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All sources NASA NTRS DOE OSTI

DOE OSTI2021

Controlled cyclization of peptoids to form chiral diketopiperazines

The present disclosure provides improved methods for controlled cyclization of peptoid dimers to form N,N′-2,5-diketopiperazines (N,N′-2,5-DKPs) with significant selectivity. In at least some examples, selectivity is based on a serendipitous conglomeration of slow exchange of amide rotamers, steric repulsion from the degree of α-substitution, and the geometric bulk of an amine nucleophile. By varying reaction conditions, the selectivity of the reaction and formation of a particular N,N′-2,5-DKP can be switched. The cyclization works in the presence of a variety of protection groups and diverse functionalities. The teachings herein provide techniques for synthesizing N,N′-2,5-DKPs that can be readily docked with drug candidates for shuttling across the blood brain barrier. This method provides a facile way to produce substituted DKPs containing groups ready for post-modification to include docking drug candidates.

Williams, Robert F.↗

NASA NTRS1987

Teaching artificial neural systems to drive: Manual training techniques for autonomous systems

A methodology was developed for manually training autonomous control systems based on artificial neural systems (ANS). In applications where the rule set governing an expert's decisions is difficult to formulate, ANS can be used to extract rules by associating the information an expert receives with the actions taken. Properly constructed networks imitate rules of behavior that permits them to function autonomously when they are trained on the spanning set of possible situations. This training can be provided manually, either under the direct supervision of a system trainer, or indirectly using a background mode where the networks assimilates training data as the expert performs its day-to-day tasks. To demonstrate these methods, an ANS network was trained to drive a vehicle through simulated freeway traffic.

Shepanski, J. F.↗

NASA NTRS2016

Climate Impact and GIS Education Using Realistic Applications of Data.gov Thematic Datasets in a Structured Lesson-Based Workbook

This project created a workbook which teaches Earth Science to undergraduate and graduate students through guided in-class activities and take-home assignments organized around climate topics which use GIS to teach key geospatial analysis techniques and cartography skills. The workbook is structured to the White House's Data.gov climate change themes, which include Coastal Flooding, Ecosystem Vulnerability, Energy Infrastructure, Arctic, Food Resilience, Human Health, Transportation, Tribal Nations, and Water. Each theme provides access to framing questions, associated data, interactive tools, and further reading (e.g. The US Climate Resilience Toolkit and National Climate Assessment). Lessons make use of the respective theme's available resources. The structured thematic approach is designed to encourage independent exploration. The goal is to teach climate concepts and concerns, GIS techniques and approaches, and effective cartographic representation and communication results; and foster a greater awareness of publicly available resources and datasets. To reach more audiences more effectively, a two level approach was used. Level 1 serves as an introductory study and relies on only freely available interactive tools to reach audiences with fewer resources and less familiarity. Level 2 presents a more advanced case study, and focuses on supporting common commercially available tool use and real-world analysis techniques.

Satellite Imagery↗

NASA NTRS1981

Why use case studies rather than simulation-gaming techniques or library research?

Method which present a student with a more challenging and true to life situation of needing to conduct research in a problem solving context--and not thinking about organization of format until research and thinking are complete are investigated. Simulation-gaming techniques which attempt to teach initiative and creativity that library research are used for this purpose. However, it is shown case studies provide the greatest opportunities to engage the students in problem solving situations in which they develop skills as researchers and writers.

Mcdonald, S. W.↗

NASA NTRS2012

IMAGESEER - IMAGEs for Education and Research

IMAGESEER is a new Web portal that brings easy access to NASA image data for non-NASA researchers, educators, and students. The IMAGESEER Web site and database are specifically designed to be utilized by the university community, to enable teaching image processing (IP) techniques on NASA data, as well as to provide reference benchmark data to validate new IP algorithms. Along with the data and a Web user interface front-end, basic knowledge of the application domains, benchmark information, and specific NASA IP challenges (or case studies) are provided.

Le Moigne, Jacqueline↗

NASA NTRS1988

Teaching old spacecraft new tricks

The technique of sending existing space probes on extended mission by altering their orbital paths with gravity-assist maneuvers and relatively brief rocket firings is examined. The use of the technique to convert the International Sun-Earth Explorer 3 mission into the International Cometary Explorer mission is discussed. Other examples are considered, including the extension of the Giotto mission and the retargeting of the Sakigake spacecraft. The original and altered trajectories of these three missions are illustrated.

Farquhar, Robert↗

DOE OSTI2022

Implementation of a Practical Teaching Course on Protein Engineering

Protein Engineering is a highly evolved field of engineering aimed at developing proteins for specific industrial, medical, and research applications. Here, we present a practical teaching course to demonstrate fundamental techniques used to express, purify and analyze a recombinant protein produced in Escherichia coli—the enhanced green fluorescent protein (eGFP). The methodologies used for eGFP production were introduced sequentially over six laboratory sessions and included (i) bacterial growth, (ii) sonication (for cell lysis), (iii) affinity chromatography and dialysis (for eGFP purification), (iv) bicinchoninic acid (BCA) and fluorometry assays for total protein and eGFP quantification, respectively, and (v) sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) for qualitative analysis. All groups were able to isolate the eGFP from the cell lysate with purity levels up to 72%. Additionally, a mass balance analysis performed by the students showed that eGFP yields up to 46% were achieved at the end of the purification process following the adopted procedures. A sensitivity analysis was performed to pinpoint the most critical steps of the downstream processing.

Gomes, Luciana (ORCID:0000000289921097)↗

DOE OSTI2022

Physics-informed machine learning modeling for predictive control using noisy data

Due to the occurrence of over-fitting at the learning phase, the modeling of chemical processes via artificial neural networks (ANN) by using corrupted data (i.e., noisy data) is an ongoing challenge. Therefore, this work investigates the effect of both Gaussian and non-Gaussian noise on the performance of process-structure based recurrent neural networks (RNN) models, which take the form of partially-connected RNN models in this work, that are used to approximate a class of multi-input-multi-outputs nonlinear systems. Furthermore, two different techniques, specifically Monte Carlo dropout and co-teaching, are utilized in the development of partially-connected RNN models. Here, these two techniques are employed to reduce the over-fitting in ANNs when noisy data is used in the training process and, hence, to improve the open-loop accuracy as well as the closed-loop performance under a Lyapunov-based model predictive controller (MPC). Aspen Plus Dynamics, a well-known high-fidelity process simulator, is used to simulate a large-scale chemical process application in order to demonstrate the anticipated improvements in both open-loop approximation and closed-loop controller performance in the presence of Gaussian and non-Gaussian noise in the data set using physics-informed RNNs.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2012

NASA IMAGESEER: NASA IMAGEs for Science, Education, Experimentation and Research

A number of web-accessible databases, including medical, military or other image data, offer universities and other users the ability to teach or research new Image Processing techniques on relevant and well-documented data. However, NASA images have traditionally been difficult for researchers to find, are often only available in hard-to-use formats, and do not always provide sufficient context and background for a non-NASA Scientist user to understand their content. The new IMAGESEER (IMAGEs for Science, Education, Experimentation and Research) database seeks to address these issues. Through a graphically-rich web site for browsing and downloading all of the selected datasets, benchmarks, and tutorials, IMAGESEER provides a widely accessible database of NASA-centric, easy to read, image data for teaching or validating new Image Processing algorithms. As such, IMAGESEER fosters collaboration between NASA and research organizations while simultaneously encouraging development of new and enhanced Image Processing algorithms. The first prototype includes a representative sampling of NASA multispectral and hyperspectral images from several Earth Science instruments, along with a few small tutorials. Image processing techniques are currently represented with cloud detection, image registration, and map cover/classification. For each technique, corresponding data are selected from four different geographic regions, i.e., mountains, urban, water coastal, and agriculture areas. Satellite images have been collected from several instruments - Landsat-5 and -7 Thematic Mappers, Earth Observing-1 (EO-1) Advanced Land Imager (ALI) and Hyperion, and the Moderate Resolution Imaging Spectroradiometer (MODIS). After geo-registration, these images are available in simple common formats such as GeoTIFF and raw formats, along with associated benchmark data.

Le Moigne, Jacqueline↗

NASA NTRS1992

Integrating principles and multidisciplinary projects in design education

The critical need to improve engineering design education in the U.S. is presented and a number of actions to achieve that end are discussed. The importance of teaching undergraduates the latest methods and principles through the means of team design in multidisciplinary projects leading to a testable product is emphasized. Desirable training for design instructors is described and techniques for selecting and managing projects that teach effectively are discussed.

Nevill, Gale E., Jr.↗

NASA NTRS1989

The JAU-JPL anthropomorphic telerobot

Work in progress on the new anthropomorphic telerobot is described. The initial robot configuration consists of a seven DOF arm and a sixteen DOF hand, having three fingers and a thumb. The robot has active compliance, enabling subsequent dual arm manipulations. To control the rather complex configuration of this robot, an exoskeleton master arm harness and a glove controller were built. The controller will be used for teleoperational tasks and as a research tool to efficiently teach the computer controller advanced manipulation techniques.

Jau, Bruno M.↗

NASA NTRS2007

Bridging the Gap between Earth Science and Students: An Integrated Approach using NASA Earth Science Climate Data

Under the auspices of the Department of Education's No Child Left Behind (NCLB) Act, beginning in 2007 students will be tested in the science area. There are many techniques that educators can employ to teach students science. The use of authentic materials or in this case authentic data can be an engaging alternative to more traditional methods. An Earth science classroom is a great place for the integration of authentic data and science concepts. The National Aeronautics and Space Administration (NASA) has a wealth of high quality Earth science data available to the general public. For instance, the Atmospheric Science Data Center (ASDC) at NASA s Langley Research Center houses over 800 Earth science data sets related to Earth's radiation budget, clouds, aerosols and tropospheric chemistry. These data sets were produced to increase academic understanding of the natural and anthropogenic factors that influence global climate; however, a major hurdle in using authentic data is the size of the data and data documentation. To facilitate the use of these data sets for educational purposes, the Mentoring and inquirY using NASA Data on Atmospheric and Earth science for Teachers and Amateurs (MY NASA DATA) project has been established to systematically support educational activities at all levels of formal and informal education. The MY NASA DATA project accomplishes this by reducing these large data holdings to microsets that are easily accessible and explored by K-12 educators and students though the project's Web page. MY NASA DATA seeks to ease the difficulty in understanding the jargon-heavy language of Earth science. This manuscript will show how MY NASA DATA provides resources for NCLB implementation in the science area through an overview of the Web site, the different microsets available, the lesson plans and computer tools, and an overview of educational support mechanisms.

Alston, Erica J.↗

NASA NTRS1998

Use of Microgravity to Control the Microstructure of Eutectics

This grant began in June of 1996. Its long term goal is to be able to control the microstructure of directionally solidified eutectic alloys, through an improved understanding of the influence of convection. The primary objective of the present projects is to test hypotheses for the reported influence of microgravity on the microstructure of three fibrous eutectics (MnBi-Bi, InSb-NiSb, Al3Ni-Al). A secondary objective is to determine the influence of convection on the microstructure of other eutectic alloys. Two doctoral students and a masters student supported as a teaching assistant were recruited for this research. Techniques were developed for directional solidification of MnBi-Bi eutectics with periodic application of current pulses to produce an oscillatory freezing rate. Image analysis techniques were developed to obtain the variation in MnBi fiber spacing, which was found to be normally distributed. The mean and standard deviation of fiber spacing were obtained for several freezing conditions. Eighteen ampoules were prepared for use in the gradient freeze furnace QUELD developed at Queen's University for use in microgravity. Nine of these ampoules will be solidified soon at Queen's in a ground-based model. We hope to solidify the other nine in the QUELD that is mounted on the Canadian Microgravity Isolation Mount on MIR. Techniques are being developed for directional solidification of the Al-Si eutectic at different freezing rates, with and without application of accelerated crucible rotation to induce convection. For the first time, theoretical methods are being developed to analyze eutectic solidification with an oscillatory freezing rate. In a classical sharp-interface model, we found that an oscillatory freezing rate increases the deviation of the average interfacial composition from the eutectic, and increases the undercooling of the two phases by different amounts. This would be expected to change the volume fraction solidifying and the fiber spacing. Because of difficulties in tracking the freezing interfaces of the two solid phases, a phase-field model is also being developed. A paper demonstrating application of phase field methods to periodic structures has been submitted for publication.

Wilcox, William R.↗

NASA NTRS2009

Johnson Space Center's Risk and Reliability Analysis Group 2008 Annual Report

The Johnson Space Center (JSC) Safety & Mission Assurance (S&MA) Directorate s Risk and Reliability Analysis Group provides both mathematical and engineering analysis expertise in the areas of Probabilistic Risk Assessment (PRA), Reliability and Maintainability (R&M) analysis, and data collection and analysis. The fundamental goal of this group is to provide National Aeronautics and Space Administration (NASA) decisionmakers with the necessary information to make informed decisions when evaluating personnel, flight hardware, and public safety concerns associated with current operating systems as well as with any future systems. The Analysis Group includes a staff of statistical and reliability experts with valuable backgrounds in the statistical, reliability, and engineering fields. This group includes JSC S&MA Analysis Branch personnel as well as S&MA support services contractors, such as Science Applications International Corporation (SAIC) and SoHaR. The Analysis Group s experience base includes nuclear power (both commercial and navy), manufacturing, Department of Defense, chemical, and shipping industries, as well as significant aerospace experience specifically in the Shuttle, International Space Station (ISS), and Constellation Programs. The Analysis Group partners with project and program offices, other NASA centers, NASA contractors, and universities to provide additional resources or information to the group when performing various analysis tasks. The JSC S&MA Analysis Group is recognized as a leader in risk and reliability analysis within the NASA community. Therefore, the Analysis Group is in high demand to help the Space Shuttle Program (SSP) continue to fly safely, assist in designing the next generation spacecraft for the Constellation Program (CxP), and promote advanced analytical techniques. The Analysis Section s tasks include teaching classes and instituting personnel qualification processes to enhance the professional abilities of our analysts as well as performing major probabilistic assessments used to support flight rationale and help establish program requirements. During 2008, the Analysis Group performed more than 70 assessments. Although all these assessments were important, some were instrumental in the decisionmaking processes for the Shuttle and Constellation Programs. Two of the more significant tasks were the Space Transportation System (STS)-122 Low Level Cutoff PRA for the SSP and the Orion Pad Abort One (PA-1) PRA for the CxP. These two activities, along with the numerous other tasks the Analysis Group performed in 2008, are summarized in this report. This report also highlights several ongoing and upcoming efforts to provide crucial statistical and probabilistic assessments, such as the Extravehicular Activity (EVA) PRA for the Hubble Space Telescope service mission and the first fully integrated PRAs for the CxP's Lunar Sortie and ISS missions.

Valentine, Mark↗

NASA NTRS1978

Applications of aerospace technology in biology and medicine

A bipolar, donor-recipient model of medical technology transfer is introduced to provide a basis for the team's methodology. That methodology is designed (1) to identify medical problems and NASA technology that in combination constitute opportunities for successful medical products, (2) to obtain the early participation of industry in the transfer proces, and (3) to obtain acceptance by the medical community of new medical products based on NASA technology. Two commercial technology transfers and five institutional technology transfers were completed in 1977. A new, commercially available teaching manikin system uses NASA-developed concepts and techniques for effective visual presentation of information and data. Drugs shipped by the National Cancer Institute to locations throughout the world are maintained at low temperatures in shipping containers that incorporate recommendations made by NASA.

Beall, H. C.↗

NASA NTRS1974

Current therapeutic techniques and rehabilitation from neurological disorders

Rancho Los Amigos Hospital is a 1100-bed teaching hospital that is primarily oriented toward rehabilitation. The individual services that deal with neuromuscular disorders are categorically disease entity oriented: They are directed toward the major problems, such as spinal cord injuries, amputations, stroke, cerebral palsy, and rheumatoid arthritis. The services at Rancho cross many traditional medical specialty barriers.

Nickel, V. L.↗

DOE OSTI2023

Practical Guide to Chemometric Analysis of Optical Spectroscopic Data

The methodology and mathematical treatment of several classic multivariate methods for the analysis of spectroscopic data is demonstrated in a straightforward way that can be used as a basis for teaching an undergraduate introductory course on chemometric analysis. The multivariate techniques of classical least squares (CLS), principal component regression (PCR), and partial least squares (PLS), as well as the univariate Beer’s law method have been described and compared, building students’ understanding by starting with the univariate method and progressing step by step into the multivariate methods. Equations for the production of regression vectors from training set spectral data is described and their use demonstrated for the prediction of constituent concentrations on a separate validation set of spectra. Extreme care is taken to ensure consistency in variable formatting of data matrices. This provides a key foundation to understanding how spectral data are manipulated using these different mathematical approaches for building quantitative regression models. Each method is applied to a real-world data set, and the results are discussed to show students the types of information that can be gleaned from each method. A training set comprised of 20 infrared absorbance spectra containing 3 constituents (benzene, polystyrene, and gasoline) of known composition are used to demonstrate the matrix operations for each regression method. A separate set of 12 real-world napalm samples (containing benzene, polystyrene and gasoline) are used as a validation set to demonstrate the ability to utilize the regression models on an unknown dataset. A toolbox (PNNL Chemometric Toolbox) written in MATLAB language is supplied in the Supplemental Information file and can be used as a companion for understanding the development and deployment of the chemometric algorithms described in this paper. The datasets of the infrared spectra are also supplied, allowing users to build and inspect the chemometric models on their own. Finally, the Toolbox includes scripts to assist users in loading their own datasets into MATLAB and performing CLS, PCR, and PLS on their data.

Upper-Division Undergraduate, Analytical Chemistry↗

NASA NTRS2005

Software Template for Instruction in Mathematics

Intelligent Math Tutor (IMT) is a software system that serves as a template for creating software for teaching mathematics. IMT can be easily connected to artificial-intelligence software and other analysis software through input and output of files. IMT provides an easy-to-use interface for generating courses that include tests that contain both multiple-choice and fill-in-the-blank questions, and enables tracking of test scores. IMT makes it easy to generate software for Web-based courses or to manufacture compact disks containing executable course software. IMT also can function as a Web-based application program, with features that run quickly on the Web, while retaining the intelligence of a high-level language application program with many graphics. IMT can be used to write application programs in text, graphics, and/or sound, so that the programs can be tailored to the needs of most handicapped persons. The course software generated by IMT follows a "back to basics" approach of teaching mathematics by inducing the student to apply creative mathematical techniques in the process of learning. Students are thereby made to discover mathematical fundamentals and thereby come to understand mathematics more deeply than they could through simple memorization.

Shelton, Robert O.↗