Characterization of Gradient Index optical components using Experimental Ray Tracing
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Optics and optical instruments↗
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TU-PIS-Exhibit Hall-1: Tools for Collecting and Analyzing Patient Dose Index Information from Imaging Equipment
The current clinical standard of organ respiratory imaging, 4D-CT, is fundamentally limited by poor soft-tissue contrast and imaging dose. These limitations are potential barriers to beneficial “4D” radiotherapy methods which optimize the target and OAR dose-volume considering breathing motion but rely on a robust motion characterization. Conversely, MRI imparts no known radiation risk and has excellent soft-tissue contrast. MRI-based motion management is therefore highly desirable and holds great promise to improve radiotherapy of moving cancers, particularly in the abdomen. Over the past decade, MRI techniques have improved significantly, making MR-based motion management clinically feasible. For example, cine MRI has high temporal resolution up to 10 f/s and has been used to track and/or characterize tumor motion, study correlation between external and internal motions. New MR technologies, such as 4D-MRI and MRI hybrid treatment machines (i.e. MR-linac or MR-Co60), have been recently developed. These technologies can lead to more accurate target volume determination and more precise radiation dose delivery via direct tumor gating or tracking. Despite all these promises, great challenges exist and the achievable clinical benefit of MRI-based tumor motion management has yet to be fully explored, much less realized. In this proposal, we will review novel MR-based motion management methods and technologies, the state-of-the-art concerning MRI development and clinical application and the barriers to more widespread adoption. Learning Objectives: Discuss the need of MR-based motion management for improving patient care in radiotherapy. Understand MR techniques for motion imaging and tumor motion characterization. Understand the current state of the art and future steps for clinical integration. Henry Ford Health System holds research agreements with Philips Healthcare. Research sponsored in part by a Henry Ford Health System Internal Mentored Grant.
60 APPLIED LIFE SCIENCES↗
TU-H-CAMPUS-TeP2-02: FLASH Irradiation Improves the Therapeutic Index Following GI Tract Irradiation
Purpose: To investigate and characterize the radiobiological effectiveness of very high dose rate radiotherapy (FLASH) compared to conventional irradiation in an in vivo model. Methods: The gastrointestinal (GI) tract of C57BL/6 mice were irradiated with doses ranging between 10 and 18 Gy using a custom stereotactic jig. A Varian Clinac 21EX was modified to allow dose rates ranging from 0.05 to 240 Gy/s at the position of the mirror. With the gantry at 180 degrees, the jig holding the individual animals was placed above the mirror to take advantage of the reduced source to target distance. Mice were irradiated with 20MeV electrons. Following irradiation, the mice were monitored twice daily for morbidity and daily for weight changes. Results: Mice irradiated with FLASH irradiation had lower weight loss compared to the mice receiving conventional irradiation. Following FLASH irradiation, a maximum weight loss of ∼20% was observed at day 6 with subsequent recovery, while following conventional irradiation, higher weight losses was observed with fewer instances of recovery. Concerning survival, all mice in the conventionally irradiated groups had a 100% mortality in the range of 15.5–18 Gy, while the mice irradiated with FLASH irradiation had a 100% survival in the same range. Conclusion: These results have demonstrated proof of principle that FLASH irradiations have a dramatic impact on the overall survival of mice following GI tract irradiations. If the increase in the therapeutic window can be validated and understood, this would revolutionize the field of radiation oncology and lead to increased cure rates with reduced side effects following treatment, resulting in increased quality of life for cancer survivors. Funding: DoD, Award#:W81XWH-14-1-0014, Weston Havens Foundation, Bio-X (Stanford University), the Office of the Dean of the Medical School, the Office of the Provost (Stanford University), and the Swedish Childhood Cancer Foundation; BL and PM are founders of TibaRay,Inc.; BL and PM have received research grants from Varian and RaySearch Laboratory.
60 APPLIED LIFE SCIENCES↗
Index theorem for non-supersymmetric fermions coupled to a non-Abelian string and electric charge quantization
Not provided.
Astronomy & Astrophysics↗
CDC-TMVI Dashboard: Contamination Distribution Centered Toxics Mobility Vulnerability Index
Visualizes census-tract-level vulnerability across 27 geospatial variables in four domains: built environment vulnerability, social vulnerability, health outcomes, and contamination sources
Newman, G.↗
Energy Supply Security Index (eesi) v0.1.0
This software computes different metrics that quantify energy supply security. It computes metrics for the amount of energy self-production, autonomy, system adequacy, self-sufficiency and autarky. The software has been developed to compute metrics that are introduced in a journal manuscript, and the software is intended to be published to make the underlying metric calculation accessible and reproducible to the reader of the article. Potential use of the software is for policymakers, energy planners and researchers to guide energy system infrastructure decisions.
Sulzer, Matthias [Swiss Federal Laboratories for M↗
Extension of Complex Refractive Index Measurements to the Near-Infrared for Liquids: Methodology and Uncertainty Analysis
Optical identification of liquid droplets, aerosols, or thin films is important for many applications. While reference spectra are sometimes available for such measurements, they are not always applicable to the observed spectrum or the given sample morphology. Reference spectra for many forms can be modeled, however, if the n/k vectors (real and imaginary refractive indices) are available. In previous work we have reported protocols to determine the n/k vectors for dozens of liquids, primarily in the mid-infrared (MIR) spectral range from 7500 to 400 cm –1 . In this work we extend the spectral range into the near-infrared (NIR) region, demonstrating a method to measure and merge the data sets to create composite n/k data ranging from 10 000 to 400 cm –1 (1.0 to 25 µm) with absorbance fidelity spanning over four orders of magnitude, and vastly improved signal-to-noise in the NIR. The precision of the composite data is evaluated for three different liquids, focusing primarily on the steps for converting the raw absorbance spectra to k values. The variability in both MIR and NIR data as well as in the final n/k vectors is also investigated for several liquids. For typical liquids, the overall variability (reported as 2σ) in the final n and k-vectors is determined to be ∼0.4% and 3%, respectively. Finally, the derived n/k data are used to calculate absorbance spectra for aerosol droplets, showing marginal variability due to the typical measurement errors in the final n/k vectors.
47 OTHER INSTRUMENTATION↗
Method for transient modulation of refractive index under exposure to high power laser pulses
Abstract not provided
42 ENGINEERING↗
High refractive index Fresnel lens on a fiber fabricated by nanoimprint lithography for immersion applications
Not Available
Koshelev, Alexander↗
Body Mass Index at Accession and Incident Cardiometabolic Risk Factors in US Army Soldiers, 2001–2011
Individuals entering US Army service are generally young and healthy, but many are overweight, which may impact cardiometabolic risk despite physical activity and fitness requirements. This analysis examines the association between Soldiers’ BMI at accession and incident cardiometabolic risk factors (CRF) using longitudinal data from 731,014 Soldiers (17.0% female; age: 21.6 [3.9] years; BMI: 24.7 [3.8] kg/m 2 ) who were assessed at Army accession, 2001–2011. CRF were defined as incident diagnoses through 2011, by ICD-9 code, of metabolic syndrome, glucose/insulin disorder, hypertension, dyslipidemia, or overweight/obesity (in those not initially overweight/obese). Multivariable-adjusted proportional hazards models were used to estimate hazard ratios (HR) and 95% confidence intervals (CI) between BMI categories at accession and CRF. Initially underweight (BMI<18.5 kg/m 2 ) were 2.4% of Soldiers, 53.5% were normal weight (18.5-<25), 34.2% were overweight (25-<30), and 10.0% were obese (≥30). Mean age range at CRF diagnosis was 24–29 years old, with generally low CRF incidence: 228 with metabolic syndrome, 3,880 with a glucose/insulin disorder, 26,373 with hypertension, and 13,404 with dyslipidemia. Of the Soldiers who were not overweight or obese at accession, 5,361 were eventually diagnosed as overweight or obese. Relative to Soldiers who were normal weight at accession, those who were overweight or obese, respectively, had significantly higher risk of developing each CRF after multivariable adjustment (HR [95% CI]: metabolic syndrome: 4.13 [2.87–5.94], 13.36 [9.00–19.83]; glucose/insulin disorder: 1.39 [1.30–1.50], 2.76 [2.52–3.04]; hypertension: 1.85 [1.80–1.90], 3.31 [3.20–3.42]; dyslipidemia: 1.81 [1.75–1.89], 3.19 [3.04–3.35]). Risk of hypertension, dyslipidemia, and overweight/obesity in initially underweight Soldiers was 40%, 31%, and 79% lower, respectively, versus normal-weight Soldiers. BMI in early adulthood has important implications for cardiometabolic health, even within young, physically active populations.
60 APPLIED LIFE SCIENCES↗
Alternate Procedures for Swell Index Testing of Granular Bentonite from GCLs
Not provided.
Engineering↗
Cyber Protection and Resilience Index: An Indicator of an Organization's Cyber Protection and Resilience Program
In 2014, the U.S. Department of Homeland Security (DHS) and its Cyber Security Advisors (CSAs) began surveying critical infrastructure by using the Cyber Infrastructure Survey Tool (C-IST). The collected information is specific to an organization’s cyber protection and resilience program on a critical cyber service (CCS), which includes management, personnel, controls, incident response, and cyber dependencies.
45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
Adaptive multi-index collocation for uncertainty quantification and sensitivity analysis
In this paper, we present an adaptive algorithm to construct response surface approximations of high-fidelity models using a hierarchy of lower fidelity models. Our algorithm is based on multiindex stochastic collocation and automatically balances physical discretization error and response surface error to construct an approximation of model outputs. This surrogate can be used for uncertainty quantification (UQ) and sensitivity analysis (SA) at a fraction of the cost of a purely high-fidelity approach. We demonstrate the effectiveness of our algorithm on a canonical test problem from the UQ literature and a complex multi-physics model that simulates the performance of an integrated nozzle for an unmanned aerospace vehicle. We find that when the input-output response is sufficiently smooth our algorithm produces approximations that can be up to orders of magnitude more accurate than single fidelity approximations for a fixed computational budget.
97 MATHEMATICS AND COMPUTING↗
Designing a dynamic vulnerability index to COVID-19 for New Mexico, USA
Motivation: Non-congregational shelters are a place where COVID-19 patients can quarantine away from their household until recovered. NM wants to establish non-congregational shelters for COVID-19 patients and first responders; Where? How many rooms? Create a decision support tool to assess which counties have the most vulnerable population to COVID-19; Socioeconomic status, community practices.
60 APPLIED LIFE SCIENCES↗
PV Fleet Performance Data Initiative: Performance Index-Based Analysis
In this analysis, we report on 250 PV systems throughout the US, comprising 157 MWdc of system capacity and over 10,000 monthly PI values based on high-frequency (subhourly) energy data and satellite-based resource data. The distribution of PI values is analyzed, and multiple causes of underperformance are assessed, including first-year startup issues, snowfall and inverter downtime. An initial distribution of raw monthly PI values was collected with mean measured / modeled performance of PI = 0.935. After correcting for the three identifiable loss factors mentioned above, an average monthly performance of PI = 0.994 was obtained, with a distribution closely following a Gumbel Extreme Value distribution. In particular, inverter availability was found to contribute a system energy loss of 2.3% on average, except in the first six months of operation when availability losses are closer to 8%. Other startup issues beyond inverter downtime such as partial string outage contributed an additional 5% underperformance in the first year of operation across the fleet. Winter performance was also found to be 5%-10% below summer performance on average, likely due to snowfall. A simple linear relationship was found between snow loss and monthly snowfall accumulation in cm, indicating between 6% - 40% loss in months with nonzero snowfall, depending on climate.
14 SOLAR ENERGY↗