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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Heat-activated Plasmonic Chemical Sensors for Harsh Environments

A passive plasmonics based chemical sensing system to be used in harsh operating environments was investigated and developed within this program. The initial proposed technology was based on combining technologies developed at the SUNY Polytechnic Institute Colleges of Nanoscale Science and Engineering (CNSE) and at the University of Minnesota (UM). Specifically, a passive wireless technique developed at UM was to utilize a heat-activated plasmonic design to passively harvest the thermal energy from within a combustion emission stream and convert this into a narrowly focused light source. This plasmonic device was based on a bullseye design patterned into a gold film using focused ion beam methods (FIB). Critical to the design was the use of thermal stabilizing under and overlayers surrounding the gold film. These stabilizing layers were based on both atomic layer deposited films as well as metal laminate layers developed by United Technologies Aerospace Systems (UTAS). While the bullseye design was never able to be thermally stabilized for operating temperatures of 500oC or higher, an alternative energy harvesting design was developed by CNSE within this program. With this new development, plasmonic sensing results are presented where thermal energy is harvested using lithographically patterned Au nanorods, replacing the need for an external incident light source. Gas sensing results using the harvested thermal energy are in good agreement with sensing experiments, which used an external incident light source. Principal Component Analysis (PCA) was used to reduce the wavelength parameter space from 665 variables down to 4 variables with similar levels of demonstrated selectivity. The method was further improved by patterning rods which harvested energy in the near infrared, which led to a factor of 10 decrease in data acquisition times as well as demonstrated selectivity with a reduced wavelength data set. The combination of a plasmonic-based energy harvesting sensing paradigm with PCA analysis and wavelength down selection offers a novel path towards simplification and integration of plasmonic-based sensing methods using selected wavelengths rather than a full spectral analysis. Integration efforts were designed and modeled for thermal and mass transport considerations by UTAS which led to the 3D printing of scaled models that would serve as the housing for the alternative energy harvesting plasmonic chemical sensor design developed by CNSE.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Resource-Efficient Chemistry on Quantum Computers with the Variational Quantum Eigensolver and The Double Unitary Coupled-Cluster approach

Applications of quantum simulation algorithms to obtain electronic energies of molecules on noisy intermediate-scale quantum (NISQ) devices require careful consideration of resources describing the complex electron correlation effects. In modeling second-quantized problems, the biggest challenge confronted is that the number of qubits scales linearly with the size of molecular basis. This poses a significant limitation on the size of the basis sets and the number of correlated electrons included in quantum simulations of chemical processes. To address this issue and to enable more realistic simulations on NISQ computers, we employ the double unitary coupled-cluster (DUCC) method to effectively downfold correlation effects into the reduced-size orbital space, commonly referred to as the active space. Using downfolding techniques, we demonstrate that properly constructed effective Hamiltonians can capture the effect of the whole orbital space in small-size active spaces. Combining the downfolding pre-processing technique with the Variational Quantum Eigensolver, we solve for the ground-state energy of H2 and Li2 in the cc-pVTZ basis using the DUCC-reduced active spaces. We compare these results to full configuration-interaction and high-level coupled-cluster reference calculations.

quantum computing, variational quantum solver, cou↗
DOE OSTI2021

Complete collision data set for electrons scattering on molecular hydrogen and its isotopologues: II. Fully vibrationally-resolved electronic excitation of the isotopologues of H 2 (X 1 $Σ^{+}_{g}$)

Here, we present a comprehensive set of vibrationally-resolved cross sections for electron-impact electronic excitation of the isotopologues of molecular hydrogen (D 2 , T 2 , HD, HT, and DT) initially in the ground electronic state. We apply the adiabatic-nuclei molecular convergent close-coupling (MCCC) method to calculate cross sections from threshold to 500 eV for excitation of all bound vibrational levels and dissociative excitation of the B 1 $Σ^{+}_{g}$, C 1 Π u , EF 1 $Σ^{+}_{g}$, B' 1 $Σ^{+}_{g}$, GK 1 $Σ^{+}_{g}$, I 1 Π g , J 1 Δ g , D 1 Π u , H 1 $Σ^{+}_{g}$, b 1 $Σ^{+}_{g}$, c 3 Π u , a 3 $Σ^{+}_{g}$, e 3 $Σ^{+}_{u}$, d 3 Π u , h 3 $Σ^{+}_{g}$, g 3 $Σ^{+}_{g}$, i 3 Π g , and j 3 Δ g electronic states from all bound vibrational levels of the ground electronic (X 1 $Σ^{+}_{g}$) state. Including the previously-published MCCC e-H2 cross sections the data set contains cross sections for over 60,000 electronic and vibrational transitions. The cross sections are presented in graphical form and provided as both numerical values and analytic fit functions in supplementary data files. The data can also be downloaded from the MCCC database at mccc-db.org.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2014

An angle-dependent estimation of CT x-ray spectrum from rotational transmission measurements

Purpose: Computed tomography (CT) performance as well as dose and image quality is directly affected by the x-ray spectrum. However, the current assessment approaches of the CT x-ray spectrum require costly measurement equipment and complicated operational procedures, and are often limited to the spectrum corresponding to the center of rotation. In order to address these limitations, the authors propose an angle-dependent estimation technique, where the incident spectra across a wide range of angular trajectories can be estimated accurately with only a single phantom and a single axial scan in the absence of the knowledge of the bowtie filter. Methods: The proposed technique uses a uniform cylindrical phantom, made of ultra-high-molecular-weight polyethylene and positioned in an off-centered geometry. The projection data acquired with an axial scan have a twofold purpose. First, they serve as a reflection of the transmission measurements across different angular trajectories. Second, they are used to reconstruct the cross sectional image of the phantom, which is then utilized to compute the intersection length of each transmission measurement. With each CT detector element recording a range of transmission measurements for a single angular trajectory, the spectrum is estimated for that trajectory. A data conditioning procedure is used to combine information from hundreds of collected transmission measurements to accelerate the estimation speed, to reduce noise, and to improve estimation stability. The proposed spectral estimation technique was validated experimentally using a clinical scanner (Somatom Definition Flash, Siemens Healthcare, Germany) with spectra provided by the manufacturer serving as the comparison standard. Results obtained with the proposed technique were compared against those obtained from a second conventional transmission measurement technique with two materials (i.e., Cu and Al). After validation, the proposed technique was applied to measure spectra from the clinical system across a range of angular trajectories [−15°, 15°] and spectrum settings (80, 100, 120, 140 kVp). Results: At 140 kVp, the proposed technique was comparable to the conventional technique in terms of the mean energy difference (MED, −0.29 keV) and the normalized root mean square difference (NRMSD, 0.84%) from the comparison standard compared to 0.64 keV and 1.56%, respectively, with the conventional technique. The average absolute MEDs and NRMSDs across kVp settings and angular trajectories were less than 0.61 keV and 3.41%, respectively, which indicates a high level of estimation accuracy and stability. Conclusions: An angle-dependent estimation technique of CT x-ray spectra from rotational transmission measurements was proposed. Compared with the conventional technique, the proposed method simplifies the measurement procedures and enables incident spectral estimation for a wide range of angular trajectories. The proposed technique is suitable for rigorous research objectives as well as routine clinical quality control procedures.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2015

Enhancing atlas based segmentation with multiclass linear classifiers

Purpose: To present a method to enrich atlases for atlas based segmentation. Such enriched atlases can then be used as a single atlas or within a multiatlas framework. Methods: In this paper, machine learning techniques have been used to enhance the atlas based segmentation approach. The enhanced atlas defined in this work is a pair composed of a gray level image alongside an image of multiclass classifiers with one classifier per voxel. Each classifier embeds local information from the whole training dataset that allows for the correction of some systematic errors in the segmentation and accounts for the possible local registration errors. The authors also propose to use these images of classifiers within a multiatlas framework: results produced by a set of such local classifier atlases can be combined using a label fusion method. Results: Experiments have been made on the in vivo images of the IBSR dataset and a comparison has been made with several state-of-the-art methods such as FreeSurfer and the multiatlas nonlocal patch based method of Coupé or Rousseau. These experiments show that their method is competitive with state-of-the-art methods while having a low computational cost. Further enhancement has also been obtained with a multiatlas version of their method. It is also shown that, in this case, nonlocal fusion is unnecessary. The multiatlas fusion can therefore be done efficiently. Conclusions: The single atlas version has similar quality as state-of-the-arts multiatlas methods but with the computational cost of a naive single atlas segmentation. The multiatlas version offers a improvement in quality and can be done efficiently without a nonlocal strategy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2011

Auto-segmentation of normal and target structures in head and neck CT images: A feature-driven model-based approach

Purpose: Intensity modulated radiation therapy (IMRT) allows greater control over dose distribution, which leads to a decrease in radiation related toxicity. IMRT, however, requires precise and accurate delineation of the organs at risk and target volumes. Manual delineation is tedious and suffers from both interobserver and intraobserver variability. State of the art auto-segmentation methods are either atlas-based, model-based or hybrid however, robust fully automated segmentation is often difficult due to the insufficient discriminative information provided by standard medical imaging modalities for certain tissue types. In this paper, the authors present a fully automated hybrid approach which combines deformable registration with the model-based approach to accurately segment normal and target tissues from head and neck CT images. Methods: The segmentation process starts by using an average atlas to reliably identify salient landmarks in the patient image. The relationship between these landmarks and the reference dataset serves to guide a deformable registration algorithm, which allows for a close initialization of a set of organ-specific deformable models in the patient image, ensuring their robust adaptation to the boundaries of the structures. Finally, the models are automatically fine adjusted by our boundary refinement approach which attempts to model the uncertainty in model adaptation using a probabilistic mask. This uncertainty is subsequently resolved by voxel classification based on local low-level organ-specific features. Results: To quantitatively evaluate the method, they auto-segment several organs at risk and target tissues from 10 head and neck CT images. They compare the segmentations to the manual delineations outlined by the expert. The evaluation is carried out by estimating two common quantitative measures on 10 datasets: volume overlap fraction or the Dice similarity coefficient (DSC), and a geometrical metric, the median symmetric Hausdorff distance (HD), which is evaluated slice-wise. They achieve an average overlap of 93% for the mandible, 91% for the brainstem, 83% for the parotids, 83% for the submandibular glands, and 74% for the lymph node levels. Conclusions: Our automated segmentation framework is able to segment anatomy in the head and neck region with high accuracy within a clinically-acceptable segmentation time.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Concepts, Challenges, and Successes in Modeling Thermodynamics of Metabolism

The modeling of the chemical reactions involved in metabolism is a daunting task. Ideally, the modeling of metabolism would use kinetic simulations, but these simulations require knowledge of the thousands of rate constants involved in the reactions. The measurement of rate constants is very labor intensive, and hence rate constants for most enzymatic reactions are not available. Consequently, constraint-based flux modeling has been the method of choice because it does not require the use of the rate constants of the law of mass action. However, this convenience also limits the predictive power of constraint-based approaches in that the law of mass action is used only as a constraint, making it difficult to predict metabolite levels or energy requirements of pathways. An alternative to both of these approaches is to model metabolism using simulations of states rather than simulations of reactions, in which the state is defined as the set of all metabolite counts or concentrations. While kinetic simulations model reactions based on the likelihood of the reaction derived from the law of mass action, states are modeled based on likelihood ratios of mass action. Both approaches provide information on the energy requirements of metabolic reactions and pathways. However, modeling states rather than reactions has the advantage that the parameters needed to model states (chemical potentials) are much easier to determine than the parameters needed to model reactions (rate constants). Herein, we discuss recent results, assumptions, and issues in using simulations of state to model metabolism.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Self-interaction corrected density functional calculations of molecular Rydberg states

A method is presented for calculating the wave function and energy of Rydberg excited states of molecules. A good estimate of the Rydberg state orbital is obtained using ground state density functional theory including Perdew-Zunger self-interaction correction and an optimized effective potential. The total energy of the excited molecule is obtained using the Delta Self-Consistent Field method where an electron is removed from the highest occupied orbital and placed in the Rydberg orbital. Results are presented for the first few Rydberg states of NH{sub 3}, H{sub 2}O, H{sub 2}CO, C{sub 2}H{sub 4}, and N(CH{sub 3}){sub 3}. The mean absolute error in the energy of the 33 molecular Rydberg states presented here is 0.18 eV. The orbitals are represented on a real space grid, avoiding the dependence on diffuse atomic basis sets. As in standard density functional theory calculations, the computational effort scales as NM{sup 2} where N is the number of orbitals and M is the number of grid points included in the calculation. Due to the slow scaling of the computational effort with system size and the high level of parallelism in the real space grid approach, the method presented here makes it possible to estimate Rydberg electron binding energy in large molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

SU-G-201-02: Application of RayStretch in Clinical Cases: A Calculation for Heterogeneity Corrections in LDR Permanent I-125 Prostate Brachytherapy

Purpose: Tissue heterogeneities and calcifications have significant impact on the dosimetry of low energy brachytherapy (BT). RayStretch is an analytical algorithm developed in our institution to incorporate heterogeneity corrections in LDR prostate brachytherapy. The aim of this work is to study its application in clinical cases by comparing its predictions with the results obtained with TG-43 and Monte Carlo (MC) simulations. Methods: A clinical implant (71 I-125 seeds, 15 needles) from a real patient was considered. On this patient, different volumes with calcifications were considered. Its properties were evaluated in three ways by i) the Treatment planning system (TPS) (TG-43), ii) a MC study using the Penelope2009 code, and iii) RayStretch. To analyse the performance of RayStretch, calcifications located in the prostate lobules covering 11% of the total prostate volume and larger calcifications located in the lobules and underneath the urethra for a total occupied volume of 30% were considered. Three mass densities (1.05, 1.20, and 1.35 g/cm3) were explored for the calcifications. Therefore, 6 different scenarios ranging from small low density calcifications to large high density ones have been discussed. Results: DVH and D90 results given by RayStretch agree within 1% with the full MC simulations. Although no effort has been done to improve RayStretch numerical performance, its present implementation is able to evaluate a clinical implant in a few seconds to the same level of accuracy as a detailed MC calculation. Conclusion: RayStretch is a robust method for heterogeneity corrections in prostate BT supported on TG-43 data. Its compatibility with commercial TPSs and its high calculation speed makes it feasible for use in clinical settings for improving treatment quality. It will allow in a second phase of this project, its use during intraoperative ultrasound planning. This study was partly supported by a fellowship grant from the Spanish Ministry of Education, by the Generalitat Valenciana under Project PROMETEOII/2013/010, by the Spanish Government under Project No. FIS2013-42156 and by the European Commission within the SeventhFramework Program through ENTERVISION (grant agreement number 264552).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

The Challenges of Air Monitoring at a Soil Remediation Project in a Suburban Setting - 20448

Air monitoring during soil excavation at a chemically and radiologically impacted site in a suburban setting presents unique challenges. Site activities were conducted in a manner that minimized the release of airborne particulates of concern, principally radionuclides of concern (ROC). Dust and air monitoring were performed to ensure the public was not being exposed to the soil contaminants. The project team collected representative air and dust data while being mindful to not impose on the lives of residents in the area. Due to the close proximity to the public, there was a high level of oversight from the client and regulatory agencies. The challenges involved with air sampling at this soil remediation site located in a suburban setting included the number of contaminants, the ranges of risks and hazards presented by the contaminants and the method of remediation, the concerns of the regulators and the public, and the perception of risk from the public. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Uncertainty quantification methodology for hyperbolic systems with application to blood flow in arteries

We present a Stochastic Finite Volume - ADER (SFV-ADER) methodology for Uncertainty Quantification (UQ) in the general framework of systems of hyperbolic balance laws with uncertainty in parameters. The resulting method is weakly intrusive, meaning that deterministic solvers need minor modifications to include random contributions, and has no theoretical accuracy barrier. An illustration of the second-order version for the viscous Burgers equation with uncertain viscosity coefficient is first given in detail, under different deterministic initial conditions; the attainment of the theoretically expected convergence rate is demonstrated empirically; results and features of our scheme are discussed. We then extend the SFV-ADER method to a non-linear hyperbolic system with source terms that models one-dimensional blood flow in arteries, assuming uncertainties in a set of parameters of the problem. Results are then compared with measurements in a well-defined 1:1 experimental replica of the network of largest arteries in the human systemic circulation. For a 99%-confidence level, severe influence of parameter fluctuations is seen in pressure profiles, while secondary effects on flow rate profiles become visible, particularly in terminal branches. In conclusion, results suggest that the proposed methodology could successfully be applied to other physical problems involving hyperbolic balance laws.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

CONSTRAINTS ON LEMAITRE-TOLMAN-BONDI MODELS FROM OBSERVATIONAL HUBBLE PARAMETER DATA

We use the observational Hubble parameter data (OHD), both the latest observational data set (Stern et al.; referred to as SJVKS) and the simulated data sets, to constrain Lemaitre-Tolman-Bondi (LTB) void models. The necessity of the consistency check on OHD itself in the LTB cosmology is stressed. Three voids are chosen as test models and are constrained using the Union2 data set of SN Ia as well as OHD. Despite their different parameterization, the results from our test models show some similarities; e.g., the best-fit voids obtained from OHD are all considerably broader than those from SN Ia. Due to the small size of the SJVKS data set, the constraints are not conclusive. The constraining power of the future OHD observations are therefore investigated through a figure of merit (FoM) analysis based on the Monte Carlo simulated data. We found that, in the case that the future OHD become more consistent with SN Ia, the results from the test models are almost unanimous: (1) as many as 32 OHD data points at the SJVKS-like uncertainty level are needed to give a higher FoM than the Union2 data set of SN Ia, (2) precise observation helps reduce this required number, (3) increasing the survey depth does not always increase the FoM. On the other hand, if the future OHD and the Union2 data set keep favoring different voids, in a similar manner as they do at present, the 1{sigma} confidence regions obtained from the two probes should finally separate. We test this conjecture and find that the minimum observational requirement (the size of the data set, the uncertainty level, and the survey depth) for this inconsistency to emerge depends strongly on the void model.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Comparison of Spectroscopic Techniques for Determining the Peroxide Value of 19 Classes of Naturally Aged, Plant-Based Edible Oils

The peroxide value of edible oils is a measure of the degree of oxidation, which directly relates to the freshness of the oil sample. Several studies previously reported in the literature have paired various spectroscopic techniques with multivariate analyses to rapidly determine peroxide values using field portable and process instrumentation; those efforts presented “best-case scenarios” with oils from narrowly defined training and test sets. The purpose of this paper is to evaluate the use of near- and mid-infrared absorption and Raman scattering spectroscopies on oil samples from different oil classes, including seasonal and vendor variations, to determine which measurement technique or combination thereof is best for predicting peroxide values. Following peroxide value assays of each oil class using an established titration-based method, global and global-subset calibration models were constructed from spectroscopic data collected on the 19 oil classes used in this study. Spectra from each optical technique were used to create partial least squares regression calibration models to predict the peroxide value of unknown oil samples. A global peroxide value model based on near-infrared (8 mm optical path length) oil measurements produced the lowest RMSEP (4.9), followed by 24 mm optical path length near infrared (5.1), Raman (6.9) and 50 µm optical path length mid-infrared (7.3). However, it was determined that the Raman RMSEP resulted from chance correlations. Global peroxide value models based on low-level fusion of the NIR (8 and 24 mm optical path length) data and all infrared data produced the same RMSEP of 5.1. Global subset models, based on any of the spectroscopies and olive oil training sets from any class (pure, extra light, extra virgin), all failed to extrapolate to the non-olive oils. However, the near-infrared global subset model built on extra virgin olive oil could extrapolate to test samples from other olive oil classes. This work demonstrates the difficulty of developing a truly global method for determining peroxide value of oils.

36 MATERIALS SCIENCE↗
DOE OSTI2016

An integrated model-driven method for in-treatment upper airway motion tracking using cine MRI in head and neck radiation therapy

Purpose: For the first time, MRI-guided radiation therapy systems can acquire cine images to dynamically monitor in-treatment internal organ motion. However, the complex head and neck (H&N) structures and low-contrast/resolution of on-board cine MRI images make automatic motion tracking a very challenging task. In this study, the authors proposed an integrated model-driven method to automatically track the in-treatment motion of the H&N upper airway, a complex and highly deformable region wherein internal motion often occurs in an either voluntary or involuntary manner, from cine MRI images for the analysis of H&N motion patterns. Methods: Considering the complex H&N structures and ensuring automatic and robust upper airway motion tracking, the authors firstly built a set of linked statistical shapes (including face, face-jaw, and face-jaw-palate) using principal component analysis from clinically approved contours delineated on a set of training data. The linked statistical shapes integrate explicit landmarks and implicit shape representation. Then, a hierarchical model-fitting algorithm was developed to align the linked shapes on the first image frame of a to-be-tracked cine sequence and to localize the upper airway region. Finally, a multifeature level set contour propagation scheme was performed to identify the upper airway shape change, frame-by-frame, on the entire image sequence. The multifeature fitting energy, including the information of intensity variations, edge saliency, curve geometry, and temporal shape continuity, was minimized to capture the details of moving airway boundaries. Sagittal cine MR image sequences acquired from three H&N cancer patients were utilized to demonstrate the performance of the proposed motion tracking method. Results: The tracking accuracy was validated by comparing the results to the average of two manual delineations in 50 randomly selected cine image frames from each patient. The resulting average dice similarity coefficient (93.28% ± 1.46%) and margin error (0.49 ± 0.12 mm) showed good agreement between the automatic and manual results. The comparison with three other deformable model-based segmentation methods illustrated the superior shape tracking performance of the proposed method. Large interpatient variations of swallowing frequency, swallowing duration, and upper airway cross-sectional area were observed from the testing cine image sequences. Conclusions: The proposed motion tracking method can provide accurate upper airway motion tracking results, and enable automatic and quantitative identification and analysis of in-treatment H&N upper airway motion. By integrating explicit and implicit linked-shape representations within a hierarchical model-fitting process, the proposed tracking method can process complex H&N structures and low-contrast/resolution cine MRI images. Future research will focus on the improvement of method reliability, patient motion pattern analysis for providing more information on patient-specific prediction of structure displacements, and motion effects on dosimetry for better H&N motion management in radiation therapy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

WE-E-18A-03: How Accurately Can the Peak Skin Dose in Fluoroscopy Be Determined Using Indirect Dose Metrics?

Purpose: Skin dosimetry is important for fluoroscopically-guided interventions, as peak skin doses (PSD) that Result in skin reactions can be reached during these procedures. The purpose of this study was to assess the accuracy of different indirect dose estimates and to determine if PSD can be calculated within ±50% for embolization procedures. Methods: PSD were measured directly using radiochromic film for 41 consecutive embolization procedures. Indirect dose metrics from procedures were collected, including reference air kerma (RAK). Four different estimates of PSD were calculated and compared along with RAK to the measured PSD. The indirect estimates included a standard method, use of detailed information from the RDSR, and two simplified calculation methods. Indirect dosimetry was compared with direct measurements, including an analysis of uncertainty associated with film dosimetry. Factors affecting the accuracy of the indirect estimates were examined. Results: PSD calculated with the standard calculation method were within ±50% for all 41 procedures. This was also true for a simplified method using a single source-to-patient distance (SPD) for all calculations. RAK was within ±50% for all but one procedure. Cases for which RAK or calculated PSD exhibited large differences from the measured PSD were analyzed, and two causative factors were identified: ‘extreme’ SPD and large contributions to RAK from rotational angiography or runs acquired at large gantry angles. When calculated uncertainty limits [−12.8%, 10%] were applied to directly measured PSD, most indirect PSD estimates remained within ±50% of the measured PSD. Conclusions: Using indirect dose metrics, PSD can be determined within ±50% for embolization procedures, and usually to within ±35%. RAK can be used without modification to set notification limits and substantial radiation dose levels. These results can be extended to similar procedures, including vascular and interventional oncology. Film dosimetry is likely an unnecessary effort for these types of procedures.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Can fractal dimensions objectivize gastropod shell morphometrics? A case study from Lake Lugu (SW China)

1. Morphometrics are fundamental for the analysis of size and shape in fossils, particularly because soft parts or DNA are rarely preserved and hard parts such as shells are commonly the only source of information. Geometric morphometrics, that is, landmark analysis, is well established for the description of shape but it exhibits a couple of shortcomings resulting from subjective choices during landmarking (number and position of landmarks) and from difficulties in resolving shape at the level of micro-sculpture. 2. With the aid of high-resolution 3D scanning technology and analyses of fractal dimensions, we test whether such shortcomings of linear and landmark morphometrics can be overcome. As a model group, we selected a clade of modern viviparid gastropods from Lake Lugu, with shells that show a high degree of sculptural variation. Linear and landmark analyses were applied to the same shells in order to establish the fractal dimensions. 3. The genetic diversity of the gastropod clade was assessed. The genetic results suggest that the gastropod clade represents a single species. The results of all morphometric methods applied are in line with the genetic results, which is that no specific morphotype could be delimited. Apart from this overall agreement, landmark and fractal dimension analyses do not correspond to each other but represent data sets with different information. Generally, the fractal dimension values quantify the roughness of the shell surface, the resolution of the 3D scans determining the level. In our approach, we captured the micro-sculpture but not the first-order sculptural elements, which explains that fractal dimension and landmark data are not in phase. 4. We can show that analyzing fractal dimensions of gastropod shells opens a window to more detailed information that can be considered in evolutionary and ecological contexts. We propose that using low-resolution 3D scans may successfully substitute landmark analyses because it overcomes the subjective landmarking. Analyses of 3D scans with higher resolution than used in this study will provide surface roughness information at the mineralogical level. We suggest that fractal dimension analyses of a combination of differently resolved 3D models will significantly improve the quality of shell morphometrics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Positivity Limiters for Filtered Spectral Approximations of Linear Kinetic Transport Equations

We analyze the properties and compare the performance of several positivity limiters for spectral approximations with respect to the angular variable of linear transport equations. It is well-known that spectral methods suffer from the occurrence of (unphysical) negative spatial particle concentrations due to the fact that the underlying polynomial approximations are not always positive at the kinetic level. Positivity limiters address this defect by enforcing positivity of the polynomial approximation on a finite set of preselected points. With a proper PDE solver, they ensure positivity of the particle concentration at each step in a time integration scheme. We review several known positivity limiters proposed in other contexts and also introduce a modification for one of them. We give error estimates for the consistency of the positive approximations produced by these limiters and compare the theoretical estimates to numerical results. We then solve two benchmark problems with these limiters, make qualitative and quantitative observations about the solutions, and then compare the efficiency of the different limiters.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Time-Adjusted Internal Target Volume: A Novel Approach Focusing on Heterogeneity of Tumor Motion Based on 4-Dimensional Computed Tomography Imaging for Radiation Therapy Planning of Lung Cancer

Purpose: To consider nonuniform tumor motion within the internal target volume (ITV) by defining time-adjusted ITV (TTV), a volume designed to include heterogeneity of tumor existence on the basis of 4-dimensional computed tomography (4D-CT). Methods and Materials: We evaluated 30 lung cancer patients. Breath-hold CT (BH-CT) and free-breathing 4D-CT scans were acquired for each patient. The tumors were manually delineated using a lung CT window setting (window, 1600 HU; level, −300 HU). Tumor in BH-CT images was defined as gross tumor volume (GTV), and the sum of tumors in 4D-CT images was defined as ITV-4D. The TTV images were generated from the 4D-CT datasets, and the tumor existence probability within ITV-4D was calculated. We calculated the TTV{sub 80} value, which is the percentage of the volume with a tumor existence probability that exceeded 80% on ITV-4D. Several factors that affected the TTV{sub 80} value, such as the ITV-4D/GTV ratio or tumor centroid deviation, were evaluated. Results: Time-adjusted ITV images were acquired for all patients, and tumor respiratory motion heterogeneity was visualized. The median (range) ITV-4D/GTV ratio and median tumor centroid deviation were 1.6 (1.0-4.1) and 6.3 mm (0.1-30.3 mm), respectively. The median TTV{sub 80} value was 43.3% (2.9-98.7%). Strong correlations were observed between the TTV{sub 80} value and the ITV-4D/GTV ratio (R=−0.71) and tumor centroid deviation (R=−0.72). The TTV images revealed the tumor motion pattern features within ITV. Conclusions: The TTV images reflected nonuniform tumor motion, and they revealed the tumor motion pattern features, suggesting that the TTV concept may facilitate various aspects of radiation therapy planning of lung cancer while incorporating respiratory motion in the future.

62 RADIOLOGY AND NUCLEAR MEDICINE↗