Development of a telescope for medium-energy gamma-ray astronomy

The Advanced Energetic Pair Telescope (AdEPT) is being developed at GSFC as a future NASA MIDEX mission to explore the medium-energy (5–200 MeV) gamma-ray range. The enabling technology for AdEPT is the Three- Dimensional Track Imager (3-DTI), a gaseous time projection chamber. The high spatial resolution 3-D electron tracking of 3-DTI enables AdEPT to achieve high angular resolution gamma-ray imaging via pair production and triplet production (pair production on electrons) in the medium-energy range. The low density and high spatial resolution of 3-DTI allows the electron positron track directions to be measured before they are dominated by Coulomb scattering. Further, the significant reduction of Coulomb scattering allows AdEPT to be the first medium-energy gamma-ray telescope to have high gamma-ray polarization sensitivity. We review the science goals that can be addressed with a medium-energy pair telescope, how these goals drive the telescope design, and the realization of this design with AdEPT. The AdEPT telescope for a future MIDEX mission is envisioned as a 8 m3 active volume filled with argon at 2 atm. The design and performance of the 3-DTI detectors for the AdEPT telescope are described as well as the outstanding instrument challenges that need to be met for the AdEPT mission

A pair production telescope for medium-energy gamma-ray polarimetry

We describe the science motivation and development of a pair production telescope for medium-energy (∼5–200 MeV) gamma-ray polarimetry. Our instrument concept, the Advanced Energetic Pair Telescope (AdEPT), takes advantage of the Three-Dimensional Track Imager, a low-density gaseous time projection chamber, to achieve angular resolution within a factor of two of the pair production kinematics limit (∼0.6° at 70 MeV), continuum sensitivity comparable with the Fermi-LAT front detector (<3 × 10−6 MeV cm−2 s−1 at 70 MeV), and minimum detectable polarization less than 10% for a 10 mCrab source in 106 s.submittedVersionFil: Hunter, Stanley D. National Aeronautics and Space Administration. Goddard Space Flight Center; Estados Unidos de América.Fil: Bloser, Peter F. University of New Hampshire. Institute for the Study of Earth, Oceans, and Space. Space Science Center; Estados Unidos de América.Fil: Depaola, Gerardo Osvaldo. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; Argentina.Fil: Dion, Michael P. Department of Energy. Office of Science. Pacific Northwest National Laboratory; Estados Unidos de América.Fil: DeNolfo, Georgia A. National Aeronautics and Space Administration. Goddard Space Flight Center; Estados Unidos de América.Fil: Hanu, Andrei. National Aeronautics and Space Administration. Goddard Space Flight Center; Estados Unidos de América.Fil: Iparraguirre, Lorenzo Marcos. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; Argentina.Fil: Legere, Jason. University of New Hampshire. Institute for the Study of Earth, Oceans, and Space. Space Science Center; Estados Unidos de América.Fil: Longo, Francesco. Università Degli Studi de Trieste. Dipartimento di fisica; Italia.Fil: McConnell, Mark L. University of New Hampshire. Institute for the Study of Earth, Oceans, and Space. Space Science Center; Estados Unidos de América.Fil: Nowicki, Suzanne F. National Aeronautics and Space Administration. Goddard Space Flight Center; Estados Unidos de América.Fil: Nowicki, Suzanne F. University of Maryland, Baltimore County. Department of Physics; Estados Unidos de América.Fil: Ryan, James M. University of New Hampshire. Institute for the Study of Earth, Oceans, and Space. Space Science Center; Estados Unidos de América.Fil: Son, Seunghee. National Aeronautics and Space Administration. Goddard Space Flight Center; Estados Unidos de América.Fil: Son, Seunghee. University of Maryland, Baltimore County. Department of Physics; Estados Unidos de América.Fil: Stecker, Floyd W. National Aeronautics and Space Administration. Goddard Space Flight Center; Estados Unidos de América.Física de Partículas y Campo

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Design and baseline characteristics of the finerenone in reducing cardiovascular mortality and morbidity in diabetic kidney disease trial

Background: Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. Patients and Methods: The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate >= 25 mL/min/1.73 m(2) and albuminuria (urinary albumin-to-creatinine ratio >= 30 to <= 5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level alpha = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. Conclusions: FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049

Development of the Next Generation High-Sensitivity CdZnTe Imaging Gamma-Ray Spectrometer for Planetary Science Applications.

The Probing In situ with Neutrons and Gamma-rays (PING) instrument, developed at NASA Goddard Space Flight Center (GSFC) by the neutron/gamma-ray group, is a technology used to determine the subsurface elemental composition of a planet. It uses a pulsed neutron generator to excite the solid materials of a planet and measures the resulting neutron and gamma-ray emissions with its detector system. A key objective of NASA is to develop instruments with reduced mass, volume and power consumption. The NASA GSFC neutron/gamma-ray group is currently developing the Imaging Gamma-Ray Spectrometer (IGS), the next generation light and compact high resolution and sensitivity instrument on PING. The spectroscopic and imaging performance of pixelated CdZnTe detectors as the innovative technology for IGS were investigated. This work has shown that pixelated CdZnTe detectors have the advantages of high-resolution spectroscopic performance, room-temperature operation thus eliminating the need for a cryogenic cooler, and Compton imaging capabilities to reject secondary gamma rays originating from the spacecraft or environment. The spectroscopic performance of a large volume single crystal pixelated CdZnTe detector showed a single pixel energy resolution of 1.4% FWHM at 662 keV. Imaging methods were developed in this study to reject gamma rays from a source placed above the detectors using Compton imaging techniques: the full-energy Compton rejection method and the imaging ratio method. Simulations have demonstrated that with the imaging ratio method, it is possible to reject a significant fraction of the gamma rays coming from a point source above the detectors thus increasing the sensitivity of the measurement to the planet surface below.PHDApplied PhysicsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/97872/1/snowicki_1.pd

Multi-Sensor Optimal Motion Planning for Radiological Contamination Surveys by Using Prediction-Difference Maps

Distributed and networked mobile sensor platforms using unmanned aerial and/or ground vehicles to survey areas of interest offer a safer and more efficient method for radiological contamination mapping; however, most applications rely on uniformly sweeping of the area in a raster-type motion without utilizing the information available in a dynamic sense. We have developed a fully autonomous optimal motion planning procedure for networks with two or more mobile sensors. The procedure utilizes well-established concepts of Gaussian processes in combination with control laws based on centroidal Voronoi tessellations to achieve optimal next-iteration sensor movements. A new method of informing optimal motion planning is proposed, whereby the absolute difference between the prior and current full-map prediction, referred to as the prediction-difference map, is used as the spatial density function within each Voronoi cell, providing immediate and iterative feedback for dynamic use of available information. The Gaussian process regression model used to estimate the contamination in unvisited locations also provides prediction uncertainties, and can be used as a quantitative metric to assess the confidence in the calculated contamination map; these estimates and prediction uncertainties are unavailable for standard uniform survey routines as they can only produce maps in the vicinity of observed locations. We present through simulation the achievable performance gains from using this new method by directly comparing to a uniform survey method. Results show that using the prediction-difference maps to inform motion planning procedures offers a faster rate of producing an accurate and convergent map relative to a uniform survey route

Multi-Sensor Optimal Motion Planning for Radiological Contamination Surveys by Using Prediction-Difference Maps

Distributed and networked mobile sensor platforms using unmanned aerial and/or ground vehicles to survey areas of interest offer a safer and more efficient method for radiological contamination mapping; however, most applications rely on uniformly sweeping of the area in a raster-type motion without utilizing the information available in a dynamic sense. We have developed a fully autonomous optimal motion planning procedure for networks with two or more mobile sensors. The procedure utilizes well-established concepts of Gaussian processes in combination with control laws based on centroidal Voronoi tessellations to achieve optimal next-iteration sensor movements. A new method of informing optimal motion planning is proposed, whereby the absolute difference between the prior and current full-map prediction, referred to as the prediction-difference map, is used as the spatial density function within each Voronoi cell, providing immediate and iterative feedback for dynamic use of available information. The Gaussian process regression model used to estimate the contamination in unvisited locations also provides prediction uncertainties, and can be used as a quantitative metric to assess the confidence in the calculated contamination map; these estimates and prediction uncertainties are unavailable for standard uniform survey routines as they can only produce maps in the vicinity of observed locations. We present through simulation the achievable performance gains from using this new method by directly comparing to a uniform survey method. Results show that using the prediction-difference maps to inform motion planning procedures offers a faster rate of producing an accurate and convergent map relative to a uniform survey route

Development of a Quasi-monoenergetic 6 MeV Gamma Facility at NASA Goddard Space Flight Center

The 6 MeV Gamma Facility has been developed at NASA Goddard Space Flight Center (GSFC) to allow in-house characterization and testing of a wide range of gamma-ray instruments such as pixelated CdZnTe detectors for planetary science and Compton and pair-production imaging telescopes for astrophysics. The 6 MeV Gamma Facility utilizes a circulating flow of water irradiated by 14 MeV neutrons to produce gamma rays via neutron capture on oxygen (O-16(n,p)N-16 yields O-16* yields O-16 + gamma). The facility provides a low cost, in-house source of 2.742, 6.129 and 7.117 MeV gamma rays, near the lower energy range of most accelerators and well above the 2.614 MeV line from the Th-228 decay chain, the highest energy gamma ray available from a natural radionuclide. The 7.13 s half-life of the N-16 decay allows the water to be irradiated on one side of a large granite block and pumped to the opposite side to decay. Separating the irradiation and decay regions allows for shielding material, the granite block, to be placed between them, thus reducing the low-energy gamma-ray continuum. Comparison between high purity germanium (HPGe) spectra from the facility and a manufactured source, Pu-238/C-13, shows that the low-energy continuum from the facility is reduced by a factor approx. 30 and the gamma-ray rate is approx.100 times higher at 6.129 MeV