Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Cluster detection”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,243 records · Page 69

Micro-machined planar field asymmetric ion mobility spectrometer as a gas chromatographic detector

A planar high field asymmetric waveform ion mobility spectrometer (PFAIMS) with a micro-machined drift tube was characterized as a detector for capillary gas chromatography. The performance of the PFAIMS was compared directly to that of a flame ionization detector (FID) for the separation of a ketone mixture from butanone to decanone. Effluent from the column was continuously sampled by the detector and mobility scans could be obtained throughout the chromatographic analysis providing chemical inforrmation in mobility scans orthogonal to retention time. Limits of detection were approximately I ng for measurement of positive ions and were comparable or slightly better than those for the FID. Direct comparison of calibration curves for the FAIMS and the FID was possible over four orders of magnitude with a semi-log plot. The concentration dependence of the PFAIMS mobility scans showed the dependence between ion intensity and ion clustering, evident in other mobility spectrometers and atmospheric pressure ionization technologies. Ions were identified using mass spectrometry as the protonated monomer and the proton bound dimer of the ketones. Residence time for column effluent in the PFAIMS was calculated as approximately 1 ms and a 36% increase in extra-column broadening versus the FID occurred with the PFAIMS.

NASA Discipline Life Sciences Technologies↗

Sulfur Molecules in Space by X-rays: A Computational Study

X-ray astronomy lacks high resolution spectra of interstellar dust analogues and molecules, severely hampering interstellar medium studies based on upcoming X-ray missions. Various theoretical approaches may be used to address this problem, but they must first be shown to reproduce reliable spectra compared to the experiment. In this work, we calculate the sulfur Kedge X-ray absorption spectra of H2S, SO2, and OCS, whose spectra are already known from X-ray experiments and predict the X-ray spectrum of CS, which as far as we are aware has not been measured, thereby hampering its detection by X-ray telescopes. We chose these four molecules as the astrochemistry of sulfur is an unsolved problem and as the four molecules are already known to exist in space. We consider three types of methods for modeling the X-ray spectra: more accurate calculations with the algebraic-diagrammatic construction (ADC) and the CC2, CCSD, and CC3coupled cluster (CC) approaches as well as more affordable ones with transition potential density functional theory (TP-DFT). A comparison of our computational results to previously reported experimental spectra shows that the core−valence separation (CVS)approaches CVS-ADC(2)-x and CVS-CC3 generally yield a good qualitative level of agreement with the experiment, suggesting that they can be used for interpreting measured spectra, while the TP-DFT method is not reliable for these molecules. However, quantitative agreement with the experiment is still outside the reach of the computational methods studied in this work.

Goranka Bilalbegovic↗

Graph theory inspired anomaly detection at the LHC

Designing model-independent anomaly detection algorithms for analyzing LHC data remains a central challenge in the search for new physics, due to the high dimensionality of collider events. In this work, we develop a graph autoencoder as an unsupervised, model-agnostic tool for anomaly detection, using the LHC Olympics dataset as a benchmark. By representing jet constituents as a graph, we introduce a method to systematically control the information available to the model through sparse graph constructions that serve as physically motivated inductive biases. Specifically, (1) we construct graph autoencoders based on locally rigid Laman graphs and globally rigid unique graphs, and (2) we explore the clustering of jet constituents into subjets to interpolate between high- and low-level input representations. We obtain the best performance, measured in terms of the Significance Improvement Characteristic curve for an intermediate level of subjet clustering and certain sparse unique graph constructions. We further investigate the role of graph connectivity in jet classification tasks. Our results demonstrate the potential of leveraging graph-theoretic insights to refine and increase the interpretability of machine learning tools for collider experiments.

Automation↗

The Importance of Being Adaptable: An Exploration of the Power and Limitations of Domain Adaptation for Simulation-Based Inference with Galaxy Clusters

The application of deep machine learning methods in astronomy has exploded in the last decade, with new models showing remarkably improved performance on benchmark tasks. Not nearly enough attention is given to understanding the models' robustness, especially when the test data are systematically different from the training data, or "out of domain." Domain shift poses a significant challenge for simulation-based inference, where models are trained on simulated data but applied to real observational data. In this paper, we explore domain shift and test domain adaptation methods for a specific scientific case: simulation-based inference for estimating galaxy cluster masses from X-ray profiles. We build datasets to mimic simulation-based inference: a training set from the Magneticum simulation, a scatter-augmented training set to capture uncertainties in scaling relations, and a test set derived from the IllustrisTNG simulation. We demonstrate that the Test Set is out of domain in subtle ways that would be difficult to detect without careful analysis. We apply three deep learning methods: a standard neural network (NN), a neural network trained on the scatter-augmented input catalogs, and a Deep Reconstruction-Regression Network (DRRN), a semi-supervised deep model engineered to address domain shift. Although the NN improves results by 17% in the Training Data, it performs 40% worse on the out-of-domain Test Set. Surprisingly, the Scatter-Augmented Neural Network (SANN) performs similarly. While the DRRN is successful in mapping the training and Test Data onto the same latent space, it consistently underperforms compared to a straightforward Yx scaling relation. These results serve as a warning that simulation-based inference must be handled with extreme care, as subtle differences between training simulations and observational data can lead to unforeseen biases creeping into the results.

Ntampaka, Michelle [Baltimore, Space Telescope Sci↗

Microbial secondary metabolites: advancements to accelerate discovery towards application

Microbial secondary metabolites not only have key roles in microbial processes and relationships but are also valued in various sectors of today’s economy, especially in human health and agriculture. The advent of genome sequencing has revealed a previously untapped reservoir of biosynthetic capacity for secondary metabolites indicating that there are new biochemistries, roles and applications of these molecules to be discovered. New predictive tools for biosynthetic gene clusters (BGCs) and their associated pathways have provided insights into this new diversity. Advanced molecular and synthetic biology tools and workflows including cell-based and cell-free expression facilitate the study of previously uncharacterized BGCs, accelerating the discovery of new metabolites and broadening our understanding of biosynthetic enzymology and the regulation of BGCs. These are complemented by new developments in metabolite detection and identification technologies, all of which are important for unlocking new chemistries that are encoded by BGCs. This renaissance of secondary metabolite research and development is catalysing toolbox development to power the bioeconomy.

Dinglasan, Jaime Lorenzo N↗

Observations of grain-boundary phase transformations in an elemental metal

The theory of grain boundary (the interface between crystallites, GB) structure has a long history 1 and the concept of GBs undergoing phase transformations was proposed 50 years ago 2,3 . The underlying assumption was that multiple stable and metastable states exist for different GB orientations 4,5,6 . The terminology ‘complexion’ was recently proposed to distinguish between interfacial states that differ in any equilibrium thermodynamic property 7 . Different types of complexion and transitions between complexions have been characterized, mostly in binary or multicomponent systems 8,9,10,11,12,13,14,15,16,17,18,19 . Simulations have provided insight into the phase behaviour of interfaces and shown that GB transitions can occur in many material systems 20,21,22,23,24 . However, the direct experimental observation and transformation kinetics of GBs in an elemental metal have remained elusive. In this work we demonstrate atomic-scale GB phase coexistence and transformations at symmetric and asymmetric $[11\bar{1}]$ tilt GBs in elemental copper. Atomic-resolution imaging reveals the coexistence of two different structures at Σ19b GBs (where Σ19 is the density of coincident sites and b is a GB variant), in agreement with evolutionary GB structure search and clustering analysis 21,25,26 . We also use finite-temperature molecular dynamics simulations to explore the coexistence and transformation kinetics of these GB phases. Our results demonstrate how GB phases can be kinetically trapped, enabling atomic-scale room-temperature observations. Our work paves the way for atomic-scale in situ studies of metallic GB phase transformations, which were previously detected only indirectly 9,15,27,28,29 , through their influence on abnormal grain growth, non-Arrhenius-type diffusion or liquid metal embrittlement.

36 MATERIALS SCIENCE↗

The foxtail millet ( Setaria italica ) terpene synthase gene family

Terpenoid metabolism plays vital roles in stress defense and the environmental adaptation of monocot crops. Here, we describe the identification of the terpene synthase (TPS) gene family of the panicoid food and bioenergy model crop foxtail millet (Setaria italica). The diploid S. italica genome contains 32 TPS genes, 17 of which were biochemically characterized in this study. Unlike other thus far investigated grasses, S. italica contains TPSs producing all three ent-, (+)- and syn-copalyl pyrophosphate stereoisomers that naturally occur as central building blocks in the biosynthesis of distinct monocot diterpenoids. Conversion of these intermediates by the promiscuous TPS SiTPS8 yielded different diterpenoid scaffolds. Additionally, a cytochrome P450 monooxygenase (CYP99A17), which genomically clustered with SiTPS8, catalyzes the C19 hydroxylation of SiTPS8 products to generate the corresponding diterpene alcohols. The presence of syntenic orthologs to about 19% of the S. italica TPSs in related grasses supports a common ancestry of selected pathway branches. Among the identified enzyme products, abietadien-19-ol, syn-pimara-7,15-dien-19-ol and germacrene-D-4-ol were detectable in planta, and gene expression analysis of the biosynthetic TPSs showed distinct and, albeit moderately, inducible expression patterns in response to biotic and abiotic stress. In vitro growth-inhibiting activity of abietadien-19-ol and syn-pimara-7,15-dien-19-ol against Fusarium verticillioides and Fusarium subglutinans may indicate pathogen defensive functions, whereas the low antifungal efficacy of tested sesquiterpenoids supports other bioactivities. Together, these findings expand the known chemical space of monocot terpenoid metabolism to enable further investigations of terpenoid-mediated stress resilience in these agriculturally important species.

59 BASIC BIOLOGICAL SCIENCES↗

An analysis of fracture trace patterns in areas of flat-lying sedimentary rocks for the detection of buried geologic structure

Two study areas in a cratonic platform underlain by flat-lying sedimentary rocks were analyzed to determine if a quantitative relationship exists between fracture trace patterns and their frequency distributions and subsurface structural closures which might contain petroleum. Fracture trace lengths and frequency (number of fracture traces per unit area) were analyzed by trend surface analysis and length frequency distributions also were compared to a standard Gaussian distribution. Composite rose diagrams of fracture traces were analyzed using a multivariate analysis method which grouped or clustered the rose diagrams and their respective areas on the basis of the behavior of the rays of the rose diagram. Analysis indicates that the lengths of fracture traces are log-normally distributed according to the mapping technique used. Fracture trace frequency appeared higher on the flanks of active structures and lower around passive reef structures. Fracture trace log-mean lengths were shorter over several types of structures, perhaps due to increased fracturing and subsequent erosion. Analysis of rose diagrams using a multivariate technique indicated lithology as the primary control for the lower grouping levels. Groupings at higher levels indicated that areas overlying active structures may be isolated from their neighbors by this technique while passive structures showed no differences which could be isolated.

Podwysocki, M. H.↗

Inflow of halo gas from the direction of the Galactic north pole

A far-UV echelle spectrum has been obtained of the UV-bright star vZ1128 in the globular cluster M3. This cluster lies in a direction 11 deg off the Galactic north pole at a distance of about 10 kpc. Only the usually strong interstellar lines are recognizable in the faint spectrum, and they show absorption at velocities from near +40 km/s to -100 km/s. Since in the direction observed the line-of-sight component of the Milky Way rotation is negligible, the detected velocities demonstrate for this direction the motion of gas from the Milky Way halo toward the disk. Gas returning to the disk in a galactic fountainlike flow may explain the observations.

De Boer, K. S.↗

RAPID: The imaging energetic particle spectrometer on Cluster

The RAPID spectrometer for the Cluster mission, an advanced particle detector for the analysis of suprathermal plasma distributions in the energy range from 20 to 400 keV and from 2 keV/nuc to 1500 keV for electrons and ions, respectively, is presented. Novel detector concepts in combination with pinhole acceptance permit the measurement of angular distributions over a range of 180 deg in polar angle for either species. The detection principle for the ionic component is based on a two dimensional analysis of a particle's velocity and energy. Electrons are identified by the well known energy range relationship. The detection techniques are described and selected areas in geospace are used to highlight the scientific objectives of this investigation.

Wilken, B.↗

The Meteoritic Component in Impact Deposits

An important part of the history of impacts on Earth, and their influence on the terrestrial environment and biotic evolution, is the provenance of the impacting bolides. This will reflect the history of the large-body object flux in the inner solar system. The physical and chemical properties of projectiles, as well as their orbital evolution, has influenced the dynamics and the relative timing of impact events. Possible impact scenarios include random impacts by individual asteroids or comets, or clusters of impacts due to major collisions in the asteroid or Kuiper belts, or large perturbations of the Oort cloud of comets. Over the last several years, a combination of trace element, isotopic, and petrologic data have yielded significant insights into this impact history. The trace element chemistry of sediments, in particular the concentration of siderophiles (e.g., Ir), is a useful tool to detect impacts and provides supporting evidence for suspected impact deposits. However, siderophiles are not especially useful in distinguishing between types of projectiles. Interelement abundances of PGEs can distinguish a chondritic signature, but since most asteroids, and probably all comets are chondritic, these data do little to distinguish between chondritic source materials. Perhaps the most significant chemical argument used to constrain provenance, is that the total amount of Ir in the global Cretaceous-Tertiary (KT) boundary ejecta layer is considerably less than that expected by a low-velocity, 10 km asteroid impact and is most consistent with the impact of a high-velocity, low-Ir comet. Alternatively, much of the Ir may have been buried in the Chicxulub crater and/or ejected to escape velocity.

Kyte, Frank T.↗

Observation of the 60Fe Nucleosynthesis-Clock Isotope in Galactic Cosmic Rays

Iron-60 (60Fe) is a radioactive isotope in cosmic rays that serves as a clock to infer an upper limit on the time between nucleosynthesis and acceleration. We have used the ACE-CRIS instrument to collect 3.55 105 iron nuclei, with energies 195 to 500 megaelectron volts per nucleon, of which we identify 15 60Fe nuclei. The 60Fe56Fe source ratio is (7.5 2.9) 105. The detection of supernova-produced 60Fe in cosmic rays implies that the time required for acceleration and transport to Earth does not greatly exceed the 60Fe half-life of 2.6 million years and that the 60Fe source distance does not greatly exceed the distance cosmic rays can diffuse over this time, 1 kiloparsec. A natural place for 60Fe origin is in nearby clusters of massive stars.

Binns, W. R.↗

Detection of significant antiviral drug effects on COVID-19 with reasonable sample sizes in randomized controlled trials: A modeling study

Development of an effective antiviral drug for Coronavirus Disease 2019 (COVID-19) is a global health priority. Although several candidate drugs have been identified through in vitro and in vivo models, consistent and compelling evidence from clinical studies is limited. The lack of evidence from clinical trials may stem in part from the imperfect design of the trials. We investigated how clinical trials for antivirals need to be designed, especially focusing on the sample size in randomized controlled trials. A modeling study was conducted to help understand the reasons behind inconsistent clinical trial findings and to design better clinical trials. We first analyzed longitudinal viral load data for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) without antiviral treatment by use of a within-host virus dynamics model. The fitted viral load was categorized into 3 different groups by a clustering approach. Comparison of the estimated parameters showed that the 3 distinct groups were characterized by different virus decay rates (p-value < 0.001). The mean decay rates were 1.17 d -1 (95% CI: 1.06 to 1.27 d -1 ), 0.777 d -1 (0.716 to 0.838 d -1 ), and 0.450 d -1 (0.378 to 0.522 d -1 ) for the 3 groups, respectively. Such heterogeneity in virus dynamics could be a confounding variable if it is associated with treatment allocation in compassionate use programs (i.e., observational studies). Subsequently, we mimicked randomized controlled trials of antivirals by simulation. An antiviral effect causing a 95% to 99% reduction in viral replication was added to the model. To be realistic, we assumed that randomization and treatment are initiated with some time lag after symptom onset. Using the duration of virus shedding as an outcome, the sample size to detect a statistically significant mean difference between the treatment and placebo groups (1:1 allocation) was 13,603 and 11,670 (when the antiviral effect was 95% and 99%, respectively) per group if all patients are enrolled regardless of timing of randomization. The sample size was reduced to 584 and 458 (when the antiviral effect was 95% and 99%, respectively) if only patients who are treated within 1 day of symptom onset are enrolled. We confirmed the sample size was similarly reduced when using cumulative viral load in log scale as an outcome. We used a conventional virus dynamics model, which may not fully reflect the detailed mechanisms of viral dynamics of SARS-CoV-2. The model needs to be calibrated in terms of both parameter settings and model structure, which would yield more reliable sample size calculation. In this study, we found that estimated association in observational studies can be biased due to large heterogeneity in viral dynamics among infected individuals, and statistically significant effect in randomized controlled trials may be difficult to be detected due to small sample size. The sample size can be dramatically reduced by recruiting patients immediately after developing symptoms. We believe this is the first study investigated the study design of clinical trials for antiviral treatment using the viral dynamics model.

60 APPLIED LIFE SCIENCES↗

Vibrational signature of hydrated protons confined in MXene interlayers

Here, the hydration structure of protons has been studied for decades in bulk water and protonated clusters due to its importance but has remained elusive in planar confined environments. Two-dimensional (2D) transition metal carbides known as MXenes show extreme capacitance in protic electrolytes, which has attracted attention in the energy storage field. We report here that discrete vibrational modes related to protons intercalated in the 2D slits between Ti 3 C 2 T x MXene layers can be detected using operando infrared spectroscopy. The origin of these modes, not observed for protons in bulk water, is attributed to protons with reduced coordination number in confinement based on Density Functional Theory calculations. This study therefore demonstrates a useful tool for the characterization of chemical species under 2D confinement.

36 MATERIALS SCIENCE↗

The Simons Observatory: science goals and forecasts for the enhanced Large Aperture Telescope

We describe updated scientific goals for the wide-field, millimeter-wave survey that will be produced by the Simons Observatory (SO). Significant upgrades to the 6-meter SO Large Aperture Telescope (LAT) are expected to be complete by 2028, and will include a doubled mapping speed with 30,000 new detectors and an automated data reduction pipeline. In addition, a new photovoltaic array will supply most of the observatory's power. The LAT survey will cover about 60% of the sky at a regular observing cadence, with five times the angular resolution and ten times the map depth of the Planck satellite. The science goals are to: (1) determine the physical conditions in the early universe and constrain the existence of new light particles; (2) measure the integrated distribution of mass, electron pressure, and electron momentum in the late-time universe, and, in combination with optical surveys, determine the neutrino mass and the effects of dark energy via tomographic measurements of the growth of structure at redshifts z ≲ 3; (3) measure the distribution of electron density and pressure around galaxy groups and clusters, and calibrate the effects of energy input from galaxy formation on the surrounding environment; (4) produce a sample of more than 30,000 galaxy clusters, and more than 100,000 extragalactic millimeter sources, including regularly sampled AGN light-curves, to study these sources and their emission physics; (5) measure the polarized emission from magnetically aligned dust grains in our Galaxy, to study the properties of dust and the role of magnetic fields in star formation; (6) constrain asteroid regoliths, search for Trans-Neptunian Objects, and either detect or eliminate large portions of the phase space in the search for Planet 9; and (7) provide a powerful new window into the transient universe on time scales of minutes to years, concurrent with observations from the Vera C. Rubin Observatory of overlapping sky.

79 ASTRONOMY AND ASTROPHYSICS↗

Early Results from GLASS-JWST. II. NIRCam Extragalactic Imaging and Photometric Catalog

We present the reduced images and multiwavelength catalog of the first JWST NIRCam extragalactic observations from the GLASS Early Release Science Program, obtained as coordinated parallels of the NIRISS observations of the Abell 2744 cluster. Images in seven bands (F090W, F115W, F150W, F200W, F277W, F356W, and F444W) have been reduced using an augmented version of the official JWST pipeline; we discuss the procedures adopted to remove or mitigate defects in the raw images. We obtain a multiband catalog by means of forced aperture photometry on point-spread function (PSF)-matched images at the position of F444W-detected sources. The catalog is intended to enable early scientific investigations, and it is optimized for faint galaxies; it contains 6368 sources, with limiting magnitude 29.7 at 5 σ in F444W. We release both images and catalog in order to allow the community to become familiar with the JWST NIRCam data and evaluate their merit and limitations given the current level of knowledge of the instrument.

79 ASTRONOMY AND ASTROPHYSICS↗

Atmospheric Effects on Remote Sensing of the Earth's Surface

The main causes and magnitude of the atmospheric effects on remote sensing of the Earth's surface are determined. Theoretical study as well as measurements are included. The knowledge gained from this study will be used to develop atmospheric correction algorithms and to test them with satellite data. In a theoretical investigation of the relative effects of the aerosol optical thickness, absorption, and size distribution on remote sensing, it was found that aerosol absorption has a significant effect on satellite measurements of surface reflectivity. The absorption effect is stronger for high than for low surface reflectances. The aerosol optical thickness is dominant for small surface reflectances. The accuracy of clustering algorithms depends on both parameters. The vegetation index, however, is affected by the optical thickness but only weakly affected by the absorption. A laboratory simulation of the atmospheric effect on the radiance of sunlight scattered from the Earth's surface-atmosphere system was performed. This experiment verified the existence of the adjacency effect (the effect of a bright field on the radiance detected above a dark field) and was used to test 3-D radiative transfer models. In a theoretical study it was found that atmospheric scattering resulting from the adjacency effect reduces the separability between surface classes.

Fraser, R. E.↗

A Very Large Array search for emission from HI associated with nearby Lyman alpha absorbers

We present a sensitive Very Large Array (VLA) search for H I emission from the vicinity of the Lyman alpha clouds in the Virgo Cluster, which were recently discovered with Hubble Space Telescope (HST) in absorption toward the nearest quasar 3C273. We searched an area of 40 by 40 arcmin centered on 3C273, covering a velocity range from 840 to 1840 km/s. The bandpass was self-calibrated on 3C273 leading to a spectral dynamic range of better than 10(exp 5) to 1. No H I was detected. The rms noise in the final images corresponds to a 3 sigma column density sensitivity of 2.8 x 10(exp 19) sq cm on scales of a few kpc. Small H I clouds could have been detected down to a few times 10(exp 6) solar mass. Our failure to detect H I emission at the higher column densities sets a lower limit to the radius of the Lyman alpha clouds of 3.9 kpc, assuming a spherical geometry.

Van Gorkom, J. H.↗