Results for “Sample curation” — Page 22

NASA NTRS2007

Sample Return Primer and Handbook

This three-part Sample Return Primer and Handbook provides a road map for conducting the terminal phase of a sample return mission. The main chapters describe element-by-element analyses and trade studies, as well as required operations plans, procedures, contingencies, interfaces, and corresponding documentation. Based on the experiences of the lead Stardust engineers, the topics include systems engineering (in particular range safety compliance), mission design and navigation, spacecraft hardware and entry, descent, and landing certification, flight and recovery operations, mission assurance and system safety, test and training, and the very important interactions with external support organizations (non-NASA tracking assets, landing site support, and science curation).

Stardust↗

NASA NTRSDate not supplied

Investigating Commercial Off-The-Shelf (COTS) Glovebox and Support Components Compared to Custom Curatorial Laboratories

There is a need envisioned to investigate the application of commercial off-the-shelf (COTS) systems as tools that could be used within commercial preliminary curation as the expected space economy is supported and begins to take flight. NASA is involved with supporting and developing the space economy [1] and therefore it’s feasible that at some point, a commercial space company would bring back materials and either store initially, or permanently, within COTS equipment as a stand-in for custom curation laboratories. While utilizing opportunities to explore this capability at NASA-Johnson Space Center (JSC) during the establishment of other laboratories [2] it was realized that cleanliness and/or other properties could be evaluated for these COTS systems during their installation in advanced research facilities that are not ISO-class rated clean rooms. Several aspects of a COTS-Curation system were explored including various gloves for curation manipulation within a negative pressure glovebox (Fig.1), Balazs organic and inorganic contaminant levels testing prior to glovebox ever being used, mode swapping comparison of recirculation vs. single pass, constant monitoring of oxygen (O2) and moisture (H2O) levels in various conditions, etc. To acquire inorganic and organic compound loads inside the glovebox, Balazs wafer testing and gas sampling were implemented. These are standardized analytical tests provided by Balazs™ NanoAnalysis, a division of Air Liquide USA. Deployment of 8-inch silicon wafer witness plates for 24-hours in an undisturbed environment capture the organic compound load and inorganic trace metal contents which can be obtained by Vapor Phase Decomposition Inductively Coupled Plasma Mass Spectrometry (VPD ICP-MS). Balazs gas sample analysis was also performed for better measurements of volatile organic compounds (VOC) in glovebox air analyzed by Thermal Desorption Gas Chromatography Mass Spectrometry (TD GC-MS). These analytical testings were carried out in a controlled ultra high pure (UHP) gaseous nitrogen (N2)-purged environment where oxygen and moisture contents were continuously monitored at certain temperature and pressure. The preliminary outcomes of these testings are promising. The COTS systems appear to maintain the steady-state controlled environment for days, if not weeks, with uninterrupted gaseous N2-supply which was operated from a standard medium pressure LN2 250L 230L dewar, exchanged as needed. The outgassing load can be maintained by selecting the glove materials that have the least outgassing and particle shedding performances. Further experiments will be considered to validate the preliminary findings. While this project is exploratory, it is not intended as an endorsement by NASA Curation for approved materials or usage for advanced curatorial activities. NASA does not endorse nor promote any one particular product or company. References: [1] McCubbin F. M. et al. (2019) Space Science Reviews 215:A48. [2] Lewis, E.K. et. al (2024) LPSC LV, Abstract #2457.

Curation↗

DOE OSTI2019

Assessment of BOLD and GenBank – Their accuracy and reliability for the identification of biological materials

Taxonomic identification of biological materials can be achieved through DNA barcoding, where an unknown “barcode” sequence is compared to a reference database. In many disciplines, obtaining accurate taxonomic identifications can be imperative (e.g., evolutionary biology, food regulatory compliance, forensics). The Barcode of Life DataSystems (BOLD) and GenBank are the main public repositories of DNA barcode sequences. In this study, an assessment of the accuracy and reliability of sequences in these databases was performed. To achieve this, 1) curated reference materials for plants, macro-fungi and insects were obtained from national collections, 2) relevant barcode sequences (rbcL, matK, trnH-psbA, ITS and COI) from these reference samples were generated and used for searching against both databases, and 3) optimal search parameters were determined that ensure the best match to the known species in either database. While GenBank outperformed BOLD for species-level identification of insect taxa (53% and 35%, respectively), both databases performed comparably for plants and macro-fungi (~81% and ~57%, respectively). Results illustrated that using a multi-locus barcode approach increased identification success. This study outlines the utility of the BLAST search tool in GenBank and the BOLD identification engine for taxonomic identifications and identifies some precautions needed when using public sequence repositories in applied scientific disciplines.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1981

Antarctic meteorite newsletter. Volume 4: Number 1, February 1981: Antarctic meteorite descriptions, 1976, 1977, 1978, 1979

This issue of the Newsletter is essentially a catalog of all antarctic meteorites in the collections of the Johnson Space Center Curation Facility and the Smithsonian except for 288 pebbles now being classed. It includes listings of all previously distributed data sheets plus a number of new ones for 1979. Indexes of samples include meteorite name/number, classification, and weathering category. Separate indexes list type 3 and 4 chondrites, all irons, all achondrites, and all carbonaceous chondrites.

Stone, R.↗

DOE OSTI2021

Impact of Pelvic Radiation Therapy for Prostate Cancer on Global Metabolic Profiles and Microbiota-Driven Gastrointestinal Late Side Effects: A Longitudinal Observational Study

Radiation therapy to the prostate and pelvic lymph nodes (PLNRT) is part of the curative treatment of high-risk prostate cancer. Yet, the broader influence of radiation therapy on patient physiology is poorly understood. We conducted comprehensive global metabolomic profiling of urine, plasma, and stools sampled from patients undergoing PLNRT for high-risk prostate cancer.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2021

Assessing biogeographic survey gaps in bacterial diversity knowledge: A global synthesis of freshwaters

Freshwaters account for 0.8% of Earth's surface area, yet support >10% of known plant and animal species making them disproportionately biodiverse. Modern molecular techniques have begun to reveal microbial diversity, but application of these approaches to address global microbial biogeography is relatively unknown in freshwaters. Our aim was to identify gaps in microbial data coverage along climatic and landscape disturbance gradients and among terrestrial biomes and hydrographic regions for all freshwater ecosystems and three freshwater habitat types: lakes and reservoirs (lentic); streams and rivers (lotic); and wetlands. We reviewed literature on microbial diversity in freshwaters surveyed using 16S ribosomal RNA sequencing which identify microbial taxa. We georeferenced survey locations and used a geographic information system to identify and map gaps in survey coverage using open-source data for climate, landscape disturbance, terrestrial biomes, and freshwater ecoregions. In our study, we compiled 3,425 georeferenced survey locations reported from 963 studies. Streams were surveyed most frequently (60.8% of survey locations), followed by lakes (33.5%) and wetlands (5.6%). Surveys were concentrated in North America, central and western Europe, and Southeast Asia; 35% of freshwater ecoregions were surveyed at least once across freshwater habitat types, whereas 23%, 23%, and 12% were surveyed at least once for lentic, lotic, and wetland habitat types, respectively. The climatic gap analysis indicated coverage is high for temperate regions but lacking in the tropics and Arctic, particularly for wetland ecosystems. Our assessment revealed high climatic coverage of freshwater microbial diversity knowledge, but expansive ecoregional gaps attributable to biased sampling near research institutions in North America, western Europe, and China. Future surveys should target ecoregions in Africa, South America, Central Asia, Australia, and Antarctica. An essential next step will be to curate and disseminate sequencing efforts to facilitate the study of processes driving global diversity patterns.

16S rRNA↗

DOE OSTI2022

A Neural Network Approach to Predict Gibbs Free Energy of Ternary Solid Solutions

Here, we present a data-centric deep learning (DL) approach using neural networks (NNs) to predict the thermodynamics of ternary solid solutions. We explore how NNs can be trained with a dataset of Gibbs free energies computed from a CALPHAD database to predict ternary systems as a function of composition and temperature. We have chosen the energetics of the FCC solid solution phase in 226 binaries consisting of 23 elements at 11 different temperatures to demonstrate the feasibility. The number of binary data points included in the present study is 102,000. We select six ternaries to augment the binary dataset to investigate their influence on the NN prediction accuracy. We examine the sensitivity of data sampling on the prediction accuracy of NNs over selected ternary systems. It is anticipated that the current DL workflow can be further elevated by integrating advanced descriptors beyond the elemental composition and more curated training datasets to improve prediction accuracy and applicability.

42 ENGINEERING↗

DOE OSTI2024

Real-time confinement regime detection in fusion plasmas with convolutional neural networks and high-bandwidth edge fluctuation measurements

Abstract A real-time detection of the plasma confinement regime can enable new advanced plasma control capabilities for both the access to and sustainment of enhanced confinement regimes in fusion devices. For example, a real-time indication of the confinement regime can facilitate transition to the high-performing wide-pedestal (WP) quiescent H-mode, or avoid unwanted transitions to lower confinement regimes that may induce plasma termination. To demonstrate real-time confinement regime detection, we use the 2D beam emission spectroscopy (BES) diagnostic system to capture localized density fluctuations of long wavelength turbulent modes in the edge region at a 1 MHz sampling rate. BES data from 330 discharges in either L-mode, H-mode, quiescent H (QH)-mode, or WP QH-mode were collected from the DIII-D tokamak and curated to develop a high-quality database to train a deep-learning classification model for real-time confinement detection. We utilize the 6×8 spatial configuration with a time window of 1024 µ s and recast the input to obtain spectral-like features via fast Fourier transform preprocessing. We employ a shallow 3D convolutional neural network for the multivariate time-series classification task and utilize a softmax in the final dense layer to retrieve a probability distribution over the different confinement regimes. Our model classifies the global confinement state on 44 unseen test discharges with an average F 1 score of 0.94, using only ∼1 ms snippets of BES data at a time. This activity demonstrates the feasibility for real-time data analysis of fluctuation diagnostics in future devices such as ITER, where the need for reliable and advanced plasma control is urgent.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2014

Ames Life Science Data Archive: Translational Rodent Research at Ames

The Life Science Data Archive (LSDA) office at Ames is responsible for collecting, curating, distributing and maintaining information pertaining to animal and plant experiments conducted in low earth orbit aboard various space vehicles from 1965 to present. The LSDA will soon be archiving data and tissues samples collected on the next generation of commercial vehicles; e.g., SpaceX & Cygnus Commercial Cargo Craft. To date over 375 rodent flight experiments with translational application have been archived by the Ames LSDA office. This knowledge base of fundamental research can be used to understand mechanisms that affect higher organisms in microgravity and help define additional research whose results could lead the way to closing gaps identified by the Human Research Program (HRP). This poster will highlight Ames contribution to the existing knowledge base and how the LSDA can be a resource to help answer the questions surrounding human health in long duration space exploration. In addition, it will illustrate how this body of knowledge was utilized to further our understanding of how space flight affects the human system and the ability to develop countermeasures that negate the deleterious effects of space flight. The Ames Life Sciences Data Archive (ALSDA) includes current descriptions of over 700 experiments conducted aboard the Shuttle, International Space Station (ISS), NASA/MIR, Bion/Cosmos, Gemini, Biosatellites, Apollo, Skylab, Russian Foton, and ground bed rest studies. Research areas cover Behavior and Performance, Bone and Calcium Physiology, Cardiovascular Physiology, Cell and Molecular Biology, Chronobiology, Developmental Biology, Endocrinology, Environmental Monitoring, Gastrointestinal Physiology, Hematology, Immunology, Life Support System, Metabolism and Nutrition, Microbiology, Muscle Physiology, Neurophysiology, Pharmacology, Plant Biology, Pulmonary Physiology, Radiation Biology, Renal, Fluid and Electrolyte Physiology, and Toxicology. These experiment descriptions and data can be accessed online via the public LSDA website (http://lsda.jsc.nasa.gov) and information can be requested via the Data Request form at http://lsda.jsc.nasa.gov/common/dataRequest/dataRequest.aspx or by contacting the ALSDA Office at: Alison.J.French@nasa.gov

Life Sciences↗

DOE OSTI2024

Machine learning framework for predicting uranium enrichments from M400 CZT gamma spectra

A machine learning framework was developed for predicting uranium enrichments from M400 CZT gamma spectra. This framework leverages the availability of a large amount of measured M400 gamma spectra and uses a recently updated version of Gamma Detector Response and Analysis Software (GADRAS) for gamma spectrum analysis and generation. It also leverages the existing machine learning modules in Python for gamma spectrum data processing, curation, model training, benchmarking, and optimization of the deep machine learning models. The framework is used to develop a deep learning model to analyze gamma spectra from a set of U 3 O 8 samples with enrichments ranging from 0.31 to 93.17% and UF 6 cylinders with enrichments ranging from 0.2 to 4.95%, and the model performance is tested using a set of measured spectra and the respective declared enrichment values. Results show that the model can correctly classify 99.35% of the U 3 O 8 sample enrichments, and can predict the samples’ enrichments within an average absolute error of 0.099% (in percentage points of enrichment). For the UF 6 cylinders, the average absolute error was approximately 0.03%, with an accuracy of 98% in classifying discrete enrichment values of UF 6 samples. Finally, the results also show that the model has performed significantly better in terms of predicting enrichments in UF 6 cylinders based on measured gamma spectra than the GEM code, with a standard deviation (of the relative errors) of 2.23% (compared with the 11.51% value for the GEM code) based on results from a set of test data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS2018

Three Proposed Compendia for Genesis Solar Wind Samples: Science Results, Collector Materials Characterization and Cleaning Techniques

Final Paper and not the abstract is attached. Introduction: Planetary material and cosmochemistry research using Genesis solar wind samples (including the development and implementation of cleaning and analytical techniques) has matured sufficiently that compilations on several topics, if made publically accessible, would be beneficial for researchers and reviewers. We propose here three compendia based on content, organization and source of documents (e.g. published peer-reviewed, published, internal memos, archives). For planning purposes, suggestions are solicited from potential users of Genesis solar wind samples for the type of science content and/or organizational style that would be most useful to them. These compendia are proposed as living documents, periodically updated. Similar to the existing compendia described below, the curation compendia are like library or archival finding aids, they are guides to published or archival documents and should not be cited as primary sources.

Allton, J. H.↗

DOE OSTI2013

Galectin-1 Is an Independent Prognostic Factor for Local Recurrence and Survival After Definitive Radiation Therapy for Patients With Squamous Cell Carcinoma of the Uterine Cervix

Purpose: To investigate the role of galectin-1 in patients with cervical cancer after definitive radiation therapy. Methods and Materials: We reviewed 154 patients with International Federation of Gynecology and Obstetrics stage I-II squamous cell carcinoma. Patients underwent curative-intent radiation therapy. Paraffin-embedded tissues were analyzed using immunohistochemistry staining for galectin-1. The rates of cancer-specific survival (CSS), local recurrence (LR), and distant metastasis were compared among patient tissue samples with no, weak, and strong galectin-1 expression. The Kaplan-Meier method and the Cox proportional hazard model with hazard ratios and 95% confidence intervals (CIs) were used for univariate and multivariate analyses, respectively. Results: The areas under the curve for the intracellular expression scores of galectin-1 for both LR and CSS were significantly higher than those for stromal expression. There were no significant differences in the demographic data, such as stage and serum tumor markers, between patients with and without intracellular expression of galectin-1 in cancer tissue samples. Using multivariate analyses, the hazard ratios of LR and CSS were 2.60 (95% CI 1.50-4.52) (P=.001) and 1.94 (95% CI 1.18-3.19) (P=.010), respectively. Conclusion: Galectin-1 is an independent prognostic factor associated with LR and CSS in stage I-II cervical cancer patients undergoing definitive radiation therapy. Further studies targeting galectin-1 may improve the local control of cervical cancer.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2019

Synthesis, optical imaging, and absorption spectroscopy data for 179072 metal oxides

Abstract Optical absorption spectroscopy is an important materials characterization for applications such as solar energy generation. This data descriptor describes the to date (Dec 2018) largest publicly available curated materials science dataset for near infrared to near UV (UV-Vis) light absorbance, composition and processing properties of metal oxides. By supplying the complete synthesis and processing history of each of the 179072 samples from 99965 unique compositions we believe the dataset will enable the community to develop predictive models for materials, such as prediction of optical properties based on composition and processing, and ultimately serve as a benchmark dataset for continued integration of machine learning in materials science. The dataset is also a resource for identifying materials composition and synthesis to attain specific optical properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Materials Characterization, Prediction, and Control Project: Summary Report on Material Characterization, Part 1

The Pacific Northwest National Laboratory (PNNL) undertook the Materials Characterization, Prediction, and Control (MCPC) Laboratory Directed Research and Development Project to advance understanding of nuclear material processing and enable multifold acceleration in the development and qualification of new material systems in national security and advanced energy applications (Smith 2021). The MCPC Project executed research across three scientific vertices—material characterization, predictive modeling, and data analytics—with extensive support by a data curation and management team. The central technical objective in the MCPC Project was to improve the prediction and characterization of the process-structure-property relationships within the microstructurally refined region of stainless-steel samples prepared utilizing friction stir processing (FSP). Application of the FSP technique is well established at PNNL within the Solid Phase Processing capability through many years of investment across a range of materials and applications (PNNL 2024). Three distinct rounds of FSP experiments were performed by the experimental team, producing replicate samples utilizing across different nominal processing conditions (Condition IDs) listed in Table 1. The starting material on which FSP was applied was commercially available unprocessed stainless-steel type 316L material. Chosen processing conditions were very diverse, and some were intentionally chosen to produce defects. Several samples experienced tool breakage during experimentation, so a full set of three replicates was not produced for every nominal processing condition.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Materials Characterization, Prediction, and Control Project: Summary Report on Material Characterization, Part 2

The Pacific Northwest National Laboratory (PNNL) undertook the Materials Characterization, Prediction, and Control (MCPC) Laboratory Directed Research and Development Project to advance understanding of nuclear material processing and enable multifold acceleration in the development and qualification of new material systems in national security and advanced energy applications (Smith 2021). The MCPC Project executed research across three scientific vertices—material characterization, predictive modeling, and data analytics—with extensive support by a data curation and management team. The central technical objective in the MCPC Project was to improve the prediction and characterization of the process-structure-property relationships within the microstructurally refined region of stainless-steel samples prepared utilizing friction stir processing (FSP). Application of the FSP technique is well established at PNNL within the Solid Phase Processing capability through many years of investment across a range of materials and applications (PNNL 2024).

36 MATERIALS SCIENCE↗

DOE OSTI2024

Materials Characterization, Prediction, and Control Project: Summary Report on Material Characterization, Part 3

The Pacific Northwest National Laboratory (PNNL) undertook the Materials Characterization, Prediction, and Control (MCPC) Laboratory Directed Research and Development Project to advance understanding of nuclear material processing and enable multifold acceleration in the development and qualification of new material systems in national security and advanced energy applications (Smith 2021). The MCPC Project executed research across three scientific vertices—material characterization, predictive modeling, and data analytics—with extensive support by a data curation and management team. The central technical objective in the MCPC Project was to improve the prediction and characterization of the process-structure-property relationships within the microstructurally refined region of stainless-steel samples prepared utilizing friction stir processing (FSP). Application of the FSP technique is well established at PNNL within the Solid Phase Processing capability through many years of investment across a range of materials and applications (PNNL 2024).

36 MATERIALS SCIENCE↗

DOE OSTI2024

Materials Characterization, Prediction, and Control Project: Summary Report on Material Characterization, Part 4

The Pacific Northwest National Laboratory (PNNL) undertook the Materials Characterization, Prediction, and Control (MCPC) Laboratory Directed Research and Development Project to advance understanding of nuclear material processing and enable multifold acceleration in the development and qualification of new material systems in national security and advanced energy applications (Smith 2021). The MCPC Project executed research across three scientific vertices—material characterization, predictive modeling, and data analytics—with extensive support by a data curation and management team. The central technical objective in the MCPC Project was to improve the prediction and characterization of the process-structure-property relationships within the microstructurally refined region of stainless-steel samples prepared utilizing friction stir processing (FSP). Application of the FSP technique is well established at PNNL within the Solid Phase Processing capability through many years of investment across a range of materials and applications (PNNL 2024).

36 MATERIALS SCIENCE↗

NASA NTRS1992

Material selection and evaluation of new encapsulation compounds for electric cables for launch support system

Eight urethane compounds were evaluated as possible replacement for the existing encapsulating compoounds for electrical cables for the Launch Support System at Kennedy Space Center (KSC). The existing encapsulating compound, PR-1535, contains the curative MOCA 4-4'-Methylene-BIS (2-chloroaniline), which is a suspect carcinogen and hence may be the subject of further restrictions of its use by the Occupational Safety and Health Administration (OSHA). The samples made in the configuration of cable joints and in the form of disks were evaluated for flammability and hypergolic compatibility. These also underwent accelerated weatherability tests that measured the residual hardness of the exposed samples. Three candidates and the existing compound passed the hardness test. Of these, only one candidate and the existing compound passed the flammability test. The thermal and hydrolytic stability (weatherability) of these samples was studied using thermogravimetric analysis (DSC) techniques. The TMA and DSC data correlated with the residual hardness data; whereas, the TGA data showed no correlation. A hypergolic compatibility test will be conducted on the compound V-356-HE80, which passed both the flammability and accelerated weatherability tests.

Ray, Asit K.↗