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At least 181 records · Page 10

Detection of Anomalies in Environmental Gamma Radiation Background with Hopfield Artificial Neural Network - Consortium on Nuclear Security Technologies (CONNECT) Q3 Report

Environmental screening of gamma radiation consists of detecting weak nuisance and anomaly signal in the presence of strong and highly varying background. In a typical scenario, a mobile detector-spectrometer continuously measures gamma radiation spectra in short, e.g., one-second, signal acquisition intervals. The measurement data is a 2D matrix, where one dimension is gamma ray energy, and the other dimension is the number of measurements or total time. In principle, gamma radiation sources can be detected and identified from the measured data by their unique spectral lines. Detecting sources from data measured in a search scenario is difficult due to the highly varying background because of naturally occurring radioactive material (NORM), and low signal-to-noise ratio (S/N) of spectral signal measured during one-second acquisition intervals. The objective of this work is to investigate performance of a Hopfield Neural Network (HNN) in in detection and identification of weak nuisances and anomalies events in the presence of a highly fluctuating background. Performance of HNN algorithm is benchmarked using search data from an environmental screening campaign. One data set contained a 137 Cs source, and another dataset contained a 131 I source.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Application of X-Ray Pulsar Navigation: A Characterization of the Earth Orbit Trade Space

The potential for pulsars as a navigation source has been studied since their discovery in 1967. X-ray pulsar navigation (XNAV) is a celestial navigation system that uses the consistent timing nature of x-ray photons from milli-second pulsars (MSP) to perform space navigation. By comparing the detected arrival of x-ray photons to a reference database of expected pulsar lightcurve timing models, one can infer a range and range rate measurement based on light time delay. Much of the challenge of XNAV comes from the faint signal, availability, and distant nature of pulsars. This is a study of potential pulsar XNAV measurements to measure extended Kalman filter (EKF) tracking performance with a wide trade space of bounded Earth orbits, using a simulation of existing x-ray detector space hardware. An example of an x-ray detector for XNAV is the NASA Station Explorer for X-ray Timing and Navigation (SEXTANT) mission, a technology demonstration of XNAV set to perform on the International Space Station (ISS) in late 2016early 2017. XNAV hardware implementation is driven by trajectory and environmental influences which add noise to the x-ray pulse signal. In a closed Earth orbit, the radiation environment can exponentially increase the signal noise from x-ray pulsar sources, decreasing the quality and frequency of measurements. The SEXTANT mission in particular improves on the signal to noise ratio by focusing an array of 56 x-ray silicon drift detectors at one pulsar target at a time. This reduces timing glitches and other timing noise contributions from ambient x-ray sources to within a 100 nanosecond resolution. This study also considers the SEXTANT scheduling challenges inherent in a single target observation. Finally, as the navigation sources are now relatively inertial targets, XNAV measurements are also subject to periods of occultation from various celestial bodies. This study focuses on the characterization of these drivers in closed Earth orbits and is not a tuning analysis of the EKF. The study shows that the closed Earth orbit for XNAV performance is reliant on the orbit semi-major axis and eccentricity as well as orbit inclination. These parameters are the primary drivers of pulsar measurement availability and significantly influence the natural spacecraft orbit dynamics. Sensitivity to initial orbit determination error growth due to the scarcity of XNAV measurements within an orbital period require appropriate timing of initial XNAV measurements. The orbit angles of argument of perigee and right ascension of the ascending node, alongside the other orbit parameters, complete the initial cadence of XNAV measurements. The performance of initial XNAV measurements then propagates throughout the experimental period. The study provides a basis to missions who wish to consider XNAV as a potential navigation source in a closed Earth orbit design. It provides a family of orbit trajectories as well as other modeling considerations needed to effectively evaluate if XNAV is an effective navigation source for a potential mission. As an EKF is sensitive to a linearized estimated state, this study has a direct benefit of providing effective XNAV measurements to maintain spacecraft tracking, independent of other navigation sources. In the particular use case of the SEXTANT mission, it also provides a novel scheduling algorithm which addresses the need to prioritize and manage pulsar observations for effective navigation.

PULSAR↗

Application of X-Ray Pulsar Navigation: A Characterization of the Earth Orbit Trade Space

The potential for pulsars as a navigation source has been studied since their discovery in 1967. X-ray pulsar navigation (XNAV) is a celestial navigation system that uses the consistent timing nature of x-ray photons from millisecond pulsars (MSP) to perform space navigation. By comparing the detected arrival of x-ray photons to a reference database of expected pulsar light-curve timing models, one can infer a range and range rate measurement based on light time delay. Much of the challenge of XNAV comes from the faint signal, availability, and distant nature of pulsars. This is a study of potential pulsar XNAV measurements to measure extended Kalman filter (EKF) tracking performance with a wide trade space of bounded Earth orbits, using a simulation of existing x-ray detector space hardware. An example of an x-ray detector for XNAV is the NASA Station Explorer for X-ray Timing and Navigation (SEXTANT) mission, a technology demonstration of XNAV set to perform on the International Space Station (ISS) in late 2016early 2017. XNAV hardware implementation is driven by trajectory and environmental influences which add noise to the x-ray pulse signal. In a closed Earth orbit, the radiation environment can exponentially increase the signal noise from x-ray pulsar sources, decreasing the quality and frequency of measurements. The SEXTANT mission in particular improves on the signal to noise ratio by focusing an array of 56 x-ray silicon drift detectors at one pulsar target at a time. This reduces timing glitches and other timing noise contributions from ambient x-ray sources to within a 100 nanosecond resolution. This study also considers the SEXTANT scheduling challenges inherent in a single target observation. Finally, as the navigation sources are now relatively inertial targets, XNAV measurements are also subject to periods of occultation from various celestial bodies. This study focuses on the characterization of these drivers in closed Earth orbits and is not a tuning analysis of the EKF. The study shows that the closed Earth orbit for XNAV performance is reliant on the orbit semi-major axis and eccentricity as well as orbit inclination. These parameters are the primary drivers of pulsar measurement availability and significantly influence the natural spacecraft orbit dynamics. Sensitivity to initial orbit determination error growth due to the scarcity of XNAV measurements within an orbital period require appropriate timing of initial XNAV measurements. The orbit angles of argument of perigee and right ascension of the ascending node, alongside the other orbit parameters, complete the initial cadence of XNAV measurements. The performance of initial XNAV measurements then propagates throughout the experimental period. The study provides a basis to missions who wish to consider XNAV as a potential navigation source in a closed Earth orbit design. It provides a family of orbit trajectories as well as other modeling considerations needed to effectively evaluate if XNAV is an effective navigation source for a potential mission. As an EKF is sensitive to a linearized estimated state, this study has a direct benefit of providing effective XNAV measurements to maintain spacecraft tracking, independent of other navigation sources. In the particular use case of the SEXTANT mission, it also provides a novel scheduling algorithm which addresses the need to prioritize and manage pulsar observations for effective navigation.

x-ray↗

A microprocessor based anti-aliasing filter for a PCM system

Described is the design and evaluation of a microprocessor based digital filter. The filter was made to investigate the feasibility of a digital replacement for the analog pre-sampling filters used in telemetry systems at the NASA Ames-Dryden Flight Research Facility (DFRF). The digital filter will utilize an Intel 2920 Analog Signal Processor (ASP) chip. Testing includes measurements of: (1) the filter frequency response and, (2) the filter signal resolution. The evaluation of the digital filter was made on the basis of circuit size, projected environmental stability and filter resolution. The 2920 based digital filter was found to meet or exceed the pre-sampling filter specifications for limited signal resolution applications.

Morrow, D. C.↗

Signaling from below: rodents select for deeper fruiting truffles with stronger volatile emissions

Many plant and fungal species use volatile organic compounds (VOCs) as chemical signals to convey information about the location or quality of their fruits or fruiting bodies to animal dispersers. Identifying the environmental factors and biotic interactions that shape fruit selection by animals is key to understanding the evolutionary processes that underpin chemical signaling. Using four Elaphomyces truffle species, we explored the role of fruiting depth, VOC emissions, and protein content in selection by five rodent species. We used stable isotope analysis of nitrogen (δ15N) in truffles to estimate fruiting depth, proton-transfer-reaction mass spectrometry to determine volatile emission composition, and nitrogen concentrations to calculate digestible protein of truffles. We coupled field surveys of truffle availability with truffle spore loads in rodent scat to determine selection by rodents. Despite presumably easier access to the shallow fruiting species, E. americanus (0.5-cm depth) and E. verruculosus (2.5-cm depth), most rodents selected for truffles fruiting deeper in the soil, E. macrosporus (4.1-cm depth) and E. bartlettii (5.0-cm depth). The deeper fruiting species had distinct VOC profiles and produced significantly higher quantities of odiferous compounds. Myodes gapperi (southern red-backed vole), a fungal specialist, also selected for truffles with high levels of digestible protein, E. verruculosus and E. macrosporus. Our results highlight the importance of chemical signals in truffle selection by rodents and suggest that VOCs are under strong selective pressures relative to protein rewards. Strong chemical signals likely allow detection of truffles deep within the soil and reduce foraging effort by rodents. Finally, for rodents that depend on fungi as a major food source, protein content may also be important in selecting truffles.

54 ENVIRONMENTAL SCIENCES↗

Skyfall: Signal Fusion from a Smartphone Falling from the Stratosphere

A smartphone plummeted from a stratospheric height of 36 km, providing a near-real-time record of its rapid descent and ground impact. An app recorded and streamed useful internal multi-sensor data at high sample rates. Signal fusion with external and internal sensor systems permitted a more detailed reconstruction of the Skyfall chronology, including its descent speed, rotation rate, and impact deceleration. Our results reinforce the potential of smartphones as an agile and versatile geophysical data collection system for environmental and disaster monitoring IoT applications. We discuss mobile environmental sensing capabilities and present a flexible data model to record and stream signals of interest. The Skyfall case study can be used as a guide to smartphone signal processing methods that are transportable to other hardware platforms and operating systems.

47 OTHER INSTRUMENTATION↗

Towards a self-driving trigger at the LHC: adaptive response in real time

Real-time data filtering and selection—or trigger—systems at high-throughput scientific facilities such as the experiments at the Large Hadron Collider must process extremely high-rate data streams under stringent bandwidth, latency, and storage constraints. Yet these systems are typically designed as static, hand-tuned menus of selection criteria grounded in prior knowledge and simulation. In this work, we further explore the concept of a self-driving trigger, an autonomous data-filtering framework that reallocates resources and adjusts thresholds dynamically in real-time to optimize signal efficiency, rate stability, and computational cost as instrumentation and environmental conditions evolve. We introduce a benchmark ecosystem to emulate realistic collider scenarios and demonstrate real-time optimization of a menu including canonical energy sum triggers as well as modern anomaly-detection algorithms that target non-standard event topologies using machine learning. Using simulated data streams and publicly available collision data from the Compact Muon Solenoid experiment, we demonstrate the capability to dynamically and automatically optimize trigger performance under specific cost objectives without manual retuning. Our adaptive strategy shifts trigger design from static menus with heuristic tuning to intelligent, automated, data-driven control, unlocking greater flexibility and discovery potential in future high-energy physics analyses.

Emami, Shaghayegh [Michigan U.] (ORCID:00090007589↗

Leaf habit affects the distribution of drought sensitivity but not water transport efficiency in the tropics

Abstract Considering the global intensification of aridity in tropical biomes due to climate change, we need to understand what shapes the distribution of drought sensitivity in tropical plants. We conducted a pantropical data synthesis representing 1117 species to test whether xylem‐specific hydraulic conductivity (K S ), water potential at leaf turgor loss (Ψ TLP ) and water potential at 50% loss of K S (Ψ P50 ) varied along climate gradients. The Ψ TLP and Ψ P50 increased with climatic moisture only for evergreen species, but K S did not. Species with high Ψ TLP and Ψ P50 values were associated with both dry and wet environments. However, drought‐deciduous species showed high Ψ TLP and Ψ P50 values regardless of water availability, whereas evergreen species only in wet environments. All three traits showed a weak phylogenetic signal and a short half‐life. These results suggest strong environmental controls on trait variance, which in turn is modulated by leaf habit along climatic moisture gradients in the tropics.

54 ENVIRONMENTAL SCIENCES↗

Machine Learning of Bacterial Transcriptomes Reveals Responses Underlying Differential Antibiotic Susceptibility

In vitro antibiotic susceptibility testing often fails to accurately predict in vivo drug efficacies, in part due to differences in the molecular composition between standardized bacteriologic media and physiological environments within the body. Here, we investigate the interrelationship between antibiotic susceptibility and medium composition in Escherichia coli K-12 MG1655 as contextualized through machine learning of transcriptomics data. Application of independent component analysis, a signal separation algorithm, shows that complex phenotypic changes induced by environmental conditions or antibiotic treatment are directly traced to the action of a few key transcriptional regulators, including RpoS, Fur, and Fnr. Integrating machine learning results with biochemical knowledge of transcription factor activation reveals medium-dependent shifts in respiration and iron availability that drive differential antibiotic susceptibility. By extension, the data generation and data analytics workflow used here can interrogate the regulatory state of a pathogen under any measured condition and can be applied to any strain or organism for which sufficient transcriptomics data are available.

59 BASIC BIOLOGICAL SCIENCES↗

Extreme metrics from large ensembles: investigating the effects of ensemble size on their estimates

Abstract. We consider the problem of estimating the ensemble sizes required to characterize the forced component and the internal variability of a number of extreme metrics. While we exploit existing large ensembles, our perspective is that of a modeling center wanting to estimate a priori such sizes on the basis of an existing small ensemble (we assume the availability of only five members here). We therefore ask if such a small-size ensemble is sufficient to estimate accurately the population variance (i.e., the ensemble internal variability) and then apply a well-established formula that quantifies the expected error in the estimation of the population mean (i.e., the forced component) as a function of the sample size n, here taken to mean the ensemble size. We find that indeed we can anticipate errors in the estimation of the forced component for temperature and precipitation extremes as a function of n by plugging into the formula an estimate of the population variance derived on the basis of five members. For a range of spatial and temporal scales, forcing levels (we use simulations under Representative Concentration Pathway 8.5) and two models considered here as our proof of concept, it appears that an ensemble size of 20 or 25 members can provide estimates of the forced component for the extreme metrics considered that remain within small absolute and percentage errors. Additional members beyond 20 or 25 add only marginal precision to the estimate, and this remains true when statistical inference through extreme value analysis is used. We then ask about the ensemble size required to estimate the ensemble variance (a measure of internal variability) along the length of the simulation and – importantly – about the ensemble size required to detect significant changes in such variance along the simulation with increased external forcings. Using the F test, we find that estimates on the basis of only 5 or 10 ensemble members accurately represent the full ensemble variance even when the analysis is conducted at the grid-point scale. The detection of changes in the variance when comparing different times along the simulation, especially for the precipitation-based metrics, requires larger sizes but not larger than 15 or 20 members. While we recognize that there will always exist applications and metric definitions requiring larger statistical power and therefore ensemble sizes, our results suggest that for a wide range of analysis targets and scales an effective estimate of both forced component and internal variability can be achieved with sizes below 30 members. This invites consideration of the possibility of exploring additional sources of uncertainty, such as physics parameter settings, when designing ensemble simulations.

54 ENVIRONMENTAL SCIENCES↗

Application of a pulsed laser for measurements of bathymetry and algal fluorescence.

The technique of measuring water depths with an airborne pulsed dye laser is studied, with emphasis on the degrading effect of some environmental and operational parameters on the transmitted and reflected laser signals. Extrapolation of measurements of laser stimulated fluorescence, performed as a function of both the algal cell concentration and the distance between the algae and the laser/receiver, indicate that a laser system operating from a height of 500 m should be capable of detecting chlorophyll concentrations as low as 1.0 mg/cu m.-

Hickman, G. D.↗

Flexible DCP interface

The author has identified the following significant results. A user of an ERTS data collection system must supply the sensors and signal conditioning interface. The electronic interface must be compatible with the NASA-furnished data collection platform (DCP). A universal signal conditioning system for use with a wide range of environmental sensors is described. The interface is environmentally and electronically compatible with the DCP and has operated satisfactorily for a complete winter wheat growing season in Kansas.

Kanemasu, E. T.↗

Flexible DCP interface

The author has identified the following significant results. A user of an ERTS data collection system (DCS) must supply the sensors and signal-conditioning interface. The electronic interface must be compatible with the NASA-furnished data collection platform. A universal signal-conditioning system for use with a wide range of environmental sensors is described. The interface is environmentally and electronically compatible with the DCP and has operated satisfactorily for a complete winter wheat growing season in Kansas.

Kanemasu, E. T.↗

Spaceflight payload design flight experience G-408

Worcester Polytechnic Institute's first payload of spaceflight experiments flew aboard Columbia, STS-40, during June of 1991 and culminated eight years of work by students and faculty. The Get Away Special (GAS) payload was installed on the GAS bridge assembly at the aft end of the cargo bay behind the Spacelab Life Sciences (SLS-1) laboratory. The Experiments were turned on by astronaut signal after reaching orbit and then functioned for 72 hours. Environmental and experimental measurements were recorded on three cassette tapes which, together with zeolite crystals grown on orbit, formed the basis of subsequent analyses. The experiments were developed over a number of years by undergraduate students meeting their project requirements for graduation. The experiments included zeolite crystal growth, fluid behavior, and microgravity acceleration measurement in addition to environmental data acquisition. Preparation also included structural design, thermal design, payload integration, and experiment control. All of the experiments functioned on orbit and the payload system performed within design estimates.

Durgin, William W.↗

Low power, compact charge coupled device signal processing system

A variety of charged coupled devices (CCDs) for performing programmable correlation for preprocessing environmental sensor data preparatory to its transmission to the ground were developed. A total of two separate ICs were developed and a third was evaluated. The first IC was a CCD chirp z transform IC capable of performing a 32 point DFT at frequencies to 1 MHz. All on chip circuitry operated as designed with the exception of the limited dynamic range caused by a fixed pattern noise due to interactions between the digital and analog circuits. The second IC developed was a 64 stage CCD analog/analog correlator for performing time domain correlation. Multiplier errors were found to be less than 1 percent at designed signal levels and less than 0.3 percent at the measured smaller levels. A prototype IC for performing time domain correlation was also evaluated.

Bosshart, P. W.↗

Can Zn isotopes in sediments record past eutrophication of freshwater lakes? A pilot study at Lake Baldegg (Switzerland)

In this study, the speciation and isotopic composition of Zn were traced across the sediments of a freshwater lake that experienced one hundred years of strong eutrophication, in order to assess the potential of sedimentary Zn isotopes to record such an environmental disturbance. Here, the results indicate that the sedimentary Zn isotope signal varied with the change from pre-eutrophic to eutrophic conditions in the investigated lake. The average δ 66 Zn JMC value of the dominantly allochthonous lithogenic sediments deposited during the pre-eutrophic period was +0.27‰ ±0.05‰ (i.e. similar to the δ 66 Zn JMC value of +0.28‰ ±0.05‰ proposed for Bulk Silicate Earth), while enhanced autochthonous biochemical sedimentation during the eutrophic period resulted in significantly lower δ 66 Zn JMC values down to +0.04‰ ±0.06‰. Synchrotron-based X-ray absorption spectroscopy data revealed a concomitant change in Zn speciation from a dominant fraction of Zn in clay minerals during the pre-eutrophic period to a major fraction of Zn in ZnS during the eutrophic period. A linear regression relating the sedimentary Zn isotope signal to the fraction of Zn in ZnS indicated δ 66 Zn JMC values of +0.27‰ ±0.06‰ and 0.00‰ ±0.08‰ for Zn in clay minerals and in ZnS, respectively. The enrichment of light Zn in ZnS in the eutrophic sediments is tentatively attributed to enhanced biological uptake of light Zn in the water column, which resulted in an enhanced flux of organic-bound Zn towards the sediments and further transformation of organic Zn into ZnS upon biomass mineralization during early diagenesis. This hypothesis is in agreement with the fractionation towards lighter Zn reported for both biological uptake of Zn and ZnS precipitation. The results of this study emphasize the potential of sedimentary Zn isotopes to register past eutrophic periods in freshwater lakes, and thus to serve as a probe of paleo-environmental conditions and/or past land use at the catchment scale.

58 GEOSCIENCES↗

Anomaly Detection in Gamma Spectra Using Hopfield Neural Network with B-SAT and Grover’s Algorithm on a Quantum Computing Simulator

Environmental screening of gamma radiation consists of detecting weak nuisance and anomaly signal in the presence of strong and highly varying background. In a typical scenario, a mobile detector-spectrometer continuously measures gamma radiation spectra in short, e.g., one-second, signal acquisition intervals. In principle, gamma radiation sources can be detected and identified by their unique spectral lines. However, detecting sources from data measured in a search scenario is difficult due to the highly varying background because of naturally occurring radioactive material (NORM), and low signal-to-noise ratio (S/N) of spectral signal measured during one-second acquisition intervals. In recent prior work, we have developed a Hopfield Neural Network (HNN) in conjunction with an image processing algorithm to detect a weak signal anomaly hidden among the highly fluctuating background spectra. The objective of this work is to explore quantum computing methods to increase the speed of HNN. The approach is based on the Grover’s search algorithm in conjunction with a 3-SAT problem formalism. The Grover’s algorithm is implemented on a quantum computing simulator using Qiskit software. Performance of HNN algorithm is benchmarked using search data from an environmental screening campaign, where the anomaly is a subset of measurements containing a 137 Cs source. Results indicate that using Grover’s algorithm on a quantum simulator reduces runtime of HNN by two orders of magnitude.

61 RADIATION PROTECTION AND DOSIMETRY↗

Binaural room simulation

In every-day listening the auditory event perceived by a listener is determined not only by the sound signal that a sound emits but also by a variety of environmental parameters. These parameters are the position, orientation and directional characteristics of the sound source, the listener's position and orientation, the geometrical and acoustical properties of surfaces which affect the sound field and the sound propagation properties of the surrounding fluid. A complete set of these parameters can be called an Acoustic Environment. If the auditory event perceived by a listener is manipulated in such a way that the listener is shifted acoustically into a different acoustic environment without moving himself physically, a Virtual Acoustic Environment has been created. Here, we deal with a special technique to set up nearly arbitrary Virtual Acoustic Environments, the Binaural Room Simulation. The purpose of the Binaural Room Simulation is to compute the binaural impulse response related to a virtual acoustic environment taking into account all parameters mentioned above. One possible way to describe a Virtual Acoustic Environment is the concept of the virtual sound sources. Each of the virtual sources emits a certain signal which is correlated but not necessarily identical with the signal emitted by the direct sound source. If source and receiver are non moving, the acoustic environment becomes a linear time-invariant system. Then, the Binaural Impulse Response from the source to a listener' s eardrums contains all relevant auditory information related to the Virtual Acoustic Environment. Listening into the simulated environment can easily be achieved by convolving the Binaural Impulse Response with dry signals and representing the results via headphones.

Lehnert, H.↗