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DOE OSTI2021

How New Mexico Leveraged a COVID-19 Case Forecasting Model to Preemptively Address the Healthcare Needs of the State: Quantitative Analysis

Prior to the COVID-19 pandemic, US hospitals relied on static projections of future trends for long-term planning and were only beginning to consider forecasting methods for short-term planning of staffing and other resources. With the overwhelming burden imposed by COVID-19 on the health care system, an emergent need exists to accurately forecast hospitalization needs within an actionable timeframe. Our goal was to leverage an existing COVID-19 case and death forecasting tool to generate the expected number of concurrent hospitalizations, occupied intensive care unit (ICU) beds, and in-use ventilators 1 day to 4 weeks in the future for New Mexico and each of its five health regions. We developed a probabilistic model that took as input the number of new COVID-19 cases for New Mexico from Los Alamos National Laboratory’s COVID-19 Forecasts Using Fast Evaluations and Estimation tool, and we used the model to estimate the number of new daily hospital admissions 4 weeks into the future based on current statewide hospitalization rates. The model estimated the number of new admissions that would require an ICU bed or use of a ventilator and then projected the individual lengths of hospital stays based on the resource need. By tracking the lengths of stay through time, we captured the projected simultaneous need for inpatient beds, ICU beds, and ventilators. We used a postprocessing method to adjust the forecasts based on the differences between prior forecasts and the subsequent observed data. Thus, we ensured that our forecasts could reflect a dynamically changing situation on the ground. Forecasts made between September 1 and December 9, 2020, showed variable accuracy across time, health care resource needs, and forecast horizon. Forecasts made in October, when new COVID-19 cases were steadily increasing, had an average accuracy error of 20.0%, while the error in forecasts made in September, a month with low COVID-19 activity, was 39.7%. Across health care use categories, state-level forecasts were more accurate than those at the regional level. Although the accuracy declined as the forecast was projected further into the future, the stated uncertainty of the prediction improved. Forecasts were within 5% of their stated uncertainty at the 50% and 90% prediction intervals at the 3- to 4-week forecast horizon for state-level inpatient and ICU needs. However, uncertainty intervals were too narrow for forecasts of state-level ventilator need and all regional health care resource needs. Real-time forecasting of the burden imposed by a spreading infectious disease is a crucial component of decision support during a public health emergency. Our proposed methodology demonstrated utility in providing near-term forecasts, particularly at the state level. This tool can aid other stakeholders as they face COVID-19 population impacts now and in the future.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

Spectroscopic research of Lambda hypernuclei up to medium-heavy mass region with the (e,e'K + ) reaction

In 2009 (August-November), the E05-115 experiment was carried out at JLab to investigate L hypernuclei in the wide mass region up to A = 52 ($7\atop{Λ}$He, $10\atop{Λ}$Be, $12\atop{Λ}$B and $52\atop{Λ}$V) with the (e,e'K + ) reaction. This is the first attempt to investigate a medium heavy L hypernucleus with the (e,e'K + ) reaction. Experimentally, it is difficult to measure heavier L hypernuclei as background rates of particles which originate from electromagnetic processes are roughly in proportion to Z2 (Z: target proton number) in the (e,e'K + ) experiment. To perform the experiment, many experimental techniques have been developed and introduced such as optimization of the electron spectrometer configuration (tilt method), clean kaon identification, particle tracking under high multiplicity environment, precise energy scale calibration and so on. In the present thesis, experimental results of the elementary process of p(e,e'K + )L, L hypernuclei of $7\atop{Λ}$He, $10\atop{Λ}$Be, $12\atop{Λ}$B and $52\atop{Λ}$V are shown. Elementary processes of the electroproduction of L and Σ 0 , p(e,e'K + )L, Σ 0 were used for the absolute energy scale calibration of our spectrometer systems. A careful Monte Carlo simulation shows that the binding energy can be obtained with a systematic error of 0.11 MeV with our energy scale calibration method. A study of the elementary process of L is important to understand L hypernuclei as it is essential for theoretical calculations of L hypernuclei. The differential cross section of the p(e,e'K + )L reaction at the small K + scattering angle (theta-CM/gamma-K approx. 15.5°), the small Q 2 (approx 0.01 [GeV/c] 2 ) and the total energy of W = 1.92 GeV, where no experimental data exists was obtained to be 235 ± 13$+28\atop{-24}$ nb/sr. The ground state (1/2 + ) binding energy of $7\atop{Λ}$He was already measured in JLab E01-011 (2005). In the present work, the binding energy of 1/2 + state was determined to be B Λ = 5.55 ± 0.10 ±0.11 MeV with five times more statistic and smaller systematic errors than those of the previous experiment. The ground state binding energy is important to test the phe- nomenologically introduced CSB (Charge Symmetry Breaking) LN interaction for A = 7, T = 1 hypernuclear systems. In addition, a peak which is interpreted as 3/2 + and 5/2 + states was measured to be B Λ = 3.65 ± 0.20 ±0.11 MeV with sufficient statistic for the first time. Only three events of the ground state of $10\atop{Λ}$ Be had been observed in the emulsion experiments. The present experiment is the first spectroscopic measurement of 10/L-Be, and the detailed structures have been successfully measured for the first time. About three times better energy resolution was achieved in the present experiment (0.78 MeV in FWHM) than that of the mirror L hy- pernucleus, $10\atop{Λ}$B (2.2 MeV in FWHM) which was measured in the (π + ,K + ) experiment at KEK. The result of the ground state binding energy was obtained to be B Λ = 8.55 ± 0.07 ± 0.11 MeV which serves also to discuss about the CSB effect in the LN interaction. $12\atop{Λ}$B has been measured with the world best energy resolution of 0:5 MeV (FWHM) among the reaction spectroscopy of L hypernuclei. The results of $12\atop{Λ}$B are compared with the experimental results in the previous experiments to confirm the consistency. Furthermore, the obtained ground state binding energies of $12\atop{Λ}$B (B Λ = 11.38 ± 0.02 ± 0.11 MeV) and $52\atop{Λ}$V (B Λ = 21.88 ± 0.59 ± 0.11 MeV) indicate that the reported value of 12/L-C which has been used as a reference of binding energy measurements for the (π + ,K + ) experiments would be shallower by ~ 0.5 MeV. A pilot study for investigation in the medium-heavy mass region with the (e,e'K + ) experiment was performed by measuring $52\atop{Λ}$V. The ground state binding energy of $52\atop{Λ}$V has been measured, overcoming high multiplicity environment. The results are discussed with the ex- perimental results of 51/L-V measured at KEK. The present result is the first measurement of L's binding energy of the ground state without the emulsion reference in the medium-heavy mass region, which could be a substantial improvement in the information needed for understanding the single particle potential of L. In the present experiment, L hypernuclear measurement with a small systematic error of ~ 0.1 MeV by the (e,e'K + ) reaction has been established. Moreover, the present work opened a door to the heavier L hypernuclear measurement with the (e,e'K + ) reaction in the future.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Novel Instrumentation for Advanced Quantum Chromodynamics Studies with Flavor Sensitivity

The true nature of ordinary matter has always fascinated humankind, whose imagination has been pointed to the right direction since the 5th century BC with the first known atomic theory by Leucippus and Democritus. They described the matter as formed by small, invisible, indivisible, and eternal particles: the atoms. A long investigation followed them, including contributions from several of history?s greatest philosophers and scientists. The progress led to the understanding that atoms have an internal structure consisting of a central nucleus composed of protons and neutrons, surrounded by a cloud of electrons. About 50 years ago, scientists discovered that nucleons also have an internal structure. Through the Deep Inelastic Scattering (DIS) experiments, on which a lepton is scattered off a nucleon, it was possible to access the distribution of partons inside the nucleon along the longitudinal direction defined by the hard-scale probe. It was a crucial step in developing Quantum Chromodynamics (QCD), currently the best theory describing the subatomic matter. Ultimately, DIS was recognized as a limited tool to investigate the nucleon structure because it is mainly sensitive to observables at the probe?s energy scale. In recent decades, theoretical developments have allowed defining soft-scale observables by measuring more complex processes. Reactions such as Semi-Inclusive Deep Inelastic Scattering (SIDIS) with single or di-hadron production, can provide information about the momentum of parton inside the nucleon. In particular, polarized SIDIS allows access to the Transverse-Momentum-Dependent (TMD) parton distributions describing the correlations of the quark and gluon degrees of freedom in transverse momentum and spin. This study can provide three-dimensional imaging of nucleon structure and inner dynamics, as long as the hadronic component in the final state can be measured. Identifying the species of the produced particles provides information on the quark flavor and assumes a crucial role in this context. The thesis describes the work carried out by the author in preparing novel instrumentation for particle identification in the final state of DIS experiments, to support modern analysis of the parton dynamics within the basic confined object (nucleon) with flavor sensitivity. The work has been focused on the CLAS12 spectrometer in operation at Jefferson Laboratory (JLab), Newport News, VA, USA, and the ePIC experiment in preparation for the future Electron-Ion Collider (EIC) at Brookhaven National Laboratory (BNL), Long Island, NY, USA. CLAS12 is a fixed-target experiment using a 12 GeV beam of polarized electrons scattering off polarized nuclear targets. In 2018 and 2022, two Ring Imaging Cherenkov (RICH) detector modules were installed to improve the ?±/K± separation in the high-momentum region (3÷8 GeV/c) of the experiment. The author contributed to the assembly, installation, and com- missioning of the second RICH module, to the efficiency studies of the first module, and to the first SIDIS analysis with high-momentum kaons identified by the RICH. These studies led to the observation of the first spin asymmetry with high-momentum kaons from the CLAS12 experiment, and an initial assessment of the systematic error associated with the hadron identification. ePIC will be the first experiment at the future EIC, the new collider designed to expand the frontiers of QCD. The author was involved in the development of the dual-radiator Ring Imaging Cherenkov (dRICH). This detector will interpolate the measurements of the Cherenkov angles of photons produced by relativistic particles crossing two different radiators to identify charged hadrons. The author contributed to the studies conducted with the dRICH prototype, developing the reconstruction and analysis software and simulations, characterizing the aerogel radiator samples, and being responsible for the tracking system used during the beam tests. The performance obtained by the prototype has been progressively improved and the results are now comparable with the expectation derived from the simulation and satisfy the requirements of the experiment. In Chapter 1, the SIDIS theory is briefly introduced, outlying the connection with the experimental measurement. Chapter 2 includes the description of the CLAS12 RICH, its assembly and installation, and the efficiency study. In Chapter 3, the analysis of the Beam-Spin Asymmetry associated with SIDIS kaons is described. Chapter 4 describes the contribution to the dRICH for EIC, starting from a description of the ePIC experiment and focusing on the studies performed for the dRICH prototype. The conclusions of this work are summarized at the end.

Vallarino, Simone↗

DOE OSTI2023

Connecting Large‐Scale Meteorological Patterns to Extratropical Cyclones in CMIP6 Climate Models Using Self‐Organizing Maps

Abstract Extratropical cyclones (ETCs) are responsible for the majority of cool‐season extreme events in the northeastern United States (NEUS), often leading to high‐impact weather conditions that can have wide‐ranging socioeconomic impacts. Evaluating the ability of climate models to adequately simulate ETC dynamics is essential for improving model performance and increasing confidence in future projections used by stakeholders and policymakers. ETCs are traditionally studied using techniques such as case studies and synoptic typing, however, these approaches can be time‐consuming, require subjective analysis, and do not necessarily identify the coincident large‐scale meteorological patterns (LSMPs). Here, we apply self‐organizing maps (SOMs) as an automated machine‐learning approach to characterize the LSMPs and associated frequency and intensity of discrete ETC events over NEUS. The dominant patterns of geopotential height variability are identified through SOM analysis of five reanalysis products during the last four decades. ETC events are tracked using TempestExtremes and are integrated with SOMs to classify the accumulated cyclone activity (ACA) associated with each pattern. We then evaluate the skill of CMIP6 historical experiments in simulating the LSMPs and ETC events identified in the SOM. Our results identify a robust bias toward more zonal patterns, with models struggling to reproduce the more amplified patterns typically associated with the highest cyclone activity. While model resolution has some impact on simulation credibility, model configuration appears to be more important in LSMP representation. The vast majority of CMIP6 models produce too few ETCs, although model errors are distributed around historical reanalyses when ACA is normalized by storm frequency.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

TH-AB-202-08: A Robust Real-Time Surface Reconstruction Method On Point Clouds Captured From a 3D Surface Photogrammetry System

Purpose: Surface photogrammetry (e.g. VisionRT, C-Rad) provides a noninvasive way to obtain high-frequency measurement for patient motion monitoring in radiotherapy. This work aims to develop a real-time surface reconstruction method on the acquired point clouds, whose acquisitions are subject to noise and missing measurements. In contrast to existing surface reconstruction methods that are usually computationally expensive, the proposed method reconstructs continuous surfaces with comparable accuracy in real-time. Methods: The key idea in our method is to solve and propagate a sparse linear relationship from the point cloud (measurement) manifold to the surface (reconstruction) manifold, taking advantage of the similarity in local geometric topology in both manifolds. With consistent point cloud acquisition, we propose a sparse regression (SR) model to directly approximate the target point cloud as a sparse linear combination from the training set, building the point correspondences by the iterative closest point (ICP) method. To accommodate changing noise levels and/or presence of inconsistent occlusions, we further propose a modified sparse regression (MSR) model to account for the large and sparse error built by ICP, with a Laplacian prior. We evaluated our method on both clinical acquired point clouds under consistent conditions and simulated point clouds with inconsistent occlusions. The reconstruction accuracy was evaluated w.r.t. root-mean-squared-error, by comparing the reconstructed surfaces against those from the variational reconstruction method. Results: On clinical point clouds, both the SR and MSR models achieved sub-millimeter accuracy, with mean reconstruction time reduced from 82.23 seconds to 0.52 seconds and 0.94 seconds, respectively. On simulated point cloud with inconsistent occlusions, the MSR model has demonstrated its advantage in achieving consistent performance despite the introduced occlusions. Conclusion: We have developed a real-time and robust surface reconstruction method on point clouds acquired by photogrammetry systems. It serves an important enabling step for real-time motion tracking in radiotherapy. This work is supported in part by NIH grant R01 CA169102-02.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

WE-G-BRD-01: A Data-Driven 4D-MRI Motion Model to Estimate Full Field-Of-View Abdominal Motion From 2D Image Navigators During MR-Linac Treatment

Purpose: To estimate full field-of-view abdominal respiratory motion from fast 2D image navigators using a 4D-MRI based motion model. This will allow for radiation dose accumulation mapping during MR-Linac treatment. Methods: Experiments were conducted on a Philips Ingenia 1.5T MRI. First, a retrospectively ordered 4D-MRI was constructed using 3D transient-bSSFP with radial in-plane sampling. Motion fields were calculated through 3D non-rigid registration. From these motion fields a PCA-based abdominal motion model was constructed and used to warp a 3D reference volume to fast 2D cine-MR image navigators that can be used for real-time tracking. To test this procedure, a time-series consisting of two interleaved orthogonal slices (sagittal and coronal), positioned on the pancreas or kidneys, were acquired for 1m38s (dynamic scan-time=0.196ms), during normal, shallow, or deep breathing. The coronal slices were used to update the optimal weights for the first two PCA components, in order to warp the 3D reference image and construct a dynamic 4D-MRI time-series. The interleaved sagittal slices served as an independent measure to test the model’s accuracy and fit. Spatial maps of the root-mean-squared error (RMSE) and histograms of the motion differences within the pancreas and kidneys were used to evaluate the method. Results: Cranio-caudal motion was accurately calculated within the pancreas using the model for normal and shallow breathing with an RMSE of 1.6mm and 1.5mm and a histogram median and standard deviation below 0.2 and 1.7mm, respectively. For deep-breathing an underestimation of the inhale amplitude was observed (RMSE=4.1mm). Respiratory-induced antero-posterior and lateral motion were correctly mapped (RMSE=0.6/0.5mm). Kidney motion demonstrated good motion estimation with RMSE-values of 0.95 and 2.4mm for the right and left kidney, respectively. Conclusion: We have demonstrated a method that can calculate dynamic 3D abdominal motion in a large volume, while acquiring real-time cine-MR images for MR-guided radiotherapy.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2018

A Minimum Variance Algorithm for Overdetermined TOA Equations with an Altitude Constraint.

We present a direct (non-iterative) method for solving for the location of a radio frequency (RF) emitter, or an RF navigation receiver, using four or more time of arrival (TOA) measurements and an assumed altitude above an ellipsoidal earth. Both the emitter tracking problem and the navigation application are governed by the same equations, but with slightly different interpreta- tions of several variables. We treat the assumed altitude as a soft constraint, with a specified noise level, just as the TOA measurements are handled, with their respective noise levels. With 4 or more TOA measurements and the assumed altitude, the problem is overdetermined and is solved in the weighted least squares sense for the 4 unknowns, the 3-dimensional position and time. We call the new technique the TAQMV (TOA Altitude Quartic Minimum Variance) algorithm, and it achieves the minimum possible error variance for given levels of TOA and altitude estimate noise. The method algebraically produces four solutions, the least-squares solution, and potentially three other low residual solutions, if they exist. In the lightly overdermined cases where multiple local minima in the residual error surface are more likely to occur, this algebraic approach can produce all of the minima even when an iterative approach fails to converge. Algorithm performance in terms of solution error variance and divergence rate for bas eline (iterative) and proposed approach are given in tables.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

TH-EF-BRB-08: Robotic Motion Compensation for Radiation Therapy: A 6DOF Phantom Study

Purpose: The high accuracy of frame-based stereotactic radiosurgery (SRS), which uses a rigid frame fixed to the patient’s skull, is offset by potential drawbacks of poor patient compliance and clinical workflow restrictions. Recent research into frameless SRS has so far resulted in reduced accuracy. In this study, we investigate the use of a novel 6 degree-of-freedom (6DOF) robotic head motion cancellation system that continuously detects and compensates for patient head motions during a SRS delivery. This approach has the potential to reduce invasiveness while still achieving accuracies better or equal to traditional frame-based SRS. Methods: A 6DOF parallel kinematics robotics stage was constructed, and controlled using an inverse kinematics-based motion compensation algorithm. A 6DOF stereoscopic infrared (IR) marker tracking system was used to monitor real-time motions at sub-millimeter and sub-degree levels. A novel 6DOF calibration technique was first applied to properly orient the camera coordinate frame to match that of the LINAC and robotic control frames. Simulated head motions were measured by the system, and the robotic stage responded to these 6DOF motions automatically, returning the reflective marker coordinate frame to its original position. Results: After the motions were introduced to the system in the phantom-based study, the robotic stage automatically and rapidly returned the phantom to LINAC isocenter. When errors exceeded the compensation lower threshold of 0.25 mm or 0.25 degrees, the system registered the 6DOF error and generated a cancellation trajectory. The system responded in less than 0.5 seconds and returned all axes to less than 0.1 mm and 0.1 degree after the 6DOF compensation was performed. Conclusion: The 6DOF real-time motion cancellation system was found to be effective at compensating for translational and rotational motions to current SRS requirements. This system can improve frameless SRS by automatically returning patients to isocenter with high 6DOF accuracy.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Vehicle Position Detection Based on Machine Learning Algorithms in Dynamic Wireless Charging

Dynamic wireless charging (DWC) has emerged as a viable approach to mitigate range anxiety by ensuring continuous and uninterrupted charging for electric vehicles in motion. DWC systems rely on the length of the transmitter, which can be categorized into long-track transmitters and segmented coil arrays. The segmented coil array, favored for its heightened efficiency and reduced electromagnetic interference, stands out as the preferred option. However, in such DWC systems, the need arises to detect the vehicle’s position, specifically to activate the transmitter coils aligned with the receiver pad and de-energize uncoupled transmitter coils. This paper introduces various machine learning algorithms for precise vehicle position determination, accommodating diverse ground clearances of electric vehicles and various speeds. Through testing eight different machine learning algorithms and comparing the results, the random forest algorithm emerged as superior, displaying the lowest error in predicting the actual position.

47 OTHER INSTRUMENTATION↗

DOE OSTI2019

Machine Learning for Solar Technology Portfolio Management

Technology readiness level (TRL) labeling and forecasting today is done entirely manually. A computationally-assisted model of a TRL-like classification for estimation and tracking could enable a research and development (R&D) portfolio manager to more accurately estimate the relative level of development for technologies in that portfolio. This report describes the work to understand readiness level systems, train a machine learning algorithm to recognize textual indicators of particular readiness levels within written material from carefully chosen case studies in renewable technology development, and apply that algorithm to predict the readiness levels of other technology development cases. We account for the results of each step of the work conducted, including the predictive accuracy of the trained model: 54% correct, within a +/-1 readiness level error threshold and a root mean squared error of 1.88. Great potential remains to improve and apply this model for management of individual projects and across portfolios.

14 SOLAR ENERGY↗

DOE OSTI2019

Machine Learning for Solar Technology Portfolio Management

14 SOLAR ENERGY↗

DOE OSTI2016

A TRACER METHOD FOR COMPUTING TYPE IA SUPERNOVA YIELDS: BURNING MODEL CALIBRATION, RECONSTRUCTION OF THICKENED FLAMES, AND VERIFICATION FOR PLANAR DETONATIONS

We refine our previously introduced parameterized model for explosive carbon–oxygen fusion during thermonuclear Type Ia supernovae (SNe Ia) by adding corrections to post-processing of recorded Lagrangian fluid-element histories to obtain more accurate isotopic yields. Deflagration and detonation products are verified for propagation in a medium of uniform density. A new method is introduced for reconstructing the temperature–density history within the artificially thick model deflagration front. We obtain better than 5% consistency between the electron capture computed by the burning model and yields from post-processing. For detonations, we compare to a benchmark calculation of the structure of driven steady-state planar detonations performed with a large nuclear reaction network and error-controlled integration. We verify that, for steady-state planar detonations down to a density of 5 × 10{sup 6} g cm{sup −3}, our post-processing matches the major abundances in the benchmark solution typically to better than 10% for times greater than 0.01 s after the passage of the shock front. As a test case to demonstrate the method, presented here with post-processing for the first time, we perform a two-dimensional simulation of a SN Ia in the scenario of a Chandrasekhar-mass deflagration–detonation transition (DDT). We find that reconstruction of deflagration tracks leads to slightly more complete silicon burning than without reconstruction. The resulting abundance structure of the ejecta is consistent with inferences from spectroscopic studies of observed SNe Ia. We confirm the absence of a central region of stable Fe-group material for the multi-dimensional DDT scenario. Detailed isotopic yields are tabulated and change only modestly when using deflagration reconstruction.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2014

Eye Gaze Tracking using Correlation Filters

In this paper, we studied a method for eye gaze tracking that provide gaze estimation from a standard webcam with a zoom lens and reduce the setup and calibration requirements for new users. Specifically, we have developed a gaze estimation method based on the relative locations of points on the top of the eyelid and eye corners. Gaze estimation method in this paper is based on the distances between top point of the eyelid and eye corner detected by the correlation filters. Advanced correlation filters were found to provide facial landmark detections that are accurate enough to determine the subjects gaze direction up to angle of approximately 4-5 degrees although calibration errors often produce a larger overall shift in the estimates. This is approximately a circle of diameter 2 inches for a screen that is arm s length from the subject. At this accuracy it is possible to figure out what regions of text or images the subject is looking but it falls short of being able to determine which word the subject has looked at.

Karakaya, Mahmut↗

DOE OSTI2022

Comparison of Motion Analysis Systems in Tracking Upper Body Movement of Myoelectric Bypass Prosthesis Users

Current literature lacks a comparative analysis of different motion capture systems for tracking upper limb (UL) movement as individuals perform standard tasks. To better understand the performance of various motion capture systems in quantifying UL movement in the prosthesis user population, this study compares joint angles derived from three systems that vary in cost and motion capture mechanisms: a marker-based system (Vicon), an inertial measurement unit system (Xsens), and a markerless system (Kinect). Ten healthy participants (5F/5M; 29.6 ± 7.1 years) were trained with a TouchBionic i-Limb Ultra myoelectric terminal device mounted on a bypass prosthetic device. Participants were simultaneously recorded with all systems as they performed standardized tasks. Root mean square error and bias values for degrees of freedom in the right elbow, shoulder, neck, and torso were calculated. The IMU system yielded more accurate kinematics for shoulder, neck, and torso angles while the markerless system performed better for the elbow angles. By evaluating the ability of each system to capture kinematic changes of simulated upper limb prosthesis users during a variety of standardized tasks, this study provides insight into the advantages and limitations of using different motion capture technologies for upper limb functional assessment.

42 ENGINEERING↗

DOE OSTI2012

Dosimetric and deformation effects of image-guided interventions during stereotactic body radiation therapy of the prostate using an endorectal balloon

Purpose: During stereotactic body radiation therapy (SBRT) for the treatment of prostate cancer, an inflatable endorectal balloon (ERB) may be used to reduce motion of the target and reduce the dose to the posterior rectal wall. This work assessed the dosimetric impact of manual interventions on ERB position in patients receiving prostate SBRT and investigated the impact of ERB interventions on prostate shape. Methods: The data of seven consecutive patients receiving SBRT for the treatment of clinical stage T1cN0M0 prostate cancer enrolled in a multi-institutional, IRB-approved trial were analyzed. The SBRT dose was 50 Gy in five fractions to a planning target volume (PTV) that included the prostate (implanted with three fiducial markers) with a 3-5 mm margin. All plans were based on simulation images that included an ERB inflated with 60 cm{sup 3} of air. Daily kilovoltage cone-beam computed tomography (CBCT) imaging was performed to localize the PTV, and an automated fusion with the planning images yielded displacements required for PTV relocalization. When the ERB volume and/or position were judged to yield inaccurate repositioning, manual adjustment (ERB reinflation and/or repositioning) was performed. Based on all 59 CBCT image sets acquired, a deformable registration algorithm was used to determine the dose received by, displacement of, and deformation of the prostate, bladder (BLA), and anterior rectal wall (ARW). This dose tracking methodology was applied to images taken before and after manual adjustment of the ERB (intervention), and the delivered dose was compared to that which would have been delivered in the absence of intervention. Results: Interventions occurred in 24 out of 35 (69%) of the treated fractions. The direct effect of these interventions was an increase in the prostate radiation dose that included 95% of the PTV (D95) from 9.6 {+-} 1.0 to 10.0 {+-} 0.2 Gy (p = 0.06) and an increase in prostate coverage from 94.0% {+-} 8.5% to 97.8% {+-} 1.9% (p = 0.03). Additionally, ERB interventions reduced prostate deformation in the anterior-posterior (AP) direction, reduced errors in the sagittal rotation of the prostate, and increased the similarity in shape of the prostate to the radiotherapy plan (increased Dice coefficient from 0.76 {+-} 0.06 to 0.80 {+-} 0.04, p = 0.01). Postintervention decreases in prostate volume receiving less than the prescribed dose and decreases in the voxel-wise displacement of the prostate, bladder, and anterior rectal wall were observed, which resulted in improved dose-volume histogram (DVH) characteristics. Conclusions: Image-guided interventions in ERB volume and/or position during prostate SBRT were necessary to ensure the delivery of the dose distribution as planned. ERB interventions resulted in reductions in prostate deformations that would have prevented accurate localization of patient anatomy.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

The Second Skin: A Wearable Sensor Suite that Enables Real-Time Human Biomechanics Tracking Through Deep Learning

Objective: Real-time determination of human kinematics and kinetics could advance biomechanics research and enable valuable applications of biofeedback and generalizable exoskeleton control. Here, this work aims to investigate a taskindependent, user-independent method for obtaining precise realtime joint state estimation across lower-body joints during a wide variety of tasks. Methods: We developed a generalizable sensing approach using a suit comprised of inertial measurement units (IMUs) and pressure insoles. With the suit, we collected a dataset of 33 tasks commonly performed during construction and hazardous waste cleanup (N = 10). We then trained deep learning user-independent, task-agnostic models to estimate joint lowerbody kinematics and dynamics using only worn sensor data. We likewise computed joint kinematics and dynamics analytically from sensor data to serve as a comparison tool for model results. Results: Our models achieved overall angle estimation root-meansquared-errors (RMSE) of 6.56±.92°, 8.60±1.01°, 7.58±.89°, and 6.00±.73° compared to 13.9±.1.3°, 15.31±1.0°, 10.76±.70°, and 7.56±.48° via analytical methods at the lower back, hip, knee, and ankle, respectively. Likewise, our models achieved overall normalized moment estimation RMSEs of .207±.069 Nm/kg, .242±.044 Nm/kg, .202±.038 Nm/kg, and .193±.034 Nm/kg compared to .306±.036 Nm/kg, .407±.021 Nm/kg, 1.18 ±.022 Nm/kg, and 1.73±.071 Nm/kg via analytical methods at the lower back, hip, knee, and ankle, respectively. Conclusion: These results are comparable to other state-of-the-art wearable sensing systems, establishing deep learning as a viable sensing approach that generalizes to new users and tasks. Significance: This work shows promise for enabling accurate real-world biomechanical data collection and enhancement of biofeedback systems and wearable robot control.

Casey, Ryan T. F. [Georgia Institute of Technology↗

DOE OSTI2020

A control-oriented combustion model framework for compression ignition engines operating on low-reactivity fuel

This work focuses on zero-dimensional modeling of the heat release rate in a compression ignition engine operating on gasoline-like fuels. Due to the properties of gasoline, such as high volatility and longer ignition delay than diesel, the injection strategies can vary significantly from the operation with conventional diesel fuel. Different injection strategies are commonly used to achieve varying degrees of in-cylinder stratification in order to shape the combustion event and maximize efficiency. The proposed zero-dimensional combustion model was developed to account for the different stages in combustion caused by the fuel stratification. As the ignition delay model is an integral part of the entire combustion process and significantly affects the prediction accuracy, special attention has been paid to local phenomena influencing ignition delay. A one-dimensional spray model by Musculus and Kattke was employed in conjunction with a Lagrangian tracking approach in order to estimate the local air–fuel ratio within the spray tip, as a proxy for reactivity. The local air–fuel ratio, in-cylinder temperature and pressure were used in an integral fashion to estimate the ignition delay. Heat release rates were modeled using first-order non-linear differential equations. The proposed combustion model was validated against experimental data of a heavy-duty compression ignition engine with up to three injection events at mostly 1038 r/min and 14 bar brake mean effective pressure. Further validation of the model was carried out at other engine loads and speeds. Model prediction errors in CA50 of less than 1 °CA across all conditions were found. Modeling results of other combustion metrics such as combustion duration and indicated mean effective pressure are also highly satisfactory. In addition, the model has been shown to be capable of estimating the ringing intensity for most conditions.

Pamminger, Michael↗

DOE OSTI2013

BioWatch Sample Management System (SMS) Field Operator Guide

The BioWatch Sample Management System is software developed by Los Alamos National Laboratory to support the Department of Homeland Security BioWatch program. Field Operators use the software to keep track of samples and to provide information on the sample management process to other users and software programs within BioWatch. The information tracked about a sample includes the date and time the filter media is assembled in a filter holder, deployed to the field, placed in and removed from a collector, and received from the field, and identifies who performs each task. Field Operators can also use the software to prepare and print forms to document the chain-of-custody transfer of the samples. The BioWatch SMS Field Operator Guide provides easy-to-understand procedures for each task a Field Operator performs. This guide gives basic information about using the computer and other equipment, instructions about checking and editing data, and provides reference information, including appendices of error messages and solutions, words used interchangeably, and safety warnings plus a glossary and an index.

99 GENERAL AND MISCELLANEOUS↗