Results for “analytical detection method” — Page 16

NASA NTRS1994

Special relativity effects for space-based coherent lidar experiments

There is a great need to develop a system that can measure accurately atmospheric wind profiles because an accurate data of wind profiles in the atmosphere constitutes single most input for reliable simulations of global climate numerical methods. Also such data helps us understand atmospheric circulation and climate dynamics better. Because of this need for accurate wind measurements, a space-based Laser Atmospheric Winds Sounder (LAWS) is being designed at MSFC to measure wind profiles in the lower atmosphere of the earth with an accuracy of 1 m/s at lower altitudes to 5m/s at higher altitudes. This system uses an orbiting spacecraft with a pulsed laser source and measures the Doppler shift between the transmitted and received frequencies to estimate the atmospheric wind velocities. If a significant return from the ground (sea) is possible, the spacecraft speed and height are estimated from it and these results and the Doppler shift are then used to estimate the wind velocities in the atmosphere. It is expected that at the proposed wavelengths, there will be enough backscatter from the aerosols but there may no be significant return from the ground. So a coherent (heterodyne) detection system is being proposed for signal processing because it can provide high signal to noise ratio and sensitivity and thus make the best use of low ground return. However, for a heterodyne detection scheme to provide the best results, it is important that the receiving aperture be aligned properly for the proposed wind sounder, this amounts to only a few microradians tolerance in alignment. It is suspected that the satellite motion relative to the ground may introduce errors in the order of a few microradians because of special relativity. Hence, the problem of laser scattering off a moving fixed target when the source and receiver are moving, which was not treated in the past in the literature, was analyzed in the following, using relativistic electrodynamics and applied to the case of the space-based coherent lidar, assuming flat ground. Here an interest in developing analytical expression for the location of the receiving point for the return with respect to the satellite, receiving angle and Doppler shift in frequency and amount of tip, all as measured in the satellite moving coordinate system and the diffuse scattering angle at the ground which does not require any compensation. All the three cases of retro-reflection, specular reflection and diffuse scattering by the ground should be treated though retro-reflection and diffuse scattering are more important.

Raogudimetla, V. S.↗

NASA NTRSDate not supplied

Clinical Decision Support - Concepts of Operation

We are entering a new era in space exploration to return to the moon and explore Mars. Crew members operating independently during long duration space exploration missions will require a clinical decision support system (CDSS) to increase autonomy by augmenting their knowledge, skills and abilities in different scenarios. Significant changes to in-flight and habitat medical care due to constraints on mass, volume, power, crew time and medical evacuation capabilities are needed to increase crew autonomy and self-reliance in decision making and task performance. The Exploration Medical Capability (ExMC) Element of the Human Research Program (HRP) pushes the boundary of space medical systems to advance the care of astronauts on future exploration missions beyond low Earth orbit by identifying and testing next-generation medical care and crew health maintenance technologies. Clinical decision support (CDS) presents knowledge and data in a context aware manner to augment a crew members’ knowledge, skills and abilities during the process of observation, orientation, decisions and action. A comprehensive crew health and performance CDSS is required to augment crew capability and will be used in different scenarios for several reasons. In general, the CDSS’s role is to assist the crew in prevention, detection, diagnosis and treatment of crew health and performance related conditions that may arise in exploration spaceflight. For example, CDSS would assist a high acuity scenario such as a heart attack by supplying clear instructions, vital signs and treatment reminders. A lower severity scenario such as kidney stone risk could interface to vehicle systems and display more complex predictive data during a diagnosis. A CDSS needs to contribute to successful missions by maintaining a high performing crew who can potentially exhibit countless medical conditions related to derangements from the space environment (sleep, cognition, nutrition and exercise) as well as conditions intrinsic to humans anywhere. While supporting the crew’s ability to make sound clinical decisions is desirable in any mission, it is essential for exploration missions with significant communication delays, no evacuation capability, and extended exposure to the flight environment. Such missions correspond with medical Level of Care V (LOC V), the highest level specified in NASA-STD-3001. The project focuses on CDS implementation research to derive requirements for LOC V, where the need for increased autonomy results in new practices and the inclusion of non-clinical data, such as vehicle environmental measures and physical exercise results, from other human and vehicle domains and advanced analytics. The CDS project describes how the CDSS is intended to be used by defining concepts of operations (ConOps). The process to derive ConOps focuses on increased autonomy that reduces the likelihood and consequences of accepted medical conditions. These crew health and performance inputs are grouped by common datasets and analysis models. Use cases are derived to research new clinical scenarios, architectural development and workflows. Implementation research is conducted with protypes to inform assumptions and derive requirements. The project also establishes how externally developed analysis and approaches can be added to expand a clinical decision support system and thus highlight how a comprehensive system can be globally developed with collaborators. This presentation will cover example scenarios from the CDS ConOps and the method to derive them. One example scenario will be CDSS alerting an increased kidney stone risk during a mission, with diagnosis and treatment options provided during the intervention.

clinical decision support↗

NASA NTRSDate not supplied

Clinical Decision Support - Concepts of Operation

We are entering a new era in space exploration to return to the moon and explore Mars. Crew members operating independently during long duration space exploration missions will require a clinical decision support system (CDSS) to increase autonomy by augmenting their knowledge, skills and abilities in different scenarios. Significant changes to in-flight and habitat medical care due to constraints on mass, volume, power, crew time and medical evacuation capabilities are needed to increase crew autonomy and self-reliance in decision making and task performance. The Exploration Medical Capability (ExMC) Element of the Human Research Program (HRP) pushes the boundary of space medical systems to advance the care of astronauts on future exploration missions beyond low Earth orbit by identifying and testing next-generation medical care and crew health maintenance technologies. Clinical decision support (CDS) presents knowledge and data in a context aware manner to augment a crew members’ knowledge, skills and abilities during the process of observation, orientation, decisions and action. A comprehensive crew health and performance CDSS is required to augment crew capability and will be used in different scenarios for several reasons. In general, the CDSS’s role is to assist the crew in prevention, detection, diagnosis and treatment of crew health and performance related conditions that may arise in exploration spaceflight. For example, CDSS would assist a high acuity scenario such as a heart attack by supplying clear instructions, vital signs and treatment reminders. A lower severity scenario such as kidney stone risk could interface to vehicle systems and display more complex predictive data during a diagnosis. A CDSS needs to contribute to successful missions by maintaining a high performing crew who can potentially exhibit countless medical conditions related to derangements from the space environment (sleep, cognition, nutrition and exercise) as well as conditions intrinsic to humans anywhere. While supporting the crew’s ability to make sound clinical decisions is desirable in any mission, it is essential for exploration missions with significant communication delays, no evacuation capability, and extended exposure to the flight environment. Such missions correspond with medical Level of Care V (LOC V), the highest level specified in NASA-STD-3001. The project focuses on CDS implementation research to derive requirements for LOC V, where the need for increased autonomy results in new practices and the inclusion of non-clinical data, such as vehicle environmental measures and physical exercise results, from other human and vehicle domains and advanced analytics. The CDS project describes how the CDSS is intended to be used by defining concepts of operations (ConOps). The process to derive ConOps focuses on increased autonomy that reduces the likelihood and consequences of accepted medical conditions. These crew health and performance inputs are grouped by common datasets and analysis models. Use cases are derived to research new clinical scenarios, architectural development and workflows. Implementation research is conducted with protypes to inform assumptions and derive requirements. The project also establishes how externally developed analysis and approaches can be added to expand a clinical decision support system and thus highlight how a comprehensive system can be globally developed with collaborators. This presentation will cover example scenarios from the CDS ConOps and the method to derive them. One example scenario will be CDSS alerting an increased kidney stone risk during a mission, with diagnosis and treatment options provided during the intervention.

clinical decision support↗

NASA NTRS2011

The Analysis of the Patterns of Radiation-Induced DNA Damage Foci by a Stochastic Monte Carlo Model of DNA Double Strand Breaks Induction by Heavy Ions and Image Segmentation Software

To create a generalized mechanistic model of DNA damage in human cells that will generate analytical and image data corresponding to experimentally observed DNA damage foci and will help to improve the experimental foci yields by simulating spatial foci patterns and resolving problems with quantitative image analysis. Material and Methods: The analysis of patterns of RIFs (radiation-induced foci) produced by low- and high-LET (linear energy transfer) radiation was conducted by using a Monte Carlo model that combines the heavy ion track structure with characteristics of the human genome on the level of chromosomes. The foci patterns were also simulated in the maximum projection plane for flat nuclei. Some data analysis was done with the help of image segmentation software that identifies individual classes of RIFs and colocolized RIFs, which is of importance to some experimental assays that assign DNA damage a dual phosphorescent signal. Results: The model predicts the spatial and genomic distributions of DNA DSBs (double strand breaks) and associated RIFs in a human cell nucleus for a particular dose of either low- or high-LET radiation. We used the model to do analyses for different irradiation scenarios. In the beam-parallel-to-the-disk-of-a-flattened-nucleus scenario we found that the foci appeared to be merged due to their high density, while, in the perpendicular-beam scenario, the foci appeared as one bright spot per hit. The statistics and spatial distribution of regions of densely arranged foci, termed DNA foci chains, were predicted numerically using this model. Another analysis was done to evaluate the number of ion hits per nucleus, which were visible from streaks of closely located foci. In another analysis, our image segmentaiton software determined foci yields directly from images with single-class or colocolized foci. Conclusions: We showed that DSB clustering needs to be taken into account to determine the true DNA damage foci yield, which helps to determine the DSB yield. Using the model analysis, a researcher can refine the DSB yield per nucleus per particle. We showed that purely geometric artifacts, present in the experimental images, can be analytically resolved with the model, and that the quantization of track hits and DSB yields can be provided to the experimentalists who use enumeration of radiation-induced foci in immunofluorescence experiments using proteins that detect DNA damage. An automated image segmentaiton software can prove useful in a faster and more precise object counting for colocolized foci images.

Ponomarev, Artem↗

NASA NTRS2016

The IPAC Image Subtraction and Discovery Pipeline for the Intermediate Palomar Transient Factory

We describe the near real-time transient-source discovery engine for the intermediate Palomar Transient Factory (iPTF), currently in operations at the Infrared Processing and Analysis Center (IPAC), Caltech. We coin this system the IPAC/iPTF Discovery Engine (or IDE). We review the algorithms used for PSF-matching, image subtraction, detection, photometry, and machine-learned (ML) vetting of extracted transient candidates. We also review the performance of our ML classifier. For a limiting signal-to-noise ratio of 4 in relatively unconfused regions, bogus candidates from processing artifacts and imperfect image subtractions outnumber real transients by approximately equal to 10:1. This can be considerably higher for image data with inaccurate astrometric and/or PSF-matching solutions. Despite this occasionally high contamination rate, the ML classifier is able to identify real transients with an efficiency (or completeness) of approximately equal to 97% for a maximum tolerable false-positive rate of 1% when classifying raw candidates. All subtraction-image metrics, source features, ML probability-based real-bogus scores, contextual metadata from other surveys, and possible associations with known Solar System objects are stored in a relational database for retrieval by the various science working groups. We review our efforts in mitigating false-positives and our experience in optimizing the overall system in response to the multitude of science projects underway with iPTF.

methods: analytical â€“ methods: data analysis â€“↗

NASA NTRSDate not supplied

In-Situ Reaction Monitoring for Lunar Applications Utilizing a Single Quadrupole Residual Gas Analyzer

With a revived focus to create a permeant presence on the moon and in preparation for future Mars exploration, it is imperative that all re-sources are utilized to their fullest potential. In-Situ Resource Utilization (ISRU) will be critical for future mission success as it would enable independent operation of missions while minimally relying on the complex supply chain created between the Earth, moon and Mars. One of the most critical resources that have been identified for ISRU is the creation of liquid oxygen (O2) for not only breathable air, but also for rocket fuel. On the moon and potentially Mars, one of the most O2 rich resources is in the presence of regolith. Although there are numerous minerals within regolith and various processes to extract O2, this is not the scope of this paper. Since the O2 extraction method can vary, a critical standardized analytical method is needed to verify O2 (or oxygenated precursor compounds) for extraction efficiency and purity. Our group utilizes a modified consumer off-the-shelf (COTS), Residual Gas Analyzer (RGA) Single Quadrupole Mass Spectrometer (QMS). Due to the current field mission requirements, the gas analysis module will need to rely only on mass-to-charge ratios (m/z) and peak intensities to differentiate and quantitate targeted gas-phase reactants or products, i.e. carbon monoxide (CO), carbon dioxide (CO2), methane (CH4) and hydrogen (H2). However, due to solar wind implanted volatiles and various other compounds present in lunar regolith, such as nitrogen (N2), helium (He), and deuterium (D2), deconvolution and quantification of isobaric compounds becomes quite difficult. Specifically, the presence of N2 makes quantification of CO, an oxygenated precursor, difficult due to both compounds having a peak at m/z 28. Approaches to differentiate isobaric components: Initially, the solution to overcome isobaric overlap was to use isotopic ratios, particularly be-tween carbon-13 and nitrogen-15. Although limited literature discuss isotopic composition and attempt to quantify the ratios, variation is particularly high and limited to a few lunar regolith samples. The following were identified as potential approaches to quantify isobaric species, N2 and CO, using our RGA. Threshold Ionization. CO and N2 both have peaks at m/z 28, but only N2 is capable of producing a peak at m/z 7. While a N2 peak at m/z 7 is generally rare, instrument parameters can be optimized in order to maximize the peak intensity. Typically a standard ionization energy of 70 eV is used to monitor a batch process and would produce reliable results for a majority of the reactants or products that we are interested in quantifying. However, to analyze the rare molecular fragment of N2 (N2+ at m/z 7), a different ionization energy may be beneficial. Threshold Ionization Mass Spectrometry (TIMS) will be explored to optimize the N2+ peak at m/z 7 by varying parameters such as ionization energy and pressure. Therefore, a quantitative value at m/z 7 will be used to determine the product gas concentration of N2, which will be subtracted from the total concentration determined at m/z 28 enabling us to approximate the amount of CO. Secondary Detector (infrared gas detector, IR). Another approach to quantitate and differentiate be-tween isobaric components is to leverage alternative modes of detection. Unlike mass spectrometry, which generally uses a separation step prior to analysis (i.e. gas chromatography), IR produces energy that is specifically absorbed depending on the bond and configuration of the molecule. This technique could be leveraged since it is generally only active on non-symmetric molecules, i.e. CO. Utilizing concentrations of CO determined from another detector could help correct concentrations of CO obtained from the QMS. However, the inclusion of another detector adds additional mission requirements, such as power, software changes and avionics updates that add additional cost and schedule requirements.

mass spectrometry↗