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SOC Synthetic Microstructure Bank

QUICK START: Start with property_library.html (can be found by typing the filename into the query box) and use the interactive table to filter, sort, and select a microstructure with the desired properties. Search for the alphabetic code to obtain the corresponding dataset. Full description: This is a bank of 1,970 unique 3-phase electrode microstructure files. When you account for reassigning phase IDs (e.g. declare that 1=Ni and 2=pore, instead of 1=pore and 2=Ni), it actually represents 5,910 unique electrode microstructures, each of which could be considered to be either an air or a fuel electrode (e.g. declare that the phase IDs correspond to pore, Ni, and YSZ; or that they correspond to pore, LSCF, and GDC; or whatever electron-conductor and ion-conductor combination is being studied). The voxel size is 50 nm and each electrode file contains a 4x4 grid of (12.5 micron)^3 sub-volumes. If placed together in a grid, they comprise a 50x50x12.5 micron electrode (note that the interfaces between sub-volumes will be sharp; this can be mitigated via simulating annealing/relaxation). The sub-volumes can also be used individually for a reasonably sized 12.5 micron cubic region-of-interest. A user can simply consider the voxel size to be a different value to rescale the volumes (and all of their morphological features, including particle size) as desired. These microstructures were generated using DREAM3D. The general procedure is outlined in https://doi.org/10.1016/j.jpowsour.2018.03.025 The file names are an alphabetic code having to do with the input parameters used in DREAM3D when they were generated. Most users would be best served by starting with the file property_library.html or property_library_subvols.html (which lists properties for each individual subvolume). These files contain a catalogue of the actual, measured properties of every microstructure in the database. Any combination of property values can be filtered and sorted until a desired electrode is found, at which point the user can find the file corresponding to that alphabetic code. The properties in the catalogue include connected TPB density, and for each phase: phase fraction, average particle size, polydispersity of particle size, tortuosity, and connected pair-wise interfacial area. They also include what fraction of each property is connected through to the interfaces of the volume. If the desired combination of properties is not found at first, remember that the phase IDs can be re-assigned arbitrarily, e.g. swapping 1s and 2s. In fact, the database was generated with this in mind so as not to generate redundant microstructures. If the database does not contain the desired property combinations, try to search for the other possible permutations of those properties with re-assigned phase IDs. Please cite https://doi.org/10.1149/10301.0909ecst for use. Please contact the maintainer, William K. Epting, for additional information or assistance.

3D microstructure↗

INGENIOUS Thermal Conductivity Measurement Source Categorization

Thermal conductivity (TC) data taken for different wells at a specified drill depth. This is an abridged version of the complete SMU heat flow database, downloaded from the SMU node of the NGDS at the beginning of INGENIOUS (approximately April 2021), and filtered to the INGENIOUS study area. This National Geothermal Data System (NGDS) project aggregates geothermal data collected and curated by the SMU Geothermal Laboratory and its partner organizations. All columns in this database are the same as the SMU database, except for 2 additions associated with this project. Repeated columns are for data correlation purposes. Column descriptions and data types are the same as previous iterations of the SMU database. The new values that are the addition are two new columns developed as part of the INGENIOUS project: INGENIOUS TC Value | INGENIOUS notes INGENIOUS notes are individual notes that were written for specific data points during the analysis process. There are not always notes associated with each input value. INGENIOUS TC Value includes 4 values: 1. Assumed Measured These are values that are assumed to be measured thermal conductivity values, either within a specific well or within the same study region. Many of these have either a published reference, a reported standard deviation, or a unique thermal conductivity value. 2. Data release - assumed measured These are values in the SMU database that are from proprietary data that were added to the SMU database and are labeled as data release for their reference. These values were searched for in person at the SMU Geothermal Laboratory as well as virtual examination of data available on the NGDS. For many of these, there are reported thermal conductivity values associated with the heat flow data in the database, but no specific table or reference to measurements in the original data release files. 3. Known measured These are values that have a reported measurement, either as an original file in the SMU data files on the NGDS or a reported table in a publication. In the rare circumstances, Maria Richards or David Blackwell confirmed measurement. Confirmation of measurement would be written in the INGENIOUS notes column. 4. Unmeasured Unmeasured values are those that are known to be unmeasured, either estimated from another report or no information given. In the SMU database, there are wells that have a heat flow but no thermal conductivity. These are categorized as unmeasured. There are also heat flow values that are stated to have estimated or generalized average thermal conductivity values for the region and rock type. Because these are known to be unmeasured, they are categorized as such. 5. Blank Blank values are either A quality or X quality. These quality values are stated in the INGENIOUS notes. These values were not going to change associated with the heat flow analysis, so these were not examined.

15 GEOTHERMAL ENERGY↗

Kaona: Deep Searching and Curating Aviation Safety Reporting Systems

Context: Several works in the literature have examined how safety narrative databases can be leveraged to share lessons learned. However, less attention has been given in augmenting existing processes of safety reporting systems. Aim: In this work, we introduce Kaona: An interface that weaves machine learning in existing aviation safety reporting systems activities. Method: We provide a use case of search, curation and newsletter writing to showcase how Kaona features build on existing processes and on its own to enhance information retrieval, curation and synthesis of narratives. Results: We created two instances of Kaona internally for evaluation, one using all public NASA's ASRS narratives and another using all public C3RS narratives. Data ranged from 1998 to 2024. Conclusion: Our tool provides a new way to explore safety narratives, serving to re-imagine how text databases can benefit of novel information retrieval mechanisms in the era of large language models.

asrs↗

Populating a Graph Database to Run a Usage-Based Discovery Tool

Most dataset discovery tools for Earth Observation data rely on descriptions and other metadata of the datasets, using keyword searches or attribute filtering to determine relevance. However, these descriptions often do not include the potential uses of the data. Thus, a user working on floods will rarely see few if any rainfall datasets show up in such a search. The Usage Based Discovery tool, on the other hand, offers usage instances to the user, either research articles or applications, along with the datasets that those usage instances used. This allows a user, particularly one new to the world of Earth Observation data, to investigate which datasets are used in similar cases. The information that powers Usage-Based Discovery is a graph database of relationships of usage to dataset and usage to topic, allowing the user to narrow their search for similar cases. In order to scale out to a graph database rich enough to provide a satisfactory user experience, we combine manual and automated processes to populate the graph. The initial content of the graph has been seeded primarily via human-aided data curation methods, using sites like Google Scholar. To scale up this effort, we’ve employed crowdsourcing. It is easy for anyone to contribute to our graph using their Open Researcher and Contributor Identifier for authorization. We’re now experimenting with Machine Learning and Natural Language Processing to help automate population of the graph, starting with the classification of research articles by topic. Finding adequate training data in the absence of a comprehensive and open research article API continues to be a significant challenge.

Vincent Inverso↗

Methods and means used in programming intelligent searches of technical documents

In order to meet the data research requirements of the Safety, Reliability & Quality Assurance activities at Kennedy Space Center (KSC), a new computer search method for technical data documents was developed. By their very nature, technical documents are partially encrypted because of the author's use of acronyms, abbreviations, and shortcut notations. This problem of computerized searching is compounded at KSC by the volume of documentation that is produced during normal Space Shuttle operations. The Centralized Document Database (CDD) is designed to solve this problem. It provides a common interface to an unlimited number of files of various sizes, with the capability to perform any diversified types and levels of data searches. The heart of the CDD is the nature and capability of its search algorithms. The most complex form of search that the program uses is with the use of a domain-specific database of acronyms, abbreviations, synonyms, and word frequency tables. This database, along with basic sentence parsing, is used to convert a request for information into a relational network. This network is used as a filter on the original document file to determine the most likely locations for the data requested. This type of search will locate information that traditional techniques, (i.e., Boolean structured key-word searching), would not find.

Gross, David L.↗

Adaptive learning-driven high-throughput synthesis of oxygen reduction reaction Fe–N–C electrocatalysts

Reducing human reliance on inefficient energy systems and fossil fuels has become more urgent due to the consequences of global climate change. However, traditional trial-and-error approaches have hampered our ability to accelerate the discovery and implementation of functional materials for efficient energy conversion devices, such as polymer electrolyte fuel cells (PEFCs). To address this, we develop an adaptive learning framework that integrates machine learning and state-of-the-art capabilities in high-throughput synthesis to achieve expedited optimization of iron-nitrogen-carbon PEFC oxygen reduction reaction (ORR) electrocatalysts. We use statistical inference, uncertainty quantification, and global optimization to build a computational design-of-experiment tool that identifies the optimum compositions to be investigated next to reduce the demands placed on experimental materials discovery. We benchmark the ability of the proposed strategy to discover optimum catalyst synthesis conditions in a six-dimensional search space when starting with a thirty-six-sample database. By following the adaptive learning strategy, we synthesize fourteen new catalysts from approximately ten billion unique compositions and discover four catalysts that outperform all original samples. The best machine learning-optimized catalyst is 33% more active than the highest-performing one in the initial database, showing an ORR activity seven times larger than those typically reported for the same class of materials.

36 MATERIALS SCIENCE↗

ATCCfinder - Download and Search the ATCC Genome Portal

Much strain-specific sequence data exists in research conducted before the deployment of large sequencing repositories, making it challenging to identify and validate the identity of strains used in these studies through bioinformatics and phenotyping. The American Type Culture Collection (ATCC) is an organization that sells a wide variety of microbes with strain-level taxonomy classification and associated sequenced reference genomes. Currently, ATCC does not provide a method for searching for sequence similarity between a query sequence and their database of reference genomes. Here I propose the software ATCCfinder, which utilizes ATCC application interface software (API) to generate query-able databases from ATCC Genome resources.

Koehler, Samuel↗

Astronomical data analysis software and systems I; Proceedings of the 1st Annual Conference, Tucson, AZ, Nov. 6-8, 1991

Consideration is given to a definition of a distribution format for X-ray data, the Einstein on-line system, the NASA/IPAC extragalactic database, COBE astronomical databases, Cosmic Background Explorer astronomical databases, the ADAM software environment, the Groningen Image Processing System, search for a common data model for astronomical data analysis systems, deconvolution for real and synthetic apertures, pitfalls in image reconstruction, a direct method for spectral and image restoration, and a discription of a Poisson imagery super resolution algorithm. Also discussed are multivariate statistics on HI and IRAS images, a faint object classification using neural networks, a matched filter for improving SNR of radio maps, automated aperture photometry of CCD images, interactive graphics interpreter, the ROSAT extreme ultra-violet sky survey, a quantitative study of optimal extraction, an automated analysis of spectra, applications of synthetic photometry, an algorithm for extra-solar planet system detection and data reduction facilities for the William Herschel telescope.

Worrall, Diana M.↗

X-ray emission from chemically peculiar stars

We have searched the Roentgen Satellite (ROSAT) All-Sky Survey (RASS) database at the positions of about 100 magnetic Bp-Ap stars of the helium-strong, helium-weak, silicon, and strontium-chromium subclasses. We detect X-ray sources at the positions of 10 of these stars; in four cases the X-ray emission presumably arises from an early-type companion with a radiatively driven wind, while we believe that the magnetic chemically peculiar (CP) star is the most likely X-ray source (as opposed to a binary companion) in at least three and at most five of the six remaining cases. The helium-strong stars have X-ray emission levels that are characteristic of the luminous OB stars with massive winds (log L(sub x)/L(sub bol) is about -7), whereas the He-weak and Si stars (which generally show no evidence for significant mass loss) have log L(sub x)/L(sub bol) values that can reach as high as about -6. In contrast, we find no convincing evidence that the cooler SrCrEu-type CP stars are intrinsic X-ray sources. We discuss the X-ray and radio emission properties of our sample of CP stars, and argue that both types of emission may be magnetospheric in origin; however, there is clearly not a simple one-to-one correspondence between them, since many of the magnetic stars that are detected radio sources were not detected as X-ray sources in the present survey.

Drake, S. A.↗

"Built-In" Action/Issues Tracking and Post-Ops Analysis Tool for Realtime Console Operations

Marshall Space Flight Center's (MSFC) Payload Operations Integration Center (POIC) for the International Space Station (ISS) uses a number of formal databases to manage and track flight plan changes, onboard and ground equipment anomalies, and other events. However, individual console positions encounter many action items and/or occurrences that don't fit neatly into the databases, and while console logs are comprehensive, manual or automated searches do not always yield consistent results. The Payload Communications Manager (PAYCOM) team, whose members speak directly with the ISS onboard crew with respect to NASA payload operations, has found a creative way to reformat a mandatory Daily Report to organize action items, standing reminders, significant events, and other comments. While the report keeps others appraised of PAYCOMs activities and issues of the moment, the format makes it easy to capture very brief summaries of the items in a "Roll Off Matrix", including start and stop dates, resolution, and possible applicability to future ops. The matrix provides accountability for all action items, gives direct insight into the issues surrounding various payloads and methods of dealing with them, yields indirect information on PAYCOM priorities and processes, and provides a roadmap that makes it easier to get back to extensive details if needed. This paper describes how the ISS PAYCOM Daily Report and Roll Off Matrix are organized, used, and inter-related to each other and the PAYCOM operations log. While the application is for a manned vehicle, the concepts could apply in a wide spectrum of operational settings.

Scott, David W.↗

An optimized FM-index library for nucleotide and amino acid search

Abstract Background Pattern matching is a key step in a variety of biological sequence analysis pipelines. The FM-index is a compressed data structure for pattern matching, with search run time that is independent of the length of the database text. Implementation of the FM-index is reasonably complicated, so that increased adoption will be aided by the availability of a fast and flexible FM-index library. Results We present AvxWindowedFMindex (AWFM-index), a lightweight, open-source, thread-parallel FM-index library written in C that is optimized for indexing nucleotide and amino acid sequences. AWFM-index introduces a new approach to storing FM-index data in a strided bit-vector format that enables extremely efficient computation of the FM-index occurrence function via AVX2 bitwise instructions, and combines this with optional on-disk storage of the index’s suffix array and a cache-efficient lookup table for partial k-mer searches. The AWFM-index performs exact match count and locate queries faster than SeqAn3’s FM-index implementation across a range of comparable memory footprints. When optimized for speed, AWFM-index is $$\sim $$ ∼ 2–4x faster than SeqAn3 for nucleotide search, and $$\sim $$ ∼ 2–6x faster for amino acid search; it is also $$\sim $$ ∼ 4x faster with similar memory footprint when storing the suffix array in on-disk SSD storage. Conclusions AWFM-index is easy to incorporate into bioinformatics software, offers run-time performance parameterization, and provides clients with FM-index functionality at both a high-level (count or locate all instances of a query string) and low-level (step-wise control of the FM-index backward-search process). The open-source library is available for download at https://github.com/TravisWheelerLab/AvxWindowFmIndex.

59 BASIC BIOLOGICAL SCIENCES↗

TropiRoot 1.0: Database of tropical root characteristics across environments

Tropical ecosystems contain the world's largest biodiversity of vascular plants. Yet, our understanding of tropical functional diversity and its contribution to global diversity patterns is constrained by data availability. This discrepancy underscores an urgent need to bridge data gaps by incorporating comprehensive tropical root data into global datasets. Here, we provide a database of tropical root characteristics. This new database, TropiRoot 1.0, will be instrumental in evaluating an array of hypotheses pertaining to root functional ecology and plant biogeography, both within the tropics and relative to other global biomes. The data compilation was conducted by the TropiRoot Initiative, in partnership with the Fine-Root Ecology Database (FRED) and the Global Root Trait (GRooT) database, Colorado State University (CSU) and the Smithsonian Tropical Research Institute (STRI). Literature search and data extraction were conducted between 2020 and 2024. Literature was identified using Web of Science, Scopus, and complemented using the expert knowledge of members of TropiRoot. To provide broad environmental and geographical distributions, literature searches included root characteristics (traits) across global change drivers, natural gradients, and from different continents. We adopted FRED standardized data columns and streamlined the format to enhance accessibility for data extraction across various user groups. This optimized framework resulted in a smaller, yet comprehensive datasheet. To make the database compatible with other global root trait initiatives, column identification was standardized following the codes provided by FRED. These efforts culminated in data extracted from 104 new sources, resulting in more than 8000 rows of data (either species or community data). Most of the data in TropiRoot 1.0 include root characteristics such as root biomass, morphology, root dynamics, mass fraction, architecture, anatomy, physiology, and root chemistry. This initiative represents a 30% increase in the currently available data for tropical roots in FRED. TropiRoot 1.0 contains root characteristics from 25 different countries, where seven are located in Asia, six in South America, five in Central America and the Caribbean, four in Africa, two in North America, and 1 in Oceania. Due to the volume of data, when ancillary data were available, including soil data, these data were either extracted and included in the database or its availability was recorded in an additional column. Multiple contributors checked the entries for outliers during the collation process to ensure data quality. For text-based observations, we examined all cells to ensure that their content relates to their specific categories. For numerical observations, we ordered each numerical value from least to greatest and plotted the values, checking apparent outliers against the data in their respective sources and correcting or removing incorrect or impossible values. Some data (soil and aboveground) have different columns for the same variable presented in different units, including originally published units, but root characteristics data had units converted to match those reported in FRED. By filling a gap from global databases, TropiRoot 1.0 expands our knowledge of otherwise so far underrepresented regions and our ability to assess global trends. This advancement can be used to improve tropical forest representation in vegetation models. The data are freely available and should be cited when used.

FRED↗

High Voltage EEE Parts for EMA/EHA Applications on Manned Launch Vehicles

The objective of this paper is an assessment of high voltage electronic components required for high horsepower electric thrust vector control (TVC) systems for human spaceflight launch critical application. The scope consists of creating of a database of available Grade 1 electrical, electronic and electromechanical (EEE) parts suited to this application, a qualification path for potential non-Grade 1 EEE parts that could be used in these designs, and pathfinder testing to validate aspects of the proposed qualification plan. Advances in the state of the art in high power electric power systems enable high horsepower electric actuators, such as the electromechnical actuator (EMA) and the electro-hydrostatic actuator (EHA), to be used in launch vehicle TVC systems, dramaticly reducing weight, complexity and operating costs. Designs typically use high voltage insulated gate bipolar transistors (HV-IGBT). However, no Grade 1 HV-IGBT exists and it is unlikely that market factors alone will produce such high quality parts. Furthermore, the perception of risk, the lack of qualification methodoloy, the absence of manned space flight heritage and other barriers impede the adoption of commercial grade parts onto the critical path. The method of approach is to identify high voltage electronic component types and key parameters for parts currently used in high horsepower EMA/EHA applications, to search for higher quality substitutes and custom manufacturers, to create a database for these parts, and then to explore ways to qualify these parts for use in human spaceflight launch critical application, including grossly derating and possibly treating hybrid parts as modules. This effort is ongoing, but results thus far include identification of over 60 HV-IGBT from four manufacturers, including some with a high reliability process flow. Voltage ranges for HV-IGBT have been identified, as has screening tests used to characterize HV-IGBT. BSI BS ISO 21350 Space systems Off-the-shelf item utilization, developed from Marshall Work Instruction MWI8060.1 OFF-THE-SHELF HARDWARE UTILIZATION IN FLIGHT HARDWARE DEVELOPMENTwas found to provide guidance for including commercial off-the-shelf (COTS) hardware for use in critical applications.

Griffin, Trent↗

Novel Gloeobacterales spp. from Diverse Environments across the Globe

Photosynthetic Cyanobacteria and their descendants are the only known organisms capable of oxygenic photosynthesis. Their metabolism permanently changed the Earth’s surface and the evolutionary trajectory of life, but little is known about their evolutionary history. Genomes of the Gloeobacterales, an order of deeply divergent photosynthetic Cyanobacteria, may hold clues about the evolutionary process. However, there are only three published genomes within this order, and it is difficult to make broad inferences based on such little data. Here, I describe five species within the Gloeobacterales retrieved from publicly available databases and examine their photosynthetic gene content and the environments in which Gloeobacterales genomes and 16S rRNA gene sequences are found. The Gloeobacterales contain reduced photosystems and inhabit cold, wet-rock, and low-light environments. They are likely present in low abundances due to their low growth rate. Future searches for Gloeobacterales should target these environments, and samples should be deeply sequenced to capture the low-abundance taxa. Publicly available databases contain undescribed taxa within the Gloeobacterales. However, searching through all available data with current methods is computationally expensive. Therefore, new methods must be developed to search for these and other evolutionarily important taxa. Once identified, these novel photosynthetic Cyanobacteria will help illuminate the origin and evolution of oxygenic photosynthesis. Early branching photosynthetic Cyanobacteria such as the Gloeobacterales may provide clues into the evolutionary history of oxygenic photosynthesis, but there are few genomes or cultured taxa from this order. Five new metagenome-assembled genomes suggest that members of the Gloeobacterales all contain reduced photosystems and lack genes associated with thylakoids and circadian rhythms. Their distribution suggests that they may thrive in environments that are marginal for other species, including wet-rock and cold environments. These traits may aid in the discovery and cultivation of novel species in this clade.

59 BASIC BIOLOGICAL SCIENCES↗

[No Title]

The Two Micron All-Sky Survey will result in a database of millions of newly-discovered near-infrared bright sources of all types, from stars to nebulae to distant galaxies. The full potential of thesurvey will be greatly expanded by providing optical (blue and/or visual) identifications to thesesources from existing databases of optical objects from digitized Schmidt plate archives. I willdescribe the procedures developed at IPAC to identify infrared sources in the IRAS Faint SourceSurvey using such optical archives, and how these will be applied to the 2MASS survey. I willsummarize some of the expected results and in particular will discuss a search for distant near-infrared luminous Active Galactic Nuclei in the 2MASS database.

2MASS Survey↗

Automated Indexing of Structured Scientific Metadata Using Apache Solr

Scientific datasets are continuously growing with the amount of raw data being collected worldwide. This amount of data poses the biggest challenge to web search engines on how to retrieve them efficiently. This paper discusses how major scientific data centers are using popular open-source search platforms such as Solr [1] to retrieve structured data stored in data sources such as relational database management systems using its import handler mechanisms [2]. Additionally, we will also focus on how we can configure Solr to serve advanced full-text, faceted search capabilities, along with its key features, which simplify representing and delivering better performance to the scientific search interfaces.

Guntupally, Kavya↗

The IMG/M data management and analysis system v.7: content updates and new features

The Integrated Microbial Genomes & Microbiomes system at the Department of Energy (DOE) Joint Genome Institute (JGI) continues to provide support for users to perform comparative analysis of isolate and single cell genomes, metagenomes, and metatranscriptomes. In addition to datasets produced by the JGI, IMG v.7 also includes datasets imported from public sources such as NCBI Genbank, SRA, and the DOE National Microbiome Data Collaborative (NMDC), or submitted by external users. In the past couple years, we have continued our effort to help the user community by improving the annotation pipeline, upgrading the contents with new reference database versions, and adding new analysis functionalities such as advanced scaffold search, Average Nucleotide Identity (ANI) for high-quality metagenome bins, new cassette search, improved gene neighborhood display, and improvements to metatranscriptome data display and analysis. Here, we also extended the collaboration and integration efforts with other DOE-funded projects such as NMDC and DOE Biology Knowledgebase (KBase).

59 BASIC BIOLOGICAL SCIENCES↗

Knowledge, attitudes, and practices associated with bioterrorism preparedness in healthcare workers: a systematic review

Introduction Bioterrorism is an important issue in the field of biosecurity, and effectively dealing with bioterrorism has become an urgent task worldwide. Healthcare workers are considered bioterrorism first responders, who shoulder essential responsibilities and must be equipped to deal with bioterrorism. This study aims to extract and summarize the main research components of the bioterrorism knowledge, attitude, and practice dimensions among healthcare workers. Method This study utilized a systematic review research design based on the PRISMA 2020 guidelines. A literature search was conducted in the PubMed, Web of Science, and Scopus databases for peer-reviewed literature, and the Mixed Methods Appraisal Tool (MMAT) version 2018 was used to assess the quality of the literature. Result A total of 16 studies were included in the final selection. Through the analysis and summary of the included studies, three main aspects and 14 subaspects of the knowledge dimension, three main aspects and 10 subaspects of the attitude dimension, and two main aspects and six subaspects of the practice dimension were extracted. Conclusion This study conducted a literature review on bioterrorism knowledge, attitudes, and practices for healthcare workers based on the PRISMA 2020 guidelines. The findings can guide improvements in health literacy and provide beneficial information to professional organizations that need to respond effectively to bioterrorism.

Li, Tiantian↗