SEARCH · Engineering Papers

Results for “performance monitoring”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,135 records · Page 63

All sources NASA NTRS DOE OSTI

NASA NTRS2018

Blind to Chemistry: Molecular Contaminant Films We Could Be Missing During Visual Inspections and the Potential Impact to System Performance

Throughout the assembly, integration and test process, molecular contamination levels of space mission hardware are monitored to meet system performance requirements. Qualitatively, reflective surfaces and witness mirrors are continuously inspected for the visible presence of molecular contaminant films. Quantitatively, periodic reflectance measurements of witness mirrors indicate changes of mirror reflectivity over time due to the accumulation of molecular contaminant films. However, both methods only consider the presence of a contaminant film and not the molecular composition. Additionally, there is a risk that hardware may appear to be “visibly clean” even with a molecular contaminant film present on critical surfaces. To address these issues, experiments were performed to quantify the maximum molecular contaminant film that could be missed in visual inspections on witness mirrors with five different contaminants present. The corresponding changes in mirror reflectivity were modeled using the program STACK to determine the impact to space mission hardware performance. The results of this study not only show the criticality in considering the chemical make-up of molecular contaminant films on system performance, but also the need to recognize and understand the limitations of traditional visual inspection techniques on detecting molecular contaminant films.

Seasly, Elaine↗

DOE OSTI2021

Preprocessing for Unintended Conducted Emissions Classification with ResNet

Characterization of Unintended Conducted Emissions (UCE) from electronic devices is important when diagnosing electromagnetic interference, performing nonintrusive load monitoring (NILM) of power systems, and monitoring electronic device health, among other applications. Prior work has demonstrated that UCE analysis can serve as a diagnostic tool for energy efficiency investigations and detailed load analysis. While explaining the feature selection of deep networks with certainty is often not fully comprehensive, or in other applications, quite lacking, additional tools/methods for further corroboration and confirmation can help further the understanding of the researcher. This is true especially in the subject application of the study in this paper. Often the focus of such efforts is the selected features themselves, and there is not as much understanding gained about the noise in the collected data. If selected feature and noise characteristics are known, it can be used to further shape the design of the deep network or associated preprocessing. This is additionally difficult when the available data are limited, as in the case which the authors investigated in this study. Here, the authors present a novel work (which is a proposed complementary portion of the overall solution to the deep network classification explainability problem for this application) by applying a systematic progression of preprocessing and a deep neural network (ResNet architecture) to classify UCE data obtained via current transformers. By using a methodical application of preprocessing techniques prior to a deep classifier, hypotheses can be produced concerning what features the deep network deems important relative to what it perceives as noise. For instance, it is hypothesized in this particular study as a result of execution of the proposed method and periodic inspection of the classifier output that the UCE spectral features are relatively close to each other or to the interferers, as systematically reducing the beta parameter of the Kaiser window produced progressively better classification performance, but only to a point, as going below the Beta of eight produced decreased classifier performance, as well as the hypothesis that further spectral feature resolution was not as important to the classifier as rejection of the leakage from a spectrally distant interference. This can be very important in unpredictable low-FNR applications, where knowing the difference between features and noise is difficult. As a side-benefit, much was learned regarding the best preprocessing to use with the selected deep network for the UCE collected from these low power consumer devices obtained via current transformers. Baseline rectangular windowed FFT preprocessing provided a 62% classification increase versus using raw samples. After performing a more optimal preprocessing, more than 90% classification accuracy was achieved across 18 low-power consumer devices for scenarios in which the in-band features-to-noise ratio (FNR) was very poor.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS2014

Early Evaluation of the VIIRS Calibration, Cloud Mask and Surface Reflectance Earth Data Records

Surface reflectance is one of the key products fromVIIRS and as withMODIS, is used in developing several higherorder land products. The VIIRS Surface Reflectance (SR) Intermediate Product (IP) is based on the heritageMODIS Collection 5 product (Vermote, El Saleous, & Justice, 2002). The quality and character of surface reflectance depend on the accuracy of the VIIRS Cloud Mask (VCM), the aerosol algorithms and the adequate calibration of the sensor. The focus of this paper is the early evaluation of the VIIRS SR product in the context of the maturity of the operational processing system, the Interface Data Processing System (IDPS). After a brief introduction, the paper presents the calibration performance and the role of the surface reflectance in calibration monitoring. The analysis of the performance of the cloud mask with a focus on vegetation monitoring (no snow conditions) shows typical problems over bright surfaces and high elevation sites. Also discussed is the performance of the aerosol input used in the atmospheric correction and in particular the artifacts generated by the use of the Navy Aerosol Analysis and Prediction System. Early quantitative results of the performance of the SR product over the AERONET sites showthatwith the fewadjustments recommended, the accuracy iswithin the threshold specifications. The analysis of the adequacy of the SR product (Land PEATE adjusted version) in applications of societal benefits is then presented. We conclude with a set of recommendations to ensure consistency and continuity of the JPSS mission with the MODIS Land Climate Data Record.

Surface reflectance↗

NASA NTRS2006

Cassini Camera Contamination Anomaly: Experiences and Lessons Learned

We discuss the contamination 'Haze' anomaly for the Cassini Narrow Angle Camera (NAC), one of two optical telescopes that comprise the Imaging Science Subsystem (ISS). Cassini is a Saturn Orbiter with a 4-year nominal mission. The incident occurred in 2001, five months after Jupiter encounter during the Cruise phase and ironically at the resumption of planned maintenance decontamination cycles. The degraded optical performance was first identified by the Instrument Operations Team with the first ISS Saturn imaging six weeks later. A distinct haze of varying size from image to image marred the images of Saturn. A photometric star calibration of the Pleiades, 4 days after the incident, showed stars with halos. Analysis showed that while the halo's intensity was only 1 - 2% of the intensity of the central peak of a star, the halo contained 30 - 70% of its integrated flux. This condition would impact science return. In a review of our experiences, we examine the contamination control plan, discuss the analysis of the limited data available and describe the one-year campaign to remove the haze from the camera. After several long conservative heating activities and interim analysis of their results, the contamination problem as measured by the camera's point spread function was essentially back to preanomaly size and at a point where there would be more risk to continue. We stress the importance of the flexibility of operations and instrument design, the need to do early infight instrument calibration and continual monitoring of instrument performance.

Cassini↗

NASA NTRS2022

Influence of Vegetation on Simulation of the Water Balance and Hydrological Response to El Niño–Southern Oscillation in Western Tropical South America

Land surface models (LSMs) rely on vegetation parameters for use in hydrological and energy balance analysis, monitoring, and forecasting. This study examines the influence that vegetation representation in the Noah-Multiparameterization (Noah-MP) LSM has on hydrological simulations across the diverse climate zones of western tropical South America (WTSA), with specific consideration of hydrological variability associated with El Niño–Southern Oscillation (ENSO). The influence of model representation of vegetation on simulated hydrology is evaluated through three simulation experiments that use 1) satellite-derived constant MODIS; 2) satellite-derived time-varying MODIS; and 3) the Noah-MP dynamic leaf model. We find substantial differences in vegetation fields between these simulations, with the Noah-MP dynamic leaf model diverging significantly from satellite-derived vegetation fields in many ecoregions. Impacts on simulated hydrology were, however, found to be modest across climate zones, except for select extreme events. Also, although impacts on hydrology under ENSO-induced variability were small, we find that the Noah-MP dynamic leaf model simulates a positive relationship between rainfall and vegetation in humid ecoregions of WTSA, where satellite observations may indicate the opposite. The relatively small sensitivity of simulated hydrology to vegetation scheme suggests that the performance of hydrological monitoring and forecasting in WTSA that uses Noah-MP is largely unaffected by the choice of vegetation scheme, such that using a simple climatological default is generally no worse than adopting more complicated options. The presence of some differences between the time-varying and constant MODIS simulations for hydrologic extremes, however, indicates that time-varying MODIS configuration might be more suitable for hydrological hazards applications.

South America↗

DOE OSTI2016

Technical Note: Development and performance of a software tool for quality assurance of online replanning with a conventional Linac or MR-Linac

Purpose: To develop an integrated quality assurance (QA) software tool for online replanning capable of efficiently and automatically checking radiation treatment (RT) planning parameters and gross plan quality, verifying treatment plan data transfer from treatment planning system (TPS) to record and verify (R&V) system, performing a secondary monitor unit (MU) calculation with or without a presence of a magnetic field from MR-Linac, and validating the delivery record consistency with the plan. Methods: The software tool, named ArtQA, was developed to obtain and compare plan and treatment parameters from both the TPS and the R&V system database. The TPS data are accessed via direct file reading and the R&V data are retrieved via open database connectivity and structured query language. Plan quality is evaluated with both the logical consistency of planning parameters and the achieved dose–volume histograms. Beams in between the TPS and R&V system are matched based on geometry configurations. To consider the effect of a 1.5 T transverse magnetic field from MR-Linac in the secondary MU calculation, a method based on modified Clarkson integration algorithm was developed and tested for a series of clinical situations. Results: ArtQA has been used in their clinic and can quickly detect inconsistencies and deviations in the entire RT planning process. With the use of the ArtQA tool, the efficiency for plan check including plan quality, data transfer, and delivery check can be improved by at least 60%. The newly developed independent MU calculation tool for MR-Linac reduces the difference between the plan and calculated MUs by 10%. Conclusions: The software tool ArtQA can be used to perform a comprehensive QA check from planning to delivery with conventional Linac or MR-Linac and is an essential tool for online replanning where the QA check needs to be performed rapidly.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

Design and performance of optimal detectors for guided wave structural health monitoring

Ultrasonic guided wave measurements in a long term structural health monitoring system are affected by measurement noise, environmental conditions, transducer aging and malfunction. This results in measurement variability which affects detection performance, especially in complex structures where baseline data comparison is required. This paper derives the optimal detector structure, within the framework of detection theory, where a guided wave signal at the sensor is represented by a single feature value that can be used for comparison with a threshold. Three different types of detectors are derived depending on the underlying structure’s complexity: (i) Simple structures where defect reflections can be identified without the need for baseline data; (ii) Simple structures that require baseline data due to overlap of defect scatter with scatter from structural features; (iii) Complex structure with dense structural features that require baseline data. The detectors are derived by modeling the effects of variabilities and uncertainties as random processes. Analytical solutions for the performance of detectors in terms of the probability of detection and false alarm are derived. A finite element model is used to generate guided wave signals and the performance results of a Monte-Carlo simulation are compared with the theoretical performance. initial results demonstrate that the problems of signal complexity and environmental variability can in fact be exploited to improve detection performance.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

Four-Dimensional Patient Dose Reconstruction for Scanned Ion Beam Therapy of Moving Liver Tumors

Purpose: Estimation of the actual delivered 4-dimensional (4D) dose in treatments of patients with mobile hepatocellular cancer with scanned carbon ion beam therapy. Methods and Materials: Six patients were treated with 4 fractions to a total relative biological effectiveness (RBE)–weighted dose of 40 Gy (RBE) using a single field. Respiratory motion was addressed by dedicated margins and abdominal compression (5 patients) or gating (1 patient). 4D treatment dose reconstructions based on the treatment records and the measured motion monitoring data were performed for the single-fraction dose and a total of 17 fractions. To assess the impact of uncertainties in the temporal correlation between motion trajectory and beam delivery sequence, 3 dose distributions for varying temporal correlation were calculated per fraction. For 3 patients, the total treatment dose was formed from the fractional distributions using all possible combinations. Clinical target volume (CTV) coverage was analyzed using the volumes receiving at least 95% (V{sub 95}) and 107% (V{sub 107}) of the planned doses. Results: 4D dose reconstruction based on daily measured data is possible in a clinical setting. V{sub 95} and V{sub 107} values for the single fractions ranged between 72% and 100%, and 0% and 32%, respectively. The estimated total treatment dose to the CTV exhibited improved and more robust dose coverage (mean V{sub 95} > 87%, SD < 3%) and overdose (mean V{sub 107} < 4%, SD < 3%) with respect to the single-fraction dose for all analyzed patients. Conclusions: A considerable impact of interplay effects on the single-fraction CTV dose was found for most of the analyzed patients. However, due to the fractionated treatment, dose heterogeneities were substantially reduced for the total treatment dose. 4D treatment dose reconstruction for scanned ion beam therapy is technically feasible and may evolve into a valuable tool for dose assessment.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2016

Understanding sources of organic aerosol during CalNex-2010 using the CMAQ-VBS

Abstract. Community Multiscale Air Quality (CMAQ) model simulations utilizing the traditional organic aerosol (OA) treatment (CMAQ-AE6) and a volatility basis set (VBS) treatment for OA (CMAQ-VBS) were evaluated against measurements collected at routine monitoring networks (Chemical Speciation Network (CSN) and Interagency Monitoring of Protected Visual Environments (IMPROVE)) and those collected during the 2010 California at the Nexus of Air Quality and Climate Change (CalNex) field campaign to examine important sources of OA in southern California. Traditionally, CMAQ treats primary organic aerosol (POA) as nonvolatile and uses a two-product framework to represent secondary organic aerosol (SOA) formation. CMAQ-VBS instead treats POA as semivolatile and lumps OA using volatility bins spaced an order of magnitude apart. The CMAQ-VBS approach underpredicted organic carbon (OC) at IMPROVE and CSN sites to a greater degree than CMAQ-AE6 due to the semivolatile POA treatment. However, comparisons to aerosol mass spectrometer (AMS) measurements collected at Pasadena, CA, indicated that CMAQ-VBS better represented the diurnal profile and primary/secondary split of OA. CMAQ-VBS SOA underpredicted the average measured AMS oxygenated organic aerosol (OOA, a surrogate for SOA) concentration by a factor of 5.2, representing a considerable improvement to CMAQ-AE6 SOA predictions (factor of 24 lower than AMS). We use two new methods, one based on species ratios (SOA/ΔCO and SOA/Ox) and another on a simplified SOA parameterization, to apportion the SOA underprediction for CMAQ-VBS to slow photochemical oxidation (estimated as 1.5 × lower than observed at Pasadena using −log(NOx : NOy)), low intrinsic SOA formation efficiency (low by 1.6 to 2 × for Pasadena), and low emissions or excessive dispersion for the Pasadena site (estimated to be 1.6 to 2.3 × too low/excessive). The first and third factors are common to CMAQ-AE6, while the intrinsic SOA formation efficiency for that model is estimated to be too low by about 7 × . From source-apportioned model results, we found most of the CMAQ-VBS modeled POA at the Pasadena CalNex site was attributable to meat cooking emissions (48 %, consistent with a substantial fraction of cooking OA in the observations). This is compared to 18 % from gasoline vehicle emissions, 13 % from biomass burning (in the form of residential wood combustion), and 8 % from diesel vehicle emissions. All "other" inventoried emission sources (e.g., industrial, point, and area sources) comprised the final 13 %. The CMAQ-VBS semivolatile POA treatment underpredicted AMS hydrocarbon-like OA (HOA) + cooking-influenced OA (CIOA) at Pasadena by a factor of 1.8 compared to a factor of 1.4 overprediction of POA in CMAQ-AE6, but it did capture the AMS diurnal profile of HOA and CIOA well, with the exception of the midday peak. Overall, the CMAQ-VBS with its semivolatile treatment of POA, SOA from intermediate volatility organic compounds (IVOCs), and aging of SOA improves SOA model performance (though SOA formation efficiency is still 1.6–2 × too low). However, continued efforts are needed to better understand assumptions in the parameterization (e.g., SOA aging) and provide additional certainty to how best to apply existing emission inventories in a framework that treats POA as semivolatile, which currently degrades existing model performance at routine monitoring networks. The VBS and other approaches (e.g., AE6) require additional work to appropriately incorporate IVOC emissions and subsequent SOA formation.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2009

Cooperative Three-Robot System for Traversing Steep Slopes

Teamed Robots for Exploration and Science in Steep Areas (TRESSA) is a system of three autonomous mobile robots that cooperate with each other to enable scientific exploration of steep terrain (slope angles up to 90 ). Originally intended for use in exploring steep slopes on Mars that are not accessible to lone wheeled robots (Mars Exploration Rovers), TRESSA and systems like TRESSA could also be used on Earth for performing rescues on steep slopes and for exploring steep slopes that are too remote or too dangerous to be explored by humans. TRESSA is modeled on safe human climbing of steep slopes, two key features of which are teamwork and safety tethers. Two of the autonomous robots, denoted Anchorbots, remain at the top of a slope; the third robot, denoted the Cliffbot, traverses the slope. The Cliffbot drives over the cliff edge supported by tethers, which are payed out from the Anchorbots (see figure). The Anchorbots autonomously control the tension in the tethers to counter the gravitational force on the Cliffbot. The tethers are payed out and reeled in as needed, keeping the body of the Cliffbot oriented approximately parallel to the local terrain surface and preventing wheel slip by controlling the speed of descent or ascent, thereby enabling the Cliffbot to drive freely up, down, or across the slope. Due to the interactive nature of the three-robot system, the robots must be very tightly coupled. To provide for this tight coupling, the TRESSA software architecture is built on a combination of (1) the multi-robot layered behavior-coordination architecture reported in "An Architecture for Controlling Multiple Robots" (NPO-30345), NASA Tech Briefs, Vol. 28, No. 10 (October 2004), page 65, and (2) the real-time control architecture reported in "Robot Electronics Architecture" (NPO-41784), NASA Tech Briefs, Vol. 32, No. 1 (January 2008), page 28. The combination architecture makes it possible to keep the three robots synchronized and coordinated, to use data from all three robots for decision- making at each step, and to control the physical connections among the robots. In addition, TRESSA (as in prior systems that have utilized this architecture) , incorporates a capability for deterministic response to unanticipated situations from yet another architecture reported in Control Architecture for Robotic Agent Command and Sensing (NPO-43635), NASA Tech Briefs, Vol. 32, No. 10 (October 2008), page 40. Tether tension control is a major consideration in the design and operation of TRESSA. Tension is measured by force sensors connected to each tether at the Cliffbot. The direction of the tension (both azimuth and elevation) is also measured. The tension controller combines a controller to counter gravitational force and an optional velocity controller that anticipates the motion of the Cliffbot. The gravity controller estimates the slope angle from the inclination of the tethers. This angle and the weight of the Cliffbot determine the total tension needed to counteract the weight of the Cliffbot. The total needed tension is broken into components for each Anchorbot. The difference between this needed tension and the tension measured at the Cliffbot constitutes an error signal that is provided to the gravity controller. The velocity controller computes the tether speed needed to produce the desired motion of the Cliffbot. Another major consideration in the design and operation of TRESSA is detection of faults. Each robot in the TRESSA system monitors its own performance and the performance of its teammates in order to detect any system faults and prevent unsafe conditions. At startup, communication links are tested and if any robot is not communicating, the system refuses to execute any motion commands. Prior to motion, the Anchorbots attempt to set tensions in the tethers at optimal levels for counteracting the weight of the Cliffbot; if either Anchorbot fails to reach its optimal tension level within a specified time, it sends message to the other robots and the commanded motion is not executed. If any mechanical error (e.g., stalling of a motor) is detected, the affected robot sends a message triggering stoppage of the current motion. Lastly, messages are passed among the robots at each time step (10 Hz) to share sensor information during operations. If messages from any robot cease for more than an allowable time interval, the other robots detect the communication loss and initiate stoppage.

Stroupe, Ashley↗

DOE OSTI2019

Experimental and Numerical Investigation of PZT Response in Composite Structures with Variable Degradation Levels

Commercial aerospace vehicles have been increasingly demanding to withstand harsh conditions with low-weight material, i.e., composites. Unfortunately, low-velocity impacts strongly affect their performance. Structural health monitoring with permanently attached sensors allows achieving cost-effective maintenance and tearing down knockdown factors. However, the degradation of transducers adopted for online detection of damage negatively affects the diagnosis. That deterioration is addressed in this work with the electromechanical impedance approach employed at relatively low ultrasonic frequencies. Several degradation conditions are investigated with experimental and numerical simulations. The results demonstrate how the self-diagnosis approach detects pure sensor failures without any structural dependence. However, self-detection of the mixed mode of failures is challenging due to the opposite effect that different types of failure return. Numerical simulations provide a spectral response in compliance with measurements. On top of that, numerical results demonstrate that the combination of different types of damage may induce missed detection. That is where a multi-parameter self-diagnosis approach may further improve the overall monitoring system.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Data-driven evaluation of HVAC operation and savings in commercial buildings

Commercial buildings consumed 36% of electricity, or 1.35 trillion kWh, in the United States in 2017, and almost 30% of this energy was wasted. Much of this loss can be attributed to inefficient heating ventilation and air conditioning (HVAC) systems. By improving the operational conditions of HVAC, significant savings can be achieved. However, most buildings and building equipment do not use costly sub-meters to monitor and address performance issues, and on-site auditing can be expensive and insufficient. Alternatively in this study, we propose a data-driven method to identify savings opportunities using only whole building meter data and without setting foot in the building. For this purpose, we introduced two algorithms that virtually quantify the value of a thermostat setpoint setback and HVAC rescheduling. Additionally, we developed novel methods for detecting occupancy patterns and quantifying the baseload of the HVAC operation. Using a clustering algorithm, we identified those buildings for which HVAC savings was significant and further categorized the buildings based on their potential for savings. A population study of over 432 commercial buildings demonstrated a median percentage energy savings of 1.6% from a baseload reduction and 2.1% from HVAC rescheduling. Additionally, results indicate that retail buildings have the highest potential for savings among the building types studied.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2017

Quantitative decoding of the response a ceramic mixed potential sensor array for engine emissions control and diagnostics

The development of on-board sensors for emissions monitoring is necessary for continuous monitoring of the performance of catalytic systems in automobiles. We have fabricated mixed potential electrochemical gas sensing devices with Pt, La 0.8 Sr 0.2 CrO 3 (LSCO), and Au/Pd alloy electrodes and a porous yttria-stabilized zirconia electrolyte. The three-electrode design takes advantage of the preferential selectivity of the Pt + Au/Pd and Pt + LSCO pairs towards different species of gases and has additional tunable selectivity achieved by applying a current bias to the latter pair. Voltages were recorded in single, binary, and ternary gas streams of NO, NO 2 , C 3 H 8 , and CO. We have also trained artificial neural networks to examine the voltage output from sensors in biased and unbiased modes to both identify which single test gas or binary mixture of two test gases is present in a gas stream as well as extract concentration values. We were then able to identify single and binary mixtures of these gases with accuracy of at least 98%. For determining concentration, the peak in the error distribution for binary mixtures was 5% and 80% of test data fell under <12% error. The sensor stability was also evaluated over the course of over 100 days and the ability to retrain ANNs with a small dataset was demonstrated.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2018

Long-Term in Situ Reduction in Soil Lead Bioavailability Measured in a Mouse Model

In this study, effects of different treatments on the bioavailability of lead (Pb) in soil from a smelter emission contaminated site in Joplin, Missouri, were evaluated in a mouse model. Similar estimates of relative bioavailability for Pb in untreated or treated soil were obtained in mice and in the well-established juvenile swine model. In the mouse model, treatments that used phosphate (phosphoric acid or triple superphosphate) combined with iron oxide or biosolids compost significantly reduced soil Pb bioavailability. Notably, effects of these remediation procedures were persistent, given that up to 16 years had elapsed between soil treatment and sample collection. Remediation of soils was associated with changes in Pb species present in soil. Differences in Pb species in ingested soil and in feces from treated mice indicated that changes in Pb speciation occurred during transit through the gastrointestinal tract. Use of the mouse model facilitates evaluation of remediation procedures and allows monitoring of the performance of procedures under laboratory and field conditions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

A NWB-based dataset and processing pipeline of human single-neuron activity during a declarative memory task

A challenge for data sharing in systems neuroscience is the multitude of different data formats used. Neurodata Without Borders: Neurophysiology 2.0 (NWB:N) has emerged as a standardized data format for the storage of cellular-level data together with meta-data, stimulus information, and behavior. A key next step to facilitate NWB:N adoption is to provide easy to use processing pipelines to import/export data from/to NWB:N. Here, we present a NWB-formatted dataset of 1863 single neurons recorded from the medial temporal lobes of 59 human subjects undergoing intracranial monitoring while they performed a recognition memory task. We provide code to analyze and export/import stimuli, behavior, and electrophysiological recordings to/from NWB in both MATLAB and Python. The data files are NWB:N compliant, which affords interoperability between programming languages and operating systems. This combined data and code release is a case study for how to utilize NWB:N for human single-neuron recordings and enables easy re-use of this hard-to-obtain data for both teaching and research on the mechanisms of human memory.

Science & Technology - Other Topics↗

DOE OSTI2015

THE DISTANCE MEASUREMENT OF NGC 1313 WITH CEPHEIDS

We present the detection of Cepheids in the barred spiral galaxy NGC 1313, using the Wide Field and Planetary Camera 2 on the Hubble Space Telescope. Twenty B(F450W) and V(F555W) epochs of observations spanning over three weeks were obtained, on which the profile-fitting photometry of all stars in the monitored field was performed using the package HSTphot. A sample of 26 variable stars have been identified to be Cepheids, with periods between 3 and 14 days. Based on the derived period-luminosity relations in B- and V-bands, we obtain an extinction-corrected distance modulus of μ{sub NGC} {sub 1313} = 28.32 ± 0.08 (random) ± 0.06 (systematic), employing the Large Magellanic Cloud as the distance zero point calibrator. The above moduli correspond to a distance of 4.61 ± 0.17 (random) ±0.13 (systematic) Mpc, consistent with previous measurements reported in the literature within uncertainties. In addition, the reddening to NGC 1313 is found to be small.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

Imaging of Hydrogel Microsphere Structure and Foreign Body Response Based on Endogenous X-Ray Phase Contrast

Transplantation of functional islets encapsulated in stable biomaterials has the potential to cure Type I diabetes. However, the success of these materials requires the ability to understand their stability in vivo. Imaging techniques that enable monitoring of biomaterial performance are critical to further development in the field. In this study, we demonstrate for the first time that X-ray phase contrast (XPC) imaging techniques enable 3D imaging and evaluation of islet volume, alginate hydrogel structure and local soft tissue response. Islets were encapsulated in alginate systems prepared in methods used in clinical trials and implanted in a rodent omentum pouch model as a treatment for type I diabetes. Microbeads were imaged with XPC prior to implantation and following implantation into an omentum pouch. Islets could be identified within alginate beads and the islet volume quantified. Omental adipose tissue could be distinguished from inflammatory regions resulting from implanted beads. Individual beads and the local encapsulation response were visualized and quantifiable. Measurements were in agreement with histology. The 3D structure of the microbeads could be characterized with XPC and failed beads could also be identified. These results point to the substantial potential of XPC as a tool for imaging biomaterials in small animal models.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Recursive Gaussian Process over graphs for Integrating Multi-timescale Measurements in Low-Observable Distribution Systems

The transition to a smarter grid is empowered by enhanced sensor deployments and smart metering infrastructure in the distribution system. Measurements from these sensors and meters can be used for many applications, including distribution system state estimation (DSSE). However, these measurements are typically sampled at different rates and could be intermittent due to losses during the aggregation process. These multi timescale measurements should be reconciled in real-time to perform accurate grid monitoring. This paper tackles this problem by formulating a recursive multi-task Gaussian process (RGP-G) approach that sequentially aggregates sensor measurements. Specifically, we formulate a recursive multi-task GP with and without network connectivity information to reconcile the multi time-scale measurements in distribution systems. Here, the proposed framework is capable of aggregating the multi-time scale measurements batch-wise or in real-time. Following the aggregation of the multi time-scale measurements, the spatial states of the consistent time-series are estimated using matrix completion based DSSE approach. Simulation results on IEEE 37 and IEEE 123 bus test systems illustrate the efficiency of the proposed methods from the standpoint of both multi time-scale data aggregation and DSSE.

42 ENGINEERING↗