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At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

AI-Enabled Robots for Automated Nondestructive Evaluation and Repair of Power Plant Boilers. Final Report

Boiler failure could cause loss of life and safety issues, cost hundreds of thousands of dollars in equipment repairs, property damage and production losses, and drive up the cost of electric power. Boiler maintenance is challenging and risky for inspectors working on scaffolding in confined hazardous spaces inside of a boiler and sometimes the space is hard to access. The operation is also time-consuming due to the large area of vertical structures for inspection and the tremendous effort needed for scaffolding. Recently, the use of robotics (e.g., drones and crawlers) in power plants for maintenance is growing rapidly. However, the existing robotics solutions show two notable technological gaps: no live repair capability, and no Artificial Intelligence (AI) for smart autonomy. The objective of this project is to develop an integrated autonomous robotic platform that is equipped with compact non-destructive evaluation (NDE) sensors to perform live inspection, operates onboard repair devices to perform live repair, and uses AI for intelligent data fusion and predictive analysis for automated and smart spatiotemporal inspection, analysis and repair of the furnace walls in coal-fired boilers. The approach to achieve the objective includes developing NDE sensors with signal processing techniques, designing and evaluating repair devices for robots based on fusion and solid-state technologies, and an autonomous robotic platform that can attach to and navigate on boiler furnace walls using magnetic drive tracks. The robot is also powered by AI to automate data gathering (e.g., 3D mapping and damage localization) and predictive analysis. This project has advanced the state-of-the-art by providing technological breakthroughs including compact NDE and repair tools for robots, AI capabilities for smart autonomy, and a robotic platform for automated boiler maintenance. This project has great potential to result in significant benefits including limiting or eliminating the need to send operators to assess difficult-to-access or hazardous areas, enabling automated live inspection and repair, avoiding time consuming scaffolding (especially for partial maintenance during unplanned outage), collecting comprehensive and well-organized data smartly, and avoiding or limiting the need for onsite or remote piloting technicians. The impacts can be tremendous in terms of the time and cost savings, reducing the risk for human operators, and increasing boiler reliability, usability, and efficiency. In addition, by developing the new technologies on the autonomous inspection and repair robot, by involving multiple undergraduate and graduate students working together with the faculty members on this project, and by generating knowledge and building up collaborations with industrial partners, this effort will significantly update the education capabilities, support long-term fundamental research, and maintain the leadership of Colorado School of Mines and Michigan State University in energy fields.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS1989

Image processing using Gallium Arsenide (GaAs) technology

The need to increase the information return from space-borne imaging systems has increased in the past decade. The use of multi-spectral data has resulted in the need for finer spatial resolution and greater spectral coverage. Onboard signal processing will be necessary in order to utilize the available Tracking and Data Relay Satellite System (TDRSS) communication channel at high efficiency. A generally recognized approach to the increased efficiency of channel usage is through data compression techniques. The compression technique implemented is a differential pulse code modulation (DPCM) scheme with a non-uniform quantizer. The need to advance the state-of-the-art of onboard processing was recognized and a GaAs integrated circuit technology was chosen. An Adaptive Programmable Processor (APP) chip set was developed which is based on an 8-bit slice general processor. The reason for choosing the compression technique for the Multi-spectral Linear Array (MLA) instrument is described. Also a description is given of the GaAs integrated circuit chip set which will demonstrate that data compression can be performed onboard in real time at data rate in the order of 500 Mb/s.

Miller, Warner H.↗
DOE OSTI2015

WE-EF-303-04: An Advanced Image Processing Method to Improve the Spatial Resolution of Proton Radiographies

Purpose: We present an optimization method to improve the spatial resolution and the water equivalent thickness accuracy of proton radiographies. Methods: The method is designed for imaging systems measuring only the residual range of protons without relying on tracker detectors to determine the beam trajectory before and after the target. Specifically, the method was used for an imaging set-up consisting of a stack of 61 parallel-plate ionization chambers (PPIC) working as a range telescope. The method uses a decomposition approach of the residual range signal measured by the PPIC and constructs subimages with small size pixels geometrically rearranged and appropriately averaged to be merged into a final single radiography. The method was tested using Monte Carlo simulated and experimental proton radiographies of a PMMA step phantom and an anthropomorphic head phantom. Results: For the step phantom, the effective spatial resolution was found to be 4 and 3 times higher than the nominal resolution for the simulated and experimental radiographies, respectively. For the head phantom, a gamma index was calculated to quantify the conformity of the simulated proton radiographies with a digitally reconstructed X-ray radiography convolved with a Gaussian kernel equal to the proton beam spot-size. For DTA=2.5 mm and RD=2.5%, the passing ratio was 100%/85% for the optimized/non-optimized case, respectively. An extension of the method allows reducing the dose given to the patient during radiography acquisition. We show that despite a dose reduction of 25 times (leading to a dose of 0.016 mGy for the current imaging set-up), the image quality of the optimized radiographies remains fairly unaffected for both the simulated and experimental results. Conclusion: The optimization method leads to a significant increase of the spatial resolution allowing recovering image details that are unresolved in non-optimized radiographies. These results represent a major step towards clinical application of proton radiography.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Iterative image-domain decomposition for dual-energy CT

Purpose: Dual energy CT (DECT) imaging plays an important role in advanced imaging applications due to its capability of material decomposition. Direct decomposition via matrix inversion suffers from significant degradation of image signal-to-noise ratios, which reduces clinical values of DECT. Existing denoising algorithms achieve suboptimal performance since they suppress image noise either before or after the decomposition and do not fully explore the noise statistical properties of the decomposition process. In this work, the authors propose an iterative image-domain decomposition method for noise suppression in DECT, using the full variance-covariance matrix of the decomposed images. Methods: The proposed algorithm is formulated in the form of least-square estimation with smoothness regularization. Based on the design principles of a best linear unbiased estimator, the authors include the inverse of the estimated variance-covariance matrix of the decomposed images as the penalty weight in the least-square term. The regularization term enforces the image smoothness by calculating the square sum of neighboring pixel value differences. To retain the boundary sharpness of the decomposed images, the authors detect the edges in the CT images before decomposition. These edge pixels have small weights in the calculation of the regularization term. Distinct from the existing denoising algorithms applied on the images before or after decomposition, the method has an iterative process for noise suppression, with decomposition performed in each iteration. The authors implement the proposed algorithm using a standard conjugate gradient algorithm. The method performance is evaluated using an evaluation phantom (Catphan©600) and an anthropomorphic head phantom. The results are compared with those generated using direct matrix inversion with no noise suppression, a denoising method applied on the decomposed images, and an existing algorithm with similar formulation as the proposed method but with an edge-preserving regularization term. Results: On the Catphan phantom, the method maintains the same spatial resolution on the decomposed images as that of the CT images before decomposition (8 pairs/cm) while significantly reducing their noise standard deviation. Compared to that obtained by the direct matrix inversion, the noise standard deviation in the images decomposed by the proposed algorithm is reduced by over 98%. Without considering the noise correlation properties in the formulation, the denoising scheme degrades the spatial resolution to 6 pairs/cm for the same level of noise suppression. Compared to the edge-preserving algorithm, the method achieves better low-contrast detectability. A quantitative study is performed on the contrast-rod slice of Catphan phantom. The proposed method achieves lower electron density measurement error as compared to that by the direct matrix inversion, and significantly reduces the error variation by over 97%. On the head phantom, the method reduces the noise standard deviation of decomposed images by over 97% without blurring the sinus structures. Conclusions: The authors propose an iterative image-domain decomposition method for DECT. The method combines noise suppression and material decomposition into an iterative process and achieves both goals simultaneously. By exploring the full variance-covariance properties of the decomposed images and utilizing the edge predetection, the proposed algorithm shows superior performance on noise suppression with high image spatial resolution and low-contrast detectability.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

Towards a unified model of neutrino-nucleus interactions

The achievement of the goals of the ongoing and future accelerator-based neutrino experiments – notably the determination of CP violating phase in the lepton sector – will require the development of advanced models of neutrino-nucleus interactions. In this review, we summarise the present status of experimental studies of neutrino-nucleus scattering, and discuss the developments and perspectives of the theoretical approach based on factorisation of the nuclear cross section, which has recently emerged as a promising framework for the description of the variety of processes contributing to the detected signals.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Characterizing proteases in sorghum drought response using activity-based protein profiling (ABPP)

Sorghum (Sorghum bicolor) is a C4 grass species that is a major food and bioenergy crop grown worldwide. Understanding the response of sorghum to climate change is therefore critical to future sustainable food and bioenergy production. Major advancements in genome sequencing have provided a wealth of genomic data for DOE-relevant plant species, but the functions of many of these genes remain unknown. Genotype to phenotype characterization of sorghum and other bioenergy crops is needed to identify key genes responsible for plant resilience to drought and other environmental stressors. Proteases, which modulate protein degradation and cellular signaling processes by catalyzing the hydrolysis of proteins into smaller proteins, peptides, or amino acids, are highly implicated in plant drought stress responses. We developed a method for using activity-based protein profiling (ABPP) of selected protease activities (serine and cysteine proteases) to characterize drought stress responses in sorghum roots and leaves. Analysis of these ABPP data identified several known serine and cysteine proteases as well as uncharacterized sorghum proteins which may have protease activities that can be explored in future validation studies.

09 BIOMASS FUELS↗
NASA NTRS1984

Method and apparatus for self-calibration and phasing of array antenna

A technique for self-calibrating and phasing a lens-feed array antenna, while normal operation is stopped, utilizes reflected energy of a continuous and coherent wave broadcast by a transmitter through a central feed while a phase controller advances the phase angles of reciprocal phase shifters in radiation electronics of the array elements at different rates to provide a distinct frequency modulation of electromagnetic wave energy returned by reflection in one mode and leakage in another mode from the radiation electronics of each array element. The composite return signal received by a synchronous receiver goes through a Fourier transform processing system and produces a response function for each antenna element. Compensation of the phase angles for the antenna elements required to conform the antenna response to a precomputed array pattern is derived from the reciprocal square root of the response functions for the antenna elements which, for a rectangular array of NXM elements, is a response function T(n,m). A third mode of calibration uses an external pilot tone from a separate antenna element. Respective responses are thus obtained from the three modes of calibration.

Wu, C.↗
NASA NTRS1997

Applications of Data Assimilation to Analysis of the Ocean on Large Scales

It is commonplace to begin talks on this topic by noting that oceanographic data are too scarce and sparse to provide complete initial and boundary conditions for large-scale ocean models. Even considering the availability of remotely-sensed data such as radar altimetry from the TOPEX and ERS-1 satellites, a glance at a map of available subsurface data should convince most observers that this is still the case. Data are still too sparse for comprehensive treatment of interannual to interdecadal climate change through the use of models, since the new data sets have not been around for very long. In view of the dearth of data, we must note that the overall picture is changing rapidly. Recently, there have been a number of large scale ocean analysis and prediction efforts, some of which now run on an operational or at least quasi-operational basis, most notably the model based analyses of the tropical oceans. These programs are modeled on numerical weather prediction. Aside from the success of the global tide models, assimilation of data in the tropics, in support of prediction and analysis of seasonal to interannual climate change, is probably the area of large scale ocean modeling and data assimilation in which the most progress has been made. Climate change is a problem which is particularly suited to advanced data assimilation methods. Linear models are useful, and the linear theory can be exploited. For the most part, the data are sufficiently sparse that implementation of advanced methods is worthwhile. As an example of a large scale data assimilation experiment with a recent extensive data set, we present results of a tropical ocean experiment in which the Kalman filter was used to assimilate three years of altimetric data from Geosat into a coarsely resolved linearized long wave shallow water model. Since nonlinear processes dominate the local dynamic signal outside the tropics, subsurface dynamical quantities cannot be reliably inferred from surface height anomalies. Because of its potential for large scale synoptic coverage of the deep ocean, acoustic travel time data should be a natural complement to satellite altimetry. Satellite data give us vertical integrals associated with thermodynamic and dynamic processes.

Miller, Robert N.↗
NASA NTRS2014

Blade Vibration Measurement System

The Phase I project successfully demonstrated that an advanced noncontacting stress measurement system (NSMS) could improve classification of blade vibration response in terms of mistuning and closely spaced modes. The Phase II work confirmed the microwave sensor design process, modified the sensor so it is compatible as an upgrade to existing NSMS, and improved and finalized the NSMS software. The result will be stand-alone radar/tip timing radar signal conditioning for current conventional NSMS users (as an upgrade) and new users. The hybrid system will use frequency data and relative mode vibration levels from the radar sensor to provide substantially superior capabilities over current blade-vibration measurement technology. This frequency data, coupled with a reduced number of tip timing probes, will result in a system capable of detecting complex blade vibrations that would confound traditional NSMS systems. The hardware and software package was validated on a compressor rig at Mechanical Solutions, Inc. (MSI). Finally, the hybrid radar/tip timing NSMS software package and associated sensor hardware will be installed for use in the NASA Glenn spin pit test facility.

Platt, Michael J.↗
DOE OSTI2019

Revisiting metabolic engineering strategies for microbial synthesis of oleochemicals

Microbial production of oleochemicals from renewable feedstocks remains an attractive route to produce high-energy density, liquid transportation fuels and high-value chemical products. Metabolic engineering strategies have been applied to demonstrate production of a wide range of oleochemicals, including free fatty acids, fatty alcohols, esters, olefins, alkanes, ketones, and polyesters in both bacteria and yeast. The majority of these demonstrations synthesized products containing long-chain fatty acids. These successes motivated additional effort to produce analogous molecules comprised of medium-chain fatty acids, molecules that are less common in natural oils and therefore of higher commercial value. Substantial progress has been made towards producing a subset of these chemicals, but significant work remains for most. The other primary challenge to producing oleochemicals in microbes is improving the performance, in terms of yield, rate, and titer, of biocatalysts such that economic large-scale processes are feasible. Common metabolic engineering strategies include blocking pathways that compete with synthesis of oleochemical building blocks and/or consume products, pulling flux through pathways by removing regulatory signals, pushing flux into biosynthesis by overexpressing rate-limiting enzymes, and engineering cells to tolerate the presence of oleochemical products. In this review, we describe the basic fundamentals of oleochemical synthesis and summarize advances since 2013 towards improving performance of heterotrophic microbial cell factories.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1993

Integrated flexible manufacturing program for manufacturing automation and rapid prototyping

The Kansas City Division of Allied Signal Inc., as part of the Integrated Flexible Manufacturing Program (IFMP), is developing an integrated manufacturing environment. Several systems are being developed to produce standards and automation tools for specific activities within the manufacturing environment. The Advanced Manufacturing Development System (AMDS) is concentrating on information standards (STEP) and product data transfer; the Expert Cut Planner system (XCUT) is concentrating on machining operation process planning standards and automation capabilities; the Advanced Numerical Control system (ANC) is concentrating on NC data preparation standards and NC data generation tools; the Inspection Planning and Programming Expert system (IPPEX) is concentrating on inspection process planning, coordinate measuring machine (CMM) inspection standards and CMM part program generation tools; and the Intelligent Scheduling and Planning System (ISAPS) is concentrating on planning and scheduling tools for a flexible manufacturing system environment. All of these projects are working together to address information exchange, standardization, and information sharing to support rapid prototyping in a Flexible Manufacturing System (FMS) environment.

Brooks, S. L.↗
DOE OSTI2017

Final report of a scalable, automated, semipermanent seismic array (SASSA) method for detecting CO 2 extent during geologic CO 2 injection

The scalable, automated, semipermanent seismic array (SASSA) project led and managed by the Energy & Environmental Research Center (EERC) was designed as a 3-year proof-of-concept study to evaluate and demonstrate an innovative application of the seismic method. The concept was to use a sparse surface array of 96 nodal seismic sensors paired with a single, remotely operated active seismic source at a fixed location to monitor for CO 2 saturation changes in a subsurface reservoir by processing the data for time-lapse changes at individual, strategically chosen reservoir reflection points. The combination of autonomous equipment and modern processing algorithms was used to apply the seismic method in a manner different from the normal paradigm of collecting a spatially dense data set to produce an image. It was used instead to monitor individual, strategically chosen reservoir reflection points for detectable signal character changes that could be attributed to the passing of a CO 2 saturation front or, possibly, changes in reservoir pressure. Data collection occurred over the course of 1 year at an oil field undergoing CO 2 injection for enhanced oil recovery (EOR) and focused on four overlapping “five-spot” EOR injector–producer patterns. Selection, procurement, configuration, installation, and testing of project equipment and collection of five baseline data sets were completed in advance of CO 2 injection within the study area. Weekly remote data collection produced 41 incremental time-lapse records for each of the 96 nodes. Validation was provided by two methods: 1) a conventional 2-D seismic line acquired through the center of the study area before injection started and again after the project ended and processed in a time-lapse manner and 2) by CO 2 saturation maps created from reservoir simulations based on injection and production history matching. Interpreted results were encouraging but mixed, with indications of changes likely due to the presence of CO 2 on some node reflection points where and when effects would be expected and noneffects where no CO 2 was expected, while results at some locations where simulation outputs suggested CO 2 should be present were ambiguous. Acquisition noise impacted interpretation of data at several locations. Many lessons learned were generated by the study to inform and improve results on a follow-up study. The ultimate aim of the project was to evaluate whether deployment of a SASSA technology can provide a useful and cost-effective monitoring solution for future CO 2 injection projects. The answer appears to be affirmative, with the expectation that lessons learned applied to future iterations, together with technology advances, will likely result in significant improvements.

58 GEOSCIENCES↗
NASA NTRS2003

Three-Gorge Reservoir: A 'Controlled Experiment' for Calibration/Validation of Time-Variable Gravity Signals Detected from Space

With the advances of measurements, modern space geodesy has become a new type of remote sensing for the Earth dynamics, especially for mass transports in the geophysical fluids on large spatial scales. A case in point is the space gravity mission GRACE (Gravity Recovery And Climate Experiment) which has been in orbit collecting gravity data since early 2002. The data promise to be able to detect changes of water mass equivalent to sub-cm thickness on spatial scale of several hundred km every month or so. China s Three-Gorge Reservoir has already started the process of water impoundment in phases. By 2009,40 km3 of water will be stored behind one of the world s highest dams and spanning a section of middle Yangtze River about 600 km in length. For the GRACE observations, the Three-Gorge Reservoir would represent a geophysical controlled experiment , one that offers a unique opportunity to do detailed geophysical studies. -- Assuming a complete documentation of the water level and history of the water impoundment process and aided with a continual monitoring of the lithospheric loading response (such as in area gravity and deformation), one has at hand basically a classical forwardinverse modeling problem of surface loading, where the input and certain output are known. The invisible portion of the impounded water, i.e. underground storage, poses either added values as an observable or a complication as an unknown to be modeled. Wang (2000) has studied the possible loading effects on a local scale; we here aim for larger spatial scales upwards from several hundred km, with emphasis on the time-variable gravity signals that can be detected by GRACE and follow-on missions. Results using the Green s function approach on the PREM elastic Earth model indicate the geoid height variations reaching several millimeters on wavelengths of about a thousand kilometers. The corresponding vertical deformations have amplitude of a few centimeters. In terms of long-wavelength spherical harmonics, the induced geoid height variations are very close to the accuracy of GRACE- recoverable gravity field, while the low-degree (2 to 5) harmonics should be detectable. With a large regional time-variable gravity signal, the Three-Gorge experiment can serve as a useful calibration/verification for GRACE (including the elastic loading effects), and future gravity missions (especially for visco-elastic yielding as well as underground water variations).

Chao, Benjamin F.↗
NASA NTRSDate not supplied

Low SWaP Onboard Satellite Navigation, Guidance, and Control Technology

Onboard autonomy is a necessity for responsive space operations. Autonomous navigation, guidance, and control (NGC) enables space missions to reduce their dependence on high demand ground assets and costly ground personnel. It also allows for in-situ decision making and higher return on mission data. A flight software and hardware system providing this capability, called “autoNGC,” is currently being developed at NASA Goddard Space Flight Center for infusion into multiple future missions. The first build of autoNGC, providing autonomous navigation for lunar orbiting spacecraft, is targeted for completion by Fall 2024. It provides sensor fusion of multiple measurement types including pseudo-range from a weak signal Global Navigation Satellite Service (GNSS) receiver, 1-way and 2-way direct to Earth (DTE) range and Doppler, bearing and range from optical camera sensed images, and an accelerometer. AutoNGC is also being targeted for future missions that involve small body proximity operations, Sun Earth Libration point orbits, and distributed systems missions (DSMs) including those at outer planets. AutoNGC flight software is being built upon the plug-and-play architecture of the core Flight System (cFS) [Ref. 1]. Figure (Slide 7) shows the message-based software bus layout of various software applications (“apps”) consisting of the standard cFS apps and autoNGC interface apps and libraries. Accurate onboard navigation and timing is obtained through the Goddard Enhanced Onboard Navigation System (GEONS) software library [Ref. 2], which fuses different measurement types through an extended Kalman filter (EKF) framework. Optical measurements that are ingested in GEONS are provided by the cFS Goddard Image Analysis and Navigation Tool (cGIANT) app [Ref. 3]. This app processes optical images to extract the bearing angles of the centroid of the imaged body (near or far), the range to the imaged body, and/or of the features on the surface of a body to perform terrain relative navigation (TRN). Measurement of range to the body’s center of mass can also be derived from the detection of the limb. The first build of autoNGC for a lunar orbiting spacecraft is a minimal size, weight, and power (SWaP) hardware design allowing for inclusion into CubeSats and SmallSat-size class buses. Advancements in miniaturized space processors, such as the SpaceCube 3.0 Mini and the SpaceCube Mini-Z [Ref. 4] are utilized for low SWaP while maintaining a high level of performance. Figure (Slide 11) shows the composition of the first autoNGC build. The current enclosure design has dimensions 12 cm x 17 cm x 13.5 cm. The box mass is expected to be less than 2 kg, and the nominal power is 21 W. The hardware interfaces are designed for flexibility with a variety of sensor inputs. The achievable navigation performance depends on the sensors utilized, including the onboard clock for 1-way pseudo-range measurements. Analysis using a configuration that consists of weak signal GPS, TRN, and 1-way DTE has shown position and velocity accuracies of 10 meters and 2 cm/s (3-σ ) RSS, respectively, with onboard time knowledge estimated to better than 13 ns (3-σ ), for a spacecraft in a representative 12-hour eccentric lunar orbit. Other measurement types such as x-rays from known pulsars (called XNAV) and cross-links can also be processed in GEONS. With the plug-and-play architecture of autoNGC, cFS apps can easily be added and replaced, even after launch. Goddard is actively seeking partners to collaborate in the development of additional capabilities for autoNGC, including industry, academia, and others across the US Government. Plans are being formulated to make the autoNGC software platform available for use by any US government organization to leverage the non-recurring engineering associated with the development of onboard autonomous NGC 3 capabilities. As advancements in space qualified sensors, microprocessors, and algorithms are made, the autoNGC platform provides a ready starting point for inclusion of these technologies.

C. J. Gramling↗
DOE OSTI2016

The current state of the art of quantitative phosphoproteomics and its applications to diabetes research

Protein phosphorylation is a fundamental regulatory mechanism in many cellular processes and aberrant perturbation of phosphorylation has been revealed in various human diseases. Kinases and their cognate inhibitors have been hotspot for drug development. Therefore, the emerging tools, which enable a system-wide quantitative profiling of phosphoproteome, would offer a powerful impetus in unveiling novel signaling pathways, drug targets and/or biomarkers for the disease of interest. In this review, we will highlight recent advances in phosphoproteomics, the current state-of-the-art of the technologies, and the challenges and future perspectives of this research area. Finally, we will underscore some exemplary applications of phosphoproteomics in diabetes research.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Image-Based Methods to Score Fungal Pathogen Symptom Progression and Severity in Excised Arabidopsis Leaves

Image-based symptom scoring of plant diseases is a powerful tool for associating disease resistance with plant genotypes. Advancements in technology have enabled new imaging and image processing strategies for statistical analysis of time-course experiments. There are several tools available for analyzing symptoms on leaves and fruits of crop plants, but only a few are available for the model plant Arabidopsis thaliana (Arabidopsis). Arabidopsis and the model fungus Botrytis cinerea (Botrytis) comprise a potent model pathosystem for the identification of signaling pathways conferring immunity against this broad host-range necrotrophic fungus. Here, we present two strategies to assess severity and symptom progression of Botrytis infection over time in Arabidopsis leaves. Thus, a pixel classification strategy using color hue values from red-green-blue (RGB) images and a random forest algorithm was used to establish necrotic, chlorotic, and healthy leaf areas. Secondly, using chlorophyll fluorescence (ChlFl) imaging, the maximum quantum yield of photosystem II (Fv/Fm) was determined to define diseased areas and their proportion per total leaf area. Both RGB and ChlFl imaging strategies were employed to track disease progression over time. This has provided a robust and sensitive method for detecting sensitive or resistant genetic backgrounds. A full methodological workflow, from plant culture to data analysis, is described.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1972

Development of performance criteria for advanced Viking seismic experiments

The characteristics and requirements of the seismic instrument for mapping the internal structure of the planet Mars are briefly described. The types of signals expected to exist are microseismic background generated by wind and pressure variations and thermal effects, disturbances of or in the landed vehicle, signals caused by faulting and volcanic activity, and signals due to meteoritic impacts. The advanced instrument package should include a short-period vertical component system, a long-period or wide-band 3-component system, a high frequency vertical component system, and a system for detection and rejection of lander noises. The Viking '75, Surveyor, and Apollo systems are briefly described as potential instruments to be considered for modification. Data processing and control systems are also summarized.

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