nitrate plus nitrite concentration) along the lower Kansas River. The water quality maps are created using locally tuned models of the target water quality parameters, and this study describes the steps used to design, calibrate, and validate the empirical correlations. Water quality parameters such as chlorophyll‐a concentration are correlated with well‐studied absorption and scattering features in the visible spectrum (roughly 400–700 nm). Nutrients (such as nitrate plus nitrite concentration) lack strong absorption features in the visible spectrum, and in those cases we describe a novel surrogate data modeling approach that identifies overlapping water parcels between the in situ gauging and the remote sensing imagery. Measurements from the overlapping water parcels yield excellent correlations () for the target water quality parameters for limited windows of time (or limited sections of river reaches). Examples are provided illustrating how the water quality maps can be used to track river inputs from ungauged sources (such as creeks), or reveal the mixing patterns at the confluences.

Tufillaro, Nicholas↗

DOE OSTI2016

SU-G-TeP1-06: Fast GPU Framework for Four-Dimensional Monte Carlo in Adaptive Intensity Modulated Proton Therapy (IMPT) for Mobile Tumors

Purpose: To demonstrate the feasibility of fast Monte Carlo (MC) treatment planning and verification using four-dimensional CT (4DCT) for adaptive IMPT for lung cancer patients. Methods: A validated GPU MC code, gPMC, has been linked to the patient database at our institution and employed to compute the dose-influence matrices (Dij) on the planning CT (pCT). The pCT is an average of the respiratory motion of the patient. The Dijs and patient structures were fed to the optimizer to calculate a treatment plan. To validate the plan against motion, a 4D dose distribution averaged over the possible starting phases is calculated using the 4DCT and a model of the time structure of the delivered spot map. The dose is accumulated using vector maps created by a GPU-accelerated deformable image registration program (DIR) from each phase of the 4DCT to the reference phase using the B-spline method. Calculation of the Dij matrices and the DIR are performed on a cluster, with each field and vector map calculated in parallel. Results: The Dij production takes ∼3.5s per beamlet for 10e6 protons, depending on the energy and the CT size. Generating a plan with 4D simulation of 1000 spots in 4 fields takes approximately 1h. To test the framework, IMPT plans for 10 lung cancer patients were generated for validation. Differences between the planned and the delivered dose of 19% in dose to some organs at risk and 1.4/21.1% in target mean dose/homogeneity with respect to the plan were observed, suggesting potential for improvement if adaptation is considered. Conclusion: A fast MC treatment planning framework has been developed that allows reliable plan design and verification for mobile targets and adaptation of treatment plans. This will significantly impact treatments for lung tumors, as 4D-MC dose calculations can now become part of planning strategies.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

Mapping the N = 40 island of inversion: Precision mass measurements of neutron-rich Fe isotopes

Nuclear properties across the chart of nuclides are key to improving and validating our understanding of the strong interaction in nuclear physics. Here we present high-precision mass measurements of neutron-rich Fe isotopes performed at the TITAN facility. The multiple-reflection time-of-flight mass spectrometer (MR-ToF-MS), achieving a resolving power greater than 600000 for the first time, enabled the measurement of 63–70 Fe, including first-time high-precision direct measurements (δm/m ≈ 10 -7 ) of 68–70 Fe, as well as the discovery of a long-lived isomeric state in 69 Fe. These measurements are accompanied by both mean-field and ab initio calculations using the most recent realizations which enable theoretical assignment of the spin-parities of the 69 Fe ground and isomeric states. Together with mean-field calculations of quadrupole deformation parameters for the Fe isotope chain, these results benchmark a maximum of deformation in the N = 40 island of inversion in Fe and shed light on trends in level densities indicated in the newly refined mass surface.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2011

Mapping topological order in coordinate space

The organization of the electrons in the ground state is classified by means of topological invariants, defined as global properties of the wave function. Here we address the Chern number of a two-dimensional insulator and we show that the corresponding topological order can be mapped by means of a ''topological marker'', defined in r space, and which may vary in different regions of the same sample. Notably, this applies equally well to periodic and open boundary conditions. Simulations over a model Hamiltonian validate our theory.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2014

A test for a conjecture on the nature of attractors for smooth dynamical systems

Dynamics arising persistently in smooth dynamical systems ranges from regular dynamics (periodic, quasiperiodic) to strongly chaotic dynamics (Anosov, uniformly hyperbolic, nonuniformly hyperbolic modelled by Young towers). The latter include many classical examples such as Lorenz and Hénon-like attractors and enjoy strong statistical properties. It is natural to conjecture (or at least hope) that most dynamical systems fall into these two extreme situations. We describe a numerical test for such a conjecture/hope and apply this to the logistic map where the conjecture holds by a theorem of Lyubich, and to the 40-dimensional Lorenz-96 system where there is no rigorous theory. The numerical outcome is almost identical for both (except for the amount of data required) and provides evidence for the validity of the conjecture.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Mission planning for photogrammetry-based autonomous 3D Mapping of Dams using a commercial UAV

The application of autonomous unmanned aerial vehicles (UAVs) for conducting inspections of dams represents an innovative approach aimed at enhancing safety, efficiency, and cost-effectiveness. In this context, this paper presents algorithms for UAV mission design in autonomous dam inspections that include the creation of a 3D map based on photogrammetry. The algorithms were systematically developed to incorporate a comprehensive set of parameters that account for the geometric characteristics of the dam and adhere to photogrammetry specifications. To validate the proposed methodology, we utilized a commercial programmable quadrotor, specifically the Parrot Anafi USA Gov drone, which is equipped with high-quality cameras and can be programmed with the help of a software development kit (SDK) provided by the manufacturer. Our results demonstrate the efficacy of our method, highlighting how the generated maps can be used for hazard detection in the downstream slope of dams.

42 ENGINEERING↗

DOE OSTI2021

Quantitative assessment of the influence of external magnetic field on clustering of nano-Fe3O4 particles in cementitious paste

In view of active rheology control of cementitious materials, nano-Fe{sub 3}O{sub 4} can be added as responsive particles. Following the concept of magnetorheological fluids, it is assumed that magnetic nanoparticles will form chains or clusters in cementitious paste following magnetic field lines. A quantitative experimental validation of this assumption is presented herein. The clustering of nano-Fe{sub 3}O{sub 4} particles under magnetic fields is studied by mapping iron (Fe) element distribution in cementitious paste using energy dispersive X-ray spectroscopy. By means of image analysis, the Fe-element patterns are quantified by the deviation of Fe-elements in a unit area from the mean value expected in case of a uniform distribution, as expressed by coefficient of variation (COV). The magneto-rheological responses of cementitious pastes are evaluated using small amplitude oscillatory shear technique. Results show that the magneto-rheological effect exhibits a linear relationship with the relative change of COV, providing a quantitative validation of magnetic clustering in cementitious paste.

36 MATERIALS SCIENCE↗

NASA NTRS2012

The Invasive Species Forecasting System (ISFS): An iRODS-Based, Cloud-Enabled Decision Support System for Invasive Species Habitat Suitability Modeling

The Invasive Species Forecasting System (ISFS) is an online decision support system that allows users to load point occurrence field sample data for a plant species of interest and quickly generate habitat suitability maps for geographic regions of interest, such as a national park, monument, forest, or refuge. Target customers for ISFS are natural resource managers and decision makers who have a need for scientifically valid, model- based predictions of the habitat suitability of plant species of management concern. In a joint project involving NASA and the Maryland Department of Natural Resources, ISFS has been used to model the potential distribution of Wavyleaf Basketgrass in Maryland's Chesapeake Bay Watershed. Maximum entropy techniques are used to generate predictive maps using predictor datasets derived from remotely sensed data and climate simulation outputs. The workflow to run a model is implemented in an iRODS microservice using a custom ISFS file driver that clips and re-projects data to geographic regions of interest, then shells out to perform MaxEnt processing on the input data. When the model completes, all output files and maps from the model run are registered in iRODS and made accessible to the user. The ISFS user interface is a web browser that uses the iRODS PHP client to interact with the ISFS/iRODS- server. ISFS is designed to reside in a VMware virtual machine running SLES 11 and iRODS 3.0. The ISFS virtual machine is hosted in a VMware vSphere private cloud infrastructure to deliver the online service.

Gill, Roger↗

DOE OSTI2019

Genetic Control of Flowering in Switchgrass

Objective 1. Conduct GWAS of flowering time and identify genes for control and regulation of flowering time. Two switchgrass association panels were used to complete this objective, the northern and southern panels. Together, the two panels consisted of 985 switchgrass genotypes representing 110 accessions and the entire geographic range of switchgrass in the USA. Genotyping of both panels has been completed. Paul Grabowski completed the GWAS analysis of the northern panel, discovering numerous SNP markers within putative flowering time genes that are significantly associated with flowering time phenotype. The most important of these is an ortholog of the FT gene in rice, brachypodium, and arabidopsis. The manuscript describing these results has been published. The second manuscript, involving the second panel, is still under development. Objective 2. Validate genes associated with flowering time in the segregating populations. Three switchgrass double crosses (F2s) were successfully created in October 2013, each having a sufficient number of viable seeds to generate mapping populations. Each F2 mapping population is a cross between two siblings from an F1 cross of an early-flowering upland plant (Summer) and a late-flowering lowland plant (Ellsworth). A total of 286 genotypes were evaluated at two field locations (DeKalb, IL and West Lafayette, IN). Several loci were identified as critical for regulating flowering time, including validation of loci identified from previous studies, and several that are co-located with orthologs of candidate genes involved in the circadian clock, vernalization, and floral meristem development pathways.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2013

Does Preinterventional Flat-Panel Computer Tomography Pooled Blood Volume Mapping Predict Final Infarct Volume After Mechanical Thrombectomy in Acute Cerebral Artery Occlusion?

PurposeDecreased cerebral blood volume is known to be a predictor for final infarct volume in acute cerebral artery occlusion. To evaluate the predictability of final infarct volume in patients with acute occlusion of the middle cerebral artery (MCA) or the distal internal carotid artery (ICA) and successful endovascular recanalization, pooled blood volume (PBV) was measured using flat-panel detector computed tomography (FPD CT).Materials and MethodsTwenty patients with acute unilateral occlusion of the MCA or distal ACI without demarcated infarction, as proven by CT at admission, and successful Thrombolysis in cerebral infarction score (TICI 2b or 3) endovascular thrombectomy were included. Cerebral PBV maps were acquired from each patient immediately before endovascular thrombectomy. Twenty-four hours after recanalization, each patient underwent multislice CT to visualize final infarct volume. Extent of the areas of decreased PBV was compared with the final infarct volume proven by follow-up CT the next day.ResultsIn 15 of 20 patients, areas of distinct PBV decrease corresponded to final infarct volume. In 5 patients, areas of decreased PBV overestimated final extension of ischemia probably due to inappropriate timing of data acquisition and misery perfusion.ConclusionPBV mapping using FPD CT is a promising tool to predict areas of irrecoverable brain parenchyma in acute thromboembolic stroke. Further validation is necessary before routine use for decision making for interventional thrombectomy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2019

High-Resolution Electron Microscopy and Kinetic Studies of Precipitation Hardening Reactions in Cast Al-5.8Zn-2.2Mg-2.5Cu

Precipitation age hardening (T6) response of Al-5.8Zn-2.2Mg-2.5Cu alloy in near-net-shaped cast condition was investigated. Cast samples were manufactured using the controlled diffusion solidification (CDS) technology combined with a metallic mold tilt pour gravity casting process. This study was conducted using (1) non-isothermal aging during differential scanning calorimetry (DSC) experiments and (2) isothermal aging during which transient bulk and micro-hardness measurements taken at four aging temperatures of 343, 393, 433 and 473 K. A detailed microstructural investigation combined with a quantitative image analysis was carried out on both DSC and hardness specimens using high-resolution electron microscopy (HREM) and energy-dispersive spectroscopy (EDS) elemental mappings. Hardness measurements were analyzed using a kinetic modeling approach (single state variable combined with a kinetic equation that is valid for the Al-Zn-Mg-Cu alloys). The results confirm the formation of hardening phases of GP zone, intermediate hardening metastable phase η′ and equilibrium phase η. The results of calorimetric measurements, electron microscopy and selected area diffraction patterns are in good agreement and confirm transient precipitation/dissolution sequences. A mean value of activation energy Q{sub A} of 75 kJ/mol was evaluated for combined bulk diffusion rate of alloying elements during precipitation of strengthening phases within Al matrix.

36 MATERIALS SCIENCE↗

DOE OSTI2016

Simulation-based coefficients for adjusting climate impact on energy consumption of commercial buildings

This paper presents a new technique for and the results of normalizing building energy consumption to enable a fair comparison among various types of buildings located near different weather stations across the U.S. The method was developed for the U.S. Building Energy Asset Score, a whole-building energy efficiency rating system focusing on building envelope, mechanical systems, and lighting systems. The Asset Score is calculated based on simulated energy use under standard operating conditions. Existing weather normalization methods such as those based on heating and cooling degrees days are not robust enough to adjust all climatic factors such as humidity and solar radiation. In this work, over 1000 sets of climate coefficients were developed to separately adjust building heating, cooling, and fan energy use at each weather station in the United States. This paper also presents a robust, standardized weather station mapping based on climate similarity rather than choosing the closest weather station. This proposed simulated-based climate adjustment was validated through testing on several hundreds of thousands of modeled buildings. Results indicated the developed climate coefficients can isolate and adjust for the impacts of local climate for asset rating.

Asset Rating↗

DOE OSTI2023

Feature-adjacent multi-fidelity physics-informed machine learning for partial differential equations

Physics-informed neural networks have emerged as an alternative method for solving partial differential equations. However, for complex problems, the training of such networks can still require high-fidelity data which can be expensive to generate. To reduce or even eliminate the dependency on high-fidelity data, we propose a novel multi-fidelity architecture which is based on a feature space shared by the low- and high-fidelity solutions. In the feature space, the projections of the low-fidelity and high-fidelity solutions are adjacent by constraining their relative distance. The feature space is represented with an encoder and its mapping to the original solution space is effected through a decoder. In conclusion, the proposed multi-fidelity approach is validated on forward and inverse problems for steady and unsteady problems described by partial differential equations.

97 MATHEMATICS AND COMPUTING↗