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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Very-Long-Distance Remote Hearing and Vibrometry

A proposed development of laser-based instrumentation systems would extend the art of laser Doppler vibrometry beyond the prior limits of laser-assisted remote hearing and industrial vibrometry for detecting defects in operating mechanisms. A system according to the proposal could covertly measure vibrations of objects at distances as large as thousands of kilometers and could process the measurement data to enable recognition of vibrations characteristic of specific objects of interest, thereby enabling recognition of the objects themselves. A typical system as envisioned would be placed in orbit around the Earth for use as a means of determining whether certain objects on or under the ground are of interest as potential military targets. Terrestrial versions of these instruments designed for airborne or land- or sea-based operation could be similarly useful for military or law-enforcement purposes. Prior laser-based remote-hearing systems are not capable of either covert operation or detecting signals beyond modest distances when operated at realistic laser power levels. The performances of prior systems for recognition of objects by remote vibrometry are limited by low signal-to-noise ratios and lack of filtering of optical signals returned from targets. The proposed development would overcome these limitations. A system as proposed would include a narrow-band laser as its target illuminator, a lock-in-detection receiver subsystem, and a laser-power-control subsystem that would utilize feedback of the intensity of background illumination of the target to adjust the laser power. The laser power would be set at a level high enough to enable the desired measurements but below the threshold of detectability by an imaginary typical modern photodetector located at the target and there exposed to the background illumination. The laser beam would be focused tightly on the distant target, such that the receiving optics would be exposed to only one speckle. The return signal would be extremely-narrow-band filtered (to sub-kilohertz bandwidth) in the optical domain by a whispering-gallery- mode filter so as to remove most of the background illumination. The filtered optical signal would be optically amplified. This combination of optical filtering and optical amplification would provide an optical signal that would be strong enough to be detectable but not so strong as to saturate the detector in the lock-in detection subsystem.

Maleki, Lute↗
DOE OSTI2013

Advanced simulation capability for environmental management - current status and future applications

The U.S. Department of Energy (US DOE) Office of Environmental Management (EM), Office of Soil and Groundwater (EM-12), is supporting development of the Advanced Simulation Capability for Environmental Management (ASCEM). ASCEM is a state-of-the-art scientific tool and approach that is currently aimed at understanding and predicting contaminant fate and transport in natural and engineered systems. ASCEM is a modular and open source high-performance computing tool. It will be used to facilitate integrated approaches to modeling and site characterization, and provide robust and standardized assessments of performance and risk for EM cleanup and closure activities. The ASCEM project continues to make significant progress in development of capabilities, with current emphasis on integration of capabilities in FY12. Capability development is occurring for both the Platform and Integrated Tool-sets and High-Performance Computing (HPC) multi-process simulator. The Platform capabilities provide the user interface and tools for end-to-end model development, starting with definition of the conceptual model, management of data for model input, model calibration and uncertainty analysis, and processing of model output, including visualization. The HPC capabilities target increased functionality of process model representations, tool-sets for interaction with Platform, and verification and model confidence testing. The integration of the Platform and HPC capabilities were tested and evaluated for EM applications in a set of demonstrations as part of Site Applications Thrust Area activities in 2012. The current maturity of the ASCEM computational and analysis capabilities has afforded the opportunity for collaborative efforts to develop decision analysis tools to support and optimize radioactive waste disposal. Recent advances in computerized decision analysis frameworks provide the perfect opportunity to bring this capability into ASCEM. This will allow radioactive waste disposal to be evaluated based on decision needs, such as disposal, closure, and maintenance. Decision models will be used in ASCEM to identify information/data needs, and model refinements that might be necessary to effectively reduce uncertainty in waste disposal decisions. Decision analysis models start with tools for framing the problem, and continue with modeling both the science side of the problem (for example, inventories, source terms, fate and transport, receptors, risk, etc.), and the cost side of the problem, which could include costs of implementation of any action that is chosen (e.g., for disposal or closure), and the values associated with those actions. The cost side of the decision problem covers economic, environmental and societal costs, which correspond to the three pillars of sustainability (economic, social, and environmental). These tools will facilitate stakeholder driven decision analysis to support optimal sustainable solutions in ASCEM. In this paper the current state of ASCEM is first described, followed by a description of the approach that will be taken to augment ASCEM for simulating fate and transport with tools that facilitate a top-down or systems level view of finding optimal, sustainable solutions to difficult environmental (including radioactive waste) problems. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2013

Advanced Simulation Capability for Environmental Management - Current Status and Phase II Demonstration Results - 13161

The U.S. Department of Energy (US DOE) Office of Environmental Management (EM), Office of Soil and Groundwater, is supporting development of the Advanced Simulation Capability for Environmental Management (ASCEM). ASCEM is a state-of-the-art scientific tool and approach for understanding and predicting contaminant fate and transport in natural and engineered systems. The modular and open source high-performance computing tool facilitates integrated approaches to modeling and site characterization that enable robust and standardized assessments of performance and risk for EM cleanup and closure activities. The ASCEM project continues to make significant progress in development of computer software capabilities with an emphasis on integration of capabilities in FY12. Capability development is occurring for both the Platform and Integrated Tool-sets and High-Performance Computing (HPC) Multi-process Simulator. The Platform capabilities provide the user interface and tools for end-to-end model development, starting with definition of the conceptual model, management of data for model input, model calibration and uncertainty analysis, and processing of model output, including visualization. The HPC capabilities target increased functionality of process model representations, tool-sets for interaction with Platform, and verification and model confidence testing. The Platform and HPC capabilities are being tested and evaluated for EM applications in a set of demonstrations as part of Site Applications Thrust Area activities. The Phase I demonstration focusing on individual capabilities of the initial tool-sets was completed in 2010. The Phase II demonstration completed in 2012 focused on showcasing integrated ASCEM capabilities. For Phase II, the Hanford Site deep vadose zone (BC Cribs) served as an application site for an end-to-end demonstration of capabilities, with emphasis on integration and linkages between the Platform and HPC components. Other demonstrations, addressing attenuation-based remedies at the Savannah River Site F Area and performance assessment for a representative waste tank, illustrate integration of linked ASCEM capabilities and initial integration efforts with tools from the Cementitious Barriers Partnership. (authors)

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Characterization of SETD3 methyltransferase–mediated protein methionine methylation

Most characterized protein methylation events encompass arginine and lysine N-methylation, and only a few cases of protein methionine thiomethylation have been reported. Newly discovered oncohistone mutations include lysine-to-methionine substitutions at positions 27 and 36 of histone H3.3. In these cases, the methionine substitution localizes to the active-site pocket of the corresponding histone lysine methyltransferase, thereby inhibiting the respective transmethylation activity. SET domain–containing 3 (SETD3) is a protein (i.e. actin) histidine methyltransferase. Here, we generated an actin variant in which the histidine target of SETD3 was substituted with methionine. As for previously characterized histone SET domain proteins, the methionine substitution substantially (76-fold) increased binding affinity for SETD3 and inhibited SETD3 activity on histidine. Unexpectedly, SETD3 was active on the substituted methionine, generating S-methylmethionine in the context of actin peptide. The ternary structure of SETD3 in complex with the methionine-containing actin peptide at 1.9 Å resolution revealed that the hydrophobic thioether side chain is packed by the aromatic rings of Tyr 312 and Trp 273 , as well as the hydrocarbon side chain of Ile 310 . Our results suggest that placing methionine properly in the active site—within close proximity to and in line with the incoming methyl group of SAM—would allow some SET domain proteins to selectively methylate methionine in proteins.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Importance of appropriate genome information for the design of mating type primers in black and yellow morel populations

Abstract Morels are highly prized edible fungi where sexual reproduction is essential for fruiting-body production. As a result, a comprehensive understanding of their sexual reproduction is of great interest. Central to this is the identification of the reproductive strategies used by morels. Sexual reproduction in fungi is controlled by mating-type ( MAT ) genes and morels are thought to be mainly heterothallic with two idiomorphs, MAT1-1 and MAT1-2. Genomic sequencing of black (Elata clade) and yellow (Esculenta clade) morel species has led to the development of PCR primers designed to amplify genes from the two idiomorphs for rapid genotyping of isolates from these two clades. To evaluate the design and theoretical performance of these primers we performed a thorough bioinformatic investigation, including the detection of the MAT region in publicly available Morchella genomes and in-silico PCR analyses. All examined genomes, including those used for primer design, appeared to be heterothallic. This indicates an inherent fault in the original primer design which utilized a single Morchella genome, as the use of two genomes with complementary mating types would be required to design accurate primers for both idiomorphs. Furthermore, potential off-targets were identified for some of the previously published primer sets, but verification was challenging due to lack of adequate genomic information and detailed methodologies for primer design. Examinations of the black morel specific primer pairs (MAT11L/R and MAT22L/R) indicated the MAT22 primers would correctly target and amplify the MAT1-2 idiomorph, but the MAT11 primers appear to be capable of amplifying incorrect off-targets within the genome. The yellow morel primer pairs (EMAT1-1 L/R and EMAT1-2 L/R) appear to have reporting errors, as the published primer sequences are dissimilar with reported amplicon sequences and the EMAT1-2 primers appear to amplify the RNA polymerase II subunit ( RPB2 ) gene. The lack of the reference genome used in primer design and descriptive methodology made it challenging to fully assess the apparent issues with the primers for this clade. In conclusion, additional work is still required for the generation of reliable primers to investigate mating types in morels and to assess their performance on different clades and across multiple geographical regions.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2006

An Improved Flow Cytometry Method For Precise Quantitation Of Natural-Killer Cell Activity

The ability to assess NK cell cytotoxicity using flow cytometry has been previously described and can serve as a powerful tool to evaluate effector immune function in the clinical setting. Previous methods used membrane permeable dyes to identify target cells. The use of these dyes requires great care to achieve optimal staining and results in a broad spectral emission that can make multicolor cytometry difficult. Previous methods have also used negative staining (the elimination of target cells) to identify effector cells. This makes a precise quantitation of effector NK cells impossible due to the interfering presence of T and B lymphocytes, and the data highly subjective to the variable levels of NK cells normally found in human peripheral blood. In this study an improved version of the standard flow cytometry assay for NK activity is described that has several advantages of previous methods. Fluorescent antibody staining (CD45FITC) is used to positively identify target cells in place of membranepermeable dyes. Fluorescent antibody staining of target cells is less labor intensive and more easily reproducible than membrane dyes. NK cells (true effector lymphocytes) are also positively identified by fluorescent antibody staining (CD56PE) allowing a simultaneous absolute count assessment of both NK cells and target cells. Dead cells are identified by membrane disruption using the DNA intercalating dye PI. Using this method, an exact NK:target ratio may be determined for each assessment, including quantitation of NK target complexes. Backimmunoscatter gating may be used to track live vs. dead Target cells via scatter properties. If desired, NK activity may then be normalized to standardized ratios for clinical comparisons between patients, making the determination of PBMC counts or NK cell percentages prior to testing unnecessary. This method provides an exact cytometric determination of NK activity that highly reproducible and may be suitable for routine use in the clinical setting.

Crucian, Brian↗
DOE OSTI2016

SU-F-T-201: Acceleration of Dose Optimization Process Using Dual-Loop Optimization Technique for Spot Scanning Proton Therapy

Purpose: The purpose was to demonstrate a developed acceleration technique of dose optimization and to investigate its applicability to the optimization process in a treatment planning system (TPS) for proton therapy. Methods: In the developed technique, the dose matrix is divided into two parts, main and halo, based on beam sizes. The boundary of the two parts is varied depending on the beam energy and water equivalent depth by utilizing the beam size as a singular threshold parameter. The optimization is executed with two levels of iterations. In the inner loop, doses from the main part are updated, whereas doses from the halo part remain constant. In the outer loop, the doses from the halo part are recalculated. We implemented this technique to the optimization process in the TPS and investigated the dependence on the target volume of the speedup effect and applicability to the worst-case optimization (WCO) in benchmarks. Results: We created irradiation plans for various cubic targets and measured the optimization time varying the target volume. The speedup effect was improved as the target volume increased, and the calculation speed increased by a factor of six for a 1000 cm3 target. An IMPT plan for the RTOG benchmark phantom was created in consideration of ±3.5% range uncertainties using the WCO. Beams were irradiated at 0, 45, and 315 degrees. The target’s prescribed dose and OAR’s Dmax were set to 3 Gy and 1.5 Gy, respectively. Using the developed technique, the calculation speed increased by a factor of 1.5. Meanwhile, no significant difference in the calculated DVHs was found before and after incorporating the technique into the WCO. Conclusion: The developed technique could be adapted to the TPS’s optimization. The technique was effective particularly for large target cases.

60 APPLIED LIFE SCIENCES↗
NASA NTRSDate not supplied

Analysis of CDC Bioreactor Internal Thermal Measurements and Sample Coupon Temperatures

The Center for Disease Control and Prevention (CDC) bioreactor is an integral laboratory tool for the Environmental Control and Life Support Systems (ECLSS) biofilm formation and growth research program. Critical to this research is the need to adjust and maintain various surface temperatures of the coupons housed within the CDC Bioreactor. The purpose of this study was to provide quantitative temperature gradient information when the CDC Bioreactor was operating according to several process scenarios. Two primary process parameters were evaluated. For the first set of test parameters, the liquid level was maintained at 350 mL, with an inlet flowrate of 0.1 mL/min, 1 mL/min, 10 mL/min. The liquid was allowed to gravity drain out of the outlet spout. For the second set of test parameters, the liquid level within the reactor was maintained at 550 mL, with an inlet flow of 0.1 mL/min, 1 mL/min, 10 mL/min and draining intermittently controlled to 0.8 mL/min to maintain the 550 mL level. Due to the placement of the thermocouple in the reactor, a difference in temperature occurred between the coupon surfaces and target Bioreactor temperature when operated according to the first set of test parameters. When the reactor was operated according to the second set of parameters, which resulted in the thermocouple being submerged, the temperature gradient was eliminated. The results demonstrated minimal temperature gradient between the top and bottom coupon surfaces for coupons placed in a single rod within the CDC Bioreactor for both sets of test parameters evaluated. The collection of this information helped to explain previous ECLSS biofilm formation test runs, along with providing guidance on best operating practices for future ECLSS experiments. The placement of the thermocouple also helps to explain the challenge of achieving and maintaining bulk liquid temperatures when biofilm is grown according to the standardized test methods.

CDC Bioreactor↗
DOE OSTI2026

Transfer learning for analysis of collective and non-collective Thomson scattering spectra

Thomson scattering (TS) diagnostics provide reliable, minimally perturbative measurements of fundamental plasma parameters, such as electron density (⁠n e ) and electron temperature (⁠T e ⁠). Deep neural networks can provide accurate estimates of ⁠n e and T e when conventional fitting algorithms may fail, such as when TS spectra are dominated by noise, or when fast analysis is required for real-time operation. Although deep neural networks typically require large training sets, transfer learning can improve model performance on a target task with limited data by leveraging pre-trained models from related source tasks, where select hidden layers are further trained using target data. We present five architecturally diverse deep neural networks, pre-trained on synthetic TS data and adapted for experimentally measured TS data, to evaluate the efficacy of transfer learning in estimating n e and T e in both the collective and non-collective scattering regimes. We evaluate errors in n e and T e estimates as a function of training set size for models trained with and without transfer learning, and we observe decreases in model error from transfer learning when the training set contains ≲ 200 experimentally measured spectra.

Artificial neural networks↗
NASA NTRS1992

Development of a tool-set for simultaneous, multi-site observations of astronomical objects

A network of ground and space based telescopes can provide continuous observation of astronomical objects. In a 'Target of Opportunity' scenario triggered by the system, any telescope on the network may request supporting observations. We propose to develop a set of data collection and display tools to support these observations. We plan to demonstrate the usefulness of this tool set for simultaneous multi-site observations of astronomical targets. Possible candidates for the proposed demonstration include the Extreme Ultraviolet Explorer, International Ultraviolet Explorer, ALEXIS, and sounding rocket experiments. Ground based observations operated by the University of California, Berkeley; the Jet Propulsion Laboratory; and Fairborn Observatory, Mesa, Arizona will be used to demonstrate the proposed concept. Although the demonstration will involve astronomical investigations, these tools will be applicable to a large number of scientific disciplines. The software tools and systems developed as a result of our work will be made available to the scientific community.

Chakrabarti, Supriya↗
DOE OSTI2018

Moving K-12 Zero Energy Schools to the Mainstream: Establishing Design Guidelines and Energy Targets

K-12 school buildings are ideal candidates to lead the market shift from buildings that consume energy to buildings that produce as much renewable energy as they use, and there are now resources available to guide owners and project teams as they make that shift. Chief among them is the Advanced Energy Design Guide for K-12 School Buildings: Achieving Zero Energy (K-12 ZE AEDG). Starting with a feasibility study to prove that zero energy schools were possible, a committee of industry experts used extensive energy modeling to create a set of energy use intensity allowances for school buildings such that on-site renewable energy could meet the buildings' energy loads . These energy targets were compared with the energy use intensities of a limited number of schools that have achieved very high levels of energy performance. The allowances represent a 'zero energy ready' (rather than zero energy) school, because in many situations the ability to use on-site renewable sources is limited by utilities, policies, or economics. From these targets, the guidance for achieving a zero energy school was created and developed into the K-12 ZE AEDG, which covers the process of designing and building zero energy schools from the perspective of an owner and a project team. The K-12 ZE AEDG advocates setting an absolute energy target before design begins. The K-12 ZE AEDG also contains practical, cost-effective strategies for achieving the energy target and outreach approaches and disseminating these market-friendly strategies to design and school owner communities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Identification and preliminary characterization of conserved uncharacterized proteins from Chlamydomonas reinhardtii , Arabidopsis thaliana , and Setaria viridis

Abstract The rapid accumulation of sequenced plant genomes in the past decade has outpaced the still difficult problem of genome‐wide protein‐coding gene annotation. A substantial fraction of protein‐coding genes in all plant genomes are poorly annotated or unannotated and remain functionally uncharacterized. We identified unannotated proteins in three model organisms representing distinct branches of the green lineage (Viridiplantae): Arabidopsis thaliana (eudicot), Setaria viridis (monocot), and Chlamydomonas reinhardtii (Chlorophyte alga). Using similarity searching, we identified a subset of unannotated proteins that were conserved between these species and defined them as Deep Green proteins. Bioinformatic, genomic, and structural predictions were performed to begin classifying Deep Green genes and proteins. Compared to whole proteomes for each species, the Deep Green set was enriched for proteins with predicted chloroplast targeting signals predictive of photosynthetic or plastid functions, a result that was consistent with enrichment for daylight phase diurnal expression patterning. Structural predictions using AlphaFold and comparisons to known structures showed that a significant proportion of Deep Green proteins may possess novel folds. Though only available for three organisms, the Deep Green genes and proteins provide a starting resource of high‐value targets for further investigation of potentially new protein structures and functions conserved across the green lineage.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

An active learning high-throughput microstructure calibration framework for solving inverse structure–process problems in materials informatics

Determining a process–structure–property relationship is the holy grail of materials science, where both computational prediction in the forward direction and materials design in the inverse direction are essential. Problems in materials design are often considered in the context of process–property linkage by bypassing the materials structure, or in the context of structure–property linkage as in microstructure-sensitive design problems. However, there is a lack of research effort in studying materials design problems in the context of process–structure linkage, which has a great implication in reverse engineering. In this paper, given a target microstructure, we propose an active learning high-throughput microstructure calibration framework to derive a set of processing parameters, which can produce an optimal microstructure that is statistically equivalent to the target microstructure. The proposed framework is formulated as a noisy multi-objective optimization problem, where each objective function measures a deterministic or statistical difference of the same microstructure descriptor between a candidate microstructure and a target microstructure. Furthermore, to significantly reduce the physical waiting wall-time, we enable the high-throughput feature of the microstructure calibration framework by adopting an asynchronously parallel Bayesian optimization to exploit high-performance computing resources. Case studies in additive manufacturing and grain growth are used to demonstrate the applicability of the proposed framework, where kinetic Monte Carlo (kMC) simulation is used as a forward predictive model, such that for a given target microstructure, the target processing parameters that produced this microstructure are successfully recovered.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Mucosal Melanoma of the Head and Neck: A Systematic Review of the Literature

Primary mucosal melanoma of the head and neck (MMHN) comprises approximately 1% of all malignant melanomas. It presents more commonly in an elderly population and has no significant gender predominance. Given its rarity, most evidence of the causes, behavior, and treatment approaches for MMHN originates from isolated case reports and retrospective series. Between 1945 and 2011, at least 1951 cases of MMHN have been reported in the literature. Despite numerous technological developments in surgery and radiation therapy, as well as advances in systemic modalities, MMHN is an aggressive malignancy with a very poor prognosis. Complete surgical excision with clear margins remains the primary treatment modality. Adjuvant postoperative radiation therapy may improve locoregional control but does not appear to affect survival. Definitive particle radiation therapy promises to provide high rates of local control for nonoperable patients. Recent molecular evidence suggests that proto-oncogene KIT aberrations in a subset of mucosal melanomas may represent a potential diagnostic value and serve as a therapeutic target for tyrosine kinase inhibitors in an adjuvant setting for patients with advanced MMHN.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

Evaluating proton stereotactic body radiotherapy to reduce chest wall dose in the treatment of lung cancer

Stereotactic body radiotherapy (SBRT) can produce excellent local control of several types of solid tumor; however, toxicity to nearby critical structures is a concern. We found previously that in SBRT for lung cancer, the chest wall (CW) volume receiving 20, 30, or 40 Gy (V{sub 20}, V{sub 30}, or V{sub 40}) was linked with the development of neuropathy. Here we sought to determine whether the dosimetric advantages of protons could produce lower CW doses than traditional photon-based SBRT. We searched an institutional database to identify patients treated with photon SBRT for lung cancer with tumors within < 2.5 cm of the CW. We found 260 cases; of these, chronic grade ≥ 2 CW pain was identified in 23 patients. We then selected 10 representative patients from this group and generated proton SBRT treatment plans, using the identical dose of 50 Gy in 4 fractions, and assessed potential differences in CW dose between the 2 plans. The proton SBRT plans reduced the CW doses at all dose levels measured. The median CW V{sub 20} was 364.0 cm{sup 3} and 160.0 cm{sup 3} (p < 0.0001), V{sub 30} was 144.6 cm{sup 3}vs 77.0 cm{sup 3} (p = 0.0012), V{sub 35} was 93.9 cm{sup 3}vs 57.9 cm{sup 3} (p = 0.005), V{sub 40} was 66.5 cm{sup 3}vs 45.4 cm{sup 3} (p = 0.0112), and mean lung dose was 5.9 Gy vs 3.8 Gy (p = 0.0001) for photons and protons, respectively. Coverage of the planning target volume (PTV) was comparable between the 2 sets of plans (96.4% for photons and 97% for protons). From a dosimetric standpoint, proton SBRT can achieve the same coverage of the PTV while significantly reducing the dose to the CW and lung relative to photon SBRT and therefore may be beneficial for the treatment of lesions closer to critical structures.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2023

Using machine learning to predict the correlation of spectra using SDSS magnitudes as an improvement to the Locus Algorithm

The Locus Algorithm is a new technique to improve the quality of differential photometry by optimising the choices of reference stars. At the heart of this algorithm is a routine to assess how good each potential reference star is by comparing its SDSS magnitude values to those of the target star. In this way, the difference in wavelength-dependent effects of the Earth’s atmospheric scattering between target and reference can be minimised. This paper sets out a new way to estimate the quality of each reference star using machine learning. A random subset of stars from SDSS with spectra was chosen. For each one, a suitable reference star, also with a spectrum, was chosen. The correlation between the two spectra in the SDSS r band (between 550 nm and 700 nm) was taken to be the gold-standard measure of how well they match up for differential photometry. The five SDSS magnitude values for each of these stars were used as predictors. A number of supervised machine learning models were constructed on a training set of the stars and were each evaluated on a testing set. The model using Support Vector Regression had the best performance of these models. It was then tested on a final, hold-out, validation set of stars to get an unbiased measure of its performance. With an R 2 of 0.62, the SVR model presents enhanced performance for the Locus Algorithm technique.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Chespa: Streamlining Expansive Chemical Space Evaluation of Molecular Sets

Thousands of chemical properties can be calculated for small molecules, which can be used to place the molecules within the context of a broader “chemical space.” These definitions vary based on compounds of interest and the goals for the given chemical space definition. Here, we introduce a customizable (i.e., modular) Python module, chespa, built to easily assess different chemical space definitions through cluster-ing of compounds in these spaces and visualize trends of these clusters. To demonstrate this, chespa currently streamlines prediction of vari-ous molecule descriptors (predicted chemical properties, molecular substructures, AI-based chemical space, and chemical class ontology) in order to test 6 different chemical space definitions. Furthermore, we investigated how these varying definitions trend with mass spectrometry (MS)-based observability, i.e., the ability of a molecule to be observed with MS (e.g., as a function of the molecule ionizability), using an example data set from the U.S. EPA's Non-Targeted Analysis Collaborative Trial (ENTACT), where blinded samples had been analyzed previously, providing 1,398 data points. Improved understanding of observability would offer many advantages in small molecule identifica-tion, such as (i) a priori selection of experimental conditions based on suspected sample composition, (ii) the ability to reduce the number of candidate structures during compound identification by removing those less likely to ionize, and, in turn, (iii) a reduced false discovery rate and increased confidence in identifications. Factors controlling observability are not fully understood, making prediction of this property non-trivial and a prime candidate for chemical space analysis. Chespa is available at github.com/pnnl/chespa.

Nunez, Jamie↗
DOE OSTI2018

Structure of the activated Edc1-Dcp1-Dcp2-Edc3 mRNA decapping complex with substrate analog poised for catalysis

The conserved decapping enzyme Dcp2 recognizes and removes the 5' eukaryotic cap from mRNA transcripts in a critical step of many cellular RNA decay pathways. Dcp2 is a dynamic enzyme that functions in concert with the essential activator Dcp1 and a diverse set of coactivators to selectively and efficiently decap target mRNAs in the cell. Here we present a 2.84 Å crystal structure of K . lactis Dcp1–Dcp2 in complex with coactivators Edc1 and Edc3, and with substrate analog bound to the Dcp2 active site. Our structure shows how Dcp2 recognizes cap substrate in the catalytically active conformation of the enzyme, and how coactivator Edc1 forms a three-way interface that bridges the domains of Dcp2 to consolidate the active conformation. Kinetic data reveal Dcp2 has selectivity for the first transcribed nucleotide during the catalytic step. The heterotetrameric Edc1–Dcp1–Dcp2–Edc3 structure shows how coactivators Edc1 and Edc3 can act simultaneously to activate decapping catalysis.

Science & Technology - Other Topics↗