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Fixture based on T-connector enables mass-spectrometric analysis of volatile contents of cylindrical containers without exposing contents to ambient conditions. Used to sample volatile contents of pressurized containers, contents of such enclosed processing systems as gas-phase reactors, gases in automotive emission systems, and gas in hostile environments.
The BOREAS TE-5 team collected several data sets to investigate the vegetation-atmosphere CO2 and H2O exchange processes. These data were collected to provide detailed information within the canopy during times when TE-05 sampled canopy CO2 for carbon and oxygen isotope analysis. These measurements were made in both the NSA and SSA at the OJP, OBS, UBS, and OA sites from 25-May1994 to 08-Sep1994. CO2 profile data were not collected at SSA-OA during the first IFC. The data are available in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Activity Archive Center (DAAC).
The recent successful rendezvous of the Stardust spacecraft with comet Wild-2 will be followed by its return of cometary dust to Earth in January 2006. Results from two separate dust impact detectors suggest that the spacecraft collected approximately the nominal fluence of at least 1,000 particles larger than 15 micrometers in size. While constituting only about one microgram total, these samples will be sufficient to answer many outstanding questions about the nature of cometary materials. More than two decades of laboratory studies of stratospherically collected interplanetary dust particles (IDPs) of similar size have established the necessary microparticle handling and analytical techniques necessary to study them. It is likely that some IDPs are in fact derived from comets, although complex orbital histories of individual particles have made these assignments difficult to prove. Analysis of bona fide cometary samples will be essential for answering some fundamental outstanding questions in cosmochemistry, such as (1) the proportion of interstellar and processed materials that comprise comets and (2) whether the Solar System had a O-16-rich reservoir. Abundant silicate stardust grains have recently been discovered in anhydrous IDPs, in far greater abundances (200 5,500 ppm) than those in meteorites (25 ppm). Insight into the more subtle O isotopic variations among chondrites and refractory phases will require significantly higher precision isotopic measurements on micrometer-sized samples than are currently available.
A Microscope Imaging System (CMIS) with intelligent controls is disclosed that provides techniques for scanning, identifying, detecting and tracking microscopic changes in selected characteristics or features of various surfaces including, but not limited to, cells, spheres, and manufactured products subject to difficult-to-see imperfections. The practice of the present invention provides applications that include colloidal hard spheres experiments, biological cell detection for patch clamping, cell movement and tracking, as well as defect identification in products, such as semiconductor devices, where surface damage can be significant, but difficult to detect. The CMIS system is a machine vision system, which combines intelligent image processing with remote control capabilities and provides the ability to auto-focus on a microscope sample, automatically scan an image, and perform machine vision analysis on multiple samples simultaneously.
The Mars Science Laboratory (MSL) Curiosity Rover carries a suite of instruments, one of which is the Sample Analysis at Mars (SAM) experiment. SAM is devoted to the in situ molecular analysis of gases evolving from solid samples collected by Curiosity on Mars surface/sub-surface. Among its three analytical devices, SAM has a gaschromatograph coupled to a quadrupole mass spectrometer (GC-QMS). The GC-QMS is devoted to the separation and identification of organic and inorganic material. Before proceeding to the GC-QMS analysis, the solid sample collected by Curiosity is subjected to a thermal treatment thanks to the pyrolysis oven to release the volatiles into the gas processing system. Depending on the sample, a derivatization method by wet chemistry: MTBSTFA of TMAH can also be applied to analyze the most refractory compounds. The GC is able to separate the organic molecules which are then detected and identified by the QMS (Figure 1). For the second time after the Viking landers in 1976, SAM detected chlorinated organic compounds with the pyrolysis GC-QMS experiment. The detection of perchlorates salts (ClO4-) in soil at the Phoenix Landing site suggests that the chlorohydrocarbons detected could come from the reaction of organics with oxychlorines. Indeed, laboratory pyrolysis experiments have demonstrated that oxychlorines decomposed into molecular oxygen and volatile chlorine (HCl and/or Cl2) when heated which then react with the organic matter in the solid samples by oxidation and/or chlorination processes.
Lunar apatites contain 100s-1000s ppm sulfur [1-3]. This was initially puzzling because lunar basalts are thought to form, including at the time of apatite crystallization, in low oxygen fugacity (fO2) conditions where sulfur exists in its reduced form (S2-), a substitution not previously observed in natural apatite. It has been recently shown, using S-XANES measurements of the oxidation state of sulfur in apatites and proximal mesostasis in the lunar basalts 12039 and 10044, that sulfur is indeed present as S2- in both the mesostasis glass and apatite when measurements were performed far from cracks or pits in the thin section [4]. This observation is consistent with other mineralogical indications of the low fO2 during formation of these samples (~IW-1) such as the presence of Fe-metal, ulvöspinel, ilmenite, fayalite, and silica in the thin sections. In the same study, in addition to clear spectral evidence for the dominance of S2-, analyses of apatite grains in both samples that occurred near cracks or pits in the thin section sometimes revealed non-negligible spectral evidence (e.g., S6+/ΣS > 0.03; [4]) for the presence of S6+. Because S6+ was not observed in the mesostasis glass near the apatite grains measured, or in any phase far from cracks or pits in the studied thin sections, this S6+ was interpreted as either primary S2- in the sulfide altered to S6+ in the thin section, or S6+ of secondary origin, deposited in the fractures of the samples [4, 5]. Whether this is of lunar or terrestrial origin is unknown but has implications for lunar petrogenesis if lunar [e.g., 5], or sample handling and curation if terrestrial. To test between lunar and terrestrial origins for observed S6+ in Apollo-era thin sections, we will measure the oxidation state of sulfur in apatite and associated phases in a specially frozen sample from a boulder sampled at Station 1A during the Apollo 17 mission as part of the NASA Apollo Next Generation Sample Analysis (ANGSA) program. Here, we present “control” measurements of samples 71035 and 71055, using Apollo era thin sections of aliquots of these rocks that were processed upon return to Earth and since stored under N2 atmospheres at room temperature. These will be compared to measurements using newly made thin sections of aliquots of the same rocks (71035 and 71055). In addition, 71036, which has been in cold storage (-20℃) since the return of the Apollo 17 mission to Earth, has been recently made available through the ANGSA program. With 71036 we can test the effect of storage temperature on potential oxidation of S2- to S6+ in the relatively oxidizing and warm conditions of Earth’s surface.
The presence of water ice in permanently shadowed regions on the lunar surface may enable a sustained human presence on the Moon with minimal need for consumables. The first step toward utilizing lunar water ice to advance human space exploration will be to determine the abundance, accessibility, and distribution of this valuable resource. This paper will describe the most recent test results from the Light Water Analysis and Volatile Extraction (Light WAVE) system that was designed to capture icy regolith samples acquired from a drill. Regolith samples are then weighed, sealed, and heated to release volatiles. Volatiles are captured in a volume with a known temperature and the ideal gas law is used to determine the total quantity of volatiles in the volume. The composition of the volatile mixture is determined using a mass spectrometer so that each volatile can be quantified. By quantifying the amount of water extracted from the regolith sample, and acquiring the mass of the sample, water concentration by mass can be determined. The goal of recent testing was to determine the accuracy of water quantification using a combination of ideal gas law and mass spectrometer analysis. The Light WAVE system maybe applied to future water ice investigation missions without an inherent limit to the number of samples that can be processed, and the system may also enable lunar water sample return.
A hyperspectral stimulated emission depletion ("STED") microscope system for high-resolution imaging of samples labeled with multiple fluorophores (e.g., two to ten fluorophores). The hyperspectral STED microscope includes a light source, optical systems configured for generating an excitation light beam and a depletion light beam, optical systems configured for focusing the excitation and depletion light beams on a sample, and systems for collecting and processing data generated by interaction of the excitation and depletion light beams with the sample. Hyperspectral STED data may be analyzed using multivariate curve resolution analysis techniques to deconvolute emission from the multiple fluorophores. The hyperspectral STED microscope described herein can be used for multi-color, subdiffraction imaging of samples (e.g., materials and biological materials) and for analyzing a tissue by Forster Resonance Energy Transfer ("FRET").
The major objectives of this work are: (1) obtain quantitative evidence for the suppression of heterogeneous nucleation/crystallization in containerless melts in micro-g; (2) study melt homogenization in the absence of gravity driven convection; (3) develop the procedures for preparing precursor samples suitable for flight experiments; (4) perform comparative property analysis of glasses melted on Earth and in micro-g; (5) determine the feasibility of preparing glass shells in micro-g for use as laser fusion targets; and (6) assess the operational performance of the single axis acoustic levitator/furnace apparatus for processing multicomponent, glass forming melts in micro-g. Ways of obtaining these goals are discussed.
Accurate, high throughput, and unbiased analysis of plutonium oxide particles is needed for analysis of the phenomenology associated with process parameters in their synthesis. Compared to qualitative and taxonomic descriptors, quantitative descriptors of particle morphology through scanning electron microscopy (SEM) have shown success in analyzing process parameters of uranium oxides. Among other candidates, a neural network called a Vector Quantizing Variational Autoencoder (VQ-VAE) has shown the ability to quantitatively describe particle morphology to attain >85% accuracy in identifying uranium oxide processing routes. We utilize a VQ-VAE to quantitatively describe plutonium dioxide (PuO 2 ) particles created in a designed experiment and investigate their phenomenology and prediction of their process parameters. PuO 2 was calcined from Pu(III) oxalates that were precipitated under varying synthetic conditions that related to concentrations, temperature, addition and digestion times, precipitant feed, and strike order; the surface morphology of the resulting PuO 2 powders were analyzed by SEM. A pipeline was developed to extract and quantify useful image representations for individual particles with the VQ-VAE, then further reduce the dimensionality of the feature space using a bottlenecking neural network fit to perform multiple classification tasks simultaneously. The reduced feature space could predict process parameters with greater than 80% accuracies for some parameters with a single particle. They also showed utility for grouping particles with similar surface morphology characteristics together. Both the clustering and classification results reveal valuable information regarding which chemical process parameters chiefly influence the PuO 2 particle morphologies: strike order and oxalic acid feedstock. Doing the same analysis with multiple particles was shown to improve the classification accuracy on each process parameter over the use of a single particle, with statistically significant results generally seen with as few as four particles in a sample.
The current gold standard for unambiguous molecular identification in metabolomics analysis is comparing two or more orthogonal properties from the analysis of authentic reference materials (standards) to experimental data acquired in the same laboratory with the same analytical methods. This represents a significant limitation for comprehensive chemical identification of small molecules in complex samples. The process is time-consuming and costly, and the majority of molecules are not yet represented by standards. Thus, there is a need to assemble evidence for the presence of small molecules in complex samples through the use of libraries containing calculated chemical properties. To address this need, we developed a Multi-Attribute Matching Engine (MAME) and a library derived in-part from our in silico Chemical Library Engine (ISiCLE). Here, we describe an initial evaluation of these methods in a blinded analysis of synthetic chemical mixtures as part of the U.S. Environmental Protection Agency’s (EPA) Non-Targeted Analysis Collaborative Trial (ENTACT, Phase 1). For molecules in all mixtures, the initial blinded false negative rate (FNR), false discovery rate (FDR), and accuracy were 57%, 77%, and 91%, respectively. For high evidence scores, the FDR was 35%. After unblinding of the sample compositions, we optimized the scoring parameters to better exploit the available evidence, and increased the accuracy for molecules suspected as present. The final FNR, FDR, and accuracy were 67%, 53%, and 96%, respectively. For high evidence scores, the FDR was 10%. This study demonstrates that multi-attribute matching methods in conjunction with in silico libraries may one day enable reduced reliance on experimentally-derived libraries for building evidence for the presence of molecules in complex samples.
Beginning in 2004 personnel at MSFC began serious efforts to develop a new generation of lunar simulants. The first two products were a replication of the previous JSC-1 simulant under a contract to Orbitec and a major workshop in 2005 on future simulant development. Beginning in 2006 the project refocused its efforts and approached simulant development in a new and more comprehensive manner, examining new approaches in simulant development and ways to more accurately compare simulants to actual lunar materials. This led to a multi-year effort with five major tasks running in parallel. The five tasks are Requirements, Lunar Analysis, Process Development, Feed Stocks, and Standards. Major progress has been made in all five areas. A substantial draft of a formal requirements document now exists and has been largely stable since 2007. It does evolve as specific details of the standards and Lunar Analysis efforts proceed. Lunar Analysis has turned out to be vastly more difficult than anticipated. After great effort to mine existing published and gray literature, the team has realized the necessity of making new measurements of the Apollo samples, an effort that is currently in progress. Process development is substantially ahead of expectations in 2006. It is now practical to synthesize glasses of appropriate composition and purity. It is also possible to make agglutinate particles in significant quantities. A series of minerals commonly found on the Moon has been synthesized. Separation of mineral constituents from starting rock material is also proceeding. Customized grinding and mixing processes have been developed and tested are now being documented. Identification and development of appropriate feedstocks has been both easier and more difficult than anticipated. The Stillwater Mining Company, operating in the Stillwater layered mafic intrusive complex of Montana, has been an amazing resource for the project, but finding adequate sources for some of the components remains a difficult problem. For example the ratio of clino- to ortho-pyroxenes in the Stillwater is not an exact match for lunar materials. One of the sources being examined as an alternative pyroxene source is the Bushveld Complex in South Africa. Standards have been a major success for the project. The Figure of Merit algorithms have been created, tested, and are being considered for an ISO standard. Agreement has been reached in the community about how to make many of the critical measurements. There remains much work to do: (1) driving down the cost of simulants remains a major obstacle; (2) documentation and cost data analysis have not kept up with progress; (3) educating users in the complexity of the lunar regolith and the use of simulants remains a major task. In summary the project has made enormous progress and is successfully placing simulant development and use on a rigorous, scientifically defensible, engineering basis.
A search is presented for the decay of the 125 GeV Higgs boson (H) to a pair of new light pseudoscalar bosons (a), followed by the prompt decay of each a boson to a bottom quark-antiquark pair, $ \textrm{H}\to \textrm{aa}\to \textrm{b}\overline{\textrm{b}}\textrm{b}\overline{\textrm{b}} $. The analysis is performed using a data sample of proton-proton collisions collected with the CMS detector at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 138 fb$^{−1}$. To reduce the background from standard model processes, the search requires the Higgs boson to be produced in association with a leptonically decaying W or Z boson. The analysis probes the production of new light bosons in a 15 < m$_{a}$ < 60 GeV mass range. Assuming the standard model predictions for the Higgs boson production cross sections for pp → WH and ZH, model independent upper limits at 95% confidence level are derived for the branching fraction $ \mathcal{B}\left(\textrm{H}\to \textrm{aa}\to \textrm{b}\overline{\textrm{b}}\textrm{b}\overline{\textrm{b}}\right) $. The combined WH and ZH observed upper limit on the branching fraction ranges from 1.10 for m$_{a}$ = 20 GeV to 0.36 for m$_{a}$ = 60 GeV, complementing other measurements in the μμττ, ττττ and bbℓℓ (ℓ = μ, τ) channels.[graphic not available: see fulltext]
As global temperatures rise, large amounts of carbon sequestered in permafrost are becoming available for microbial degradation. However, accurate prediction of carbon gas emissions produced from thawing permafrost is limited by our understanding of the resident microbial communities and their associated carbon metabolism. Here, metagenomic sequencing of 214 samples from intact, thawing and thawed sites collected over three years enabled the recovery of 1,529 metagenome-assembled genomes (MAGs), including many from phyla with poor genomic representation. These genomes were shown to broadly reflect the diversity of this complex ecosystem with genus-level representatives recovered for >60% of the community, constituting a two orders of magnitude increase in the number of genomes available for understanding carbon processing in this environment. Metabolic reconstruction, supported by metatranscriptomic and metaproteomic data, revealed key populations involved in organic matter degradation, including bacteria encoding a pathway for xylose degradation only previously identified in fungi. Combined analysis of the microbial communities and geochemical data highlighted lineages correlated with the production of greenhouse gases and suggest novel syntrophic relationships. Our findings link changing biogeochemistry to specific microbial lineages involved in each stage of carbon processing, providing key information for predicting the impact of climate change on these systems.
The purpose of this experiment was to evaluate the host response to wild-type West Nile virus (WNV-NY99 382) and mutant WNV-E218A (WNV-NY99 382 E218A 2 nt) virus infection. Sample data was obtained from mouse cortex tissue for mRNA, miRNA, proteomics, lipidomics, and metabolomics expression analysis. Tissues from this experiment were matched to tissues from GSE77192 (WCB001), using 1/4 of the cortex and 1/2 of cerebellum from the same mice. Secondary host-associated viral dataset downloads contain one or more statistically processed (normalization data transformation) quantitative dataset collections resulting in qualitative expression analyses of primary host-pathogen experimental study designs. Leveraging unique high-resolution Omics capabilities for proteomics, metabolomics, lipidomics, and transcriptomics dataset downloads each have a direct relationship to a primary sample submission corresponding to a specific West Nile virus infection.
Abstract In this paper, we propose a control Lyapunov‐barrier function‐based model predictive control method utilizing a feed‐forward neural network specified control barrier function (CBF) and a recurrent neural network (RNN) predictive model to stabilize nonlinear processes with input constraints, and to guarantee that safety requirements are met for all times. The nonlinear system is first modeled using RNN techniques, and a CBF is characterized by constructing a feed‐forward neural network (FNN) model with unique structures and properties. The FNN model for the CBF is trained based on data samples collected from safe and unsafe operating regions, and the resulting FNN model is verified to demonstrate that the safety properties of the CBF are satisfied. Given sufficiently small bounded modeling errors for both the FNN and the RNN models, the proposed control system is able to guarantee closed‐loop stability while preventing the closed‐loop states from entering unsafe regions in state‐space under sample‐and‐hold control action implementation. We provide the theoretical analysis for bounded unsafe sets in state‐space, and demonstrate the effectiveness of the proposed control strategy using a nonlinear chemical process example with a bounded unsafe region.
Wetland loss in Louisiana has been accelerating due primarily to anthropogenic and nature processes, and is being advocated as a problem with national importance. Accurate measurement or modeling of wetland-wide water level changes, its varying extent, its storage and discharge changes resulting in part from sediment loads, erosion and subsidence are fundamental to assessment of hurricane-induced flood hazards and wetland ecology. Here, we use innovative method to integrate interferometric SAR (InSAR) and satellite radar altimetry for measuring absolute or geocentric water level changes and applied the methodology to remote areas of swamp forest in coastal Louisiana. Coherence analysis of InSAR pairs suggested that the HH polarization is preferred for this type of observation, and polarimetric analysis can help to identi:fy double-bonnce backscattering areas in the wetland. Envisat radar altimeter-measured 18- Hz (along-track sampling of 417 m) water level data processed with regional stackfile method have been used to provide vertical references for water bodies separated by levees. The high-resolution (approx.40 m) relative water changes measured from ALOS PALSAR L-band and Radarsat-l C-band InSAR are then integrated with Envisat radar altimetry to obtain absolute water level. The resulting water level time series were validated with in situ gauge observations within the swamp forest. Furthermore, we compare our water elevation changes with 2D flood modeling from LISFLOOD hydrodynamic model. Our study demonstrates that this new technique allows retrospective reconstruction and concurrent monitoring of water conditions and flow dynamics in wetlands, especially those lacking gauge networks.
We report that wearable sensor technologies are essential to the realization of personalized medicine through continuously monitoring an individual’s state of health. Sampling human sweat, which is rich in physiological information13, could enable non-invasive monitoring. Previously reported sweat-based and other noninvasive biosensors either can only monitor a single analyte at a time or lack on-site signal processing circuitry and sensor calibration mechanisms for accurate analysis of the physiological state14–18. Given the complexity of sweat secretion, simultaneous and multiplexed screening of target biomarkers is critical and requires full system integration to ensure the accuracy of measurements. Here we present a mechanically flexible and fully integrated (that is, no external analysis is needed) sensor array for multiplexed in situ perspiration analysis, which simultaneously and selectively measures sweat metabolites (such as glucose and lactate) and electrolytes (such as sodium and potassium ions), as well as the skin temperature (to calibrate the response of the sensors). Lastly, our work bridges the technological gap between signal transduction, conditioning (amplification and filtering), processing and wireless transmission in wearable biosensors by merging plasticbased sensors that interface with the skin with silicon integrated circuits consolidated on a flexible circuit board for complex signal processing.