Evidence of multiple bacterial, viral, and parasitic infectious disease agents in Mastomys natalensis rodents in riverine areas in selected parts of Zambia
Not Available
Munjita, Samuel Munalula [Department of Biomedical↗
SEARCH · Search NASA
Results for “Collaborative control”
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.
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Application of dexterous space robotics technology to myoelectric prostheses
Future space missions will require robots equipped with highly dexterous robotic hands to perform a variety of tasks. A major technical challenge in making this possible is an improvement in the way these dexterous robotic hands are remotely controlled or teleoperated. NASA is currently investigating the feasibility of using myoelectric signals to teleoperate a dexterous robotic hand. In theory, myoelectric control of robotic hands will require little or no mechanical parts and will greatly reduce the bulk and weight usually found in dexterous robotic hand control devices. An improvement in myoelectric control of multifinger hands will also benefit prosthetics users. Therefore, as an effort to transfer dexterous space robotics technology to prosthetics applications and to benefit from existing myoelectric technology, NASA is collaborating with the Limbs of Love Foundation, the Institute for Rehabilitation and Research, and Rice University in developing improved myoelectric control multifinger hands and prostheses. In this paper, we will address the objectives and approaches of this collaborative effort and discuss the technical issues associated with myoelectric control of multifinger hands. We will also report our current progress and discuss plans for future work.
Hess, Clifford↗
Controlling Malaria and Other Diseases Using Remote Sensing
Remote sensing offers the vantage of monitoring a vast area of the Earth continuously. Once developed and launched, a satellite gives years of service in collecting data from the land, the oceans, and the atmosphere. Since the 1980s, attempts have been made to relate disease occurrence with remotely sensed environmental and geophysical parameters, using data from Landsat, SPOT, AVHRR, and other satellites. With higher spatial resolution, the recent satellite sensors provide a new outlook for disease control. At sub-meter to I 10m resolution, surface types associated with disease carriers can be identified more accurately. The Ikonos panchromatic sensor with I m resolution, and the Advanced Land Imager with 1 Om resolution on the newly launched Earth Observing-1, both have displayed remarkable mapping capabilities. In addition, an entire array of geophysical parameters can now be measured or inferred from various satellites. Airborne remote sensing, with less concerns on instrument weight, size, and power consumption, also offers a low-cost alternative for regional applications. NASA/GSFC began to collaborate with the Mahidol University on malaria and filariasis control using remote sensing in late 2000. The objectives are: (1) To map the breeding sites for the major vector species; (2) To identify the potential sites for larvicide and insecticide applications; (3) To explore the linkage of vector population and transmission intensity to environmental variables; (4) To monitor the impact of climate change and human activities on vector population and transmission; and (5) To develop a predictive model for disease distribution. Field studies are being conducted in several provinces in Thailand. Data analyses will soon begin. Malaria data in South Korea are being used as surrogates for developing classification techniques. GIS has been shown to be invaluable in making the voluminous remote sensing data more readily understandable. It will be used throughout this study to clearly demonstrate the spatial relationship between the disease intensities, geophysical variables, and socioeconomic parameters. Asides from malaria and filariasis, application of remote sensing to the control of other diseases have been vigorously pursued by NASA's Environment and Health Initiative. The current program includes projects on Rift Valley fever, St. Louis encephalitis, dengue fever, ebola, African dust and diseases, meningitis, asthma, bartonellosis, cholera, and urban health concerns. Results from these projects indicate that remote sensing will play an increasingly important role in disease control in the future.
Kiang, Richard K.↗
Conference report on the 1st US–Japan workshop on power and particle control by liquid metal plasma-facing components in a steady state magnetic fusion DEMO reactor
As part of the US–Japan bilateral collaboration program, a new series of workshops have been inaugurated on the subject of 'Power and Particle Control by Liquid Metal Plasma-Facing Components in a Steady State Magnetic Fusion DEMO Reactor'. The first workshop of this series was held at Princeton Plasma Physics Laboratory on 11–13 March 2019. This conference report is intended to share 24 technical presentations, discussion and the planning of future workshops with the world magnetic fusion community.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Outline for Feasibility Study on a Nuclear Material Accounting and Control System for Measurement of High-Activity Waste at Tokai Reprocessing Plant during Decommissioning
The objective of this collaboration between the DOE/NNSA International Nuclear Security Program (INS) and JAEA is to conduct a feasibility study on nuclear material accounting and control needs and requirements for NDA measurement of high-activity waste at TRP during the decommissioning process. Under this study, both sides will exchange information, perform an assessment of needs and requirements, and develop joint recommendations for development of the A-HMMS.
98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
NextGen Technologies on the FAA's Standard Terminal Automation Replacement System
This paper describes the integration, evaluation, and results from a high-fidelity human-in-the-loop (HITL) simulation of key NASA Air Traffic Management Technology Demonstration - 1 (ATD- 1) technologies implemented in an enhanced version of the FAA's Standard Terminal Automation Replacement System (STARS) platform. These ATD-1 technologies include: (1) a NASA enhanced version of the FAA's Time-Based Flow Management, (2) a NASA ground-based automation technology known as controller-managed spacing (CMS), and (3) a NASA advanced avionics airborne technology known as flight-deck interval management (FIM). These ATD-1 technologies have been extensively tested in large-scale HITL simulations using general-purpose workstations to study air transportation technologies. These general purpose workstations perform multiple functions and are collectively referred to as the Multi-Aircraft Control System (MACS). Researchers at NASA Ames Research Center and Raytheon collaborated to augment the STARS platform by including CMS and FIM advisory tools to validate the feasibility of integrating these automation enhancements into the current FAA automation infrastructure. NASA Ames acquired three STARS terminal controller workstations, and then integrated the ATD-1 technologies. HITL simulations were conducted to evaluate the ATD-1 technologies when using the STARS platform. These results were compared with the results obtained when the ATD-1 technologies were tested in the MACS environment. Results collected from the numerical data show acceptably minor differences, and, together with the subjective controller questionnaires showing a trend towards preferring STARS, validate the ATD-1/STARS integration.
air traffic management↗
Recent studies of rotorcraft blade-vortex interaction noise
Recent results are presented from several research efforts aimed at the understanding of rotorcraft blade-vortex interaction (BVI) in terms of the noise generation, directivity, and control. The results are based on work performed by NASA Langley Research Center researchers, both alone and in collaboration with other research organizations. Based on analysis of a simplified physical model, the critical parameters controlling BVI noise generation have been identified. The detailed mapping of the acoustic radiation field of a model rotor in a wind tunnel has revealed the extreme sensitivity of directivity to rotor advance ratio and disk attitude. The control and reduction of BVI noise through the use of higher harmonic pitch control is discussed.
BLADE VORTEX INTERACTION↗
Performance Evaluation of Intelligent Solar Control Software Through Hardware-in-the-Loop (CRADA Final Report)
Recent research has highlighted the potential for solar to act as a zero-marginal-cost and zero-emission flexibility resource on the bulk power system when operated with advanced control systems. To increase the performance of these systems, leading technologies, including machine learning (ML) and hierarchical inverter set point allocation, have been developed by Latimer Controls, Inc. to estimate the headroom of large PV plants for grid operation and control; however, these technologies lack comprehensive validation under real-world application scenarios. Latimer Controls, Inc. received two voucher awards for research at a national laboratory from the Department of Energy American Made Solar Prize Round 6. The National Renewable Energy Laboratory (NREL) was selected to collaborate with Latimer staff to conduct a performance evaluation of Latimer PV control software. The NREL team will develop a hardware-in-the-loop (HIL) testbed to perform testing and validation of the Latimer PV control technology in a de-risked yet realistic testbed environment. Latimer and NREL worked together to analyze the test data, draw conclusions from the results, and disseminate the resulting scientific findings. In this CRADA work, we propose to test and validate the real-world application of the Latimer Control solution in an HIL environment. We evaluate the performance of different flexible solar technologies in responding to automatic generation control signals in a closed-loop fashion. In particular, a data-driven potential high limit (PHL) estimation is developed for large solar plants to accurately estimate their headroom so that they have fast and short-time regulation and control capability to participate in grid services and respond to grid signals in real time (e.g., AGC). This PHL estimation algorithm is embedded in a hardware power plant controller (PPC) and tested with an IEEE-39 bus system model developed in RTDS. To account for the varying cloud conditions and diverse inverter dispatches, we developed a 135-MW PV plant with detailed modeling of 27 individual PV modules and inverters using RTDS. The real-world communications used in such big plants, such as ModBus TCP/IP for inverter level and DNP3 for plant level, were developed to emulate the real-world applications in big PV plants. The ML-based PHL estimation method is tested under nine separate weather scenarios against the ‘reference-control’ solution, hereafter referred to as the baseline solution. The baseline method reserves a subset of inverters (reference group) to operate at their PHL at all times and dispatches only the remaining inverters (control group) at curtailed levels to fulfill the flexibility need. Despite being successfully piloted by NREL in California in 2017 and Chile in 2020, there exist two gaps in the state of the art to fully unlock the flexibility of PV plants: a. There is a trade-off between the PHL estimation accuracy and the flexibility range. b. There lacks granularity in the PHL estimation to capture the variation across inverters. The Latimer solution seeks to address these gaps by applying machine learning methods to improve PHL estimation accuracy while accounting for variability at every inverter. Performance metrics were taken from the 2023 Georgia Power CARES utility-scale RFP. The results demonstrate that the ML-based approach outperforms the traditional baseline method in PHL estimation accuracy for 7 of 9 scenarios. The average PHL error across the nine scenarios was 7.40% for the ML-based method, 2.06% less than the 9.46% PHL error average across scenarios that was exhibited by the baseline method. Additionally, the PHL error was below 5% for at least 95% of the testing interval for 3 of 9 tested intervals with the ML approach, whereas it did not achieve this metric for any of the baseline tests. Overall, simulation results indicate the superior performance of an ML-based approach compared to the conventional baseline reference-control approach, showcasing its potential to support grid stability and operational efficiency. This laboratory HIL testing using real PPC, representative power system simulation models in real-time with detailed PV plant and inverter models, and real-world communication protocols gives us confidence that this machine learning based PHL estimation algorithm works well in the hardware PPC and therefore de-risks future field commissioning. The end goal of this project is to advance grid technology to address the grid operation challenges brought by solar plant’s variability and uncertainties in power generation.
14 SOLAR ENERGY↗
In-Space Crew-Collaborative Task Scheduling
For all past and current human space missions, the final scheduling of tasks to be done in space has been devoid of crew control, flexibility, and insight. Ground controllers, with minimal input from the crew, schedule the tasks and uplink the timeline to the crew or uplink the command sequences to the hardware. Prior to the International Space Station (ISS), the crew could make requests about tomorrow s timeline, they could omit a task, or they could request that something in the timeline be delayed. This lack of control over one's own schedule has had negative consequences. There is anecdotal consensus among astronauts that control over their own schedules will mitigate the stresses of long duration missions. On ISS, a modicum of crew control is provided by the job jar. Ground controllers prepare a task list (a.k.a. "job jar") of non-conflicting tasks from which jobs can be chosen by the in space crew. Because there is little free time and few interesting non-conflicting activities, the task-list approach provides little relief from the tedium of being micro-managed by the timeline. Scheduling for space missions is a complex and laborious undertaking which usually requires a large cadre of trained specialists and suites of complex software tools. It is a giant leap from today s ground prepared timeline (with a job jar) to full crew control of the timeline. However, technological advances, currently in-work or proposed, make it reasonable to consider scheduling a collaborative effort by the ground-based teams and the in-space crew. Collaboration would allow the crew to make minor adjustments, add tasks according to their preferences, understand the reasons for the placement of tasks on the timeline, and provide them a sense of control. In foreseeable but extraordinary situations, such as a quick response to anomalies and extended or unexpected loss of signal, the crew should have the autonomous ability to make appropriate modifications to the timeline, extend the timeline, or even start over with a new timeline. The Vision for Space Exploration (VSE), currently being pursued by the National Aeronautics and Space Administration (NASA), will send humans to Mars in a few decades. Stresses on the human mind will be exacerbated by the longer durations and greater distances, and it will be imperative to implement stress-reducing innovations such as giving the crew control of their daily activities.
Jaap, John↗
The Use of Software Agents for Autonomous Control of a DC Space Power System
In order to enable manned deep-space missions, the spacecraft must be controlled autonomously using on-board algorithms. A control architecture is proposed to enable this autonomous operation for an spacecraft electric power system and then implemented using a highly distributed network of software agents. These agents collaborate and compete with each other in order to implement each of the control functions. A subset of this control architecture is tested against a steadystate power system simulation and found to be able to solve a constrained optimization problem with competing objectives using only local information.
autonomous control↗
Rotorcraft blade/vortex interaction noise - Its generation, radiation, and control
Recent results are presented from several research efforts aimed at the understanding of rotorcraft blade-vortex interaction noise generation, directivity, and control. The results are based on work performed by researches at the NASA Langley Research Center, both alone and in collaboration with other research organizations. Based on analysis of a simplified physical model, the critical parameters controlling the noise generation are identified. Detailed mapping of the acoustic radiation field reveals the extreme sensitivity of directivity to rotor advance ratio and disk attitude. A means of controlling blade-vortex interaction noise by higher harmonic pitch control is discussed.
Preisser, J. S.↗
Automatic Imagery Data Analysis for Proactive Computer-Based Workflow Management during Nuclear Power Plant Outages
This report is being submitted for the task “Final Report” of DOE NEUP Project 15-8121 “Automatic Imagery Data Analysis for Proactive Computer-Based Workflow Management during Nuclear Power Plant Outages.” Typical nuclear power plant (NPP) outages always involve thousands of maintenance and refueling activities and a large number of workers in limited workspaces, while having tight schedules and zero-tolerance for accidents. During an outage, thousands of workers will be working in various workspaces across the NPP. High outage costs and expensive delays (approximately 1.5 million dollars of loss per day of delay) in NPP maintenance demand tight outage schedules. In packed workspaces, an automatic system that monitors human behaviors in real-time and provides insights about current and pending schedule deviations from the plan is critical for ensuring: 1) effective collaboration among workers and worker teams from different trades; 2) less waste of time and resources due to the lack of situational awareness; and 3) proactive outage project control. The overall goal of this project is to test the hypothesis that real-time imagery-based object tracking and spatial analysis, as well as human behavior modeling of outage participants, will significantly improve the efficiency of outage control while lowering the rates of accidents and incidents. Three objectives of this project are: 1) Establish real-time object tracking and spatiotemporal analysis methods that automatically assess the productivity of field activities and detect anomalous spatiotemporal relationships among activities that cause inefficiencies and risks; 2) Establish realtime human tracking and human factor modeling methods for automatically diagnosing unexpected actions of and interactions between outage participants, those which cause inefficient collaborations between Advanced Outage Control Center (AOCC), satellite outage centers, NPP workers, and maintenance service providers; and 3) Test the proposed automated object tracking, human behavior modeling, and spatiotemporal analysis methods in outage control case studies in order to characterize the effectiveness of automated imagery-data-driven methods in proactively improving the efficiency and safety of workflows in outage coordination and risk management. Recent studies of detailed human behavior monitoring on construction sites have examined the potential of applying advanced computer vision algorithms in detecting and tracking anomalous workers (i.e., workers who do not wear hard hats or safety vests) for ensuring job site safety. Some studies of human factor studies revealed the importance of modeling detailed interactions between individuals within and across teams in better understanding the impact of human in proactive project control. Other studies in the construction domain have developed computational simulation frameworks that formalize detailed spatiotemporal interactions between tasks in order to simulate the impacts of individual tasks on the performance of workflows. While integrated analyses that combine human factor assessment, as well as image processing and simulation, are in demand for effective decision-making, limited studies have examined the potential of such integrated analyses in NPP outage control. This research project has examined an automatic outage monitoring and control system that integrates human factor analysis, computer vision techniques, and simulation methods in order to enable engineers to better understand the interactions between humans, resources, and workflows during outage processes. The project aims at providing NPP maintenance agencies insights into more efficient use of limited resources in extending the life of a nuclear plant, as well as reducing waste while ensuring sufficient generation of electricity. This study is significant for the safety of nuclear plants, sustainable electricity generation for livable communities, and cost savings for maintaining electricity infrastructures in the United States.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
m:N ConOps/R&R Remote Simulation
This presentation details the experimental design of an investigation of small unmanned aircraft system (sUAS) operations involving multiple vehicle management by a remote operator. The study is part of an ongoing effort to explore multiple vehicle control by multiple operators, i.e., the control of N vehicles by m operators (m:N operations). For this effort, NASA and collaborators have developed prototypes of a concept of operations (ConOps), roles and responsibilities (R&R) for operators and supervisors, and a ground control station (GCS), including software displays and interfaces. Participants in this study acted as the pilot-in-command of twelve aircraft flying pre-approved routes in a simulation of a food delivery operation utilizing sUAS in the San Diego, CA area. Each participant experienced four experimental trials. Twice within the course of each trial, participants were responsible for responding to a sudden, unanticipated, and high-priority contingency: an airspace restriction for sUAS operations known as a UAS Volume Reservation (UVR). Upon issuance of a UVR, pilots were expected to reroute affected vehicles around the airspace. The level of automation (LoA) and workload of the flight rerouting task were varied. The LoA was manipulated by providing reroute suggestions ("auto" condition) for aircraft or by requiring pilots to manually reroute ("manual" condition) affected vehicles. Workload was varied as a function of the number of vehicles affected by the UVR contingencies: 2 vehicles ("low workload" condition) versus 4 vehicles ("high workload" condition). Additionally, some vehicles required pilots to adjust for terrain conflicts while avoiding the UVR region. Due to the COVID-19 pandemic, in-person data collection for this study was not possible. Researchers adapted to this circumstance through the development of remote data collection protocol. Participants were able to view adapted GCS displays using the Microsoft Teams teleconferencing platform and responded to events by using a verbal protocol developed for the experiment. Using this protocol, participants provided instructions for actions to a researcher, referred to as the surrogate, to carry out on their behalf. This presentation describes the experiment design, including special details for remote data collection via a subject-surrogate configuration, and concludes with planned data analysis and results to be presented at a later date.
multi-UAS↗
Quantifying the Value of Grid-Interactive Efficient Buildings through Field Study: Preprint
Quantifying the annual energy impacts of efficient technologies in commercial buildings has been well established by the building science field. As we move toward enabling grid-interactive efficient buildings (GEB) targeting flexible building operation and carbon reduction, quantification methods to evaluate time-sensitive peak load and emissions impact are much less defined. A number of national laboratories are working to field validate four different GEB software solutions that provide the capability to control multiple building end-use systems in multiple load flexibility modes (i.e., energy efficiency, load shed, load shift, and possible load modulation at the second to sub-second level). To guide the laboratory leads in effective measurement and verification (M&V) practices, two of the laboratories collaborated to define metrics to quantify the impacts of flexible load control on building demand, utility costs, carbon emissions, facility management, and occupant comfort. This paper summarizes the proposed metrics to quantify peak load and emission impacts in the field, decision parameters, approaches to accurately conduct M&V, lessons learned, and outstanding needs and next steps.
ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗
Quantifying the Value of Grid-Interactive Efficient Buildings through Field Study
Quantifying the annual energy impacts of efficient technologies in commercial buildings has been well established by the building science field. As we move toward enabling grid-interactive efficient buildings (GEB) targeting flexible building operation and carbon reduction, quantification methods to evaluate time-sensitive peak load and emissions impact are much less defined. A number of national laboratories are working to field validate four different GEB software solutions that provide the capability to control multiple building end-use systems in multiple load flexibility modes (i.e., energy efficiency, load shed, load shift, and possible load modulation at the second to sub-second level). To guide the laboratory leads in effective measurement and verification (M&V) practices, two of the laboratories collaborated to define metrics to quantify the impacts of flexible load control on building demand, utility costs, carbon emissions, facility management, and occupant comfort. This paper summarizes the proposed metrics to quantify peak load and emission impacts in the field, decision parameters, approaches to accurately conduct M&V, lessons learned, and outstanding needs and next steps.
Langner, Rois↗
The digital mirror Langmuir probe: Field programmable gate array implementation of real-time Langmuir probe biasing
High bandwidth, high spatial resolution measurements of electron temperature, density, and plasma potential are valuable for resolving turbulence in the boundary plasma of tokamaks. While conventional Langmuir probes can provide such measurements, either their temporal or spatial resolution is limited: the former by the sweep rate necessary for obtaining I-V characteristics and the latter by the need to use multiple electrodes, as is the case in triple and double probe configurations. The Mirror Langmuir Probe (MLP) bias technique overcomes these limitations by rapidly switching the voltage on a single electrode cycling between three bias states, each dynamically optimized for the local plasma conditions. The MLP system on Alcator C-Mod used analog circuitry to perform this function, measuring Te, VF, and Isat at 1.1 MSPS. Recently, a new prototype digital MLP controller has been implemented on a Red Pitaya Field Programmable Gate Array (FPGA) board which reproduces the functionality of the original controller and performs all data acquisition. There is also the potential to provide the plasma parameters externally for use with feedback control systems. The use of FPGA technology means the system is readily customizable at a fraction of the development time and implementation cost. A second Red Pitaya was used to test the MLP by simulating the current response of a physical probe using C-Mod experimental measurements. This project is available as a git repository to facilitate extensibility (e.g., real-time control outputs and more voltage states) and scalability through collaboration.
47 OTHER INSTRUMENTATION↗
tRNA ligase structure reveals kinetic competition between non-conventional mRNA splicing and mRNA decay
Yeast tRNA ligase (Trl1) is an essential trifunctional enzyme that catalyzes exon-exon ligation during tRNA biogenesis and the non-conventional splicing of HAC1 mRNA during the unfolded protein response (UPR). The UPR regulates the protein folding capacity of the endoplasmic reticulum (ER). ER stress activates Ire1, an ER-resident kinase/RNase, which excises an intron from HAC1 mRNA followed by exon-exon ligation by Trl1. The spliced product encodes for a potent transcription factor that drives the UPR. Here we report the crystal structure of Trl1 RNA ligase domain from Chaetomium thermophilum at 1.9 Å resolution. Structure-based mutational analyses uncovered kinetic competition between RNA ligation and degradation during HAC1 mRNA splicing. Incompletely processed HAC1 mRNA is degraded by Xrn1 and the Ski/exosome complex. We establish cleaved HAC1 mRNA as endogenous substrate for ribosome-associated quality control. We conclude that mRNA decay and surveillance mechanisms collaborate in achieving fidelity of non-conventional mRNA splicing during the UPR.
59 BASIC BIOLOGICAL SCIENCES↗
Optical Properties of Aerosols from Long Term Ground-Based Aeronet Measurements
AERONET is an optical ground-based aerosol monitoring network and data archive supported by NASA's Earth Observing System and expanded by federation with many non-NASA institutions including AEROCAN (AERONET CANada) and PHOTON (PHOtometrie pour le Traiteinent Operatonnel de Normalisation Satellitaire). The network hardware consists of identical automatic sun-sky scanning spectral radiometers owned by national agencies and universities purchased for their own monitoring and research objectives. Data are transmitted hourly through the data collection system (DCS) on board the geostationary meteorological satellites GMS, GOES and METEOSAT and received in a common archive for daily processing utilizing a peer reviewed series of algorithms thus imposing a standardization and quality control of the product data base. Data from this collaboration provides globally distributed near real time observations of aerosol spectral optical depths, aerosol size distributions, and precipitable water in diverse aerosol regimes. Access to the AERONET data base has shifted from the interactive program 'demonstrat' (reserved for PI's) to the AERONET homepage allowing faster access and greater development for GIS object oriented retrievals and analysis with companion geocoded data sets from satellites, LIDAR and solar flux measurements for example. We feel that a significant yet under utilized component of the AERONET data base are inversion products made from hourly principal plane and almucanter measurements. The current inversions have been shown to retrieve aerosol volume size distributions. A significant enhancement to the inversion code has been developed and is presented in these proceedings.
Holben, B. N.↗