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Operando identification of the point of [Mn 2 ]O 4 spinel formation during γ-MnO 2 discharge within batteries
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Muon reconstruction and identification with the Run II D0 detector
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A feature point identification method for positron emission particle tracking with multiple tracers
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Identification of internal radioactive contaminants in elpasolites (CLYC, CLLB, CLLBC) and other inorganic scintillators
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Performance of modular ring imaging Cherenkov detector for particle identification
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Electron Microscopic Evaluation and Fission Product Identification of Irradiated TRISO Coated Particles from the AGR-1 Experiment: A Preliminary Review
Post-irradiation examination of coated particle fuel from the AGR-1 experiment is in progress at Idaho National Laboratory and Oak Ridge National Laboratory. In this paper a brief summary of results from characterization of microstructures in the coating layers of selected irradiated fuel particles with burnup of 11.3% and 19.3% FIMA will be given. The main objectives of the characterization were to study irradiation effects, fuel kernel porosity, layer debonding, layer degradation or corrosion, fission-product precipitation, grain sizes, and transport of fission products from the kernels across the TRISO layers. Characterization techniques such as scanning electron microscopy, transmission electron microscopy, energy dispersive spectroscopy, and wavelength dispersive spectroscopy were used. A new approach to microscopic quantification of fission-product precipitates is also briefly demonstrated. Microstructural characterization focused on fission-product precipitates in the SiC-IPyC interface, the SiC layer and the fuel-buffer interlayer. The results provide significant new insights into mechanisms of fission-product transport. Although Pd-rich precipitates were identified at the SiC-IPyC interlayer, no significant SiC-layer thinning was observed for the particles investigated. Characterization of these precipitates highlighted the difficulty of measuring low concentrations of Ag in precipitates with significantly higher concentrations of Pd and U. Different approaches to resolving this problem are discussed. An initial hypothesis is provided to explain fission-product precipitate compositions and locations. No SiC phase transformations were observed and no debonding of the SiC-IPyC interlayer as a result of irradiation was observed for the samples investigated. Lessons learned from the post-irradiation examination are described and future actions are recommended.
Identification of a millisecond isomeric state in 129Cd81via the detection of internal conversion and Compton electrons
The decay of an isomeric state in the neutron-rich nucleus 129Cd has been observed via the detection of internal conversion and Compton electrons providing first experimental information on excited states in this nucleus. The isomer was populated in the projectile fission of a 238U beam at the Radioactive Isotope Beam Factory at RIKEN. From the measured yields of γ-rays and internal conversion electrons, a multipolarity of E 3 was tentatively assigned to the isomeric transition. A half-life of T1/2=3.6(2) msT1/2=3.6(2) ms was determined for the new state which was assigned a spin of (21/2+)(21/2+), based on a comparison to shell model calculations performed using state-of-the-art realistic effective interactions.
Identification of candidate genes in Arabidopsis and Populus cell wall biosynthesis using text-mining, co-expression network analysis and comparative genomics
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Identification of combustion mode under MILD conditions using Chemical Explosive Mode Analysis
Direct Numerical Simulations (DNS) data of Moderate or Intense Low-oxygen Dilution (MILD) combustion are analysed in this paper to identify the contributions of the autoignition and flame modes. This is performed using an extended Chemical Explosive Mode Analysis (CEMA) which accounts for diffusion effects allowing it to discriminate between deflagration and autoignition. This analysis indicates that in premixed MILD combustion conditions, the main combustion mode is ignition for all dilution and turbulence levels and for the two reactant temperature conditions considered. In non-premixed conditions, the preponderance of the ignition mode was observed to depend on the axial location and mixture fraction stratification. With a large mixture fraction lengthscale, ignition is more preponderant in the early part of the domain while the deflagrative mode increases further downstream. On the other hand, when the mixture fraction lengthscale is small, sequential autoignition is observed. Finally, the various combustion modes are observed to correlate strongly with mixture fraction where lean mixtures are more likely to autoignite while stoichiometric and rich mixtures are more likely to react as deflagrative structures.
A Bayesian Framework for Milling Stability Prediction and Reverse Parameter Identification
This paper describes a physics-guided Bayesian framework for identifying the milling stability boundary and system parameters through iterative testing. Prior uncertainties for the parameters are identified through physical simulation and literature reviews, without physical testing of the actual milling system. Those uncertainties are then propagated to the stability map using a physics-based stability model, which is used to suggest a test point. The uncertainties are updated based on the new information acquired from the cutting test to form a new probability distribution, called the posterior. Finally, the posterior are compared to measured values for the stability boundary and system parameters to evaluate the approach. Based on experimental observations, the advantages and disadvantages of using a physics-guided model are discussed.
A posteriori clear-sky identification methods in solar irradiance time series: Review and preliminary validation using sky imagers
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Identification of Radiolytically-Active Thermal Transition Phases in Boehmite
Abstract not provided
Application of multiplexed ion mobility spectrometry towards the identification of host protein signatures of treatment effect in pulmonary tuberculosis
Rationale: The monitoring of TB treatments in clinical practice and clinical trials relies on traditional sputum-based culture status indicators at specific time points. Accurate, predictive, blood-based protein markers would provide a simpler and more informative view of patient health and response to treatment. Objective: We utilized sensitive, high throughput multiplexed ion mobility-mass spectrometry (IM-MS) to characterize the serum proteome of TB patients at the start of and at 8 weeks of rifamycin-based treatment. We sought to identify treatment specific signatures within patients as well as correlate the proteome signatures to various clinical markers of treatment efficacy. Methods: Serum samples were collected from 289 subjects enrolled in CDC TB Trials Consortium Study 29 at time of enrollment and at the end of the intensive phase (after 40 doses of TB treatment). Serum proteins were immunoafinity-depleted of high abundant components, digested to peptides and analyzed for data acquisition utilizing a unique liquid chromatography IM-MS platform (LC-IM-MS). Linear mixed models were utilized to identify serum protein changes in the host response to antibiotic treatment as well as correlations with culture status end points. Results: A total of 10,137 peptides corresponding to 872 proteins were identified, quantified, and used for statistical analysis across the longitudinal patient cohort. In response to TB treatment, 244 proteins were sig- ni?cantly altered. Pathway/network comparisons helped visualize the interconnected proteins, identifying up regulated (lipid transport, coagulation cascade, endopeptidase activity) and down regulated (acute phase) processes and pathways in addition to other cross regulated networks (inflammation, cell adhesion, extracellular matrix). Detection of possible lung injury serum proteins such as HPSE, significantly downregulated upon treatment. Analyses of microbiologic data over time identified a core set of serum proteins (TTHY, AFAM, CRP, RET4, SAA1, PGRP2) which change in response to treatment and also strongly correlate with culture status. A similar set of proteins at baseline were found to be predictive of week 6 and 8 culture status. Conclusion: A comprehensive host serum protein dataset reflective of TB treatment effect is defined. A repeating set of serum proteins (TTHY, AFAM, CRP, RET4, SAA1, PGRP2, among others) were found to change significantly in response to treatment, to strongly correlate with culture status, and at baseline to be predictive of future culture conversion. If validated in cohorts with long term follow-up to capture failure and relapse of TB, these protein markers could be developed for monitoring of treatment in clinical trials and in patient care.
Identification of the heparin binding site on adeno-associated virus serotype 3B (AAV-3B)
Adeno-associated virus is a promising vector for gene therapy. In the current study, the binding site on AAV serotype 3B for the heparan sulfate proteoglycan (HSPG) receptor has been characterized. X-ray diffraction identified a disaccharide binding site at the most positively charged region on the virus surface. The contributions of basic amino acids at this and other sites were characterized using site-directed mutagenesis. Both heparin and cell binding are correlated to positive charge at the disaccharide binding site, and transduction is significantly decreased in AAV-3B vectors mutated at this site to reduce heparin binding. While the receptor attachment sites of AAV-3B and AAV-2 are both in the general vicinity of the viral spikes, the exact amino acids that participate in electrostatic interactions are distinct. Diversity in the mechanisms of cell attachment by AAV serotypes will be an important consideration for the rational design of improved gene therapy vectors.
Systematic identification and elimination of flux bottlenecks in the aldehyde production pathway of Synechococcus elongatus PCC 7942
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Identification of novel metabolic engineering targets for S-adenosyl-L-methionine production in Saccharomyces cerevisiae via genome-scale engineering
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