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At least 577 records · Page 32

OBO Foundry in 2021: operationalizing open data principles to evaluate ontologies

Biological ontologies are used to organize, curate and interpret the vast quantities of data arising from biological experiments. While this works well when using a single ontology, integrating multiple ontologies can be problematic, as they are developed independently, which can lead to incompatibilities. The Open Biological and Biomedical Ontologies (OBO) Foundry was created to address this by facilitating the development, harmonization, application and sharing of ontologies, guided by a set of overarching principles. One challenge in reaching these goals was that the OBO principles were not originally encoded in a precise fashion, and interpretation was subjective. Here, we show how we have addressed this by formally encoding the OBO principles as operational rules and implementing a suite of automated validation checks and a dashboard for objectively evaluating each ontology’s compliance with each principle. This entailed a substantial effort to curate metadata across all ontologies and to coordinate with individual stakeholders. We have applied these checks across the full OBO suite of ontologies, revealing areas where individual ontologies require changes to conform to our principles. Our work demonstrates how a sizable, federated community can be organized and evaluated on objective criteria that help improve overall quality and interoperability, which is vital for the sustenance of the OBO project and towards the overall goals of making data Findable, Accessible, Interoperable, and Reusable (FAIR).

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

From Rules to Reasoning: A Survey of Large Language Model-Based Approaches to Scientific Hypothesis and Idea Generation

Scientific hypothesis generation represents a fundamental challenge in contemporary research due to exponentially expanding literature volumes and increasing disciplinary specialization. Large language models (LLMs) have emerged as transformative tools for automated scientific discovery, moving beyond traditional rule-based and literature-mining approaches. Four paradigmatic approaches define current LLM-driven hypothesis generation: direct prompting and fine-tuning methods, knowledge-enhanced frameworks integrating retrieval-augmented generation (RAG), multi-agent collaborative systems simulating research teams, and reasoning-focused approaches implementing cognitive architectures. Domain-specific applications demonstrate statistical equivalence to human expert performance in social psychology, experimental validation in biomedical research, and near-expert quality in astronomy. Evaluation methodologies encompass human expert assessment, LLM-as-judge frameworks, and comprehensive benchmarking systems. Technical challenges include hallucination management, knowledge integration limitations, and balancing novelty with feasibility. Future directions emphasize hybrid neural-symbolic architectures and sophisticated human-AI collaboration models for responsible scientific discovery acceleration.

AI-driven discovery↗

Diagnostic imaging applications; Proceedings of the Meeting, Amsterdam, Netherlands, October 8, 9, 1984

It is more important than ever that engineers have an understanding of the future needs of clinical and research medicine, and that physicians know somthing about probable future developments in instrumentation capabilities. Only by maintaining such a dialog can the most effective application of technological advances to medicine be achieved. This workshop attempted to provide this kind of information transfer in the limited field of diagnostic imaging. Biomedical research at the Jet Propulsion Laboratory is discussed, taking into account imaging results from space exploration missions, as well as biomedical research tasks based in these technologies. Attention is also given to current and future indications for magnetic resonance in medicine, high speed quantitative digital microscopy, computer processing of radiographic images, computed tomography and its modern applications, position emission tomography, and developments related to medical ultrasound.

Beckenbach, E. S.↗

Terabit Wireless Communication Challenges

This presentation briefly discusses a research effort on Terabit Wireless communication systems for possible space applications. Recently, terahertz (THz) technology (300-3000 GHz frequency) has attracted a great deal of interest from academia and industry. This is due to a number of interesting features of THz waves, including the nearly unlimited bandwidths available, and the non-ionizing radiation nature which does not damage human tissues and DNA with minimum health threat. Also, as millimeter-wave communication systems mature, the focus of research is, naturally, moving to the THz range. Many scientists regard THz as the last great frontier of the electromagnetic spectrum, but finding new applications outside the traditional niches of radio astronomy, Earth and planetary remote sensing, and molecular spectroscopy particularly in biomedical imaging and wireless communications has been relatively slow. Radiologists find this area of study so attractive because t-rays are non-ionizing, which suggests no harm is done to tissue or DNA. They also offer the possibility of performing spectroscopic measurements over a very wide frequency range, and can even capture signatures from liquids and solids. According to Shannon theory, the broad bandwidth of the THz frequency bands can be used for terabit-per-second (Tb/s) wireless communication systems. This enables several new applications, such as cell phones with 360 degrees autostereoscopic displays, optic-fiber replacement, and wireless Tb/s file transferring. Although THz technology could satisfy the demand for an extremely high data rate, a number of technical challenges need to be overcome before its development. This presentation provides an overview the state-of-the- art in THz wireless communication and the technical challenges for an emerging application in Terabit wireless systems. The main issue for THz wave propagation is the high atmospheric attenuation, which is dominated by water vapor absorption in the THz frequency band. The technical challenges in design such a system and the techniques to overcome the challenges will be discussed in this presentation.

Hwu, Shian U.↗

Artificial intelligence in cancer research, diagnosis and therapy

Artificial intelligence and machine learning techniques are breaking into biomedical research and health care, which importantly includes cancer research and oncology, where the potential applications are vast. These include detection and diagnosis of cancer, subtype classification, optimization of cancer treatment and identification of new therapeutic targets in drug discovery. While big data used to train machine learning models may already exist, leveraging this opportunity to realize the full promise of artificial intelligence in both the cancer research space and the clinical space will first require significant obstacles to be surmounted. In this Viewpoint article, we asked four experts for their opinions on how we can begin to implement artificial intelligence while ensuring standards are maintained so as transform cancer diagnosis and the prognosis and treatment of patients with cancer and to drive biological discovery.

60 APPLIED LIFE SCIENCES↗

Mechanically Robust High Magnetic Performance Sm-Co Sintered Magnets (Final Report)

Samarium-cobalt based permanent magnets (SmCo 5 and Sm 2 Co 17 ) have excellent magnetic properties, good corrosion resistance, and long-term thermal stability. Sm-Co sintered magnets have been widely used in electric machines, telecommunication, biomedical devices, and magnetic sensors. They are the most preferred magnets for high-temperature applications (200 - 550 °C). However, Sm-Co sintered magnets are brittle. They cannot be used for applications subjected to high stress, vibration, or mechanical shock. Sm-Co sintered magnets are prone to chipping, and fracture in the course of block magnet manufacturing, part machining, assembly, and operation. The brittleness leads to a magnet production loss of up to 20-30% in volume and imposes limitations on part size and shape. Developing mechanically robust high-performance Sm-Co sintered magnets is of great scientific and technical significance. This project is in response to the current market need for mechanically robust high magnetic performance Sm-Co sintered magnets and their novel manufacturing processes. The project will focus on scaling-up, validation, and technology maturation study of the mechanically tough high magnetic performance Sm-Co magnets developed by Ames Laboratory at a lab-scale with the collaboration of the industry partner Electron Energy Corporation (EEC).

36 MATERIALS SCIENCE↗

Mass spectrometry

A review of mass spectrometry in organic chemistry is given, dealing with advances in instrumentation and computer techniques, selected topics in gas-phase ion chemistry, and applications in such fields as biomedicine, natural-product studies, and environmental pollution analysis. Innovative techniques and instrumentation are discussed, along with chromatographic-mass spectrometric on-line computer techniques, mass spectral interpretation and management techniques, and such topics in gas-phase ion chemistry as electron-impact ionization and decomposition, photoionization, field ionization and desorption, high-pressure mass spectrometry, ion cyclotron resonance, and isomerization reactions of organic ions. Applications of mass spectrometry are examined with respect to bio-oligomers and their constituents, biomedically important substances, microbiology, environmental organic analysis, and organic geochemistry.

Burlingame, A. L.↗

Space medicine research publications: 1987-1988

A list of publications of investigators supported by the Biomedical Research and Clinical Programs of the Life Sciences Division, Office of Space Science and Applications is given. Included are publications entered into the Life Sciences Bibliographic Database by the George Washington University as of 31 December 1988. Principal Investigators whose research tasks resulted in publication are identified by asterisk. Publications are organized into the following subject areas: space physiology and countermeasures (cardiopulmonary, musculoskeletal, neuroscience, and regulatory physiology), space human factors, environmental health, radiation health, clinical medicine, and general space medicine.

Source record↗

New Modular Camera No Ordinary Joe

Although dubbed 'Little Joe' for its small-format characteristics, a new wavefront sensor camera has proved that it is far from coming up short when paired with high-speed, low-noise applications. SciMeasure Analytical Systems, Inc., a provider of cameras and imaging accessories for use in biomedical research and industrial inspection and quality control, is the eye behind Little Joe's shutter, manufacturing and selling the modular, multi-purpose camera worldwide to advance fields such as astronomy, neurobiology, and cardiology.

Source record↗

Recent Advances in the Application of Functionalized Lignin in Value-Added Polymeric Materials

The quest for converting lignin into high-value products has been continuously pursued in the past few decades. In its native form, lignin is a group of heterogeneous polymers comprised of phenylpropanoids. The major commercial lignin streams, including Kraft lignin, lignosulfonates, soda lignin and organosolv lignin, are produced from industrial processes including the paper and pulping industry and emerging lignocellulosic biorefineries. Although lignin has been viewed as a low-cost and renewable feedstock to replace petroleum-based materials, its utilization in polymeric materials has been suppressed due to the low reactivity and inherent physicochemical properties of lignin. Hence, various lignin modification strategies have been developed to overcome these problems. Herein, we review recent progress made in the utilization of functionalized lignins in commodity polymers including thermoset resins, blends/composites, grafted functionalized copolymers and carbon fiber precursors. In the synthesis of thermoset resins such as polyurethane, phenol-formaldehyde and epoxy, they are covalently incorporated into the polymer matrix, and the discussion is focused on chemical modifications improving the reactivity of technical lignins. In blends/composites, functionalization of technical lignins is based upon tuning the intermolecular forces between polymer components. In addition, grafted functional polymers have expanded the utilization of lignin-based copolymers to biomedical materials and value-added additives. Different modification approaches have also been applied to facilitate the application of lignin as carbon fiber precursors, heavy metal adsorbents and nanoparticles. These emerging fields will create new opportunities in cost-effectively integrating the lignin valorization into lignocellulosic biorefineries.

36 MATERIALS SCIENCE↗

Colossal Terahertz Emission with Ultrafast Tunability Based on Van der Waals Ferroelectric NbOI 2

Abstract Terahertz (THz) technology is critical for quantum material physics, biomedical imaging, ultrafast electronics, and next‐generation wireless communications. However, standing in the way of widespread applications is the scarcity of efficient ultrafast THz sources with on‐demand fast modulation and easy on‐chip integration capability. Here the discovery of colossal THz emission is reported from a van der Waals (vdW) ferroelectric semiconductor NbOI 2 . Using THz emission spectroscopy, a THz generation efficiency an order of magnitude higher than that of ZnTe, a standard nonlinear crystal for ultrafast THz generation is observed. The underlying generation mechanisms associated are further uncovered with its large ferroelectric polarization by studying the THz emission dependence on excitation wavelength, incident polarization, and fluence. Moreover, the ultrafast coherent amplification and annihilation of the THz emission and associated coherent phonon oscillations by employing a double‐pump scheme are demonstrated. These findings combined with first‐principles calculations, inform a new understanding of the THz light–matter interaction in emergent vdW ferroelectrics and pave the way to develop high‐performance THz devices on them for quantum materials sensing and ultrafast electronics.

Subedi, Sujan [Department of Materials Science and↗

Structure-guided utilization of lignocellulose for catalysis, energy, and biomaterials

As a complex composite of cellulose, hemicellulose, and lignin, plant lignocellulose has long served as a major resource for biomass conversion, materials engineering, and bio-based product development. High-resolution structural insights enabled by solid-state nuclear magnetic resonance (ssNMR) now allow the mapping of polymer interfaces, identification of functional group accessibility, and tracking of molecular organization during processing, all of which are critical factors for optimizing catalytic strategies. These insights could drive transformative progress in lignocellulose-based applications, including selective depolymerization, improved pretreatment design, and efficient upcycling of lignin into resins, plastics, and biomedical materials. In industry-relevant contexts, such as biofuel generation and renewable material manufacturing, understanding the hydration dynamics, cross-linking patterns, and structural heterogeneity is also essential. The ability to visualize these features in native biomass presents a unique opportunity to develop new strategies for sustainability and performance. As the structural toolbox continues to expand, it is becoming a central enabler for innovations in renewable energy, green chemistry, and advanced bioproducts.

bioproduct↗

Manufacturing Dissolvable Alloy Components using ShAPE: A Study on Solid Phase Processing of Mg-W Composites and WJ11 Alloys

Dissolvable alloys and composites are an emerging class of materials that demonstrate tailored sorptivity in corrosive environments. This work explored the viability of solid phase processing (SPP) techniques, namely the shear assisted processing and extrusion (ShAPETM) method, to manufacture dissolvable magnesium composites and alloys components such as rods and tubes. The study also determined the effects of material composition and manufacturing process conditions on material microstructures developed during SPP and the resulting performance of the components. Explicit properties of interest included ultimate tensile strength, ultimate compressive strength, and yield strength. The application fields of interest for dissolvable alloys were identified as oil-and-gas operations and biomedical implants. Accordingly, PNNL collaborated with industrial and academia partners, Fortek Industries, Houston and University of Pittsburgh, during the course of this project for material and ShAPE process development. PNNL determined the viability of the using ShAPE to process the custom-designed materials provided by the project partners. This was done by identifying process parameters such as tool rotation rate, tool plunge rate, and process cooling optimal for manufacturing components with consolidated microstructures. Subsequently, PNNL also performed microstructural characterization on unprocessed and processed samples and mechanical property testing. One of the major findings from this work is that ShAPE was able to manufacture dissolvable magnesium composite and alloy rods and tubes with consolidated homogeneous microstructures and minimal macroscale defects on component surfaces. It was observed that samples processed via ShAPE demonstrated an average grain size < 2 - 5 µm, which was markedly lower than that of the precursors with 8 – 13 µm grains. Results showed that the ShAPE synthesized dissolvable magnesium composite and alloy strength was on par with or better than those components that were manufactured using traditional manufacturing processes such as forging and extrusion. It is noteworthy that the ShAPE samples were made with considerably lower number of process steps.

36 MATERIALS SCIENCE↗

Carbon Nanotube Composites: Strongest Engineering Material Ever?

The primary goal of the carbon nanotube project at Johnson Space Center (JSC) is to fabricate structural materials with a much higher strength-to-weight ratio than any engineered material today, Single-wall nanotubes present extraordinary mechanical properties along with new challenges for materials processing. Our project includes nanotube production, characterization, purification, and incorporation into applications studies. Now is the time to move from studying individual nanotubes to applications work. Current research at JSC focuses on structural polymeric materials to attempt to lower the weight of spacecraft necessary for interplanetary missions. These nanoscale fibers present unique new challenges to composites engineers. Preliminary studies show good nanotube dispersion and wetting by the epoxy materials. Results of tensile strength tests will also be reported. Other applications of nanotubes are also of interest for energy storage, gas storage, nanoelectronics, field emission, and biomedical uses.

Mayeaux, Brian↗

Autogenic Feedback Training Applications for Man in Space

Finding an effective treatment for the motion sickness-like symptoms that occur in space has become a high priority for NASA. This paper reviews the back-round research and procedures of an experiment designed to prevent space motion sickness in shuttle crewmembers. The preventive method used, Autogenic - Feedback Training (AFT) involves training subjects to control voluntarily several of their own physiological responses to environmental stressors. AFT has been used reliably to increase tolerance to motion sickness during around based tests in over 300 men and women under a variety of conditions that induce motion sickness, and preliminary evidence from space suggests that AFT may be an effective treatment for space motion sickness as well. Other applications of AFT described include; (1) a potential treatment for post flight orthostatic intolerance, a serious biomedical problem resulting from long duration exposure to micro-g and (2) improving pilot performance during emergency flying conditions.

Cowings, Patricia S.↗

ECTFE (HALAR) as a New Material for Primary Sample Containment of Astromaterials

Fluoropolymers, such as Teflon® (PTFE, PFA, FEP) and Viton® (FKM), have been used for over 40 years in curating astromaterials at NASA JSC. In general, fluoropolymers have low outgassing and particle shedding properties that reduce cross-contamination to curated samples. Ethylene - Chlorotrifluoroethylene (ECTFE), commonly called Halar® (trademark of Solvay Solexis), is a partially fluorinated semi-crystalline copolymer in the same class of fluoropolymers with superior abrasion resistance and extremely low permeability to liquids, gases, and vapors than any other fluoropolymer (fig. 1). ECTFE coatings are becoming more popular in the nuclear, semiconductor, and biomedical industry for lining isolation containment gloveboxes and critical piping as well as other clean room applications. A study was conducted at NASA JSC to evaluate the potential use of Halar on future sample return missions as a material for primary sample containment.

Calaway, Michael J.↗

A pre-training and self-training approach for biomedical named entity recognition

Named entity recognition (NER) is a key component of many scientific literature mining tasks, such as information retrieval, information extraction, and question answering; however, many modern approaches require large amounts of labeled training data in order to be effective. This severely limits the effectiveness of NER models in applications where expert annotations are difficult and expensive to obtain. In this work, we explore the effectiveness of transfer learning and semi-supervised self-training to improve the performance of NER models in biomedical settings with very limited labeled data (250-2000 labeled samples). We first pre-train a BiLSTM-CRF and a BERT model on a very large general biomedical NER corpus such as MedMentions or Semantic Medline, and then we fine-tune the model on a more specific target NER task that has very limited training data; finally, we apply semi-supervised self-training using unlabeled data to further boost model performance. We show that in NER tasks that focus on common biomedical entity types such as those in the Unified Medical Language System (UMLS), combining transfer learning with self-training enables a NER model such as a BiLSTM-CRF or BERT to obtain similar performance with the same model trained on 3x-8x the amount of labeled data. We further show that our approach can also boost performance in a low-resource application where entities types are more rare and not specifically covered in UMLS.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Applications of Kinetic Methods in Thermal Analysis: A Review

Determining kinetic parameters such as activation energy (Ea), pre-exponential factor (A), rate constants, and reaction order (n) via thermal analysis techniques is important to material synthesis and fabrication, industrial production, biomedicals, energy storage, catalysis, etc. Various kinetic methods based on the non-isothermal techniques have been developed to obtain the kinetic parameters. In this review, we focus on introducing various kinetic methods in non-isothermal analysis and their applications in different reactions, including thermal decomposition, solid-state phase transformation, crystallization, thermal ignition, curing process, etc.

Zhang, Xin↗