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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Improving Traditional Registrational Trial End Points: Development and Application of a Desirability of Outcome Ranking End Point for Complicated Urinary Tract Infection Clinical Trials

Abstract Background Traditional end points used in registrational randomized, controlled trials (RCTs) often do not allow for complete interpretation of the full range of potential clinical outcomes. Desirability of outcome ranking (DOOR) is an approach to the design and analysis of clinical trials that incorporates benefits and risks of novel treatment strategies and provides a global assessment of patient experience. Methods Through a multidisciplinary committee of experts in infectious diseases, clinical trial design, drug regulation, and patient experience, we developed a DOOR end point for infectious disease syndromes and demonstrated how this could be applied to 3 registrational drug trials (ZEUS, APEKS-cUTI, and DORI-05) for complicated urinary tract infections (cUTIs). ZEUS compared fosfomycin to piperacillin/tazobactam, APEKS-cUTI compared cefiderocol to imipenem, and DORI-05 compared doripenem to levofloxacin. Using DOOR, we estimated the probability of a more desirable outcome with each investigational antibacterial drug. Results In each RCT, the DOOR distribution was similar and the probability that a patient in the investigational arm would have a more desirable outcome than a patient in the control arm had a 95% confidence interval containing 50%, indicating no significant difference between treatment arms. DOOR facilitated improved understanding of potential trade-offs between clinical efficacy and safety. Partial credit and subgroup analyses also highlight unique attributes of DOOR. Conclusions DOOR can effectively be used in registrational cUTI trials. The DOOR end point presented here can be adapted for other infectious disease syndromes and prospectively incorporated into future clinical trials.

Immunology↗
DOE OSTI2026

Data for An End-to-End Pipeline for Succinic Acid Production at an Industrially Relevant Scale Using Issatchenkia orientalis

Microbial production of succinic acid (SA) at an industrially relevant scale has been hindered by high downstream processing costs arising from neutral pH fermentation for over three decades. Here, we metabolically engineer the acid-tolerant yeast Issatchenkia orientalis for SA production, attaining the highest titers in sugar-based media at low pH (pH 3) in fed-batch fermentations, i.e. 109.5 g/L in minimal medium and 104.6 g/L in sugarcane juice medium. We further perform batch fermentation using sugarcane juice medium in a pilot-scale fermenter (300×) and achieve 63.1 g/L of SA, which can be directly crystallized with a yield of 64.0%. Finally, we simulate an end-to-end low-pH SA production pipeline, and techno-economic analysis and life cycle assessment indicate our process is financially viable and can reduce greenhouse gas emissions by 34–90% relative to fossil-based production processes. We expect I. orientalis can serve as a general industrial platform for production of organic acids.

Metabolomics↗
DOE OSTI2020

Heterogeneous Machine Learning on High Performance Computing for End to End Driving of Autonomous Vehicles

Current artificial intelligence techniques for end to end driving of autonomous vehicles typically rely on a single form of learning or training processes along with a corresponding dataset or simulation environment. Relatively speaking, success has been shown for a variety of learning modalities in which it can be shown that the machine can successfully “drive” a vehicle. However, the realm of real-world driving extends significantly beyond the realm of limited test environments for machine training. This creates an enormous gap in capability between these two realms. With their superior neural network structures and learning capabilities, humans can be easily trained within a short period of time to proceed from limited test environments to real world driving. For machines though, this gap is guarded by at least two challenges: 1) machine learning techniques remain brittle and unable to generalize to a wide range of scenarios, and 2) effective training data that enhances generalization and generates the desired driving behavior. Further, each challenge can be computationally intensive on its own thereby exasperating the gap. Moreover, is has not yet been shown that a single form of learning or training is capable of addressing a large range of scenarios. As a result, solving the first challenge does not inherently solve the second and vice versa. The work described here discusses an approach to address the first challenge that would also provide a foundation for solving the second. Our approach utilizes a combination of conditional imitation learning with a static dataset, reinforcement learning with a simulation environment, and high-performance computing to train a neural network. As a result, this reduces the “time to solution” from to the existing techniques for autonomous driving and provides an extensible framework to address the second key challenge.

autonomous vehicles↗
DOE OSTI2022

Module 5: End Use Assessment - Lesson 5.1: Introduction to End Use Assessment [Slides]

End use assessment is the process of performing a technical evaluation of the stated end use in relation to the requested commodity and the activities of the end user. An end use assessment requires sufficiently detailed information on the procurement request, commodity technical specifications, end use conditions, end user business activities, industry norms and trends, and WMD or delivery system applications of stated end use. Reviewers should be aware of red flags related to end use assessment. Use best practices when writing an end use assessment. Be familiar with technical resources for end use assessments.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS2006

Standardizing an End-to-end Accounting Service

Currently there are no space system standards available for space agencies to accomplish end-to-end accounting. Such a standard does not exist for spacecraft operations nor for tracing the relationship between the mission planning activities, the command sequences designed to perform those activities, the commands formulated to initiate those activities and the mission data and specifically the mission data products created by those activities. In order for space agencies to cross-support one another for data accountability/data tracing and for inter agency spacecraft to interoperate with each other, an international CCSDS standard for end-to-end data accountability/tracing needs to be developed. We will first describe the end-to-end accounting service model and functionality that supports the service. This model will describe how science plans that are ultimately transformed into commands can be associated with the telemetry products generated as a result of their execution. Moreover, the interaction between end-to-end accounting and service management will be explored. Finally, we will show how the standard end-to-end accounting service can be applied to a real life flight project i.e., the Mars Reconnaissance Orbiter project.

recommendations↗
NASA NTRS2013

Orion MPCV GN and C End-to-End Phasing Tests

End-to-end integration tests are critical risk reduction efforts for any complex vehicle. Phasing tests are an end-to-end integrated test that validates system directional phasing (polarity) from sensor measurement through software algorithms to end effector response. Phasing tests are typically performed on a fully integrated and assembled flight vehicle where sensors are stimulated by moving the vehicle and the effectors are observed for proper polarity. Orion Multi-Purpose Crew Vehicle (MPCV) Pad Abort 1 (PA-1) Phasing Test was conducted from inertial measurement to Launch Abort System (LAS). Orion Exploration Flight Test 1 (EFT-1) has two end-to-end phasing tests planned. The first test from inertial measurement to Crew Module (CM) reaction control system thrusters uses navigation and flight control system software algorithms to process commands. The second test from inertial measurement to CM S-Band Phased Array Antenna (PAA) uses navigation and communication system software algorithms to process commands. Future Orion flights include Ascent Abort Flight Test 2 (AA-2) and Exploration Mission 1 (EM-1). These flights will include additional or updated sensors, software algorithms and effectors. This paper will explore the implementation of end-to-end phasing tests on a flight vehicle which has many constraints, trade-offs and compromises. Orion PA-1 Phasing Test was conducted at White Sands Missile Range (WSMR) from March 4-6, 2010. This test decreased the risk of mission failure by demonstrating proper flight control system polarity. Demonstration was achieved by stimulating the primary navigation sensor, processing sensor data to commands and viewing propulsion response. PA-1 primary navigation sensor was a Space Integrated Inertial Navigation System (INS) and Global Positioning System (GPS) (SIGI) which has onboard processing, INS (3 accelerometers and 3 rate gyros) and no GPS receiver. SIGI data was processed by GN&C software into thrust magnitude and direction commands. The processing changes through three phases of powered flight: pitchover, downrange and reorientation. The primary inputs to GN&C are attitude position, attitude rates, angle of attack (AOA) and angle of sideslip (AOS). Pitch and yaw attitude and attitude rate responses were verified by using a flight spare SIGI mounted to a 2-axis rate table. AOA and AOS responses were verified by using a data recorded from SIGI movements on a robotic arm located at NASA Johnson Space Center. The data was consolidated and used in an open-loop data input to the SIGI. Propulsion was the Launch Abort System (LAS) Attitude Control Motor (ACM) which consisted of a solid motor with 8 nozzles. Each nozzle has active thrust control by varying throat area with a pintle. LAS ACM pintles are observable through optically transparent nozzle covers. SIGI movements on robot arm, SIGI rate table movements and LAS ACM pintle responses were video recorded as test artifacts for analysis and evaluation. The PA-1 Phasing Test design was determined based on test performance requirements, operational restrictions and EGSE capabilities. This development progressed during different stages. For convenience these development stages are initial, working group, tiger team, Engineering Review Team (ERT) and final.

Neumann, Brian C.↗
DOE OSTI2021

Accelerating End-to-End Deep Learning for Particle Reconstruction using CMS open data

Machine learning algorithms are gaining ground in high energy physics for applications in particle and event identification, physics analysis, detector reconstruction, simulation and trigger. Currently, most data-analysis tasks at LHC experiments benefit from the use of machine learning. Incorporating these computational tools in the experimental framework presents new challenges. This paper reports on the implementation of the end-to-end deep learning with the CMS software framework and the scaling of the end-to-end deep learning with multiple GPUs. The end-to-end deep learning technique combines deep learning algorithms and low-level detector representation for particle and event identification. We demonstrate the end-to-end implementation on a top quark benchmark and perform studies with various hardware architectures including single and multiple GPUs and Google TPU.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1998

End-to-End Data System Architecture for the Space Station Biological Research Project

The Space Station Biological Research Project (SSBRP) Is developing hardware referred to as the "facility" for providing life sciences research capability on the International Space Station. This hardware includes several biological specimen habitats, habitat holding racks, a centrifuge and a glovebox. An SSBRP end to end data system architecture has been developed to allow command and control of the facility from the ground, either with crew assistance or autonomously. The data system will be capable of handling commands, sensor data, and video from multiple cameras. The data will traverse through several onboard and ground networks and processing entities including the SSBRP and Space Station onboard and ground data systems. A large number of onboard and ground (,entities of the data system are being developed by the Space Station Program, other NASA centers and the International Partners. The SSBRP part of the system which includes the habitats, holding racks, and the ground operations center, User Operations Facility (UOF) will be developed by a multitude of geographically distributed development organizations. The SSBRP has the responsibility to define the end to end data and communications systems to make the interfaces manageable and verifiable with multiple contractors with widely varying development constraints and schedules. This paper provides an overview of the SSBRP end-to-end data system. Specifically, it describes the hardware, software and functional interactions of individual systems, and interface requirements among various entities of the end-to-end system.

Mian, Arshad↗
NASA NTRS2002

LWS/SET End-to-End Data System

This paper describes the concept for the End-to-End Data System that will support NASA's Living With a Star Space Environment Testbed missions. NASA has initiated the Living With a Star (LWS) Program to develop a better scientific understanding to address the aspects of the connected Sun-Earth system that affect life and society. A principal goal of the program is to bridge the gap.between science, engineering, and user application communities. The Space Environment Testbed (SET) Project is one element of LWS. The Project will enable future science, operational, and commercial objectives in space and atmospheric environments by improving engineering approaches to the accommodation and/or mitigation of the effects of solar variability on technological systems. The End-to-end data system allows investigators to access the SET control center, command their experiments, and receive data from their experiments back at their home facility, using the Internet. The logical functioning of major components of the end-to-end data system are described, including the GSFC Payload Operations Control Center (POCC), SET Payloads, the GSFC SET Simulation Lab, SET Experiment PI Facilities, and Host Systems. Host Spacecraft Operations Control Centers (SOCC) and the Host Spacecraft are essential links in the end-to-end data system, but are not directly under the control of the SET Project. Formal interfaces will be established between these entities and elements of the SET Project. The paper describes data flow through the system, from PI facilities connecting to the SET operations center via the Internet, communications to SET carriers and experiments via host systems, to telemetry returns to investigators from their flight experiments. It also outlines the techniques that will be used to meet mission requirements, while holding development and operational costs to a minimum. Additional information is included in the original extended abstract.

Giffin, Geoff↗
NASA NTRS2016

A Robust Method to Integrate End-to-End Mission Architecture Optimization Tools

End-to-end mission simulations include multiple phases of flight. For example, an end-to-end Mars mission simulation may include launch from Earth, interplanetary transit to Mars and entry, descent and landing. Each phase of flight is optimized to meet specified constraints and often depend on and impact subsequent phases. The design and optimization tools and methodologies used to combine different aspects of end-to-end framework and their impact on mission planning are presented. This work focuses on a robust implementation of a Multidisciplinary Design Analysis and Optimization (MDAO) method that offers the flexibility to quickly adapt to changing mission design requirements. Different simulations tailored to the liftoff, ascent, and atmospheric entry phases of a trajectory are integrated and optimized in the MDAO program Isight, which provides the user a graphical interface to link simulation inputs and outputs. This approach provides many advantages to mission planners, as it is easily adapted to different mission scenarios and can improve the understanding of the integrated system performance within a particular mission configuration. A Mars direct entry mission using the Space Launch System (SLS) is presented as a generic end-to-end case study. For the given launch period, the SLS launch performance is traded for improved orbit geometry alignment, resulting in an optimized a net payload that is comparable to that in the SLS Mission Planner's Guide.

Lugo, Rafael↗
DOE OSTI2020

End-to-End Physics Event Classification with CMS Open Data: Applying Image-Based Deep Learning to Detector Data for the Direct Classification of Collision Events at the LHC

This paper describes the construction of novel end-to-end image-based classifiers that directly leverage low-level simulated detector data to discriminate signal and background processes in pp collision events at the Large Hadron Collider at CERN. To better understand what end-to-end classifiers are capable of learning from the data and to address a number of associated challenges, we distinguish the decay of the standard model Higgs boson into two photons from its leading background sources using high-fidelity simulated CMS Open Data. We demonstrate the ability of end-to-end classifiers to learn from the angular distribution of the photons recorded as electromagnetic showers, their intrinsic shapes, and the energy of their constituent hits, even when the underlying particles are not fully resolved, delivering a clear advantage in such cases over purely kinematics-based classifiers.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

An End-To-End Earthquake Detection Method for Joint Phase Picking and Association Using Deep Learning

Earthquake monitoring by seismic networks typically involves a workflow consisting of phase detection/picking, association, and location tasks. In recent years, the accuracy of these individual stages has been improved through the use of machine learning techniques. Here, in this study, we introduce a new end-to-end approach that improves overall earthquake detection accuracy by jointly optimizing each stage of the detection pipeline. We propose a neural network architecture for the task of multi-station processing of seismic waveforms recorded over a seismic network. This end-to-end architecture consists of three sub-networks: a backbone network that extracts features from raw waveforms, a phase picking sub-network that picks P- and S-wave arrivals based on these features, and an event detection sub-network that aggregates the features from multiple stations to associate and detect earthquakes across a seismic network. We use these sub-networks together with a shift-and-stack module based on back-projection that introduces kinematic constraints on arrival times, allowing the neural network model to generalize to different velocity models and to variable station geometry in seismic networks. We evaluate our proposed method on the STanford EArthquake Dataset (STEAD) and on the 2019 Ridgecrest, CA earthquake sequence. The results demonstrate that our end-to-end approach can effectively pick P- and S-wave arrivals and achieve earthquake detection accuracy rivaling that of other state-of-the-art approaches. Because our approach preserves information across tasks in the detection pipeline, it has the potential to outperform approaches that do not.

58 GEOSCIENCES↗
DOE OSTI2021

End-to-End Jet Classification of Boosted Top Quarks with CMS Open Data

We describe a novel application of the end-to-end deep learning technique to the task of discriminating top quark-initiated jets from those originating from the hadronization of a light quark or a gluon. The end-to-end deep learning technique combines deep learning algorithms and low-level detector representation of the high-energy collision event. In this study, we use lowlevel detector information from the simulated CMS Open Data samples to construct the top jet classifiers. To optimize classifier performance we progressively add low-level information from the CMS tracking detector, including pixel detector reconstructed hits and impact parameters, and demonstrate the value of additional tracking information even when no new spatial structures are added. Relying only on calorimeter energy deposits and reconstructed pixel detector hits, the end-to-end classifier achieves a ROC-AUC score of 0.975±0.002 for the task of classifying boosted top quark jets. After adding derived track quantities, the classifier ROC-AUC score increases to 0.9824±0.0013, serving as the first performance benchmark for these CMS Open Data samples.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

End-to-end jet classification of boosted top quarks with the CMS open data

Here we describe a novel application of the end-to-end deep learning technique to the task of discriminating top quark-initiated jets from those originating from the hadronization of a light quark or a gluon. The end-to-end deep learning technique uses low-level detector representation of high-energy collision event as inputs to deep learning algorithms. In this study, we use low-level detector information from the simulated Compact Muon Solenoid (CMS) open data samples to construct the top jet classifiers. To optimize classifier performance we progressively add low-level information from the CMS tracking detector, including pixel detector reconstructed hits and impact parameters, and demonstrate the value of additional tracking information even when no new spatial structures are added. Relying only on calorimeter energy deposits and reconstructed pixel detector hits, the end-to-end classifier achieves an area under the receiver operator curve (AUC) score of 0.975 ± 0.002 for the task of classifying boosted top quark jets. After adding derived track quantities, the classifier AUC score increases to 0.9824 ± 0.0013, serving as the first performance benchmark for these CMS open data samples.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1978

End-to-End Information System design at the NASA Jet Propulsion Laboratory

Recognizing a pressing need of the 1980s to optimize the two-way flow of information between a ground-based user and a remote space-based sensor, an end-to-end approach to the design of information systems has been adopted at the Jet Propulsion Laboratory. The objectives of this effort are to ensure that all flight projects adequately cope with information flow problems at an early stage of system design, and that cost-effective, multi-mission capabilities are developed when capital investments are made in supporting elements. The paper reviews the End-to-End Information System (EEIS) activity at the Laboratory, and notes the ties to the NASA End-to-End Data System program.

Hooke, A. J.↗
NASA NTRS1978

End-to-End Information System design at the NASA Jet Propulsion Laboratory

In recognition of a pressing need of the 1980s to optimize the two-way flow of information between a ground-based user and a remote-space-based sensor, an end-to-end approach to the design of information systems has been adopted at the JPL. This paper reviews End-to-End Information System (EEIS) activity at the JPL, with attention given to the scope of the EEIS transfer function, and functional and physical elements of the EEIS. The relationship between the EEIS and the NASA End-to-End Data System program is discussed.

Hooke, A. J.↗
NASA NTRS1993

Miniature modular microwave end-to-end receiver

An end-to-end microwave receiver system contained in a single miniature hybrid package mounted on a single heatsink is presented. It includes an input end connected to a microwave receiver antenna and an output end which produces a digital count proportional to the amplitude of a signal of a selected microwave frequency band received at the antenna and corresponding to one of the water vapor absorption lines near frequencies of 20 GHz or 30 GHz. The hybrid package is on the order of several centimeters in length and a few centimeters in height and width. The package includes an L-shaped carrier having a base surface, a vertical wall extending up from the base surface and forming a corner therewith, and connection pins extending through the vertical wall. Modular blocks rest on the base surface against the vertical wall and support microwave monolithic integrated circuits on top surfaces thereof connected to the external connection pins. The modular blocks lie end-to-end on the base surface so as to be modularly removable by sliding along the base surface beneath the external connection pins away from the vertical wall.

Sukamto, Lin M.↗
NASA NTRS2001

Achieving End-to-End QoS in the Next Generation Internet: Integrated Services Over Differentiated Service Networks

Currently there are two approaches to provide Quality of Service (QoS) in the next generation Internet: An early one is the Integrated Services (IntServ) with the goal of allowing end-to-end QoS to be provided to applications; the other one is the Differentiated Services (DiffServ) architecture providing QoS in the backbone. In this context, a DiffServ network may be viewed as a network element in the total end-to-end path. The objective of this paper is to investigate the possibility of providing end-to-end QoS when IntServ runs over DiffServ backbone in the next generation Internet. Our results show that the QoS requirements of IntServ applications can be successfully achieved when IntServ traffic is mapped to the DiffServ domain in next generation Internet.

Bai, Haowei↗