Complete volumetric decomposition of individual trabecular plates and rods and its morphological correlations with anisotropic elastic moduli in human trabecular bone.

PubMed

Liu, X Sherry; Sajda, Paul; Saha, Punam K; Wehrli, Felix W; Bevill, Grant; Keaveny, Tony M; Guo, X Edward

2008-02-01

Trabecular plates and rods are important microarchitectural features in determining mechanical properties of trabecular bone. A complete volumetric decomposition of individual trabecular plates and rods was used to assess the orientation and morphology of 71 human trabecular bone samples. The ITS-based morphological analyses better characterize microarchitecture and help predict anisotropic mechanical properties of trabecular bone. Standard morphological analyses of trabecular architecture lack explicit segmentations of individual trabecular plates and rods. In this study, a complete volumetric decomposition technique was developed to segment trabecular bone microstructure into individual plates and rods. Contributions of trabecular type-associated morphological parameters to the anisotropic elastic moduli of trabecular bone were studied. Seventy-one human trabecular bone samples from the femoral neck (FN), tibia, and vertebral body (VB) were imaged using muCT or serial milling. Complete volumetric decomposition was applied to segment trabecular bone microstructure into individual plates and rods. The orientation of each individual trabecula was determined, and the axial bone volume fractions (aBV/TV), axially aligned bone volume fraction along each orthotropic axis, were correlated with the elastic moduli. The microstructural type-associated morphological parameters were derived and compared with standard morphological parameters. Their contributions to the anisotropic elastic moduli, calculated by finite element analysis (FEA), were evaluated and compared. The distribution of trabecular orientation suggested that longitudinal plates and transverse rods dominate at all three anatomic sites. aBV/TV along each axis, in general, showed a better correlation with the axial elastic modulus (r(2) = 0.95 approximately 0.99) compared with BV/TV (r(2) = 0.93 approximately 0.94). The plate-associated morphological parameters generally showed higher correlations with the corresponding standard morphological parameters than the rod-associated parameters. Multiple linear regression models of six elastic moduli with individual trabeculae segmentation (ITS)-based morphological parameters (adjusted r(2) = 0.95 approximately 0.98) performed equally well as those with standard morphological parameters (adjusted r(2) = 0.94 approximately 0.97) but revealed specific contributions from individual trabecular plates or rods. The ITS-based morphological analyses provide a better characterization of the morphology and trabecular orientation of trabecular bone. The axial loading of trabecular bone is mainly sustained by the axially aligned trabecular bone volume. Results suggest that trabecular plates dominate the overall elastic properties of trabecular bone.

Projection of landfill stabilization period by time series analysis of leachate quality and transformation trends of VOCs.

PubMed

Sizirici, Banu; Tansel, Berrin

2010-01-01

The purpose of this study was to evaluate suitability of using the time series analysis for selected leachate quantity and quality parameters to forecast the duration of post closure period of a closed landfill. Selected leachate quality parameters (i.e., sodium, chloride, iron, bicarbonate, total dissolved solids (TDS), and ammonium as N) and volatile organic compounds (VOCs) (i.e., vinyl chloride, 1,4-dichlorobenzene, chlorobenzene, benzene, toluene, ethyl benzene, xylenes, total BTEX) were analyzed by the time series multiplicative decomposition model to estimate the projected levels of the parameters. These parameters were selected based on their detection levels and consistency of detection in leachate samples. In addition, VOCs detected in leachate and their chemical transformations were considered in view of the decomposition stage of the landfill. Projected leachate quality trends were analyzed and compared with the maximum contaminant level (MCL) for the respective parameters. Conditions that lead to specific trends (i.e., increasing, decreasing, or steady) and interactions of leachate quality parameters were evaluated. Decreasing trends were projected for leachate quantity, concentrations of sodium, chloride, TDS, ammonia as N, vinyl chloride, 1,4-dichlorobenzene, benzene, toluene, ethyl benzene, xylenes, and total BTEX. Increasing trends were projected for concentrations of iron, bicarbonate, and chlorobenzene. Anaerobic conditions in landfill provide favorable conditions for corrosion of iron resulting in higher concentrations over time. Bicarbonate formation as a byproduct of bacterial respiration during waste decomposition and the lime rock cap system of the landfill contribute to the increasing levels of bicarbonate in leachate. Chlorobenzene is produced during anaerobic biodegradation of 1,4-dichlorobenzene, hence, the increasing trend of chlorobenzene may be due to the declining trend of 1,4-dichlorobenzene. The time series multiplicative decomposition model in general provides an adequate forecast for future planning purposes for the parameters monitored in leachate. The model projections for 1,4-dichlorobenzene were relatively less accurate in comparison to the projections for vinyl chloride and chlorobenzene. Based on the trends observed, future monitoring needs for the selected leachate parameters were identified.

An optimized ensemble local mean decomposition method for fault detection of mechanical components

NASA Astrophysics Data System (ADS)

Zhang, Chao; Li, Zhixiong; Hu, Chao; Chen, Shuai; Wang, Jianguo; Zhang, Xiaogang

2017-03-01

Mechanical transmission systems have been widely adopted in most of industrial applications, and issues related to the maintenance of these systems have attracted considerable attention in the past few decades. The recently developed ensemble local mean decomposition (ELMD) method shows satisfactory performance in fault detection of mechanical components for preventing catastrophic failures and reducing maintenance costs. However, the performance of ELMD often heavily depends on proper selection of its model parameters. To this end, this paper proposes an optimized ensemble local mean decomposition (OELMD) method to determinate an optimum set of ELMD parameters for vibration signal analysis. In OELMD, an error index termed the relative root-mean-square error (Relative RMSE) is used to evaluate the decomposition performance of ELMD with a certain amplitude of the added white noise. Once a maximum Relative RMSE, corresponding to an optimal noise amplitude, is determined, OELMD then identifies optimal noise bandwidth and ensemble number based on the Relative RMSE and signal-to-noise ratio (SNR), respectively. Thus, all three critical parameters of ELMD (i.e. noise amplitude and bandwidth, and ensemble number) are optimized by OELMD. The effectiveness of OELMD was evaluated using experimental vibration signals measured from three different mechanical components (i.e. the rolling bearing, gear and diesel engine) under faulty operation conditions.

Analysis on Vertical Scattering Signatures in Forestry with PolInSAR

NASA Astrophysics Data System (ADS)

Guo, Shenglong; Li, Yang; Zhang, Jingjing; Hong, Wen

2014-11-01

We apply accurate topographic phase to the Freeman-Durden decomposition for polarimetric SAR interferometry (PolInSAR) data. The cross correlation matrix obtained from PolInSAR observations can be decomposed into three scattering mechanisms matrices accounting for the odd-bounce, double-bounce and volume scattering. We estimate the phase based on the Random volume over Ground (RVoG) model, and as the initial input parameter of the numerical method which is used to solve the parameters of decomposition. In addition, the modified volume scattering model introduced by Y. Yamaguchi is applied to the PolInSAR target decomposition in forest areas rather than the pure random volume scattering as proposed by Freeman-Durden to make best fit to the actual measured data. This method can accurately retrieve the magnitude associated with each mechanism and their vertical location along the vertical dimension. We test the algorithms with L- and P- band simulated data.

Optimal classification for the diagnosis of duchenne muscular dystrophy images using support vector machines.

PubMed

Zhang, Ming-Huan; Ma, Jun-Shan; Shen, Ying; Chen, Ying

2016-09-01

This study aimed to investigate the optimal support vector machines (SVM)-based classifier of duchenne muscular dystrophy (DMD) magnetic resonance imaging (MRI) images. T1-weighted (T1W) and T2-weighted (T2W) images of the 15 boys with DMD and 15 normal controls were obtained. Textural features of the images were extracted and wavelet decomposed, and then, principal features were selected. Scale transform was then performed for MRI images. Afterward, SVM-based classifiers of MRI images were analyzed based on the radical basis function and decomposition levels. The cost (C) parameter and kernel parameter [Formula: see text] were used for classification. Then, the optimal SVM-based classifier, expressed as [Formula: see text]), was identified by performance evaluation (sensitivity, specificity and accuracy). Eight of 12 textural features were selected as principal features (eigenvalues [Formula: see text]). The 16 SVM-based classifiers were obtained using combination of (C, [Formula: see text]), and those with lower C and [Formula: see text] values showed higher performances, especially classifier of [Formula: see text]). The SVM-based classifiers of T1W images showed higher performance than T1W images at the same decomposition level. The T1W images in classifier of [Formula: see text]) at level 2 decomposition showed the highest performance of all, and its overall correct sensitivity, specificity, and accuracy reached 96.9, 97.3, and 97.1 %, respectively. The T1W images in SVM-based classifier [Formula: see text] at level 2 decomposition showed the highest performance of all, demonstrating that it was the optimal classification for the diagnosis of DMD.

Temperature Responses of Soil Organic Matter Components With Varying Recalcitrance

NASA Astrophysics Data System (ADS)

Simpson, M. J.; Feng, X.

2007-12-01

The response of soil organic matter (SOM) to global warming remains unclear partly due to the chemical heterogeneity of SOM composition. In this study, the decomposition of SOM from two grassland soils was investigated in a one-year laboratory incubation at six different temperatures. SOM was separated into solvent- extractable compounds, suberin- and cutin-derived compounds, and lignin monomers by solvent extraction, base hydrolysis, and CuO oxidation, respectively. These SOM components had distinct chemical structures and recalcitrance, and their decomposition was fitted by a two-pool exponential decay model. The stability of SOM components was assessed using geochemical parameters and kinetic parameters derived from model fitting. Lignin monomers exhibited much lower decay rates than solvent-extractable compounds and a relatively low percentage of lignin monomers partitioned into the labile SOM pool, which confirmed the generally accepted recalcitrance of lignin compounds. Suberin- and cutin-derived compounds had a poor fitting for the exponential decay model, and their recalcitrance was shown by the geochemical degradation parameter which stabilized during the incubation. The aliphatic components of suberin degraded faster than cutin-derived compounds, suggesting that cutin-derived compounds in the soil may be at a higher stage of degradation than suberin- derived compounds. The temperature sensitivity of decomposition, expressed as Q10, was derived from the relationship between temperature and SOM decay rates. SOM components exhibited varying temperature responses and the decomposition of the recalcitrant lignin monomers had much higher Q10 values than soil respiration or the solvent-extractable compounds decomposition. Our study shows that the decomposition of recalcitrant SOM is highly sensitive to temperature, more so than bulk soil mineralization. This observation suggests a potential acceleration in the degradation of the recalcitrant SOM pool with global warming.

Forest height estimation from mountain forest areas using general model-based decomposition for polarimetric interferometric synthetic aperture radar images

NASA Astrophysics Data System (ADS)

Minh, Nghia Pham; Zou, Bin; Cai, Hongjun; Wang, Chengyi

2014-01-01

The estimation of forest parameters over mountain forest areas using polarimetric interferometric synthetic aperture radar (PolInSAR) images is one of the greatest interests in remote sensing applications. For mountain forest areas, scattering mechanisms are strongly affected by the ground topography variations. Most of the previous studies in modeling microwave backscattering signatures of forest area have been carried out over relatively flat areas. Therefore, a new algorithm for the forest height estimation from mountain forest areas using the general model-based decomposition (GMBD) for PolInSAR image is proposed. This algorithm enables the retrieval of not only the forest parameters, but also the magnitude associated with each mechanism. In addition, general double- and single-bounce scattering models are proposed to fit for the cross-polarization and off-diagonal term by separating their independent orientation angle, which remains unachieved in the previous model-based decompositions. The efficiency of the proposed approach is demonstrated with simulated data from PolSARProSim software and ALOS-PALSAR spaceborne PolInSAR datasets over the Kalimantan areas, Indonesia. Experimental results indicate that forest height could be effectively estimated by GMBD.

Parameter estimation methods for gene circuit modeling from time-series mRNA data: a comparative study.

PubMed

Fan, Ming; Kuwahara, Hiroyuki; Wang, Xiaolei; Wang, Suojin; Gao, Xin

2015-11-01

Parameter estimation is a challenging computational problem in the reverse engineering of biological systems. Because advances in biotechnology have facilitated wide availability of time-series gene expression data, systematic parameter estimation of gene circuit models from such time-series mRNA data has become an important method for quantitatively dissecting the regulation of gene expression. By focusing on the modeling of gene circuits, we examine here the performance of three types of state-of-the-art parameter estimation methods: population-based methods, online methods and model-decomposition-based methods. Our results show that certain population-based methods are able to generate high-quality parameter solutions. The performance of these methods, however, is heavily dependent on the size of the parameter search space, and their computational requirements substantially increase as the size of the search space increases. In comparison, online methods and model decomposition-based methods are computationally faster alternatives and are less dependent on the size of the search space. Among other things, our results show that a hybrid approach that augments computationally fast methods with local search as a subsequent refinement procedure can substantially increase the quality of their parameter estimates to the level on par with the best solution obtained from the population-based methods while maintaining high computational speed. These suggest that such hybrid methods can be a promising alternative to the more commonly used population-based methods for parameter estimation of gene circuit models when limited prior knowledge about the underlying regulatory mechanisms makes the size of the parameter search space vastly large. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Study on the decomposition of trace benzene over V2O5-WO3 ...

EPA Pesticide Factsheets

Commercial and laboratory-prepared V2O5–WO3/TiO2-based catalysts with different compositions were tested for catalytic decomposition of chlorobenzene （ClBz） in simulated flue gas. Resonance enhanced multiphoton ionization-time of flight mass spectrometry (REMPI-TOFMS) was employed to measure real-time, trace concentrations of ClBz contained in the flue gas before and after the catalyst. The effects of various parameters, including vanadium content of the catalyst, the catalyst support, as well as the reaction temperature on decomposition of ClBz were investigated. The results showed that the ClBz decomposition efficiency was significantly enhanced when nano-TiO2 instead of conventional TiO2 was used as the catalyst support. No promotion effects were found in the ClBz decomposition process when the catalysts were wet-impregnated with CuO and CeO2. Tests with different concentrations (1,000, 500, and 100 ppb) of ClBz showed that ClBz-decomposition efficiency decreased with increasing concentration, unless active sites were plentiful. A comparison between ClBz and benzene decomposition on the V2O5–WO3/TiO2-based catalyst and the relative kinetics analysis showed that two different active sites were likely involved in the decomposition mechanism and the V=O and V-O-Ti groups may only work for the degradation of the phenyl group and the benzene ring rather than the C-Cl bond. V2O5-WO3/TiO2 based catalysts, that have been used for destruction of a wide variet

Wavelet-bounded empirical mode decomposition for measured time series analysis

NASA Astrophysics Data System (ADS)

Moore, Keegan J.; Kurt, Mehmet; Eriten, Melih; McFarland, D. Michael; Bergman, Lawrence A.; Vakakis, Alexander F.

2018-01-01

Empirical mode decomposition (EMD) is a powerful technique for separating the transient responses of nonlinear and nonstationary systems into finite sets of nearly orthogonal components, called intrinsic mode functions (IMFs), which represent the dynamics on different characteristic time scales. However, a deficiency of EMD is the mixing of two or more components in a single IMF, which can drastically affect the physical meaning of the empirical decomposition results. In this paper, we present a new approached based on EMD, designated as wavelet-bounded empirical mode decomposition (WBEMD), which is a closed-loop, optimization-based solution to the problem of mode mixing. The optimization routine relies on maximizing the isolation of an IMF around a characteristic frequency. This isolation is measured by fitting a bounding function around the IMF in the frequency domain and computing the area under this function. It follows that a large (small) area corresponds to a poorly (well) separated IMF. An optimization routine is developed based on this result with the objective of minimizing the bounding-function area and with the masking signal parameters serving as free parameters, such that a well-separated IMF is extracted. As examples of application of WBEMD we apply the proposed method, first to a stationary, two-component signal, and then to the numerically simulated response of a cantilever beam with an essentially nonlinear end attachment. We find that WBEMD vastly improves upon EMD and that the extracted sets of IMFs provide insight into the underlying physics of the response of each system.

Complete Volumetric Decomposition of Individual Trabecular Plates and Rods and Its Morphological Correlations With Anisotropic Elastic Moduli in Human Trabecular Bone

PubMed Central

Liu, X Sherry; Sajda, Paul; Saha, Punam K; Wehrli, Felix W; Bevill, Grant; Keaveny, Tony M; Guo, X Edward

2008-01-01

Trabecular plates and rods are important microarchitectural features in determining mechanical properties of trabecular bone. A complete volumetric decomposition of individual trabecular plates and rods was used to assess the orientation and morphology of 71 human trabecular bone samples. The ITS-based morphological analyses better characterize microarchitecture and help predict anisotropic mechanical properties of trabecular bone. Introduction Standard morphological analyses of trabecular architecture lack explicit segmentations of individual trabecular plates and rods. In this study, a complete volumetric decomposition technique was developed to segment trabecular bone microstructure into individual plates and rods. Contributions of trabecular type–associated morphological parameters to the anisotropic elastic moduli of trabecular bone were studied. Materials and Methods Seventy-one human trabecular bone samples from the femoral neck (FN), tibia, and vertebral body (VB) were imaged using μCT or serial milling. Complete volumetric decomposition was applied to segment trabecular bone microstructure into individual plates and rods. The orientation of each individual trabecula was determined, and the axial bone volume fractions (aBV/TV), axially aligned bone volume fraction along each orthotropic axis, were correlated with the elastic moduli. The microstructural type–associated morphological parameters were derived and compared with standard morphological parameters. Their contributions to the anisotropic elastic moduli, calculated by finite element analysis (FEA), were evaluated and compared. Results The distribution of trabecular orientation suggested that longitudinal plates and transverse rods dominate at all three anatomic sites. aBV/TV along each axis, in general, showed a better correlation with the axial elastic modulus (r 2 = 0.95∼0.99) compared with BV/TV (r 2 = 0.93∼0.94). The plate-associated morphological parameters generally showed higher correlations with the corresponding standard morphological parameters than the rod-associated parameters. Multiple linear regression models of six elastic moduli with individual trabeculae segmentation (ITS)-based morphological parameters (adjusted r 2 = 0.95∼0.98) performed equally well as those with standard morphological parameters (adjusted r 2 = 0.94∼0.97) but revealed specific contributions from individual trabecular plates or rods. Conclusions The ITS-based morphological analyses provide a better characterization of the morphology and trabecular orientation of trabecular bone. The axial loading of trabecular bone is mainly sustained by the axially aligned trabecular bone volume. Results suggest that trabecular plates dominate the overall elastic properties of trabecular bone. PMID:17907921

Experimental and modeling study on decomposition kinetics of methane hydrates in different media.

PubMed

Liang, Minyan; Chen, Guangjin; Sun, Changyu; Yan, Lijun; Liu, Jiang; Ma, Qinglan

2005-10-13

The decomposition kinetic behaviors of methane hydrates formed in 5 cm3 porous wet activated carbon were studied experimentally in a closed system in the temperature range of 275.8-264.4 K. The decomposition rates of methane hydrates formed from 5 cm3 of pure free water and an aqueous solution of 650 g x m(-3) sodium dodecyl sulfate (SDS) were also measured for comparison. The decomposition rates of methane hydrates in seven different cases were compared. The results showed that the methane hydrates dissociate more rapidly in porous activated carbon than in free systems. A mathematical model was developed for describing the decomposition kinetic behavior of methane hydrates below ice point based on an ice-shielding mechanism in which a porous ice layer was assumed to be formed during the decomposition of hydrate, and the diffusion of methane molecules through it was assumed to be one of the control steps. The parameters of the model were determined by correlating the decomposition rate data, and the activation energies were further determined with respect to three different media. The model was found to well describe the decomposition kinetic behavior of methane hydrate in different media.

Kinetics of the cellular decomposition of supersaturated solid solutions

NASA Astrophysics Data System (ADS)

Ivanov, M. A.; Naumuk, A. Yu.

2014-09-01

A consistent description of the kinetics of the cellular decomposition of supersaturated solid solutions with the development of a spatially periodic structure of lamellar (platelike) type, which consists of alternating phases of precipitates on the basis of the impurity component and depleted initial solid solution, is given. One of the equations, which determines the relationship between the parameters that describe the process of decomposition, has been obtained from a comparison of two approaches in order to determine the rate of change in the free energy of the system. The other kinetic parameters can be described with the use of a variational method, namely, by the maximum velocity of motion of the decomposition boundary at a given temperature. It is shown that the mutual directions of growth of the lamellae of different phases are determined by the minimum value of the interphase surface energy. To determine the parameters of the decomposition, a simple thermodynamic model of states with a parabolic dependence of the free energy on the concentrations has been used. As a result, expressions that describe the decomposition rate, interlamellar distance, and the concentration of impurities in the phase that remain after the decomposition have been derived. This concentration proves to be equal to the half-sum of the initial concentration and the equilibrium concentration corresponding to the decomposition temperature.

Viscosity effects on the thermal decomposition of bis(perfluoro-2-N-propoxypropionyl) peroxide in dense carbon dioxide and fluorinated solvents.

PubMed

Bunyard, W C; Kadla, J F; DeYoung, J; DeSimone, J M

2001-08-01

The thermal decomposition of the free-radical initiator bis(perfluoro-2-N-propoxyprionyl) peroxide (BPPP) was studied in dense carbon dioxide and a series of fluorinated solvents. For the fluorinated solvents, the observed first-order decomposition rate constants, k(obs), increased with decreasing solvent viscosity, suggesting a single-bond decomposition mechanism. The k(obs) values are comparatively larger in dense carbon dioxide and similar to the "zero-viscosity" rate constants extrapolated from the decomposition kinetics in the fluorinated solvents. The decomposition activation parameters demonstrate a compensation behavior of the activation enthalpy with the activation entropy upon change in solvent viscosity. Comparison of the change in activation parameter values upon change in solvent viscosity for BPPP with two additional initiators, acetyl peroxide (AP) and trifluoroacetyl peroxide (TFAP), further suggests that carbon dioxide exerts a very minimal influence on the decomposition mechanism of these initiators through solvent-cage effects.

A molecular dynamics study of model SI clathrate hydrates: the effect of guest size and guest-water interaction on decomposition kinetics.

PubMed

Das, Subhadip; Baghel, Vikesh Singh; Roy, Sudip; Kumar, Rajnish

2015-04-14

One of the options suggested for methane recovery from natural gas hydrates is molecular replacement of methane by suitable guests like CO2 and N2. This approach has been found to be feasible through many experimental and molecular dynamics simulation studies. However, the long term stability of the resultant hydrate needs to be evaluated; the decomposition rate of these hydrates is expected to depend on the interaction between these guest and water molecules. In this work, molecular dynamics simulation has been performed to illustrate the effect of guest molecules with different sizes and interaction strengths with water on structure I (SI) hydrate decomposition and hence the stability. The van der Waals interaction between water of hydrate cages and guest molecules is defined by Lennard Jones potential parameters. A wide range of parameter spaces has been scanned by changing the guest molecules in the SI hydrate, which acts as a model gas for occupying the small and large cages of the SI hydrate. All atomistic simulation results show that the stability of the hydrate is sensitive to the size and interaction of the guest molecules with hydrate water. The increase in the interaction of guest molecules with water stabilizes the hydrate, which in turn shows a slower rate of hydrate decomposition. Similarly guest molecules with a reasonably small (similar to Helium) or large size increase the decomposition rate. The results were also analyzed by calculating the structural order parameter to understand the dynamics of crystal structure and correlated with the release rate of guest molecules from the solid hydrate phase. The results have been explained based on the calculation of potential energies felt by guest molecules in amorphous water, hydrate bulk and hydrate-water interface regions.

Do soil organisms affect aboveground litter decomposition in the semiarid Patagonian steppe, Argentina?

PubMed

Araujo, Patricia I; Yahdjian, Laura; Austin, Amy T

2012-01-01

Surface litter decomposition in arid and semiarid ecosystems is often faster than predicted by climatic parameters such as annual precipitation or evapotranspiration, or based on standard indices of litter quality such as lignin or nitrogen concentrations. Abiotic photodegradation has been demonstrated to be an important factor controlling aboveground litter decomposition in aridland ecosystems, but soil fauna, particularly macrofauna such as termites and ants, have also been identified as key players affecting litter mass loss in warm deserts. Our objective was to quantify the importance of soil organisms on surface litter decomposition in the Patagonian steppe in the absence of photodegradative effects, to establish the relative importance of soil organisms on rates of mass loss and nitrogen release. We estimated the relative contribution of soil fauna and microbes to litter decomposition of a dominant grass using litterboxes with variable mesh sizes that excluded groups of soil fauna based on size class (10, 2, and 0.01 mm), which were placed beneath shrub canopies. We also employed chemical repellents (naphthalene and fungicide). The exclusion of macro- and mesofauna had no effect on litter mass loss over 3 years (P = 0.36), as litter decomposition was similar in all soil fauna exclusions and naphthalene-treated litter. In contrast, reduction of fungal activity significantly inhibited litter decomposition (P < 0.001). Although soil fauna have been mentioned as a key control of litter decomposition in warm deserts, biogeographic legacies and temperature limitation may constrain the importance of these organisms in temperate aridlands, particularly in the southern hemisphere.

A CATALOG OF BULGE+DISK DECOMPOSITIONS AND UPDATED PHOTOMETRY FOR 1.12 MILLION GALAXIES IN THE SLOAN DIGITAL SKY SURVEY

DOE Office of Scientific and Technical Information (OSTI.GOV)

Simard, Luc; McConnachie, Alan W.; Trevor Mendel, J.

We perform two-dimensional, point-spread-function-convolved, bulge+disk decompositions in the g and r bandpasses on a sample of 1,123,718 galaxies from the Legacy area of the Sloan Digital Sky Survey Data Release Seven. Four different decomposition procedures are investigated which make improvements to sky background determinations and object deblending over the standard SDSS procedures that lead to more robust structural parameters and integrated galaxy magnitudes and colors, especially in crowded environments. We use a set of science-based quality assurance metrics, namely, the disk luminosity-size relation, the galaxy color-magnitude diagram, and the galaxy central (fiber) colors to show the robustness of our structuralmore » parameters. The best procedure utilizes simultaneous, two-bandpass decompositions. Bulge and disk photometric errors remain below 0.1 mag down to bulge and disk magnitudes of g {approx_equal} 19 and r {approx_equal} 18.5. We also use and compare three different galaxy fitting models: a pure Sersic model, an n{sub b} = 4 bulge + disk model, and a Sersic (free n{sub b}) bulge + disk model. The most appropriate model for a given galaxy is determined by the F-test probability. All three catalogs of measured structural parameters, rest-frame magnitudes, and colors are publicly released here. These catalogs should provide an extensive comparison set for a wide range of observational and theoretical studies of galaxies.« less

Next Generation Anodes for Lithium Ion Batteries: Thermodynamic Understanding and Abuse Performance.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fenton, Kyle R.; Allcorn, Eric; Nagasubramanian, Ganesan

The objectives of this project are to elucidate degradation mechanisms, decomposition products, and abuse response for next generation silicon based anodes; and understand the contribution of various materials properties and cell build parameters towards thermal runaway enthalpies. Quantify the contributions from various cell parameters such as particle size, composition, state of charge (SOC), electrolyte to active materials ratio, etc.

Use of the Morlet mother wavelet in the frequency-scale domain decomposition technique for the modal identification of ambient vibration responses

NASA Astrophysics Data System (ADS)

Le, Thien-Phu

2017-10-01

The frequency-scale domain decomposition technique has recently been proposed for operational modal analysis. The technique is based on the Cauchy mother wavelet. In this paper, the approach is extended to the Morlet mother wavelet, which is very popular in signal processing due to its superior time-frequency localization. Based on the regressive form and an appropriate norm of the Morlet mother wavelet, the continuous wavelet transform of the power spectral density of ambient responses enables modes in the frequency-scale domain to be highlighted. Analytical developments first demonstrate the link between modal parameters and the local maxima of the continuous wavelet transform modulus. The link formula is then used as the foundation of the proposed modal identification method. Its practical procedure, combined with the singular value decomposition algorithm, is presented step by step. The proposition is finally verified using numerical examples and a laboratory test.

Crop residue decomposition in Minnesota biochar-amended plots

NASA Astrophysics Data System (ADS)

Weyers, S. L.; Spokas, K. A.

2014-06-01

Impacts of biochar application at laboratory scales are routinely studied, but impacts of biochar application on decomposition of crop residues at field scales have not been widely addressed. The priming or hindrance of crop residue decomposition could have a cascading impact on soil processes, particularly those influencing nutrient availability. Our objectives were to evaluate biochar effects on field decomposition of crop residue, using plots that were amended with biochars made from different plant-based feedstocks and pyrolysis platforms in the fall of 2008. Litterbags containing wheat straw material were buried in July of 2011 below the soil surface in a continuous-corn cropped field in plots that had received one of seven different biochar amendments or a uncharred wood-pellet amendment 2.5 yr prior to start of this study. Litterbags were collected over the course of 14 weeks. Microbial biomass was assessed in treatment plots the previous fall. Though first-order decomposition rate constants were positively correlated to microbial biomass, neither parameter was statistically affected by biochar or wood-pellet treatments. The findings indicated only a residual of potentially positive and negative initial impacts of biochars on residue decomposition, which fit in line with established feedstock and pyrolysis influences. Overall, these findings indicate that no significant alteration in the microbial dynamics of the soil decomposer communities occurred as a consequence of the application of plant-based biochars evaluated here.

An Optimal Orthogonal Decomposition Method for Kalman Filter-Based Turbofan Engine Thrust Estimation

NASA Technical Reports Server (NTRS)

Litt, Jonathan S.

2007-01-01

A new linear point design technique is presented for the determination of tuning parameters that enable the optimal estimation of unmeasured engine outputs, such as thrust. The engine's performance is affected by its level of degradation, generally described in terms of unmeasurable health parameters related to each major engine component. Accurate thrust reconstruction depends on knowledge of these health parameters, but there are usually too few sensors to be able to estimate their values. In this new technique, a set of tuning parameters is determined that accounts for degradation by representing the overall effect of the larger set of health parameters as closely as possible in a least squares sense. The technique takes advantage of the properties of the singular value decomposition of a matrix to generate a tuning parameter vector of low enough dimension that it can be estimated by a Kalman filter. A concise design procedure to generate a tuning vector that specifically takes into account the variables of interest is presented. An example demonstrates the tuning parameters ability to facilitate matching of both measured and unmeasured engine outputs, as well as state variables. Additional properties of the formulation are shown to lend themselves well to diagnostics.

An Optimal Orthogonal Decomposition Method for Kalman Filter-Based Turbofan Engine Thrust Estimation

NASA Technical Reports Server (NTRS)

Litt, Jonathan S.

2007-01-01

A new linear point design technique is presented for the determination of tuning parameters that enable the optimal estimation of unmeasured engine outputs, such as thrust. The engine s performance is affected by its level of degradation, generally described in terms of unmeasurable health parameters related to each major engine component. Accurate thrust reconstruction depends on knowledge of these health parameters, but there are usually too few sensors to be able to estimate their values. In this new technique, a set of tuning parameters is determined that accounts for degradation by representing the overall effect of the larger set of health parameters as closely as possible in a least-squares sense. The technique takes advantage of the properties of the singular value decomposition of a matrix to generate a tuning parameter vector of low enough dimension that it can be estimated by a Kalman filter. A concise design procedure to generate a tuning vector that specifically takes into account the variables of interest is presented. An example demonstrates the tuning parameters ability to facilitate matching of both measured and unmeasured engine outputs, as well as state variables. Additional properties of the formulation are shown to lend themselves well to diagnostics.

An Optimal Orthogonal Decomposition Method for Kalman Filter-Based Turbofan Engine Thrust Estimation

NASA Technical Reports Server (NTRS)

Litt, Jonathan S.

2005-01-01

A new linear point design technique is presented for the determination of tuning parameters that enable the optimal estimation of unmeasured engine outputs such as thrust. The engine s performance is affected by its level of degradation, generally described in terms of unmeasurable health parameters related to each major engine component. Accurate thrust reconstruction depends upon knowledge of these health parameters, but there are usually too few sensors to be able to estimate their values. In this new technique, a set of tuning parameters is determined which accounts for degradation by representing the overall effect of the larger set of health parameters as closely as possible in a least squares sense. The technique takes advantage of the properties of the singular value decomposition of a matrix to generate a tuning parameter vector of low enough dimension that it can be estimated by a Kalman filter. A concise design procedure to generate a tuning vector that specifically takes into account the variables of interest is presented. An example demonstrates the tuning parameters ability to facilitate matching of both measured and unmeasured engine outputs, as well as state variables. Additional properties of the formulation are shown to lend themselves well to diagnostics.

Development of a novel hydroxyl ammonium nitrate based liquid propellant for air-independent propulsion

NASA Astrophysics Data System (ADS)

Fontaine, Joseph Henry

The focus of this dissertation is the development of an Unmanned Undersea Vehicle (UUV) liquid propellant employing Hydroxyl Ammonium Nitrate (HAN) as the oxidizer. Hydroxyl Ammonium Nitrate is a highly acidic aqueous based liquid oxidizer. Therefore, in order to achieve efficient combustion of a propellant using this oxidizer, the fuel must be highly water soluble and compatible with the oxidizer to prevent a premature ignition prior to being heated within the combustion chamber. An extensive search of the fuel to be used with this oxidizer was conducted. Propylene glycol was chosen as the fuel for this propellant, and the propellant given the name RF-402. The propellant development process will first evaluate the propellants thermal stability and kinetic parameters using a Differential Scanning Calorimeter (DSC). The purpose of the thermal stability analysis is to determine the temperature at which the propellant decomposition begins for the future safe handling of the propellant and the optimization of the combustion chamber. Additionally, the thermogram results will provide information regarding any undesirable endotherms prior to the decomposition and whether or not the decomposition process is a multi-step process. The Arrhenius type kinetic parameters will be determined using the ASTM method for thermally unstable materials. The activation energy and pre-exponential factor of the propellant will be determined by evaluating the decomposition peak temperature over a temperature scan rate ranging from 1°C per minute to 10°C per minute. The kinetic parameters of the propellant will be compared to those of 81 wt% HAN to determine if the HAN decomposition is controlling the overall decomposition of the propellant RF-402. The lifetime of individual droplets will be analyzed using both experimental and theoretical techniques. The theoretical technique will involve modeling the lifetime of an individual droplet in a combustion chamber like operating environment. The experimental technique will consist of subjecting droplets suspended from a fine gauge thermocouple to an instantaneous hot gas source and recording its temperature response while imaging it using a high power video microscope to determine the physical response of the droplet. This analysis will be the foundation for all future efforts in developing a propulsion system employing the use of RF-402.

Bayesian inference of spectral induced polarization parameters for laboratory complex resistivity measurements of rocks and soils

NASA Astrophysics Data System (ADS)

Bérubé, Charles L.; Chouteau, Michel; Shamsipour, Pejman; Enkin, Randolph J.; Olivo, Gema R.

2017-08-01

Spectral induced polarization (SIP) measurements are now widely used to infer mineralogical or hydrogeological properties from the low-frequency electrical properties of the subsurface in both mineral exploration and environmental sciences. We present an open-source program that performs fast multi-model inversion of laboratory complex resistivity measurements using Markov-chain Monte Carlo simulation. Using this stochastic method, SIP parameters and their uncertainties may be obtained from the Cole-Cole and Dias models, or from the Debye and Warburg decomposition approaches. The program is tested on synthetic and laboratory data to show that the posterior distribution of a multiple Cole-Cole model is multimodal in particular cases. The Warburg and Debye decomposition approaches yield unique solutions in all cases. It is shown that an adaptive Metropolis algorithm performs faster and is less dependent on the initial parameter values than the Metropolis-Hastings step method when inverting SIP data through the decomposition schemes. There are no advantages in using an adaptive step method for well-defined Cole-Cole inversion. Finally, the influence of measurement noise on the recovered relaxation time distribution is explored. We provide the geophysics community with a open-source platform that can serve as a base for further developments in stochastic SIP data inversion and that may be used to perform parameter analysis with various SIP models.

Regular Decompositions for H(div) Spaces

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kolev, Tzanio; Vassilevski, Panayot

We study regular decompositions for H(div) spaces. In particular, we show that such regular decompositions are closely related to a previously studied “inf-sup” condition for parameter-dependent Stokes problems, for which we provide an alternative, more direct, proof.

Reactivity continuum modeling of leaf, root, and wood decomposition across biomes

NASA Astrophysics Data System (ADS)

Koehler, Birgit; Tranvik, Lars J.

2015-07-01

Large carbon dioxide amounts are released to the atmosphere during organic matter decomposition. Yet the large-scale and long-term regulation of this critical process in global carbon cycling by litter chemistry and climate remains poorly understood. We used reactivity continuum (RC) modeling to analyze the decadal data set of the "Long-term Intersite Decomposition Experiment," in which fine litter and wood decomposition was studied in eight biome types (224 time series). In 32 and 46% of all sites the litter content of the acid-unhydrolyzable residue (AUR, formerly referred to as lignin) and the AUR/nitrogen ratio, respectively, retarded initial decomposition rates. This initial rate-retarding effect generally disappeared within the first year of decomposition, and rate-stimulating effects of nutrients and a rate-retarding effect of the carbon/nitrogen ratio became more prevalent. For needles and leaves/grasses, the influence of climate on decomposition decreased over time. For fine roots, the climatic influence was initially smaller but increased toward later-stage decomposition. The climate decomposition index was the strongest climatic predictor of decomposition. The similar variability in initial decomposition rates across litter categories as across biome types suggested that future changes in decomposition may be dominated by warming-induced changes in plant community composition. In general, the RC model parameters successfully predicted independent decomposition data for the different litter-biome combinations (196 time series). We argue that parameterization of large-scale decomposition models with RC model parameters, as opposed to the currently common discrete multiexponential models, could significantly improve their mechanistic foundation and predictive accuracy across climate zones and litter categories.

Limited-memory adaptive snapshot selection for proper orthogonal decomposition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oxberry, Geoffrey M.; Kostova-Vassilevska, Tanya; Arrighi, Bill

2015-04-02

Reduced order models are useful for accelerating simulations in many-query contexts, such as optimization, uncertainty quantification, and sensitivity analysis. However, offline training of reduced order models can have prohibitively expensive memory and floating-point operation costs in high-performance computing applications, where memory per core is limited. To overcome this limitation for proper orthogonal decomposition, we propose a novel adaptive selection method for snapshots in time that limits offline training costs by selecting snapshots according an error control mechanism similar to that found in adaptive time-stepping ordinary differential equation solvers. The error estimator used in this work is related to theory boundingmore » the approximation error in time of proper orthogonal decomposition-based reduced order models, and memory usage is minimized by computing the singular value decomposition using a single-pass incremental algorithm. Results for a viscous Burgers’ test problem demonstrate convergence in the limit as the algorithm error tolerances go to zero; in this limit, the full order model is recovered to within discretization error. The resulting method can be used on supercomputers to generate proper orthogonal decomposition-based reduced order models, or as a subroutine within hyperreduction algorithms that require taking snapshots in time, or within greedy algorithms for sampling parameter space.« less

Utilization of a balanced steady state free precession signal model for improved fat/water decomposition.

PubMed

Henze Bancroft, Leah C; Strigel, Roberta M; Hernando, Diego; Johnson, Kevin M; Kelcz, Frederick; Kijowski, Richard; Block, Walter F

2016-03-01

Chemical shift based fat/water decomposition methods such as IDEAL are frequently used in challenging imaging environments with large B0 inhomogeneity. However, they do not account for the signal modulations introduced by a balanced steady state free precession (bSSFP) acquisition. Here we demonstrate improved performance when the bSSFP frequency response is properly incorporated into the multipeak spectral fat model used in the decomposition process. Balanced SSFP allows for rapid imaging but also introduces a characteristic frequency response featuring periodic nulls and pass bands. Fat spectral components in adjacent pass bands will experience bulk phase offsets and magnitude modulations that change the expected constructive and destructive interference between the fat spectral components. A bSSFP signal model was incorporated into the fat/water decomposition process and used to generate images of a fat phantom, and bilateral breast and knee images in four normal volunteers at 1.5 Tesla. Incorporation of the bSSFP signal model into the decomposition process improved the performance of the fat/water decomposition. Incorporation of this model allows rapid bSSFP imaging sequences to use robust fat/water decomposition methods such as IDEAL. While only one set of imaging parameters were presented, the method is compatible with any field strength or repetition time. © 2015 Wiley Periodicals, Inc.

The thermal stability of sodium beta'-Alumina solid electrolyte ceramic in AMTEC cells

DOE Office of Scientific and Technical Information (OSTI.GOV)

Williams, Roger M.; Ryan, Margaret A.; Homer, Margie L.

1999-01-22

A critical component of alkali metal thermal-to electric converter (AMTEC) devices for long duration space missions is the beta'-alumina solid electrolyte ceramic (BASE), for which there exists no substitute. The temperature and environmental conditions under which BASE remains stable control operational parameters of AMTEC devices. We have used mass loss experiments in vacuum to 1573K to characterize the kinetics of BASE decomposition, and conductivity and exchange current measurements in sodium vapor filled exposure cells to 1223K to investigate changes in the BASE which affect its ionic conductivity. There is no clear evidence of direct thermal decomposition of BASE below 1273K,more » although limited soda loss may occur. Reactive metals such as Mn or Cr can react with BASE at temperatures at least as low as 1223K.« less

Density-dependent liquid nitromethane decomposition: molecular dynamics simulations based on ReaxFF.

PubMed

Rom, Naomi; Zybin, Sergey V; van Duin, Adri C T; Goddard, William A; Zeiri, Yehuda; Katz, Gil; Kosloff, Ronnie

2011-09-15

The decomposition mechanism of hot liquid nitromethane at various compressions was studied using reactive force field (ReaxFF) molecular dynamics simulations. A competition between two different initial thermal decomposition schemes is observed, depending on compression. At low densities, unimolecular C-N bond cleavage is the dominant route, producing CH(3) and NO(2) fragments. As density and pressure rise approaching the Chapman-Jouget detonation conditions (∼30% compression, >2500 K) the dominant mechanism switches to the formation of the CH(3)NO fragment via H-transfer and/or N-O bond rupture. The change in the decomposition mechanism of hot liquid NM leads to a different kinetic and energetic behavior, as well as products distribution. The calculated density dependence of the enthalpy change correlates with the change in initial decomposition reaction mechanism. It can be used as a convenient and useful global parameter for the detection of reaction dynamics. Atomic averaged local diffusion coefficients are shown to be sensitive to the reactions dynamics, and can be used to distinguish between time periods where chemical reactions occur and diffusion-dominated, nonreactive time periods. © 2011 American Chemical Society

Nonlinear mode decomposition: A noise-robust, adaptive decomposition method

NASA Astrophysics Data System (ADS)

Iatsenko, Dmytro; McClintock, Peter V. E.; Stefanovska, Aneta

2015-09-01

The signals emanating from complex systems are usually composed of a mixture of different oscillations which, for a reliable analysis, should be separated from each other and from the inevitable background of noise. Here we introduce an adaptive decomposition tool—nonlinear mode decomposition (NMD)—which decomposes a given signal into a set of physically meaningful oscillations for any wave form, simultaneously removing the noise. NMD is based on the powerful combination of time-frequency analysis techniques—which, together with the adaptive choice of their parameters, make it extremely noise robust—and surrogate data tests used to identify interdependent oscillations and to distinguish deterministic from random activity. We illustrate the application of NMD to both simulated and real signals and demonstrate its qualitative and quantitative superiority over other approaches, such as (ensemble) empirical mode decomposition, Karhunen-Loève expansion, and independent component analysis. We point out that NMD is likely to be applicable and useful in many different areas of research, such as geophysics, finance, and the life sciences. The necessary matlab codes for running NMD are freely available for download.

Phase-only asymmetric optical cryptosystem based on random modulus decomposition

NASA Astrophysics Data System (ADS)

Xu, Hongfeng; Xu, Wenhui; Wang, Shuaihua; Wu, Shaofan

2018-06-01

We propose a phase-only asymmetric optical cryptosystem based on random modulus decomposition (RMD). The cryptosystem is presented for effectively improving the capacity to resist various attacks, including the attack of iterative algorithms. On the one hand, RMD and phase encoding are combined to remove the constraints that can be used in the attacking process. On the other hand, the security keys (geometrical parameters) introduced by Fresnel transform can increase the key variety and enlarge the key space simultaneously. Numerical simulation results demonstrate the strong feasibility, security and robustness of the proposed cryptosystem. This cryptosystem will open up many new opportunities in the application fields of optical encryption and authentication.

Object-oriented crop mapping and monitoring using multi-temporal polarimetric RADARSAT-2 data

NASA Astrophysics Data System (ADS)

Jiao, Xianfeng; Kovacs, John M.; Shang, Jiali; McNairn, Heather; Walters, Dan; Ma, Baoluo; Geng, Xiaoyuan

2014-10-01

The aim of this paper is to assess the accuracy of an object-oriented classification of polarimetric Synthetic Aperture Radar (PolSAR) data to map and monitor crops using 19 RADARSAT-2 fine beam polarimetric (FQ) images of an agricultural area in North-eastern Ontario, Canada. Polarimetric images and field data were acquired during the 2011 and 2012 growing seasons. The classification and field data collection focused on the main crop types grown in the region, which include: wheat, oat, soybean, canola and forage. The polarimetric parameters were extracted with PolSAR analysis using both the Cloude-Pottier and Freeman-Durden decompositions. The object-oriented classification, with a single date of PolSAR data, was able to classify all five crop types with an accuracy of 95% and Kappa of 0.93; a 6% improvement in comparison with linear-polarization only classification. However, the time of acquisition is crucial. The larger biomass crops of canola and soybean were most accurately mapped, whereas the identification of oat and wheat were more variable. The multi-temporal data using the Cloude-Pottier decomposition parameters provided the best classification accuracy compared to the linear polarizations and the Freeman-Durden decomposition parameters. In general, the object-oriented classifications were able to accurately map crop types by reducing the noise inherent in the SAR data. Furthermore, using the crop classification maps we were able to monitor crop growth stage based on a trend analysis of the radar response. Based on field data from canola crops, there was a strong relationship between the phenological growth stage based on the BBCH scale, and the HV backscatter and entropy.

Towards a representation of priming on soil carbon decomposition in the global land biosphere model ORCHIDEE (version 1.9.5.2)

NASA Astrophysics Data System (ADS)

Guenet, Bertrand; Esteban Moyano, Fernando; Peylin, Philippe; Ciais, Philippe; Janssens, Ivan A.

2016-03-01

Priming of soil carbon decomposition encompasses different processes through which the decomposition of native (already present) soil organic matter is amplified through the addition of new organic matter, with new inputs typically being more labile than the native soil organic matter. Evidence for priming comes from laboratory and field experiments, but to date there is no estimate of its impact at global scale and under the current anthropogenic perturbation of the carbon cycle. Current soil carbon decomposition models do not include priming mechanisms, thereby introducing uncertainty when extrapolating short-term local observations to ecosystem and regional to global scale. In this study we present a simple conceptual model of decomposition priming, called PRIM, able to reproduce laboratory (incubation) and field (litter manipulation) priming experiments. Parameters for this model were first optimized against data from 20 soil incubation experiments using a Bayesian framework. The optimized parameter values were evaluated against another set of soil incubation data independent from the ones used for calibration and the PRIM model reproduced the soil incubations data better than the original, CENTURY-type soil decomposition model, whose decomposition equations are based only on first-order kinetics. We then compared the PRIM model and the standard first-order decay model incorporated into the global land biosphere model ORCHIDEE (Organising Carbon and Hydrology In Dynamic Ecosystems). A test of both models was performed at ecosystem scale using litter manipulation experiments from five sites. Although both versions were equally able to reproduce observed decay rates of litter, only ORCHIDEE-PRIM could simulate the observed priming (R2 = 0.54) in cases where litter was added or removed. This result suggests that a conceptually simple and numerically tractable representation of priming adapted to global models is able to capture the sign and magnitude of the priming of litter and soil organic matter.

Towards a representation of priming on soil carbon decomposition in the global land biosphere model ORCHIDEE (version 1.9.5.2)

NASA Astrophysics Data System (ADS)

Guenet, B.; Moyano, F. E.; Peylin, P.; Ciais, P.; Janssens, I. A.

2015-10-01

Priming of soil carbon decomposition encompasses different processes through which the decomposition of native (already present) soil organic matter is amplified through the addition of new organic matter, with new inputs typically being more labile than the native soil organic matter. Evidence for priming comes from laboratory and field experiments, but to date there is no estimate of its impact at global scale and under the current anthropogenic perturbation of the carbon cycle. Current soil carbon decomposition models do not include priming mechanisms, thereby introducing uncertainty when extrapolating short-term local observations to ecosystem and regional to global scale. In this study we present a simple conceptual model of decomposition priming, called PRIM, able to reproduce laboratory (incubation) and field (litter manipulation) priming experiments. Parameters for this model were first optimized against data from 20 soil incubation experiments using a Bayesian framework. The optimized parameter values were evaluated against another set of soil incubation data independent from the ones used for calibration and the PRIM model reproduced the soil incubations data better than the original, CENTURY-type soil decomposition model, whose decomposition equations are based only on first order kinetics. We then compared the PRIM model and the standard first order decay model incorporated into the global land biosphere model ORCHIDEE. A test of both models was performed at ecosystem scale using litter manipulation experiments from 5 sites. Although both versions were equally able to reproduce observed decay rates of litter, only ORCHIDEE-PRIM could simulate the observed priming (R2 = 0.54) in cases where litter was added or removed. This result suggests that a conceptually simple and numerically tractable representation of priming adapted to global models is able to capture the sign and magnitude of the priming of litter and soil organic matter.

Experimental investigation of the catalytic decomposition and combustion characteristics of a non-toxic ammonium dinitramide (ADN)-based monopropellant thruster

NASA Astrophysics Data System (ADS)

Chen, Jun; Li, Guoxiu; Zhang, Tao; Wang, Meng; Yu, Yusong

2016-12-01

Low toxicity ammonium dinitramide (ADN)-based aerospace propulsion systems currently show promise with regard to applications such as controlling satellite attitude. In the present work, the decomposition and combustion processes of an ADN-based monopropellant thruster were systematically studied, using a thermally stable catalyst to promote the decomposition reaction. The performance of the ADN propulsion system was investigated using a ground test system under vacuum, and the physical properties of the ADN-based propellant were also examined. Using this system, the effects of the preheating temperature and feed pressure on the combustion characteristics and thruster performance during steady state operation were observed. The results indicate that the propellant and catalyst employed during this work, as well as the design and manufacture of the thruster, met performance requirements. Moreover, the 1 N ADN thruster generated a specific impulse of 223 s, demonstrating the efficacy of the new catalyst. The thruster operational parameters (specifically, the preheating temperature and feed pressure) were found to have a significant effect on the decomposition and combustion processes within the thruster, and the performance of the thruster was demonstrated to improve at higher feed pressures and elevated preheating temperatures. A lower temperature of 140 °C was determined to activate the catalytic decomposition and combustion processes more effectively compared with the results obtained using other conditions. The data obtained in this study should be beneficial to future systematic and in-depth investigations of the combustion mechanism and characteristics within an ADN thruster.

Gamma-irradiation effect on a commercial composite anticorrosive pigment and acidity-to-alkalinity conversion

NASA Astrophysics Data System (ADS)

Song, Weiqiang; Niu, Kaihui; Wu, Longchao

2016-05-01

A commercial composite anticorrosive pigment based on aluminum dihydrogen tripolyphosphate was studied after exposure to gamma irradiation (Co60, 0, 20, 50, 100 and 150 kGy) using FTIR, XRD, TGA and acid-base titration technologies. Although the FTIR spectra showed that the effect of the irradiation on functional groups in the pigments was not obvious, the decrease in the crystal lattice parameters of the irradiated pigments was observed in the XRD spectra compared to the non-irradiated sample. But the extent of the lattice parameter decrease monotonically with the increase of absorbed dose from 20 to 150 kGy, which was attributed to the decomposition of water and the simultaneous occurrence of lattice damage when the pigments were exposed to gamma rays. Of particular significance was the displayed basicity of the aqueous solutions of the irradiated pigments compared to the acidity of the solution of the non-irradiated pigment, which was attributed to the decomposition of P-OH groups (combined water).

Dynamic Bayesian wavelet transform: New methodology for extraction of repetitive transients

NASA Astrophysics Data System (ADS)

Wang, Dong; Tsui, Kwok-Leung

2017-05-01

Thanks to some recent research works, dynamic Bayesian wavelet transform as new methodology for extraction of repetitive transients is proposed in this short communication to reveal fault signatures hidden in rotating machine. The main idea of the dynamic Bayesian wavelet transform is to iteratively estimate posterior parameters of wavelet transform via artificial observations and dynamic Bayesian inference. First, a prior wavelet parameter distribution can be established by one of many fast detection algorithms, such as the fast kurtogram, the improved kurtogram, the enhanced kurtogram, the sparsogram, the infogram, continuous wavelet transform, discrete wavelet transform, wavelet packets, multiwavelets, empirical wavelet transform, empirical mode decomposition, local mean decomposition, etc.. Second, artificial observations can be constructed based on one of many metrics, such as kurtosis, the sparsity measurement, entropy, approximate entropy, the smoothness index, a synthesized criterion, etc., which are able to quantify repetitive transients. Finally, given artificial observations, the prior wavelet parameter distribution can be posteriorly updated over iterations by using dynamic Bayesian inference. More importantly, the proposed new methodology can be extended to establish the optimal parameters required by many other signal processing methods for extraction of repetitive transients.

The Multiscale Robin Coupled Method for flows in porous media

NASA Astrophysics Data System (ADS)

Guiraldello, Rafael T.; Ausas, Roberto F.; Sousa, Fabricio S.; Pereira, Felipe; Buscaglia, Gustavo C.

2018-02-01

A multiscale mixed method aiming at the accurate approximation of velocity and pressure fields in heterogeneous porous media is proposed. The procedure is based on a new domain decomposition method in which the local problems are subject to Robin boundary conditions. The domain decomposition procedure is defined in terms of two independent spaces on the skeleton of the decomposition, corresponding to interface pressures and fluxes, that can be chosen with great flexibility to accommodate local features of the underlying permeability fields. The well-posedness of the new domain decomposition procedure is established and its connection with the method of Douglas et al. (1993) [12], is identified, also allowing us to reinterpret the known procedure as an optimized Schwarz (or Two-Lagrange-Multiplier) method. The multiscale property of the new domain decomposition method is indicated, and its relation with the Multiscale Mortar Mixed Finite Element Method (MMMFEM) and the Multiscale Hybrid-Mixed (MHM) Finite Element Method is discussed. Numerical simulations are presented aiming at illustrating several features of the new method. Initially we illustrate the possibility of switching from MMMFEM to MHM by suitably varying the Robin condition parameter in the new multiscale method. Then we turn our attention to realistic flows in high-contrast, channelized porous formations. We show that for a range of values of the Robin condition parameter our method provides better approximations for pressure and velocity than those computed with either the MMMFEM and the MHM. This is an indication that our method has the potential to produce more accurate velocity fields in the presence of rough, realistic permeability fields of petroleum reservoirs.

Wavelet decomposition and radial basis function networks for system monitoring

NASA Astrophysics Data System (ADS)

Ikonomopoulos, A.; Endou, A.

1998-10-01

Two approaches are coupled to develop a novel collection of black box models for monitoring operational parameters in a complex system. The idea springs from the intention of obtaining multiple predictions for each system variable and fusing them before they are used to validate the actual measurement. The proposed architecture pairs the analytical abilities of the discrete wavelet decomposition with the computational power of radial basis function networks. Members of a wavelet family are constructed in a systematic way and chosen through a statistical selection criterion that optimizes the structure of the network. Network parameters are further optimized through a quasi-Newton algorithm. The methodology is demonstrated utilizing data obtained during two transients of the Monju fast breeder reactor. The models developed are benchmarked with respect to similar regressors based on Gaussian basis functions.

An asymptotic induced numerical method for the convection-diffusion-reaction equation

NASA Technical Reports Server (NTRS)

Scroggs, Jeffrey S.; Sorensen, Danny C.

1988-01-01

A parallel algorithm for the efficient solution of a time dependent reaction convection diffusion equation with small parameter on the diffusion term is presented. The method is based on a domain decomposition that is dictated by singular perturbation analysis. The analysis is used to determine regions where certain reduced equations may be solved in place of the full equation. Parallelism is evident at two levels. Domain decomposition provides parallelism at the highest level, and within each domain there is ample opportunity to exploit parallelism. Run time results demonstrate the viability of the method.

Surrogate models for sheet metal stamping problem based on the combination of proper orthogonal decomposition and radial basis function

NASA Astrophysics Data System (ADS)

Dang, Van Tuan; Lafon, Pascal; Labergere, Carl

2017-10-01

In this work, a combination of Proper Orthogonal Decomposition (POD) and Radial Basis Function (RBF) is proposed to build a surrogate model based on the Benchmark Springback 3D bending from the Numisheet2011 congress. The influence of the two design parameters, the geometrical parameter of the die radius and the process parameter of the blank holder force, on the springback of the sheet after a stamping operation is analyzed. The classical Design of Experience (DoE) uses Full Factorial to design the parameter space with sample points as input data for finite element method (FEM) numerical simulation of the sheet metal stamping process. The basic idea is to consider the design parameters as additional dimensions for the solution of the displacement fields. The order of the resultant high-fidelity model is reduced through the use of POD method which performs model space reduction and results in the basis functions of the low order model. Specifically, the snapshot method is used in our work, in which the basis functions is derived from snapshot deviation of the matrix of the final displacements fields of the FEM numerical simulation. The obtained basis functions are then used to determine the POD coefficients and RBF is used for the interpolation of these POD coefficients over the parameter space. Finally, the presented POD-RBF approach which is used for shape optimization can be performed with high accuracy.

Block matrix based LU decomposition to analyze kinetic damping in active plasma resonance spectroscopy

NASA Astrophysics Data System (ADS)

Roehl, Jan Hendrik; Oberrath, Jens

2016-09-01

``Active plasma resonance spectroscopy'' (APRS) is a widely used diagnostic method to measure plasma parameter like electron density. Measurements with APRS probes in plasmas of a few Pa typically show a broadening of the spectrum due to kinetic effects. To analyze the broadening a general kinetic model in electrostatic approximation based on functional analytic methods has been presented [ 1 ] . One of the main results is, that the system response function Y(ω) is given in terms of the matrix elements of the resolvent of the dynamic operator evaluated for values on the imaginary axis. To determine the response function of a specific probe the resolvent has to be approximated by a huge matrix which is given by a banded block structure. Due to this structure a block based LU decomposition can be implemented. It leads to a solution of Y(ω) which is given only by products of matrices of the inner block size. This LU decomposition allows to analyze the influence of kinetic effects on the broadening and saves memory and calculation time. Gratitude is expressed to the internal funding of Leuphana University.

Radiation noise of the bearing applied to the ceramic motorized spindle based on the sub-source decomposition method

NASA Astrophysics Data System (ADS)

Bai, X. T.; Wu, Y. H.; Zhang, K.; Chen, C. Z.; Yan, H. P.

2017-12-01

This paper mainly focuses on the calculation and analysis on the radiation noise of the angular contact ball bearing applied to the ceramic motorized spindle. The dynamic model containing the main working conditions and structural parameters is established based on dynamic theory of rolling bearing. The sub-source decomposition method is introduced in for the calculation of the radiation noise of the bearing, and a comparative experiment is adopted to check the precision of the method. Then the comparison between the contribution of different components is carried out in frequency domain based on the sub-source decomposition method. The spectrum of radiation noise of different components under various rotation speeds are used as the basis of assessing the contribution of different eigenfrequencies on the radiation noise of the components, and the proportion of friction noise and impact noise is evaluated as well. The results of the research provide the theoretical basis for the calculation of bearing noise, and offers reference to the impact of different components on the radiation noise of the bearing under different rotation speed.

Critical analysis of nitramine decomposition data: Activation energies and frequency factors for HMX and RDX decomposition

NASA Technical Reports Server (NTRS)

Schroeder, M. A.

1980-01-01

A summary of a literature review on thermal decomposition of HMX and RDX is presented. The decomposition apparently fits first order kinetics. Recommended values for Arrhenius parameters for HMX and RDX decomposition in the gaseous and liquid phases and for decomposition of RDX in solution in TNT are given. The apparent importance of autocatalysis is pointed out, as are some possible complications that may be encountered in interpreting extending or extrapolating kinetic data for these compounds from measurements carried out below their melting points to the higher temperatures and pressure characteristic of combustion.

Theoretical study of the decomposition mechanism of environmentally friendly insulating medium C3F7CN in the presence of H2O in a discharge

NASA Astrophysics Data System (ADS)

Zhang, Xiaoxing; Li, Yi; Xiao, Song; Tian, Shuangshuang; Deng, Zaitao; Tang, Ju

2017-08-01

C3F7CN has been the focus of the alternative gas research field over the past two years because of its excellent insulation properties and environmental characteristics. Experimental studies on its insulation performance have made many achievements. However, few studies on the formation mechanism of the decomposition components exist. A discussion of the decomposition characteristics of insulating media will provide guidance for scientific experimental research and the work that must be completed before further engineering application. In this study, the decomposition mechanism of C3F7CN in the presence of trace H2O under discharge was calculated based on the density functional theory and transition state theory. The reaction heat, Gibbs free energy, and activation energy of different decomposition pathways were investigated. The ionization parameters and toxicity of C3F7CN and various decomposition products were analyzed from the molecular structure perspective. The formation mechanism of the C3F7CN discharge decomposition components and the influence of trace water were evaluated. This paper confirms that C3F7CN has excellent decomposition characteristics, which provide theoretical support for later experiments and related engineering applications. However, the existence of trace water has a negative impact on C3F7CN’s insulation performance. Thus, strict trace water content standards should be developed to ensure dielectric insulation and the safety of maintenance personnel.

Thermal decomposition of nano-enabled thermoplastics: Possible environmental health and safety implications

PubMed Central

Sotiriou, Georgios A.; Singh, Dilpreet; Zhang, Fang; Chalbot, Marie-Cecile G.; Spielman-Sun, Eleanor; Hoering, Lutz; Kavouras, Ilias G.; Lowry, Gregory V.; Wohlleben, Wendel; Demokritou, Philip

2015-01-01

Nano-enabled products (NEPs) are currently part of our life prompting for detailed investigation of potential nano-release across their life-cycle. Particularly interesting is their end-of-life thermal decomposition scenario. Here, we examine the thermal decomposition of a widely used NEP, namely thermoplastic nanocomposites, and assess the properties of the byproducts (released aerosol and residual ash) and possible environmental health and safety implications. We focus on establishing a fundamental understanding on the effect of thermal decomposition parameters, such as polymer matrix, nanofiller properties, decomposition temperature, on the properties of byproducts using a recently-developed lab-based experimental integrated platform. Our results indicate that thermoplastic polymer matrix strongly influences size and morphology of released aerosol, while there was minimal but detectable nano-release, especially when inorganic nanofillers were used. The chemical composition of the released aerosol was found not to be strongly influenced by the presence of nanofiller at least for the low, industry-relevant loadings assessed here. Furthermore, the morphology and composition of residual ash was found to be strongly influenced by the presence of nanofiller. The findings presented here on thermal decomposition/incineration of NEPs raise important questions and concerns regarding the potential fate and transport of released engineered nanomaterials in environmental media and potential environmental health and safety implications. PMID:26642449

G W calculations using the spectral decomposition of the dielectric matrix: Verification, validation, and comparison of methods

DOE PAGES

Pham, T. Anh; Nguyen, Huy -Viet; Rocca, Dario; ...

2013-04-26

Inmore » a recent paper we presented an approach to evaluate quasiparticle energies based on the spectral decomposition of the static dielectric matrix. This method does not require the calculation of unoccupied electronic states or the direct diagonalization of large dielectric matrices, and it avoids the use of plasmon-pole models. The numerical accuracy of the approach is controlled by a single parameter, i.e., the number of eigenvectors used in the spectral decomposition of the dielectric matrix. Here we present a comprehensive validation of the method, encompassing calculations of ionization potentials and electron affinities of various molecules and of band gaps for several crystalline and disordered semiconductors. Lastly, we demonstrate the efficiency of our approach by carrying out G W calculations for systems with several hundred valence electrons.« less

Integration of a Physically based Distributed Hydrological Model with a Model of Carbon and Nitrogen Cycling: A Case Study at the Luquillo Critical Zone Observatory, Puerto Rico

NASA Astrophysics Data System (ADS)

Bastola, S.; Dialynas, Y. G.; Bras, R. L.; Arnone, E.; Noto, L. V.

2015-12-01

The dynamics of carbon and nitrogen cycles, increasingly influenced by human activities, are the key to the functioning of ecosystems. These cycles are influenced by the composition of the substrate, availability of nitrogen, the population of microorganisms, and by environmental factors. Therefore, land management and use, climate change, and nitrogen deposition patterns influence the dynamics of these macronutrients at the landscape scale. In this work a physically based distributed hydrological model, the tRIBS model, is coupled with a process-based multi-compartment model of the biogeochemical cycle to simulate the dynamics of carbon and nitrogen (CN) in the Mameyes River basin, Puerto Rico. The model includes a wide range of processes that influence the movement, production, alteration of nutrients in the landscape and factors that affect the CN cycling. The tRIBS integrates geomorphological and climatic factors that influence the cycling of CN in soil. Implementing the decomposition module into tRIBS makes the model a powerful complement to a biogeochemical observation system and a forecast tool able to analyze the influences of future changes on ecosystem services. The soil hydrologic parameters of the model were obtained using ranges of published parameters and observed streamflow data at the outlet. The parameters of the decomposition module are based on previously published data from studies conducted in the Luquillio CZO (budgets of soil organic matter and CN ratio for each of the dominant vegetation types across the landscape). Hydrological fluxes, wet depositon of nitrogen, litter fall and its corresponding CN ratio drive the decomposition model. The simulation results demonstrate a strong influence of soil moisture dynamics on the spatiotemporal distribution of nutrients at the landscape level. The carbon in the litter pool and the nitrate and ammonia pool respond quickly to soil moisture content. Moreover, the CN ratios of the plant litter have significant influence in the dynamics of CN cycling.

Robust and automated three-dimensional segmentation of densely packed cell nuclei in different biological specimens with Lines-of-Sight decomposition.

PubMed

Mathew, B; Schmitz, A; Muñoz-Descalzo, S; Ansari, N; Pampaloni, F; Stelzer, E H K; Fischer, S C

2015-06-08

Due to the large amount of data produced by advanced microscopy, automated image analysis is crucial in modern biology. Most applications require reliable cell nuclei segmentation. However, in many biological specimens cell nuclei are densely packed and appear to touch one another in the images. Therefore, a major difficulty of three-dimensional cell nuclei segmentation is the decomposition of cell nuclei that apparently touch each other. Current methods are highly adapted to a certain biological specimen or a specific microscope. They do not ensure similarly accurate segmentation performance, i.e. their robustness for different datasets is not guaranteed. Hence, these methods require elaborate adjustments to each dataset. We present an advanced three-dimensional cell nuclei segmentation algorithm that is accurate and robust. Our approach combines local adaptive pre-processing with decomposition based on Lines-of-Sight (LoS) to separate apparently touching cell nuclei into approximately convex parts. We demonstrate the superior performance of our algorithm using data from different specimens recorded with different microscopes. The three-dimensional images were recorded with confocal and light sheet-based fluorescence microscopes. The specimens are an early mouse embryo and two different cellular spheroids. We compared the segmentation accuracy of our algorithm with ground truth data for the test images and results from state-of-the-art methods. The analysis shows that our method is accurate throughout all test datasets (mean F-measure: 91%) whereas the other methods each failed for at least one dataset (F-measure≤69%). Furthermore, nuclei volume measurements are improved for LoS decomposition. The state-of-the-art methods required laborious adjustments of parameter values to achieve these results. Our LoS algorithm did not require parameter value adjustments. The accurate performance was achieved with one fixed set of parameter values. We developed a novel and fully automated three-dimensional cell nuclei segmentation method incorporating LoS decomposition. LoS are easily accessible features that ensure correct splitting of apparently touching cell nuclei independent of their shape, size or intensity. Our method showed superior performance compared to state-of-the-art methods, performing accurately for a variety of test images. Hence, our LoS approach can be readily applied to quantitative evaluation in drug testing, developmental and cell biology.

Kinetic Analysis of Isothermal Decomposition Process of Sodium Bicarbonate Using the Weibull Probability Function—Estimation of Density Distribution Functions of the Apparent Activation Energies

NASA Astrophysics Data System (ADS)

Janković, Bojan

2009-10-01

The decomposition process of sodium bicarbonate (NaHCO3) has been studied by thermogravimetry in isothermal conditions at four different operating temperatures (380 K, 400 K, 420 K, and 440 K). It was found that the experimental integral and differential conversion curves at the different operating temperatures can be successfully described by the isothermal Weibull distribution function with a unique value of the shape parameter ( β = 1.07). It was also established that the Weibull distribution parameters ( β and η) show independent behavior on the operating temperature. Using the integral and differential (Friedman) isoconversional methods, in the conversion (α) range of 0.20 ≤ α ≤ 0.80, the apparent activation energy ( E a ) value was approximately constant ( E a, int = 95.2 kJmol-1 and E a, diff = 96.6 kJmol-1, respectively). The values of E a calculated by both isoconversional methods are in good agreement with the value of E a evaluated from the Arrhenius equation (94.3 kJmol-1), which was expressed through the scale distribution parameter ( η). The Málek isothermal procedure was used for estimation of the kinetic model for the investigated decomposition process. It was found that the two-parameter Šesták-Berggren (SB) autocatalytic model best describes the NaHCO3 decomposition process with the conversion function f(α) = α0.18(1-α)1.19. It was also concluded that the calculated density distribution functions of the apparent activation energies ( ddfE a ’s) are not dependent on the operating temperature, which exhibit the highly symmetrical behavior (shape factor = 1.00). The obtained isothermal decomposition results were compared with corresponding results of the nonisothermal decomposition process of NaHCO3.

A Perturbation Based Decomposition of Compound-Evoked Potentials for Characterization of Nerve Fiber Size Distributions.

PubMed

Szlavik, Robert B

2016-02-01

The characterization of peripheral nerve fiber distributions, in terms of diameter or velocity, is of clinical significance because information associated with these distributions can be utilized in the differential diagnosis of peripheral neuropathies. Electro-diagnostic techniques can be applied to the investigation of peripheral neuropathies and can yield valuable diagnostic information while being minimally invasive. Nerve conduction velocity studies are single parameter tests that yield no detailed information regarding the characteristics of the population of nerve fibers that contribute to the compound-evoked potential. Decomposition of the compound-evoked potential, such that the velocity or diameter distribution of the contributing nerve fibers may be determined, is necessary if information regarding the population of contributing nerve fibers is to be ascertained from the electro-diagnostic study. In this work, a perturbation-based decomposition of compound-evoked potentials is proposed that facilitates determination of the fiber diameter distribution associated with the compound-evoked potential. The decomposition is based on representing the single fiber-evoked potential, associated with each diameter class, as being perturbed by contributions, of varying degree, from all the other diameter class single fiber-evoked potentials. The resultant estimator of the contributing nerve fiber diameter distribution is valid for relatively large separations in diameter classes. It is also useful in situations where the separation between diameter classes is small and the concomitant single fiber-evoked potentials are not orthogonal.

Diagnosis of the Ill-condition of the RFM Based on Condition Index and Variance Decomposition Proportion (CIVDP)

NASA Astrophysics Data System (ADS)

Qing, Zhou; Weili, Jiao; Tengfei, Long

2014-03-01

The Rational Function Model (RFM) is a new generalized sensor model. It does not need the physical parameters of sensors to achieve a high accuracy that is compatible to the rigorous sensor models. At present, the main method to solve RPCs is the Least Squares Estimation. But when coefficients has a large number or the distribution of the control points is not even, the classical least square method loses its superiority due to the ill-conditioning problem of design matrix. Condition Index and Variance Decomposition Proportion (CIVDP) is a reliable method for diagnosing the multicollinearity among the design matrix. It can not only detect the multicollinearity, but also can locate the parameters and show the corresponding columns in the design matrix. In this paper, the CIVDP method is used to diagnose the ill-condition problem of the RFM and to find the multicollinearity in the normal matrix.

Biophysical controls on surface fuel litterfall and decomposition in the northern Rocky Mountains, USA

Treesearch

Robert E. Keane

2008-01-01

Litterfall and decomposition rates of the organic matter that comprise forest fuels are important to fire management, because they define fuel treatment longevity and provide parameters to design, test, and validate ecosystem models. This study explores the environmental factors that control litterfall and decomposition in the context of fuel management for several...

Optimized Kernel Entropy Components.

PubMed

Izquierdo-Verdiguier, Emma; Laparra, Valero; Jenssen, Robert; Gomez-Chova, Luis; Camps-Valls, Gustau

2017-06-01

This brief addresses two main issues of the standard kernel entropy component analysis (KECA) algorithm: the optimization of the kernel decomposition and the optimization of the Gaussian kernel parameter. KECA roughly reduces to a sorting of the importance of kernel eigenvectors by entropy instead of variance, as in the kernel principal components analysis. In this brief, we propose an extension of the KECA method, named optimized KECA (OKECA), that directly extracts the optimal features retaining most of the data entropy by means of compacting the information in very few features (often in just one or two). The proposed method produces features which have higher expressive power. In particular, it is based on the independent component analysis framework, and introduces an extra rotation to the eigen decomposition, which is optimized via gradient-ascent search. This maximum entropy preservation suggests that OKECA features are more efficient than KECA features for density estimation. In addition, a critical issue in both the methods is the selection of the kernel parameter, since it critically affects the resulting performance. Here, we analyze the most common kernel length-scale selection criteria. The results of both the methods are illustrated in different synthetic and real problems. Results show that OKECA returns projections with more expressive power than KECA, the most successful rule for estimating the kernel parameter is based on maximum likelihood, and OKECA is more robust to the selection of the length-scale parameter in kernel density estimation.

Early diagenesis of vascular plant tissues: Lignin and cutin decomposition and biogeochemical implications

NASA Astrophysics Data System (ADS)

Opsahl, Stephen; Benner, Ronald

1995-12-01

Long-term subaqueous decomposition patterns of five different vascular plant tissues including mangrove leaves and wood ( Avicennia germinans), cypress needles and wood ( Taxodium distichum) and smooth cordgrass ( Spartina alternifora) were followed for a period of 4.0 years, representing the longest litter bag decomposition study to date. All tissues decomposed under identical conditions and final mass losses were 97, 68, 86, 39, and 93%, respectively. Analysis of the lignin component of herbaceous tissues using alkaline CuO oxidation was complicated by the presence of a substantial ester-bound phenol component composed primarily of cinnamyl phenols. To overcome this problem, we introduce a new parameter to represent lignin, Λ6. Λ6 is comprised only of the six syringyl and vanillyl phenols and was found to be much less sensitive to diagenetic variation than the commonly used parameter Λ, which includes the cinnamyl phenols. Patterns of change in lignin content were strongly dependent on tissue type, ranging from 77% enrichment in smooth cordgrass to 6% depletion in cypress needles. In contrast, depletion of cutin was extensive (65-99%) in all herbaceous tissues. Despite these differences in the overall reactivity of lignin and cutin, both macromolecules were extensively degraded during the decomposition period. The long-term decomposition series also provided very useful information about the compositional parameters which are derived from the specific oxidation products of both lignin and cutin. The relative lability of ester-bound cinnamyl phenols compromised their use in parameters to distinguish woody from herbaceous plant debris. The dimer to monomer ratios of lignin-derived phenols indicated that most intermonomeric linkages in lignin degraded at similar rates. Acid to aldehyde ratios of vanillyl and syringyl phenols became elevated, particularly during the latter stages of decomposition supporting the use of these parameters as indicators of diagenetic alteration. Given the observation that cutin-derived source indicator parameters were generally more sensitive to diagenetic alteration than those of lignin, we suggest the distributional patterns of cutin-derived acids and their associated positional isomers may be most useful for tissue-specific distinctions complementing the general categorical information obtained from lignin phenol analysis alone.

Applications of singular value analysis and partial-step algorithm for nonlinear orbit determination

NASA Technical Reports Server (NTRS)

Ryne, Mark S.; Wang, Tseng-Chan

1991-01-01

An adaptive method in which cruise and nonlinear orbit determination problems can be solved using a single program is presented. It involves singular value decomposition augmented with an extended partial step algorithm. The extended partial step algorithm constrains the size of the correction to the spacecraft state and other solve-for parameters. The correction is controlled by an a priori covariance and a user-supplied bounds parameter. The extended partial step method is an extension of the update portion of the singular value decomposition algorithm. It thus preserves the numerical stability of the singular value decomposition method, while extending the region over which it converges. In linear cases, this method reduces to the singular value decomposition algorithm with the full rank solution. Two examples are presented to illustrate the method's utility.

Long-term litter decomposition controlled by manganese redox cycling

PubMed Central

Keiluweit, Marco; Nico, Peter; Harmon, Mark E.; Mao, Jingdong; Pett-Ridge, Jennifer; Kleber, Markus

2015-01-01

Litter decomposition is a keystone ecosystem process impacting nutrient cycling and productivity, soil properties, and the terrestrial carbon (C) balance, but the factors regulating decomposition rate are still poorly understood. Traditional models assume that the rate is controlled by litter quality, relying on parameters such as lignin content as predictors. However, a strong correlation has been observed between the manganese (Mn) content of litter and decomposition rates across a variety of forest ecosystems. Here, we show that long-term litter decomposition in forest ecosystems is tightly coupled to Mn redox cycling. Over 7 years of litter decomposition, microbial transformation of litter was paralleled by variations in Mn oxidation state and concentration. A detailed chemical imaging analysis of the litter revealed that fungi recruit and redistribute unreactive Mn2+ provided by fresh plant litter to produce oxidative Mn3+ species at sites of active decay, with Mn eventually accumulating as insoluble Mn3+/4+ oxides. Formation of reactive Mn3+ species coincided with the generation of aromatic oxidation products, providing direct proof of the previously posited role of Mn3+-based oxidizers in the breakdown of litter. Our results suggest that the litter-decomposing machinery at our coniferous forest site depends on the ability of plants and microbes to supply, accumulate, and regenerate short-lived Mn3+ species in the litter layer. This observation indicates that biogeochemical constraints on bioavailability, mobility, and reactivity of Mn in the plant–soil system may have a profound impact on litter decomposition rates. PMID:26372954

Long-term litter decomposition controlled by manganese redox cycling.

PubMed

Keiluweit, Marco; Nico, Peter; Harmon, Mark E; Mao, Jingdong; Pett-Ridge, Jennifer; Kleber, Markus

2015-09-22

Litter decomposition is a keystone ecosystem process impacting nutrient cycling and productivity, soil properties, and the terrestrial carbon (C) balance, but the factors regulating decomposition rate are still poorly understood. Traditional models assume that the rate is controlled by litter quality, relying on parameters such as lignin content as predictors. However, a strong correlation has been observed between the manganese (Mn) content of litter and decomposition rates across a variety of forest ecosystems. Here, we show that long-term litter decomposition in forest ecosystems is tightly coupled to Mn redox cycling. Over 7 years of litter decomposition, microbial transformation of litter was paralleled by variations in Mn oxidation state and concentration. A detailed chemical imaging analysis of the litter revealed that fungi recruit and redistribute unreactive Mn(2+) provided by fresh plant litter to produce oxidative Mn(3+) species at sites of active decay, with Mn eventually accumulating as insoluble Mn(3+/4+) oxides. Formation of reactive Mn(3+) species coincided with the generation of aromatic oxidation products, providing direct proof of the previously posited role of Mn(3+)-based oxidizers in the breakdown of litter. Our results suggest that the litter-decomposing machinery at our coniferous forest site depends on the ability of plants and microbes to supply, accumulate, and regenerate short-lived Mn(3+) species in the litter layer. This observation indicates that biogeochemical constraints on bioavailability, mobility, and reactivity of Mn in the plant-soil system may have a profound impact on litter decomposition rates.

Resonance-Based Sparse Signal Decomposition and its Application in Mechanical Fault Diagnosis: A Review.

PubMed

Huang, Wentao; Sun, Hongjian; Wang, Weijie

2017-06-03

Mechanical equipment is the heart of industry. For this reason, mechanical fault diagnosis has drawn considerable attention. In terms of the rich information hidden in fault vibration signals, the processing and analysis techniques of vibration signals have become a crucial research issue in the field of mechanical fault diagnosis. Based on the theory of sparse decomposition, Selesnick proposed a novel nonlinear signal processing method: resonance-based sparse signal decomposition (RSSD). Since being put forward, RSSD has become widely recognized, and many RSSD-based methods have been developed to guide mechanical fault diagnosis. This paper attempts to summarize and review the theoretical developments and application advances of RSSD in mechanical fault diagnosis, and to provide a more comprehensive reference for those interested in RSSD and mechanical fault diagnosis. Followed by a brief introduction of RSSD's theoretical foundation, based on different optimization directions, applications of RSSD in mechanical fault diagnosis are categorized into five aspects: original RSSD, parameter optimized RSSD, subband optimized RSSD, integrated optimized RSSD, and RSSD combined with other methods. On this basis, outstanding issues in current RSSD study are also pointed out, as well as corresponding instructional solutions. We hope this review will provide an insightful reference for researchers and readers who are interested in RSSD and mechanical fault diagnosis.

Resonance-Based Sparse Signal Decomposition and Its Application in Mechanical Fault Diagnosis: A Review

PubMed Central

Huang, Wentao; Sun, Hongjian; Wang, Weijie

2017-01-01

Mechanical equipment is the heart of industry. For this reason, mechanical fault diagnosis has drawn considerable attention. In terms of the rich information hidden in fault vibration signals, the processing and analysis techniques of vibration signals have become a crucial research issue in the field of mechanical fault diagnosis. Based on the theory of sparse decomposition, Selesnick proposed a novel nonlinear signal processing method: resonance-based sparse signal decomposition (RSSD). Since being put forward, RSSD has become widely recognized, and many RSSD-based methods have been developed to guide mechanical fault diagnosis. This paper attempts to summarize and review the theoretical developments and application advances of RSSD in mechanical fault diagnosis, and to provide a more comprehensive reference for those interested in RSSD and mechanical fault diagnosis. Followed by a brief introduction of RSSD’s theoretical foundation, based on different optimization directions, applications of RSSD in mechanical fault diagnosis are categorized into five aspects: original RSSD, parameter optimized RSSD, subband optimized RSSD, integrated optimized RSSD, and RSSD combined with other methods. On this basis, outstanding issues in current RSSD study are also pointed out, as well as corresponding instructional solutions. We hope this review will provide an insightful reference for researchers and readers who are interested in RSSD and mechanical fault diagnosis. PMID:28587198

Preparation, non-isothermal decomposition kinetics, heat capacity and adiabatic time-to-explosion of NTOxDNAZ.

PubMed

Ma, Haixia; Yan, Biao; Li, Zhaona; Guan, Yulei; Song, Jirong; Xu, Kangzhen; Hu, Rongzu

2009-09-30

NTOxDNAZ was prepared by mixing 3,3-dinitroazetidine (DNAZ) and 3-nitro-1,2,4-triazol-5-one (NTO) in ethanol solution. The thermal behavior of the title compound was studied under a non-isothermal condition by DSC and TG/DTG methods. The kinetic parameters were obtained from analysis of the DSC and TG/DTG curves by Kissinger method, Ozawa method, the differential method and the integral method. The main exothermic decomposition reaction mechanism of NTOxDNAZ is classified as chemical reaction, and the kinetic parameters of the reaction are E(a)=149.68 kJ mol(-1) and A=10(15.81)s(-1). The specific heat capacity of the title compound was determined with continuous C(p) mode of microcalorimeter. The standard mole specific heat capacity of NTOxDNAZ was 352.56 J mol(-1)K(-1) in 298.15K. Using the relationship between C(p) and T and the thermal decomposition parameters, the time of the thermal decomposition from initialization to thermal explosion (adiabatic time-to-explosion) was obtained.

Uncertainty in the fate of soil organic carbon: A comparison of three conceptually different soil decomposition models

USGS Publications Warehouse

He, Yujie; Yang, Jinyan; Zhuang, Qianlai; McGuire, A. David; Zhu, Qing; Liu, Yaling; Teskey, Robert O.

2014-01-01

Conventional Q10 soil organic matter decomposition models and more complex microbial models are available for making projections of future soil carbon dynamics. However, it is unclear (1) how well the conceptually different approaches can simulate observed decomposition and (2) to what extent the trajectories of long-term simulations differ when using the different approaches. In this study, we compared three structurally different soil carbon (C) decomposition models (one Q10 and two microbial models of different complexity), each with a one- and two-horizon version. The models were calibrated and validated using 4 years of measurements of heterotrophic soil CO2 efflux from trenched plots in a Dahurian larch (Larix gmelinii Rupr.) plantation. All models reproduced the observed heterotrophic component of soil CO2 efflux, but the trajectories of soil carbon dynamics differed substantially in 100 year simulations with and without warming and increased litterfall input, with microbial models that produced better agreement with observed changes in soil organic C in long-term warming experiments. Our results also suggest that both constant and varying carbon use efficiency are plausible when modeling future decomposition dynamics and that the use of a short-term (e.g., a few years) period of measurement is insufficient to adequately constrain model parameters that represent long-term responses of microbial thermal adaption. These results highlight the need to reframe the representation of decomposition models and to constrain parameters with long-term observations and multiple data streams. We urge caution in interpreting future soil carbon responses derived from existing decomposition models because both conceptual and parameter uncertainties are substantial.

A contribution to the knowledge of HMX decomposition and application of results. [at atmospheric pressure

NASA Technical Reports Server (NTRS)

Kraeutle, K. J.

1980-01-01

The decomposition of cyclotramethylenetetranitramine (HMX) in the solid and liquid phase was studied by isothermal and nonisothermal heating at atmospheric pressure. Decomposition rates of solid HMX changed with sample size and gaseous environment. Kinetic parameters were obtained from weight loss measurements in the temperature range 229 C - 269 C. These tests also yielded highly porous solid residues. Qualitative aspects of solid and liquid phase decomposition of HMX with additives were also investigated in isothermal and nonisothermal tests.

a Hybrid Method in Vegetation Height Estimation Using Polinsar Images of Campaign Biosar

NASA Astrophysics Data System (ADS)

Dehnavi, S.; Maghsoudi, Y.

2015-12-01

Recently, there have been plenty of researches on the retrieval of forest height by PolInSAR data. This paper aims at the evaluation of a hybrid method in vegetation height estimation based on L-band multi-polarized air-borne SAR images. The SAR data used in this paper were collected by the airborne E-SAR system. The objective of this research is firstly to describe each interferometry cross correlation as a sum of contributions corresponding to single bounce, double bounce and volume scattering processes. Then, an ESPIRIT (Estimation of Signal Parameters via Rotational Invariance Techniques) algorithm is implemented, to determine the interferometric phase of each local scatterer (ground and canopy). Secondly, the canopy height is estimated by phase differencing method, according to the RVOG (Random Volume Over Ground) concept. The applied model-based decomposition method is unrivaled, as it is not limited to specific type of vegetation, unlike the previous decomposition techniques. In fact, the usage of generalized probability density function based on the nth power of a cosine-squared function, which is characterized by two parameters, makes this method useful for different vegetation types. Experimental results show the efficiency of the approach for vegetation height estimation in the test site.

Parametric study and global sensitivity analysis for co-pyrolysis of rape straw and waste tire via variance-based decomposition.

PubMed

Xu, Li; Jiang, Yong; Qiu, Rong

2018-01-01

In present study, co-pyrolysis behavior of rape straw, waste tire and their various blends were investigated. TG-FTIR indicated that co-pyrolysis was characterized by a four-step reaction, and H 2 O, CH, OH, CO 2 and CO groups were the main products evolved during the process. Additionally, using BBD-based experimental results, best-fit multiple regression models with high R 2 -pred values (94.10% for mass loss and 95.37% for reaction heat), which correlated explanatory variables with the responses, were presented. The derived models were analyzed by ANOVA at 95% confidence interval, F-test, lack-of-fit test and residues normal probability plots implied the models described well the experimental data. Finally, the model uncertainties as well as the interactive effect of these parameters were studied, the total-, first- and second-order sensitivity indices of operating factors were proposed using Sobol' variance decomposition. To the authors' knowledge, this is the first time global parameter sensitivity analysis has been performed in (co-)pyrolysis literature. Copyright © 2017 Elsevier Ltd. All rights reserved.

Spatial, temporal, and hybrid decompositions for large-scale vehicle routing with time windows

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bent, Russell W

This paper studies the use of decomposition techniques to quickly find high-quality solutions to large-scale vehicle routing problems with time windows. It considers an adaptive decomposition scheme which iteratively decouples a routing problem based on the current solution. Earlier work considered vehicle-based decompositions that partitions the vehicles across the subproblems. The subproblems can then be optimized independently and merged easily. This paper argues that vehicle-based decompositions, although very effective on various problem classes also have limitations. In particular, they do not accommodate temporal decompositions and may produce spatial decompositions that are not focused enough. This paper then proposes customer-based decompositionsmore » which generalize vehicle-based decouplings and allows for focused spatial and temporal decompositions. Experimental results on class R2 of the extended Solomon benchmarks demonstrates the benefits of the customer-based adaptive decomposition scheme and its spatial, temporal, and hybrid instantiations. In particular, they show that customer-based decompositions bring significant benefits over large neighborhood search in contrast to vehicle-based decompositions.« less

Decomposition Mechanism of C5F10O: An Environmentally Friendly Insulation Medium.

PubMed

Zhang, Xiaoxing; Li, Yi; Xiao, Song; Tang, Ju; Tian, Shuangshuang; Deng, Zaitao

2017-09-05

SF 6 , the most widely used electrical-equipment-insulation gas, has serious greenhouse effects. C 5 F 10 O has attracted much attention as an alternative gas in recent two years, but the environmental impact of its decomposition products is unclear. In this work, the decomposition characteristics of C 5 F 10 O were studied based on gas chromatography-mass spectrometry and density functional theory. We found that the amount of decomposition products of C 5 F 10 O, namely, CF 4 , C 2 F 6 , C 3 F 6 , C 3 F 8 , C 4 F 10 , and C 6 F 14 , increased with increased number of discharges. Under a high-energy electric field, the C-C bond of C 5 F 10 O between carbonyl carbon and α-carbon atoms was most likely to break and generate CF 3 CO•, C 3 F 7 • or C 3 F 7 CO•, CF 3 • free radicals. CF 3 •, and C 3 F 7 • free radicals produced by the breakage more easily recombined to form small molecular products. By analyzing the ionization parameters, toxicity, and environmental effects of C 5 F 10 O and its decomposition products, we found that C 5 F 10 O gas mixtures exhibit great decomposition and environmental characteristics with low toxicity, with great potential to replace SF 6 .

Calculation of excitation energies from the CC2 linear response theory using Cholesky decomposition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baudin, Pablo, E-mail: baudin.pablo@gmail.com; qLEAP – Center for Theoretical Chemistry, Department of Chemistry, Aarhus University, Langelandsgade 140, DK-8000 Aarhus C; Marín, José Sánchez

2014-03-14

A new implementation of the approximate coupled cluster singles and doubles CC2 linear response model is reported. It employs a Cholesky decomposition of the two-electron integrals that significantly reduces the computational cost and the storage requirements of the method compared to standard implementations. Our algorithm also exploits a partitioning form of the CC2 equations which reduces the dimension of the problem and avoids the storage of doubles amplitudes. We present calculation of excitation energies of benzene using a hierarchy of basis sets and compare the results with conventional CC2 calculations. The reduction of the scaling is evaluated as well asmore » the effect of the Cholesky decomposition parameter on the quality of the results. The new algorithm is used to perform an extrapolation to complete basis set investigation on the spectroscopically interesting benzylallene conformers. A set of calculations on medium-sized molecules is carried out to check the dependence of the accuracy of the results on the decomposition thresholds. Moreover, CC2 singlet excitation energies of the free base porphin are also presented.« less

Generalized Finsler geometric continuum physics with applications in fracture and phase transformations

NASA Astrophysics Data System (ADS)

Clayton, J. D.

2017-02-01

A theory of deformation of continuous media based on concepts from Finsler differential geometry is presented. The general theory accounts for finite deformations, nonlinear elasticity, and changes in internal state of the material, the latter represented by elements of a state vector of generalized Finsler space whose entries consist of one or more order parameter(s). Two descriptive representations of the deformation gradient are considered. The first invokes an additive decomposition and is applied to problems involving localized inelastic deformation mechanisms such as fracture. The second invokes a multiplicative decomposition and is applied to problems involving distributed deformation mechanisms such as phase transformations or twinning. Appropriate free energy functions are posited for each case, and Euler-Lagrange equations of equilibrium are derived. Solutions are obtained for specific problems of tensile fracture of an elastic cylinder and for amorphization of a crystal under spherical and uniaxial compression. The Finsler-based approach is demonstrated to be more general and potentially more physically descriptive than existing hyperelasticity models couched in Riemannian geometry or Euclidean space, without incorporation of supplementary ad hoc equations or spurious fitting parameters. Predictions for single crystals of boron carbide ceramic agree qualitatively, and in many instances quantitatively, with results from physical experiments and atomic simulations involving structural collapse and failure of the crystal along its c-axis.

Pyrosequencing-based assessment of microbial community shifts in leachate from animal carcass burial lysimeter.

PubMed

Kim, Hyun Young; Seo, Jiyoung; Kim, Tae-Hun; Shim, Bomi; Cha, Seok Mun; Yu, Seungho

2017-06-01

This study examined the use of microbial community structure as a bio-indicator of decomposition levels. High-throughput pyrosequencing technology was used to assess the shift in microbial community of leachate from animal carcass lysimeter. The leachate samples were collected monthly for one year and a total of 164,639 pyrosequencing reads were obtained and used in the taxonomic classification and operational taxonomy units (OTUs) distribution analysis based on sequence similarity. Our results show considerable changes in the phylum-level bacterial composition, suggesting that the microbial community is a sensitive parameter affected by the burial environment. The phylum classification results showed that Proteobacteria (Pseudomonas) were the most influential taxa in earlier decomposition stage whereas Firmicutes (Clostridium, Sporanaerobacter, and Peptostreptococcus) were dominant in later stage under anaerobic conditions. The result of this study can provide useful information on a time series of leachate profiles of microbial community structures and suggest patterns of microbial diversity in livestock burial sites. In addition, this result can be applicable to predict the decomposition stages under clay loam based soil conditions of animal livestock. Copyright © 2017 Elsevier B.V. All rights reserved.

A model-data fusion analysis for examining the response of carbon exchange to environmental variation in crop field

NASA Astrophysics Data System (ADS)

Yokozawa, M.; Sakurai, G.; Ono, K.; Mano, M.; Miyata, A.

2011-12-01

Agricultural activities, cultivating crops, managing soil, harvesting and post-harvest treatments, are not only affected from the surrounding environment but also change the environment reversely. The changes in environment, temperature, radiation and precipitation, brings changes in crop productivity. On the other hand, the status of crops, i.e. the growth and phenological stage, change the exchange of energy, H2O and CO2 between crop vegetation surface and atmosphere. Conducting the stable agricultural harvests, reducing the Greenhouse Effect Gas (GHG) emission and enhancing carbon sequestration in soil are preferable as a win-win activity. We conducted model-data fusion analysis for examining the response of cropland-atmosphere carbon exchange to environmental variation. The used model consists of two sub models, paddy rice growth sub-model and soil decomposition sub-model. The crop growth sub-model mimics the rice plant growth processes including formation of reproductive organs as well as leaf expansion. The soil decomposition sub-model simulates the decomposition process of soil organic carbon. Assimilating the data on the time changes in CO2 flux measured by eddy covariance method, rice plant biomass, LAI and the final yield with the model, the parameters were calibrated using a stochastic optimization algorithm with a particle filter. The particle filter, which is one of Monte Carlo filters, enable us to evaluating time changes in parameters based on the observed data until the time and to make prediction of the system. Iterative filtering and prediction with changing parameters and/or boundary condition enable us to obtain time changes in parameters governing the crop production as well as carbon exchange. In this paper, we applied the model-data fusion analysis to the two datasets on paddy rice field sites in Japan: only a single rice cultivation, and a single rice and wheat cultivation. We focused on the parameters related to crop production as well as soil carbon storage. As a result, the calibrated model with estimated parameters could accurately predict the NEE flux in the subsequent years (Fig.1). The temperature sensitivity, Q10s in the decomposition rate of soil organic carbon (SOC) were obtained as 1.4 for no cultivation period and 2.9 for cultivation period (submerged soil condition).

Explosive decomposition of ethylene oxide at elevated condition: effect of ignition energy, nitrogen dilution, and turbulence.

PubMed

Pekalski, A A; Zevenbergen, J F; Braithwaite, M; Lemkowitz, S M; Pasman, H J

2005-02-14

Experimental and theoretical investigation of explosive decomposition of ethylene oxide (EO) at fixed initial experimental parameters (T=100 degrees C, P=4 bar) in a 20-l sphere was conducted. Safety-related parameters, namely the maximum explosion pressure, the maximum rate of pressure rise, and the Kd values, were experimentally determined for pure ethylene oxide and ethylene oxide diluted with nitrogen. The influence of the ignition energy on the explosion parameters was also studied. All these dependencies are quantified in empirical formulas. Additionally, the effect of turbulence on explosive decomposition of ethylene oxide was investigated. In contrast to previous studies, it is found that turbulence significantly influences the explosion severity parameters, mostly the rate of pressure rise. Thermodynamic models are used to calculate the maximum explosion pressure of pure and of nitrogen-diluted ethylene oxide, at different initial temperatures. Soot formation was experimentally observed. Relation between the amounts of soot formed and the explosion pressure was experimentally observed and was calculated.

Automatic classification of visual evoked potentials based on wavelet decomposition

NASA Astrophysics Data System (ADS)

Stasiakiewicz, Paweł; Dobrowolski, Andrzej P.; Tomczykiewicz, Kazimierz

2017-04-01

Diagnosis of part of the visual system, that is responsible for conducting compound action potential, is generally based on visual evoked potentials generated as a result of stimulation of the eye by external light source. The condition of patient's visual path is assessed by set of parameters that describe the time domain characteristic extremes called waves. The decision process is compound therefore diagnosis significantly depends on experience of a doctor. The authors developed a procedure - based on wavelet decomposition and linear discriminant analysis - that ensures automatic classification of visual evoked potentials. The algorithm enables to assign individual case to normal or pathological class. The proposed classifier has a 96,4% sensitivity at 10,4% probability of false alarm in a group of 220 cases and area under curve ROC equals to 0,96 which, from the medical point of view, is a very good result.

An Optimal Strategy for Accurate Bulge-to-disk Decomposition of Disk Galaxies

NASA Astrophysics Data System (ADS)

Gao, Hua; Ho, Luis C.

2017-08-01

The development of two-dimensional (2D) bulge-to-disk decomposition techniques has shown their advantages over traditional one-dimensional (1D) techniques, especially for galaxies with non-axisymmetric features. However, the full potential of 2D techniques has yet to be fully exploited. Secondary morphological features in nearby disk galaxies, such as bars, lenses, rings, disk breaks, and spiral arms, are seldom accounted for in 2D image decompositions, even though some image-fitting codes, such as GALFIT, are capable of handling them. We present detailed, 2D multi-model and multi-component decomposition of high-quality R-band images of a representative sample of nearby disk galaxies selected from the Carnegie-Irvine Galaxy Survey, using the latest version of GALFIT. The sample consists of five barred and five unbarred galaxies, spanning Hubble types from S0 to Sc. Traditional 1D decomposition is also presented for comparison. In detailed case studies of the 10 galaxies, we successfully model the secondary morphological features. Through a comparison of best-fit parameters obtained from different input surface brightness models, we identify morphological features that significantly impact bulge measurements. We show that nuclear and inner lenses/rings and disk breaks must be properly taken into account to obtain accurate bulge parameters, whereas outer lenses/rings and spiral arms have a negligible effect. We provide an optimal strategy to measure bulge parameters of typical disk galaxies, as well as prescriptions to estimate realistic uncertainties of them, which will benefit subsequent decomposition of a larger galaxy sample.

An Optimal Strategy for Accurate Bulge-to-disk Decomposition of Disk Galaxies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gao Hua; Ho, Luis C.

The development of two-dimensional (2D) bulge-to-disk decomposition techniques has shown their advantages over traditional one-dimensional (1D) techniques, especially for galaxies with non-axisymmetric features. However, the full potential of 2D techniques has yet to be fully exploited. Secondary morphological features in nearby disk galaxies, such as bars, lenses, rings, disk breaks, and spiral arms, are seldom accounted for in 2D image decompositions, even though some image-fitting codes, such as GALFIT, are capable of handling them. We present detailed, 2D multi-model and multi-component decomposition of high-quality R -band images of a representative sample of nearby disk galaxies selected from the Carnegie-Irvine Galaxymore » Survey, using the latest version of GALFIT. The sample consists of five barred and five unbarred galaxies, spanning Hubble types from S0 to Sc. Traditional 1D decomposition is also presented for comparison. In detailed case studies of the 10 galaxies, we successfully model the secondary morphological features. Through a comparison of best-fit parameters obtained from different input surface brightness models, we identify morphological features that significantly impact bulge measurements. We show that nuclear and inner lenses/rings and disk breaks must be properly taken into account to obtain accurate bulge parameters, whereas outer lenses/rings and spiral arms have a negligible effect. We provide an optimal strategy to measure bulge parameters of typical disk galaxies, as well as prescriptions to estimate realistic uncertainties of them, which will benefit subsequent decomposition of a larger galaxy sample.« less

L'utilisation de la polarimetrie radar et de la decomposition de Touzi pour la caracterisation et la classification des physionomies vegetales des milieux humides : le cas du lac Saint-Pierre

NASA Astrophysics Data System (ADS)

Gosselin, Gabriel

Wetlands fill many important ecological functions and contribute to the biodiversity of fauna and flora. Although there is a growing recognition of the importance to protect these areas, it remains that their integrity is still threatened by the pressure of human activities. The inventory and the systematic monitoring of wetlands are a necessity and remote sensing is the only realistic way to achieve this goal. The primary objective of this thesis is to contribute and improve the wetland characterization using satellite polarimetric data acquired in L (ALOS-PALSAR) and C (RADARSAT-2) band. This thesis is based on two hypotheses (Ch. 1). The first hypothesis stipulate that classes of plant physiognomies, based on plant structure, are more appropriate than classes of plant species because they are best adapted to the information content of polarimetric radar data. The second hypothesis states that polarimetric decomposition algorithms allow an optimal extraction of polarimetric information compared to a multi-polarized approach based on the HH, HV and VV channels (Ch. 3). In particular, the contribution of the incoherent Touzi decomposition for the inventory and monitoring of wetlands is examined in detail. This decomposition allows the characterization of the scattering type, its phase, orientation, symmetry, degree of polarization and the backscattered power of a target with a series of parameters extracted from an analysis of the coherency matrix eigenvectors and eigenvalues. The lake Saint-Pierre region was chosen as the study site because of the great diversity of its wetlands that are covering more than 20 000 ha. One of the challenges posed by this thesis is that there is neither a standard system enumerating all the possible physiognomic classes nor an accurate description of their characteristics and dimensions. Special attention was given to the creation of these classes by combining several data sources and more than 50 plant species were grouped into nine physiognomic classes (Ch. 7, 8 and 9). Several analyzes are proposed to validate the hypotheses of this thesis (Ch. 9). Sensitivity analysis using scatter plots are performs to study the characteristics and dispersion of plant physiognomic classes in various features space consisting of polarimetric parameters or polarization channels (Ch. 10 and 12). Time series of made of RADARSAT-2 images are used to deepen the understanding of the seasonal evolution of plant physiognomies (Ch. 12). The transformed divergence algorithm is used to quantify the separability between physiognomic classes and to identify the parameters (s) that contribute the most to their separability (Ch. 11 and 13). Classifications are also proposed and the results compared to an existing map of the lake Saint-Pierre wetlands (Ch. 14). Finally, an analysis of the potential of polarimetric parameters in C and L-band is proposed for the monitoring of peatlands hydrology (Ch. 15 and 16). Sensitivity analyses show that the parameters of the 1st component, relative to the dominant (polarized) part of the signal, are sufficient for a general characterization of plant physiognomies. The parameters of the second and third components are, however, needed for better class separability (Ch. 11 and 13) and a better discrimination between wetlands and uplands (Ch. 14). This thesis shows that it is preferable to consider individually the parameters of the 1st, 2nd and 3rd components rather than their weighted sum by their respective eigenvalues (Ch. 10 and 12). This thesis also examines the complementarity between the structural parameters and those related to the backscattered power, often ignored and normalized by most polarimetric decomposition. (Abstract shortened by UMI.)

Tree decomposition based fast search of RNA structures including pseudoknots in genomes.

PubMed

Song, Yinglei; Liu, Chunmei; Malmberg, Russell; Pan, Fangfang; Cai, Liming

2005-01-01

Searching genomes for RNA secondary structure with computational methods has become an important approach to the annotation of non-coding RNAs. However, due to the lack of efficient algorithms for accurate RNA structure-sequence alignment, computer programs capable of fast and effectively searching genomes for RNA secondary structures have not been available. In this paper, a novel RNA structure profiling model is introduced based on the notion of a conformational graph to specify the consensus structure of an RNA family. Tree decomposition yields a small tree width t for such conformation graphs (e.g., t = 2 for stem loops and only a slight increase for pseudo-knots). Within this modelling framework, the optimal alignment of a sequence to the structure model corresponds to finding a maximum valued isomorphic subgraph and consequently can be accomplished through dynamic programming on the tree decomposition of the conformational graph in time O(k(t)N(2)), where k is a small parameter; and N is the size of the projiled RNA structure. Experiments show that the application of the alignment algorithm to search in genomes yields the same search accuracy as methods based on a Covariance model with a significant reduction in computation time. In particular; very accurate searches of tmRNAs in bacteria genomes and of telomerase RNAs in yeast genomes can be accomplished in days, as opposed to months required by other methods. The tree decomposition based searching tool is free upon request and can be downloaded at our site h t t p ://w.uga.edu/RNA-informatics/software/index.php.

Next Generation Anodes for Lithium-Ion Batteries: Thermodynamic Understanding and Abuse Performance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fenton, Kyle R.; Allcorn, Eric; Nagasubramanian, Ganesan

The objectives of this report are as follows: elucidate degradation mechanisms, decomposition products, and abuse response for next generation silicon based anodes; and Understand the contribution of various materials properties and cell build parameters towards thermal runaway enthalpies. Quantify the contributions from particle size, composition, state of charge (SOC), electrolyte to active materials ratio, etc.

Long-term litter decomposition controlled by manganese redox cycling

DOE PAGES

Keiluweit, Marco; Nico, Peter S.; Harmon, Mark; ...

2015-09-08

Litter decomposition is a keystone ecosystem process impacting nutrient cycling and productivity, soil properties, and the terrestrial carbon (C) balance, but the factors regulating decomposition rate are still poorly understood. Traditional models assume that the rate is controlled by litter quality, relying on parameters such as lignin content as predictors. However, a strong correlation has been observed between the manganese (Mn) content of litter and decomposition rates across a variety of forest ecosystems. Here, we show that long-term litter decomposition in forest ecosystems is tightly coupled to Mn redox cycling. Over 7 years of litter decomposition, microbial transformation of littermore » was paralleled by variations in Mn oxidation state and concentration. A detailed chemical imaging analysis of the litter revealed that fungi recruit and redistribute unreactive Mn 2+ provided by fresh plant litter to produce oxidative Mn 3+ species at sites of active decay, with Mn eventually accumulating as insoluble Mn 3+/4+ oxides. Formation of reactive Mn 3+ species coincided with the generation of aromatic oxidation products, providing direct proof of the previously posited role of Mn 3+-based oxidizers in the breakdown of litter. Our results suggest that the litter-decomposing machinery at our coniferous forest site depends on the ability of plants and microbes to supply, accumulate, and regenerate short-lived Mn 3+ species in the litter layer. As a result, this observation indicates that biogeochemical constraints on bioavailability, mobility, and reactivity of Mn in the plant–soil system may have a profound impact on litter decomposition rates.« less

Wall Shear Stress Distribution in a Patient-Specific Cerebral Aneurysm Model using Reduced Order Modeling

NASA Astrophysics Data System (ADS)

Han, Suyue; Chang, Gary Han; Schirmer, Clemens; Modarres-Sadeghi, Yahya

2016-11-01

We construct a reduced-order model (ROM) to study the Wall Shear Stress (WSS) distributions in image-based patient-specific aneurysms models. The magnitude of WSS has been shown to be a critical factor in growth and rupture of human aneurysms. We start the process by running a training case using Computational Fluid Dynamics (CFD) simulation with time-varying flow parameters, such that these parameters cover the range of parameters of interest. The method of snapshot Proper Orthogonal Decomposition (POD) is utilized to construct the reduced-order bases using the training CFD simulation. The resulting ROM enables us to study the flow patterns and the WSS distributions over a range of system parameters computationally very efficiently with a relatively small number of modes. This enables comprehensive analysis of the model system across a range of physiological conditions without the need to re-compute the simulation for small changes in the system parameters.

The effects of temperature on decomposition and allelopathic phytotoxicity of boneseed litter.

PubMed

Al Harun, Md Abdullah Yousuf; Johnson, Joshua; Uddin, Md Nazim; Robinson, Randall W

2015-07-01

Decomposition of plant litter is a fundamental process in ecosystem function, carbon and nutrient cycling and, by extension, climate change. This study aimed to investigate the role of temperature on the decomposition of water soluble phenolics (WSP), carbon and soil nutrients in conjunction with the phytotoxicity dynamics of Chrysanthemoides monilifera subsp. monilifera (boneseed) litter. Treatments consisted of three factors including decomposition materials (litter alone, litter with soil and soil alone), decomposition periods and temperatures (5-15, 15-25 and 25-35°C (night/day)). Leachates were collected on 0, 5, 10, 20, 40 and 60th days to analyse physico-chemical parameters and phytotoxicity. Water soluble phenolics and dissolved organic carbon (DOC) increased with increasing temperature while nutrients like SO4(-2) and NO3(-1) decreased. Speed of germination, hypocotyl and radical length and weight of Lactuca sativa exposed to leachates were decreased with increasing decomposition temperature. All treatment components had significant effects on these parameters. There had a strong correlation between DOC and WSP, and WSP content of the leachates with radical length of test species. This study identified complex interactivity among temperature, WSP, DOC and soil nutrient dynamics of litter occupied soil and that these factors work together to influence phytotoxicity. Copyright © 2015. Published by Elsevier B.V.

Adaptive fault feature extraction from wayside acoustic signals from train bearings

NASA Astrophysics Data System (ADS)

Zhang, Dingcheng; Entezami, Mani; Stewart, Edward; Roberts, Clive; Yu, Dejie

2018-07-01

Wayside acoustic detection of train bearing faults plays a significant role in maintaining safety in the railway transport system. However, the bearing fault information is normally masked by strong background noises and harmonic interferences generated by other components (e.g. axles and gears). In order to extract the bearing fault feature information effectively, a novel method called improved singular value decomposition (ISVD) with resonance-based signal sparse decomposition (RSSD), namely the ISVD-RSSD method, is proposed in this paper. A Savitzky-Golay (S-G) smoothing filter is used to filter singular vectors (SVs) in the ISVD method as an extension of the singular value decomposition (SVD) theorem. Hilbert spectrum entropy and a stepwise optimisation strategy are used to optimize the S-G filter's parameters. The RSSD method is able to nonlinearly decompose the wayside acoustic signal of a faulty train bearing into high and low resonance components, the latter of which contains bearing fault information. However, the high level of noise usually results in poor decomposition results from the RSSD method. Hence, the collected wayside acoustic signal must first be de-noised using the ISVD component of the ISVD-RSSD method. Next, the de-noised signal is decomposed by using the RSSD method. The obtained low resonance component is then demodulated with a Hilbert transform such that the bearing fault can be detected by observing Hilbert envelope spectra. The effectiveness of the ISVD-RSSD method is verified through both laboratory field-based experiments as described in the paper. The results indicate that the proposed method is superior to conventional spectrum analysis and ensemble empirical mode decomposition methods.

Sensor-Based Vibration Signal Feature Extraction Using an Improved Composite Dictionary Matching Pursuit Algorithm

PubMed Central

Cui, Lingli; Wu, Na; Wang, Wenjing; Kang, Chenhui

2014-01-01

This paper presents a new method for a composite dictionary matching pursuit algorithm, which is applied to vibration sensor signal feature extraction and fault diagnosis of a gearbox. Three advantages are highlighted in the new method. First, the composite dictionary in the algorithm has been changed from multi-atom matching to single-atom matching. Compared to non-composite dictionary single-atom matching, the original composite dictionary multi-atom matching pursuit (CD-MaMP) algorithm can achieve noise reduction in the reconstruction stage, but it cannot dramatically reduce the computational cost and improve the efficiency in the decomposition stage. Therefore, the optimized composite dictionary single-atom matching algorithm (CD-SaMP) is proposed. Second, the termination condition of iteration based on the attenuation coefficient is put forward to improve the sparsity and efficiency of the algorithm, which adjusts the parameters of the termination condition constantly in the process of decomposition to avoid noise. Third, composite dictionaries are enriched with the modulation dictionary, which is one of the important structural characteristics of gear fault signals. Meanwhile, the termination condition of iteration settings, sub-feature dictionary selections and operation efficiency between CD-MaMP and CD-SaMP are discussed, aiming at gear simulation vibration signals with noise. The simulation sensor-based vibration signal results show that the termination condition of iteration based on the attenuation coefficient enhances decomposition sparsity greatly and achieves a good effect of noise reduction. Furthermore, the modulation dictionary achieves a better matching effect compared to the Fourier dictionary, and CD-SaMP has a great advantage of sparsity and efficiency compared with the CD-MaMP. The sensor-based vibration signals measured from practical engineering gearbox analyses have further shown that the CD-SaMP decomposition and reconstruction algorithm is feasible and effective. PMID:25207870

Sensor-based vibration signal feature extraction using an improved composite dictionary matching pursuit algorithm.

PubMed

Cui, Lingli; Wu, Na; Wang, Wenjing; Kang, Chenhui

2014-09-09

This paper presents a new method for a composite dictionary matching pursuit algorithm, which is applied to vibration sensor signal feature extraction and fault diagnosis of a gearbox. Three advantages are highlighted in the new method. First, the composite dictionary in the algorithm has been changed from multi-atom matching to single-atom matching. Compared to non-composite dictionary single-atom matching, the original composite dictionary multi-atom matching pursuit (CD-MaMP) algorithm can achieve noise reduction in the reconstruction stage, but it cannot dramatically reduce the computational cost and improve the efficiency in the decomposition stage. Therefore, the optimized composite dictionary single-atom matching algorithm (CD-SaMP) is proposed. Second, the termination condition of iteration based on the attenuation coefficient is put forward to improve the sparsity and efficiency of the algorithm, which adjusts the parameters of the termination condition constantly in the process of decomposition to avoid noise. Third, composite dictionaries are enriched with the modulation dictionary, which is one of the important structural characteristics of gear fault signals. Meanwhile, the termination condition of iteration settings, sub-feature dictionary selections and operation efficiency between CD-MaMP and CD-SaMP are discussed, aiming at gear simulation vibration signals with noise. The simulation sensor-based vibration signal results show that the termination condition of iteration based on the attenuation coefficient enhances decomposition sparsity greatly and achieves a good effect of noise reduction. Furthermore, the modulation dictionary achieves a better matching effect compared to the Fourier dictionary, and CD-SaMP has a great advantage of sparsity and efficiency compared with the CD-MaMP. The sensor-based vibration signals measured from practical engineering gearbox analyses have further shown that the CD-SaMP decomposition and reconstruction algorithm is feasible and effective.

Estimation of beech pyrolysis kinetic parameters by Shuffled Complex Evolution.

PubMed

Ding, Yanming; Wang, Changjian; Chaos, Marcos; Chen, Ruiyu; Lu, Shouxiang

2016-01-01

The pyrolysis kinetics of a typical biomass energy feedstock, beech, was investigated based on thermogravimetric analysis over a wide heating rate range from 5K/min to 80K/min. A three-component (corresponding to hemicellulose, cellulose and lignin) parallel decomposition reaction scheme was applied to describe the experimental data. The resulting kinetic reaction model was coupled to an evolutionary optimization algorithm (Shuffled Complex Evolution, SCE) to obtain model parameters. To the authors' knowledge, this is the first study in which SCE has been used in the context of thermogravimetry. The kinetic parameters were simultaneously optimized against data for 10, 20 and 60K/min heating rates, providing excellent fits to experimental data. Furthermore, it was shown that the optimized parameters were applicable to heating rates (5 and 80K/min) beyond those used to generate them. Finally, the predicted results based on optimized parameters were contrasted with those based on the literature. Copyright © 2015 Elsevier Ltd. All rights reserved.

Spectral response model for a multibin photon-counting spectral computed tomography detector and its applications.

PubMed

Liu, Xuejin; Persson, Mats; Bornefalk, Hans; Karlsson, Staffan; Xu, Cheng; Danielsson, Mats; Huber, Ben

2015-07-01

Variations among detector channels in computed tomography can lead to ring artifacts in the reconstructed images and biased estimates in projection-based material decomposition. Typically, the ring artifacts are corrected by compensation methods based on flat fielding, where transmission measurements are required for a number of material-thickness combinations. Phantoms used in these methods can be rather complex and require an extensive number of transmission measurements. Moreover, material decomposition needs knowledge of the individual response of each detector channel to account for the detector inhomogeneities. For this purpose, we have developed a spectral response model that binwise predicts the response of a multibin photon-counting detector individually for each detector channel. The spectral response model is performed in two steps. The first step employs a forward model to predict the expected numbers of photon counts, taking into account parameters such as the incident x-ray spectrum, absorption efficiency, and energy response of the detector. The second step utilizes a limited number of transmission measurements with a set of flat slabs of two absorber materials to fine-tune the model predictions, resulting in a good correspondence with the physical measurements. To verify the response model, we apply the model in two cases. First, the model is used in combination with a compensation method which requires an extensive number of transmission measurements to determine the necessary parameters. Our spectral response model successfully replaces these measurements by simulations, saving a significant amount of measurement time. Second, the spectral response model is used as the basis of the maximum likelihood approach for projection-based material decomposition. The reconstructed basis images show a good separation between the calcium-like material and the contrast agents, iodine and gadolinium. The contrast agent concentrations are reconstructed with more than 94% accuracy.

Spectral response model for a multibin photon-counting spectral computed tomography detector and its applications

PubMed Central

Liu, Xuejin; Persson, Mats; Bornefalk, Hans; Karlsson, Staffan; Xu, Cheng; Danielsson, Mats; Huber, Ben

2015-01-01

Abstract. Variations among detector channels in computed tomography can lead to ring artifacts in the reconstructed images and biased estimates in projection-based material decomposition. Typically, the ring artifacts are corrected by compensation methods based on flat fielding, where transmission measurements are required for a number of material-thickness combinations. Phantoms used in these methods can be rather complex and require an extensive number of transmission measurements. Moreover, material decomposition needs knowledge of the individual response of each detector channel to account for the detector inhomogeneities. For this purpose, we have developed a spectral response model that binwise predicts the response of a multibin photon-counting detector individually for each detector channel. The spectral response model is performed in two steps. The first step employs a forward model to predict the expected numbers of photon counts, taking into account parameters such as the incident x-ray spectrum, absorption efficiency, and energy response of the detector. The second step utilizes a limited number of transmission measurements with a set of flat slabs of two absorber materials to fine-tune the model predictions, resulting in a good correspondence with the physical measurements. To verify the response model, we apply the model in two cases. First, the model is used in combination with a compensation method which requires an extensive number of transmission measurements to determine the necessary parameters. Our spectral response model successfully replaces these measurements by simulations, saving a significant amount of measurement time. Second, the spectral response model is used as the basis of the maximum likelihood approach for projection-based material decomposition. The reconstructed basis images show a good separation between the calcium-like material and the contrast agents, iodine and gadolinium. The contrast agent concentrations are reconstructed with more than 94% accuracy. PMID:26839904

Use of Direct Dynamics Simulations to Determine Unimolecular Reaction Paths and Arrhenius Parameters for Large Molecules.

PubMed

Yang, Li; Sun, Rui; Hase, William L

2011-11-08

In a previous study (J. Chem. Phys.2008, 129, 094701) it was shown that for a large molecule, with a total energy much greater than its barrier for decomposition and whose vibrational modes are harmonic oscillators, the expressions for the classical Rice-Ramsperger-Kassel-Marcus (RRKM) (i.e., RRK) and classical transition-state theory (TST) rate constants become equivalent. Using this relationship, a molecule's unimolecular rate constants versus temperature may be determined from chemical dynamics simulations of microcanonical ensembles for the molecule at different total energies. The simulation identifies the molecule's unimolecular pathways and their Arrhenius parameters. In the work presented here, this approach is used to study the thermal decomposition of CH3-NH-CH═CH-CH3, an important constituent in the polymer of cross-linked epoxy resins. Direct dynamics simulations, at the MP2/6-31+G* level of theory, were used to investigate the decomposition of microcanonical ensembles for this molecule. The Arrhenius A and Ea parameters determined from the direct dynamics simulation are in very good agreement with the TST Arrhenius parameters for the MP2/6-31+G* potential energy surface. The simulation method applied here may be particularly useful for large molecules with a multitude of decomposition pathways and whose transition states may be difficult to determine and have structures that are not readily obvious.

Reduced-order modelling of parameter-dependent, linear and nonlinear dynamic partial differential equation models.

PubMed

Shah, A A; Xing, W W; Triantafyllidis, V

2017-04-01

In this paper, we develop reduced-order models for dynamic, parameter-dependent, linear and nonlinear partial differential equations using proper orthogonal decomposition (POD). The main challenges are to accurately and efficiently approximate the POD bases for new parameter values and, in the case of nonlinear problems, to efficiently handle the nonlinear terms. We use a Bayesian nonlinear regression approach to learn the snapshots of the solutions and the nonlinearities for new parameter values. Computational efficiency is ensured by using manifold learning to perform the emulation in a low-dimensional space. The accuracy of the method is demonstrated on a linear and a nonlinear example, with comparisons with a global basis approach.

Reduced-order modelling of parameter-dependent, linear and nonlinear dynamic partial differential equation models

PubMed Central

Xing, W. W.; Triantafyllidis, V.

2017-01-01

In this paper, we develop reduced-order models for dynamic, parameter-dependent, linear and nonlinear partial differential equations using proper orthogonal decomposition (POD). The main challenges are to accurately and efficiently approximate the POD bases for new parameter values and, in the case of nonlinear problems, to efficiently handle the nonlinear terms. We use a Bayesian nonlinear regression approach to learn the snapshots of the solutions and the nonlinearities for new parameter values. Computational efficiency is ensured by using manifold learning to perform the emulation in a low-dimensional space. The accuracy of the method is demonstrated on a linear and a nonlinear example, with comparisons with a global basis approach. PMID:28484327

Fault Detection of Bearing Systems through EEMD and Optimization Algorithm

PubMed Central

Lee, Dong-Han; Ahn, Jong-Hyo; Koh, Bong-Hwan

2017-01-01

This study proposes a fault detection and diagnosis method for bearing systems using ensemble empirical mode decomposition (EEMD) based feature extraction, in conjunction with particle swarm optimization (PSO), principal component analysis (PCA), and Isomap. First, a mathematical model is assumed to generate vibration signals from damaged bearing components, such as the inner-race, outer-race, and rolling elements. The process of decomposing vibration signals into intrinsic mode functions (IMFs) and extracting statistical features is introduced to develop a damage-sensitive parameter vector. Finally, PCA and Isomap algorithm are used to classify and visualize this parameter vector, to separate damage characteristics from healthy bearing components. Moreover, the PSO-based optimization algorithm improves the classification performance by selecting proper weightings for the parameter vector, to maximize the visualization effect of separating and grouping of parameter vectors in three-dimensional space. PMID:29143772

Comparative kinetic analysis on thermal degradation of some cephalosporins using TG and DSC data

PubMed Central

2013-01-01

Background The thermal decomposition of cephalexine, cefadroxil and cefoperazone under non-isothermal conditions using the TG, respectively DSC methods, was studied. In case of TG, a hyphenated technique, including EGA, was used. Results The kinetic analysis was performed using the TG and DSC data in air for the first step of cephalosporin’s decomposition at four heating rates. The both TG and DSC data were processed according to an appropriate strategy to the following kinetic methods: Kissinger-Akahira-Sunose, Friedman, and NPK, in order to obtain realistic kinetic parameters, even if the decomposition process is a complex one. The EGA data offer some valuable indications about a possible decomposition mechanism. The obtained data indicate a rather good agreement between the activation energy’s values obtained by different methods, whereas the EGA data and the chemical structures give a possible explanation of the observed differences on the thermal stability. A complete kinetic analysis needs a data processing strategy using two or more methods, but the kinetic methods must also be applied to the different types of experimental data (TG and DSC). Conclusion The simultaneous use of DSC and TG data for the kinetic analysis coupled with evolved gas analysis (EGA) provided us a more complete picture of the degradation of the three cephalosporins. It was possible to estimate kinetic parameters by using three different kinetic methods and this allowed us to compare the Ea values obtained from different experimental data, TG and DSC. The thermodegradation being a complex process, the both differential and integral methods based on the single step hypothesis are inadequate for obtaining believable kinetic parameters. Only the modified NPK method allowed an objective separation of the temperature, respective conversion influence on the reaction rate and in the same time to ascertain the existence of two simultaneous steps. PMID:23594763

A Wavelet-Based Methodology for Grinding Wheel Condition Monitoring

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liao, T. W.; Ting, C.F.; Qu, Jun

2007-01-01

Grinding wheel surface condition changes as more material is removed. This paper presents a wavelet-based methodology for grinding wheel condition monitoring based on acoustic emission (AE) signals. Grinding experiments in creep feed mode were conducted to grind alumina specimens with a resinoid-bonded diamond wheel using two different conditions. During the experiments, AE signals were collected when the wheel was 'sharp' and when the wheel was 'dull'. Discriminant features were then extracted from each raw AE signal segment using the discrete wavelet decomposition procedure. An adaptive genetic clustering algorithm was finally applied to the extracted features in order to distinguish differentmore » states of grinding wheel condition. The test results indicate that the proposed methodology can achieve 97% clustering accuracy for the high material removal rate condition, 86.7% for the low material removal rate condition, and 76.7% for the combined grinding conditions if the base wavelet, the decomposition level, and the GA parameters are properly selected.« less

Data decomposition of Monte Carlo particle transport simulations via tally servers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Romano, Paul K.; Siegel, Andrew R.; Forget, Benoit

An algorithm for decomposing large tally data in Monte Carlo particle transport simulations is developed, analyzed, and implemented in a continuous-energy Monte Carlo code, OpenMC. The algorithm is based on a non-overlapping decomposition of compute nodes into tracking processors and tally servers. The former are used to simulate the movement of particles through the domain while the latter continuously receive and update tally data. A performance model for this approach is developed, suggesting that, for a range of parameters relevant to LWR analysis, the tally server algorithm should perform with minimal overhead on contemporary supercomputers. An implementation of the algorithmmore » in OpenMC is then tested on the Intrepid and Titan supercomputers, supporting the key predictions of the model over a wide range of parameters. We thus conclude that the tally server algorithm is a successful approach to circumventing classical on-node memory constraints en route to unprecedentedly detailed Monte Carlo reactor simulations.« less

Cross-biome transplants of plant litter show decomposition models extend to a broader climatic range but lose predictability at the decadal time scale

Treesearch

William S. Currie; Mark E. Harmon; Ingrid C. Burke; Stephen C. Hart; William J. Parton; Whendee L. Silver

2009-01-01

We analyzed results from 10-year long field incubations of foliar and fine root litter from the Long-term lntersite Decomposition Experiment Team (LIDET) study. We tested whether a variety of climate and litter quality variables could be used to develop regression models of decomposition parameters across wide ranges in litter quality and climate and whether these...

Wavelet-based statistical classification of skin images acquired with reflectance confocal microscopy

PubMed Central

Halimi, Abdelghafour; Batatia, Hadj; Le Digabel, Jimmy; Josse, Gwendal; Tourneret, Jean Yves

2017-01-01

Detecting skin lentigo in reflectance confocal microscopy images is an important and challenging problem. This imaging modality has not yet been widely investigated for this problem and there are a few automatic processing techniques. They are mostly based on machine learning approaches and rely on numerous classical image features that lead to high computational costs given the very large resolution of these images. This paper presents a detection method with very low computational complexity that is able to identify the skin depth at which the lentigo can be detected. The proposed method performs multiresolution decomposition of the image obtained at each skin depth. The distribution of image pixels at a given depth can be approximated accurately by a generalized Gaussian distribution whose parameters depend on the decomposition scale, resulting in a very-low-dimension parameter space. SVM classifiers are then investigated to classify the scale parameter of this distribution allowing real-time detection of lentigo. The method is applied to 45 healthy and lentigo patients from a clinical study, where sensitivity of 81.4% and specificity of 83.3% are achieved. Our results show that lentigo is identifiable at depths between 50μm and 60μm, corresponding to the average location of the the dermoepidermal junction. This result is in agreement with the clinical practices that characterize the lentigo by assessing the disorganization of the dermoepidermal junction. PMID:29296480

Evaluation of moving-coil loudspeaker and passive radiator parameters using normal-incidence sound transmission measurements: theoretical developments.

PubMed

Leishman, Timothy W; Anderson, Brian E

2013-07-01

The parameters of moving-coil loudspeaker drivers are typically determined using direct electrical excitation and measurement. However, as electro-mechano-acoustical devices, their parameters should also follow from suitable mechanical or acoustical evaluations. This paper presents the theory of an acoustical method of excitation and measurement using normal-incidence sound transmission through a baffled driver as a plane-wave tube partition. Analogous circuits enable key parameters to be extracted from measurement results in terms of open and closed-circuit driver conditions. Associated tools are presented that facilitate adjacent field decompositions and derivations of sound transmission coefficients (in terms of driver parameters) directly from the circuits. The paper also clarifies the impact of nonanechoic receiving tube terminations and the specific benefits of downstream field decompositions.

Moisture can be the dominant environmental parameter governing cadaver decomposition in soil.

PubMed

Carter, David O; Yellowlees, David; Tibbett, Mark

2010-07-15

Forensic taphonomy involves the use of decomposition to estimate postmortem interval (PMI) or locate clandestine graves. Yet, cadaver decomposition remains poorly understood, particularly following burial in soil. Presently, we do not know how most edaphic and environmental parameters, including soil moisture, influence the breakdown of cadavers following burial and alter the processes that are used to estimate PMI and locate clandestine graves. To address this, we buried juvenile rat (Rattus rattus) cadavers (approximately 18 g wet weight) in three contrasting soils from tropical savanna ecosystems located in Pallarenda (sand), Wambiana (medium clay), or Yabulu (loamy sand), Queensland, Australia. These soils were sieved (2mm), weighed (500 g dry weight), calibrated to a matric potential of -0.01 megapascals (MPa), -0.05 MPa, or -0.3 MPa (wettest to driest) and incubated at 22 degrees C. Measurements of cadaver decomposition included cadaver mass loss, carbon dioxide-carbon (CO(2)-C) evolution, microbial biomass carbon (MBC), protease activity, phosphodiesterase activity, ninhydrin-reactive nitrogen (NRN) and soil pH. Cadaver burial resulted in a significant increase in CO(2)-C evolution, MBC, enzyme activities, NRN and soil pH. Cadaver decomposition in loamy sand and sandy soil was greater at lower matric potentials (wetter soil). However, optimal matric potential for cadaver decomposition in medium clay was exceeded, which resulted in a slower rate of cadaver decomposition in the wettest soil. Slower cadaver decomposition was also observed at high matric potential (-0.3 MPa). Furthermore, wet sandy soil was associated with greater cadaver decomposition than wet fine-textured soil. We conclude that gravesoil moisture content can modify the relationship between temperature and cadaver decomposition and that soil microorganisms can play a significant role in cadaver breakdown. We also conclude that soil NRN is a more reliable indicator of gravesoil than soil pH. (c) 2010 Elsevier Ireland Ltd. All rights reserved.

Experimental Modal Analysis and Dynamic Component Synthesis. Volume 3. Modal Parameter Estimation

DTIC Science & Technology

1987-12-01

residues as well as poles is achieved. A singular value decomposition method has been used to develop a complex mode indicator function ( CMIF )[70...which can be used to help determine the number of poles before the analysis. The CMIF is formed by performing a singular value decomposition of all of...servo systems which can include both low and high damping modes. "• CMIF can be used to indicate close or repeated eigenvalues before the parameter

Influence of gamma-irradiation on the non-isothermal decomposition of calcium-gadolinium oxalate

NASA Astrophysics Data System (ADS)

Moharana, S. C.; Praharaj, J.; Bhatta, D.

Thermal decomposition of co-precipitated unirradiated and irradiated Ca-Gd oxalate has been studied by adopting differential thermal analysis (DTA) and thermogravimetric (TG) techniques. The reaction occurs through two stages corresponding to the decomposition of gadolinium oxalate (Gd-Ox) followed by that of calcium oxalate (Ca-Ox). The kinetic parameters for both the stages are calculated by using solid state reaction models and Coats-Redfern's equation. The co-precipitation as well as irradiation alter the DTA peak temperatures and the kinetic parameters of Ca-Ox. The decomposition of Gd-Ox follows the two dimensional Contracting area (R-2) mechanism, while that of Ca-Ox follows the Avrami-Erofeev (A(2)) mechanism (n =2), which are also exhibited by the co-precipitated and irradiated samples. Co-precipitation decreases the energy of activation and the pre-exponential factor of the individual components but the reverse phenomenon takes place upon irradiation of the co-precipitate. The mechanisms underlying the phenomena are explored.

Synthesis and characterization of an energetic compound Cu(Mtta)2(NO3)2 and effect on thermal decomposition of ammonium perchlorate.

PubMed

Yang, Qi; Chen, Sanping; Xie, Gang; Gao, Shengli

2011-12-15

An energetic coordination compound Cu(Mtta)(2)(NO(3))(2) has been synthesized by using 1-methyltetrazole (Mtta) as ligand and its structure has been characterized by X-ray single crystal diffraction. The central copper (II) cation was coordinated by four O atoms from two Mtta ligands and two N atoms from two NO(3)(-) anions to form a six-coordinated and distorted octahedral structure. 2D superamolecular layer structure was formed by the extensive intermolecular hydrogen bonds between Mtta ligands and NO(3)(-) anions. Thermal decomposition process of the compound was predicted based on DSC and TG-DTG analyses results. The kinetic parameters of the first exothermic process of the compound were studied by the Kissinger's and Ozawa-Doyle's methods. Sensitivity tests revealed that the compound was insensitive to mechanical stimuli. In addition, compound was explored as additive to promote the thermal decomposition of ammonium perchlorate (AP) by differential scanning calorimetry. Copyright © 2011 Elsevier B.V. All rights reserved.

A reduced-order model for compressible flows with buffeting condition using higher order dynamic mode decomposition with a mode selection criterion

NASA Astrophysics Data System (ADS)

Kou, Jiaqing; Le Clainche, Soledad; Zhang, Weiwei

2018-01-01

This study proposes an improvement in the performance of reduced-order models (ROMs) based on dynamic mode decomposition to model the flow dynamics of the attractor from a transient solution. By combining higher order dynamic mode decomposition (HODMD) with an efficient mode selection criterion, the HODMD with criterion (HODMDc) ROM is able to identify dominant flow patterns with high accuracy. This helps us to develop a more parsimonious ROM structure, allowing better predictions of the attractor dynamics. The method is tested in the solution of a NACA0012 airfoil buffeting in a transonic flow, and its good performance in both the reconstruction of the original solution and the prediction of the permanent dynamics is shown. In addition, the robustness of the method has been successfully tested using different types of parameters, indicating that the proposed ROM approach is a tool promising for using in both numerical simulations and experimental data.

Sensory irritation and incapacitation evoked by thermal decomposition products of polymers and comparisons with known sensory irritants.

PubMed

Barrow, C S; Alarie, Y; Stock, M F

1978-01-01

A decrease in respiratory rate in mice during exposure to irritating airborne chemicals has been utilized as a response parameter to characterize the degree of upper respiratory tract irritation (sensory irritation) to the thermal decomposition products of various polymers. These included polystyrene, polyvinyl chloride, flexible polyurethane foam, polytetrafluorethylene, a fiber glass reinforced polyester resin, and Douglas Fir. Each of the materials was thermally decomposed in a low-mass vertical furnace in an air atmosphere at a programmed heating rate of 20 degrees C/min. Mice, in groups of four, were exposed to graded concentrations of the thermal decomposition products of each of the above materials. Dose-response curves were obtained by utilizing the maximum percent decrease in respiratory rate as the response parameter during each exposure. Comparison of these dose-response curves with other sensory irritants such as chlorine, ammonia, hydrogen chloride, sulfur dioxide, and toluene diisocyanate gave an indication of the sensory irrtation potential of the thermal decomposition products of these various polymers versus that of well-known single airborne chemical irritants. Total stress and incapacitation of the organism during exposure to sensory irritants such as from the thermal decomposition products of synthetic polymers is discussed.

Knowledge-based approach to system integration

NASA Technical Reports Server (NTRS)

Blokland, W.; Krishnamurthy, C.; Biegl, C.; Sztipanovits, J.

1988-01-01

To solve complex problems one can often use the decomposition principle. However, a problem is seldom decomposable into completely independent subproblems. System integration deals with problem of resolving the interdependencies and the integration of the subsolutions. A natural method of decomposition is the hierarchical one. High-level specifications are broken down into lower level specifications until they can be transformed into solutions relatively easily. By automating the hierarchical decomposition and solution generation an integrated system is obtained in which the declaration of high level specifications is enough to solve the problem. We offer a knowledge-based approach to integrate the development and building of control systems. The process modeling is supported by using graphic editors. The user selects and connects icons that represent subprocesses and might refer to prewritten programs. The graphical editor assists the user in selecting parameters for each subprocess and allows the testing of a specific configuration. Next, from the definitions created by the graphical editor, the actual control program is built. Fault-diagnosis routines are generated automatically as well. Since the user is not required to write program code and knowledge about the process is present in the development system, the user is not required to have expertise in many fields.

Bayesian Hierarchical Grouping: perceptual grouping as mixture estimation

PubMed Central

Froyen, Vicky; Feldman, Jacob; Singh, Manish

2015-01-01

We propose a novel framework for perceptual grouping based on the idea of mixture models, called Bayesian Hierarchical Grouping (BHG). In BHG we assume that the configuration of image elements is generated by a mixture of distinct objects, each of which generates image elements according to some generative assumptions. Grouping, in this framework, means estimating the number and the parameters of the mixture components that generated the image, including estimating which image elements are “owned” by which objects. We present a tractable implementation of the framework, based on the hierarchical clustering approach of Heller and Ghahramani (2005). We illustrate it with examples drawn from a number of classical perceptual grouping problems, including dot clustering, contour integration, and part decomposition. Our approach yields an intuitive hierarchical representation of image elements, giving an explicit decomposition of the image into mixture components, along with estimates of the probability of various candidate decompositions. We show that BHG accounts well for a diverse range of empirical data drawn from the literature. Because BHG provides a principled quantification of the plausibility of grouping interpretations over a wide range of grouping problems, we argue that it provides an appealing unifying account of the elusive Gestalt notion of Prägnanz. PMID:26322548

Towards a paradigm shift in the modeling of soil organic carbon decomposition for earth system models

NASA Astrophysics Data System (ADS)

He, Yujie

Soils are the largest terrestrial carbon pools and contain approximately 2200 Pg of carbon. Thus, the dynamics of soil carbon plays an important role in the global carbon cycle and climate system. Earth System Models are used to project future interactions between terrestrial ecosystem carbon dynamics and climate. However, these models often predict a wide range of soil carbon responses and their formulations have lagged behind recent soil science advances, omitting key biogeochemical mechanisms. In contrast, recent mechanistically-based biogeochemical models that explicitly account for microbial biomass pools and enzyme kinetics that catalyze soil carbon decomposition produce notably different results and provide a closer match to recent observations. However, a systematic evaluation of the advantages and disadvantages of the microbial models and how they differ from empirical, first-order formulations in soil decomposition models for soil organic carbon is still needed. This dissertation consists of a series of model sensitivity and uncertainty analyses and identifies dominant decomposition processes in determining soil organic carbon dynamics. Poorly constrained processes or parameters that require more experimental data integration are also identified. This dissertation also demonstrates the critical role of microbial life-history traits (e.g. microbial dormancy) in the modeling of microbial activity in soil organic matter decomposition models. Finally, this study surveys and synthesizes a number of recently published microbial models and provides suggestions for future microbial model developments.

Interacting Microbe and Litter Quality Controls on Litter Decomposition: A Modeling Analysis

PubMed Central

Moorhead, Daryl; Lashermes, Gwenaëlle; Recous, Sylvie; Bertrand, Isabelle

2014-01-01

The decomposition of plant litter in soil is a dynamic process during which substrate chemistry and microbial controls interact. We more clearly quantify these controls with a revised version of the Guild-based Decomposition Model (GDM) in which we used a reverse Michaelis-Menten approach to simulate short-term (112 days) decomposition of roots from four genotypes of Zea mays that differed primarily in lignin chemistry. A co-metabolic relationship between the degradation of lignin and holocellulose (cellulose+hemicellulose) fractions of litter showed that the reduction in decay rate with increasing lignin concentration (LCI) was related to the level of arabinan substitutions in arabinoxylan chains (i.e., arabinan to xylan or A∶X ratio) and the extent to which hemicellulose chains are cross-linked with lignin in plant cell walls. This pattern was consistent between genotypes and during progressive decomposition within each genotype. Moreover, decay rates were controlled by these cross-linkages from the start of decomposition. We also discovered it necessary to divide the Van Soest soluble (labile) fraction of litter C into two pools: one that rapidly decomposed and a second that was more persistent. Simulated microbial production was consistent with recent studies suggesting that more rapidly decomposing materials can generate greater amounts of potentially recalcitrant microbial products despite the rapid loss of litter mass. Sensitivity analyses failed to identify any model parameter that consistently explained a large proportion of model variation, suggesting that feedback controls between litter quality and microbial activity in the reverse Michaelis-Menten approach resulted in stable model behavior. Model extrapolations to an independent set of data, derived from the decomposition of 12 different genotypes of maize roots, averaged within <3% of observed respiration rates and total CO2 efflux over 112 days. PMID:25264895

Full-envelope aerodynamic modeling of the Harrier aircraft

NASA Technical Reports Server (NTRS)

Mcnally, B. David

1986-01-01

A project to identify a full-envelope model of the YAV-8B Harrier using flight-test and parameter identification techniques is described. As part of the research in advanced control and display concepts for V/STOL aircraft, a full-envelope aerodynamic model of the Harrier is identified, using mathematical model structures and parameter identification methods. A global-polynomial model structure is also used as a basis for the identification of the YAV-8B aerodynamic model. State estimation methods are used to ensure flight data consistency prior to parameter identification.Equation-error methods are used to identify model parameters. A fixed-base simulator is used extensively to develop flight test procedures and to validate parameter identification software. Using simple flight maneuvers, a simulated data set was created covering the YAV-8B flight envelope from about 0.3 to 0.7 Mach and about -5 to 15 deg angle of attack. A singular value decomposition implementation of the equation-error approach produced good parameter estimates based on this simulated data set.

Gas Sensing Analysis of Ag-Decorated Graphene for Sulfur Hexafluoride Decomposition Products Based on the Density Functional Theory

PubMed Central

Zhang, Xiaoxing; Huang, Rong; Gui, Yingang; Zeng, Hong

2016-01-01

Detection of decomposition products of sulfur hexafluoride (SF6) is one of the best ways to diagnose early latent insulation faults in gas-insulated equipment, and the occurrence of sudden accidents can be avoided effectively by finding early latent faults. Recently, functionalized graphene, a kind of gas sensing material, has been reported to show good application prospects in the gas sensor field. Therefore, calculations were performed to analyze the gas sensing properties of intrinsic graphene (Int-graphene) and functionalized graphene-based material, Ag-decorated graphene (Ag-graphene), for decomposition products of SF6, including SO2F2, SOF2, and SO2, based on density functional theory (DFT). We thoroughly investigated a series of parameters presenting gas-sensing properties of adsorbing process about gas molecule (SO2F2, SOF2, SO2) and double gas molecules (2SO2F2, 2SOF2, 2SO2) on Ag-graphene, including adsorption energy, net charge transfer, electronic state density, and the highest and lowest unoccupied molecular orbital. The results showed that the Ag atom significantly enhances the electrochemical reactivity of graphene, reflected in the change of conductivity during the adsorption process. SO2F2 and SO2 gas molecules on Ag-graphene presented chemisorption, and the adsorption strength was SO2F2 > SO2, while SOF2 absorption on Ag-graphene was physical adsorption. Thus, we concluded that Ag-graphene showed good selectivity and high sensitivity to SO2F2. The results can provide a helpful guide in exploring Ag-graphene material in experiments for monitoring the insulation status of SF6-insulated equipment based on detecting decomposition products of SF6. PMID:27809269

Determination of Kinetic Parameters for the Thermal Decomposition of Parthenium hysterophorus

NASA Astrophysics Data System (ADS)

Dhaundiyal, Alok; Singh, Suraj B.; Hanon, Muammel M.; Rawat, Rekha

2018-02-01

A kinetic study of pyrolysis process of Parthenium hysterophorous is carried out by using thermogravimetric analysis (TGA) equipment. The present study investigates the thermal degradation and determination of the kinetic parameters such as activation E and the frequency factor A using model-free methods given by Flynn Wall and Ozawa (FWO), Kissinger-Akahira-Sonuse (KAS) and Kissinger, and model-fitting (Coats Redfern). The results derived from thermal decomposition process demarcate decomposition of Parthenium hysterophorous among the three main stages, such as dehydration, active and passive pyrolysis. It is shown through DTG thermograms that the increase in the heating rate caused temperature peaks at maximum weight loss rate to shift towards higher temperature regime. The results are compared with Coats Redfern (Integral method) and experimental results have shown that values of kinetic parameters obtained from model-free methods are in good agreement. Whereas the results obtained through Coats Redfern model at different heating rates are not promising, however, the diffusion models provided the good fitting with the experimental data.

Size-controlled magnetic nanoparticles with lecithin for biomedical applications

NASA Astrophysics Data System (ADS)

Park, S. I.; Kim, J. H.; Kim, C. G.; Kim, C. O.

2007-05-01

Lecithin-adsorbed magnetic nanoparticles were prepared by three-step process that the thermal decomposition was combined with ultrasonication. Experimental parameters were three items—molar ratio between Fe(CO) 5 and oleic acid, keeping time at decomposition temperature and lecithin concentration. As the molar ratio between Fe(CO) 5 and oleic acid, and keeping time at decomposition temperature increased, the particle size increased. However, the change of lecithin concentration did not show the remarkable particle size variation.

Estimation of slip distribution using an inverse method based on spectral decomposition of Green's function utilizing Global Positioning System (GPS) data

NASA Astrophysics Data System (ADS)

Jin, Honglin; Kato, Teruyuki; Hori, Muneo

2007-07-01

An inverse method based on the spectral decomposition of the Green's function was employed for estimating a slip distribution. We conducted numerical simulations along the Philippine Sea plate (PH) boundary in southwest Japan using this method to examine how to determine the essential parameters which are the number of deformation function modes and their coefficients. Japanese GPS Earth Observation Network (GEONET) Global Positioning System (GPS) data were used for three years covering 1997-1999 to estimate interseismic back slip distribution in this region. The estimated maximum back slip rate is about 7 cm/yr, which is consistent with the Philippine Sea plate convergence rate. Areas of strong coupling are confined between depths of 10 and 30 km and three areas of strong coupling were delineated. These results are consistent with other studies that have estimated locations of coupling distribution.

Synthesis, structure and antidiabetic activity of chromium(III) complexes of metformin Schiff-bases

NASA Astrophysics Data System (ADS)

Mahmoud, M. A.; Zaitone, S. A.; Ammar, A. M.; Sallam, S. A.

2016-03-01

A series of Cr3+ complexes with Schiff-bases of metformin with each of salicylaldehyde (HL1); 2,3-dihydroxybenzaldehyde (H2L2); 2,4-dihydroxybenzaldehyde (H2L3); 2,5-dihydroxybenzaldehyde (H2L4); 3,4-dihydroxybenzaldehyde (H2L5) and 2-hydroxynaphthaldehyde (HL6) were synthesized by template reaction. The new compounds were characterized through elemental analysis, conductivity and magnetic moment measurements, IR, UV-Vis., NMR and mass spectroscopy. The complexes have octahedral structure with μ value of hexacoordinated chromium ion. TGA, DTG and DTA analysis confirm the proposed stereochemistry and a mechanism for thermal decomposition was proposed. Thermodynamic parameters are calculated for the second and third decomposition steps. [CrL4Cl(H2O)2].3H2O and [CrL5Cl(H2O)2].2½H2O were able to produce significant decreases in the blood glucose level.

Kinetics of hydrogen peroxide decomposition by catalase: hydroxylic solvent effects.

PubMed

Raducan, Adina; Cantemir, Anca Ruxandra; Puiu, Mihaela; Oancea, Dumitru

2012-11-01

The effect of water-alcohol (methanol, ethanol, propan-1-ol, propan-2-ol, ethane-1,2-diol and propane-1,2,3-triol) binary mixtures on the kinetics of hydrogen peroxide decomposition in the presence of bovine liver catalase is investigated. In all solvents, the activity of catalase is smaller than in water. The results are discussed on the basis of a simple kinetic model. The kinetic constants for product formation through enzyme-substrate complex decomposition and for inactivation of catalase are estimated. The organic solvents are characterized by several physical properties: dielectric constant (D), hydrophobicity (log P), concentration of hydroxyl groups ([OH]), polarizability (α), Kamlet-Taft parameter (β) and Kosower parameter (Z). The relationships between the initial rate, kinetic constants and medium properties are analyzed by linear and multiple linear regression.

Effect of gamma-irradiation on thermal decomposition kinetics, X-ray diffraction pattern and spectral properties of tris(1,2-diaminoethane)nickel(II)sulphate

NASA Astrophysics Data System (ADS)

Jayashri, T. A.; Krishnan, G.; Rema Rani, N.

2014-12-01

Tris(1,2-diaminoethane)nickel(II)sulphate was prepared, and characterised by various chemical and spectral techniques. The sample was irradiated with 60Co gamma rays for varying doses. Sulphite ion and ammonia were detected and estimated in the irradiated samples. Non-isothermal decomposition kinetics, X-ray diffraction pattern, Fourier transform infrared spectroscopy, electronic, fast atom bombardment mass spectra, and surface morphology of the complex were studied before and after irradiation. Kinetic parameters were evaluated by integral, differential, and approximation methods. Irradiation enhanced thermal decomposition, lowering thermal and kinetic parameters. The mechanism of decomposition is controlled by R3 function. From X-ray diffraction studies, change in lattice parameters and subsequent changes in unit cell volume and average crystallite size were observed. Both unirradiated and irradiated samples of the complex belong to trigonal crystal system. Decrease in the intensity of the peaks was observed in the infrared spectra of irradiated samples. Electronic spectral studies revealed that the M-L interaction is unaffected by irradiation. Mass spectral studies showed that the fragmentation patterns of the unirradiated and irradiated samples are similar. The additional fragment with m/z 256 found in the irradiated sample is attributed to S8+. Surface morphology of the complex changed upon irradiation.

Representation of Dissolved Organic Carbon in the JULES Dynamic Global Vegetation Model

NASA Astrophysics Data System (ADS)

Nakhavali, Mahdi; Friedlingstein, Pierre; Guenet, Bertrand; Ciais, Philip

2017-04-01

Current global models of the carbon cycle consider only vertical gas exchanges between terrestrial or oceanic reservoirs and the atmosphere, hence not considering lateral transport of carbon from the continent to the oceans. This also means that such models implicitly consider that all the CO2 which is not respired to the atmosphere is stored on land, hence overestimating the land sink of carbon. Moving toward a boundless carbon cycle that is integrating the whole continuum from land to ocean to atmosphere is needed in order to better understand Earth's carbon cycle and to make more reliable projection of its future. Here we present an original representation of Dissolved Organic Carbon (DOC) processes in the Joint UK Land Environment Simulator (JULES). The standard version of JULES represent energy, water and carbon cycles and exchanges with the atmosphere, but only account for water run-off, not including export of carbon from terrestrial ecosystems to the aquatic environments. The aim of the project is to include in JULES a representation of DOC production in terrestrial soils, due to incomplete decomposition of organic matter, its decomposition to the atmosphere, and its export to the river network by leaching. In new developed version of JULES (JULES-DOCM), DOC pools, based on their decomposition rate, are classified into labile and recalcitrant within 3 meters of soil. Based on turnover rate, DOC coming from plant material pools and microbial biomass is directed to labile pool, while DOC from humus is directed to recalcitrant pool. Both of these pools have free (dissolved) and locked (adsorbed) form where just the free pool is subjected to decomposition and leaching. DOC production and decomposition are controlled by rate modifiers (moisture, temperature, vegetation fraction and decomposition rate) at each soil layer. Decomposed DOC is released to the atmosphere following a fixed carbon use efficiency. Leaching accounts for both surface (runoff) and subsurface (groundwater) components and is parameterized as Top soil leaching (from top 20cm) and Bottom soil leaching (down to 3 meters) depending on DOC concentration and runoff leaving that layer. The model parameters are calibrated against specific sites (Brasschaat, Hainich and Carlow) for which observations of DOC concentration and leaching are available. Tuning is performed optimizing parameters such as DOC labile and recalcitrant resident time, DOC vertical distribution and CUE. Once this calibration has been performed at the site level, the model is used for global simulations with the major historical forcing (climate, atmospheric CO2 and land-use changes) in order to estimate the changes of DOC export and their attribution to anthropogenic activities.

Assessing first-order emulator inference for physical parameters in nonlinear mechanistic models

USGS Publications Warehouse

Hooten, Mevin B.; Leeds, William B.; Fiechter, Jerome; Wikle, Christopher K.

2011-01-01

We present an approach for estimating physical parameters in nonlinear models that relies on an approximation to the mechanistic model itself for computational efficiency. The proposed methodology is validated and applied in two different modeling scenarios: (a) Simulation and (b) lower trophic level ocean ecosystem model. The approach we develop relies on the ability to predict right singular vectors (resulting from a decomposition of computer model experimental output) based on the computer model input and an experimental set of parameters. Critically, we model the right singular vectors in terms of the model parameters via a nonlinear statistical model. Specifically, we focus our attention on first-order models of these right singular vectors rather than the second-order (covariance) structure.

Effects of micro-water on decomposition of the environment-friendly insulating medium C5F10O

NASA Astrophysics Data System (ADS)

Xiao, Song; Li, Yi; Zhang, Xiaoxing; Tian, Shuangshuang; Deng, Zaitao; Tang, Ju

2017-06-01

SF6 is widely used in all kinds of high-voltage electrical equipment because of its excellent insulation and arc-extinguishing performance. However, this compound leads to serious greenhouse effect, which harms the environment. Many research institutions are now actively in search of SF6 alternative gas. C5F10O has attracted much attention as an alternative gas with low global warming potential (GWP) and excellent dielectric strength. In this paper, we analyzed the possible decomposition paths of C5F10O under micro-water environment through density functional theory. We also evaluated the ionization parameters and toxicity of the decomposition products. The results show that OH• and H• produced by H2O exhibited a catalytic effect on the decomposition of C5F10O. CF4, C2F6, C3F6, C3F8, C4F10, C5F12, C6F14, C3F7COH, C3F7OH, CF3COH, C3F7H, and CF3OH were produced in the micro-water environment. Based on molecular configuration calculation, the ionization parameters of these products were inferior to perfluorocarbons, such as C3F8, leading to reduced insulation performance of the system. Moreover, CF2O and HF are hazardous to human health and equipment safety. Results will provide a basis for further study of the insulation characteristic of the C5F10O gas mixture under micro-water condition to guide the formulation of their relevant international standards prior to engineering applications.

Characterizing Feedback Control Mechanisms in Nonlinear Microbial Models of Soil Organic Matter Decomposition by Stability Analysis

NASA Astrophysics Data System (ADS)

Georgiou, K.; Tang, J.; Riley, W. J.; Torn, M. S.

2014-12-01

Soil organic matter (SOM) decomposition is regulated by biotic and abiotic processes. Feedback interactions between such processes may act to dampen oscillatory responses to perturbations from equilibrium. Indeed, although biological oscillations have been observed in small-scale laboratory incubations, the overlying behavior at the plot-scale exhibits a relatively stable response to disturbances in input rates and temperature. Recent studies have demonstrated the ability of microbial models to capture nonlinear feedbacks in SOM decomposition that linear Century-type models are unable to reproduce, such as soil priming in response to increased carbon input. However, these microbial models often exhibit strong oscillatory behavior that is deemed unrealistic. The inherently nonlinear dynamics of SOM decomposition have important implications for global climate-carbon and carbon-concentration feedbacks. It is therefore imperative to represent these dynamics in Earth System Models (ESMs) by introducing sub-models that accurately represent microbial and abiotic processes. In the present study we explore, both analytically and numerically, four microbe-enabled model structures of varying levels of complexity. The most complex model combines microbial physiology, a non-linear mineral sorption isotherm, and enzyme dynamics. Based on detailed stability analysis of the nonlinear dynamics, we calculate the system modes as functions of model parameters. This dependence provides insight into the source of state oscillations. We find that feedback mechanisms that emerge from careful representation of enzyme and mineral interactions, with parameter values in a prescribed range, are critical for both maintaining system stability and capturing realistic responses to disturbances. Corroborating and expanding upon the results of recent studies, we explain the emergence of oscillatory responses and discuss the appropriate microbe-enabled model structure for inclusion in ESMs.

Three-Component Decomposition of Polarimetric SAR Data Integrating Eigen-Decomposition Results

NASA Astrophysics Data System (ADS)

Lu, Da; He, Zhihua; Zhang, Huan

2018-01-01

This paper presents a novel three-component scattering power decomposition of polarimetric SAR data. There are two problems in three-component decomposition method: volume scattering component overestimation in urban areas and artificially set parameter to be a fixed value. Though volume scattering component overestimation can be partly solved by deorientation process, volume scattering still dominants some oriented urban areas. The speckle-like decomposition results introduced by artificially setting value are not conducive to further image interpretation. This paper integrates the results of eigen-decomposition to solve the aforementioned problems. Two principal eigenvectors are used to substitute the surface scattering model and the double bounce scattering model. The decomposed scattering powers are obtained using a constrained linear least-squares method. The proposed method has been verified using an ESAR PolSAR image, and the results show that the proposed method has better performance in urban area.

Stability analysis of gyroscopic systems with delay via decomposition

NASA Astrophysics Data System (ADS)

Aleksandrov, A. Yu.; Zhabko, A. P.; Chen, Y.

2018-05-01

A mechanical system describing by the second order linear differential equations with a positive parameter at the velocity forces and with time delay in the positional forces is studied. Using the decomposition method and Lyapunov-Krasovskii functionals, conditions are obtained under which from the asymptotic stability of two auxiliary first order subsystems it follows that, for sufficiently large values of the parameter, the original system is also asymptotically stable. Moreover, it is shown that the proposed approach can be applied to the stability investigation of linear gyroscopic systems with switched positional forces.

Assessment of derelict soil quality: Abiotic, biotic and functional approaches.

PubMed

Vincent, Quentin; Auclerc, Apolline; Beguiristain, Thierry; Leyval, Corinne

2018-02-01

The intensification and subsequent closing down of industrial activities during the last century has left behind large surfaces of derelict lands. Derelict soils have low fertility, can be contaminated, and many of them remain unused. However, with the increasing demand of soil surfaces, they might be considered as a resource, for example for non-food biomass production. The study of their physico-chemical properties and of their biodiversity and biological activity may provide indications for their potential re-use. The objective of our study was to investigate the quality of six derelict soils, considering abiotic, biotic, and functional parameters. We studied (i) the soil bacteria, fungi, meso- and macro-fauna and plant communities of six different derelict soils (two from coking plants, one from a settling pond, two constructed ones made from different substrates and remediated soil, and an inert waste storage one), and (ii) their decomposition function based on the decomposer trophic network, enzyme activities, mineralization activity, and organic pollutant degradation. Biodiversity levels in these soils were high, but all biotic parameters, except the mycorrhizal colonization level, discriminated them. Multivariate analysis showed that biotic parameters co-varied more with fertility proxies than with soil contamination parameters. Similarly, functional parameters significantly co-varied with abiotic parameters. Among functional parameters, macro-decomposer proportion, enzyme activity, average mineralization capacity, and microbial polycyclic aromatic hydrocarbon degraders were useful to discriminate the soils. We assessed their quality by combining abiotic, biotic, and functional parameters: the compost-amended constructed soil displayed the highest quality, while the settling pond soil and the contaminated constructed soil displayed the lowest. Although differences among the soils were highlighted, this study shows that derelict soils may provide a biodiversity ecosystem service and are functional for decomposition. Copyright © 2017 Elsevier B.V. All rights reserved.

Control of complex dynamics and chaos in distributed parameter systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chakravarti, S.; Marek, M.; Ray, W.H.

This paper discusses a methodology for controlling complex dynamics and chaos in distributed parameter systems. The reaction-diffusion system with Brusselator kinetics, where the torus-doubling or quasi-periodic (two characteristic incommensurate frequencies) route to chaos exists in a defined range of parameter values, is used as an example. Poincare maps are used for characterization of quasi-periodic and chaotic attractors. The dominant modes or topos, which are inherent properties of the system, are identified by means of the Singular Value Decomposition. Tested modal feedback control schemas based on identified dominant spatial modes confirm the possibility of stabilization of simple quasi-periodic trajectories in themore » complex quasi-periodic or chaotic spatiotemporal patterns.« less

Estimation of beam material random field properties via sensitivity-based model updating using experimental frequency response functions

NASA Astrophysics Data System (ADS)

Machado, M. R.; Adhikari, S.; Dos Santos, J. M. C.; Arruda, J. R. F.

2018-03-01

Structural parameter estimation is affected not only by measurement noise but also by unknown uncertainties which are present in the system. Deterministic structural model updating methods minimise the difference between experimentally measured data and computational prediction. Sensitivity-based methods are very efficient in solving structural model updating problems. Material and geometrical parameters of the structure such as Poisson's ratio, Young's modulus, mass density, modal damping, etc. are usually considered deterministic and homogeneous. In this paper, the distributed and non-homogeneous characteristics of these parameters are considered in the model updating. The parameters are taken as spatially correlated random fields and are expanded in a spectral Karhunen-Loève (KL) decomposition. Using the KL expansion, the spectral dynamic stiffness matrix of the beam is expanded as a series in terms of discretized parameters, which can be estimated using sensitivity-based model updating techniques. Numerical and experimental tests involving a beam with distributed bending rigidity and mass density are used to verify the proposed method. This extension of standard model updating procedures can enhance the dynamic description of structural dynamic models.

Machine Learning Techniques for Global Sensitivity Analysis in Climate Models

NASA Astrophysics Data System (ADS)

Safta, C.; Sargsyan, K.; Ricciuto, D. M.

2017-12-01

Climate models studies are not only challenged by the compute intensive nature of these models but also by the high-dimensionality of the input parameter space. In our previous work with the land model components (Sargsyan et al., 2014) we identified subsets of 10 to 20 parameters relevant for each QoI via Bayesian compressive sensing and variance-based decomposition. Nevertheless the algorithms were challenged by the nonlinear input-output dependencies for some of the relevant QoIs. In this work we will explore a combination of techniques to extract relevant parameters for each QoI and subsequently construct surrogate models with quantified uncertainty necessary to future developments, e.g. model calibration and prediction studies. In the first step, we will compare the skill of machine-learning models (e.g. neural networks, support vector machine) to identify the optimal number of classes in selected QoIs and construct robust multi-class classifiers that will partition the parameter space in regions with smooth input-output dependencies. These classifiers will be coupled with techniques aimed at building sparse and/or low-rank surrogate models tailored to each class. Specifically we will explore and compare sparse learning techniques with low-rank tensor decompositions. These models will be used to identify parameters that are important for each QoI. Surrogate accuracy requirements are higher for subsequent model calibration studies and we will ascertain the performance of this workflow for multi-site ALM simulation ensembles.

Thermal stabilities of drops of burning thermoplastics under the UL 94 vertical test conditions.

PubMed

Wang, Yong; Zhang, Jun

2013-02-15

The properties of polymer melts will strongly affect the fire hazard of the pool induced by polymer melt flow. In this study the thermal stabilities of eight thermoplastic polymers as well as their melting drops generated under the UL 94 vertical burning test conditions were investigated by thermogravimetric experiments. It was found that the kinetic compensation effect existed for the decomposition reactions of the polymers and their drops. For polymethylmethacrylate (PMMA), high impact polystyrene (HIPS), poly(acrylonitrile-butadiene-styrene) (ABS), polyamide 6 (PA6), polypropylene (PP) and low density polyethylene (LDPE), the onset decomposition temperature and the two decomposition kinetic parameters (the pre-exponential factor and the activation energy) of the drop were less than those of the polymer. However, the onset decomposition temperature and the two kinetic parameters of PC's drop were greater than those of polycarbonate (PC). Interestingly, for polyethylenevinylacetate (EVA18) the drop hardly contained the vinyl acetate chain segments. Similarly, for the PMMA/LDPE blends and the PMMA/PP blends, when the volume fraction of PMMA was less than 50% the drop hardly contained PMMA, implying that the blend would not drip until PMMA burned away and its surface temperature approached the decomposition temperature of the continuous phase composed of LDPE or PP. Copyright © 2012 Elsevier B.V. All rights reserved.

Quantification of whispering gallery mode spectrum variability in application to sensing nanobiophotonics

NASA Astrophysics Data System (ADS)

Saetchnikov, Anton; Skakun, Victor; Saetchnikov, Vladimir; Tcherniavskaia, Elina; Ostendorf, Andreas

2017-10-01

An approach for the automated whispering gallery mode (WGM) signal decomposition and its parameter estimation is discussed. The algorithm is based on the peak picking and can be applied for the preprocessing of the raw signal acquired from the multiplied WGM-based biosensing chips. Quantitative estimations representing physically meaningful parameters of the external disturbing factors on the WGM spectral shape are the output values. Derived parameters can be directly applied to the further deep qualitative and quantitative interpretations of the sensed disturbing factors. The algorithm is tested on both simulated and experimental data taken from the bovine serum albumin biosensing task. The proposed solution is expected to be a useful contribution to the preprocessing phase of the complete data analysis engine and is expected to push the WGM technology toward the real-live sensing nanobiophotonics.

Polarimetric scattering model for estimation of above ground biomass of multilayer vegetation using ALOS-PALSAR quad-pol data

NASA Astrophysics Data System (ADS)

Sai Bharadwaj, P.; Kumar, Shashi; Kushwaha, S. P. S.; Bijker, Wietske

Forests are important biomes covering a major part of the vegetation on the Earth, and as such account for seventy percent of the carbon present in living beings. The value of a forest's above ground biomass (AGB) is considered as an important parameter for the estimation of global carbon content. In the present study, the quad-pol ALOS-PALSAR data was used for the estimation of AGB for the Dudhwa National Park, India. For this purpose, polarimetric decomposition components and an Extended Water Cloud Model (EWCM) were used. The PolSAR data orientation angle shifts were compensated for before the polarimetric decomposition. The scattering components obtained from the polarimetric decomposition were used in the Water Cloud Model (WCM). The WCM was extended for higher order interactions like double bounce scattering. The parameters of the EWCM were retrieved using the field measurements and the decomposition components. Finally, the relationship between the estimated AGB and measured AGB was assessed. The coefficient of determination (R2) and root mean square error (RMSE) were 0.4341 and 119 t/ha respectively.

Simulation of the microwave heating of a thin multilayered composite material: A parameter analysis

NASA Astrophysics Data System (ADS)

Tertrais, Hermine; Barasinski, Anaïs; Chinesta, Francisco

2018-05-01

Microwave (MW) technology relies on volumetric heating. Thermal energy is transferred to the material that can absorb it at specific frequencies. The complex physics involved in this process is far from being understood and that is why a simulation tool has been developed in order to solve the electromagnetic and thermal equations in such a complex material as a multilayered composite part. The code is based on the in-plane-out-of-plane separated representation within the Proper Generalized Decomposition framework. To improve the knowledge on the process, a parameter study in carried out in this paper.

Video denoising using low rank tensor decomposition

NASA Astrophysics Data System (ADS)

Gui, Lihua; Cui, Gaochao; Zhao, Qibin; Wang, Dongsheng; Cichocki, Andrzej; Cao, Jianting

2017-03-01

Reducing noise in a video sequence is of vital important in many real-world applications. One popular method is block matching collaborative filtering. However, the main drawback of this method is that noise standard deviation for the whole video sequence is known in advance. In this paper, we present a tensor based denoising framework that considers 3D patches instead of 2D patches. By collecting the similar 3D patches non-locally, we employ the low-rank tensor decomposition for collaborative filtering. Since we specify the non-informative prior over the noise precision parameter, the noise variance can be inferred automatically from observed video data. Therefore, our method is more practical, which does not require knowing the noise variance. The experimental on video denoising demonstrates the effectiveness of our proposed method.

Retrieval of the non-depolarizing components of depolarizing Mueller matrices by using symmetry conditions and least squares minimization

NASA Astrophysics Data System (ADS)

Kuntman, Ertan; Canillas, Adolf; Arteaga, Oriol

2017-11-01

Experimental Mueller matrices contain certain amount of uncertainty in their elements and these uncertainties can create difficulties for decomposition methods based on analytic solutions. In an earlier paper [1], we proposed a decomposition method for depolarizing Mueller matrices by using certain symmetry conditions. However, because of the experimental error, that method creates over-determined systems with non-unique solutions. Here we propose to use least squares minimization approach in order to improve the accuracy of our results. In this method, we are taking into account the number of independent parameters of the corresponding symmetry and the rank constraints on the component matrices to decide on our fitting model. This approach is illustrated with experimental Mueller matrices that include material media with different Mueller symmetries.

Chemical Kinetics of the TPS and Base Bleeding During Flight Test

NASA Technical Reports Server (NTRS)

Osipov, Viatcheslav; Ponizhovskaya, Ekaterina; Hafiychuck, Halyna; Luchinsky, Dmitry; Smelyanskiy, Vadim; Dagostino, Mark; Canabal, Francisco; Mobley, Brandon L.

2012-01-01

The present research deals with thermal degradation of polyurethane foam (PUF) during flight test. Model of thermal decomposition was developed that accounts for polyurethane kinetics parameters extracted from thermogravimetric analyses and radial heat losses to the surrounding environment. The model predicts mass loss of foam, the temperature and kinetic of release of the exhaust gases and char as function of heat and radiation loads. When PUF is heated, urethane bond break into polyol and isocyanate. In the first stage, isocyanate pyrolyses and oxidizes. As a result, the thermo-char and oil droplets (yellow smoke) are released. In the second decomposition stage, pyrolysis and oxidization of liquid polyol occur. Next, the kinetics of chemical compound release and the information about the reactions occurring in the base area are coupled to the CFD simulations of the base flow in a single first stage motor vertically stacked vehicle configuration. The CFD simulations are performed to estimate the contribution of the hot out-gassing, chemical reactions, and char oxidation to the temperature rise of the base flow. The results of simulations are compared with the flight test data.

Wavelet-based unsupervised learning method for electrocardiogram suppression in surface electromyograms.

PubMed

Niegowski, Maciej; Zivanovic, Miroslav

2016-03-01

We present a novel approach aimed at removing electrocardiogram (ECG) perturbation from single-channel surface electromyogram (EMG) recordings by means of unsupervised learning of wavelet-based intensity images. The general idea is to combine the suitability of certain wavelet decomposition bases which provide sparse electrocardiogram time-frequency representations, with the capacity of non-negative matrix factorization (NMF) for extracting patterns from images. In order to overcome convergence problems which often arise in NMF-related applications, we design a novel robust initialization strategy which ensures proper signal decomposition in a wide range of ECG contamination levels. Moreover, the method can be readily used because no a priori knowledge or parameter adjustment is needed. The proposed method was evaluated on real surface EMG signals against two state-of-the-art unsupervised learning algorithms and a singular spectrum analysis based method. The results, expressed in terms of high-to-low energy ratio, normalized median frequency, spectral power difference and normalized average rectified value, suggest that the proposed method enables better ECG-EMG separation quality than the reference methods. Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.

Quantitative evaluation of muscle synergy models: a single-trial task decoding approach

PubMed Central

Delis, Ioannis; Berret, Bastien; Pozzo, Thierry; Panzeri, Stefano

2013-01-01

Muscle synergies, i.e., invariant coordinated activations of groups of muscles, have been proposed as building blocks that the central nervous system (CNS) uses to construct the patterns of muscle activity utilized for executing movements. Several efficient dimensionality reduction algorithms that extract putative synergies from electromyographic (EMG) signals have been developed. Typically, the quality of synergy decompositions is assessed by computing the Variance Accounted For (VAF). Yet, little is known about the extent to which the combination of those synergies encodes task-discriminating variations of muscle activity in individual trials. To address this question, here we conceive and develop a novel computational framework to evaluate muscle synergy decompositions in task space. Unlike previous methods considering the total variance of muscle patterns (VAF based metrics), our approach focuses on variance discriminating execution of different tasks. The procedure is based on single-trial task decoding from muscle synergy activation features. The task decoding based metric evaluates quantitatively the mapping between synergy recruitment and task identification and automatically determines the minimal number of synergies that captures all the task-discriminating variability in the synergy activations. In this paper, we first validate the method on plausibly simulated EMG datasets. We then show that it can be applied to different types of muscle synergy decomposition and illustrate its applicability to real data by using it for the analysis of EMG recordings during an arm pointing task. We find that time-varying and synchronous synergies with similar number of parameters are equally efficient in task decoding, suggesting that in this experimental paradigm they are equally valid representations of muscle synergies. Overall, these findings stress the effectiveness of the decoding metric in systematically assessing muscle synergy decompositions in task space. PMID:23471195

Structural investigation of oxovanadium(IV) Schiff base complexes: X-ray crystallography, electrochemistry and kinetic of thermal decomposition.

PubMed

Asadi, Mozaffar; Asadi, Zahra; Savaripoor, Nooshin; Dusek, Michal; Eigner, Vaclav; Shorkaei, Mohammad Ranjkesh; Sedaghat, Moslem

2015-02-05

A series of new VO(IV) complexes of tetradentate N2O2 Schiff base ligands (L(1)-L(4)), were synthesized and characterized by FT-IR, UV-vis and elemental analysis. The structure of the complex VOL(1)⋅DMF was also investigated by X-ray crystallography which revealed a vanadyl center with distorted octahedral coordination where the 2-aza and 2-oxo coordinating sites of the ligand were perpendicular to the "-yl" oxygen. The electrochemical properties of the vanadyl complexes were investigated by cyclic voltammetry. A good correlation was observed between the oxidation potentials and the electron withdrawing character of the substituents on the Schiff base ligands, showing the following trend: MeO5-H>5-Br>5-Cl. Furthermore, the kinetic parameters of thermal decomposition were calculated by using the Coats-Redfern equation. According to the Coats-Redfern plots the kinetics of thermal decomposition of studied complexes is of the first-order in all stages, the free energy of activation for each following stage is larger than the previous one and the complexes have good thermal stability. The preparation of VOL(1)⋅DMF yielded also another compound, one kind of vanadium oxide [VO]X, with different habitus of crystals, (platelet instead of prisma) and without L(1) ligand, consisting of a V10O28 cage, diaminium moiety and dimethylamonium as a counter ions. Because its crystal structure was also new, we reported it along with the targeted complex. Copyright © 2014 Elsevier B.V. All rights reserved.

Fast Reactions of Aluminum and Explosive Decomposition Products in a Post-Detonation Environment

NASA Astrophysics Data System (ADS)

Tappan, Bryce; Manner, Virginia; Lloyd, Joseph; Pemberton, Steven; Explosives Applications; Special Projects Team

2011-06-01

In order to determine the reaction behavior of Al in HMX/cast-cured binder formulations shortly after the passage of the detonation, a series of cylinder tests was performed on formulations with varying amounts of 2 μm spherical Al as well as LiF (an inert surrogate for Al). In these studies, both detonation velocity and cylinder expansion velocity are measured in order to determine exactly how and when Al contributes to the explosive event, particularly in the presence of oxidizing/energetic binders. The U.S. Army ARDEC at Picatinny has recently coined the term ``combined effects explosives'' for these materials as they demonstrate both high metal pushing capability and high blast ability. This study is aimed at developing a fundamental understanding of the reaction of Al with explosives decomposition products, where both the detonation and post-detonation environment are analyzed. Reaction rates of Al metal are determined via comparison of predicted performance based on thermoequilibrium calculations. The JWL equation of state, detonation velocities, wall velocities, and parameters at the C-J plane are some of the parameters that will be discussed.

Structural modal parameter identification using local mean decomposition

NASA Astrophysics Data System (ADS)

Keyhani, Ali; Mohammadi, Saeed

2018-02-01

Modal parameter identification is the first step in structural health monitoring of existing structures. Already, many powerful methods have been proposed for this concept and each method has some benefits and shortcomings. In this study, a new method based on local mean decomposition is proposed for modal identification of civil structures from free or ambient vibration measurements. The ability of the proposed method was investigated using some numerical studies and the results compared with those obtained from the Hilbert-Huang transform (HHT). As a major advantage, the proposed method can extract natural frequencies and damping ratios of all active modes from only one measurement. The accuracy of the identified modes depends on their participation in the measured responses. Nevertheless, the identified natural frequencies have reasonable accuracy in both cases of free and ambient vibration measurements, even in the presence of noise. The instantaneous phase angle and the natural logarithm of instantaneous amplitude curves obtained from the proposed method have more linearity rather than those from the HHT algorithm. Also, the end effect is more restricted for the proposed method.

Decomposition dynamic of two aquatic macrophytes Trapa bispinosa Roxb. and Nelumbo nucifera detritus.

PubMed

Zhou, Xiaohong; Feng, Deyou; Wen, Chunzi; Liu, Dan

2018-03-29

In freshwater ecosystems, aquatic macrophytes play significant roles in nutrient cycling. One problem in this process is nutrient loss in the tissues of untimely harvested plants. In this study, we used two aquatic species, Nelumbo nucifera and Trapa bispinosa Roxb., to investigate the decomposition dynamics and nutrient release from detritus. Litter bags containing 10 g of stems (plus petioles) and leaves for each species detritus were incubated in the pond from November 2016 to May 2017. Nine times litterbags were retrieved on days 6, 14, 25, 45, 65, 90, 125, 145, and 165 after the decomposition experiment for the monitoring of biomass loss and nutrient release. The results suggested that the dry masses of N. nucifera and T. bispinosa decomposed by 49.35-69.40 and 82.65-91.65%, respectively. The order of decomposition rate constants (k) is as follows: leaves of T. bispinosa (0.0122 day -1 ) > stems (plus petioles) of T. bispinosa (0.0090 day -1 ) > leaves of N. nucifera (0.0060 day -1 ) > stems (plus petioles) of N. nucifera (0.0030 day -1 ). Additionally, the orders of time for 50% dry mass decay, time for 95% dry mass decay, and turnover rate are as follows: leaves < stems (plus petioles) and T. bispinosa < N. nucifera, respectively. This result indicated that the dry mass loss, k values, and other parameters related to k values are significantly different in species- and tissue-specific. The C, N, and P concentration and the C/N, C/P, and N/P ratios presented the irregular temporal changes trends during the whole decay period. In addition, nutrient accumulation index (AI) was significantly changed depending on the dry mass remaining and C, N, and P concentration in detritus at different decomposition times. The nutrient AIs were 36.72, 8.08, 6.35, and 2.56% for N; 31.25, 9.85, 4.00, and 1.63% for P; 25.15, 16.96, 7.36, and 6.16% for C in the stems (plus petioles) of N. nucifera, leaves of N. nucifera, stems (plus petioles) of T. bispinosa, and leaves of T. bispinosa, respectively, at the day 165. These results indicated that 63.28-97.44% of N, 68.75-98.37% of P, and 74.85-93.84% of C were released from the plant detritus to the water at the day 165 of the decomposition period. The initial detritus chemistry, particularly the P-related parameters (P concentration and C/P and N/P ratios), strongly affected dry mass loss, decomposition rates, and nutrient released from detritus into water. Two-way ANOVA results also confirm that the effects on the species were significant for decomposition dynamics (dry mass loss), nutrient release (nutrient concentration, their ratios, and nutrient AI) (P < 0.01), and expected N concentration (P > 0.05). In addition, the decomposition time had also significant effects on the detritus decomposition dynamic and nutrient release. However, the contributors of species and decomposition time on detritus decomposition were significantly different on the basis of their F values of two-way ANOVA results. This study can provide scientific bases for the aquatic plant scientific management in freshwater ecosystems of the East region of China.

Intramolecular distribution of stable nitrogen and oxygen isotopes of nitrous oxide emitted during coal combustion.

PubMed

Ogawa, Mitsuteru; Yoshida, Naohiro

2005-11-01

The intramolecular distribution of stable isotopes in nitrous oxide that is emitted during coal combustion was analyzed using an isotopic ratio mass spectrometer equipped with a modified ion collector system (IRMS). The coal was combusted in a test furnace fitted with a single burner and the flue gases were collected at the furnace exit following removal of SO(x), NO(x), and H2O in order to avoid the formation of artifact nitrous oxide. The nitrous oxide in the flue gases proved to be enriched in 15N relative to the fuel coal. In air-staged combustion experiments, the staged air ratio was controlled over a range of 0 (unstaged combustion), 20%, and 30%. As the staged air ratio increased, the delta15N and delta18O of the nitrous oxide in the flue gases became depleted. The central nitrogen of the nitrous oxide molecule, N(alpha), was enriched in 15N relative to that occupying the end position of the molecule, N(beta), but this preference, expressed as delta15N(alpha)-delta15N(beta), decreased with the increase in the staged air ratio. Thermal decomposition and hydrogen reduction experiments carried out using a tube reactor allowed qualitative estimates of the kinetic isotope effects that occurred during the decomposition of the nitrous oxide and quantitative estimates of the extent to which the nitrous oxide had decomposed. The site preference of nitrous oxide increased with the extent of the decomposition reactions. Assuming that no site preference exists in nitrous oxide before decomposition, the behavior of nitrous oxide in the test combustion furnace was analyzed using the Rayleigh equation based on a single distillation model. As a result, the extent of decomposition of nitrous oxide was estimated as 0.24-0.26 during the decomposition reaction governed by the thermal decomposition and as 0.35-0.38 during the decomposition reaction governed by the hydrogen reduction in staged combustion. The intramolecular distribution of nitrous oxide can be a valuable parameter to estimate the extent of decomposition reaction and to understand the reaction pathway of nitrous oxide at the high temperature.

Pursuing reliable thermal analysis techniques for energetic materials: decomposition kinetics and thermal stability of dihydroxylammonium 5,5'-bistetrazole-1,1'-diolate (TKX-50).

PubMed

Muravyev, Nikita V; Monogarov, Konstantin A; Asachenko, Andrey F; Nechaev, Mikhail S; Ananyev, Ivan V; Fomenkov, Igor V; Kiselev, Vitaly G; Pivkina, Alla N

2016-12-21

Thermal decomposition of a novel promising high-performance explosive dihydroxylammonium 5,5'-bistetrazole-1,1'-diolate (TKX-50) was studied using a number of thermal analysis techniques (thermogravimetry, differential scanning calorimetry, and accelerating rate calorimetry, ARC). To obtain more comprehensive insight into the kinetics and mechanism of TKX-50 decomposition, a variety of complementary thermoanalytical experiments were performed under various conditions. Non-isothermal and isothermal kinetics were obtained at both atmospheric and low (up to 0.3 Torr) pressures. The gas products of thermolysis were detected in situ using IR spectroscopy, and the structure of solid-state decomposition products was determined by X-ray diffraction and scanning electron microscopy. Diammonium 5,5'-bistetrazole-1,1'-diolate (ABTOX) was directly identified to be the most important intermediate of the decomposition process. The important role of bistetrazole diol (BTO) in the mechanism of TKX-50 decomposition was also rationalized by thermolysis experiments with mixtures of TKX-50 and BTO. Several widely used thermoanalytical data processing techniques (Kissinger, isoconversional, formal kinetic approaches, etc.) were independently benchmarked against the ARC data, which are more germane to the real storage and application conditions of energetic materials. Our study revealed that none of the Arrhenius parameters reported before can properly describe the complex two-stage decomposition process of TKX-50. In contrast, we showed the superior performance of the isoconversional methods combined with isothermal measurements, which yielded the most reliable kinetic parameters of TKX-50 thermolysis. In contrast with the existing reports, the thermal stability of TKX-50 was determined in the ARC experiments to be lower than that of hexogen, but close to that of hexanitrohexaazaisowurtzitane (CL-20).

Water-fat separation with parallel imaging based on BLADE.

PubMed

Weng, Dehe; Pan, Yanli; Zhong, Xiaodong; Zhuo, Yan

2013-06-01

Uniform suppression of fat signal is desired in clinical applications. Based on phase differences introduced by different chemical shift frequencies, Dixon method and its variations are used as alternatives of fat saturation methods, which are sensitive to B0 inhomogeneities. Iterative Decomposition of water and fat with Echo Asymmetry and Least squares estimation (IDEAL) separates water and fat images with flexible echo shifting. Periodically Rotated Overlapping ParallEL Lines with Enhanced Reconstruction (PROPELLER, alternatively termed as BLADE), in conjunction with IDEAL, yields Turboprop IDEAL (TP-IDEAL) and allows for decomposition of water and fat signal with motion correction. However, the flexibility of its parameter setting is limited, and the related phase correction is complicated. To address these problems, a novel method, BLADE-Dixon, is proposed in this study. This method used the same polarity readout gradients (fly-back gradients) to acquire in-phase and opposed-phases images, which led to less complicated phase correction and more flexible parameter setting compared to TP-IDEAL. Parallel imaging and undersampling were integrated to reduce scan time. Phantom, orbit, neck and knee images were acquired with BLADE-Dixon. Water-fat separation results were compared to those measured with conventional turbo spin echo (TSE) Dixon and TSE with fat saturation, respectively, to demonstrate the performance of BLADE-Dixon. Copyright © 2013 Elsevier Inc. All rights reserved.

Fault feature analysis of cracked gear based on LOD and analytical-FE method

NASA Astrophysics Data System (ADS)

Wu, Jiateng; Yang, Yu; Yang, Xingkai; Cheng, Junsheng

2018-01-01

At present, there are two main ideas for gear fault diagnosis. One is the model-based gear dynamic analysis; the other is signal-based gear vibration diagnosis. In this paper, a method for fault feature analysis of gear crack is presented, which combines the advantages of dynamic modeling and signal processing. Firstly, a new time-frequency analysis method called local oscillatory-characteristic decomposition (LOD) is proposed, which has the attractive feature of extracting fault characteristic efficiently and accurately. Secondly, an analytical-finite element (analytical-FE) method which is called assist-stress intensity factor (assist-SIF) gear contact model, is put forward to calculate the time-varying mesh stiffness (TVMS) under different crack states. Based on the dynamic model of the gear system with 6 degrees of freedom, the dynamic simulation response was obtained for different tooth crack depths. For the dynamic model, the corresponding relation between the characteristic parameters and the degree of the tooth crack is established under a specific condition. On the basis of the methods mentioned above, a novel gear tooth root crack diagnosis method which combines the LOD with the analytical-FE is proposed. Furthermore, empirical mode decomposition (EMD) and ensemble empirical mode decomposition (EEMD) are contrasted with the LOD by gear crack fault vibration signals. The analysis results indicate that the proposed method performs effectively and feasibility for the tooth crack stiffness calculation and the gear tooth crack fault diagnosis.

Novel techniques for data decomposition and load balancing for parallel processing of vision systems: Implementation and evaluation using a motion estimation system

NASA Technical Reports Server (NTRS)

Choudhary, Alok Nidhi; Leung, Mun K.; Huang, Thomas S.; Patel, Janak H.

1989-01-01

Computer vision systems employ a sequence of vision algorithms in which the output of an algorithm is the input of the next algorithm in the sequence. Algorithms that constitute such systems exhibit vastly different computational characteristics, and therefore, require different data decomposition techniques and efficient load balancing techniques for parallel implementation. However, since the input data for a task is produced as the output data of the previous task, this information can be exploited to perform knowledge based data decomposition and load balancing. Presented here are algorithms for a motion estimation system. The motion estimation is based on the point correspondence between the involved images which are a sequence of stereo image pairs. Researchers propose algorithms to obtain point correspondences by matching feature points among stereo image pairs at any two consecutive time instants. Furthermore, the proposed algorithms employ non-iterative procedures, which results in saving considerable amounts of computation time. The system consists of the following steps: (1) extraction of features; (2) stereo match of images in one time instant; (3) time match of images from consecutive time instants; (4) stereo match to compute final unambiguous points; and (5) computation of motion parameters.

Synthesis of seaweed based carbon acid catalyst by thermal decomposition of ammonium sulfate for biodiesel production

NASA Astrophysics Data System (ADS)

Ee, Tang Zo; Lim, Steven; Ling, Pang Yean; Huei, Wong Kam; Chyuan, Ong Hwai

2017-04-01

Experiment was carried out to study the feasibility of biomass derived solid acid catalyst for the production of biodiesel using Palm Fatty Acid Distillate (PFAD). Malaysia indigenous seaweed was selected as the biomass to be carbonized as the catalyst support. Sulfonation of seaweed based carbon material was carried out by thermal decomposition of ammonium sulfate, (NH4)2SO4. The effects of carbonization temperature at 200 to 600°C on the catalyst physical and chemical properties were studied. The effect of reaction parameters on the fatty acid methyl ester (FAME) yield was studied by varying the concentration of ammonium sulfate (5.0 to 40.0 w/v%) and thermal decomposition time (15 to 90 min). Characterizations of catalyst were carried out to study the catalyst surface morphology with Scanning Electron Microscope (SEM), acid density with back titration and functional group attached with FT-IR. Results showed that when the catalyst sulfonated with 10.0 w/v% ammonium sulfate solution and heated to 235°C for 30 min, the highest FAME yield achieved was 23.7% at the reaction condition of 5.0 wt.% catalyst loading, esterification time of 4 h, methanol to PFAD molar ratio of 20:1 at 100°C reaction temperature.

Decomposition of aquatic plants in lakes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Godshalk, G.L.

1977-01-01

This study was carried out to systematically determine the effects of temperature and oxygen concentration, two environmental parameters crucial to lake metabolism in general, on decomposition of five species of aquatic vascular plants of three growth forms in a Michigan lake. Samples of dried plant material were decomposed in flasks in the laboratory under three different oxygen regimes, aerobic-to-anaerobic, strict anaerobic, and aerated, each at 10/sup 0/C and 25/sup 0/C. In addition, in situ decomposition of the same species was monitored using the litter bag technique under four conditions.

Signal decomposition for surrogate modeling of a constrained ultrasonic design space

NASA Astrophysics Data System (ADS)

Homa, Laura; Sparkman, Daniel; Wertz, John; Welter, John; Aldrin, John C.

2018-04-01

The U.S. Air Force seeks to improve the methods and measures by which the lifecycle of composite structures are managed. Nondestructive evaluation of damage - particularly internal damage resulting from impact - represents a significant input to that improvement. Conventional ultrasound can detect this damage; however, full 3D characterization has not been demonstrated. A proposed approach for robust characterization uses model-based inversion through fitting of simulated results to experimental data. One challenge with this approach is the high computational expense of the forward model to simulate the ultrasonic B-scans for each damage scenario. A potential solution is to construct a surrogate model using a subset of simulated ultrasonic scans built using a highly accurate, computationally expensive forward model. However, the dimensionality of these simulated B-scans makes interpolating between them a difficult and potentially infeasible problem. Thus, we propose using the chirplet decomposition to reduce the dimensionality of the data, and allow for interpolation in the chirplet parameter space. By applying the chirplet decomposition, we are able to extract the salient features in the data and construct a surrogate forward model.

Morphological characteristics of waste polyethylene/polypropylene plastics during pyrolysis and representative morphological signal characterizing pyrolysis stages.

PubMed

Wang, H; Chen, D; Yuan, G; Ma, X; Dai, X

2013-02-01

In this work, the morphological characteristics of waste polyethylene (PE)/polypropylene (PP) plastics during their pyrolysis process were investigated, and based on their basic image changing patterns representative morphological signals describing the pyrolysis stages were obtained. PE and PP granules and films were used as typical plastics for testing, and influence of impurities was also investigated. During pyrolysis experiments, photographs of the testing samples were taken sequentially with a high-speed infrared camera, and the quantitative parameters that describe the morphological characteristics of these photographs were explored using the "Image Pro Plus (v6.3)" digital image processing software. The experimental results showed that plastics pyrolysis involved four stages: melting, two stages of decomposition which are characterized with bubble formation caused by volatile evaporating, and ash deposition; and each stage was characterized with its own phase changing behaviors and morphological features. Two stages of decomposition are the key step of pyrolysis since they took up half or more of the reaction time; melting step consumed another half of reaction time in experiments when raw materials were heated up from ambient temperatures; and coke-like deposition appeared as a result of decomposition completion. Two morphological signals defined from digital image processing, namely, pixel area of the interested reaction region and bubble ratio (BR) caused by volatile evaporating were found to change regularly with pyrolysis stages. In particular, for all experimental scenarios with plastics films and granules, the BR curves always exhibited a slowly drop as melting started and then a sharp increase followed by a deep decrease corresponding to the first stage of intense decomposition, afterwards a second increase - drop section corresponding to the second stage of decomposition appeared. As ash deposition happened, the BR dropped to zero or very low values. When impurities were involved, the shape of BR curves showed that intense decomposition started earlier but morphological characteristics remained the same. In addition, compared to parameters such as pressure, the BR reflects reaction stages better and its change with pyrolysis process of PE/PP plastics with or without impurities was more intrinsically process correlated; therefore it can be adopted as a signal for pyrolysis process characterization, as well as offering guide to process improvement and reactor design. Copyright © 2012 Elsevier Ltd. All rights reserved.

Detecting the Extent of Cellular Decomposition after Sub-Eutectoid Annealing in Rolled UMo Foils

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kautz, Elizabeth J.; Jana, Saumyadeep; Devaraj, Arun

2017-07-31

This report presents an automated image processing approach to quantifying microstructure image data, specifically the extent of eutectoid (cellular) decomposition in rolled U-10Mo foils. An image processing approach is used here to be able to quantitatively describe microstructure image data in order to relate microstructure to processing parameters (time, temperature, deformation).

Quantitative separation of tetralin hydroperoxide from its decomposition products by high performance liquid chromatography

NASA Technical Reports Server (NTRS)

Worstell, J. H.; Daniel, S. R.

1981-01-01

A method for the separation and analysis of tetralin hydroperoxide and its decomposition products by high pressure liquid chromatography has been developed. Elution with a single, mixed solvent from a micron-Porasil column was employed. Constant response factors (internal standard method) over large concentration ranges and reproducible retention parameters are reported.

Decomposition Techniques for Icesat/glas Full-Waveform Data

NASA Astrophysics Data System (ADS)

Liu, Z.; Gao, X.; Li, G.; Chen, J.

2018-04-01

The geoscience laser altimeter system (GLAS) on the board Ice, Cloud, and land Elevation Satellite (ICESat), is the first long-duration space borne full-waveform LiDAR for measuring the topography of the ice shelf and temporal variation, cloud and atmospheric characteristics. In order to extract the characteristic parameters of the waveform, the key step is to process the full waveform data. In this paper, the modified waveform decomposition method is proposed to extract the echo components from full-waveform. First, the initial parameter estimation is implemented through data preprocessing and waveform detection. Next, the waveform fitting is demonstrated using the Levenberg-Marquard (LM) optimization method. The results show that the modified waveform decomposition method can effectively extract the overlapped echo components and missing echo components compared with the results from GLA14 product. The echo components can also be extracted from the complex waveforms.

Mueller matrix imaging and analysis of cancerous cells

NASA Astrophysics Data System (ADS)

Fernández, A.; Fernández-Luna, J. L.; Moreno, F.; Saiz, J. M.

2017-08-01

Imaging polarimetry is a focus of increasing interest in diagnostic medicine because of its non-invasive nature and its potential for recognizing abnormal tissues. However, handling polarimetric images is not an easy task, and different intermediate steps have been proposed to introduce physical parameters that may be helpful to interpret results. In this work, transmission Mueller matrices (MM) corresponding to cancer cell samples have been experimentally obtained, and three different transformations have been applied: MM-Polar Decomposition, MM-Transformation and MM-Differential Decomposition. Special attention has been paid to diattenuation as a sensitive parameter to identify apoptosis processes induced by cisplatin and etoposide.

Towards accurate modeling of noncovalent interactions for protein rigidity analysis.

PubMed

Fox, Naomi; Streinu, Ileana

2013-01-01

Protein rigidity analysis is an efficient computational method for extracting flexibility information from static, X-ray crystallography protein data. Atoms and bonds are modeled as a mechanical structure and analyzed with a fast graph-based algorithm, producing a decomposition of the flexible molecule into interconnected rigid clusters. The result depends critically on noncovalent atomic interactions, primarily on how hydrogen bonds and hydrophobic interactions are computed and modeled. Ongoing research points to the stringent need for benchmarking rigidity analysis software systems, towards the goal of increasing their accuracy and validating their results, either against each other and against biologically relevant (functional) parameters. We propose two new methods for modeling hydrogen bonds and hydrophobic interactions that more accurately reflect a mechanical model, without being computationally more intensive. We evaluate them using a novel scoring method, based on the B-cubed score from the information retrieval literature, which measures how well two cluster decompositions match. To evaluate the modeling accuracy of KINARI, our pebble-game rigidity analysis system, we use a benchmark data set of 20 proteins, each with multiple distinct conformations deposited in the Protein Data Bank. Cluster decompositions for them were previously determined with the RigidFinder method from Gerstein's lab and validated against experimental data. When KINARI's default tuning parameters are used, an improvement of the B-cubed score over a crude baseline is observed in 30% of this data. With our new modeling options, improvements were observed in over 70% of the proteins in this data set. We investigate the sensitivity of the cluster decomposition score with case studies on pyruvate phosphate dikinase and calmodulin. To substantially improve the accuracy of protein rigidity analysis systems, thorough benchmarking must be performed on all current systems and future extensions. We have measured the gain in performance by comparing different modeling methods for noncovalent interactions. We showed that new criteria for modeling hydrogen bonds and hydrophobic interactions can significantly improve the results. The two new methods proposed here have been implemented and made publicly available in the current version of KINARI (v1.3), together with the benchmarking tools, which can be downloaded from our software's website, http://kinari.cs.umass.edu.

Towards accurate modeling of noncovalent interactions for protein rigidity analysis

PubMed Central

2013-01-01

Background Protein rigidity analysis is an efficient computational method for extracting flexibility information from static, X-ray crystallography protein data. Atoms and bonds are modeled as a mechanical structure and analyzed with a fast graph-based algorithm, producing a decomposition of the flexible molecule into interconnected rigid clusters. The result depends critically on noncovalent atomic interactions, primarily on how hydrogen bonds and hydrophobic interactions are computed and modeled. Ongoing research points to the stringent need for benchmarking rigidity analysis software systems, towards the goal of increasing their accuracy and validating their results, either against each other and against biologically relevant (functional) parameters. We propose two new methods for modeling hydrogen bonds and hydrophobic interactions that more accurately reflect a mechanical model, without being computationally more intensive. We evaluate them using a novel scoring method, based on the B-cubed score from the information retrieval literature, which measures how well two cluster decompositions match. Results To evaluate the modeling accuracy of KINARI, our pebble-game rigidity analysis system, we use a benchmark data set of 20 proteins, each with multiple distinct conformations deposited in the Protein Data Bank. Cluster decompositions for them were previously determined with the RigidFinder method from Gerstein's lab and validated against experimental data. When KINARI's default tuning parameters are used, an improvement of the B-cubed score over a crude baseline is observed in 30% of this data. With our new modeling options, improvements were observed in over 70% of the proteins in this data set. We investigate the sensitivity of the cluster decomposition score with case studies on pyruvate phosphate dikinase and calmodulin. Conclusion To substantially improve the accuracy of protein rigidity analysis systems, thorough benchmarking must be performed on all current systems and future extensions. We have measured the gain in performance by comparing different modeling methods for noncovalent interactions. We showed that new criteria for modeling hydrogen bonds and hydrophobic interactions can significantly improve the results. The two new methods proposed here have been implemented and made publicly available in the current version of KINARI (v1.3), together with the benchmarking tools, which can be downloaded from our software's website, http://kinari.cs.umass.edu. PMID:24564209

More of the same? In situ leaf and root decomposition rates do not vary between 80 native and nonnative deciduous forest species.

PubMed

Jo, Insu; Fridley, Jason D; Frank, Douglas A

2016-01-01

Invaders often have greater rates of production and produce more labile litter than natives. The increased litter quantity and quality of invaders should increase nutrient cycling through faster litter decomposition. However, the limited number of invasive species that have been included in decomposition studies has hindered the ability to generalize their impacts on decomposition rates. Further, previous decomposition studies have neglected roots. We measured litter traits and decomposition rates of leaves for 42 native and 36 nonnative woody species, and those of fine roots for 23 native and 25 nonnative species that occur in temperate deciduous forests throughout the Eastern USA. Among the leaf and root traits that differed between native and invasive species, only leaf nitrogen was significantly associated with decomposition rate. However, native and nonnative species did not differ systematically in leaf and root decomposition rates. We found that among the parameters measured, litter decomposer activity was driven by litter chemical quality rather than tissue density and structure. Our results indicate that litter decomposition rate per se is not a pathway by which forest woody invasive species affect North American temperate forest soil carbon and nutrient processes. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Human versus animal: contrasting decomposition dynamics of mammalian analogues in experimental taphonomy.

PubMed

Stokes, Kathryn L; Forbes, Shari L; Tibbett, Mark

2013-05-01

Taphonomic studies regularly employ animal analogues for human decomposition due to ethical restrictions relating to the use of human tissue. However, the validity of using animal analogues in soil decomposition studies is still questioned. This study compared the decomposition of skeletal muscle tissues (SMTs) from human (Homo sapiens), pork (Sus scrofa), beef (Bos taurus), and lamb (Ovis aries) interred in soil microcosms. Fixed interval samples were collected from the SMT for microbial activity and mass tissue loss determination; samples were also taken from the underlying soil for pH, electrical conductivity, and nutrient (potassium, phosphate, ammonium, and nitrate) analysis. The overall patterns of nutrient fluxes and chemical changes in nonhuman SMT and the underlying soil followed that of human SMT. Ovine tissue was the most similar to human tissue in many of the measured parameters. Although no single analogue was a precise predictor of human decomposition in soil, all models offered close approximations in decomposition dynamics. © 2013 American Academy of Forensic Sciences.

New class of single-source precursors for the synthesis of main group-transition metal oxides: heterobimetallic Pb-Mn beta-diketonates.

PubMed

Zhang, Haitao; Yang, Jen-Hsien; Shpanchenko, Roman V; Abakumov, Artem M; Hadermann, Joke; Clérac, Rodolphe; Dikarev, Evgeny V

2009-09-07

Heterometallic lead-manganese beta-diketonates have been isolated in pure form by several synthetic methods that include solid-state and solution techniques. Two compounds with different Pb/Mn ratios, PbMn(2)(hfac)(6) (1) and PbMn(hfac)(4) (2) (hfac = hexafluoroacetylacetonate), can be obtained in quantitative yield by using different starting materials. Single crystal X-ray investigation revealed that the solid-state structure of 1 contains trinuclear molecules in which lead metal center is sandwiched between two [Mn(hfac)(3)] units, while 2 consists of infinite chains of alternating [Pb(hfac)(2)] and [Mn(hfac)(2)] fragments. The heterometallic structures are held together by strong Lewis acid-base interactions between metal atoms and diketonate ligands acting in chelating-bridging fashion. Spectroscopic investigation confirmed the retention of heterometallic structures in solutions of non-coordinating solvents as well as upon sublimation-deposition procedure. Thermal decomposition of heterometallic diketonates has been systematically investigated in a wide range of temperatures and annealing times. For the first time, it has been shown that thermal decomposition of heterometallic diketonates results in mixed-metal oxides, while both the structure of precursors and the thermolysis conditions have a significant influence on the nature of the resulting oxides. Five different Pb-Mn oxides have been detected by X-ray powder diffraction when studying the decomposition of 1 and 2 in the temperature range 500-800 degrees C. The phase that has been previously reported as "Pb(0.43)MnO(2.18)" was synthesized in the pure form by decomposition of 1, and crystallographically characterized. The orthorhombic unit cell parameters of this oxide, obtained by electron diffraction technique, have been subsequently refined using X-ray powder diffraction data. Besides that, a previously unknown lead-manganese oxide has been obtained at low temperature decomposition and short annealing times. The parameters of its monoclinically distorted unit cell have been determined. The EDX analysis revealed that this compound has a Pb/Mn ratio close to 1:4 and contains no appreciable amount of fluorine.

Radar Imaging of Non-Uniformly Rotating Targets via a Novel Approach for Multi-Component AM-FM Signal Parameter Estimation

PubMed Central

Wang, Yong

2015-01-01

A novel radar imaging approach for non-uniformly rotating targets is proposed in this study. It is assumed that the maneuverability of the non-cooperative target is severe, and the received signal in a range cell can be modeled as multi-component amplitude-modulated and frequency-modulated (AM-FM) signals after motion compensation. Then, the modified version of Chirplet decomposition (MCD) based on the integrated high order ambiguity function (IHAF) is presented for the parameter estimation of AM-FM signals, and the corresponding high quality instantaneous ISAR images can be obtained from the estimated parameters. Compared with the MCD algorithm based on the generalized cubic phase function (GCPF) in the authors’ previous paper, the novel algorithm presented in this paper is more accurate and efficient, and the results with simulated and real data demonstrate the superiority of the proposed method. PMID:25806870

Determination of the heat of hydride formation/decomposition by high-pressure differential scanning calorimetry (HP-DSC).

PubMed

Rongeat, Carine; Llamas-Jansa, Isabel; Doppiu, Stefania; Deledda, Stefano; Borgschulte, Andreas; Schultz, Ludwig; Gutfleisch, Oliver

2007-11-22

Among the thermodynamic properties of novel materials for solid-state hydrogen storage, the heat of formation/decomposition of hydrides is the most important parameter to evaluate the stability of the compound and its temperature and pressure of operation. In this work, the desorption and absorption behaviors of three different classes of hydrides are investigated under different hydrogen pressures using high-pressure differential scanning calorimetry (HP-DSC). The HP-DSC technique is used to estimate the equilibrium pressures as a function of temperature, from which the heat of formation is derived. The relevance of this procedure is demonstrated for (i) magnesium-based compounds (Ni-doped MgH2), (ii) Mg-Co-based ternary hydrides (Mg-CoHx) and (iii) Alanate complex hydrides (Ti-doped NaAlH4). From these results, it can be concluded that HP-DSC is a powerful tool to obtain a good approximation of the thermodynamic properties of hydride compounds by a simple and fast study of desorption and absorption properties under different pressures.

Non-stationary least-squares complex decomposition for microseismic noise attenuation

NASA Astrophysics Data System (ADS)

Chen, Yangkang

2018-06-01

Microseismic data processing and imaging are crucial for subsurface real-time monitoring during hydraulic fracturing process. Unlike the active-source seismic events or large-scale earthquake events, the microseismic event is usually of very small magnitude, which makes its detection challenging. The biggest trouble of microseismic data is the low signal-to-noise ratio issue. Because of the small energy difference between effective microseismic signal and ambient noise, the effective signals are usually buried in strong random noise. I propose a useful microseismic denoising algorithm that is based on decomposing a microseismic trace into an ensemble of components using least-squares inversion. Based on the predictive property of useful microseismic event along the time direction, the random noise can be filtered out via least-squares fitting of multiple damping exponential components. The method is flexible and almost automated since the only parameter needed to be defined is a decomposition number. I use some synthetic and real data examples to demonstrate the potential of the algorithm in processing complicated microseismic data sets.

Improving performance of channel equalization in RSOA-based WDM-PON by QR decomposition.

PubMed

Li, Xiang; Zhong, Wen-De; Alphones, Arokiaswami; Yu, Changyuan; Xu, Zhaowen

2015-10-19

In reflective semiconductor optical amplifier (RSOA)-based wavelength division multiplexed passive optical network (WDM-PON), the bit rate is limited by low modulation bandwidth of RSOAs. To overcome the limitation, we apply QR decomposition in channel equalizer (QR-CE) to achieve successive interference cancellation (SIC) for discrete Fourier transform spreading orthogonal frequency division multiplexing (DFT-S OFDM) signal. Using an RSOA with a 3-dB modulation bandwidth of only ~800 MHz, we experimentally demonstrate a 15.5-Gb/s over 20-km SSMF DFT-S OFDM transmission with QR-CE. The experimental results show that DFTS-OFDM with QR-CE attains much better BER performance than DFTS-OFDM and OFDM with conventional channel equalizers. The impacts of several parameters on QR-CE are investigated. It is found that 2 sub-bands in one OFDM symbol and 1 pilot in each sub-band are sufficient to achieve optimal performance and maintain the high spectral efficiency.

Infrared dim-small target tracking via singular value decomposition and improved Kernelized correlation filter

NASA Astrophysics Data System (ADS)

Qian, Kun; Zhou, Huixin; Rong, Shenghui; Wang, Bingjian; Cheng, Kuanhong

2017-05-01

Infrared small target tracking plays an important role in applications including military reconnaissance, early warning and terminal guidance. In this paper, an effective algorithm based on the Singular Value Decomposition (SVD) and the improved Kernelized Correlation Filter (KCF) is presented for infrared small target tracking. Firstly, the super performance of the SVD-based algorithm is that it takes advantage of the target's global information and obtains a background estimation of an infrared image. A dim target is enhanced by subtracting the corresponding estimated background with update from the original image. Secondly, the KCF algorithm is combined with Gaussian Curvature Filter (GCF) to eliminate the excursion problem. The GCF technology is adopted to preserve the edge and eliminate the noise of the base sample in the KCF algorithm, helping to calculate the classifier parameter for a small target. At last, the target position is estimated with a response map, which is obtained via the kernelized classifier. Experimental results demonstrate that the presented algorithm performs favorably in terms of efficiency and accuracy, compared with several state-of-the-art algorithms.

Validation of Heat Transfer Thermal Decomposition and Container Pressurization of Polyurethane Foam.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Scott, Sarah Nicole; Dodd, Amanda B.; Larsen, Marvin E.

Polymer foam encapsulants provide mechanical, electrical, and thermal isolation in engineered systems. In fire environments, gas pressure from thermal decomposition of polymers can cause mechanical failure of sealed systems. In this work, a detailed uncertainty quantification study of PMDI-based polyurethane foam is presented to assess the validity of the computational model. Both experimental measurement uncertainty and model prediction uncertainty are examined and compared. Both the mean value method and Latin hypercube sampling approach are used to propagate the uncertainty through the model. In addition to comparing computational and experimental results, the importance of each input parameter on the simulation resultmore » is also investigated. These results show that further development in the physics model of the foam and appropriate associated material testing are necessary to improve model accuracy.« less

Using Rényi parameter to improve the predictive power of singular value decomposition entropy on stock market

NASA Astrophysics Data System (ADS)

Jiang, Jiaqi; Gu, Rongbao

2016-04-01

This paper generalizes the method of traditional singular value decomposition entropy by incorporating orders q of Rényi entropy. We analyze the predictive power of the entropy based on trajectory matrix using Shanghai Composite Index and Dow Jones Index data in both static test and dynamic test. In the static test on SCI, results of global granger causality tests all turn out to be significant regardless of orders selected. But this entropy fails to show much predictability in American stock market. In the dynamic test, we find that the predictive power can be significantly improved in SCI by our generalized method but not in DJI. This suggests that noises and errors affect SCI more frequently than DJI. In the end, results obtained using different length of sliding window also corroborate this finding.

Stability evaluation of short-circuiting gas metal arc welding based on ensemble empirical mode decomposition

NASA Astrophysics Data System (ADS)

Huang, Yong; Wang, Kehong; Zhou, Zhilan; Zhou, Xiaoxiao; Fang, Jimi

2017-03-01

The arc of gas metal arc welding (GMAW) contains abundant information about its stability and droplet transition, which can be effectively characterized by extracting the arc electrical signals. In this study, ensemble empirical mode decomposition (EEMD) was used to evaluate the stability of electrical current signals. The welding electrical signals were first decomposed by EEMD, and then transformed to a Hilbert-Huang spectrum and a marginal spectrum. The marginal spectrum is an approximate distribution of amplitude with frequency of signals, and can be described by a marginal index. Analysis of various welding process parameters showed that the marginal index of current signals increased when the welding process was more stable, and vice versa. Thus EEMD combined with the marginal index can effectively uncover the stability and droplet transition of GMAW.

A Subspace Approach to the Structural Decomposition and Identification of Ankle Joint Dynamic Stiffness.

PubMed

Jalaleddini, Kian; Tehrani, Ehsan Sobhani; Kearney, Robert E

2017-06-01

The purpose of this paper is to present a structural decomposition subspace (SDSS) method for decomposition of the joint torque to intrinsic, reflexive, and voluntary torques and identification of joint dynamic stiffness. First, it formulates a novel state-space representation for the joint dynamic stiffness modeled by a parallel-cascade structure with a concise parameter set that provides a direct link between the state-space representation matrices and the parallel-cascade parameters. Second, it presents a subspace method for the identification of the new state-space model that involves two steps: 1) the decomposition of the intrinsic and reflex pathways and 2) the identification of an impulse response model of the intrinsic pathway and a Hammerstein model of the reflex pathway. Extensive simulation studies demonstrate that SDSS has significant performance advantages over some other methods. Thus, SDSS was more robust under high noise conditions, converging where others failed; it was more accurate, giving estimates with lower bias and random errors. The method also worked well in practice and yielded high-quality estimates of intrinsic and reflex stiffnesses when applied to experimental data at three muscle activation levels. The simulation and experimental results demonstrate that SDSS accurately decomposes the intrinsic and reflex torques and provides accurate estimates of physiologically meaningful parameters. SDSS will be a valuable tool for studying joint stiffness under functionally important conditions. It has important clinical implications for the diagnosis, assessment, objective quantification, and monitoring of neuromuscular diseases that change the muscle tone.

Response of SOM Decomposition to Anthropogenic N Deposition: Simulations From the PnET-SOM Model.

NASA Astrophysics Data System (ADS)

Tonitto, C.; Goodale, C. L.; Ollinger, S. V.; Jenkins, J. P.

2008-12-01

Anthropogenic forcing of the C and N cycles has caused rapid change in atmospheric CO2 and N deposition, with complex and uncertain effects on forest C and N balance. With some exceptions, models of forest ecosystem response to anthropogenic perturbation have historically focused more on aboveground than belowground processes; the complexity of soil organic matter (SOM) is often represented with abstract or incomplete SOM pools, and remains difficult to quantify. We developed a model of SOM dynamics in northern hardwood forests with explicit feedbacks between C and N cycles. The soil model is linked to the aboveground dynamics of the PnET model to form PnET-SOM. The SOM model includes: 1) physically measurable SOM pools, including humic and mineral-associated SOM in O, A, and B soil horizons, 2) empirical soil turnover times based on 14C data, 3) alternative SOM decomposition algorithms with and without explicit microbial processing, and 4) soluble element transport explicitly linked to the hydrologic cycle. We tested model sensitivity to changes in litter decomposition rate (k) and completeness of decomposition (limit value) by altering these parameters based on experimental observations from long-term litter decomposition experiments with N fertilization treatments. After a 100 year simulation, the Oe+Oa horizon SOC pool was reduced by 15 % and the A-horizon humified SOC was reduced by 7 % for N deposition scenarios relative to forests without N fertilization. In contrast, predictions for slower time-scale pools showed negligible variation in response to variation in the limit values tested, with A-horizon mineral SOC pools reduced by < 3 % and B-horizon mineral SOC reduced by 0.1 % for N deposition scenarios relative to forests without N fertilization. The model was also used to test the effect of varying initial litter decomposition rate to simulate response to N deposition. In contrast to the effect of varying limit values, simulations in which only k-values were varied did not drastically alter the predicted SOC pool distribution throughout the soil profile, but did significantly alter the Oi SOC pool. These results suggest that describing soil response to N deposition via alteration of the limit value alone, or as a combined alteration of limit value and the initial decomposition rate, can lead to significant variation in predicted long-term C storage.

Model and Data Reduction for Control, Identification and Compressed Sensing

NASA Astrophysics Data System (ADS)

Kramer, Boris

This dissertation focuses on problems in design, optimization and control of complex, large-scale dynamical systems from different viewpoints. The goal is to develop new algorithms and methods, that solve real problems more efficiently, together with providing mathematical insight into the success of those methods. There are three main contributions in this dissertation. In Chapter 3, we provide a new method to solve large-scale algebraic Riccati equations, which arise in optimal control, filtering and model reduction. We present a projection based algorithm utilizing proper orthogonal decomposition, which is demonstrated to produce highly accurate solutions at low rank. The method is parallelizable, easy to implement for practitioners, and is a first step towards a matrix free approach to solve AREs. Numerical examples for n ≥ 106 unknowns are presented. In Chapter 4, we develop a system identification method which is motivated by tangential interpolation. This addresses the challenge of fitting linear time invariant systems to input-output responses of complex dynamics, where the number of inputs and outputs is relatively large. The method reduces the computational burden imposed by a full singular value decomposition, by carefully choosing directions on which to project the impulse response prior to assembly of the Hankel matrix. The identification and model reduction step follows from the eigensystem realization algorithm. We present three numerical examples, a mass spring damper system, a heat transfer problem, and a fluid dynamics system. We obtain error bounds and stability results for this method. Chapter 5 deals with control and observation design for parameter dependent dynamical systems. We address this by using local parametric reduced order models, which can be used online. Data available from simulations of the system at various configurations (parameters, boundary conditions) is used to extract a sparse basis to represent the dynamics (via dynamic mode decomposition). Subsequently, a new, compressed sensing based classification algorithm is developed which incorporates the extracted dynamic information into the sensing basis. We show that this augmented classification basis makes the method more robust to noise, and results in superior identification of the correct parameter. Numerical examples consist of a Navier-Stokes, as well as a Boussinesq flow application.

Thermal Analysis of porous fin with uniform magnetic field using Adomian decomposition Sumudu transform method

NASA Astrophysics Data System (ADS)

Patel, Trushit; Meher, Ramakanta

2017-09-01

In this paper, we consider a Roseland approximation to radiate heat transfer, Darcy's model to simulate the flow in porous media and finite-length fin with insulated tip to study the thermal performance and to predict the temperature distribution in a vertical isothermal surface. The energy balance equations of the porous fin with several temperature dependent properties are solved using the Adomian Decomposition Sumudu Transform Method (ADSTM). The effects of various thermophysical parameters, such as the convection-conduction parameter, Surface-ambient radiation parameter, Rayleigh numbers and Hartman number are determined. The results obtained from the ADSTM are further compared with the fourth-fifth order Runge-Kutta-Fehlberg method and Least Square Method(LSM) (Hoshyar et al. 2016 ) to determine the accuracy of the solution.

Climate fails to predict wood decomposition at regional scales

Treesearch

Mark A. Bradford; Robert J. Warren; Petr Baldrian; Thomas W. Crowther; Daniel S. Maynard; Emily E. Oldfield; William R. Wieder; Stephen A. Wood; Joshua R. King

2014-01-01

Decomposition of organic matter strongly influences ecosystem carbon storage1. In Earth-system models, climate is a predominant control on the decomposition rates of organic matter2, 3, 4, 5. This assumption is based on the mean response of decomposition to climate, yet there is a growing appreciation in other areas of global change science that projections based on...

An Efficient Local Correlation Matrix Decomposition Approach for the Localization Implementation of Ensemble-Based Assimilation Methods

NASA Astrophysics Data System (ADS)

Zhang, Hongqin; Tian, Xiangjun

2018-04-01

Ensemble-based data assimilation methods often use the so-called localization scheme to improve the representation of the ensemble background error covariance (Be). Extensive research has been undertaken to reduce the computational cost of these methods by using the localized ensemble samples to localize Be by means of a direct decomposition of the local correlation matrix C. However, the computational costs of the direct decomposition of the local correlation matrix C are still extremely high due to its high dimension. In this paper, we propose an efficient local correlation matrix decomposition approach based on the concept of alternating directions. This approach is intended to avoid direct decomposition of the correlation matrix. Instead, we first decompose the correlation matrix into 1-D correlation matrices in the three coordinate directions, then construct their empirical orthogonal function decomposition at low resolution. This procedure is followed by the 1-D spline interpolation process to transform the above decompositions to the high-resolution grid. Finally, an efficient correlation matrix decomposition is achieved by computing the very similar Kronecker product. We conducted a series of comparison experiments to illustrate the validity and accuracy of the proposed local correlation matrix decomposition approach. The effectiveness of the proposed correlation matrix decomposition approach and its efficient localization implementation of the nonlinear least-squares four-dimensional variational assimilation are further demonstrated by several groups of numerical experiments based on the Advanced Research Weather Research and Forecasting model.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hermann, Andrew T.; Wiley, John B.

The thermal stability and decomposition pathways of six Dion-Jacobson-related double-layered perovskites, ALaNb{sub 2}O{sub 7} (A = H, Li, Na, Ag) and (ACl)LaNb{sub 2}O{sub 7} (A = Fe, Cu), are investigated. These compounds are made by low temperature (<400 deg. C) ion exchange reactions from RbLaNb{sub 2}O{sub 7}. All the compounds are low temperature phases with some of them exhibiting decomposition exotherms consistent with metastability. Decomposition temperatures and reactions pathways vary with the identity of A with most decompositions resulting in the formation of a niobate (containing A) and LaNbO{sub 4}. Results from differential scanning calorimetry and high temperature X-ray powdermore » diffraction studies are presented and structural parameters pertinent to compound stability discussed.« less

Bromamine Decomposition Revisited: A Holistic Approach for Analyzing Acid and Base Catalysis Kinetics.

PubMed

Wahman, David G; Speitel, Gerald E; Katz, Lynn E

2017-11-21

Chloramine chemistry is complex, with a variety of reactions occurring in series and parallel and many that are acid or base catalyzed, resulting in numerous rate constants. Bromide presence increases system complexity even further with possible bromamine and bromochloramine formation. Therefore, techniques for parameter estimation must address this complexity through thoughtful experimental design and robust data analysis approaches. The current research outlines a rational basis for constrained data fitting using Brønsted theory, application of the microscopic reversibility principle to reversible acid or base catalyzed reactions, and characterization of the relative significance of parallel reactions using fictive product tracking. This holistic approach was used on a comprehensive and well-documented data set for bromamine decomposition, allowing new interpretations of existing data by revealing that a previously published reaction scheme was not robust; it was not able to describe monobromamine or dibromamine decay outside of the conditions for which it was calibrated. The current research's simplified model (3 reactions, 17 constants) represented the experimental data better than the previously published model (4 reactions, 28 constants). A final model evaluation was conducted based on representative drinking water conditions to determine a minimal model (3 reactions, 8 constants) applicable for drinking water conditions.

Development of an all-metal thick film cost effective metallization system for solar cells

NASA Technical Reports Server (NTRS)

Ross, B.

1981-01-01

The objectives of the investigation were to provide all-metal screenable pastes using economical base metals, suitable for application to low-to-high conductivity silicon of either conductivity type and possibly to aluminum surfaces. Experiments were conducted with variations in paste parameters, firing conditions, including gas ambients, furnace furniture, silicon surface and others. A liquid medium, intended to provide transport during the carbon fluoride decomposition was incorporated in the paste with promising results.

Design, Fabrication, Characterization and Modeling of Integrated Functional Materials

DTIC Science & Technology

2012-10-01

films. The successful optimization of the PZT thin film growth parameters allowed us to set the stage for doping PZT with rare earth elements...Lanthanum (La)-doped PZT (PLZT) (where Pb2+ is substituted by La3+), has a dramatic enhancement in the piezoelectric properties. There have been only a...few recent reports on the growth of La- PZT films. However, most of the reports were based on chemical routes such as metal organic decomposition

Linking Combat Systems Capabilities and Ship Design Through Modeling and Computer Simulation

DTIC Science & Technology

2013-09-01

23 C. OVERVIEW OF FIVE—PARAMETER METHOD .................................24 1. Lift /Drag Ratio (L/D Ratio...FOR TESTING ..............29 1. Parameter 1: Lift /Drag Ratio (calculated value) ............................29 2. Parameter 2: Overall Propulsion...34 G. METRIC CONVERSIONS—JANE’S DATA ............................................35 H. DECOMPOSITION – LIFT TO DRAG RATIO AND

Extended FDD-WT method based on correcting the errors due to non-synchronous sensing of sensors

NASA Astrophysics Data System (ADS)

Tarinejad, Reza; Damadipour, Majid

2016-05-01

In this research, a combinational non-parametric method called frequency domain decomposition-wavelet transform (FDD-WT) that was recently presented by the authors, is extended for correction of the errors resulting from asynchronous sensing of sensors, in order to extend the application of the algorithm for different kinds of structures, especially for huge structures. Therefore, the analysis process is based on time-frequency domain decomposition and is performed with emphasis on correcting time delays between sensors. Time delay estimation (TDE) methods are investigated for their efficiency and accuracy for noisy environmental records and the Phase Transform - β (PHAT-β) technique was selected as an appropriate method to modify the operation of traditional FDD-WT in order to achieve the exact results. In this paper, a theoretical example (3DOF system) has been provided in order to indicate the non-synchronous sensing effects of the sensors on the modal parameters; moreover, the Pacoima dam subjected to 13 Jan 2001 earthquake excitation was selected as a case study. The modal parameters of the dam obtained from the extended FDD-WT method were compared with the output of the classical signal processing method, which is referred to as 4-Spectral method, as well as other literatures relating to the dynamic characteristics of Pacoima dam. The results comparison indicates that values are correct and reliable.

Fast reactions of aluminum and explosive decomposition products in a post-detonation environment

NASA Astrophysics Data System (ADS)

Tappan, Bryce C.; Manner, Virginia W.; Lloyd, Joseph M.; Pemberton, Steven J.

2012-03-01

In order to determine the reaction behavior of Al in RDX or HMX/cast-cured binder formulations shortly after the passage of the detonation, a series of cylinder tests was performed on formulations comprising of varying binder systems and either 3.5 μm spherical Al or LiF (an inert salt with a similar molecular weight and density to Al). In these studies, both detonation velocity and cylinder expansion velocity are measured in order to determine exactly how and when Al contributes to the explosive event, particularly in the presence of oxidizing/energetic binders. The U.S. Army Research, Development and Engineering Laboratory at Picatinny have recently coined the term "combined effects" explosives for materials such as these; as they demonstrate both high metal pushing capability and high blast ability. This study is aimed at developing a fundamental understanding of the reaction of Al with explosives decomposition products, where both the detonation and early post-detonation environment are analyzed. Reaction rates of Al metal are investigated via comparison of predicted performance based on thermoequilibrium calculations. The detonation velocities, wall velocities, and parameters at the CJ plane are some of the parameters that will be discussed.

Modeling carbon cycle process of soil profile in Loess Plateau of China

NASA Astrophysics Data System (ADS)

Yu, Y.; Finke, P.; Guo, Z.; Wu, H.

2011-12-01

SoilGen2 is a process-based model, which could reconstruct soil formation under various climate conditions, parent materials, vegetation types, slopes, expositions and time scales. Both organic and inorganic carbon cycle processes could be simulated, while the later process is important in carbon cycle of arid and semi-arid regions but seldom being studied. After calibrating parameters of dust deposition rate and segments depth affecting elements transportation and deposition in the profile, modeling results after 10000 years were confronted with measurements of two soil profiles in loess plateau of China, The simulated trends of organic carbon and CaCO3 in the profile are similar to measured values. Relative sensitivity analysis for carbon cycle process have been done and the results show that the change of organic carbon in long time scale is more sensitive to precipitation, temperature, plant carbon input and decomposition parameters (decomposition rate of humus, ratio of CO2/(BIO+HUM), etc.) in the model. As for the inorganic carbon cycle, precipitation and potential evaporation are important for simulation quality, while the leaching and deposition of CaCO3 are not sensitive to pCO2 and temperature of atmosphere.

Modeling of a pitching and plunging airfoil using experimental flow field and load measurements

NASA Astrophysics Data System (ADS)

Troshin, Victor; Seifert, Avraham

2018-01-01

The main goal of the current paper is to outline a low-order modeling procedure of a heaving airfoil in a still fluid using experimental measurements. Due to its relative simplicity, the proposed procedure is applicable for the analysis of flow fields within complex and unsteady geometries and it is suitable for analyzing the data obtained by experimentation. Currently, this procedure is used to model and predict the flow field evolution using a small number of low profile load sensors and flow field measurements. A time delay neural network is used to estimate the flow field. The neural network estimates the amplitudes of the most energetic modes using four sensory inputs. The modes are calculated using proper orthogonal decomposition of the flow field data obtained experimentally by time-resolved, phase-locked particle imaging velocimetry. To permit the use of proper orthogonal decomposition, the measured flow field is mapped onto a stationary domain using volume preserving transformation. The analysis performed by the model showed good estimation quality within the parameter range used in the training procedure. However, the performance deteriorates for cases out of this range. This situation indicates that, to improve the robustness of the model, both the decomposition and the training data sets must be diverse in terms of input parameter space. In addition, the results suggest that the property of volume preservation of the mapping does not affect the model quality as long as the model is not based on the Galerkin approximation. Thus, it may be relaxed for cases with more complex geometry and kinematics.

Explosive and pyrotechnic aging demonstration

NASA Technical Reports Server (NTRS)

Rouch, L. L., Jr.; Maycock, J. N.

1976-01-01

The survivability was experimentally verified of fine selected explosive and pyrotechnic propellant materials when subjected to sterilization, and prolonged exposure to space environments. This verification included thermal characterization, sterilization heat cycling, sublimation measurements, isothermal decomposition measurements, and accelerated aging at a preselected elevated temperature. Temperatures chosen for sublimation and isothermal decomposition measurements were those in which the decomposition processess occurring would be the same as those taking place in real-time aging. The elevated temperature selected (84 C) for accelerated aging was based upon the parameters calculated from the kinetic data obtained in the isothermal measurement tests and was such that one month of accelerated aging in the laboratory approximated one year of real-time aging at 66 C. Results indicate that HNS-IIA, pure PbN6, KDNBF, and Zr/KC10 are capable of withstanding sterilization. The accelerated aging tests indicated that unsterilized HNS-IIA and Zr/KC104 can withstand the 10 year, elevated temperature exposure, pure PbN6 and KDNBF exhibit small weight losses (less than 2 percent) and B/KC104 exhibits significant changes in its thermal characteristics. Accelerated aging tests after sterilization indicated that only HNS-IIA exhibited high stability.

Erosion of soil organic carbon: implications for carbon sequestration

USGS Publications Warehouse

Van Oost, Kristof; Van Hemelryck, Hendrik; Harden, Jennifer W.; McPherson, B.J.; Sundquist, E.T.

2009-01-01

Agricultural activities have substantially increased rates of soil erosion and deposition, and these processes have a significant impact on carbon (C) mineralization and burial. Here, we present a synthesis of erosion effects on carbon dynamics and discuss the implications of soil erosion for carbon sequestration strategies. We demonstrate that for a range of data-based parameters from the literature, soil erosion results in increased C storage onto land, an effect that is heterogeneous on the landscape and is variable on various timescales. We argue that the magnitude of the erosion term and soil carbon residence time, both strongly influenced by soil management, largely control the strength of the erosion-induced sink. In order to evaluate fully the effects of soil management strategies that promote carbon sequestration, a full carbon account must be made that considers the impact of erosion-enhanced disequilibrium between carbon inputs and decomposition, including effects on net primary productivity and decomposition rates.

Forward Looking Radar Imaging by Truncated Singular Value Decomposition and Its Application for Adverse Weather Aircraft Landing.

PubMed

Huang, Yulin; Zha, Yuebo; Wang, Yue; Yang, Jianyu

2015-06-18

The forward looking radar imaging task is a practical and challenging problem for adverse weather aircraft landing industry. Deconvolution method can realize the forward looking imaging but it often leads to the noise amplification in the radar image. In this paper, a forward looking radar imaging based on deconvolution method is presented for adverse weather aircraft landing. We first present the theoretical background of forward looking radar imaging task and its application for aircraft landing. Then, we convert the forward looking radar imaging task into a corresponding deconvolution problem, which is solved in the framework of algebraic theory using truncated singular decomposition method. The key issue regarding the selecting of the truncated parameter is addressed using generalized cross validation approach. Simulation and experimental results demonstrate that the proposed method is effective in achieving angular resolution enhancement with suppressing the noise amplification in forward looking radar imaging.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Whitford, W.G.; Elkins, N.Z.; Parker, L.W.

In laboratory microcosms of coal mine spoil amended with bark and wood chips, the activity of termites increased organic matter and increased total nitrogen. Termite survival was reduced in microcosms with spoil and paper or straw amendments. Field studies evaluating the efficacy of organic amendments in developing a soil biota showed that decomposition rates of wood chip-bark amended spoil were the same as unmined soil and that decomposition rates were lower than all other mulch-spoil combinations. Wood and bark amended-spoil had the highest density and diversity of soil fauna. Top dressing spoils with borrow soil did not improve any ofmore » the soil biological parameters measured. Based on these data it was recommended that reclamation procedures be changed to eliminate borrow soil top-dressing and that wood removed from mined areas be returned to the contoured spoil as wood chip amendment in addition to straw mulch.« less

Hemodynamics of a Patient-Specific Aneurysm Model with Proper Orthogonal Decomposition

NASA Astrophysics Data System (ADS)

Han, Suyue; Chang, Gary Han; Modarres-Sadeghi, Yahya

2017-11-01

Wall shear stress (WSS) and oscillatory shear index (OSI) are two of the most-widely studied hemodynamic quantities in cardiovascular systems that have been shown to have the ability to elicit biological responses of the arterial wall, which could be used to predict the aneurysm development and rupture. In this study, a reduced-order model (ROM) of the hemodynamics of a patient-specific cerebral aneurysm is studied. The snapshot Proper Orthogonal Decomposition (POD) is utilized to construct the reduced-order bases of the flow using a CFD training set with known inflow parameters. It was shown that the area of low WSS and high OSI is correlated to higher POD modes. The resulting ROM can reproduce both WSS and OSI computationally for future parametric studies with significantly less computational cost. Agreement was observed between the WSS and OSI values obtained using direct CFD results and ROM results.

Computer simulations of austenite decomposition of microalloyed 700 MPa steel during cooling

NASA Astrophysics Data System (ADS)

Pohjonen, Aarne; Paananen, Joni; Mourujärvi, Juho; Manninen, Timo; Larkiola, Jari; Porter, David

2018-05-01

We present computer simulations of austenite decomposition to ferrite and bainite during cooling. The phase transformation model is based on Johnson-Mehl-Avrami-Kolmogorov type equations. The model is parameterized by numerical fitting to continuous cooling data obtained with Gleeble thermo-mechanical simulator and it can be used for calculation of the transformation behavior occurring during cooling along any cooling path. The phase transformation model has been coupled with heat conduction simulations. The model includes separate parameters to account for the incubation stage and for the kinetics after the transformation has started. The incubation time is calculated with inversion of the CCT transformation start time. For heat conduction simulations we employed our own parallelized 2-dimensional finite difference code. In addition, the transformation model was also implemented as a subroutine in commercial finite-element software Abaqus which allows for the use of the model in various engineering applications.

Characteristic analysis on UAV-MIMO channel based on normalized correlation matrix.

PubMed

Gao, Xi jun; Chen, Zi li; Hu, Yong Jiang

2014-01-01

Based on the three-dimensional GBSBCM (geometrically based double bounce cylinder model) channel model of MIMO for unmanned aerial vehicle (UAV), the simple form of UAV space-time-frequency channel correlation function which includes the LOS, SPE, and DIF components is presented. By the methods of channel matrix decomposition and coefficient normalization, the analytic formula of UAV-MIMO normalized correlation matrix is deduced. This formula can be used directly to analyze the condition number of UAV-MIMO channel matrix, the channel capacity, and other characteristic parameters. The simulation results show that this channel correlation matrix can be applied to describe the changes of UAV-MIMO channel characteristics under different parameter settings comprehensively. This analysis method provides a theoretical basis for improving the transmission performance of UAV-MIMO channel. The development of MIMO technology shows practical application value in the field of UAV communication.

Characteristic Analysis on UAV-MIMO Channel Based on Normalized Correlation Matrix

PubMed Central

Xi jun, Gao; Zi li, Chen; Yong Jiang, Hu

2014-01-01

Based on the three-dimensional GBSBCM (geometrically based double bounce cylinder model) channel model of MIMO for unmanned aerial vehicle (UAV), the simple form of UAV space-time-frequency channel correlation function which includes the LOS, SPE, and DIF components is presented. By the methods of channel matrix decomposition and coefficient normalization, the analytic formula of UAV-MIMO normalized correlation matrix is deduced. This formula can be used directly to analyze the condition number of UAV-MIMO channel matrix, the channel capacity, and other characteristic parameters. The simulation results show that this channel correlation matrix can be applied to describe the changes of UAV-MIMO channel characteristics under different parameter settings comprehensively. This analysis method provides a theoretical basis for improving the transmission performance of UAV-MIMO channel. The development of MIMO technology shows practical application value in the field of UAV communication. PMID:24977185

Kinetics of Thermal Decomposition of Ammonium Perchlorate by TG/DSC-MS-FTIR

NASA Astrophysics Data System (ADS)

Zhu, Yan-Li; Huang, Hao; Ren, Hui; Jiao, Qing-Jie

2014-01-01

The method of thermogravimetry/differential scanning calorimetry-mass spectrometry-Fourier transform infrared (TG/DSC-MS-FTIR) simultaneous analysis has been used to study thermal decomposition of ammonium perchlorate (AP). The processing of nonisothermal data at various heating rates was performed using NETZSCH Thermokinetics. The MS-FTIR spectra showed that N2O and NO2 were the main gaseous products of the thermal decomposition of AP, and there was a competition between the formation reaction of N2O and that of NO2 during the process with an iso-concentration point of N2O and NO2. The dependence of the activation energy calculated by Friedman's iso-conversional method on the degree of conversion indicated that the AP decomposition process can be divided into three stages, which are autocatalytic, low-temperature diffusion and high-temperature, stable-phase reaction. The corresponding kinetic parameters were determined by multivariate nonlinear regression and the mechanism of the AP decomposition process was proposed.

Detection and identification of concealed weapons using matrix pencil

NASA Astrophysics Data System (ADS)

Adve, Raviraj S.; Thayaparan, Thayananthan

2011-06-01

The detection and identification of concealed weapons is an extremely hard problem due to the weak signature of the target buried within the much stronger signal from the human body. This paper furthers the automatic detection and identification of concealed weapons by proposing the use of an effective approach to obtain the resonant frequencies in a measurement. The technique, based on Matrix Pencil, a scheme for model based parameter estimation also provides amplitude information, hence providing a level of confidence in the results. Of specific interest is the fact that Matrix Pencil is based on a singular value decomposition, making the scheme robust against noise.

Preparation, characterization and thermolysis of phenylenediammonium dinitrate salts.

PubMed

Kapoor, Inder Pal Singh; Srivastava, Pratibha; Singh, Gurdip

2008-02-11

Four phenylenediammonium dinitrate salts were prepared and characterized by elemental, Infrared spectroscopy (IR), Ultraviolet spectroscopy (UV) and gravimetric methods. These dinitrates find application in propellant, explosives and pyrotechnics. Their thermal decomposition has been studied using thermogravimetry (TG) and simultaneous thermogravimetry-differential scanning calorimetry (TG-DSC). Kinetics parameters were evaluated by model fitting and isoconversional methods. Their thermolytic pathways have also been suggested, which involves decomposition followed by ignition.

A compositional approach to building applications in a computational environment

NASA Astrophysics Data System (ADS)

Roslovtsev, V. V.; Shumsky, L. D.; Wolfengagen, V. E.

2014-04-01

The paper presents an approach to creating an applicative computational environment to feature computational processes and data decomposition, and a compositional approach to application building. The approach in question is based on the notion of combinator - both in systems with variable binding (such as λ-calculi) and those allowing programming without variables (combinatory logic style). We present a computation decomposition technique based on objects' structural decomposition, with the focus on computation decomposition. The computational environment's architecture is based on a network with nodes playing several roles simultaneously.

CO2 fluxes and ecosystem dynamics at five European treeless peatlands - merging data and process oriented modelling

NASA Astrophysics Data System (ADS)

Metzger, C.; Jansson, P.-E.; Lohila, A.; Aurela, M.; Eickenscheidt, T.; Belelli-Marchesini, L.; Dinsmore, K. J.; Drewer, J.; van Huissteden, J.; Drösler, M.

2014-06-01

The carbon dioxide (CO2) exchange of five different peatland systems across Europe with a wide gradient in landuse intensity, water table depth, soil fertility and climate was simulated with the process oriented CoupModel. The aim of the study was to find out to what extent CO2 fluxes measured at different sites, can be explained by common processes and parameters implemented in the model. The CoupModel was calibrated to fit measured CO2 fluxes, soil temperature, snow depth and leaf area index (LAI) and resulting differences in model parameters were analysed. Finding site independent model parameters would mean that differences in the measured fluxes could be explained solely by model input data: water table, meteorological data, management and soil inventory data. The model, utilizing a site independent configuration for most of the parameters, captured seasonal variability in the major fluxes well. Parameters that differed between sites included the rate of soil organic decomposition, photosynthetic efficiency, and regulation of the mobile carbon (C) pool from senescence to shooting in the next year. The largest difference between sites was the rate coefficient for heterotrophic respiration. Setting it to a common value would lead to underestimation of mean total respiration by a factor of 2.8 up to an overestimation by a factor of 4. Despite testing a wide range of different responses to soil water and temperature, heterotrophic respiration rates were consistently lowest on formerly drained sites and highest on the managed sites. Substrate decomposability, pH and vegetation characteristics are possible explanations for the differences in decomposition rates. Applying common parameter values for the timing of plant shooting and senescence, and a minimum temperature for photosynthesis, had only a minor effect on model performance, even though the gradient in site latitude ranged from 48° N (South-Germany) to 68° N (northern Finland). This was also true for common parameters defining the moisture and temperature response for decomposition. CoupModel is able to describe measured fluxes at different sites or under different conditions, providing that the rate of soil organic decomposition, photosynthetic efficiency, and the regulation of the mobile carbon (C) pool are estimated from available information on specific soil conditions, vegetation and management of the ecosystems.

Wavelet transforms with discrete-time continuous-dilation wavelets

NASA Astrophysics Data System (ADS)

Zhao, Wei; Rao, Raghuveer M.

1999-03-01

Wavelet constructions and transforms have been confined principally to the continuous-time domain. Even the discrete wavelet transform implemented through multirate filter banks is based on continuous-time wavelet functions that provide orthogonal or biorthogonal decompositions. This paper provides a novel wavelet transform construction based on the definition of discrete-time wavelets that can undergo continuous parameter dilations. The result is a transformation that has the advantage of discrete-time or digital implementation while circumventing the problem of inadequate scaling resolution seen with conventional dyadic or M-channel constructions. Examples of constructing such wavelets are presented.

An Extension of the Partial Credit Model with an Application to the Measurement of Change.

ERIC Educational Resources Information Center

Fischer, Gerhard H.; Ponocny, Ivo

1994-01-01

An extension to the partial credit model, the linear partial credit model, is considered under the assumption of a certain linear decomposition of the item x category parameters into basic parameters. A conditional maximum likelihood algorithm for estimating basic parameters is presented and illustrated with simulation and an empirical study. (SLD)

Algebraic multigrid domain and range decomposition (AMG-DD / AMG-RD)*

DOE PAGES

Bank, R.; Falgout, R. D.; Jones, T.; ...

2015-10-29

In modern large-scale supercomputing applications, algebraic multigrid (AMG) is a leading choice for solving matrix equations. However, the high cost of communication relative to that of computation is a concern for the scalability of traditional implementations of AMG on emerging architectures. This paper introduces two new algebraic multilevel algorithms, algebraic multigrid domain decomposition (AMG-DD) and algebraic multigrid range decomposition (AMG-RD), that replace traditional AMG V-cycles with a fully overlapping domain decomposition approach. While the methods introduced here are similar in spirit to the geometric methods developed by Brandt and Diskin [Multigrid solvers on decomposed domains, in Domain Decomposition Methods inmore » Science and Engineering, Contemp. Math. 157, AMS, Providence, RI, 1994, pp. 135--155], Mitchell [Electron. Trans. Numer. Anal., 6 (1997), pp. 224--233], and Bank and Holst [SIAM J. Sci. Comput., 22 (2000), pp. 1411--1443], they differ primarily in that they are purely algebraic: AMG-RD and AMG-DD trade communication for computation by forming global composite “grids” based only on the matrix, not the geometry. (As is the usual AMG convention, “grids” here should be taken only in the algebraic sense, regardless of whether or not it corresponds to any geometry.) Another important distinguishing feature of AMG-RD and AMG-DD is their novel residual communication process that enables effective parallel computation on composite grids, avoiding the all-to-all communication costs of the geometric methods. The main purpose of this paper is to study the potential of these two algebraic methods as possible alternatives to existing AMG approaches for future parallel machines. As a result, this paper develops some theoretical properties of these methods and reports on serial numerical tests of their convergence properties over a spectrum of problem parameters.« less

The biology and ecology of Necrodes littoralis, a species of forensic interest in Europe.

PubMed

Charabidze, Damien; Vincent, Benoît; Pasquerault, Thierry; Hedouin, Valéry

2016-01-01

Necrodes littoralis (Linnaeus, 1758) (Coleoptera: Silphidae), also known as the "shore sexton beetle," is a common silphid beetle that visits and breeds on large vertebrate cadavers. This study describes, for the first time, the involvement of N. littoralis on human corpses based on a large dataset of 154 French forensic cases. Various parameters regarding corpse location, decomposition stages, and entomofauna were extracted from each file. Compared to all of the forensic entomology cases analyzed between 1990 and 2013 (1028), N. littoralis was observed, on average, in one case out of eight; most of these cases occurred during spring and summer (73.5%). More than 90% of the cases were located outdoors, especially in woodlands, bushes, and fields. The decomposition stage of the corpse varied among cases, with more than 50% in the advanced decomposition stage, 36% in the early decomposition stage, and less than 10% in the fresh, mummified, or skeletonized stages. Regarding other necrophagous species sampled with N. littoralis, Calliphorid flies were found in 94% of the cases and Fanniidae/Muscidae in 65% of the cases. Chrysomya albiceps, a heliophilic species mostly located in the Mediterranean area, was present in 34% of the cases (only 20% in the whole dataset). The most common coleopteran species were Necrobia spp. (Coleoptera: Cleridae) and Creophilus maxillosus (Coleoptera: Staphylinidae); these beetles were observed in 27% of the cases. The over-representation of these species is likely due to similar requirements regarding the climate and decomposition stage. As N. littoralis is frequently observed and tends to become more common, we conclude that the developmental data for this species would be a precious tool for forensic entomologists in Europe.

Thermal degradation of ternary blend films containing PVA/chitosan/vanillin

NASA Astrophysics Data System (ADS)

Kasai, Deepak; Chougale, Ravindra; Masti, Saraswati; Narasgoudar, Shivayogi

2018-05-01

The ternary chitosan/poly (vinyl alcohol)/vanillin blend films were prepared by solution casting method. The influence of equal weight percent of poly (vinyl alcohol) and vanillin on thermal stability of the chitosan blend films were investigated by using thermogravimetric analysis (TGA). The kinetic parameters such as enthalpy (ΔH*), entropy (ΔS*), and Gibbs free energy (ΔG*) in the first and second decomposition steps based on the thermogravimetric data were calculated. The thermal stabilities of the blend films were confirmed by thermodynamic parameters obtained in the activation energies, which indicated that increase in the equal weight percent of PVA/vanillin decreased the thermal stability of the chitosan film.

Predicting responses from Rasch measures.

PubMed

Linacre, John M

2010-01-01

There is a growing family of Rasch models for polytomous observations. Selecting a suitable model for an existing dataset, estimating its parameters and evaluating its fit is now routine. Problems arise when the model parameters are to be estimated from the current data, but used to predict future data. In particular, ambiguities in the nature of the current data, or overfit of the model to the current dataset, may mean that better fit to the current data may lead to worse fit to future data. The predictive power of several Rasch and Rasch-related models are discussed in the context of the Netflix Prize. Rasch-related models are proposed based on Singular Value Decomposition (SVD) and Boltzmann Machines.

A Method to Solve Interior and Exterior Camera Calibration Parameters for Image Resection

NASA Technical Reports Server (NTRS)

Samtaney, Ravi

1999-01-01

An iterative method is presented to solve the internal and external camera calibration parameters, given model target points and their images from one or more camera locations. The direct linear transform formulation was used to obtain a guess for the iterative method, and herein lies one of the strengths of the present method. In all test cases, the method converged to the correct solution. In general, an overdetermined system of nonlinear equations is solved in the least-squares sense. The iterative method presented is based on Newton-Raphson for solving systems of nonlinear algebraic equations. The Jacobian is analytically derived and the pseudo-inverse of the Jacobian is obtained by singular value decomposition.

Health monitoring of pipeline girth weld using empirical mode decomposition

NASA Astrophysics Data System (ADS)

Rezaei, Davood; Taheri, Farid

2010-05-01

In the present paper the Hilbert-Huang transform (HHT), as a time-series analysis technique, has been combined with a local diagnostic approach in an effort to identify flaws in pipeline girth welds. This method is based on monitoring the free vibration signals of the pipe at its healthy and flawed states, and processing the signals through the HHT and its associated signal decomposition technique, known as empirical mode decomposition (EMD). The EMD method decomposes the vibration signals into a collection of intrinsic mode functions (IMFs). The deviations in structural integrity, measured from a healthy-state baseline, are subsequently evaluated by two damage sensitive parameters. The first is a damage index, referred to as the EM-EDI, which is established based on an energy comparison of the first or second IMF of the vibration signals, before and after occurrence of damage. The second parameter is the evaluation of the lag in instantaneous phase, a quantity derived from the HHT. In the developed methodologies, the pipe's free vibration is monitored by piezoceramic sensors and a laser Doppler vibrometer. The effectiveness of the proposed techniques is demonstrated through a set of numerical and experimental studies on a steel pipe with a mid-span girth weld, for both pressurized and nonpressurized conditions. To simulate a crack, a narrow notch is cut on one side of the girth weld. Several damage scenarios, including notches of different depths and at various locations on the pipe, are investigated. Results from both numerical and experimental studies reveal that in all damage cases the sensor located at the notch vicinity could successfully detect the notch and qualitatively predict its severity. The effect of internal pressure on the damage identification method is also monitored. Overall, the results are encouraging and promise the effectiveness of the proposed approaches as inexpensive systems for structural health monitoring purposes.

Sensitivity analysis of a model of CO2 exchange in tundra ecosystems by the adjoint method

NASA Technical Reports Server (NTRS)

Waelbroek, C.; Louis, J.-F.

1995-01-01

A model of net primary production (NPP), decomposition, and nitrogen cycling in tundra ecosystems has been developed. The adjoint technique is used to study the sensitivity of the computed annual net CO2 flux to perturbation in initial conditions, climatic inputs, and model's main parameters describing current seasonal CO2 exchange in wet sedge tundra at Barrow, Alaska. The results show that net CO2 flux is most sensitive to parameters characterizing litter chemical composition and more sensitive to decomposition parameters than to NPP parameters. This underlines the fact that in nutrient-limited ecosystems, decomposition drives net CO2 exchange by controlling mineralization of main nutrients. The results also indicate that the short-term (1 year) response of wet sedge tundra to CO2-induced warming is a significant increase in CO2 emission, creating a positive feedback to atmosphreic CO2 accumulation. However, a cloudiness increase during the same year can severely alter this response and lead to either a slight decrease or a strong increase in emitted CO2, depending on its exact timing. These results demonstrate that the adjoint method is well suited to study systems encountering regime changes, as a single run of the adjoint model provides sensitivities of the net CO2 flux to perturbations in all parameters and variables at any time of the year. Moreover, it is shown that large errors due to the presence of thresholds can be avoided by first delimiting the range of applicability of the adjoint results.

A parallel algorithm for nonlinear convection-diffusion equations

NASA Technical Reports Server (NTRS)

Scroggs, Jeffrey S.

1990-01-01

A parallel algorithm for the efficient solution of nonlinear time-dependent convection-diffusion equations with small parameter on the diffusion term is presented. The method is based on a physically motivated domain decomposition that is dictated by singular perturbation analysis. The analysis is used to determine regions where certain reduced equations may be solved in place of the full equation. The method is suitable for the solution of problems arising in the simulation of fluid dynamics. Experimental results for a nonlinear equation in two-dimensions are presented.

Dynamics of controllably induced bruises assessed by diffuse reflectance spectroscopy and pulsed photothermal radiometry

NASA Astrophysics Data System (ADS)

Marin, Ana; Milanič, Matija; Verdel, Nina; Vidovič, Luka; Majaron, Boris

2018-02-01

Combination of diffuse reflectance spectroscopy (DRS) and pulsed photothermal radiometry (PPTR) was recently successfully used to study evolution of accidental traumatic bruises. Yet, accidental bruises introduce many unknowns into the evolution analysis and thus a more controllable and repeatable approach for bruising is desired. In this study, evolution of bruises induced by aluminum projectiles of known mass and velocity were studied by DRS and PPTR. Bruises were induced on volar forearm skin of two healthy volunteers. Inverse Monte Carlo including four-layer skin model, was used to analyze the DRS and PPTR data to determine skin chromophores, their concentrations and depths. For bruise analysis, a bruise model was constructed and evolved according to hemoglobin diffusion kinetics. Bruise analysis of PPTR signals yielded bruise evolution parameters, most importantly hemoglobin diffusion constant, hemoglobin decomposition time and blood pool depth. The study results show that chronological tracking of hemoglobin decomposition can be assessed by the combined DRS and PPTR technique on induced bruise. Parameters of individual bruises were compared and two trends in chronological behavior of hemoglobin decomposition time discerned. Changes in bruise diffuse reflectance spectra were noted. Induced bruise parameters, however, still showed some scatter and thus further research is needed to reduce bruise variability.

Prediction of S-wave velocity using complete ensemble empirical mode decomposition and neural networks

NASA Astrophysics Data System (ADS)

Gaci, Said; Hachay, Olga; Zaourar, Naima

2017-04-01

One of the key elements in hydrocarbon reservoirs characterization is the S-wave velocity (Vs). Since the traditional estimating methods often fail to accurately predict this physical parameter, a new approach that takes into account its non-stationary and non-linear properties is needed. In this view, a prediction model based on complete ensemble empirical mode decomposition (CEEMD) and a multiple layer perceptron artificial neural network (MLP ANN) is suggested to compute Vs from P-wave velocity (Vp). Using a fine-to-coarse reconstruction algorithm based on CEEMD, the Vp log data is decomposed into a high frequency (HF) component, a low frequency (LF) component and a trend component. Then, different combinations of these components are used as inputs of the MLP ANN algorithm for estimating Vs log. Applications on well logs taken from different geological settings illustrate that the predicted Vs values using MLP ANN with the combinations of HF, LF and trend in inputs are more accurate than those obtained with the traditional estimating methods. Keywords: S-wave velocity, CEEMD, multilayer perceptron neural networks.

Asymmetric multiple information cryptosystem based on chaotic spiral phase mask and random spectrum decomposition

NASA Astrophysics Data System (ADS)

Rafiq Abuturab, Muhammad

2018-01-01

A new asymmetric multiple information cryptosystem based on chaotic spiral phase mask (CSPM) and random spectrum decomposition is put forwarded. In the proposed system, each channel of secret color image is first modulated with a CSPM and then gyrator transformed. The gyrator spectrum is randomly divided into two complex-valued masks. The same procedure is applied to multiple secret images to get their corresponding first and second complex-valued masks. Finally, first and second masks of each channel are independently added to produce first and second complex ciphertexts, respectively. The main feature of the proposed method is the different secret images encrypted by different CSPMs using different parameters as the sensitive decryption/private keys which are completely unknown to unauthorized users. Consequently, the proposed system would be resistant to potential attacks. Moreover, the CSPMs are easier to position in the decoding process owing to their own centering mark on axis focal ring. The retrieved secret images are free from cross-talk noise effects. The decryption process can be implemented by optical experiment. Numerical simulation results demonstrate the viability and security of the proposed method.

Investigation of KDP crystal surface based on an improved bidimensional empirical mode decomposition method

NASA Astrophysics Data System (ADS)

Lu, Lei; Yan, Jihong; Chen, Wanqun; An, Shi

2018-03-01

This paper proposed a novel spatial frequency analysis method for the investigation of potassium dihydrogen phosphate (KDP) crystal surface based on an improved bidimensional empirical mode decomposition (BEMD) method. Aiming to eliminate end effects of the BEMD method and improve the intrinsic mode functions (IMFs) for the efficient identification of texture features, a denoising process was embedded in the sifting iteration of BEMD method. With removing redundant information in decomposed sub-components of KDP crystal surface, middle spatial frequencies of the cutting and feeding processes were identified. Comparative study with the power spectral density method, two-dimensional wavelet transform (2D-WT), as well as the traditional BEMD method, demonstrated that the method developed in this paper can efficiently extract texture features and reveal gradient development of KDP crystal surface. Furthermore, the proposed method was a self-adaptive data driven technique without prior knowledge, which overcame shortcomings of the 2D-WT model such as the parameters selection. Additionally, the proposed method was a promising tool for the application of online monitoring and optimal control of precision machining process.

Least squares parameter estimation methods for material decomposition with energy discriminating detectors

PubMed Central

Le, Huy Q.; Molloi, Sabee

2011-01-01

Purpose: Energy resolving detectors provide more than one spectral measurement in one image acquisition. The purpose of this study is to investigate, with simulation, the ability to decompose four materials using energy discriminating detectors and least squares minimization techniques. Methods: Three least squares parameter estimation decomposition techniques were investigated for four-material breast imaging tasks in the image domain. The first technique treats the voxel as if it consisted of fractions of all the materials. The second method assumes that a voxel primarily contains one material and divides the decomposition process into segmentation and quantification tasks. The third is similar to the second method but a calibration was used. The simulated computed tomography (CT) system consisted of an 80 kVp spectrum and a CdZnTe (CZT) detector that could resolve the x-ray spectrum into five energy bins. A postmortem breast specimen was imaged with flat panel CT to provide a model for the digital phantoms. Hydroxyapatite (HA) (50, 150, 250, 350, 450, and 550 mg∕ml) and iodine (4, 12, 20, 28, 36, and 44 mg∕ml) contrast elements were embedded into the glandular region of the phantoms. Calibration phantoms consisted of a 30∕70 glandular-to-adipose tissue ratio with embedded HA (100, 200, 300, 400, and 500 mg∕ml) and iodine (5, 15, 25, 35, and 45 mg∕ml). The x-ray transport process was simulated where the Beer–Lambert law, Poisson process, and CZT absorption efficiency were applied. Qualitative and quantitative evaluations of the decomposition techniques were performed and compared. The effect of breast size was also investigated. Results: The first technique decomposed iodine adequately but failed for other materials. The second method separated the materials but was unable to quantify the materials. With the addition of a calibration, the third technique provided good separation and quantification of hydroxyapatite, iodine, glandular, and adipose tissues. Quantification with this technique was accurate with errors of 9.83% and 6.61% for HA and iodine, respectively. Calibration at one point (one breast size) showed increased errors as the mismatch in breast diameters between calibration and measurement increased. A four-point calibration successfully decomposed breast diameter spanning the entire range from 8 to 20 cm. For a 14 cm breast, errors were reduced from 5.44% to 1.75% and from 6.17% to 3.27% with the multipoint calibration for HA and iodine, respectively. Conclusions: The results of the simulation study showed that a CT system based on CZT detectors in conjunction with least squares minimization technique can be used to decompose four materials. The calibrated least squares parameter estimation decomposition technique performed the best, separating and accurately quantifying the concentrations of hydroxyapatite and iodine. PMID:21361193

A practical material decomposition method for x-ray dual spectral computed tomography.

PubMed

Hu, Jingjing; Zhao, Xing

2016-03-17

X-ray dual spectral CT (DSCT) scans the measured object with two different x-ray spectra, and the acquired rawdata can be used to perform the material decomposition of the object. Direct calibration methods allow a faster material decomposition for DSCT and can be separated in two groups: image-based and rawdata-based. The image-based method is an approximative method, and beam hardening artifacts remain in the resulting material-selective images. The rawdata-based method generally obtains better image quality than the image-based method, but this method requires geometrically consistent rawdata. However, today's clinical dual energy CT scanners usually measure different rays for different energy spectra and acquire geometrically inconsistent rawdata sets, and thus cannot meet the requirement. This paper proposes a practical material decomposition method to perform rawdata-based material decomposition in the case of inconsistent measurement. This method first yields the desired consistent rawdata sets from the measured inconsistent rawdata sets, and then employs rawdata-based technique to perform material decomposition and reconstruct material-selective images. The proposed method was evaluated by use of simulated FORBILD thorax phantom rawdata and dental CT rawdata, and simulation results indicate that this method can produce highly quantitative DSCT images in the case of inconsistent DSCT measurements.

[Litter decomposition and nutrient release in Acacia mangium plantations established on degraded soils of Colombia].

PubMed

Castellanos-Barliza, Jeiner; León Peláez, Juan Diego

2011-03-01

Several factors control the decomposition in terrestrial ecosystems such as humidity, temperature, quality of litter and microbial activity. We investigated the effects of rainfall and soil plowing prior to the establishment of Acacia mangium plantations, using the litterbag technique, during a six month period, in forests plantations in Bajo Cauca region, Colombia. The annual decomposition constants (k) of simple exponential model, oscillated between 1.24 and 1.80, meanwhile k1 y k2 decomposition constants of double exponential model were 0.88-1.81 and 0.58-7.01. At the end of the study, the mean residual dry matter (RDM) was 47% of the initial value for the three sites. We found a slow N, Ca and Mg release pattern from the A. mangium leaf litter, meanwhile, phosphorus (P) showed a dominant immobilization phase, suggesting its low availability in soils. Chemical leaf litter quality parameters (e.g. N and P concentrations, C/N, N/P ratios and phenols content) showed an important influence on decomposition rates. The results of this study indicated that rainfall plays an important role on the decomposition process, but not soil plowing.

Beyond Low Rank + Sparse: Multi-scale Low Rank Matrix Decomposition

PubMed Central

Ong, Frank; Lustig, Michael

2016-01-01

We present a natural generalization of the recent low rank + sparse matrix decomposition and consider the decomposition of matrices into components of multiple scales. Such decomposition is well motivated in practice as data matrices often exhibit local correlations in multiple scales. Concretely, we propose a multi-scale low rank modeling that represents a data matrix as a sum of block-wise low rank matrices with increasing scales of block sizes. We then consider the inverse problem of decomposing the data matrix into its multi-scale low rank components and approach the problem via a convex formulation. Theoretically, we show that under various incoherence conditions, the convex program recovers the multi-scale low rank components either exactly or approximately. Practically, we provide guidance on selecting the regularization parameters and incorporate cycle spinning to reduce blocking artifacts. Experimentally, we show that the multi-scale low rank decomposition provides a more intuitive decomposition than conventional low rank methods and demonstrate its effectiveness in four applications, including illumination normalization for face images, motion separation for surveillance videos, multi-scale modeling of the dynamic contrast enhanced magnetic resonance imaging and collaborative filtering exploiting age information. PMID:28450978

Through-wall image enhancement using fuzzy and QR decomposition.

PubMed

Riaz, Muhammad Mohsin; Ghafoor, Abdul

2014-01-01

QR decomposition and fuzzy logic based scheme is proposed for through-wall image enhancement. QR decomposition is less complex compared to singular value decomposition. Fuzzy inference engine assigns weights to different overlapping subspaces. Quantitative measures and visual inspection are used to analyze existing and proposed techniques.

Adaptive Fourier decomposition based ECG denoising.

PubMed

Wang, Ze; Wan, Feng; Wong, Chi Man; Zhang, Liming

2016-10-01

A novel ECG denoising method is proposed based on the adaptive Fourier decomposition (AFD). The AFD decomposes a signal according to its energy distribution, thereby making this algorithm suitable for separating pure ECG signal and noise with overlapping frequency ranges but different energy distributions. A stop criterion for the iterative decomposition process in the AFD is calculated on the basis of the estimated signal-to-noise ratio (SNR) of the noisy signal. The proposed AFD-based method is validated by the synthetic ECG signal using an ECG model and also real ECG signals from the MIT-BIH Arrhythmia Database both with additive Gaussian white noise. Simulation results of the proposed method show better performance on the denoising and the QRS detection in comparing with major ECG denoising schemes based on the wavelet transform, the Stockwell transform, the empirical mode decomposition, and the ensemble empirical mode decomposition. Copyright © 2016 Elsevier Ltd. All rights reserved.

Solid-state reaction kinetics of neodymium doped magnesium hydrogen phosphate system

NASA Astrophysics Data System (ADS)

Gupta, Rashmi; Slathia, Goldy; Bamzai, K. K.

2018-05-01

Neodymium doped magnesium hydrogen phosphate (NdMHP) crystals were grown by using gel encapsulation technique. Structural characterization of the grown crystals has been carried out by single crystal X-ray diffraction (XRD) and it revealed that NdMHP crystals crystallize in orthorhombic crystal system with space group Pbca. Kinetics of the decomposition of the grown crystals has been studied by non-isothermal analysis. The estimation of decomposition temperatures and weight loss has been made from the thermogravimetric/differential thermo analytical (TG/DTA) in conjuncture with DSC studies. The various steps involved in the thermal decomposition of the material have been analysed using Horowitz-Metzger, Coats-Redfern and Piloyan-Novikova equations for evaluating various kinetic parameters.

Effect of composting on the thermal decomposition behavior and kinetic parameters of pig manure-derived solid waste.

PubMed

Dhyani, Vaibhav; Kumar Awasthi, Mukesh; Wang, Quan; Kumar, Jitendra; Ren, Xiuna; Zhao, Junchao; Chen, Hongyu; Wang, Meijing; Bhaskar, Thallada; Zhang, Zengqiang

2018-03-01

In this work, the influence of composting on the thermal decomposition behavior and decomposition kinetics of pig manure-derived solid wastes was analyzed using thermogravimetry. Wheat straw, biochar, zeolite, and wood vinegar were added to pig manure during composting. The composting was done in the 130 L PVC reactors with 100 L effective volume for 50 days. The activation energy of pyrolysis of samples before and after composting was calculated using Friedman's method, while the pre-exponential factor was calculated using Kissinger's equation. It was observed that composting decreased the volatile content of all the samples. The additives when added together in pig manure lead to a reduction in the activation energy of decomposition, advocating the presence of simpler compounds in the compost material in comparison with the complex feedstock. Copyright © 2017 Elsevier Ltd. All rights reserved.

Transfer of Asymmetry between Proteinogenic Amino Acids under Harsh Conditions

NASA Astrophysics Data System (ADS)

Tarasevych, Arkadii V.; Vives, Thomas; Snytnikov, Valeriy N.; Guillemin, Jean-Claude

2017-09-01

The heating above 400 °C of serine, cysteine, selenocysteine and threonine leads to a complete decomposition of the amino acids and to the formation in low yields of alanine for the three formers and of 2-aminobutyric acid for the latter. At higher temperature, this amino acid is observed only when sublimable α-alkyl-α-amino acids are present, and with an enantiomeric excess dependent on several parameters. Enantiopure or enantioenriched Ser, Cys, Sel or Thr is not able to transmit its enantiomeric excess to the amino acid formed during its decomposition. The presence during the sublimation-decomposition of enantioenriched valine or isoleucine leads to the enantioenrichment of all sublimable amino acids independently of the presence of many decomposition products coming from the unstable derivative. All these studies give information on a potentially prebiotic key-reaction of abiotic transformations between α-amino acids and their evolution to homochirality.

Neural network and wavelets in prediction of cosmic ray variability: The North Africa as study case

NASA Astrophysics Data System (ADS)

Zarrouk, Neïla; Bennaceur, Raouf

2010-04-01

Since the Earth is permanently bombarded with energetic cosmic rays particles, cosmic ray flux has been monitored by ground based neutron monitors for decades. In this work an attempt is made to investigate the decomposition and reconstructions provided by Morlet wavelet technique, using data series of cosmic rays variabilities, then to constitute from this wavelet analysis an input data base for the neural network system with which we can then predict decomposition coefficients and all related parameters for other points. Thus the latter are used for the recomposition step in which the plots and curves describing the relative cosmic rays intensities are obtained in any points on the earth in which we do not have any information about cosmic rays intensities. Although neural network associated with wavelets are not frequently used for cosmic rays time series, they seems very suitable and are a good choice to obtain these results. In fact we have succeeded to derive a very useful tool to obtain the decomposition coefficients, the main periods for each point on the Earth and on another hand we have now a kind of virtual NM for these locations like North Africa countries, Maroc, Algeria, Tunisia, Libya and Cairo. We have found the aspect of very known 11-years cycle: T1, we have also revealed the variation type of T2 and especially T3 cycles which seem to be induced by particular Earth's phenomena.

A novel fusion framework of visible light and infrared images based on singular value decomposition and adaptive DUAL-PCNN in NSST domain

NASA Astrophysics Data System (ADS)

Cheng, Boyang; Jin, Longxu; Li, Guoning

2018-06-01

Visible light and infrared images fusion has been a significant subject in imaging science. As a new contribution to this field, a novel fusion framework of visible light and infrared images based on adaptive dual-channel unit-linking pulse coupled neural networks with singular value decomposition (ADS-PCNN) in non-subsampled shearlet transform (NSST) domain is present in this paper. First, the source images are decomposed into multi-direction and multi-scale sub-images by NSST. Furthermore, an improved novel sum modified-Laplacian (INSML) of low-pass sub-image and an improved average gradient (IAVG) of high-pass sub-images are input to stimulate the ADS-PCNN, respectively. To address the large spectral difference between infrared and visible light and the occurrence of black artifacts in fused images, a local structure information operator (LSI), which comes from local area singular value decomposition in each source image, is regarded as the adaptive linking strength that enhances fusion accuracy. Compared with PCNN models in other studies, the proposed method simplifies certain peripheral parameters, and the time matrix is utilized to decide the iteration number adaptively. A series of images from diverse scenes are used for fusion experiments and the fusion results are evaluated subjectively and objectively. The results of the subjective and objective evaluation show that our algorithm exhibits superior fusion performance and is more effective than the existing typical fusion techniques.

Time Series Decomposition into Oscillation Components and Phase Estimation.

PubMed

Matsuda, Takeru; Komaki, Fumiyasu

2017-02-01

Many time series are naturally considered as a superposition of several oscillation components. For example, electroencephalogram (EEG) time series include oscillation components such as alpha, beta, and gamma. We propose a method for decomposing time series into such oscillation components using state-space models. Based on the concept of random frequency modulation, gaussian linear state-space models for oscillation components are developed. In this model, the frequency of an oscillator fluctuates by noise. Time series decomposition is accomplished by this model like the Bayesian seasonal adjustment method. Since the model parameters are estimated from data by the empirical Bayes' method, the amplitudes and the frequencies of oscillation components are determined in a data-driven manner. Also, the appropriate number of oscillation components is determined with the Akaike information criterion (AIC). In this way, the proposed method provides a natural decomposition of the given time series into oscillation components. In neuroscience, the phase of neural time series plays an important role in neural information processing. The proposed method can be used to estimate the phase of each oscillation component and has several advantages over a conventional method based on the Hilbert transform. Thus, the proposed method enables an investigation of the phase dynamics of time series. Numerical results show that the proposed method succeeds in extracting intermittent oscillations like ripples and detecting the phase reset phenomena. We apply the proposed method to real data from various fields such as astronomy, ecology, tidology, and neuroscience.

Rank-based decompositions of morphological templates.

PubMed

Sussner, P; Ritter, G X

2000-01-01

Methods for matrix decomposition have found numerous applications in image processing, in particular for the problem of template decomposition. Since existing matrix decomposition techniques are mainly concerned with the linear domain, we consider it timely to investigate matrix decomposition techniques in the nonlinear domain with applications in image processing. The mathematical basis for these investigations is the new theory of rank within minimax algebra. Thus far, only minimax decompositions of rank 1 and rank 2 matrices into outer product expansions are known to the image processing community. We derive a heuristic algorithm for the decomposition of matrices having arbitrary rank.

Determination of seasonals using wavelets in terms of noise parameters changeability

NASA Astrophysics Data System (ADS)

Klos, Anna; Bogusz, Janusz; Figurski, Mariusz

2015-04-01

The reliable velocities of GNSS-derived observations are becoming of high importance nowadays. The fact on how we determine and subtract the seasonals may all cause the time series autocorrelation and affect uncertainties of linear parameters. The periodic changes in GNSS time series are commonly assumed as the sum of annual and semi-annual changes with amplitudes and phases being constant in time and the Least-Squares Estimation (LSE) is used in general to model these sine waves. However, not only seasonals' time-changeability, but also their higher harmonics should be considered. In this research, we focused on more than 230 globally distributed IGS stations that were processed at the Military University of Technology EPN Local Analysis Centre (MUT LAC) in Bernese 5.0 software. The network was divided into 7 different sub-networks with few of overlapping stations and processed separately with newest models. Here, we propose a wavelet-based trend and seasonals determination and removal of whole frequency spectrum between Chandler and quarter-annual periods from North, East and Up components and compare it with LSE-determined values. We used a Meyer symmetric, orthogonal wavelet and assumed nine levels of decomposition. The details from 6 up to 9 were analyzed here as periodic components with frequencies between 0.3-2.5 cpy. The characteristic oscillations for each of frequency band were pointed out. The details lower than 6 summed together with detrended approximation were considered as residua. The power spectral densities (PSDs) of original and decomposed data were stacked for North, East and Up components for each of sub-networks so as to show what power was removed with each of decomposition levels. Moreover, the noises that the certain frequency band follows (in terms of spectral indices of power-law dependencies) were estimated here using a spectral method and compared for all processed sub-networks. It seems, that lowest frequencies up to 0.7 cpy are characterized by lower spectral indices in comparison to higher ones being close to white noise. Basing on the fact, that decomposition levels overlap each other, the frequency-window choice becomes a main point in spectral index estimation. Our results were compared with those obtained by Maximum Likelihood Estimation (MLE) and possible differences as well as their impact on velocity uncertainties pointed out. The results show that the spectral indices estimated in time and frequency domains differ of 0.15 in maximum. Moreover, we compared the removed power basing on wavelet decomposition levels with the one subtracted with LSE, assuming the same periodicities. In comparison to LSE, the wavelet-based approach leaves the residua being closer to white noise with lower power-law amplitudes of them, what strictly reduces velocity uncertainties. The last approximation was analyzed here as long-term trend, being the non-linear and compared with LSE-determined linear one. It seems that these two trends differ at the level of 0.3 mm/yr in the most extreme case, what makes wavelet decomposition being useful for velocity determination.

Computer simulations of alkali-acetate solutions: Accuracy of the forcefields in difference concentrations

NASA Astrophysics Data System (ADS)

Ahlstrand, Emma; Zukerman Schpector, Julio; Friedman, Ran

2017-11-01

When proteins are solvated in electrolyte solutions that contain alkali ions, the ions interact mostly with carboxylates on the protein surface. Correctly accounting for alkali-carboxylate interactions is thus important for realistic simulations of proteins. Acetates are the simplest carboxylates that are amphipathic, and experimental data for alkali acetate solutions are available and can be compared with observables obtained from simulations. We carried out molecular dynamics simulations of alkali acetate solutions using polarizable and non-polarizable forcefields and examined the ion-acetate interactions. In particular, activity coefficients and association constants were studied in a range of concentrations (0.03, 0.1, and 1M). In addition, quantum-mechanics (QM) based energy decomposition analysis was performed in order to estimate the contribution of polarization, electrostatics, dispersion, and QM (non-classical) effects on the cation-acetate and cation-water interactions. Simulations of Li-acetate solutions in general overestimated the binding of Li+ and acetates. In lower concentrations, the activity coefficients of alkali-acetate solutions were too high, which is suggested to be due to the simulation protocol and not the forcefields. Energy decomposition analysis suggested that improvement of the forcefield parameters to enable accurate simulations of Li-acetate solutions can be achieved but may require the use of a polarizable forcefield. Importantly, simulations with some ion parameters could not reproduce the correct ion-oxygen distances, which calls for caution in the choice of ion parameters when protein simulations are performed in electrolyte solutions.

The origin of soil organic matter dictates its composition and bioreactivity across a mesic boreal forest latitudinal gradient

NASA Astrophysics Data System (ADS)

Kohl, Lukas; Philben, Michael; Edwards, Kate A.; Podrebarac, Frances A.; Warren, Jamie; Ziegler, Susan E.

2017-04-01

Climate transect studies and soil warming experiments have shown that soil organic matter (SOM) formed under a warmer climate is typically more resistant to microbial decomposition, as indicated by lower decomposition rates at a given temperature (bioreactivity). However, it remains unclear how climate impacts SOM via its effect on vegetation and thus litter inputs to soils, or on decomposition and thus how SOM changes over time (diagenesis). We addressed this question by studying how the chemical and biological properties of SOM vary with decomposition (depth) and climate history (latitude) in mesic boreal forests of Atlantic Canada. SOM bioreactivity, measured in a 15-months decomposition experiment, decreased from cold to warm regions, and from the topmost (L) to the deepest horizon studied (H). The variations in SOM bioreactivity with climate history and depth, however, were associated with distinct parameters of SOM chemistry. More decomposed SOM with depth was associated with lower proportions of %N as total hydrolysable amino acids (THAA), and a different THAA-based degradation index signifying a more degraded state. However, SOM from the warmer region exhibited higher lignin to carbohydrate ratios, as detected by NMR. None of the measured parameters associated with regional differences in SOM chemistry increased with depth. Together, these results indicate that the regional differences in SOM chemistry and bioreactivity in these soils did not result from significant differences in the degree of degradation, but rather resulted from chemically distinct litter inputs. The comparison of SOM and plant litter chemistry allowed us to identify how climate affects litter inputs in these forests. Vascular plant litter collected in litter traps, unlike SOM, exhibited largely similar chemical composition across all transect regions. Litter traps, however, do not collect moss litter, which is chemically distinct from vascular plant litter. We, therefore, assessed the proportions of identifiable moss to vascular plant material in the L horizon, and found that the proportion of moss litter decreases from north to south consistent with moss cover estimates across this transect. Furthermore, SOM was more similar to vascular plant litter in more southern sites, while properties of moss litter (high carbohydrate, low lignin and plant wax concentrations) were associated with the more bioreactive SOM found in the northern sites. Despite the slow rates of moss litter decomposition relative to vascular plant litter observed in many studies, these results suggest that moss derived SOM is decomposed more rapidly than vascular plant derived SOM. This is consistent with (1) initially rapid decomposition of vascular plant litter contributing to more slow turnover SOM, and (2) the role of antimicrobial compounds in reducing surface moss litter decomposition which may be reduced at depth due to their removal or inactivation over time. The decrease of SOM bioreactivity due to lower proportions of moss inputs in the warmer forests studied here signifies an important and understudied ecosystem mechanism that can control the cycling of C in these, and likely other boreal forest soils in a warmer future.

Jammed Limit of Bijel Structure Formation

DOE PAGES

Welch, P. M.; Lee, M. N.; Parra-Vasquez, A. N. G.; ...

2017-11-02

Over the past decade, methods to control microstructure in heterogeneous mixtures by arresting spinodal decomposition via the addition of colloidal particles have led to an entirely new class of bicontinuous materials known as bijels. We present a new model for the development of these materials that yields to both numerical and analytical evaluation. This model reveals that a single dimensionless parameter that captures both chemical and environmental variables dictates the dynamics and ultimate structure formed in bijels. We also demonstrate that this parameter must fall within a fixed range in order for jamming to occur during spinodal decomposition, as wellmore » as show that known experimental trends for the characteristic domain sizes and time scales for formation are recovered by this model.« less

Reduced-order model for underwater target identification using proper orthogonal decomposition

NASA Astrophysics Data System (ADS)

Ramesh, Sai Sudha; Lim, Kian Meng

2017-03-01

Research on underwater acoustics has seen major development over the past decade due to its widespread applications in domains such as underwater communication/navigation (SONAR), seismic exploration and oceanography. In particular, acoustic signatures from partially or fully buried targets can be used in the identification of buried mines for mine counter measures (MCM). Although there exist several techniques to identify target properties based on SONAR images and acoustic signatures, these methods first employ a feature extraction method to represent the dominant characteristics of a data set, followed by the use of an appropriate classifier based on neural networks or the relevance vector machine. The aim of the present study is to demonstrate the applications of proper orthogonal decomposition (POD) technique in capturing dominant features of a set of scattered pressure signals, and subsequent use of the POD modes and coefficients in the identification of partially buried underwater target parameters such as its location, size and material density. Several numerical examples are presented to demonstrate the performance of the system identification method based on POD. Although the present study is based on 2D acoustic model, the method can be easily extended to 3D models and thereby enables cost-effective representations of large-scale data.

Climate fails to predict wood decomposition at regional scales

NASA Astrophysics Data System (ADS)

Bradford, Mark A.; Warren, Robert J., II; Baldrian, Petr; Crowther, Thomas W.; Maynard, Daniel S.; Oldfield, Emily E.; Wieder, William R.; Wood, Stephen A.; King, Joshua R.

2014-07-01

Decomposition of organic matter strongly influences ecosystem carbon storage. In Earth-system models, climate is a predominant control on the decomposition rates of organic matter. This assumption is based on the mean response of decomposition to climate, yet there is a growing appreciation in other areas of global change science that projections based on mean responses can be irrelevant and misleading. We test whether climate controls on the decomposition rate of dead wood--a carbon stock estimated to represent 73 +/- 6 Pg carbon globally--are sensitive to the spatial scale from which they are inferred. We show that the common assumption that climate is a predominant control on decomposition is supported only when local-scale variation is aggregated into mean values. Disaggregated data instead reveal that local-scale factors explain 73% of the variation in wood decomposition, and climate only 28%. Further, the temperature sensitivity of decomposition estimated from local versus mean analyses is 1.3-times greater. Fundamental issues with mean correlations were highlighted decades ago, yet mean climate-decomposition relationships are used to generate simulations that inform management and adaptation under environmental change. Our results suggest that to predict accurately how decomposition will respond to climate change, models must account for local-scale factors that control regional dynamics.

Coal fly ash and lime addition enhances the rate and efficiency of decomposition of food waste during composting.

PubMed

Wong, Jonathan W-C; Fung, Shun On; Selvam, Ammaiyappan

2009-07-01

To evaluate the use of coal fly ash (CFA) on the decomposition efficiency of food waste, synthetic food waste was mixed with lime at 1.5% and 3% (equivalent to 0.94% and 1.88% CaCO(3), respectively), CFA at 5%, 10% and 15% with lime so as to achieve CaCO(3) equivalent of 1.88% and composted for 42 days in a thermophilic 20 l composter with two replicates each. Alkaline materials at 1.88% CaCO(3) equivalent successfully buffered the pH during the composting and enhanced the decomposition efficiency. When these buffering was achieved with CFA+lime, the composting period could be shortened to approximately 28 days compared with approximately 42 days in 3% lime. Organic decomposition in terms of CO(2) loss, carbon turnover and nitrogen transformation were significantly higher for treatments with 1.88% CaCO(3) equivalent. Nutrient transformations and compost maturity parameters indicated that addition of CFA (5-10%) with lime at 1.88% CaCO(3) equivalent enhances the decomposition efficiency and shortens the composting period by 35%.

Fast heap transform-based QR-decomposition of real and complex matrices: algorithms and codes

NASA Astrophysics Data System (ADS)

Grigoryan, Artyom M.

2015-03-01

In this paper, we describe a new look on the application of Givens rotations to the QR-decomposition problem, which is similar to the method of Householder transformations. We apply the concept of the discrete heap transform, or signal-induced unitary transforms which had been introduced by Grigoryan (2006) and used in signal and image processing. Both cases of real and complex nonsingular matrices are considered and examples of performing QR-decomposition of square matrices are given. The proposed method of QR-decomposition for the complex matrix is novel and differs from the known method of complex Givens rotation and is based on analytical equations for the heap transforms. Many examples illustrated the proposed heap transform method of QR-decomposition are given, algorithms are described in detail, and MATLAB-based codes are included.

Capturing molecular multimode relaxation processes in excitable gases based on decomposition of acoustic relaxation spectra

NASA Astrophysics Data System (ADS)

Zhu, Ming; Liu, Tingting; Wang, Shu; Zhang, Kesheng

2017-08-01

Existing two-frequency reconstructive methods can only capture primary (single) molecular relaxation processes in excitable gases. In this paper, we present a reconstructive method based on the novel decomposition of frequency-dependent acoustic relaxation spectra to capture the entire molecular multimode relaxation process. This decomposition of acoustic relaxation spectra is developed from the frequency-dependent effective specific heat, indicating that a multi-relaxation process is the sum of the interior single-relaxation processes. Based on this decomposition, we can reconstruct the entire multi-relaxation process by capturing the relaxation times and relaxation strengths of N interior single-relaxation processes, using the measurements of acoustic absorption and sound speed at 2N frequencies. Experimental data for the gas mixtures CO2-N2 and CO2-O2 validate our decomposition and reconstruction approach.

Effects of sterilization treatments on the analysis of TOC in water samples.

PubMed

Shi, Yiming; Xu, Lingfeng; Gong, Dongqin; Lu, Jun

2010-01-01

Decomposition experiments conducted with and without microbial processes are commonly used to study the effects of environmental microorganisms on the degradation of organic pollutants. However, the effects of biological pretreatment (sterilization) on organic matter often have a negative impact on such experiments. Based on the principle of water total organic carbon (TOC) analysis, the effects of physical sterilization treatments on determination of TOC and other water quality parameters were investigated. The results revealed that two conventional physical sterilization treatments, autoclaving and 60Co gamma-radiation sterilization, led to the direct decomposition of some organic pollutants, resulting in remarkable errors in the analysis of TOC in water samples. Furthermore, the extent of the errors varied with the intensity and the duration of sterilization treatments. Accordingly, a novel sterilization method for water samples, 0.45 microm micro-filtration coupled with ultraviolet radiation (MCUR), was developed in the present study. The results indicated that the MCUR method was capable of exerting a high bactericidal effect on the water sample while significantly decreasing the negative impact on the analysis of TOC and other water quality parameters. Before and after sterilization treatments, the relative errors of TOC determination could be controlled to lower than 3% for water samples with different categories and concentrations of organic pollutants by using MCUR.

System identification of timber masonry walls using shaking table test

NASA Astrophysics Data System (ADS)

Roy, Timir B.; Guerreiro, Luis; Bagchi, Ashutosh

2017-04-01

Dynamic study is important in order to design, repair and rehabilitation of structures. It has played an important role in the behavior characterization of structures; such as: bridges, dams, high rise buildings etc. There had been substantial development in this area over the last few decades, especially in the field of dynamic identification techniques of structural systems. Frequency Domain Decomposition (FDD) and Time Domain Decomposition are most commonly used methods to identify modal parameters; such as: natural frequency, modal damping and mode shape. The focus of the present research is to study the dynamic characteristics of typical timber masonry walls commonly used in Portugal. For that purpose, a multi-storey structural prototype of such wall has been tested on a seismic shake table at the National Laboratory for Civil Engineering, Portugal (LNEC). Signal processing has been performed of the output response, which is collected from the shaking table experiment of the prototype using accelerometers. In the present work signal processing of the output response, based on the input response has been done in two ways: FDD and Stochastic Subspace Identification (SSI). In order to estimate the values of the modal parameters, algorithms for FDD are formulated and parametric functions for the SSI are computed. Finally, estimated values from both the methods are compared to measure the accuracy of both the techniques.

Semi-empirical modelling for forest above ground biomass estimation using hybrid and fully PolSAR data

NASA Astrophysics Data System (ADS)

Tomar, Kiledar S.; Kumar, Shashi; Tolpekin, Valentyn A.; Joshi, Sushil K.

2016-05-01

Forests act as sink of carbon and as a result maintains carbon cycle in atmosphere. Deforestation leads to imbalance in global carbon cycle and changes in climate. Hence estimation of forest biophysical parameter like biomass becomes a necessity. PolSAR has the ability to discriminate the share of scattering element like surface, double bounce and volume scattering in a single SAR resolution cell. Studies have shown that volume scattering is a significant parameter for forest biophysical characterization which mainly occurred from vegetation due to randomly oriented structures. This random orientation of forest structure causes shift in orientation angle of polarization ellipse which ultimately disturbs the radar signature and shows overestimation of volume scattering and underestimation of double bounce scattering after decomposition of fully PolSAR data. Hybrid polarimetry has the advantage of zero POA shift due to rotational symmetry followed by the circular transmission of electromagnetic waves. The prime objective of this study was to extract the potential of Hybrid PolSAR and fully PolSAR data for AGB estimation using Extended Water Cloud model. Validation was performed using field biomass. The study site chosen was Barkot Forest, Uttarakhand, India. To obtain the decomposition components, m-alpha and Yamaguchi decomposition modelling for Hybrid and fully PolSAR data were implied respectively. The RGB composite image for both the decomposition techniques has generated. The contribution of all scattering from each plot for m-alpha and Yamaguchi decomposition modelling were extracted. The R2 value for modelled AGB and field biomass from Hybrid PolSAR and fully PolSAR data were found 0.5127 and 0.4625 respectively. The RMSE for Hybrid and fully PolSAR between modelled AGB and field biomass were 63.156 (t ha-1) and 73.424 (t ha-1) respectively. On the basis of RMSE and R2 value, this study suggests Hybrid PolSAR decomposition modelling to retrieve scattering element for AGB estimation from forest.

Extracting fingerprint of wireless devices based on phase noise and multiple level wavelet decomposition

NASA Astrophysics Data System (ADS)

Zhao, Weichen; Sun, Zhuo; Kong, Song

2016-10-01

Wireless devices can be identified by the fingerprint extracted from the signal transmitted, which is useful in wireless communication security and other fields. This paper presents a method that extracts fingerprint based on phase noise of signal and multiple level wavelet decomposition. The phase of signal will be extracted first and then decomposed by multiple level wavelet decomposition. The statistic value of each wavelet coefficient vector is utilized for constructing fingerprint. Besides, the relationship between wavelet decomposition level and recognition accuracy is simulated. And advertised decomposition level is revealed as well. Compared with previous methods, our method is simpler and the accuracy of recognition remains high when Signal Noise Ratio (SNR) is low.

Numerically accurate computational techniques for optimal estimator analyses of multi-parameter models

NASA Astrophysics Data System (ADS)

Berger, Lukas; Kleinheinz, Konstantin; Attili, Antonio; Bisetti, Fabrizio; Pitsch, Heinz; Mueller, Michael E.

2018-05-01

Modelling unclosed terms in partial differential equations typically involves two steps: First, a set of known quantities needs to be specified as input parameters for a model, and second, a specific functional form needs to be defined to model the unclosed terms by the input parameters. Both steps involve a certain modelling error, with the former known as the irreducible error and the latter referred to as the functional error. Typically, only the total modelling error, which is the sum of functional and irreducible error, is assessed, but the concept of the optimal estimator enables the separate analysis of the total and the irreducible errors, yielding a systematic modelling error decomposition. In this work, attention is paid to the techniques themselves required for the practical computation of irreducible errors. Typically, histograms are used for optimal estimator analyses, but this technique is found to add a non-negligible spurious contribution to the irreducible error if models with multiple input parameters are assessed. Thus, the error decomposition of an optimal estimator analysis becomes inaccurate, and misleading conclusions concerning modelling errors may be drawn. In this work, numerically accurate techniques for optimal estimator analyses are identified and a suitable evaluation of irreducible errors is presented. Four different computational techniques are considered: a histogram technique, artificial neural networks, multivariate adaptive regression splines, and an additive model based on a kernel method. For multiple input parameter models, only artificial neural networks and multivariate adaptive regression splines are found to yield satisfactorily accurate results. Beyond a certain number of input parameters, the assessment of models in an optimal estimator analysis even becomes practically infeasible if histograms are used. The optimal estimator analysis in this paper is applied to modelling the filtered soot intermittency in large eddy simulations using a dataset of a direct numerical simulation of a non-premixed sooting turbulent flame.

Use of Bayes theorem to correct size-specific sampling bias in growth data.

PubMed

Troynikov, V S

1999-03-01

The bayesian decomposition of posterior distribution was used to develop a likelihood function to correct bias in the estimates of population parameters from data collected randomly with size-specific selectivity. Positive distributions with time as a parameter were used for parametrization of growth data. Numerical illustrations are provided. The alternative applications of the likelihood to estimate selectivity parameters are discussed.

An efficient variable projection formulation for separable nonlinear least squares problems.

PubMed

Gan, Min; Li, Han-Xiong

2014-05-01

We consider in this paper a class of nonlinear least squares problems in which the model can be represented as a linear combination of nonlinear functions. The variable projection algorithm projects the linear parameters out of the problem, leaving the nonlinear least squares problems involving only the nonlinear parameters. To implement the variable projection algorithm more efficiently, we propose a new variable projection functional based on matrix decomposition. The advantage of the proposed formulation is that the size of the decomposed matrix may be much smaller than those of previous ones. The Levenberg-Marquardt algorithm using finite difference method is then applied to minimize the new criterion. Numerical results show that the proposed approach achieves significant reduction in computing time.

Ozone decomposition

PubMed Central

Batakliev, Todor; Georgiev, Vladimir; Anachkov, Metody; Rakovsky, Slavcho

2014-01-01

Catalytic ozone decomposition is of great significance because ozone is a toxic substance commonly found or generated in human environments (aircraft cabins, offices with photocopiers, laser printers, sterilizers). Considerable work has been done on ozone decomposition reported in the literature. This review provides a comprehensive summary of the literature, concentrating on analysis of the physico-chemical properties, synthesis and catalytic decomposition of ozone. This is supplemented by a review on kinetics and catalyst characterization which ties together the previously reported results. Noble metals and oxides of transition metals have been found to be the most active substances for ozone decomposition. The high price of precious metals stimulated the use of metal oxide catalysts and particularly the catalysts based on manganese oxide. It has been determined that the kinetics of ozone decomposition is of first order importance. A mechanism of the reaction of catalytic ozone decomposition is discussed, based on detailed spectroscopic investigations of the catalytic surface, showing the existence of peroxide and superoxide surface intermediates. PMID:26109880

High-order tracking differentiator based adaptive neural control of a flexible air-breathing hypersonic vehicle subject to actuators constraints.

PubMed

Bu, Xiangwei; Wu, Xiaoyan; Tian, Mingyan; Huang, Jiaqi; Zhang, Rui; Ma, Zhen

2015-09-01

In this paper, an adaptive neural controller is exploited for a constrained flexible air-breathing hypersonic vehicle (FAHV) based on high-order tracking differentiator (HTD). By utilizing functional decomposition methodology, the dynamic model is reasonably decomposed into the respective velocity subsystem and altitude subsystem. For the velocity subsystem, a dynamic inversion based neural controller is constructed. By introducing the HTD to adaptively estimate the newly defined states generated in the process of model transformation, a novel neural based altitude controller that is quite simpler than the ones derived from back-stepping is addressed based on the normal output-feedback form instead of the strict-feedback formulation. Based on minimal-learning parameter scheme, only two neural networks with two adaptive parameters are needed for neural approximation. Especially, a novel auxiliary system is explored to deal with the problem of control inputs constraints. Finally, simulation results are presented to test the effectiveness of the proposed control strategy in the presence of system uncertainties and actuators constraints. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Application of Petri net based analysis techniques to signal transduction pathways.

PubMed

Sackmann, Andrea; Heiner, Monika; Koch, Ina

2006-11-02

Signal transduction pathways are usually modelled using classical quantitative methods, which are based on ordinary differential equations (ODEs). However, some difficulties are inherent in this approach. On the one hand, the kinetic parameters involved are often unknown and have to be estimated. With increasing size and complexity of signal transduction pathways, the estimation of missing kinetic data is not possible. On the other hand, ODEs based models do not support any explicit insights into possible (signal-) flows within the network. Moreover, a huge amount of qualitative data is available due to high-throughput techniques. In order to get information on the systems behaviour, qualitative analysis techniques have been developed. Applications of the known qualitative analysis methods concern mainly metabolic networks. Petri net theory provides a variety of established analysis techniques, which are also applicable to signal transduction models. In this context special properties have to be considered and new dedicated techniques have to be designed. We apply Petri net theory to model and analyse signal transduction pathways first qualitatively before continuing with quantitative analyses. This paper demonstrates how to build systematically a discrete model, which reflects provably the qualitative biological behaviour without any knowledge of kinetic parameters. The mating pheromone response pathway in Saccharomyces cerevisiae serves as case study. We propose an approach for model validation of signal transduction pathways based on the network structure only. For this purpose, we introduce the new notion of feasible t-invariants, which represent minimal self-contained subnets being active under a given input situation. Each of these subnets stands for a signal flow in the system. We define maximal common transition sets (MCT-sets), which can be used for t-invariant examination and net decomposition into smallest biologically meaningful functional units. The paper demonstrates how Petri net analysis techniques can promote a deeper understanding of signal transduction pathways. The new concepts of feasible t-invariants and MCT-sets have been proven to be useful for model validation and the interpretation of the biological system behaviour. Whereas MCT-sets provide a decomposition of the net into disjunctive subnets, feasible t-invariants describe subnets, which generally overlap. This work contributes to qualitative modelling and to the analysis of large biological networks by their fully automatic decomposition into biologically meaningful modules.

Application of Petri net based analysis techniques to signal transduction pathways

PubMed Central

Sackmann, Andrea; Heiner, Monika; Koch, Ina

2006-01-01

Background Signal transduction pathways are usually modelled using classical quantitative methods, which are based on ordinary differential equations (ODEs). However, some difficulties are inherent in this approach. On the one hand, the kinetic parameters involved are often unknown and have to be estimated. With increasing size and complexity of signal transduction pathways, the estimation of missing kinetic data is not possible. On the other hand, ODEs based models do not support any explicit insights into possible (signal-) flows within the network. Moreover, a huge amount of qualitative data is available due to high-throughput techniques. In order to get information on the systems behaviour, qualitative analysis techniques have been developed. Applications of the known qualitative analysis methods concern mainly metabolic networks. Petri net theory provides a variety of established analysis techniques, which are also applicable to signal transduction models. In this context special properties have to be considered and new dedicated techniques have to be designed. Methods We apply Petri net theory to model and analyse signal transduction pathways first qualitatively before continuing with quantitative analyses. This paper demonstrates how to build systematically a discrete model, which reflects provably the qualitative biological behaviour without any knowledge of kinetic parameters. The mating pheromone response pathway in Saccharomyces cerevisiae serves as case study. Results We propose an approach for model validation of signal transduction pathways based on the network structure only. For this purpose, we introduce the new notion of feasible t-invariants, which represent minimal self-contained subnets being active under a given input situation. Each of these subnets stands for a signal flow in the system. We define maximal common transition sets (MCT-sets), which can be used for t-invariant examination and net decomposition into smallest biologically meaningful functional units. Conclusion The paper demonstrates how Petri net analysis techniques can promote a deeper understanding of signal transduction pathways. The new concepts of feasible t-invariants and MCT-sets have been proven to be useful for model validation and the interpretation of the biological system behaviour. Whereas MCT-sets provide a decomposition of the net into disjunctive subnets, feasible t-invariants describe subnets, which generally overlap. This work contributes to qualitative modelling and to the analysis of large biological networks by their fully automatic decomposition into biologically meaningful modules. PMID:17081284

Low rank approximation methods for MR fingerprinting with large scale dictionaries.

PubMed

Yang, Mingrui; Ma, Dan; Jiang, Yun; Hamilton, Jesse; Seiberlich, Nicole; Griswold, Mark A; McGivney, Debra

2018-04-01

This work proposes new low rank approximation approaches with significant memory savings for large scale MR fingerprinting (MRF) problems. We introduce a compressed MRF with randomized singular value decomposition method to significantly reduce the memory requirement for calculating a low rank approximation of large sized MRF dictionaries. We further relax this requirement by exploiting the structures of MRF dictionaries in the randomized singular value decomposition space and fitting them to low-degree polynomials to generate high resolution MRF parameter maps. In vivo 1.5T and 3T brain scan data are used to validate the approaches. T 1 , T 2 , and off-resonance maps are in good agreement with that of the standard MRF approach. Moreover, the memory savings is up to 1000 times for the MRF-fast imaging with steady-state precession sequence and more than 15 times for the MRF-balanced, steady-state free precession sequence. The proposed compressed MRF with randomized singular value decomposition and dictionary fitting methods are memory efficient low rank approximation methods, which can benefit the usage of MRF in clinical settings. They also have great potentials in large scale MRF problems, such as problems considering multi-component MRF parameters or high resolution in the parameter space. Magn Reson Med 79:2392-2400, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Ab initio kinetics of gas phase decomposition reactions.

PubMed

Sharia, Onise; Kuklja, Maija M

2010-12-09

The thermal and kinetic aspects of gas phase decomposition reactions can be extremely complex due to a large number of parameters, a variety of possible intermediates, and an overlap in thermal decomposition traces. The experimental determination of the activation energies is particularly difficult when several possible reaction pathways coexist in the thermal decomposition. Ab initio calculations intended to provide an interpretation of the experiment are often of little help if they produce only the activation barriers and ignore the kinetics of the decomposition process. To overcome this ambiguity, a theoretical study of a complete picture of gas phase thermo-decomposition, including reaction energies, activation barriers, and reaction rates, is illustrated with the example of the β-octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX) molecule by means of quantum-chemical calculations. We study three types of major decomposition reactions characteristic of nitramines: the HONO elimination, the NONO rearrangement, and the N-NO(2) homolysis. The reaction rates were determined using the conventional transition state theory for the HONO and NONO decompositions and the variational transition state theory for the N-NO(2) homolysis. Our calculations show that the HMX decomposition process is more complex than it was previously believed to be and is defined by a combination of reactions at any given temperature. At all temperatures, the direct N-NO(2) homolysis prevails with the activation barrier at 38.1 kcal/mol. The nitro-nitrite isomerization and the HONO elimination, with the activation barriers at 46.3 and 39.4 kcal/mol, respectively, are slow reactions at all temperatures. The obtained conclusions provide a consistent interpretation for the reported experimental data.

Polarimetric Decomposition Analysis of the Deepwater Horizon Oil Slick Using L-Band UAVSAR Data

NASA Technical Reports Server (NTRS)

Jones, Cathleen; Minchew, Brent; Holt, Benjamin

2011-01-01

We report here an analysis of the polarization dependence of L-band radar backscatter from the main slick of the Deepwater Horizon oil spill, with specific attention to the utility of polarimetric decomposition analysis for discrimination of oil from clean water and identification of variations in the oil characteristics. For this study we used data collected with the UAVSAR instrument from opposing look directions directly over the main oil slick. We find that both the Cloude-Pottier and Shannon entropy polarimetric decomposition methods offer promise for oil discrimination, with the Shannon entropy method yielding the same information as contained in the Cloude-Pottier entropy and averaged in tensity parameters, but with significantly less computational complexity

The persistence of human DNA in soil following surface decomposition.

PubMed

Emmons, Alexandra L; DeBruyn, Jennifer M; Mundorff, Amy Z; Cobaugh, Kelly L; Cabana, Graciela S

2017-09-01

Though recent decades have seen a marked increase in research concerning the impact of human decomposition on the grave soil environment, the fate of human DNA in grave soil has been relatively understudied. With the purpose of supplementing the growing body of literature in forensic soil taphonomy, this study assessed the relative persistence of human DNA in soil over the course of decomposition. Endpoint PCR was used to assess the presence or absence of human nuclear and mitochondrial DNA, while qPCR was used to evaluate the quantity of human DNA recovered from the soil beneath four cadavers at the University of Tennessee's Anthropology Research Facility (ARF). Human nuclear DNA from the soil was largely unrecoverable, while human mitochondrial DNA was detectable in the soil throughout all decomposition stages. Mitochondrial DNA copy abundances were not significantly different between decomposition stages and were not significantly correlated to soil edaphic parameters tested. There was, however, a significant positive correlation between mitochondrial DNA copy abundances and the human associated bacteria, Bacteroides, as estimated by 16S rRNA gene abundances. These results show that human mitochondrial DNA can persist in grave soil and be consistently detected throughout decomposition. Copyright © 2017 The Chartered Society of Forensic Sciences. Published by Elsevier B.V. All rights reserved.

Modelling the influence of ectomycorrhizal decomposition on plant nutrition and soil carbon sequestration in boreal forest ecosystems.

PubMed

Baskaran, Preetisri; Hyvönen, Riitta; Berglund, S Linnea; Clemmensen, Karina E; Ågren, Göran I; Lindahl, Björn D; Manzoni, Stefano

2017-02-01

Tree growth in boreal forests is limited by nitrogen (N) availability. Most boreal forest trees form symbiotic associations with ectomycorrhizal (ECM) fungi, which improve the uptake of inorganic N and also have the capacity to decompose soil organic matter (SOM) and to mobilize organic N ('ECM decomposition'). To study the effects of 'ECM decomposition' on ecosystem carbon (C) and N balances, we performed a sensitivity analysis on a model of C and N flows between plants, SOM, saprotrophs, ECM fungi, and inorganic N stores. The analysis indicates that C and N balances were sensitive to model parameters regulating ECM biomass and decomposition. Under low N availability, the optimal C allocation to ECM fungi, above which the symbiosis switches from mutualism to parasitism, increases with increasing relative involvement of ECM fungi in SOM decomposition. Under low N conditions, increased ECM organic N mining promotes tree growth but decreases soil C storage, leading to a negative correlation between C stores above- and below-ground. The interplay between plant production and soil C storage is sensitive to the partitioning of decomposition between ECM fungi and saprotrophs. Better understanding of interactions between functional guilds of soil fungi may significantly improve predictions of ecosystem responses to environmental change. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Crop residue decomposition in Minnesota biochar amended plots

NASA Astrophysics Data System (ADS)

Weyers, S. L.; Spokas, K. A.

2014-02-01

Impacts of biochar application at laboratory scales are routinely studied, but impacts of biochar application on decomposition of crop residues at field scales have not been widely addressed. The priming or hindrance of crop residue decomposition could have a cascading impact on soil processes, particularly those influencing nutrient availability. Our objectives were to evaluate biochar effects on field decomposition of crop residue, using plots that were amended with biochars made from different feedstocks and pyrolysis platforms prior to the start of this study. Litterbags containing wheat straw material were buried below the soil surface in a continuous-corn cropped field in plots that had received one of seven different biochar amendments or a non-charred wood pellet amendment 2.5 yr prior to start of this study. Litterbags were collected over the course of 14 weeks. Microbial biomass was assessed in treatment plots the previous fall. Though first-order decomposition rate constants were positively correlated to microbial biomass, neither parameter was statistically affected by biochar or wood-pellet treatments. The findings indicated only a residual of potentially positive and negative initial impacts of biochars on residue decomposition, which fit in line with established feedstock and pyrolysis influences. Though no significant impacts were observed with field-weathered biochars, effective soil management may yet have to account for repeat applications of biochar.

The design and implementation of signal decomposition system of CL multi-wavelet transform based on DSP builder

NASA Astrophysics Data System (ADS)

Huang, Yan; Wang, Zhihui

2015-12-01

With the development of FPGA, DSP Builder is widely applied to design system-level algorithms. The algorithm of CL multi-wavelet is more advanced and effective than scalar wavelets in processing signal decomposition. Thus, a system of CL multi-wavelet based on DSP Builder is designed for the first time in this paper. The system mainly contains three parts: a pre-filtering subsystem, a one-level decomposition subsystem and a two-level decomposition subsystem. It can be converted into hardware language VHDL by the Signal Complier block that can be used in Quartus II. After analyzing the energy indicator, it shows that this system outperforms Daubenchies wavelet in signal decomposition. Furthermore, it has proved to be suitable for the implementation of signal fusion based on SoPC hardware, and it will become a solid foundation in this new field.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brezov, D. S.; Mladenova, C. D.; Mladenov, I. M., E-mail: mladenov@bio21.bas.bg

In this paper we obtain the Lie derivatives of the scalar parameters in the generalized Euler decomposition with respect to arbitrary axes under left and right deck transformations. This problem can be directly related to the representation of the angular momentum in quantum mechanics. As a particular example, we calculate the angular momentum and the corresponding quantum hamiltonian in the standard Euler and Bryan representations. Similarly, in the hyperbolic case, the Laplace-Beltrami operator is retrieved for the Iwasawa decomposition. The case of two axes is considered as well.

Modified truncated randomized singular value decomposition (MTRSVD) algorithms for large scale discrete ill-posed problems with general-form regularization

NASA Astrophysics Data System (ADS)

Jia, Zhongxiao; Yang, Yanfei

2018-05-01

In this paper, we propose new randomization based algorithms for large scale linear discrete ill-posed problems with general-form regularization: subject to , where L is a regularization matrix. Our algorithms are inspired by the modified truncated singular value decomposition (MTSVD) method, which suits only for small to medium scale problems, and randomized SVD (RSVD) algorithms that generate good low rank approximations to A. We use rank-k truncated randomized SVD (TRSVD) approximations to A by truncating the rank- RSVD approximations to A, where q is an oversampling parameter. The resulting algorithms are called modified TRSVD (MTRSVD) methods. At every step, we use the LSQR algorithm to solve the resulting inner least squares problem, which is proved to become better conditioned as k increases so that LSQR converges faster. We present sharp bounds for the approximation accuracy of the RSVDs and TRSVDs for severely, moderately and mildly ill-posed problems, and substantially improve a known basic bound for TRSVD approximations. We prove how to choose the stopping tolerance for LSQR in order to guarantee that the computed and exact best regularized solutions have the same accuracy. Numerical experiments illustrate that the best regularized solutions by MTRSVD are as accurate as the ones by the truncated generalized singular value decomposition (TGSVD) algorithm, and at least as accurate as those by some existing truncated randomized generalized singular value decomposition (TRGSVD) algorithms. This work was supported in part by the National Science Foundation of China (Nos. 11771249 and 11371219).

A unifying model of concurrent spatial and temporal modularity in muscle activity.

PubMed

Delis, Ioannis; Panzeri, Stefano; Pozzo, Thierry; Berret, Bastien

2014-02-01

Modularity in the central nervous system (CNS), i.e., the brain capability to generate a wide repertoire of movements by combining a small number of building blocks ("modules"), is thought to underlie the control of movement. Numerous studies reported evidence for such a modular organization by identifying invariant muscle activation patterns across various tasks. However, previous studies relied on decompositions differing in both the nature and dimensionality of the identified modules. Here, we derive a single framework that encompasses all influential models of muscle activation modularity. We introduce a new model (named space-by-time decomposition) that factorizes muscle activations into concurrent spatial and temporal modules. To infer these modules, we develop an algorithm, referred to as sample-based nonnegative matrix trifactorization (sNM3F). We test the space-by-time decomposition on a comprehensive electromyographic dataset recorded during execution of arm pointing movements and show that it provides a low-dimensional yet accurate, highly flexible and task-relevant representation of muscle patterns. The extracted modules have a well characterized functional meaning and implement an efficient trade-off between replication of the original muscle patterns and task discriminability. Furthermore, they are compatible with the modules extracted from existing models, such as synchronous synergies and temporal primitives, and generalize time-varying synergies. Our results indicate the effectiveness of a simultaneous but separate condensation of spatial and temporal dimensions of muscle patterns. The space-by-time decomposition accommodates a unified view of the hierarchical mapping from task parameters to coordinated muscle activations, which could be employed as a reference framework for studying compositional motor control.

Synthesis of graphene by cobalt-catalyzed decomposition of methane in plasma-enhanced CVD: Optimization of experimental parameters with Taguchi method

NASA Astrophysics Data System (ADS)

Mehedi, H.-A.; Baudrillart, B.; Alloyeau, D.; Mouhoub, O.; Ricolleau, C.; Pham, V. D.; Chacon, C.; Gicquel, A.; Lagoute, J.; Farhat, S.

2016-08-01

This article describes the significant roles of process parameters in the deposition of graphene films via cobalt-catalyzed decomposition of methane diluted in hydrogen using plasma-enhanced chemical vapor deposition (PECVD). The influence of growth temperature (700-850 °C), molar concentration of methane (2%-20%), growth time (30-90 s), and microwave power (300-400 W) on graphene thickness and defect density is investigated using Taguchi method which enables reaching the optimal parameter settings by performing reduced number of experiments. Growth temperature is found to be the most influential parameter in minimizing the number of graphene layers, whereas microwave power has the second largest effect on crystalline quality and minor role on thickness of graphene films. The structural properties of PECVD graphene obtained with optimized synthesis conditions are investigated with Raman spectroscopy and corroborated with atomic-scale characterization performed by high-resolution transmission electron microscopy and scanning tunneling microscopy, which reveals formation of continuous film consisting of 2-7 high quality graphene layers.

Synthesis of graphene by cobalt-catalyzed decomposition of methane in plasma-enhanced CVD: Optimization of experimental parameters with Taguchi method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mehedi, H.-A.; Baudrillart, B.; Gicquel, A.

2016-08-14

This article describes the significant roles of process parameters in the deposition of graphene films via cobalt-catalyzed decomposition of methane diluted in hydrogen using plasma-enhanced chemical vapor deposition (PECVD). The influence of growth temperature (700–850 °C), molar concentration of methane (2%–20%), growth time (30–90 s), and microwave power (300–400 W) on graphene thickness and defect density is investigated using Taguchi method which enables reaching the optimal parameter settings by performing reduced number of experiments. Growth temperature is found to be the most influential parameter in minimizing the number of graphene layers, whereas microwave power has the second largest effect on crystalline qualitymore » and minor role on thickness of graphene films. The structural properties of PECVD graphene obtained with optimized synthesis conditions are investigated with Raman spectroscopy and corroborated with atomic-scale characterization performed by high-resolution transmission electron microscopy and scanning tunneling microscopy, which reveals formation of continuous film consisting of 2–7 high quality graphene layers.« less

Nonstationary Dynamics Data Analysis with Wavelet-SVD Filtering

NASA Technical Reports Server (NTRS)

Brenner, Marty; Groutage, Dale; Bessette, Denis (Technical Monitor)

2001-01-01

Nonstationary time-frequency analysis is used for identification and classification of aeroelastic and aeroservoelastic dynamics. Time-frequency multiscale wavelet processing generates discrete energy density distributions. The distributions are processed using the singular value decomposition (SVD). Discrete density functions derived from the SVD generate moments that detect the principal features in the data. The SVD standard basis vectors are applied and then compared with a transformed-SVD, or TSVD, which reduces the number of features into more compact energy density concentrations. Finally, from the feature extraction, wavelet-based modal parameter estimation is applied.

Scalable parallel elastic-plastic finite element analysis using a quasi-Newton method with a balancing domain decomposition preconditioner

NASA Astrophysics Data System (ADS)

Yusa, Yasunori; Okada, Hiroshi; Yamada, Tomonori; Yoshimura, Shinobu

2018-04-01

A domain decomposition method for large-scale elastic-plastic problems is proposed. The proposed method is based on a quasi-Newton method in conjunction with a balancing domain decomposition preconditioner. The use of a quasi-Newton method overcomes two problems associated with the conventional domain decomposition method based on the Newton-Raphson method: (1) avoidance of a double-loop iteration algorithm, which generally has large computational complexity, and (2) consideration of the local concentration of nonlinear deformation, which is observed in elastic-plastic problems with stress concentration. Moreover, the application of a balancing domain decomposition preconditioner ensures scalability. Using the conventional and proposed domain decomposition methods, several numerical tests, including weak scaling tests, were performed. The convergence performance of the proposed method is comparable to that of the conventional method. In particular, in elastic-plastic analysis, the proposed method exhibits better convergence performance than the conventional method.

The Identification of the Deformation Stage of a Metal Specimen Based on Acoustic Emission Data Analysis

PubMed Central

Zou, Shenao; Yan, Fengying; Yang, Guoan; Sun, Wei

2017-01-01

The acoustic emission (AE) signals of metal materials have been widely used to identify the deformation stage of a pressure vessel. In this work, Q235 steel samples with different propagation distances and geometrical structures are stretched to get the corresponding acoustic emission signals. Then the obtained acoustic emission signals are de-noised by empirical mode decomposition (EMD), and then decomposed into two different frequency ranges, i.e., one mainly corresponding to metal deformation and the other mainly corresponding to friction signals. The ratio of signal energy between two frequency ranges is defined as a new acoustic emission characteristic parameter. Differences can be observed at different deformation stages in both magnitude and data distribution range. Compared with other acoustic emission parameters, the proposed parameter is valid in different setups of the propagation medium and the coupled stiffness. PMID:28387703

Array magnetics modal analysis for the DIII-D tokamak based on localized time-series modelling

DOE PAGES

Olofsson, K. Erik J.; Hanson, Jeremy M.; Shiraki, Daisuke; ...

2014-07-14

Here, time-series analysis of magnetics data in tokamaks is typically done using block-based fast Fourier transform methods. This work presents the development and deployment of a new set of algorithms for magnetic probe array analysis. The method is based on an estimation technique known as stochastic subspace identification (SSI). Compared with the standard coherence approach or the direct singular value decomposition approach, the new technique exhibits several beneficial properties. For example, the SSI method does not require that frequencies are orthogonal with respect to the timeframe used in the analysis. Frequencies are obtained directly as parameters of localized time-series models.more » The parameters are extracted by solving small-scale eigenvalue problems. Applications include maximum-likelihood regularized eigenmode pattern estimation, detection of neoclassical tearing modes, including locked mode precursors, and automatic clustering of modes, and magnetics-pattern characterization of sawtooth pre- and postcursors, edge harmonic oscillations and fishbones.« less

Interdependence between Greece and other European stock markets: A comparison of wavelet and VMD copula, and the portfolio implications

NASA Astrophysics Data System (ADS)

Shahzad, Syed Jawad Hussain; Kumar, Ronald Ravinesh; Ali, Sajid; Ameer, Saba

2016-09-01

The interdependence of Greece and other European stock markets and the subsequent portfolio implications are examined in wavelet and variational mode decomposition domain. In applying the decomposition techniques, we analyze the structural properties of data and distinguish between short and long term dynamics of stock market returns. First, the GARCH-type models are fitted to obtain the standardized residuals. Next, different copula functions are evaluated, and based on the conventional information criteria and time varying parameter, Joe-Clayton copula is chosen to model the tail dependence between the stock markets. The short-run lower tail dependence time paths show a sudden increase in comovement during the global financial crises. The results of the long-run dependence suggest that European stock markets have higher interdependence with Greece stock market. Individual country's Value at Risk (VaR) separates the countries into two distinct groups. Finally, the two-asset portfolio VaR measures provide potential markets for Greece stock market investment diversification.

Fluorescence background removal method for biological Raman spectroscopy based on empirical mode decomposition.

PubMed

Leon-Bejarano, Maritza; Dorantes-Mendez, Guadalupe; Ramirez-Elias, Miguel; Mendez, Martin O; Alba, Alfonso; Rodriguez-Leyva, Ildefonso; Jimenez, M

2016-08-01

Raman spectroscopy of biological tissue presents fluorescence background, an undesirable effect that generates false Raman intensities. This paper proposes the application of the Empirical Mode Decomposition (EMD) method to baseline correction. EMD is a suitable approach since it is an adaptive signal processing method for nonlinear and non-stationary signal analysis that does not require parameters selection such as polynomial methods. EMD performance was assessed through synthetic Raman spectra with different signal to noise ratio (SNR). The correlation coefficient between synthetic Raman spectra and the recovered one after EMD denoising was higher than 0.92. Additionally, twenty Raman spectra from skin were used to evaluate EMD performance and the results were compared with Vancouver Raman algorithm (VRA). The comparison resulted in a mean square error (MSE) of 0.001554. High correlation coefficient using synthetic spectra and low MSE in the comparison between EMD and VRA suggest that EMD could be an effective method to remove fluorescence background in biological Raman spectra.

Polar decomposition of the Mueller matrix: a polarimetric rule of thumb for square-profile surface structure recognition.

PubMed

Sanz, J M; Saiz, J M; González, F; Moreno, F

2011-07-20

In this research, the polar decomposition (PD) method is applied to experimental Mueller matrices (MMs) measured on two-dimensional microstructured surfaces. Polarization information is expressed through a set of parameters of easier physical interpretation. It is shown that evaluating the first derivative of the retardation parameter, δ, a clear indication of the presence of defects either built on or dug in the scattering flat surface (a silicon wafer in our case) can be obtained. Although the rule of thumb thus obtained is established through PD, it can be easily implemented on conventional surface polarimetry. These results constitute an example of the capabilities of the PD approach to MM analysis, and show a direct application in surface characterization. © 2011 Optical Society of America

Reactive Goal Decomposition Hierarchies for On-Board Autonomy

NASA Astrophysics Data System (ADS)

Hartmann, L.

2002-01-01

As our experience grows, space missions and systems are expected to address ever more complex and demanding requirements with fewer resources (e.g., mass, power, budget). One approach to accommodating these higher expectations is to increase the level of autonomy to improve the capabilities and robustness of on- board systems and to simplify operations. The goal decomposition hierarchies described here provide a simple but powerful form of goal-directed behavior that is relatively easy to implement for space systems. A goal corresponds to a state or condition that an operator of the space system would like to bring about. In the system described here goals are decomposed into simpler subgoals until the subgoals are simple enough to execute directly. For each goal there is an activation condition and a set of decompositions. The decompositions correspond to different ways of achieving the higher level goal. Each decomposition contains a gating condition and a set of subgoals to be "executed" sequentially or in parallel. The gating conditions are evaluated in order and for the first one that is true, the corresponding decomposition is executed in order to achieve the higher level goal. The activation condition specifies global conditions (i.e., for all decompositions of the goal) that need to hold in order for the goal to be achieved. In real-time, parameters and state information are passed between goals and subgoals in the decomposition; a termination indication (success, failure, degree) is passed up when a decomposition finishes executing. The lowest level decompositions include servo control loops and finite state machines for generating control signals and sequencing i/o. Semaphores and shared memory are used to synchronize and coordinate decompositions that execute in parallel. The goal decomposition hierarchy is reactive in that the generated behavior is sensitive to the real-time state of the system and the environment. That is, the system is able to react to state and environment and in general can terminate the execution of a decomposition and attempt a new decomposition at any level in the hierarchy. This goal decomposition system is suitable for workstation, microprocessor and fpga implementation and thus is able to support the full range of prototyping activities, from mission design in the laboratory to development of the fpga firmware for the flight system. This approach is based on previous artificial intelligence work including (1) Brooks' subsumption architecture for robot control, (2) Firby's Reactive Action Package System (RAPS) for mediating between high level automated planning and low level execution and (3) hierarchical task networks for automated planning. Reactive goal decomposition hierarchies can be used for a wide variety of on-board autonomy applications including automating low level operation sequences (such as scheduling prerequisite operations, e.g., heaters, warm-up periods, monitoring power constraints), coordinating multiple spacecraft as in formation flying and constellations, robot manipulator operations, rendez-vous, docking, servicing, assembly, on-orbit maintenance, planetary rover operations, solar system and interstellar probes, intelligent science data gathering and disaster early warning. Goal decomposition hierarchies can support high level fault tolerance. Given models of on-board resources and goals to accomplish, the decomposition hierarchy could allocate resources to goals taking into account existing faults and in real-time reallocating resources as new faults arise. Resources to be modeled include memory (e.g., ROM, FPGA configuration memory, processor memory, payload instrument memory), processors, on-board and interspacecraft network nodes and links, sensors, actuators (e.g., attitude determination and control, guidance and navigation) and payload instruments. A goal decomposition hierarchy could be defined to map mission goals and tasks to available on-board resources. As faults occur and are detected the resource allocation is modified to avoid using the faulty resource. Goal decomposition hierarchies can implement variable autonomy (in which the operator chooses to command the system at a high or low level, mixed initiative planning (in which the system is able to interact with the operator, e.g, to request operator intervention when a working envelope is exceeded) and distributed control (in which, for example, multiple spacecraft cooperate to accomplish a task without a fixed master). The full paper will describe in greater detail how goal decompositions work, how they can be implemented, techniques for implementing a candidate application and the current state of the fpga implementation.

ENVIRONMENTAL ASSESSMENT OF THE BASE CATALYZED DECOMPOSITION (BCD) PROCESS

EPA Science Inventory

This report summarizes laboratory-scale, pilot-scale, and field performance data on BCD (Base Catalyzed Decomposition) and technology, collected to date by various governmental, academic, and private organizations.

An Intelligent Pattern Recognition System Based on Neural Network and Wavelet Decomposition for Interpretation of Heart Sounds

DTIC Science & Technology

2001-10-25

wavelet decomposition of signals and classification using neural network. Inputs to the system are the heart sound signals acquired by a stethoscope in a...Proceedings. pp. 415–418, 1990. [3] G. Ergun, “An intelligent diagnostic system for interpretation of arterpartum fetal heart rate tracings based on ANNs and...AN INTELLIGENT PATTERN RECOGNITION SYSTEM BASED ON NEURAL NETWORK AND WAVELET DECOMPOSITION FOR INTERPRETATION OF HEART SOUNDS I. TURKOGLU1, A

VizieR Online Data Catalog: 3.6um S4G Galactic bars characterization (Diaz-Garcia+, 2016)

NASA Astrophysics Data System (ADS)

Diaz-Garcia, S.; Salo, H.; Laurikainen, E.; Herrera-Endoqui, M.

2015-11-01

Here, we provide the bar strength measurements of a sample of ~600 barred galaxies drawn from the Spitzer Survey of Stellar Structure in Galaxies (Sheth et al., 2010, Cat. J/PASP/122/1397). Bars were identified based on the morphological classifications by Buta et al. (2015, Cat. J/ApJS/217/32). Besides, we provide a parameterization of the stellar contribution to the rotation curve and an estimate to the stellar-to-halo mass ratio within the optical radius for a sample of 1345 non-highly inclined galaxies (i<65°). The radial force profiles and rotation curve decomposition models of each of these galaxies are also given. Table A1 contains fundamental parameters of the galaxies such as the total stellar mass and distances (values for all the S4G sample are calculated in Munoz-Mateos et al., 2015ApJS..219....3M). Besides, we provide an estimate of the scale-heights and optical radii. We also list the inclination-corrected HI maximum velocities, the parameters of the stellar and halo components of the rotation curves, and the estimates of the halo-to-stellar mass ratios within the optical disk. In Table A2 it is given the gravitational torque parameters and radii, with and without spiral arms and halo correction. In Table A3 it is provided the maximum normalized Fourier amplitudes and radii (for the m = 2, 4, 6 and 8 components) and the bar ellipticities (from Herrera-Endoqui et al., 2015A&A...582A..86H) deprojected to the disk plane using the orientation parameters from S4G Pipeline 4 (Salo et al., 2015, Cat. J/ApJS/219/4). The evaluation of the gravitational torques and m=2 Fourier amplitude at the bar radius is also listed in both tables. In the directory "rfp" we provide the gravitational torque radial profiles, with and without spiral arms and halo correction, even Fourier amplitudes and m=2 phase of 1345 non-highly inclined disk S4G galaxies ("radialforce_profiles.dat"). Likewise, for the same sample, in the directory "rcdm" we tabulate the rotation curve decomposition model ("rotationcurve_decomposition.dat"), with the stellar component inferred from the 3.6~μm imaging and the halo component estimated using the universal rotation curve models). (5 data files).

Local sensitivity analysis for inverse problems solved by singular value decomposition

USGS Publications Warehouse

Hill, M.C.; Nolan, B.T.

2010-01-01

Local sensitivity analysis provides computationally frugal ways to evaluate models commonly used for resource management, risk assessment, and so on. This includes diagnosing inverse model convergence problems caused by parameter insensitivity and(or) parameter interdependence (correlation), understanding what aspects of the model and data contribute to measures of uncertainty, and identifying new data likely to reduce model uncertainty. Here, we consider sensitivity statistics relevant to models in which the process model parameters are transformed using singular value decomposition (SVD) to create SVD parameters for model calibration. The statistics considered include the PEST identifiability statistic, and combined use of the process-model parameter statistics composite scaled sensitivities and parameter correlation coefficients (CSS and PCC). The statistics are complimentary in that the identifiability statistic integrates the effects of parameter sensitivity and interdependence, while CSS and PCC provide individual measures of sensitivity and interdependence. PCC quantifies correlations between pairs or larger sets of parameters; when a set of parameters is intercorrelated, the absolute value of PCC is close to 1.00 for all pairs in the set. The number of singular vectors to include in the calculation of the identifiability statistic is somewhat subjective and influences the statistic. To demonstrate the statistics, we use the USDA’s Root Zone Water Quality Model to simulate nitrogen fate and transport in the unsaturated zone of the Merced River Basin, CA. There are 16 log-transformed process-model parameters, including water content at field capacity (WFC) and bulk density (BD) for each of five soil layers. Calibration data consisted of 1,670 observations comprising soil moisture, soil water tension, aqueous nitrate and bromide concentrations, soil nitrate concentration, and organic matter content. All 16 of the SVD parameters could be estimated by regression based on the range of singular values. Identifiability statistic results varied based on the number of SVD parameters included. Identifiability statistics calculated for four SVD parameters indicate the same three most important process-model parameters as CSS/PCC (WFC1, WFC2, and BD2), but the order differed. Additionally, the identifiability statistic showed that BD1 was almost as dominant as WFC1. The CSS/PCC analysis showed that this results from its high correlation with WCF1 (-0.94), and not its individual sensitivity. Such distinctions, combined with analysis of how high correlations and(or) sensitivities result from the constructed model, can produce important insights into, for example, the use of sensitivity analysis to design monitoring networks. In conclusion, the statistics considered identified similar important parameters. They differ because (1) with CSS/PCC can be more awkward because sensitivity and interdependence are considered separately and (2) identifiability requires consideration of how many SVD parameters to include. A continuing challenge is to understand how these computationally efficient methods compare with computationally demanding global methods like Markov-Chain Monte Carlo given common nonlinear processes and the often even more nonlinear models.

Hydrogen and carbon nanotube production via catalytic decomposition of methane

NASA Astrophysics Data System (ADS)

Deniz, Cansu; Karatepe, Nilgün

2013-09-01

The future energy demand is expected to increase significantly due to an increasing world population and demands for higher standards of living and better air quality. Hydrogen is considered as an energy carrier because of its high conversion efficiency and low pollutant emissions. It can be produced from various sources and transformed into electricity and other energy forms with a low pollution. The catalytic decomposition of hydrocarbon has been seen as a really useful method for production of pure hydrogen and for the environmental concern. The objective of this study was to assess the impact of catalyst composition and processing parameters on COx-free hydrogen production and to produce an available solid form of co-product carbon as carbon nanotubes via catalytic decomposition of methane. The optimum experimental conditions for methane decomposition have been investigated. Fe, Co and Ni are used as catalysts (nano materials) over different substrates as SiO2 and MgO to produce hydrogen at optimum temperatures.

Active sites and mechanisms for H2O2 decomposition over Pd catalysts

PubMed Central

Plauck, Anthony; Stangland, Eric E.; Dumesic, James A.; Mavrikakis, Manos

2016-01-01

A combination of periodic, self-consistent density functional theory (DFT-GGA-PW91) calculations, reaction kinetics experiments on a SiO2-supported Pd catalyst, and mean-field microkinetic modeling are used to probe key aspects of H2O2 decomposition on Pd in the absence of cofeeding H2. We conclude that both Pd(111) and OH-partially covered Pd(100) surfaces represent the nature of the active site for H2O2 decomposition on the supported Pd catalyst reasonably well. Furthermore, all reaction flux in the closed catalytic cycle is predicted to flow through an O–O bond scission step in either H2O2 or OOH, followed by rapid H-transfer steps to produce the H2O and O2 products. The barrier for O–O bond scission is sensitive to Pd surface structure and is concluded to be the central parameter governing H2O2 decomposition activity. PMID:27006504

Land-use legacies regulate decomposition dynamics following bioenergy crop conversion

DOE PAGES

Kallenbach, Cynthia M.; Stuart Grandy, A.

2014-07-14

Land-use conversion into bioenergy crop production can alter litter decomposition processes tightly coupled to soil carbon and nutrient dynamics. Yet, litter decomposition has been poorly described in bioenergy production systems, especially following land-use conversion. Predicting decomposition dynamics in postconversion bioenergy production systems is challenging because of the combined influence of land-use legacies with current management and litter quality. To evaluate how land-use legacies interact with current bioenergy crop management to influence litter decomposition in different litter types, we conducted a landscape-scale litterbag decomposition experiment. We proposed land-use legacies regulate decomposition, but their effects are weakened under higher quality litter andmore » when current land use intensifies ecosystem disturbance relative to prior land use. We compared sites left in historical land uses of either agriculture (AG) or Conservation Reserve Program grassland (CRP) to those that were converted to corn or switchgrass bioenergy crop production. Enzyme activities, mass loss, microbial biomass, and changes in litter chemistry were monitored in corn stover and switchgrass litter over 485 days, accompanied by similar soil measurements. Across all measured variables, legacy had the strongest effect (P < 0.05) relative to litter type and current management, where CRP sites maintained higher soil and litter enzyme activities and microbial biomass relative to AG sites. Decomposition responses to conversion depended on legacy but also current management and litter type. Within the CRP sites, conversion into corn increased litter enzymes, microbial biomass, and litter protein and lipid abundances, especially on decomposing corn litter, relative to nonconverted CRP. However, conversion into switchgrass from CRP, a moderate disturbance, often had no effect on switchgrass litter decomposition parameters. Thus, legacies shape the direction and magnitude of decomposition responses to bioenergy crop conversion and therefore should be considered a key influence on litter and soil C cycling under bioenergy crop management.« less

Steganography based on pixel intensity value decomposition

NASA Astrophysics Data System (ADS)

Abdulla, Alan Anwar; Sellahewa, Harin; Jassim, Sabah A.

2014-05-01

This paper focuses on steganography based on pixel intensity value decomposition. A number of existing schemes such as binary, Fibonacci, Prime, Natural, Lucas, and Catalan-Fibonacci (CF) are evaluated in terms of payload capacity and stego quality. A new technique based on a specific representation is proposed to decompose pixel intensity values into 16 (virtual) bit-planes suitable for embedding purposes. The proposed decomposition has a desirable property whereby the sum of all bit-planes does not exceed the maximum pixel intensity value, i.e. 255. Experimental results demonstrate that the proposed technique offers an effective compromise between payload capacity and stego quality of existing embedding techniques based on pixel intensity value decomposition. Its capacity is equal to that of binary and Lucas, while it offers a higher capacity than Fibonacci, Prime, Natural, and CF when the secret bits are embedded in 1st Least Significant Bit (LSB). When the secret bits are embedded in higher bit-planes, i.e., 2nd LSB to 8th Most Significant Bit (MSB), the proposed scheme has more capacity than Natural numbers based embedding. However, from the 6th bit-plane onwards, the proposed scheme offers better stego quality. In general, the proposed decomposition scheme has less effect in terms of quality on pixel value when compared to most existing pixel intensity value decomposition techniques when embedding messages in higher bit-planes.

A comparison of reduced-order modelling techniques for application in hyperthermia control and estimation.

PubMed

Bailey, E A; Dutton, A W; Mattingly, M; Devasia, S; Roemer, R B

1998-01-01

Reduced-order modelling techniques can make important contributions in the control and state estimation of large systems. In hyperthermia, reduced-order modelling can provide a useful tool by which a large thermal model can be reduced to the most significant subset of its full-order modes, making real-time control and estimation possible. Two such reduction methods, one based on modal decomposition and the other on balanced realization, are compared in the context of simulated hyperthermia heat transfer problems. The results show that the modal decomposition reduction method has three significant advantages over that of balanced realization. First, modal decomposition reduced models result in less error, when compared to the full-order model, than balanced realization reduced models of similar order in problems with low or moderate advective heat transfer. Second, because the balanced realization based methods require a priori knowledge of the sensor and actuator placements, the reduced-order model is not robust to changes in sensor or actuator locations, a limitation not present in modal decomposition. Third, the modal decomposition transformation is less demanding computationally. On the other hand, in thermal problems dominated by advective heat transfer, numerical instabilities make modal decomposition based reduction problematic. Modal decomposition methods are therefore recommended for reduction of models in which advection is not dominant and research continues into methods to render balanced realization based reduction more suitable for real-time clinical hyperthermia control and estimation.

A New Approach of evaluating the damage in simply-supported reinforced concrete beam by Local mean decomposition (LMD)

NASA Astrophysics Data System (ADS)

Zhang, Xuebing; Liu, Ning; Xi, Jiaxin; Zhang, Yunqi; Zhang, Wenchun; Yang, Peipei

2017-08-01

How to analyze the nonstationary response signals and obtain vibration characters is extremely important in the vibration-based structural diagnosis methods. In this work, we introduce a more reasonable time-frequency decomposition method termed local mean decomposition (LMD) to instead the widely-used empirical mode decomposition (EMD). By employing the LMD method, one can derive a group of component signals, each of which is more stationary, and then analyze the vibration state and make the assessment of structural damage of a construction or building. We illustrated the effectiveness of LMD by a synthetic data and an experimental data recorded in a simply-supported reinforced concrete beam. Then based on the decomposition results, an elementary method of damage diagnosis was proposed.

Water/cortical bone decomposition: A new approach in dual energy CT imaging for bone marrow oedema detection. A feasibility study.

PubMed

Biondi, M; Vanzi, E; De Otto, G; Banci Buonamici, F; Belmonte, G M; Mazzoni, L N; Guasti, A; Carbone, S F; Mazzei, M A; La Penna, A; Foderà, E; Guerreri, D; Maiolino, A; Volterrani, L

2016-12-01

Many studies aimed at validating the application of Dual Energy Computed Tomography (DECT) in clinical practice where conventional CT is not exhaustive. An example is given by bone marrow oedema detection, in which DECT based on water/calcium (W/Ca) decomposition was applied. In this paper a new DECT approach, based on water/cortical bone (W/CB) decomposition, was investigated. Eight patients suffering from marrow oedema were scanned with MRI and DECT. Two-materials density decomposition was performed in ROIs corresponding to normal bone marrow and oedema. These regions were drawn on DECT images using MRI informations. Both W/Ca and W/CB were considered as material basis. Scatter plots of W/Ca and W/CB concentrations were made for each ROI in order to evaluate if oedema could be distinguished from normal bone marrow. Thresholds were defined on the scatter plots in order to produce DECT images where oedema regions were highlighted through color maps. The agreement between these images and MR was scored by two expert radiologists. For all the patients, the best scores were obtained using W/CB density decomposition. In all cases, DECT color map images based on W/CB decomposition showed better agreement with MR in bone marrow oedema identification with respect to W/Ca decomposition. This result encourages further studies in order to evaluate if DECT based on W/CB decomposition could be an alternative technique to MR, which would be important when short scanning duration is relevant, as in the case of aged or traumatic patients. Copyright © 2016 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

A new adaptive algorithm for automated feature extraction in exponentially damped signals for health monitoring of smart structures

NASA Astrophysics Data System (ADS)

Qarib, Hossein; Adeli, Hojjat

2015-12-01

In this paper authors introduce a new adaptive signal processing technique for feature extraction and parameter estimation in noisy exponentially damped signals. The iterative 3-stage method is based on the adroit integration of the strengths of parametric and nonparametric methods such as multiple signal categorization, matrix pencil, and empirical mode decomposition algorithms. The first stage is a new adaptive filtration or noise removal scheme. The second stage is a hybrid parametric-nonparametric signal parameter estimation technique based on an output-only system identification technique. The third stage is optimization of estimated parameters using a combination of the primal-dual path-following interior point algorithm and genetic algorithm. The methodology is evaluated using a synthetic signal and a signal obtained experimentally from transverse vibrations of a steel cantilever beam. The method is successful in estimating the frequencies accurately. Further, it estimates the damping exponents. The proposed adaptive filtration method does not include any frequency domain manipulation. Consequently, the time domain signal is not affected as a result of frequency domain and inverse transformations.

Decomposition of Fuzzy Soft Sets with Finite Value Spaces

PubMed Central

Jun, Young Bae

2014-01-01

The notion of fuzzy soft sets is a hybrid soft computing model that integrates both gradualness and parameterization methods in harmony to deal with uncertainty. The decomposition of fuzzy soft sets is of great importance in both theory and practical applications with regard to decision making under uncertainty. This study aims to explore decomposition of fuzzy soft sets with finite value spaces. Scalar uni-product and int-product operations of fuzzy soft sets are introduced and some related properties are investigated. Using t-level soft sets, we define level equivalent relations and show that the quotient structure of the unit interval induced by level equivalent relations is isomorphic to the lattice consisting of all t-level soft sets of a given fuzzy soft set. We also introduce the concepts of crucial threshold values and complete threshold sets. Finally, some decomposition theorems for fuzzy soft sets with finite value spaces are established, illustrated by an example concerning the classification and rating of multimedia cell phones. The obtained results extend some classical decomposition theorems of fuzzy sets, since every fuzzy set can be viewed as a fuzzy soft set with a single parameter. PMID:24558342

Decomposition of fuzzy soft sets with finite value spaces.

PubMed

Feng, Feng; Fujita, Hamido; Jun, Young Bae; Khan, Madad

2014-01-01

The notion of fuzzy soft sets is a hybrid soft computing model that integrates both gradualness and parameterization methods in harmony to deal with uncertainty. The decomposition of fuzzy soft sets is of great importance in both theory and practical applications with regard to decision making under uncertainty. This study aims to explore decomposition of fuzzy soft sets with finite value spaces. Scalar uni-product and int-product operations of fuzzy soft sets are introduced and some related properties are investigated. Using t-level soft sets, we define level equivalent relations and show that the quotient structure of the unit interval induced by level equivalent relations is isomorphic to the lattice consisting of all t-level soft sets of a given fuzzy soft set. We also introduce the concepts of crucial threshold values and complete threshold sets. Finally, some decomposition theorems for fuzzy soft sets with finite value spaces are established, illustrated by an example concerning the classification and rating of multimedia cell phones. The obtained results extend some classical decomposition theorems of fuzzy sets, since every fuzzy set can be viewed as a fuzzy soft set with a single parameter.

Unusual behavior in the reactivity of 5-substituted-1H-tetrazoles in a resistively heated microreactor

PubMed Central

Gutmann, Bernhard; Glasnov, Toma N; Razzaq, Tahseen; Goessler, Walter; Roberge, Dominique M

2011-01-01

Summary The decomposition of 5-benzhydryl-1H-tetrazole in an N-methyl-2-pyrrolidone/acetic acid/water mixture was investigated under a variety of high-temperature reaction conditions. Employing a sealed Pyrex glass vial and batch microwave conditions at 240 °C, the tetrazole is comparatively stable and complete decomposition to diphenylmethane requires more than 8 h. Similar kinetic data were obtained in conductively heated flow devices with either stainless steel or Hastelloy coils in the same temperature region. In contrast, in a flow instrument that utilizes direct electric resistance heating of the reactor coil, tetrazole decomposition was dramatically accelerated with rate constants increased by two orders of magnitude. When 5-benzhydryl-1H-tetrazole was exposed to 220 °C in this type of flow reactor, decomposition to diphenylmethane was complete within 10 min. The mechanism and kinetic parameters of tetrazole decomposition under a variety of reaction conditions were investigated. A number of possible explanations for these highly unusual rate accelerations are presented. In addition, general aspects of reactor degradation, corrosion and contamination effects of importance to continuous flow chemistry are discussed. PMID:21647324

A spectral X-ray CT simulation study for quantitative determination of iron

NASA Astrophysics Data System (ADS)

Su, Ting; Kaftandjian, Valérie; Duvauchelle, Philippe; Zhu, Yuemin

2018-06-01

Iron is an essential element in the human body and disorders in iron such as iron deficiency or overload can cause serious diseases. This paper aims to explore the ability of spectral X-ray CT to quantitatively separate iron from calcium and potassium and to investigate the influence of different acquisition parameters on material decomposition performance. We simulated spectral X-ray CT imaging of a PMMA phantom filled with iron, calcium, and potassium solutions at various concentrations (15-200 mg/cc). Different acquisition parameters were considered, such as the number of energy bins (6, 10, 15, 20, 30, 60) and exposure factor per projection (0.025, 0.1, 1, 10, 100 mA s). Based on the simulation data, we investigated the performance of two regularized material decomposition approaches: projection domain method and image domain method. It was found that the former method discriminated iron from calcium, potassium and water in all cases and tended to benefit from lower number of energy bins for lower exposure factor acquisition. The latter method succeeded in iron determination only when the number of energy bins equals 60, and in this case, the contrast-to-noise ratios of the decomposed iron images are higher than those obtained using the projection domain method. The results demonstrate that both methods are able to discriminate and quantify iron from calcium, potassium and water under certain conditions. Their performances vary with the acquisition parameters of spectral CT. One can use one method or the other to benefit better performance according to the data available.

Rotordynamic forces in labyrinth seals: Theory and experiment

NASA Technical Reports Server (NTRS)

Millsaps, Knox T.; Martinez-Sanchez, Manuel

1994-01-01

A theoretical and experimental investigation of the aerodynamic forces generated by a single gland labyrinth seal executing a simultaneous spinning/whirling motion has been conducted. A lumped parameter model for a single gland seal with coupling to an upstream cavity with leakage is developed along with an appropriate solution technique. From this theory, it is shown that the presence of the upstream cavity can, in some cases, augment the cross-stiffness and direct damping by a factor of four. The parameters that govern the coupling are presented along with predictions on their influence. A simple uncoupled model is used to identify the mechanisms responsible for cross force generation. This reduced system is nondimensionalized and the physical significance of the reduced parameters is discussed. Closed form algebraic formulas are given for some simple limiting cases. It is also shown that the total cross-force predicted by the uncoupled model can be represented as the sum of an ideal component due to an inviscid flow with entry swirl and a viscous part due to the change in swirl created by friction inside the gland. The frequency dependent ideal part is solely responsible for the rotordynamic direct damping. The facility designed and built to measure these frequency dependent forces is described. Experimental data confirm the validity and usefulness of this ideal/viscous decomposition. A method for calculating the damping coefficients based on the force decomposition using only the static measurements is presented. Experimental results supporting the predicted cross force augmentation due to the effect of upstream coupling are presented.

Enhancement of nitric oxide decomposition efficiency achieved with lanthanum-based perovskite-type catalyst.

PubMed

Pan, Kuan Lun; Chen, Mei Chung; Yu, Sheng Jen; Yan, Shaw Yi; Chang, Moo Been

2016-06-01

Direct decompositions of nitric oxide (NO) by La0.7Ce0.3SrNiO4, La0.4Ba0.4Ce0.2SrNiO4, and Pr0.4Ba0.4Ce0.2SrNiO4 are experimentally investigated, and the catalysts are tested with different operating parameters to evaluate their activities. Experimental results indicate that the physical and chemical properties of La0.7Ce0.3SrNiO4 are significantly improved by doping with Ba and partial substitution with Pr. NO decomposition efficiencies achieved with La0.4Ba0.4Ce0.2SrNiO4 and Pr0.4Ba0.4Ce0.2SrNiO4 are 32% and 68%, respectively, at 400 °C with He as carrier gas. As the temperature is increased to 600 °C, NO decomposition efficiencies achieved with La0.4Ba0.4Ce0.2SrNiO4 and Pr0.4Ba0.4Ce0.2SrNiO4, respectively, reach 100% with the inlet NO concentration of 1000 ppm while the space velocity is fixed at 8000 hr(-1). Effects of O2, H2O(g), and CO2 contents and space velocity on NO decomposition are also explored. The results indicate that NO decomposition efficiencies achieved with La0.4Ba0.4Ce0.2SrNiO4 and Pr0.4Ba0.4Ce0.2SrNiO4, respectively, are slightly reduced as space velocity is increased from 8000 to 20,000 hr(-1) at 500 °C. In addition, the activities of both catalysts (La0.4Ba0.4Ce0.2SrNiO4 and Pr0.4Ba0.4Ce0.2SrNiO4) for NO decomposition are slightly reduced in the presence of 5% O2, 5% CO2, or 5% H2O(g). For durability test, with the space velocity of 8000 hr(-1) and operating temperature of 600 °C, high N2 yield is maintained throughout the durability test of 60 hr, revealing the long-term stability of Pr0.4Ba0.4Ce0.2SrNiO4 for NO decomposition. Overall, Pr0.4Ba0.4Ce0.2SrNiO4 shows good catalytic activity for NO decomposition. Nitrous oxide (NO) not only causes adverse environmental effects such as acid rain, photochemical smog, and deterioration of visibility and water quality, but also harms human lungs and respiratory system. Pervoskite-type catalysts, including La0.7Ce0.3SrNiO4, La0.4Ba0.4Ce0.2SrNiO4, and Pr0.4Ba0.4Ce0.2SrNiO4, are applied for direct NO decomposition. The results show that NO decomposition can be enhanced as La0.7Ce0.3SrNiO4 is substituted with Ba and/or Pr. At 600 °C, NO decomposition efficiencies achieved with La0.4Ba0.4Ce0.2SrNiO4 and Pr0.4Ba0.4Ce0.2SrNiO4 reach 100%, demonstrating high activity and good potential for direct NO decomposition. Effects of O2, H2O(g), and CO2 contents on catalytic activities are also evaluated and discussed.

Probabilistic assessment of landslide tsunami hazard for the northern Gulf of Mexico

NASA Astrophysics Data System (ADS)

Pampell-Manis, A.; Horrillo, J.; Shigihara, Y.; Parambath, L.

2016-01-01

The devastating consequences of recent tsunamis affecting Indonesia and Japan have prompted a scientific response to better assess unexpected tsunami hazards. Although much uncertainty exists regarding the recurrence of large-scale tsunami events in the Gulf of Mexico (GoM), geological evidence indicates that a tsunami is possible and would most likely come from a submarine landslide triggered by an earthquake. This study customizes for the GoM a first-order probabilistic landslide tsunami hazard assessment. Monte Carlo Simulation (MCS) is employed to determine landslide configurations based on distributions obtained from observational submarine mass failure (SMF) data. Our MCS approach incorporates a Cholesky decomposition method for correlated landslide size parameters to capture correlations seen in the data as well as uncertainty inherent in these events. Slope stability analyses are performed using landslide and sediment properties and regional seismic loading to determine landslide configurations which fail and produce a tsunami. The probability of each tsunamigenic failure is calculated based on the joint probability of slope failure and probability of the triggering earthquake. We are thus able to estimate sizes and return periods for probabilistic maximum credible landslide scenarios. We find that the Cholesky decomposition approach generates landslide parameter distributions that retain the trends seen in observational data, improving the statistical validity and relevancy of the MCS technique in the context of landslide tsunami hazard assessment. Estimated return periods suggest that probabilistic maximum credible SMF events in the north and northwest GoM have a recurrence of 5000-8000 years, in agreement with age dates of observed deposits.

Hyperfine Sublevel Correlation (HYSCORE) Spectra for Paramagnetic Centers with Nuclear Spin I = 1 Having Isotropic Hyperfine Interactions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maryasov, Alexander G.; Bowman, Michael K.

2004-07-08

It is shown that HYSCORE spectra of paramagnetic centers having nuclei of spin I=1 with isotropic hfi and arbitrary NQI consist of ridges having zero width. A parametric presentation of these ridges is found which shows the range of possible frequencies in the HYSCORE spectrum and aids in spectral assignments and rapid estimation of spin Hamiltonian parameters. An alternative approach for the spectral density calculation is presented that is based on spectral decomposition of the Hamiltonian. Only the eigenvalues of the Hamiltonian are needed in this approach. An atlas of HYSCORE spectra is given in the Supporting Information. This approachmore » is applied to the estimation of the spin Hamiltonian parameters of the oxovanadium-EDTA complex.« less

Paving the way to a full chip gate level double patterning application

NASA Astrophysics Data System (ADS)

Haffner, Henning; Meiring, Jason; Baum, Zachary; Halle, Scott

2007-10-01

Double patterning lithography processes can offer significant yield enhancement for challenging circuit designs. Many decomposition (i.e. the process of dividing the layout design into first and second exposures) techniques are possible, but the focus of this paper is on the use of a secondary "cut" mask to trim away extraneous features left from the first exposure. This approach has the advantage that each exposure only needs to support a subset of critical features (e.g. dense lines with the first exposure, isolated spaces with the second one). The extraneous features ("printing assist features" or PrAFs) are designed to support the process window of critical features much like the role of the subresolution assist features (SRAFs) in conventional processes. However, the printing nature of PrAFs leads to many more design options, and hence a greater process and decomposition parameter exploration space, than are available for SRAFs. A decomposition scheme using PRAFs was developed for a gate level process. A critical driver of the work was to deliver improved across-chip linewidth variation (ACLV) performance versus an optimized single exposure process while providing support for a larger range of critical features. A variety of PRAF techniques were investigated by simulation, with a PrAF scheme similar to standard SRAF rules being chosen as the optimal solution [1]. This paper discusses aspects of the code development for an automated PrAF generation and placement scheme and the subsequent decomposition of a layout into two mask levels. While PrAF placement and decomposition is straightforward for layouts with pitch and orientation restrictions, it becomes rather complex for unrestricted layout styles. Because this higher complexity yields more irregularly shaped PrAFs, mask making becomes another critical driver of the optimum placement and clean-up strategies. Examples are given of how those challenges are met or can be successfully circumvented. During subsequent decomposition of the PrAF-enhanced layout into two independent mask levels, various geometric decomposition parameters have to be considered. As an example, the removal of PrAFs has to be guaranteed by a minimum required overlap of the cut mask opening past any PrAF edge. It is discussed that process assumptions such as CD tolerances and overlay as well as inter-level relationship ground rules need to be considered to successfully optimize the final decomposition scheme. Furthermore, simulation and experimental results regarding not only ACLV but also across-device linewidth variation (ADLV) are analyzed.

3D tensor-based blind multispectral image decomposition for tumor demarcation

NASA Astrophysics Data System (ADS)

Kopriva, Ivica; Peršin, Antun

2010-03-01

Blind decomposition of multi-spectral fluorescent image for tumor demarcation is formulated exploiting tensorial structure of the image. First contribution of the paper is identification of the matrix of spectral responses and 3D tensor of spatial distributions of the materials present in the image from Tucker3 or PARAFAC models of 3D image tensor. Second contribution of the paper is clustering based estimation of the number of the materials present in the image as well as matrix of their spectral profiles. 3D tensor of the spatial distributions of the materials is recovered through 3-mode multiplication of the multi-spectral image tensor and inverse of the matrix of spectral profiles. Tensor representation of the multi-spectral image preserves its local spatial structure that is lost, due to vectorization process, when matrix factorization-based decomposition methods (such as non-negative matrix factorization and independent component analysis) are used. Superior performance of the tensor-based image decomposition over matrix factorization-based decompositions is demonstrated on experimental red-green-blue (RGB) image with known ground truth as well as on RGB fluorescent images of the skin tumor (basal cell carcinoma).

Decomposition of metabolic network into functional modules based on the global connectivity structure of reaction graph.

PubMed

Ma, Hong-Wu; Zhao, Xue-Ming; Yuan, Ying-Jin; Zeng, An-Ping

2004-08-12

Metabolic networks are organized in a modular, hierarchical manner. Methods for a rational decomposition of the metabolic network into relatively independent functional subsets are essential to better understand the modularity and organization principle of a large-scale, genome-wide network. Network decomposition is also necessary for functional analysis of metabolism by pathway analysis methods that are often hampered by the problem of combinatorial explosion due to the complexity of metabolic network. Decomposition methods proposed in literature are mainly based on the connection degree of metabolites. To obtain a more reasonable decomposition, the global connectivity structure of metabolic networks should be taken into account. In this work, we use a reaction graph representation of a metabolic network for the identification of its global connectivity structure and for decomposition. A bow-tie connectivity structure similar to that previously discovered for metabolite graph is found also to exist in the reaction graph. Based on this bow-tie structure, a new decomposition method is proposed, which uses a distance definition derived from the path length between two reactions. An hierarchical classification tree is first constructed from the distance matrix among the reactions in the giant strong component of the bow-tie structure. These reactions are then grouped into different subsets based on the hierarchical tree. Reactions in the IN and OUT subsets of the bow-tie structure are subsequently placed in the corresponding subsets according to a 'majority rule'. Compared with the decomposition methods proposed in literature, ours is based on combined properties of the global network structure and local reaction connectivity rather than, primarily, on the connection degree of metabolites. The method is applied to decompose the metabolic network of Escherichia coli. Eleven subsets are obtained. More detailed investigations of the subsets show that reactions in the same subset are really functionally related. The rational decomposition of metabolic networks, and subsequent studies of the subsets, make it more amenable to understand the inherent organization and functionality of metabolic networks at the modular level. http://genome.gbf.de/bioinformatics/

An NN-Based SRD Decomposition Algorithm and Its Application in Nonlinear Compensation

PubMed Central

Yan, Honghang; Deng, Fang; Sun, Jian; Chen, Jie

2014-01-01

In this study, a neural network-based square root of descending (SRD) order decomposition algorithm for compensating for nonlinear data generated by sensors is presented. The study aims at exploring the optimized decomposition of data 1.00,0.00,0.00 and minimizing the computational complexity and memory space of the training process. A linear decomposition algorithm, which automatically finds the optimal decomposition of N subparts and reduces the training time to 1N and memory cost to 1N, has been implemented on nonlinear data obtained from an encoder. Particular focus is given to the theoretical access of estimating the numbers of hidden nodes and the precision of varying the decomposition method. Numerical experiments are designed to evaluate the effect of this algorithm. Moreover, a designed device for angular sensor calibration is presented. We conduct an experiment that samples the data of an encoder and compensates for the nonlinearity of the encoder to testify this novel algorithm. PMID:25232912

Acid and alkali effects on the decomposition of HMX molecule: a computational study.

PubMed

Zhang, Chaoyang; Li, Yuzhen; Xiong, Ying; Wang, Xiaolin; Zhou, Mingfei

2011-11-03

The stored and wasted explosives are usually in an acid or alkali environment, leading to the importance of exploring the acid and alkali effects on the decomposition mechanism of explosives. The acid and alkali effects on the decomposition of HMX molecule in gaseous state and in aqueous solution at 298 K are studied using quantum chemistry and molecular force field calculations. The results show that both H(+) and OH(-) make the decomposition in gaseous state energetically favorable. However, the effect of H(+) is much different from that of OH(-) in aqueous solution: OH(-) can accelerate the decomposition but H(+) cannot. The difference is mainly caused by the large aqueous solvation energy difference between H(+) and OH(-). The results confirm that the dissociation of HMX is energetically favored only in the base solutions, in good agreement with previous HMX base hydrolysis experimental observations. The different acid and alkali effects on the HMX decomposition are dominated by the large aqueous solvation energy difference between H(+) and OH(-).

A knowledge-based tool for multilevel decomposition of a complex design problem

NASA Technical Reports Server (NTRS)

Rogers, James L.

1989-01-01

Although much work has been done in applying artificial intelligence (AI) tools and techniques to problems in different engineering disciplines, only recently has the application of these tools begun to spread to the decomposition of complex design problems. A new tool based on AI techniques has been developed to implement a decomposition scheme suitable for multilevel optimization and display of data in an N x N matrix format.

Theoretical evidence of the observed kinetic order dependence on temperature during the N(2)O decomposition over Fe-ZSM-5.

PubMed

Guesmi, Hazar; Berthomieu, Dorothee; Bromley, Bryan; Coq, Bernard; Kiwi-Minsker, Lioubov

2010-03-28

The characterization of Fe/ZSM5 zeolite materials, the nature of Fe-sites active in N(2)O direct decomposition, as well as the rate limiting step are still a matter of debate. The mechanism of N(2)O decomposition on the binuclear oxo-hydroxo bridged extraframework iron core site [Fe(II)(mu-O)(mu-OH)Fe(II)](+) inside the ZSM-5 zeolite has been studied by combining theoretical and experimental approaches. The overall calculated path of N(2)O decomposition involves the oxidation of binuclear Fe(II) core sites by N(2)O (atomic alpha-oxygen formation) and the recombination of two surface alpha-oxygen atoms leading to the formation of molecular oxygen. Rate parameters computed using standard statistical mechanics and transition state theory reveal that elementary catalytic steps involved into N(2)O decomposition are strongly dependent on the temperature. This theoretical result was compared to the experimentally observed steady state kinetics of the N(2)O decomposition and temperature-programmed desorption (TPD) experiments. A switch of the reaction order with respect to N(2)O pressure from zero to one occurs at around 800 K suggesting a change of the rate determining step from the alpha-oxygen recombination to alpha-oxygen formation. The TPD results on the molecular oxygen desorption confirmed the mechanism proposed.

Influence of experimental parameters on iron oxide nanoparticle properties synthesized by thermal decomposition: size and nuclear magnetic resonance studies

NASA Astrophysics Data System (ADS)

Belaïd, Sarah; Stanicki, Dimitri; Vander Elst, Luce; Muller, Robert N.; Laurent, Sophie

2018-04-01

A study of the experimental conditions to synthesize monodisperse iron oxide nanocrystals prepared from the thermal decomposition of iron(III) acetylacetonate was carried out in the presence of surfactants and a reducing agent. The influence of temperature, synthesis time and surfactant amounts on nanoparticle properties is reported. This investigation combines relaxometric characterization and size properties. The relaxometric behavior of the nanomaterials depends on the selected experimental parameters. The synthesis of iron oxide nanoparticles with a high relaxivity and a high saturation magnetization can be obtained with a short reaction time at high temperature. Moreover, the influence of surfactant concentrations determines the optimal value in order to produce iron oxide nanoparticles with a narrow size distribution. The optimized synthesis is rapid, robust and reproductive, and produces nearly monodisperse magnetic nanocrystals.

Molecular structure, thermal behavior and adiabatic time-to-explosion of 3,3-dinitroazetidinium picrate

NASA Astrophysics Data System (ADS)

Ma, Haixia; Yan, Biao; Li, Junfeng; Ren, Yinghui; Chen, Yongshi; Zhao, Fengqi; Song, Jirong; Hu, Rongzu

2010-09-01

3,3-Dinitroazetidinium picrate (DNAZṡPA) was synthesized by adding 3,3-dinitroazetidine (DNAZ) to picric acid (PA) in methanol, the single crystals suitable for X-ray measurement were obtained by recrystallization at room temperature. The compound crystallises orthorhombic with space group P2 12 12 1 and crystal parameters of a = 0.7655(1) nm, b = 0.8962(2) nm, c = 2.0507(4) nm, V = 1.4069(5) nm 3, D c = 1.776 g cm -3, Z = 4, F(0 0 0) = 768 and μ = 0.166 mm -1. The thermal behavior of DNAZṡPA was studied under a non-isothermal condition by DSC and TG-DTG methods. The kinetic parameters of the first exothermic thermal decomposition process were obtained from analysis of the DSC and TG curves by Kissinger method, Ozawa method and the integral method. The specific heat capacity of DNAZṡPA was determined with a continuous C p mode of micro-calorimeter and the standard mole specific heat capacity was 436.56 J mol -1 K -1 at 298.15 K. Using the relationship of C p with T and the thermal decomposition parameters, the time of the thermal decomposition from initialization to thermal explosion (adiabatic time-to-explosion) was evaluated to be 40.7 s. The free radical signals of DNAZṡPA and 1,3,3-trinitroazetidine (TNAZ) were detected by electron spin resonance (ESR) technique to estimate its sensitivity.

Effect of Watermarking on Diagnostic Preservation of Atherosclerotic Ultrasound Video in Stroke Telemedicine.

PubMed

Dey, Nilanjan; Bose, Soumyo; Das, Achintya; Chaudhuri, Sheli Sinha; Saba, Luca; Shafique, Shoaib; Nicolaides, Andrew; Suri, Jasjit S

2016-04-01

Embedding of diagnostic and health care information requires secure encryption and watermarking. This research paper presents a comprehensive study for the behavior of some well established watermarking algorithms in frequency domain for the preservation of stroke-based diagnostic parameters. Two different sets of watermarking algorithms namely: two correlation-based (binary logo hiding) and two singular value decomposition (SVD)-based (gray logo hiding) watermarking algorithms are used for embedding ownership logo. The diagnostic parameters in atherosclerotic plaque ultrasound video are namely: (a) bulb identification and recognition which consists of identifying the bulb edge points in far and near carotid walls; (b) carotid bulb diameter; and (c) carotid lumen thickness all along the carotid artery. The tested data set consists of carotid atherosclerotic movies taken under IRB protocol from University of Indiana Hospital, USA-AtheroPoint™ (Roseville, CA, USA) joint pilot study. ROC (receiver operating characteristic) analysis was performed on the bulb detection process that showed an accuracy and sensitivity of 100 % each, respectively. The diagnostic preservation (DPsystem) for SVD-based approach was above 99 % with PSNR (Peak signal-to-noise ratio) above 41, ensuring the retention of diagnostic parameter devalorization as an effect of watermarking. Thus, the fully automated proposed system proved to be an efficient method for watermarking the atherosclerotic ultrasound video for stroke application.

Localized instabilities and spinodal decomposition in driven systems in the presence of elasticity

NASA Astrophysics Data System (ADS)

Meca, Esteban; Münch, Andreas; Wagner, Barbara

2018-01-01

We study numerically and analytically the instabilities associated with phase separation in a solid layer on which an external material flux is imposed. The first instability is localized within a boundary layer at the exposed free surface by a process akin to spinodal decomposition. In the limiting static case, when there is no material flux, the coherent spinodal decomposition is recovered. In the present problem, stability analysis of the time-dependent and nonuniform base states as well as numerical simulations of the full governing equations are used to establish the dependence of the wavelength and onset of the instability on parameter settings and its transient nature as the patterns eventually coarsen into a flat moving front. The second instability is related to the Mullins-Sekerka instability in the presence of elasticity and arises at the moving front between the two phases when the flux is reversed. Stability analyses of the full model and the corresponding sharp-interface model are carried out and compared. Our results demonstrate how interface and bulk instabilities can be analyzed within the same framework which allows us to identify and distinguish each of them clearly. The relevance for a detailed understanding of both instabilities and their interconnections in a realistic setting is demonstrated for a system of equations modeling the lithiation and delithiation processes within the context of lithium ion batteries.

Modelling the effect of soil moisture and organic matter degradation on biogenic NO emissions from soils in Sahel rangeland (Mali)

NASA Astrophysics Data System (ADS)

Delon, C.; Mougin, E.; Serça, D.; Grippa, M.; Hiernaux, P.; Diawara, M.; Galy-Lacaux, C.; Kergoat, L.

2014-08-01

This work is an attempt to provide seasonal variation of biogenic NO emission fluxes in a sahelian rangeland in Mali (Agoufou, 15.34° N, 1.48° W) for years 2004, 2005, 2006, 2007 and 2008. Indeed, NO is one of the most important precursor for tropospheric ozone, and the contribution of the Sahel region in emitting NO is no more considered as negligible. The link between NO production in the soil and NO release to the atmosphere is investigated in this study, by taking into account vegetation litter production and degradation, microbial processes in the soil, emission fluxes, and environmental variables influencing these processes, using a coupled vegetation-litter decomposition-emission model. This model includes the Sahelian-Transpiration-Evaporation-Productivity (STEP) model for the simulation of herbaceous, tree leaf and fecal masses, the GENDEC model (GENeral DEComposition) for the simulation of the buried litter decomposition, and the NO emission model for the simulation of the NO flux to the atmosphere. Physical parameters (soil moisture and temperature, wind speed, sand percentage) which affect substrate diffusion and oxygen supply in the soil and influence the microbial activity, and biogeochemical parameters (pH and fertilization rate related to N content) are necessary to simulate the NO flux. The reliability of the simulated parameters is checked, in order to assess the robustness of the simulated NO flux. Simulated yearly average of NO flux ranges from 0.69 to 1.09 kg(N) ha-1 yr-1, and wet season average ranges from 1.16 to 2.08 kg(N) ha-1 yr-1. These results are in the same order as previous measurements made in several sites where the vegetation and the soil are comparable to the ones in Agoufou. This coupled vegetation-litter decomposition-emission model could be generalized at the scale of the Sahel region, and provide information where little data is available.

Modelling the effect of soil moisture and organic matter degradation on biogenic NO emissions from soils in Sahel rangeland (Mali)

NASA Astrophysics Data System (ADS)

Delon, C.; Mougin, E.; Serça, D.; Grippa, M.; Hiernaux, P.; Diawara, M.; Galy-Lacaux, C.; Kergoat, L.

2015-01-01

This work is an attempt to provide seasonal variation of biogenic NO emission fluxes in a sahelian rangeland in Mali (Agoufou, 15.34° N, 1.48° W) for years 2004-2008. Indeed, NO is one of the most important precursor for tropospheric ozone, and the contribution of the Sahel region in emitting NO is no more considered as negligible. The link between NO production in the soil and NO release to the atmosphere is investigated in this study, by taking into account vegetation litter production and degradation, microbial processes in the soil, emission fluxes, and environmental variables influencing these processes, using a coupled vegetation-litter decomposition-emission model. This model includes the Sahelian-Transpiration-Evaporation-Productivity (STEP) model for the simulation of herbaceous, tree leaf and fecal masses, the GENDEC model (GENeral DEComposition) for the simulation of the buried litter decomposition and microbial dynamics, and the NO emission model (NOFlux) for the simulation of the NO release to the atmosphere. Physical parameters (soil moisture and temperature, wind speed, sand percentage) which affect substrate diffusion and oxygen supply in the soil and influence the microbial activity, and biogeochemical parameters (pH and fertilization rate related to N content) are necessary to simulate the NO flux. The reliability of the simulated parameters is checked, in order to assess the robustness of the simulated NO flux. Simulated yearly average of NO flux ranges from 0.66 to 0.96 kg(N) ha-1 yr-1, and wet season average ranges from 1.06 to 1.73 kg(N) ha-1 yr-1. These results are in the same order as previous measurements made in several sites where the vegetation and the soil are comparable to the ones in Agoufou. This coupled vegetation-litter decomposition-emission model could be generalized at the scale of the Sahel region, and provide information where little data is available.

An ammonia-stabilized mixed-cation borohydride: synthesis, structure and thermal decomposition behavior.

PubMed

Yang, Yanjing; Liu, Yongfeng; Wu, Hui; Zhou, Wei; Gao, Mingxia; Pan, Hongge

2014-01-07

We demonstrate the synthesis, crystal structure and thermal decomposition behavior of a novel ammonia-stabilized mixed-cation borohydride where the NH3 groups enable the coexistence of Li and Mg cations as an "assistant". Li2Mg(BH4)4·6NH3, which is comprised of orderly arranged Mg[NH3]6(2+) ammine complexes and Li2[BH4]4(2-) complex anions, was synthesized by the mechanochemical reaction between Mg(BH4)2·6NH3 and LiBH4. This novel compound crystallizes in a tetragonal P4(3)2(1)2 (No. 96) structure with lattice parameters a = b = 10.7656(8) Å and c = 13.843(1) Å with very short dihydrogen bonds, which determine a very low onset temperature of 80 °C for hydrogen release and are also responsible for the nucleation of Li2Mg(BH4)4·3NH3 as a decomposition intermediate. Mechanistic investigations on the thermal decomposition showed that the H(δ+)-H(δ-) combination in the ammonia-stabilized mixed-cation borohydride was significantly enhanced due to the strengthened Mg-N bonds. Upon heating, 11.02 moles of H2 (equivalent to 11.1 wt%) and 3.07 moles of NH3 are evolved from one mole of Li2Mg(BH4)4·6NH3 with a three-step reaction. The insights into the formation mechanism of ammonia-stabilized mixed-cation borohydride and the role played by NH3 group are very useful as a guideline for the design and synthesis of novel B-N-based materials with high hydrogen content.

A novel hybrid decomposition-and-ensemble model based on CEEMD and GWO for short-term PM2.5 concentration forecasting

NASA Astrophysics Data System (ADS)

Niu, Mingfei; Wang, Yufang; Sun, Shaolong; Li, Yongwu

2016-06-01

To enhance prediction reliability and accuracy, a hybrid model based on the promising principle of "decomposition and ensemble" and a recently proposed meta-heuristic called grey wolf optimizer (GWO) is introduced for daily PM2.5 concentration forecasting. Compared with existing PM2.5 forecasting methods, this proposed model has improved the prediction accuracy and hit rates of directional prediction. The proposed model involves three main steps, i.e., decomposing the original PM2.5 series into several intrinsic mode functions (IMFs) via complementary ensemble empirical mode decomposition (CEEMD) for simplifying the complex data; individually predicting each IMF with support vector regression (SVR) optimized by GWO; integrating all predicted IMFs for the ensemble result as the final prediction by another SVR optimized by GWO. Seven benchmark models, including single artificial intelligence (AI) models, other decomposition-ensemble models with different decomposition methods and models with the same decomposition-ensemble method but optimized by different algorithms, are considered to verify the superiority of the proposed hybrid model. The empirical study indicates that the proposed hybrid decomposition-ensemble model is remarkably superior to all considered benchmark models for its higher prediction accuracy and hit rates of directional prediction.

Enhanced Thermal Decomposition Properties of CL-20 through Space-Confining in Three-Dimensional Hierarchically Ordered Porous Carbon.

PubMed

Chen, Jin; He, Simin; Huang, Bing; Wu, Peng; Qiao, Zhiqiang; Wang, Jun; Zhang, Liyuan; Yang, Guangcheng; Huang, Hui

2017-03-29

High energy and low signature properties are the future trend of solid propellant development. As a new and promising oxidizer, hexanitrohexaazaisowurtzitane (CL-20) is expected to replace the conventional oxidizer ammonium perchlorate to reach above goals. However, the high pressure exponent of CL-20 hinders its application in solid propellants so that the development of effective catalysts to improve the thermal decomposition properties of CL-20 still remains challenging. Here, 3D hierarchically ordered porous carbon (3D HOPC) is presented as a catalyst for the thermal decomposition of CL-20 via synthesizing a series of nanostructured CL-20/HOPC composites. In these nanocomposites, CL-20 is homogeneously space-confined into the 3D HOPC scaffold as nanocrystals 9.2-26.5 nm in diameter. The effect of the pore textural parameters and surface modification of 3D HOPC as well as CL-20 loading amount on the thermal decomposition of CL-20 is discussed. A significant improvement of the thermal decomposition properties of CL-20 is achieved with remarkable decrease in decomposition peak temperature (from 247.0 to 174.8 °C) and activation energy (from 165.5 to 115.3 kJ/mol). The exceptional performance of 3D HOPC could be attributed to its well-connected 3D hierarchically ordered porous structure, high surface area, and the confined CL-20 nanocrystals. This work clearly demonstrates that 3D HOPC is a superior catalyst for CL-20 thermal decomposition and opens new potential for further applications of CL-20 in solid propellants.

Development of rate expressions for the thermal decomposition of RDX

DOE Office of Scientific and Technical Information (OSTI.GOV)

Erickson, K.L.; Behrens, R. Jr.; Bulusu, S.

Decomposition and combustion of energetic materials involve processes in both condensed and gas phases. Development of reliable models for design, performance, stability, and hazard analyses requires detailed understanding of the mechanisms for both the initial condensed phase decomposition of the energetic material and the subsequent reaction of the decomposition species to form the ultimate reaction products. Those mechanisms must be described in terms of constitutive rate expressions that can be incorporated into mathematical models. The thermal decomposition of RDX has been studied by Behrens and Bulusu using Simultaneous Thermogravimetric Modulated Beam Mass Spectrometry (STMBMS). Their work provides a basis formore » developing some of the constitutive rate expressions that are needed in models for design, performance, stability and hazard analyses involving RDX. Behrens and Bulusu have identified four primary reaction pathways that control the liquid-phase decomposition of RDX at temperatures between 200 and 215{degrees}C, and one that controls solid-phase decomposition at temperatures below 200{degrees}C. Two of the liquid-phase pathways appear to be first order in RDX. Arrhenius parameters for the first-order rate constants were evaluated from data reported by Behrens and Bulusu. Reaction rates extrapolated to temperatures between 370 and 450{degrees}C are in good agreement with global reaction rates observed by Trott et al. using high-speed photography and laser-heated thin-film samples. Furthermore, the STMBMS results of Behrens and Bulusu appear to be consistent with condensed-phase infrared results reported by Trott et al. and Erickson et al.« less

Development of rate expressions for the thermal decomposition of RDX

DOE Office of Scientific and Technical Information (OSTI.GOV)

Erickson, K.L.; Behrens, R. Jr.; Bulusu, S.

Decomposition and combustion of energetic materials involve processes in both condensed and gas phases. Development of reliable models for design, performance, stability, and hazard analyses requires detailed understanding of the mechanisms for both the initial condensed phase decomposition of the energetic material and the subsequent reaction of the decomposition species to form the ultimate reaction products. Those mechanisms must be described in terms of constitutive rate expressions that can be incorporated into mathematical models. The thermal decomposition of RDX has been studied by Behrens and Bulusu using Simultaneous Thermogravimetric Modulated Beam Mass Spectrometry (STMBMS). Their work provides a basis formore » developing some of the constitutive rate expressions that are needed in models for design, performance, stability and hazard analyses involving RDX. Behrens and Bulusu have identified four primary reaction pathways that control the liquid-phase decomposition of RDX at temperatures between 200 and 215[degrees]C, and one that controls solid-phase decomposition at temperatures below 200[degrees]C. Two of the liquid-phase pathways appear to be first order in RDX. Arrhenius parameters for the first-order rate constants were evaluated from data reported by Behrens and Bulusu. Reaction rates extrapolated to temperatures between 370 and 450[degrees]C are in good agreement with global reaction rates observed by Trott et al. using high-speed photography and laser-heated thin-film samples. Furthermore, the STMBMS results of Behrens and Bulusu appear to be consistent with condensed-phase infrared results reported by Trott et al. and Erickson et al.« less

Early stage litter decomposition across biomes

Treesearch

Ika Djukic; Sebastian Kepfer-Rojas; Inger Kappel Schmidt; Klaus Steenberg Larsen; Claus Beier; Björn Berg; Kris Verheyen; Adriano Caliman; Alain Paquette; Alba Gutiérrez-Girón; Alberto Humber; Alejandro Valdecantos; Alessandro Petraglia; Heather Alexander; Algirdas Augustaitis; Amélie Saillard; Ana Carolina Ruiz Fernández; Ana I. Sousa; Ana I. Lillebø; Anderson da Rocha Gripp; André-Jean Francez; Andrea Fischer; Andreas Bohner; Andrey Malyshev; Andrijana Andrić; Andy Smith; Angela Stanisci; Anikó Seres; Anja Schmidt; Anna Avila; Anne Probst; Annie Ouin; Anzar A. Khuroo; Arne Verstraeten; Arely N. Palabral-Aguilera; Artur Stefanski; Aurora Gaxiola; Bart Muys; Bernard Bosman; Bernd Ahrends; Bill Parker; Birgit Sattler; Bo Yang; Bohdan Juráni; Brigitta Erschbamer; Carmen Eugenia Rodriguez Ortiz; Casper T. Christiansen; E. Carol Adair; Céline Meredieu; Cendrine Mony; Charles A. Nock; Chi-Ling Chen; Chiao-Ping Wang; Christel Baum; Christian Rixen; Christine Delire; Christophe Piscart; Christopher Andrews; Corinna Rebmann; Cristina Branquinho; Dana Polyanskaya; David Fuentes Delgado; Dirk Wundram; Diyaa Radeideh; Eduardo Ordóñez-Regil; Edward Crawford; Elena Preda; Elena Tropina; Elli Groner; Eric Lucot; Erzsébet Hornung; Esperança Gacia; Esther Lévesque; Evanilde Benedito; Evgeny A. Davydov; Evy Ampoorter; Fabio Padilha Bolzan; Felipe Varela; Ferdinand Kristöfel; Fernando T. Maestre; Florence Maunoury-Danger; Florian Hofhansl; Florian Kitz; Flurin Sutter; Francisco Cuesta; Francisco de Almeida Lobo; Franco Leandro de Souza; Frank Berninger; Franz Zehetner; Georg Wohlfahrt; George Vourlitis; Geovana Carreño-Rocabado; Gina Arena; Gisele Daiane Pinha; Grizelle González; Guylaine Canut; Hanna Lee; Hans Verbeeck; Harald Auge; Harald Pauli; Hassan Bismarck Nacro; Héctor A. Bahamonde; Heike Feldhaar; Heinke Jäger; Helena C. Serrano; Hélène Verheyden; Helge Bruelheide; Henning Meesenburg; Hermann Jungkunst; Hervé Jactel; Hideaki Shibata; Hiroko Kurokawa; Hugo López Rosas; Hugo L. Rojas Villalobos; Ian Yesilonis; Inara Melece; Inge Van Halder; Inmaculada García Quirós; Isaac Makelele; Issaka Senou; István Fekete; Ivan Mihal; Ivika Ostonen; Jana Borovská; Javier Roales; Jawad Shoqeir; Jean-Christophe Lata; Jean-Paul Theurillat; Jean-Luc Probst; Jess Zimmerman; Jeyanny Vijayanathan; Jianwu Tang; Jill Thompson; Jiří Doležal; Joan-Albert Sanchez-Cabeza; Joël Merlet; Joh Henschel; Johan Neirynck; Johannes Knops; John Loehr; Jonathan von Oppen; Jónína Sigríður Þorláksdóttir; Jörg Löffler; José-Gilberto Cardoso-Mohedano; José-Luis Benito-Alonso; Jose Marcelo Torezan; Joseph C. Morina; Juan J. Jiménez; Juan Dario Quinde; Juha Alatalo; Julia Seeber; Jutta Stadler; Kaie Kriiska; Kalifa Coulibaly; Karibu Fukuzawa; Katalin Szlavecz; Katarína Gerhátová; Kate Lajtha; Kathrin Käppeler; Katie A. Jennings; Katja Tielbörger; Kazuhiko Hoshizaki; Ken Green; Lambiénou Yé; Laryssa Helena Ribeiro Pazianoto; Laura Dienstbach; Laura Williams; Laura Yahdjian; Laurel M. Brigham; Liesbeth van den Brink; Lindsey Rustad; al. et

2018-01-01

Through litter decomposition enormous amounts of carbon is emitted to the atmosphere. Numerous large-scale decomposition experiments have been conducted focusing on this fundamental soil process in order to understand the controls on the terrestrial carbon transfer to the atmosphere. However, previous studies were mostly based on site-specific litter and methodologies...

Thermal decomposition of high-nitrogen energetic compounds: TAGzT and GUzT

NASA Astrophysics Data System (ADS)

Hayden, Heather F.

The U.S. Navy is exploring high-nitrogen compounds as burning-rate additives to meet the growing demands of future high-performance gun systems. Two high-nitrogen compounds investigated as potential burning-rate additives are bis(triaminoguanidinium) 5,5-azobitetrazolate (TAGzT) and bis(guanidinium) 5,5'-azobitetrazolate (GUzT). Small-scale tests showed that formulations containing TAGzT exhibit significant increases in the burning rates of RDX-based gun propellants. However, when GUzT, a similarly structured molecule was incorporated into the formulation, there was essentially no effect on the burning rate of the propellant. Through the use of simultaneous thermogravimetric modulated beam mass spectrometry (STMBMS) and Fourier-Transform ion cyclotron resonance (FTICR) mass spectrometry methods, an investigation of the underlying chemical and physical processes that control the thermal decomposition behavior of TAGzT and GUzT alone and in the presence of RDX, was conducted. The objective was to determine why GUzT is not as good a burning-rate enhancer in RDX-based gun propellants as compared to TAGzT. The results show that TAGzT is an effective burning-rate modifier in the presence of RDX because the decomposition of TAGzT alters the initial stages of the decomposition of RDX. Hydrazine, formed in the decomposition of TAGzT, reacts faster with RDX than RDX can decompose itself. The reactions occur at temperatures below the melting point of RDX and thus the TAGzT decomposition products react with RDX in the gas phase. Although there is no hydrazine formed in the decomposition of GUzT, amines formed in the decomposition of GUzT react with aldehydes, formed in the decomposition of RDX, resulting in an increased reaction rate of RDX in the presence of GUzT. However, GUzT is not an effective burning-rate modifier because its decomposition does not alter the initial gas-phase decomposition of RDX. The decomposition of GUzT occurs at temperatures above the melting point of RDX. Therefore, the decomposition of GUzT affects reactions that are dominant in the liquid phase of RDX. Although GUzT is not an effective burning-rate modifier, features of its decomposition where the reaction between amines formed in the decomposition of GUzT react with the aldehydes, formed in the decomposition of RDX, may have implications from an insensitive-munitions perspective.

Near-lossless multichannel EEG compression based on matrix and tensor decompositions.

PubMed

Dauwels, Justin; Srinivasan, K; Reddy, M Ramasubba; Cichocki, Andrzej

2013-05-01

A novel near-lossless compression algorithm for multichannel electroencephalogram (MC-EEG) is proposed based on matrix/tensor decomposition models. MC-EEG is represented in suitable multiway (multidimensional) forms to efficiently exploit temporal and spatial correlations simultaneously. Several matrix/tensor decomposition models are analyzed in view of efficient decorrelation of the multiway forms of MC-EEG. A compression algorithm is built based on the principle of “lossy plus residual coding,” consisting of a matrix/tensor decomposition-based coder in the lossy layer followed by arithmetic coding in the residual layer. This approach guarantees a specifiable maximum absolute error between original and reconstructed signals. The compression algorithm is applied to three different scalp EEG datasets and an intracranial EEG dataset, each with different sampling rate and resolution. The proposed algorithm achieves attractive compression ratios compared to compressing individual channels separately. For similar compression ratios, the proposed algorithm achieves nearly fivefold lower average error compared to a similar wavelet-based volumetric MC-EEG compression algorithm.

Vortex breakdown simulation - A circumspect study of the steady, laminar, axisymmetric model

NASA Technical Reports Server (NTRS)

Salas, M. D.; Kuruvila, G.

1989-01-01

The incompressible axisymmetric steady Navier-Stokes equations are written using the streamfunction-vorticity formulation. The resulting equations are discretized using a second-order central-difference scheme. The discretized equations are linearized and then solved using an exact LU decomposition, Gaussian elimination, and Newton iteration. Solutions are presented for Reynolds numbers (based on vortex core radius) 100-1800 and swirl parameter 0.9-1.1. The effects of inflow boundary conditions, the location of farfield and outflow boundaries, and mesh refinement are examined. Finally, the stability of the steady solutions is investigated by solving the time-dependent equations.

The pitch of vibrato tones: a model based on instantaneous frequency decomposition.

PubMed

Mesz, Bruno A; Eguia, Manuel C

2009-07-01

We study vibrato as the more ubiquitous manifestation of a nonstationary tone that can evoke a single overall pitch. Some recent results using nonsymmetrical vibrato tones suggest that the perceived pitch could be governed by some stability-sensitive mechanism. For nonstationary sounds the adequate tools are time-frequency representations (TFRs). We show that a recently proposed TFR could be the simplest framework to explain this hypothetical stability-sensitive mechanism. We propose a one-parameter model within this framework that is able to predict previously reported results and we present new results obtained from psychophysical experiments performed in our laboratory.

Highly Scalable Matching Pursuit Signal Decomposition Algorithm

NASA Technical Reports Server (NTRS)

Christensen, Daniel; Das, Santanu; Srivastava, Ashok N.

2009-01-01

Matching Pursuit Decomposition (MPD) is a powerful iterative algorithm for signal decomposition and feature extraction. MPD decomposes any signal into linear combinations of its dictionary elements or atoms . A best fit atom from an arbitrarily defined dictionary is determined through cross-correlation. The selected atom is subtracted from the signal and this procedure is repeated on the residual in the subsequent iterations until a stopping criterion is met. The reconstructed signal reveals the waveform structure of the original signal. However, a sufficiently large dictionary is required for an accurate reconstruction; this in return increases the computational burden of the algorithm, thus limiting its applicability and level of adoption. The purpose of this research is to improve the scalability and performance of the classical MPD algorithm. Correlation thresholds were defined to prune insignificant atoms from the dictionary. The Coarse-Fine Grids and Multiple Atom Extraction techniques were proposed to decrease the computational burden of the algorithm. The Coarse-Fine Grids method enabled the approximation and refinement of the parameters for the best fit atom. The ability to extract multiple atoms within a single iteration enhanced the effectiveness and efficiency of each iteration. These improvements were implemented to produce an improved Matching Pursuit Decomposition algorithm entitled MPD++. Disparate signal decomposition applications may require a particular emphasis of accuracy or computational efficiency. The prominence of the key signal features required for the proper signal classification dictates the level of accuracy necessary in the decomposition. The MPD++ algorithm may be easily adapted to accommodate the imposed requirements. Certain feature extraction applications may require rapid signal decomposition. The full potential of MPD++ may be utilized to produce incredible performance gains while extracting only slightly less energy than the standard algorithm. When the utmost accuracy must be achieved, the modified algorithm extracts atoms more conservatively but still exhibits computational gains over classical MPD. The MPD++ algorithm was demonstrated using an over-complete dictionary on real life data. Computational times were reduced by factors of 1.9 and 44 for the emphases of accuracy and performance, respectively. The modified algorithm extracted similar amounts of energy compared to classical MPD. The degree of the improvement in computational time depends on the complexity of the data, the initialization parameters, and the breadth of the dictionary. The results of the research confirm that the three modifications successfully improved the scalability and computational efficiency of the MPD algorithm. Correlation Thresholding decreased the time complexity by reducing the dictionary size. Multiple Atom Extraction also reduced the time complexity by decreasing the number of iterations required for a stopping criterion to be reached. The Course-Fine Grids technique enabled complicated atoms with numerous variable parameters to be effectively represented in the dictionary. Due to the nature of the three proposed modifications, they are capable of being stacked and have cumulative effects on the reduction of the time complexity.

Multi-Centrality Graph Spectral Decompositions and Their Application to Cyber Intrusion Detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Pin-Yu; Choudhury, Sutanay; Hero, Alfred

Many modern datasets can be represented as graphs and hence spectral decompositions such as graph principal component analysis (PCA) can be useful. Distinct from previous graph decomposition approaches based on subspace projection of a single topological feature, e.g., the centered graph adjacency matrix (graph Laplacian), we propose spectral decomposition approaches to graph PCA and graph dictionary learning that integrate multiple features, including graph walk statistics, centrality measures and graph distances to reference nodes. In this paper we propose a new PCA method for single graph analysis, called multi-centrality graph PCA (MC-GPCA), and a new dictionary learning method for ensembles ofmore » graphs, called multi-centrality graph dictionary learning (MC-GDL), both based on spectral decomposition of multi-centrality matrices. As an application to cyber intrusion detection, MC-GPCA can be an effective indicator of anomalous connectivity pattern and MC-GDL can provide discriminative basis for attack classification.« less

Domain Decomposition By the Advancing-Partition Method for Parallel Unstructured Grid Generation

NASA Technical Reports Server (NTRS)

Pirzadeh, Shahyar Z.; Zagaris, George

2009-01-01

A new method of domain decomposition has been developed for generating unstructured grids in subdomains either sequentially or using multiple computers in parallel. Domain decomposition is a crucial and challenging step for parallel grid generation. Prior methods are generally based on auxiliary, complex, and computationally intensive operations for defining partition interfaces and usually produce grids of lower quality than those generated in single domains. The new technique, referred to as "Advancing Partition," is based on the Advancing-Front method, which partitions a domain as part of the volume mesh generation in a consistent and "natural" way. The benefits of this approach are: 1) the process of domain decomposition is highly automated, 2) partitioning of domain does not compromise the quality of the generated grids, and 3) the computational overhead for domain decomposition is minimal. The new method has been implemented in NASA's unstructured grid generation code VGRID.

Domain Decomposition By the Advancing-Partition Method

NASA Technical Reports Server (NTRS)

Pirzadeh, Shahyar Z.

2008-01-01

A new method of domain decomposition has been developed for generating unstructured grids in subdomains either sequentially or using multiple computers in parallel. Domain decomposition is a crucial and challenging step for parallel grid generation. Prior methods are generally based on auxiliary, complex, and computationally intensive operations for defining partition interfaces and usually produce grids of lower quality than those generated in single domains. The new technique, referred to as "Advancing Partition," is based on the Advancing-Front method, which partitions a domain as part of the volume mesh generation in a consistent and "natural" way. The benefits of this approach are: 1) the process of domain decomposition is highly automated, 2) partitioning of domain does not compromise the quality of the generated grids, and 3) the computational overhead for domain decomposition is minimal. The new method has been implemented in NASA's unstructured grid generation code VGRID.

Effects of magnesium-based hydrogen storage materials on the thermal decomposition, burning rate, and explosive heat of ammonium perchlorate-based composite solid propellant.

PubMed

Liu, Leili; Li, Jie; Zhang, Lingyao; Tian, Siyu

2018-01-15

MgH 2 , Mg 2 NiH 4 , and Mg 2 CuH 3 were prepared, and their structure and hydrogen storage properties were determined through X-ray photoelectron spectroscopy and thermal analyzer. The effects of MgH 2 , Mg 2 NiH 4 , and Mg 2 CuH 3 on the thermal decomposition, burning rate, and explosive heat of ammonium perchlorate-based composite solid propellant were subsequently studied. Results indicated that MgH 2 , Mg 2 NiH 4 , and Mg 2 CuH 3 can decrease the thermal decomposition peak temperature and increase the total released heat of decomposition. These compounds can improve the effect of thermal decomposition of the propellant. The burning rates of the propellant increased using Mg-based hydrogen storage materials as promoter. The burning rates of the propellant also increased using MgH 2 instead of Al in the propellant, but its explosive heat was not enlarged. Nonetheless, the combustion heat of MgH 2 was higher than that of Al. A possible mechanism was thus proposed. Copyright © 2017. Published by Elsevier B.V.

A high-resolution analytical scanning transmission electron microscopy study of the early stages of spinodal decomposition in binary Fe–Cr

DOE Office of Scientific and Technical Information (OSTI.GOV)

Westraadt, J.E., E-mail: johan.westraadt@nmmu.ac.za; Olivier, E.J.; Neethling, J.H.

2015-11-15

Spinodal decomposition (SD) is an important phenomenon in materials science and engineering. For example, it is considered to be responsible for the 475 °C embrittlement of stainless steels comprising the bcc (ferrite) or bct (martensite) phases. Structural characterization of the evolving minute nano-scale concentration fluctuations during SD in the Fe–Cr system is, however, a notable challenge, and has mainly been considered accessible via atom probe tomography (APT) and small-angle neutron scattering. The standard tool for nanostructure characterization, viz. transmission electron microscopy (TEM), has only been successfully applied to late stages of SD when embrittlement is already severe. However, we heremore » demonstrate that the structural evolution in the early stages of SD in binary Fe–Cr, and alloys based on the binary, are accessible via analytical scanning TEM. An Fe–36 wt% Cr alloy aged at 500 °C for 1, 10 and 100 h is investigated using an aberration-corrected microscope and it is found that highly coherent and interconnected Cr-rich regions develop. The wavelength of decomposition is rather insensitive to the sample thickness and it is quantified to 2, 3 and 6 nm after ageing for 1, 10 and 100 h, which is in reasonable agreement with prior APT analysis. The concentration amplitude is more sensitive to the sample thickness and acquisition parameters but the TEM analysis is in good agreement with APT analysis for the longest ageing time. These findings open up for combinatorial TEM studies where both local crystallography and chemistry is required. - Highlights: • STEM-EELS analysis was successfully applied to resolve early stage SD in Fe–Cr. • Compositional wavelength measured with STEM-EELS compares well to previous ATP studies. • Compositional amplitude measured with STEM-EELS is a function of experimental parameters. • STEM-EELS allows for combinatorial studies of SD using complementary techniques.« less

14CO2 in combination with root-exclusion can be used to estimate plant-induced decomposition of soil organic matter

NASA Astrophysics Data System (ADS)

Heinonsalo, Jussi; Kulmala, Liisa; Mäkelä, Annikki; Oinonen, Markku; Fontaine, Sebastien; Palonen, Vesa; Pumpanen, Jukka

2017-04-01

In ecosystem models, the decomposition of soil organic matter (SOM) is estimated using temperature and moisture as main controlling parameters. However, there is increasing evidence that the decomposition is significantly affected by easily available carbohydrates. The C assimilation by the boreal forest trees will increase in the future due to climate change. As trees allocate large part of assimilated C to roots and soil microorganisms, particularly to ectomycorrhizal fungi, the rhizosphere priming effect (RPE) is assumed to increase. The aim of the experiment was to identify and quantify RPE in the field conditions. We established a three-year long trenching experiment in a boreal Scots pine forest where the belowground C flow from standing pine forest was controlled using root-exclusion with mesh fabrics. The mesh size of 1 μm excluded both tree roots and fungal hyphae and served as priming controls with decreased C supply. The unaltered C input entered the non-trenched field plots. Soil CO2 flux and 14C concentrations were measured. We were able to quantify the RPE in field conditions and show that plant-derived C flow into the soil increases SOM decomposition. Quantification of RPE allows more detailed estimation of soil organic matter decomposition in future changing climate.

Temperature sensitivity and enzymatic mechanisms of soil organic matter decomposition along an altitudinal gradient on Mount Kilimanjaro

NASA Astrophysics Data System (ADS)

Blagodatskaya, Evgenia; Blagodatsky, Sergey; Khomyakov, Nikita; Myachina, Olga; Kuzyakov, Yakov

2016-02-01

Short-term acceleration of soil organic matter decomposition by increasing temperature conflicts with the thermal adaptation observed in long-term studies. Here we used the altitudinal gradient on Mt. Kilimanjaro to demonstrate the mechanisms of thermal adaptation of extra- and intracellular enzymes that hydrolyze cellulose, chitin and phytate and oxidize monomers (14C-glucose) in warm- and cold-climate soils. We revealed that no response of decomposition rate to temperature occurs because of a cancelling effect consisting in an increase in half-saturation constants (Km), which counteracts the increase in maximal reaction rates (Vmax with temperature). We used the parameters of enzyme kinetics to predict thresholds of substrate concentration (Scrit) below which decomposition rates will be insensitive to global warming. Increasing values of Scrit, and hence stronger canceling effects with increasing altitude on Mt. Kilimanjaro, explained the thermal adaptation of polymer decomposition. The reduction of the temperature sensitivity of Vmax along the altitudinal gradient contributed to thermal adaptation of both polymer and monomer degradation. Extrapolating the altitudinal gradient to the large-scale latitudinal gradient, these results show that the soils of cold climates with stronger and more frequent temperature variation are less sensitive to global warming than soils adapted to high temperatures.

Thermal decomposition of europium sulfates Eu2(SO4)3·8H2O and EuSO4

NASA Astrophysics Data System (ADS)

Denisenko, Yu. G.; Khritokhin, N. A.; Andreev, O. V.; Basova, S. A.; Sal'nikova, E. I.; Polkovnikov, A. A.

2017-11-01

Reactions of europium sulfates Eu2(SO4)3·8H2O and EuSO4 complete decomposition were studied by Simultaneous Thermal Analysis. It was revealed that one-step dehydratation of Eu2(SO4)3·8H2O crystallohydrate is accompanied by the formation of amorphous anhydrous europium sulfate Eu2(SO4)3. Crystallization of amorphous europium (III) sulfate occurs at 381.1 °C (in argon) and 391.3 °C (in air). The average enthalpy values for dehydratation reaction of Eu2(SO4)3·8H2O (ΔH° = 141.1 kJ/mol), decomposition reactions of Eu2(SO4)3 (ΔH = 463.1 kJ/mol), Eu2O2SO4 (ΔH = 378.4 kJ/mol) and EuSO4 (ΔH = 124.1 kJ/mol) were determined. The step process mechanisms of thermal decomposition of europium (III) sulfate in air and europium (II) sulfate in inert atmosphere were established and justified. The kinetic parameters of complete thermal decomposition of europium (III) sulfate octahydrate were calculated by Kissinger model. The standard enthalpies of compound formation were calculated using thermal effects and formation enthalpy data for binary compounds.

An optimization approach for fitting canonical tensor decompositions.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dunlavy, Daniel M.; Acar, Evrim; Kolda, Tamara Gibson

Tensor decompositions are higher-order analogues of matrix decompositions and have proven to be powerful tools for data analysis. In particular, we are interested in the canonical tensor decomposition, otherwise known as the CANDECOMP/PARAFAC decomposition (CPD), which expresses a tensor as the sum of component rank-one tensors and is used in a multitude of applications such as chemometrics, signal processing, neuroscience, and web analysis. The task of computing the CPD, however, can be difficult. The typical approach is based on alternating least squares (ALS) optimization, which can be remarkably fast but is not very accurate. Previously, nonlinear least squares (NLS) methodsmore » have also been recommended; existing NLS methods are accurate but slow. In this paper, we propose the use of gradient-based optimization methods. We discuss the mathematical calculation of the derivatives and further show that they can be computed efficiently, at the same cost as one iteration of ALS. Computational experiments demonstrate that the gradient-based optimization methods are much more accurate than ALS and orders of magnitude faster than NLS.« less

Spider foraging strategy affects trophic cascades under natural and drought conditions.

PubMed

Liu, Shengjie; Chen, Jin; Gan, Wenjin; Schaefer, Douglas; Gan, Jianmin; Yang, Xiaodong

2015-07-23

Spiders can cause trophic cascades affecting litter decomposition rates. However, it remains unclear how spiders with different foraging strategies influence faunal communities, or present cascading effects on decomposition. Furthermore, increased dry periods predicted in future climates will likely have important consequences for trophic interactions in detritus-based food webs. We investigated independent and interactive effects of spider predation and drought on litter decomposition in a tropical forest floor. We manipulated densities of dominant spiders with actively hunting or sit-and-wait foraging strategies in microcosms which mimicked the tropical-forest floor. We found a positive trophic cascade on litter decomposition was triggered by actively hunting spiders under ambient rainfall, but sit-and-wait spiders did not cause this. The drought treatment reversed the effect of actively hunting spiders on litter decomposition. Under drought conditions, we observed negative trophic cascade effects on litter decomposition in all three spider treatments. Thus, reduced rainfall can alter predator-induced indirect effects on lower trophic levels and ecosystem processes, and is an example of how such changes may alter trophic cascades in detritus-based webs of tropical forests.

Spider foraging strategy affects trophic cascades under natural and drought conditions

PubMed Central

Liu, Shengjie; Chen, Jin; Gan, Wenjin; Schaefer, Douglas; Gan, Jianmin; Yang, Xiaodong

2015-01-01

Spiders can cause trophic cascades affecting litter decomposition rates. However, it remains unclear how spiders with different foraging strategies influence faunal communities, or present cascading effects on decomposition. Furthermore, increased dry periods predicted in future climates will likely have important consequences for trophic interactions in detritus-based food webs. We investigated independent and interactive effects of spider predation and drought on litter decomposition in a tropical forest floor. We manipulated densities of dominant spiders with actively hunting or sit-and-wait foraging strategies in microcosms which mimicked the tropical-forest floor. We found a positive trophic cascade on litter decomposition was triggered by actively hunting spiders under ambient rainfall, but sit-and-wait spiders did not cause this. The drought treatment reversed the effect of actively hunting spiders on litter decomposition. Under drought conditions, we observed negative trophic cascade effects on litter decomposition in all three spider treatments. Thus, reduced rainfall can alter predator-induced indirect effects on lower trophic levels and ecosystem processes, and is an example of how such changes may alter trophic cascades in detritus-based webs of tropical forests. PMID:26202370

Corrected confidence bands for functional data using principal components.

PubMed

Goldsmith, J; Greven, S; Crainiceanu, C

2013-03-01

Functional principal components (FPC) analysis is widely used to decompose and express functional observations. Curve estimates implicitly condition on basis functions and other quantities derived from FPC decompositions; however these objects are unknown in practice. In this article, we propose a method for obtaining correct curve estimates by accounting for uncertainty in FPC decompositions. Additionally, pointwise and simultaneous confidence intervals that account for both model- and decomposition-based variability are constructed. Standard mixed model representations of functional expansions are used to construct curve estimates and variances conditional on a specific decomposition. Iterated expectation and variance formulas combine model-based conditional estimates across the distribution of decompositions. A bootstrap procedure is implemented to understand the uncertainty in principal component decomposition quantities. Our method compares favorably to competing approaches in simulation studies that include both densely and sparsely observed functions. We apply our method to sparse observations of CD4 cell counts and to dense white-matter tract profiles. Code for the analyses and simulations is publicly available, and our method is implemented in the R package refund on CRAN. Copyright © 2013, The International Biometric Society.

Corrected Confidence Bands for Functional Data Using Principal Components

PubMed Central

Goldsmith, J.; Greven, S.; Crainiceanu, C.

2014-01-01

Functional principal components (FPC) analysis is widely used to decompose and express functional observations. Curve estimates implicitly condition on basis functions and other quantities derived from FPC decompositions; however these objects are unknown in practice. In this article, we propose a method for obtaining correct curve estimates by accounting for uncertainty in FPC decompositions. Additionally, pointwise and simultaneous confidence intervals that account for both model- and decomposition-based variability are constructed. Standard mixed model representations of functional expansions are used to construct curve estimates and variances conditional on a specific decomposition. Iterated expectation and variance formulas combine model-based conditional estimates across the distribution of decompositions. A bootstrap procedure is implemented to understand the uncertainty in principal component decomposition quantities. Our method compares favorably to competing approaches in simulation studies that include both densely and sparsely observed functions. We apply our method to sparse observations of CD4 cell counts and to dense white-matter tract profiles. Code for the analyses and simulations is publicly available, and our method is implemented in the R package refund on CRAN. PMID:23003003

A Four-Stage Hybrid Model for Hydrological Time Series Forecasting

PubMed Central

Di, Chongli; Yang, Xiaohua; Wang, Xiaochao

2014-01-01

Hydrological time series forecasting remains a difficult task due to its complicated nonlinear, non-stationary and multi-scale characteristics. To solve this difficulty and improve the prediction accuracy, a novel four-stage hybrid model is proposed for hydrological time series forecasting based on the principle of ‘denoising, decomposition and ensemble’. The proposed model has four stages, i.e., denoising, decomposition, components prediction and ensemble. In the denoising stage, the empirical mode decomposition (EMD) method is utilized to reduce the noises in the hydrological time series. Then, an improved method of EMD, the ensemble empirical mode decomposition (EEMD), is applied to decompose the denoised series into a number of intrinsic mode function (IMF) components and one residual component. Next, the radial basis function neural network (RBFNN) is adopted to predict the trend of all of the components obtained in the decomposition stage. In the final ensemble prediction stage, the forecasting results of all of the IMF and residual components obtained in the third stage are combined to generate the final prediction results, using a linear neural network (LNN) model. For illustration and verification, six hydrological cases with different characteristics are used to test the effectiveness of the proposed model. The proposed hybrid model performs better than conventional single models, the hybrid models without denoising or decomposition and the hybrid models based on other methods, such as the wavelet analysis (WA)-based hybrid models. In addition, the denoising and decomposition strategies decrease the complexity of the series and reduce the difficulties of the forecasting. With its effective denoising and accurate decomposition ability, high prediction precision and wide applicability, the new model is very promising for complex time series forecasting. This new forecast model is an extension of nonlinear prediction models. PMID:25111782

A four-stage hybrid model for hydrological time series forecasting.

PubMed

Di, Chongli; Yang, Xiaohua; Wang, Xiaochao

2014-01-01

Hydrological time series forecasting remains a difficult task due to its complicated nonlinear, non-stationary and multi-scale characteristics. To solve this difficulty and improve the prediction accuracy, a novel four-stage hybrid model is proposed for hydrological time series forecasting based on the principle of 'denoising, decomposition and ensemble'. The proposed model has four stages, i.e., denoising, decomposition, components prediction and ensemble. In the denoising stage, the empirical mode decomposition (EMD) method is utilized to reduce the noises in the hydrological time series. Then, an improved method of EMD, the ensemble empirical mode decomposition (EEMD), is applied to decompose the denoised series into a number of intrinsic mode function (IMF) components and one residual component. Next, the radial basis function neural network (RBFNN) is adopted to predict the trend of all of the components obtained in the decomposition stage. In the final ensemble prediction stage, the forecasting results of all of the IMF and residual components obtained in the third stage are combined to generate the final prediction results, using a linear neural network (LNN) model. For illustration and verification, six hydrological cases with different characteristics are used to test the effectiveness of the proposed model. The proposed hybrid model performs better than conventional single models, the hybrid models without denoising or decomposition and the hybrid models based on other methods, such as the wavelet analysis (WA)-based hybrid models. In addition, the denoising and decomposition strategies decrease the complexity of the series and reduce the difficulties of the forecasting. With its effective denoising and accurate decomposition ability, high prediction precision and wide applicability, the new model is very promising for complex time series forecasting. This new forecast model is an extension of nonlinear prediction models.

Local identifiability and sensitivity analysis of neuromuscular blockade and depth of hypnosis models.

PubMed

Silva, M M; Lemos, J M; Coito, A; Costa, B A; Wigren, T; Mendonça, T

2014-01-01

This paper addresses the local identifiability and sensitivity properties of two classes of Wiener models for the neuromuscular blockade and depth of hypnosis, when drug dose profiles like the ones commonly administered in the clinical practice are used as model inputs. The local parameter identifiability was assessed based on the singular value decomposition of the normalized sensitivity matrix. For the given input signal excitation, the results show an over-parameterization of the standard pharmacokinetic/pharmacodynamic models. The same identifiability assessment was performed on recently proposed minimally parameterized parsimonious models for both the neuromuscular blockade and the depth of hypnosis. The results show that the majority of the model parameters are identifiable from the available input-output data. This indicates that any identification strategy based on the minimally parameterized parsimonious Wiener models for the neuromuscular blockade and for the depth of hypnosis is likely to be more successful than if standard models are used. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Kinetics of proton transfer from tetra(4-nitro-5- tert-butyl)phthalocyanine to nitrogen-containing bases in benzene

NASA Astrophysics Data System (ADS)

Petrov, O. A.; Kuzmina, E. L.; Maizlish, V. E.; Rodionov, A. V.

2014-01-01

The acid-basic interaction between tetra(4-nitro-5- tert-butyl)phthalocyanine and pyridine, 2-methylpyridine, morpholine, piperidine, n-butylamine, diethylamine, and triethylamine in benzene is studied. It is found that the intermolecular transfer of protons of NH groups from tetra(4-nitro-5- tert-butyl)phthalocyanine to morpholine and diethylamine is characterized by unusually low values of the reaction constant rates. The effect of the structure of tetra(4-nitro-5- tert-butyl)phthalocyanine and tetra(3-nitro-5- tert-butyl)phthalocyanine, and of the nature of the base on the kinetic parameters of acid-base interaction is demonstrated. A structure is proposed for complexes with the transfer of displaced phthalocyanines' protons. It is found that they undergo decomposition over time.

Statistical Ring Opening Metathesis Copolymerization of Norbornene and Cyclopentene by Grubbs' 1st-Generation Catalyst.

PubMed

Nikovia, Christiana; Maroudas, Andreas-Philippos; Goulis, Panagiotis; Tzimis, Dionysios; Paraskevopoulou, Patrina; Pitsikalis, Marinos

2015-08-27

Statistical copolymers of norbornene (NBE) with cyclopentene (CP) were prepared by ring-opening metathesis polymerization, employing the 1st-generation Grubbs' catalyst, in the presence or absence of triphenylphosphine, PPh₃. The reactivity ratios were estimated using the Finemann-Ross, inverted Finemann-Ross, and Kelen-Tüdos graphical methods, along with the computer program COPOINT, which evaluates the parameters of binary copolymerizations from comonomer/copolymer composition data by integrating a given copolymerization equation in its differential form. Structural parameters of the copolymers were obtained by calculating the dyad sequence fractions and the mean sequence length, which were derived using the monomer reactivity ratios. The kinetics of thermal decomposition of the copolymers along with the respective homopolymers was studied by thermogravimetric analysis within the framework of the Ozawa-Flynn-Wall and Kissinger methodologies. Finally, the effect of triphenylphosphine on the kinetics of copolymerization, the reactivity ratios, and the kinetics of thermal decomposition were examined.

Comparative evaluation of thermal oxidative decomposition for oil-plant residues via thermogravimetric analysis: Thermal conversion characteristics, kinetics, and thermodynamics.

PubMed

Chen, Jianbiao; Wang, Yanhong; Lang, Xuemei; Ren, Xiu'e; Fan, Shuanshi

2017-11-01

Thermal oxidative decomposition characteristics, kinetics, and thermodynamics of rape straw (RS), rapeseed meal (RM), camellia seed shell (CS), and camellia seed meal (CM) were evaluated via thermogravimetric analysis (TGA). TG-DTG-DSC curves demonstrated that the combustion of oil-plant residues proceeded in three stages, including dehydration, release and combustion of organic volatiles, and chars oxidation. As revealed by combustion characteristic parameters, the ignition, burnout, and comprehensive combustion performance of residues were quite distinct from each other, and were improved by increasing heating rate. The kinetic parameters were determined by Coats-Redfern approach. The results showed that the most possible combustion mechanisms were order reaction models. The existence of kinetic compensation effect was clearly observed. The thermodynamic parameters (ΔH, ΔG, ΔS) at peak temperatures were calculated through the activated complex theory. With the combustion proceeding, the variation trends of ΔH, ΔG, and ΔS for RS (RM) similar to those for CS (CM). Copyright © 2017 Elsevier Ltd. All rights reserved.

Linear prediction and single-channel recording.

PubMed

Carter, A A; Oswald, R E

1995-08-01

The measurement of individual single-channel events arising from the gating of ion channels provides a detailed data set from which the kinetic mechanism of a channel can be deduced. In many cases, the pattern of dwells in the open and closed states is very complex, and the kinetic mechanism and parameters are not easily determined. Assuming a Markov model for channel kinetics, the probability density function for open and closed time dwells should consist of a sum of decaying exponentials. One method of approaching the kinetic analysis of such a system is to determine the number of exponentials and the corresponding parameters which comprise the open and closed dwell time distributions. These can then be compared to the relaxations predicted from the kinetic model to determine, where possible, the kinetic constants. We report here the use of a linear technique, linear prediction/singular value decomposition, to determine the number of exponentials and the exponential parameters. Using simulated distributions and comparing with standard maximum-likelihood analysis, the singular value decomposition techniques provide advantages in some situations and are a useful adjunct to other single-channel analysis techniques.

Shortened Mean Transit Time in CT Perfusion With Singular Value Decomposition Analysis in Acute Cerebral Infarction: Quantitative Evaluation and Comparison With Various CT Perfusion Parameters.

PubMed

Murayama, Kazuhiro; Katada, Kazuhiro; Hayakawa, Motoharu; Toyama, Hiroshi

We aimed to clarify the cause of shortened mean transit time (MTT) in acute ischemic cerebrovascular disease and examined its relationship with reperfusion. Twenty-three patients with acute ischemic cerebrovascular disease underwent whole-brain computed tomography perfusion (CTP). The maximum MTT (MTTmax), minimum MTT (MTTmin), ratio of maximum and minimum MTT (MTTmin/max), and minimum cerebral blood volume (CBV) (CBVmin) were measured by automatic region of interest analysis. Diffusion weighted image was performed to calculate infarction volume. We compared these CTP parameters between reperfusion and nonreperfusion groups and calculated correlation coefficients between the infarction core volume and CTP parameters. Significant differences were observed between reperfusion and nonreperfusion groups (MTTmin/max: P = 0.014; CBVmin ratio: P = 0.038). Regression analysis of CTP and high-intensity volume on diffusion weighted image showed negative correlation (CBVmin ratio: r = -0.41; MTTmin/max: r = -0.30; MTTmin ratio: r = -0.27). A region of shortened MTT indicated obstructed blood flow, which was attributed to the singular value decomposition method error.

A Deep Insight into the Details of the Interisomerization and Decomposition Mechanism of o-Quinolyl and o-Isoquinolyl Radicals. Quantum Chemical Calculations and Computer Modeling.

PubMed

Dubnikova, Faina; Tamburu, Carmen; Lifshitz, Assa

2016-09-29

The isomerization of o-quinolyl ↔ o-isoquinolyl radicals and their thermal decomposition were studied by quantum chemical methods, where potential energy surfaces of the reaction channels and their kinetics rate parameters were determined. A detailed kinetics scheme containing 40 elementary steps was constructed. Computer simulations were carried out to determine the isomerization mechanism and the distribution of reaction products in the decomposition. The calculated mole percent of the stable products was compared to the experimental values that were obtained in this laboratory in the past, using the single pulse shock tube. The agreement between the experimental and the calculated mole percents was very good. A map of the figures containing the mole percent's of eight stable products of the decomposition plotted vs T are presented. The fast isomerization of o-quinolyl → o-isoquinolyl radicals via the intermediate indene imine radical and the attainment of fast equilibrium between these two radicals is the reason for the identical product distribution regardless whether the reactant radical is o-quinolyl or o-isoquinolyl. Three of the main decomposition products of o-quinolyl radical, are those containing the benzene ring, namely, phenyl, benzonitrile, and phenylacetylene radicals. They undergo further decomposition mainly at high temperatures via two types of reactions: (1) Opening of the benzene ring in the radicals, followed by splitting into fragments. (2) Dissociative attachment of benzonitrile and phenyl acetylene by hydrogen atoms to form hydrogen cyanide and acetylene.

Transition from Direct to Inverse Cascade in Three-Dimensional Turbulence

NASA Astrophysics Data System (ADS)

Sahoo, Ganapati; Alexakis, Alexandros; Biferale, Luca

2017-11-01

We study a model system where the triadic interactions in Navier-Stokes equations are enhanced or suppressed in a controlled manner without affecting neither the total number of degrees of freedom nor the ideal invariants and without breaking any of the symmetries of original equations. Our numerical simulations are based on the helical decomposition of velocity Fourier modes. We introduced a parameter (0 <= λ <= 1) that controls the relative weight among homochiral and heterochiral triads in the nonlinear evolution. We show that by using this weighting protocol the turbulent evolution displays a sharp transition, for a critical value of the control parameter, from forward to backward energy transfer but still keeping the dynamics fully three dimensional, isotropic, and parity invariant. AtMath Collaboration of University of Helsinki and ERC Grant No. 339032 `NewTurb'.

Uncertainty-enabled design of electromagnetic reflectors with integrated shape control

NASA Astrophysics Data System (ADS)

Haque, Samiul; Kindrat, Laszlo P.; Zhang, Li; Mikheev, Vikenty; Kim, Daewa; Liu, Sijing; Chung, Jooyeon; Kuian, Mykhailo; Massad, Jordan E.; Smith, Ralph C.

2018-03-01

We implemented a computationally efficient model for a corner-supported, thin, rectangular, orthotropic polyvinylidene fluoride (PVDF) laminate membrane, actuated by a two-dimensional array of segmented electrodes. The laminate can be used as shape-controlled electromagnetic reflector and the model estimates the reflector's shape given an array of control voltages. In this paper, we describe a model to determine the shape of the laminate for a given distribution of control voltages. Then, we investigate the surface shape error and its sensitivity to the model parameters. Subsequently, we analyze the simulated deflection of the actuated bimorph using a Zernike polynomial decomposition. Finally, we provide a probabilistic description of reflector performance using statistical methods to quantify uncertainty. We make design recommendations for nominal parameter values and their tolerances based on optimization under uncertainty using multiple methods.

Analysis of turbine-grid interaction of grid-connected wind turbine using HHT

NASA Astrophysics Data System (ADS)

Chen, A.; Wu, W.; Miao, J.; Xie, D.

2018-05-01

This paper processes the output power of the grid-connected wind turbine with the denoising and extracting method based on Hilbert Huang transform (HHT) to discuss the turbine-grid interaction. At first, the detailed Empirical Mode Decomposition (EMD) and the Hilbert Transform (HT) are introduced. Then, on the premise of decomposing the output power of the grid-connected wind turbine into a series of Intrinsic Mode Functions (IMFs), energy ratio and power volatility are calculated to detect the unessential components. Meanwhile, combined with vibration function of turbine-grid interaction, data fitting of instantaneous amplitude and phase of each IMF is implemented to extract characteristic parameters of different interactions. Finally, utilizing measured data of actual parallel-operated wind turbines in China, this work accurately obtains the characteristic parameters of turbine-grid interaction of grid-connected wind turbine.

Thermal decomposition and kinetic evaluation of decanted 2,4,6-trinitrotoluene (TNT) for reutilization as composite material

NASA Astrophysics Data System (ADS)

Ahmed, M. F.; Hussain, A.; Malik, A. Q.

2016-08-01

Use of energetic materials has long been considered for only military purposes. However, it is very recent that their practical applications in wide range of commercial fields such as mining, road building, under water blasting and rocket propulsion system have been considered. About 5mg of 2,4,6-trinitrotoluene (TNT) in serviceable (Svc) as well as unserviceable (Unsvc) form were used for their thermal decomposition and kinetic parameters investigation. Thermogravimetric/ differential thermal analysis (TG/DTA), X-ray diffraction (XRD) and Scanning electron microscope (SEM) were used to characterize two types of TNT. Arrhenius kinetic parameters like activation energy (E) and enthalpy (AH) of both TNT samples were determined using TG curves with the help of Horowitz and Metzger method. Simultaneously, thermal decomposition range was evaluated from DTA curves. Distinct diffraction peaks showing crystalline nature were obtained from XRD analysis. SEM results indicated that Unsvc TNT contained a variety of defects like cracks and porosity. Similarly, it is observed that thermal as well as kinetic behavior of both TNT samples vary to a great extent. Likewise, a prominent change in the activation energies (E) of both samples is observed. This in-depth study provides a way forward in finding solutions for the safe reutilization of decanted TNT.

An investigation on the modelling of kinetics of thermal decomposition of hazardous mercury wastes.

PubMed

Busto, Yailen; M G Tack, Filip; Peralta, Luis M; Cabrera, Xiomara; Arteaga-Pérez, Luis E

2013-09-15

The kinetics of mercury removal from solid wastes generated by chlor-alkali plants were studied. The reaction order and model-free method with an isoconversional approach were used to estimate the kinetic parameters and reaction mechanism that apply to the thermal decomposition of hazardous mercury wastes. As a first approach to the understanding of thermal decomposition for this type of systems (poly-disperse and multi-component), a novel scheme of six reactions was proposed to represent the behaviour of mercury compounds in the solid matrix during the treatment. An integration-optimization algorithm was used in the screening of nine mechanistic models to develop kinetic expressions that best describe the process. The kinetic parameters were calculated by fitting each of these models to the experimental data. It was demonstrated that the D₁-diffusion mechanism appeared to govern the process at 250°C and high residence times, whereas at 450°C a combination of the diffusion mechanism (D₁) and the third order reaction mechanism (F3) fitted the kinetics of the conversions. The developed models can be applied in engineering calculations to dimension the installations and determine the optimal conditions to treat a mercury containing sludge. Copyright © 2013 Elsevier B.V. All rights reserved.

Investigation of thermodynamic parameters in the thermal decomposition of plastic waste-waste lube oil compounds.

PubMed

Kim, Yong Sang; Kim, Young Seok; Kim, Sung Hyun

2010-07-01

Thermal decomposition properties of plastic waste-waste lube oil compounds were investigated under nonisothermal conditions. Polyethylene (PE), polypropylene (PP), polystyrene (PS), and polyethylene terephthalate (PET) were selected as representative household plastic wastes. A plastic waste mixture (PWM) and waste lube oil (WLO) were mixed with mixing ratios of 33, 50, and 67 (w/w) % on a PWM weight basis, and thermogravimetric (TG) experiments were performed from 25 to 600 degrees C. The Flynn-Wall method and the Ozawa-Flynn-Wall method were used for analyses of thermodynamic parameters. In this study, activation energies of PWM/WLO compounds ranged from 73.4 to 229.6 kJ/mol between 0.2 and 0.8 of normalized mass conversions, and the 50% PWM/WLO compound had lower activation energies and enthalpies among the PWM/WLO samples at each mass conversion. At the point of maximum differential mass conversion, the analyzed activation energies, enthalpies, entropies, and Gibbs free energies indicated that mixing PWM and WLO has advantages in reducing energy to decrease the degree of disorder. However, no difference in overall energy that would require overcoming both thermal decomposition reactions and degree of disorder was observed among PWM/WLO compounds under these experimental conditions.

Model-based multiple patterning layout decomposition

NASA Astrophysics Data System (ADS)

Guo, Daifeng; Tian, Haitong; Du, Yuelin; Wong, Martin D. F.

2015-10-01

As one of the most promising next generation lithography technologies, multiple patterning lithography (MPL) plays an important role in the attempts to keep in pace with 10 nm technology node and beyond. With feature size keeps shrinking, it has become impossible to print dense layouts within one single exposure. As a result, MPL such as double patterning lithography (DPL) and triple patterning lithography (TPL) has been widely adopted. There is a large volume of literature on DPL/TPL layout decomposition, and the current approach is to formulate the problem as a classical graph-coloring problem: Layout features (polygons) are represented by vertices in a graph G and there is an edge between two vertices if and only if the distance between the two corresponding features are less than a minimum distance threshold value dmin. The problem is to color the vertices of G using k colors (k = 2 for DPL, k = 3 for TPL) such that no two vertices connected by an edge are given the same color. This is a rule-based approach, which impose a geometric distance as a minimum constraint to simply decompose polygons within the distance into different masks. It is not desired in practice because this criteria cannot completely capture the behavior of the optics. For example, it lacks of sufficient information such as the optical source characteristics and the effects between the polygons outside the minimum distance. To remedy the deficiency, a model-based layout decomposition approach to make the decomposition criteria base on simulation results was first introduced at SPIE 2013.1 However, the algorithm1 is based on simplified assumption on the optical simulation model and therefore its usage on real layouts is limited. Recently AMSL2 also proposed a model-based approach to layout decomposition by iteratively simulating the layout, which requires excessive computational resource and may lead to sub-optimal solutions. The approach2 also potentially generates too many stiches. In this paper, we propose a model-based MPL layout decomposition method using a pre-simulated library of frequent layout patterns. Instead of using the graph G in the standard graph-coloring formulation, we build an expanded graph H where each vertex represents a group of adjacent features together with a coloring solution. By utilizing the library and running sophisticated graph algorithms on H, our approach can obtain optimal decomposition results efficiently. Our model-based solution can achieve a practical mask design which significantly improves the lithography quality on the wafer compared to the rule based decomposition.

Evolution of various fractions during the windrow composting of chicken manure with rice chaff.

PubMed

Kong, Zhijian; Wang, Xuanqing; Liu, Qiumei; Li, Tuo; Chen, Xing; Chai, Lifang; Liu, Dongyang; Shen, Qirong

2018-02-01

Different fractions during the 85-day windrow composting were characterized based on various parameters, such as physiochemical properties and hydrolytic enzyme activities; several technologies were used, including spectral scanning techniques, confocal laser scanning microscopy (CLSM) and 13 C Nuclear Magnetic Resonance Spectroscopy ( 13 C NMR). The evaluated parameters fluctuated strongly during the first 3 weeks which was the most active period of the composting process. The principal components analysis (PCA) results showed that four classes of the samples were clearly distinguishable, in which the physiochemical parameters were similar, and that the dynamics of the composting process was significantly influenced by C/N and moisture content. The 13 C NMR results indicated that O-alkyl-C was the predominant group both in the solid and water-soluble fractions (WSF), and the decomposition of O-alkyl-C mainly occurred during the active stage. In general, the various parameters indicated that windrow composting is a feasible treatment that can be used for the resource reuse of agricultural wastes. Copyright © 2017 Elsevier Ltd. All rights reserved.

Interface conditions for domain decomposition with radical grid refinement

NASA Technical Reports Server (NTRS)

Scroggs, Jeffrey S.

1991-01-01

Interface conditions for coupling the domains in a physically motivated domain decomposition method are discussed. The domain decomposition is based on an asymptotic-induced method for the numerical solution of hyperbolic conservation laws with small viscosity. The method consists of multiple stages. The first stage is to obtain a first approximation using a first-order method, such as the Godunov scheme. Subsequent stages of the method involve solving internal-layer problem via a domain decomposition. The method is derived and justified via singular perturbation techniques.

A comparison between decomposition rates of buried and surface remains in a temperate region of South Africa.

PubMed

Marais-Werner, Anátulie; Myburgh, J; Becker, P J; Steyn, M

2018-01-01

Several studies have been conducted on decomposition patterns and rates of surface remains; however, much less are known about this process for buried remains. Understanding the process of decomposition in buried remains is extremely important and aids in criminal investigations, especially when attempting to estimate the post mortem interval (PMI). The aim of this study was to compare the rates of decomposition between buried and surface remains. For this purpose, 25 pigs (Sus scrofa; 45-80 kg) were buried and excavated at different post mortem intervals (7, 14, 33, 92, and 183 days). The observed total body scores were then compared to those of surface remains decomposing at the same location. Stages of decomposition were scored according to separate categories for different anatomical regions based on standardised methods. Variation in the degree of decomposition was considerable especially with the buried 7-day interval pigs that displayed different degrees of discolouration in the lower abdomen and trunk. At 14 and 33 days, buried pigs displayed features commonly associated with the early stages of decomposition, but with less variation. A state of advanced decomposition was reached where little change was observed in the next ±90-183 days after interment. Although the patterns of decomposition for buried and surface remains were very similar, the rates differed considerably. Based on the observations made in this study, guidelines for the estimation of PMI are proposed. This pertains to buried remains found at a depth of approximately 0.75 m in the Central Highveld of South Africa.

A parsimonious characterization of change in global age-specific and total fertility rates

PubMed Central

2018-01-01

This study aims to understand trends in global fertility from 1950-2010 though the analysis of age-specific fertility rates. This approach incorporates both the overall level, as when the total fertility rate is modeled, and different patterns of age-specific fertility to examine the relationship between changes in age-specific fertility and fertility decline. Singular value decomposition is used to capture the variation in age-specific fertility curves while reducing the number of dimensions, allowing curves to be described nearly fully with three parameters. Regional patterns and trends over time are evident in parameter values, suggesting this method provides a useful tool for considering fertility decline globally. The second and third parameters were analyzed using model-based clustering to examine patterns of age-specific fertility over time and place; four clusters were obtained. A country’s demographic transition can be traced through time by membership in the different clusters, and regional patterns in the trajectories through time and with fertility decline are identified. PMID:29377899

Numerical solution to generalized Burgers'-Fisher equation using Exp-function method hybridized with heuristic computation.

PubMed

Malik, Suheel Abdullah; Qureshi, Ijaz Mansoor; Amir, Muhammad; Malik, Aqdas Naveed; Haq, Ihsanul

2015-01-01

In this paper, a new heuristic scheme for the approximate solution of the generalized Burgers'-Fisher equation is proposed. The scheme is based on the hybridization of Exp-function method with nature inspired algorithm. The given nonlinear partial differential equation (NPDE) through substitution is converted into a nonlinear ordinary differential equation (NODE). The travelling wave solution is approximated by the Exp-function method with unknown parameters. The unknown parameters are estimated by transforming the NODE into an equivalent global error minimization problem by using a fitness function. The popular genetic algorithm (GA) is used to solve the minimization problem, and to achieve the unknown parameters. The proposed scheme is successfully implemented to solve the generalized Burgers'-Fisher equation. The comparison of numerical results with the exact solutions, and the solutions obtained using some traditional methods, including adomian decomposition method (ADM), homotopy perturbation method (HPM), and optimal homotopy asymptotic method (OHAM), show that the suggested scheme is fairly accurate and viable for solving such problems.

Numerical Solution to Generalized Burgers'-Fisher Equation Using Exp-Function Method Hybridized with Heuristic Computation

PubMed Central

Malik, Suheel Abdullah; Qureshi, Ijaz Mansoor; Amir, Muhammad; Malik, Aqdas Naveed; Haq, Ihsanul

2015-01-01

In this paper, a new heuristic scheme for the approximate solution of the generalized Burgers'-Fisher equation is proposed. The scheme is based on the hybridization of Exp-function method with nature inspired algorithm. The given nonlinear partial differential equation (NPDE) through substitution is converted into a nonlinear ordinary differential equation (NODE). The travelling wave solution is approximated by the Exp-function method with unknown parameters. The unknown parameters are estimated by transforming the NODE into an equivalent global error minimization problem by using a fitness function. The popular genetic algorithm (GA) is used to solve the minimization problem, and to achieve the unknown parameters. The proposed scheme is successfully implemented to solve the generalized Burgers'-Fisher equation. The comparison of numerical results with the exact solutions, and the solutions obtained using some traditional methods, including adomian decomposition method (ADM), homotopy perturbation method (HPM), and optimal homotopy asymptotic method (OHAM), show that the suggested scheme is fairly accurate and viable for solving such problems. PMID:25811858

Domain decomposition methods for the parallel computation of reacting flows

NASA Technical Reports Server (NTRS)

Keyes, David E.

1988-01-01

Domain decomposition is a natural route to parallel computing for partial differential equation solvers. Subdomains of which the original domain of definition is comprised are assigned to independent processors at the price of periodic coordination between processors to compute global parameters and maintain the requisite degree of continuity of the solution at the subdomain interfaces. In the domain-decomposed solution of steady multidimensional systems of PDEs by finite difference methods using a pseudo-transient version of Newton iteration, the only portion of the computation which generally stands in the way of efficient parallelization is the solution of the large, sparse linear systems arising at each Newton step. For some Jacobian matrices drawn from an actual two-dimensional reacting flow problem, comparisons are made between relaxation-based linear solvers and also preconditioned iterative methods of Conjugate Gradient and Chebyshev type, focusing attention on both iteration count and global inner product count. The generalized minimum residual method with block-ILU preconditioning is judged the best serial method among those considered, and parallel numerical experiments on the Encore Multimax demonstrate for it approximately 10-fold speedup on 16 processors.

3-D parallel program for numerical calculation of gas dynamics problems with heat conductivity on distributed memory computational systems (CS)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sofronov, I.D.; Voronin, B.L.; Butnev, O.I.

1997-12-31

The aim of the work performed is to develop a 3D parallel program for numerical calculation of gas dynamics problem with heat conductivity on distributed memory computational systems (CS), satisfying the condition of numerical result independence from the number of processors involved. Two basically different approaches to the structure of massive parallel computations have been developed. The first approach uses the 3D data matrix decomposition reconstructed at temporal cycle and is a development of parallelization algorithms for multiprocessor CS with shareable memory. The second approach is based on using a 3D data matrix decomposition not reconstructed during a temporal cycle.more » The program was developed on 8-processor CS MP-3 made in VNIIEF and was adapted to a massive parallel CS Meiko-2 in LLNL by joint efforts of VNIIEF and LLNL staffs. A large number of numerical experiments has been carried out with different number of processors up to 256 and the efficiency of parallelization has been evaluated in dependence on processor number and their parameters.« less

Downstream processing of hyperforin from Hypericum perforatum root cultures.

PubMed

Haas, Paul; Gaid, Mariam; Zarinwall, Ajmal; Beerhues, Ludger; Scholl, Stephan

2018-05-01

Hyperforin is a major metabolite of the medicinal plant Hypericum perforatum (St. John's Wort) and has recently been found in hormone induced root cultures. The objective of this study is to identify a downstream process for the production of a hyperforin-rich extract with maximum extraction efficiency and minimal decomposition. The maximum extraction time was found to be 60min. The comparison of two equipment concepts for the extraction and solvent evaporation was performed employing two different solvents. While the rotary mixer showed better results for the extraction efficiency than a stirred vessel, the latter set-up was able to handle larger volumes but did not meet all process requirements. For the evaporation the prompt evaporation of the extraction agent using nitrogen stripping led to minor decomposition. In a 5L stirred vessel, the highest specific extraction of hyperforin was 4.3mg hyperforin/g dry weight bio material. Parameters for the equipment design for extraction and solvent evaporation were determined based on the experimental data. Copyright © 2017 Elsevier B.V. All rights reserved.

Precision and Accuracy of Analysis for Boron in ITP Samples

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tovo, L.L.

'Inductively Coupled Plasma Emission Spectroscopy (ICPES) has been used by the Analytical Development Section (ADS) to measure boron in catalytic tetraphenylboron decomposition studies performed by the Waste Processing Technology (WPT) section. Analysis of these samples is complicated due to the presence of high concentrations of sodium and organic compounds. Previously, we found signal suppression in samples analyzed "as received". We suspected that the suppression was due to the high organic concentration (up to 0.01 molar organic decomposition products) in the samples. When the samples were acid digested prior to analysis, the suppression was eliminated. The precision of the reported boronmore » concentration was estimated as 10 percent based on the known precision of the inorganic boron standard used for calibration and quality control check of the ICPES analysis. However, a precision better than 10 percent was needed to evaluate ITP process operating parameters. Therefore, the purpose of this work was (1) to measure, instead of estimating, the precision of the boron measurement on ITP samples and (2) to determine the optimum precision attainable with current instrumentation.'« less

A truncated generalized singular value decomposition algorithm for moving force identification with ill-posed problems

NASA Astrophysics Data System (ADS)

Chen, Zhen; Chan, Tommy H. T.

2017-08-01

This paper proposes a new methodology for moving force identification (MFI) from the responses of bridge deck. Based on the existing time domain method (TDM), the MFI problem eventually becomes solving the linear algebraic equation in the form Ax = b . The vector b is usually contaminated by an unknown error e generating from measurement error, which often called the vector e as ''noise''. With the ill-posed problems that exist in the inverse problem, the identification force would be sensitive to the noise e . The proposed truncated generalized singular value decomposition method (TGSVD) aims at obtaining an acceptable solution and making the noise to be less sensitive to perturbations with the ill-posed problems. The illustrated results show that the TGSVD has many advantages such as higher precision, better adaptability and noise immunity compared with TDM. In addition, choosing a proper regularization matrix L and a truncation parameter k are very useful to improve the identification accuracy and to solve ill-posed problems when it is used to identify the moving force on bridge.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schaefer, Michael, E-mail: mvschaefer@mail.usf.edu, E-mail: axk650@case.edu, E-mail: mohan@case.edu, E-mail: schlaf@mail.usf.edu; Kumar, Ajay, E-mail: mvschaefer@mail.usf.edu, E-mail: axk650@case.edu, E-mail: mohan@case.edu, E-mail: schlaf@mail.usf.edu; Mohan Sankaran, R., E-mail: mvschaefer@mail.usf.edu, E-mail: axk650@case.edu, E-mail: mohan@case.edu, E-mail: schlaf@mail.usf.edu

Microplasma-assisted gas-phase nucleation has emerged as an important new approach to produce high-purity, nanometer-sized, and narrowly dispersed particles. This study aims to integrate this technique with vacuum conditions to enable synthesis and deposition in an ultrahigh vacuum compatible environment. The ultimate goal is to combine nanoparticle synthesis with photoemission spectroscopy-based electronic structure analysis. Such measurements require in vacuo deposition to prevent surface contamination from sample transfer, which can be deleterious for nanoscale materials. A homebuilt microplasma reactor was integrated into an existing atomic layer deposition system attached to a surface science multi-chamber system equipped with photoemission spectroscopy. As proof-of-concept, wemore » studied the decomposition of ferrocene vapor in the microplasma to synthesize iron oxide nanoparticles. The injection parameters were optimized to achieve complete precursor decomposition under vacuum conditions, and nanoparticles were successfully deposited. The stoichiometry of the deposited samples was characterized in situ using X-ray photoelectron spectroscopy indicating that iron oxide was formed. Additional transmission electron spectroscopy characterization allowed the determination of the size, shape, and crystal lattice of the particles, confirming their structural properties.« less

Application of generalized singular value decomposition to ionospheric tomography

NASA Astrophysics Data System (ADS)

Bhuyan, K.; Singh, S.; Bhuyan, P.

2004-10-01

The electron density distribution of the low- and mid-latitude ionosphere has been investigated by the computerized tomography technique using a Generalized Singular Value Decomposition (GSVD) based algorithm. Model ionospheric total electron content (TEC) data obtained from the International Reference Ionosphere 2001 and slant relative TEC data measured at a chain of three stations receiving transit satellite transmissions in Alaska, USA are used in this analysis. The issue of optimum efficiency of the GSVD algorithm in the reconstruction of ionospheric structures is being addressed through simulation of the equatorial ionization anomaly (EIA), in addition to its application to investigate complicated ionospheric density irregularities. Results show that the Generalized Cross Validation approach to find the regularization parameter and the corresponding solution gives a very good reconstructed image of the low-latitude ionosphere and the EIA within it. Provided that some minimum norm is fulfilled, the GSVD solution is found to be least affected by considerations, such as pixel size and number of ray paths. The method has also been used to investigate the behaviour of the mid-latitude ionosphere under magnetically quiet and disturbed conditions.

Plasmonic Thermal Decomposition/Digestion of Proteins: A Rapid On-Surface Protein Digestion Technique for Mass Spectrometry Imaging.

PubMed

Zhou, Rong; Basile, Franco

2017-09-05

A method based on plasmon surface resonance absorption and heating was developed to perform a rapid on-surface protein thermal decomposition and digestion suitable for imaging mass spectrometry (MS) and/or profiling. This photothermal process or plasmonic thermal decomposition/digestion (plasmonic-TDD) method incorporates a continuous wave (CW) laser excitation and gold nanoparticles (Au-NPs) to induce known thermal decomposition reactions that cleave peptides and proteins specifically at the C-terminus of aspartic acid and at the N-terminus of cysteine. These thermal decomposition reactions are induced by heating a solid protein sample to temperatures between 200 and 270 °C for a short period of time (10-50 s per 200 μm segment) and are reagentless and solventless, and thus are devoid of sample product delocalization. In the plasmonic-TDD setup the sample is coated with Au-NPs and irradiated with 532 nm laser radiation to induce thermoplasmonic heating and bring about site-specific thermal decomposition on solid peptide/protein samples. In this manner the Au-NPs act as nanoheaters that result in a highly localized thermal decomposition and digestion of the protein sample that is independent of the absorption properties of the protein, making the method universally applicable to all types of proteinaceous samples (e.g., tissues or protein arrays). Several experimental variables were optimized to maximize product yield, and they include heating time, laser intensity, size of Au-NPs, and surface coverage of Au-NPs. Using optimized parameters, proof-of-principle experiments confirmed the ability of the plasmonic-TDD method to induce both C-cleavage and D-cleavage on several peptide standards and the protein lysozyme by detecting their thermal decomposition products with matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS). The high spatial specificity of the plasmonic-TDD method was demonstrated by using a mask to digest designated sections of the sample surface with the heating laser and MALDI-MS imaging to map the resulting products. The solventless nature of the plasmonic-TDD method enabled the nonenzymatic on-surface digestion of proteins to proceed with undetectable delocalization of the resulting products from their precursor protein location. The advantages of this novel plasmonic-TDD method include short reaction times (<30 s/200 μm), compatibility with MALDI, universal sample compatibility, high spatial specificity, and localization of the digestion products. These advantages point to potential applications of this method for on-tissue protein digestion and MS-imaging/profiling for the identification of proteins, high-fidelity MS imaging of high molecular weight (>30 kDa) proteins, and the rapid analysis of formalin-fixed paraffin-embedded (FFPE) tissue samples.

Morphological decomposition of 2-D binary shapes into convex polygons: a heuristic algorithm.

PubMed

Xu, J

2001-01-01

In many morphological shape decomposition algorithms, either a shape can only be decomposed into shape components of extremely simple forms or a time consuming search process is employed to determine a decomposition. In this paper, we present a morphological shape decomposition algorithm that decomposes a two-dimensional (2-D) binary shape into a collection of convex polygonal components. A single convex polygonal approximation for a given image is first identified. This first component is determined incrementally by selecting a sequence of basic shape primitives. These shape primitives are chosen based on shape information extracted from the given shape at different scale levels. Additional shape components are identified recursively from the difference image between the given image and the first component. Simple operations are used to repair certain concavities caused by the set difference operation. The resulting hierarchical structure provides descriptions for the given shape at different detail levels. The experiments show that the decomposition results produced by the algorithm seem to be in good agreement with the natural structures of the given shapes. The computational cost of the algorithm is significantly lower than that of an earlier search-based convex decomposition algorithm. Compared to nonconvex decomposition algorithms, our algorithm allows accurate approximations for the given shapes at low coding costs.

Possibility of H2O2 decomposition in thin liquid films on Mars

NASA Astrophysics Data System (ADS)

Kereszturi, Akos; Gobi, Sandor

2014-11-01

In this work the pathways and possibilities of H2O2 decomposition on Mars in microscopic liquid interfacial water were analyzed by kinetic calculations. Thermal and photochemical driven decomposition, just like processes catalyzed by various metal oxides, is too slow compared to the annual duration while such microscopic liquid layers exist on Mars today, to produce substantial decomposition. The most effective analyzed process is catalyzed by Fe ions, which could decompose H2O2 under pH<4.5 with a half life of 1-2 days. This process might be important during volcanically influenced periods when sulfur release produces acidic pH, and rotational axis tilt change driven climatic changes also influence the volatile circulation and spatial occurrence just like the duration of thin liquid layer. Under current conditions, using the value of 200 K as the temperature in interfacial water (at the southern hemisphere), and applying Phoenix lander's wet chemistry laboratory results, the pH is not favorable for Fe mobility and this kind of decomposition. Despite current conditions (especially pH) being unfavorable for H2O2 decomposition, microscopic scale interfacial liquid water still might support the process. By the reaction called heterogeneous catalysis, without acidic pH and mobile Fe, but with minerals surfaces containing Fe decomposition of H2O2 with half life of 20 days can happen. This duration is still longer but not several orders than the existence of springtime interfacial liquid water on Mars today. This estimation is relevant for activation energy controlled reaction rates. The other main parameter that may influence the reaction rate is the diffusion speed. Although the available tests and theoretical calculations do not provide firm values for the diffusion speed in such a “2-dimensional” environment, using relevant estimations this parameter in the interfacial liquid layer is smaller than in bulk water. But the 20 days' duration mentioned above is still relevant, as the activation energy driven reaction rate is the main limiting factor in the decomposition and not the diffusion speed. The duration of dozen(s) days is still longer but not with orders of magnitude than the expected duration for the existence of springtime interfacial liquid water on Mars today. The results suggest such decomposition may happen today, however, because of our limited knowledge on chemical processes in thin interfacial liquid layers, this possibility waits for confirmation - and also points to the importance of conducting laboratory tests to validate the possible process. Although some tests were already realized for diffusion in an almost 2-dimensional liquid, the same is not true for activation energy, where only the value from the “normal” measurements was applied. Even if H2O2 decomposition is too slow today, the analysis of such a process is important, as under volcanic influence more effective decomposition might take place in thin interfacial liquids close to the climate of today if released sulfur produces pH<4.5. Large quantity and widespread occurrence of bulk liquid phase are not expected in the Amazonian period, but interfacial liquid water probably appeared regularly, and its locations, especially during volcanically active periods, might make certain sites than others more interesting for astrobiology with the lower concentration of oxidizing H2O2.

An operational modal analysis method in frequency and spatial domain

NASA Astrophysics Data System (ADS)

Wang, Tong; Zhang, Lingmi; Tamura, Yukio

2005-12-01

A frequency and spatial domain decomposition method (FSDD) for operational modal analysis (OMA) is presented in this paper, which is an extension of the complex mode indicator function (CMIF) method for experimental modal analysis (EMA). The theoretical background of the FSDD method is clarified. Singular value decomposition is adopted to separate the signal space from the noise space. Finally, an enhanced power spectrum density (PSD) is proposed to obtain more accurate modal parameters by curve fitting in the frequency domain. Moreover, a simulation case and an application case are used to validate this method.

Theoretical study of gas hydrate decomposition kinetics--model development.

PubMed

Windmeier, Christoph; Oellrich, Lothar R

2013-10-10

In order to provide an estimate of the order of magnitude of intrinsic gas hydrate dissolution and dissociation kinetics, the "Consecutive Desorption and Melting Model" (CDM) is developed by applying only theoretical considerations. The process of gas hydrate decomposition is assumed to comprise two consecutive and repetitive quasi chemical reaction steps. These are desorption of the guest molecule followed by local solid body melting. The individual kinetic steps are modeled according to the "Statistical Rate Theory of Interfacial Transport" and the Wilson-Frenkel approach. All missing required model parameters are directly linked to geometric considerations and a thermodynamic gas hydrate equilibrium model.

A statistical approach based on accumulated degree-days to predict decomposition-related processes in forensic studies.

PubMed

Michaud, Jean-Philippe; Moreau, Gaétan

2011-01-01

Using pig carcasses exposed over 3 years in rural fields during spring, summer, and fall, we studied the relationship between decomposition stages and degree-day accumulation (i) to verify the predictability of the decomposition stages used in forensic entomology to document carcass decomposition and (ii) to build a degree-day accumulation model applicable to various decomposition-related processes. Results indicate that the decomposition stages can be predicted with accuracy from temperature records and that a reliable degree-day index can be developed to study decomposition-related processes. The development of degree-day indices opens new doors for researchers and allows for the application of inferential tools unaffected by climatic variability, as well as for the inclusion of statistics in a science that is primarily descriptive and in need of validation methods in courtroom proceedings. © 2010 American Academy of Forensic Sciences.

Automatic network coupling analysis for dynamical systems based on detailed kinetic models.

PubMed

Lebiedz, Dirk; Kammerer, Julia; Brandt-Pollmann, Ulrich

2005-10-01

We introduce a numerical complexity reduction method for the automatic identification and analysis of dynamic network decompositions in (bio)chemical kinetics based on error-controlled computation of a minimal model dimension represented by the number of (locally) active dynamical modes. Our algorithm exploits a generalized sensitivity analysis along state trajectories and subsequent singular value decomposition of sensitivity matrices for the identification of these dominant dynamical modes. It allows for a dynamic coupling analysis of (bio)chemical species in kinetic models that can be exploited for the piecewise computation of a minimal model on small time intervals and offers valuable functional insight into highly nonlinear reaction mechanisms and network dynamics. We present results for the identification of network decompositions in a simple oscillatory chemical reaction, time scale separation based model reduction in a Michaelis-Menten enzyme system and network decomposition of a detailed model for the oscillatory peroxidase-oxidase enzyme system.

Testing the monogamy relations via rank-2 mixtures

NASA Astrophysics Data System (ADS)

Jung, Eylee; Park, DaeKil

2016-10-01

We introduce two tangle-based four-party entanglement measures t1 and t2, and two negativity-based measures n1 and n2, which are derived from the monogamy relations. These measures are computed for three four-qubit maximally entangled and W states explicitly. We also compute these measures for the rank-2 mixture ρ4=p | GHZ4>< GHZ4|+(1 -p ) | W4>< W4| by finding the corresponding optimal decompositions. It turns out that t1(ρ4) is trivial and the corresponding optimal decomposition is equal to the spectral decomposition. Probably, this triviality is a sign of the fact that the corresponding monogamy inequality is not sufficiently tight. We fail to compute t2(ρ4) due to the difficulty in the calculation of the residual entanglement. The negativity-based measures n1(ρ4) and n2(ρ4) are explicitly computed and the corresponding optimal decompositions are also derived explicitly.

Multi-focus image fusion based on window empirical mode decomposition

NASA Astrophysics Data System (ADS)

Qin, Xinqiang; Zheng, Jiaoyue; Hu, Gang; Wang, Jiao

2017-09-01

In order to improve multi-focus image fusion quality, a novel fusion algorithm based on window empirical mode decomposition (WEMD) is proposed. This WEMD is an improved form of bidimensional empirical mode decomposition (BEMD), due to its decomposition process using the adding window principle, effectively resolving the signal concealment problem. We used WEMD for multi-focus image fusion, and formulated different fusion rules for bidimensional intrinsic mode function (BIMF) components and the residue component. For fusion of the BIMF components, the concept of the Sum-modified-Laplacian was used and a scheme based on the visual feature contrast adopted; when choosing the residue coefficients, a pixel value based on the local visibility was selected. We carried out four groups of multi-focus image fusion experiments and compared objective evaluation criteria with other three fusion methods. The experimental results show that the proposed fusion approach is effective and performs better at fusing multi-focus images than some traditional methods.

Distributed Prognostics based on Structural Model Decomposition

NASA Technical Reports Server (NTRS)

Daigle, Matthew J.; Bregon, Anibal; Roychoudhury, I.

2014-01-01

Within systems health management, prognostics focuses on predicting the remaining useful life of a system. In the model-based prognostics paradigm, physics-based models are constructed that describe the operation of a system and how it fails. Such approaches consist of an estimation phase, in which the health state of the system is first identified, and a prediction phase, in which the health state is projected forward in time to determine the end of life. Centralized solutions to these problems are often computationally expensive, do not scale well as the size of the system grows, and introduce a single point of failure. In this paper, we propose a novel distributed model-based prognostics scheme that formally describes how to decompose both the estimation and prediction problems into independent local subproblems whose solutions may be easily composed into a global solution. The decomposition of the prognostics problem is achieved through structural decomposition of the underlying models. The decomposition algorithm creates from the global system model a set of local submodels suitable for prognostics. Independent local estimation and prediction problems are formed based on these local submodels, resulting in a scalable distributed prognostics approach that allows the local subproblems to be solved in parallel, thus offering increases in computational efficiency. Using a centrifugal pump as a case study, we perform a number of simulation-based experiments to demonstrate the distributed approach, compare the performance with a centralized approach, and establish its scalability. Index Terms-model-based prognostics, distributed prognostics, structural model decomposition ABBREVIATIONS

Modal identification of structures by a novel approach based on FDD-wavelet method

NASA Astrophysics Data System (ADS)

Tarinejad, Reza; Damadipour, Majid

2014-02-01

An important application of system identification in structural dynamics is the determination of natural frequencies, mode shapes and damping ratios during operation which can then be used for calibrating numerical models. In this paper, the combination of two advanced methods of Operational Modal Analysis (OMA) called Frequency Domain Decomposition (FDD) and Continuous Wavelet Transform (CWT) based on novel cyclic averaging of correlation functions (CACF) technique are used for identification of dynamic properties. By using this technique, the autocorrelation of averaged correlation functions is used instead of original signals. Integration of FDD and CWT methods is used to overcome their deficiency and take advantage of the unique capabilities of these methods. The FDD method is able to accurately estimate the natural frequencies and mode shapes of structures in the frequency domain. On the other hand, the CWT method is in the time-frequency domain for decomposition of a signal at different frequencies and determines the damping coefficients. In this paper, a new formulation applied to the wavelet transform of the averaged correlation function of an ambient response is proposed. This application causes to accurate estimation of damping ratios from weak (noise) or strong (earthquake) vibrations and long or short duration record. For this purpose, the modified Morlet wavelet having two free parameters is used. The optimum values of these two parameters are obtained by employing a technique which minimizes the entropy of the wavelet coefficients matrix. The capabilities of the novel FDD-Wavelet method in the system identification of various dynamic systems with regular or irregular distribution of mass and stiffness are illustrated. This combined approach is superior to classic methods and yields results that agree well with the exact solutions of the numerical models.

Kinetic analysis of overlapping multistep thermal decomposition comprising exothermic and endothermic processes: thermolysis of ammonium dinitramide.

PubMed

Muravyev, Nikita V; Koga, Nobuyoshi; Meerov, Dmitry B; Pivkina, Alla N

2017-01-25

This study focused on kinetic modeling of a specific type of multistep heterogeneous reaction comprising exothermic and endothermic reaction steps, as exemplified by the practical kinetic analysis of the experimental kinetic curves for the thermal decomposition of molten ammonium dinitramide (ADN). It is known that the thermal decomposition of ADN occurs as a consecutive two step mass-loss process comprising the decomposition of ADN and subsequent evaporation/decomposition of in situ generated ammonium nitrate. These reaction steps provide exothermic and endothermic contributions, respectively, to the overall thermal effect. The overall reaction process was deconvoluted into two reaction steps using simultaneously recorded thermogravimetry and differential scanning calorimetry (TG-DSC) curves by considering the different physical meanings of the kinetic data derived from TG and DSC by P value analysis. The kinetic data thus separated into exothermic and endothermic reaction steps were kinetically characterized using kinetic computation methods including isoconversional method, combined kinetic analysis, and master plot method. The overall kinetic behavior was reproduced as the sum of the kinetic equations for each reaction step considering the contributions to the rate data derived from TG and DSC. During reproduction of the kinetic behavior, the kinetic parameters and contributions of each reaction step were optimized using kinetic deconvolution analysis. As a result, the thermal decomposition of ADN was successfully modeled as partially overlapping exothermic and endothermic reaction steps. The logic of the kinetic modeling was critically examined, and the practical usefulness of phenomenological modeling for the thermal decomposition of ADN was illustrated to demonstrate the validity of the methodology and its applicability to similar complex reaction processes.

Soil respiration in the cold desert environment of the Colorado Plateau (USA): Abiotic regulators and thresholds

USGS Publications Warehouse

Fernandez, D.P.; Neff, J.C.; Belnap, J.; Reynolds, R.L.

2006-01-01

Decomposition is central to understanding ecosystem carbon exchange and nutrient-release processes. Unlike mesic ecosystems, which have been extensively studied, xeric landscapes have received little attention; as a result, abiotic soil-respiration regulatory processes are poorly understood in xeric environments. To provide a more complete and quantitative understanding about how abiotic factors influence soil respiration in xeric ecosystems, we conducted soil- respiration and decomposition-cloth measurements in the cold desert of southeast Utah. Our study evaluated when and to what extent soil texture, moisture, temperature, organic carbon, and nitrogen influence soil respiration and examined whether the inverse-texture hypothesis applies to decomposition. Within our study site, the effect of texture on moisture, as described by the inverse texture hypothesis, was evident, but its effect on decomposition was not. Our results show temperature and moisture to be the dominant abiotic controls of soil respiration. Specifically, temporal offsets in temperature and moisture conditions appear to have a strong control on soil respiration, with the highest fluxes occurring in spring when temperature and moisture were favorable. These temporal offsets resulted in decomposition rates that were controlled by soil moisture and temperature thresholds. The highest fluxes of CO2 occurred when soil temperature was between 10 and 16??C and volumetric soil moisture was greater than 10%. Decomposition-cloth results, which integrate decomposition processes across several months, support the soil-respiration results and further illustrate the seasonal patterns of high respiration rates during spring and low rates during summer and fall. Results from this study suggest that the parameters used to predict soil respiration in mesic ecosystems likely do not apply in cold-desert environments. ?? Springer 2006.

An evaluation of soil chemistry in human cadaver decomposition islands: Potential for estimating postmortem interval (PMI).

PubMed

Fancher, J P; Aitkenhead-Peterson, J A; Farris, T; Mix, K; Schwab, A P; Wescott, D J; Hamilton, M D

2017-10-01

Soil samples from the Forensic Anthropology Research Facility (FARF) at Texas State University, San Marcos, TX, were analyzed for multiple soil characteristics from cadaver decomposition islands to a depth of 5centimeters (cm) from 63 human decomposition sites, as well as depths up to 15cm in a subset of 11 of the cadaver decomposition islands plus control soils. Postmortem interval (PMI) of the cadaver decomposition islands ranged from 6 to 1752 days. Some soil chemistry, including nitrate-N (NO 3 -N), ammonium-N (NH 4 -N), and dissolved inorganic carbon (DIC), peaked at early PMI values and their concentrations at 0-5cm returned to near control values over time likely due to translocation down the soil profile. Other soil chemistry, including dissolved organic carbon (DOC), dissolved organic nitrogen (DON), orthophosphate-P (PO 4 -P), sodium (Na + ), and potassium (K + ), remained higher than the control soil up to a PMI of 1752days postmortem. The body mass index (BMI) of the cadaver appeared to have some effect on the cadaver decomposition island chemistry. To estimate PMI using soil chemistry, backward, stepwise multiple regression analysis was used with PMI as the dependent variable and soil chemistry, body mass index (BMI) and physical soil characteristics such as saturated hydraulic conductivity as independent variables. Measures of soil parameters derived from predator and microbial mediated decomposition of human remains shows promise in estimating PMI to within 365days for a period up to nearly five years. This persistent change in soil chemistry extends the ability to estimate PMI beyond the traditionally utilized methods of entomology and taphonomy in support of medical-legal investigations, humanitarian recovery efforts, and criminal and civil cases. Copyright © 2017 Elsevier B.V. All rights reserved.

Fluid identification based on P-wave anisotropy dispersion gradient inversion for fractured reservoirs

NASA Astrophysics Data System (ADS)

Zhang, J. W.; Huang, H. D.; Zhu, B. H.; Liao, W.

2017-10-01

Fluid identification in fractured reservoirs is a challenging issue and has drawn increasing attentions. As aligned fractures in subsurface formations can induce anisotropy, we must choose parameters independent with azimuths to characterize fractures and fluid effects such as anisotropy parameters for fractured reservoirs. Anisotropy is often frequency dependent due to wave-induced fluid flow between pores and fractures. This property is conducive for identifying fluid type using azimuthal seismic data in fractured reservoirs. Through the numerical simulation based on Chapman model, we choose the P-wave anisotropy parameter dispersion gradient (PADG) as the new fluid factor. PADG is dependent both on average fracture radius and fluid type but independent on azimuths. When the aligned fractures in the reservoir are meter-scaled, gas-bearing layer could be accurately identified using PADG attribute. The reflection coefficient formula for horizontal transverse isotropy media by Rüger is reformulated and simplified according to frequency and the target function for inverting PADG based on frequency-dependent amplitude versus azimuth is derived. A spectral decomposition method combining Orthogonal Matching Pursuit and Wigner-Ville distribution is used to prepare the frequency-division data. Through application to synthetic data and real seismic data, the results suggest that the method is useful for gas identification in reservoirs with meter-scaled fractures using high-qualified seismic data.

Multilevel decomposition of complete vehicle configuration in a parallel computing environment

NASA Technical Reports Server (NTRS)

Bhatt, Vinay; Ragsdell, K. M.

1989-01-01

This research summarizes various approaches to multilevel decomposition to solve large structural problems. A linear decomposition scheme based on the Sobieski algorithm is selected as a vehicle for automated synthesis of a complete vehicle configuration in a parallel processing environment. The research is in a developmental state. Preliminary numerical results are presented for several example problems.

Effect of urea additive on the thermal decomposition kinetics of flame retardant greige cotton nonwoven fabric

Treesearch

Sunghyun Nam; Brian D. Condon; Robert H. White; Qi Zhao; Fei Yao; Michael Santiago Cintrón

2012-01-01

Urea is well known to have a synergistic action with phosphorus-based flame retardants (FRs) in enhancing the FR performance of cellulosic materials, but the effect of urea on the thermal decomposition kinetics has not been thoroughly studied. In this study, the activation energy (Ea) for the thermal decomposition of greige...

Evaluating litter decomposition and soil organic matter dynamics in earth system models: contrasting analysis of long-term litter decomposition and steady-state soil carbon

NASA Astrophysics Data System (ADS)

Bonan, G. B.; Wieder, W. R.

2012-12-01

Decomposition is a large term in the global carbon budget, but models of the earth system that simulate carbon cycle-climate feedbacks are largely untested with respect to litter decomposition. Here, we demonstrate a protocol to document model performance with respect to both long-term (10 year) litter decomposition and steady-state soil carbon stocks. First, we test the soil organic matter parameterization of the Community Land Model version 4 (CLM4), the terrestrial component of the Community Earth System Model, with data from the Long-term Intersite Decomposition Experiment Team (LIDET). The LIDET dataset is a 10-year study of litter decomposition at multiple sites across North America and Central America. We show results for 10-year litter decomposition simulations compared with LIDET for 9 litter types and 20 sites in tundra, grassland, and boreal, conifer, deciduous, and tropical forest biomes. We show additional simulations with DAYCENT, a version of the CENTURY model, to ask how well an established ecosystem model matches the observations. The results reveal large discrepancy between the laboratory microcosm studies used to parameterize the CLM4 litter decomposition and the LIDET field study. Simulated carbon loss is more rapid than the observations across all sites, despite using the LIDET-provided climatic decomposition index to constrain temperature and moisture effects on decomposition. Nitrogen immobilization is similarly biased high. Closer agreement with the observations requires much lower decomposition rates, obtained with the assumption that nitrogen severely limits decomposition. DAYCENT better replicates the observations, for both carbon mass remaining and nitrogen, without requirement for nitrogen limitation of decomposition. Second, we compare global observationally-based datasets of soil carbon with simulated steady-state soil carbon stocks for both models. The models simulations were forced with observationally-based estimates of annual litterfall and model-derived climatic decomposition index. While comparison with the LIDET 10-year litterbag study reveals sharp contrasts between CLM4 and DAYCENT, simulations of steady-state soil carbon show less difference between models. Both CLM4 and DAYCENT significantly underestimate soil carbon. Sensitivity analyses highlight causes of the low soil carbon bias. The terrestrial biogeochemistry of earth system models must be critically tested with observations, and the consequences of particular model choices must be documented. Long-term litter decomposition experiments such as LIDET provide a real-world process-oriented benchmark to evaluate models and can critically inform model development. Analysis of steady-state soil carbon estimates reveal additional, but here different, inferences about model performance.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Espinosa-Paredes, Gilberto; Prieto-Guerrero, Alfonso; Nunez-Carrera, Alejandro

This paper introduces a wavelet-based method to analyze instability events in a boiling water reactor (BWR) during transient phenomena. The methodology to analyze BWR signals includes the following: (a) the short-time Fourier transform (STFT) analysis, (b) decomposition using the continuous wavelet transform (CWT), and (c) application of multiresolution analysis (MRA) using discrete wavelet transform (DWT). STFT analysis permits the study, in time, of the spectral content of analyzed signals. The CWT provides information about ruptures, discontinuities, and fractal behavior. To detect these important features in the signal, a mother wavelet has to be chosen and applied at several scales tomore » obtain optimum results. MRA allows fast implementation of the DWT. Features like important frequencies, discontinuities, and transients can be detected with analysis at different levels of detail coefficients. The STFT was used to provide a comparison between a classic method and the wavelet-based method. The damping ratio, which is an important stability parameter, was calculated as a function of time. The transient behavior can be detected by analyzing the maximum contained in detail coefficients at different levels in the signal decomposition. This method allows analysis of both stationary signals and highly nonstationary signals in the timescale plane. This methodology has been tested with the benchmark power instability event of Laguna Verde nuclear power plant (NPP) Unit 1, which is a BWR-5 NPP.« less

DFT and ab initio study of the unimolecular decomposition of the lowest singlet and triplet states of nitromethane

DOE Office of Scientific and Technical Information (OSTI.GOV)

Manaa, M.R.; Fried, L.E.

1998-11-26

The fully optimized potential energy curves for the unimolecular decomposition of the lowest singlet and triplet states of nitromethane through the C-NO{sub 2} bond dissociation pathway are calculated using various DFT and high-level ab initio electronic structure methods. The authors perform gradient corrected density functional theory (DFT) and multiconfiguration self-consistent field (MCSCF) to conclusively demonstrate that the triplet state of nitromethane is bound. The adiabatic curve of this state exhibits a 33 kcal/mol energy barrier as determined at the MCSCF level. DFT methods locate this barrier at a shorter C-N bond distance with 12--16 kcal/mol lower energy than does MCSCF.more » In addition to MCSCF and DFT, quadratic configuration interactions with single and double substitutions (QCISD) calculations are also performed for the singlet curve. The potential energy profiles of this state predicted by FT methods based on Becke`s 1988 exchange functional differ by as much as 17 kcal/mol from the predictions of MCSCF and QCISD in the vicinity of the equilibrium structure. The computational methods predict bond dissociation energies 5--9 kcal/mol lower than the experimental value. DFT techniques based on Becke`s 3-parameter exchange functional show the best overall agreement with the higher level methods.« less

Flood predictions using the parallel version of distributed numerical physical rainfall-runoff model TOPKAPI

NASA Astrophysics Data System (ADS)

Boyko, Oleksiy; Zheleznyak, Mark

2015-04-01

The original numerical code TOPKAPI-IMMS of the distributed rainfall-runoff model TOPKAPI ( Todini et al, 1996-2014) is developed and implemented in Ukraine. The parallel version of the code has been developed recently to be used on multiprocessors systems - multicore/processors PC and clusters. Algorithm is based on binary-tree decomposition of the watershed for the balancing of the amount of computation for all processors/cores. Message passing interface (MPI) protocol is used as a parallel computing framework. The numerical efficiency of the parallelization algorithms is demonstrated for the case studies for the flood predictions of the mountain watersheds of the Ukrainian Carpathian regions. The modeling results is compared with the predictions based on the lumped parameters models.

Regularization strategies for hyperplane classifiers: application to cancer classification with gene expression data.

PubMed

Andries, Erik; Hagstrom, Thomas; Atlas, Susan R; Willman, Cheryl

2007-02-01

Linear discrimination, from the point of view of numerical linear algebra, can be treated as solving an ill-posed system of linear equations. In order to generate a solution that is robust in the presence of noise, these problems require regularization. Here, we examine the ill-posedness involved in the linear discrimination of cancer gene expression data with respect to outcome and tumor subclasses. We show that a filter factor representation, based upon Singular Value Decomposition, yields insight into the numerical ill-posedness of the hyperplane-based separation when applied to gene expression data. We also show that this representation yields useful diagnostic tools for guiding the selection of classifier parameters, thus leading to improved performance.

Ambient Vibration Testing for Story Stiffness Estimation of a Heritage Timber Building

PubMed Central

Min, Kyung-Won; Kim, Junhee; Park, Sung-Ah; Park, Chan-Soo

2013-01-01

This paper investigates dynamic characteristics of a historic wooden structure by ambient vibration testing, presenting a novel estimation methodology of story stiffness for the purpose of vibration-based structural health monitoring. As for the ambient vibration testing, measured structural responses are analyzed by two output-only system identification methods (i.e., frequency domain decomposition and stochastic subspace identification) to estimate modal parameters. The proposed methodology of story stiffness is estimation based on an eigenvalue problem derived from a vibratory rigid body model. Using the identified natural frequencies, the eigenvalue problem is efficiently solved and uniquely yields story stiffness. It is noteworthy that application of the proposed methodology is not necessarily confined to the wooden structure exampled in the paper. PMID:24227999

Sulfur capture under periodically changing oxidizing and reducing conditions in PFBC

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zevenhoven, R.; Yrjas, P.; Hupa, M.

1999-07-01

During in situ sulfur capture with a calcium-based sorbent in fluidized bed combustion (FBC), a temperature optimum is found, at atmospheric pressure, at {approximately}850 C. The repeated decomposition of sulfated limestone during stages where the gas atmosphere surrounding the sorbent particle is not oxidizing but reducing has been identified to explain this maximum. Under pressurized (PFBC) conditions, an additional aspect is the direct conversion of calcium carbonate (CaCO{sub 3}) without the intermediate calcium oxide (CaO) due to the partial pressure of carbon dioxide (CO{sub 2}). In this work it was evaluated how stable calcium sulfate (CaSO{sub 4}) is in amore » gas atmosphere that periodically changes from oxidizing to reducing and vice versa. Atmospheric as well as elevated pressures are considered. CaO or CaCO{sub 3}, and/or calcium sulfide (CaS) are formed during the reducing stage. Using a pressurized thermogravimetric reactor (PTGR) a limestone was periodically sulfated under oxidizing conditions and decomposed under reducing conditions with carbon monoxide (CO), or with CO + H{sub 2} (hydrogen). Experiments at 1 bar and 15 bar were carried out, at temperatures from 850 C to 950 C, at C O and CO + H{sub 2} concentrations up to 4%-vol. The experimental data were modeled using simple first order (parallel) reaction schemes that allowed for sorbent structure changes. This gave rate parameters for the sulfation and the decomposition reactions, and identified the decomposition products. It was found that 1 bar, CO + H{sub 2} gives a higher reduction of CaSO{sub 4} than CO, at the same total concentration. The rate of decomposition increases faster with temperature than the sulfation, explaining the sulfation efficiency maximum mentioned above. At 15 bar, a different picture is seen. The reductive decomposition rate as well as the sulfation rate are slower, with CO as well as CO with small amounts of H{sub 2} as the reducing species. There is a significant effect of the water which is present in the gas at higher concentrations than H{sub 2}. Thermodynamics indicate that this leads to the decomposition of CaS, releasing H{sub 2}S.« less

Domain decomposition for aerodynamic and aeroacoustic analyses, and optimization

NASA Technical Reports Server (NTRS)

Baysal, Oktay

1995-01-01

The overarching theme was the domain decomposition, which intended to improve the numerical solution technique for the partial differential equations at hand; in the present study, those that governed either the fluid flow, or the aeroacoustic wave propagation, or the sensitivity analysis for a gradient-based optimization. The role of the domain decomposition extended beyond the original impetus of discretizing geometrical complex regions or writing modular software for distributed-hardware computers. It induced function-space decompositions and operator decompositions that offered the valuable property of near independence of operator evaluation tasks. The objectives have gravitated about the extensions and implementations of either the previously developed or concurrently being developed methodologies: (1) aerodynamic sensitivity analysis with domain decomposition (SADD); (2) computational aeroacoustics of cavities; and (3) dynamic, multibody computational fluid dynamics using unstructured meshes.

Uncertainty propagation by using spectral methods: A practical application to a two-dimensional turbulence fluid model

NASA Astrophysics Data System (ADS)

Riva, Fabio; Milanese, Lucio; Ricci, Paolo

2017-10-01

To reduce the computational cost of the uncertainty propagation analysis, which is used to study the impact of input parameter variations on the results of a simulation, a general and simple to apply methodology based on decomposing the solution to the model equations in terms of Chebyshev polynomials is discussed. This methodology, based on the work by Scheffel [Am. J. Comput. Math. 2, 173-193 (2012)], approximates the model equation solution with a semi-analytic expression that depends explicitly on time, spatial coordinates, and input parameters. By employing a weighted residual method, a set of nonlinear algebraic equations for the coefficients appearing in the Chebyshev decomposition is then obtained. The methodology is applied to a two-dimensional Braginskii model used to simulate plasma turbulence in basic plasma physics experiments and in the scrape-off layer of tokamaks, in order to study the impact on the simulation results of the input parameter that describes the parallel losses. The uncertainty that characterizes the time-averaged density gradient lengths, time-averaged densities, and fluctuation density level are evaluated. A reasonable estimate of the uncertainty of these distributions can be obtained with a single reduced-cost simulation.

ARMA Cholesky Factor Models for the Covariance Matrix of Linear Models.

PubMed

Lee, Keunbaik; Baek, Changryong; Daniels, Michael J

2017-11-01

In longitudinal studies, serial dependence of repeated outcomes must be taken into account to make correct inferences on covariate effects. As such, care must be taken in modeling the covariance matrix. However, estimation of the covariance matrix is challenging because there are many parameters in the matrix and the estimated covariance matrix should be positive definite. To overcomes these limitations, two Cholesky decomposition approaches have been proposed: modified Cholesky decomposition for autoregressive (AR) structure and moving average Cholesky decomposition for moving average (MA) structure, respectively. However, the correlations of repeated outcomes are often not captured parsimoniously using either approach separately. In this paper, we propose a class of flexible, nonstationary, heteroscedastic models that exploits the structure allowed by combining the AR and MA modeling of the covariance matrix that we denote as ARMACD. We analyze a recent lung cancer study to illustrate the power of our proposed methods.

Neural image analysis for estimating aerobic and anaerobic decomposition of organic matter based on the example of straw decomposition

NASA Astrophysics Data System (ADS)

Boniecki, P.; Nowakowski, K.; Slosarz, P.; Dach, J.; Pilarski, K.

2012-04-01

The purpose of the project was to identify the degree of organic matter decomposition by means of a neural model based on graphical information derived from image analysis. Empirical data (photographs of compost content at various stages of maturation) were used to generate an optimal neural classifier (Boniecki et al. 2009, Nowakowski et al. 2009). The best classification properties were found in an RBF (Radial Basis Function) artificial neural network, which demonstrates that the process is non-linear.

Genetics algorithm optimization of DWT-DCT based image Watermarking

NASA Astrophysics Data System (ADS)

Budiman, Gelar; Novamizanti, Ledya; Iwut, Iwan

2017-01-01

Data hiding in an image content is mandatory for setting the ownership of the image. Two dimensions discrete wavelet transform (DWT) and discrete cosine transform (DCT) are proposed as transform method in this paper. First, the host image in RGB color space is converted to selected color space. We also can select the layer where the watermark is embedded. Next, 2D-DWT transforms the selected layer obtaining 4 subband. We select only one subband. And then block-based 2D-DCT transforms the selected subband. Binary-based watermark is embedded on the AC coefficients of each block after zigzag movement and range based pixel selection. Delta parameter replacing pixels in each range represents embedded bit. +Delta represents bit “1” and -delta represents bit “0”. Several parameters to be optimized by Genetics Algorithm (GA) are selected color space, layer, selected subband of DWT decomposition, block size, embedding range, and delta. The result of simulation performs that GA is able to determine the exact parameters obtaining optimum imperceptibility and robustness, in any watermarked image condition, either it is not attacked or attacked. DWT process in DCT based image watermarking optimized by GA has improved the performance of image watermarking. By five attacks: JPEG 50%, resize 50%, histogram equalization, salt-pepper and additive noise with variance 0.01, robustness in the proposed method has reached perfect watermark quality with BER=0. And the watermarked image quality by PSNR parameter is also increased about 5 dB than the watermarked image quality from previous method.

Physics-based, Bayesian sequential detection method and system for radioactive contraband

DOEpatents

Candy, James V; Axelrod, Michael C; Breitfeller, Eric F; Chambers, David H; Guidry, Brian L; Manatt, Douglas R; Meyer, Alan W; Sale, Kenneth E

2014-03-18

A distributed sequential method and system for detecting and identifying radioactive contraband from highly uncertain (noisy) low-count, radionuclide measurements, i.e. an event mode sequence (EMS), using a statistical approach based on Bayesian inference and physics-model-based signal processing based on the representation of a radionuclide as a monoenergetic decomposition of monoenergetic sources. For a given photon event of the EMS, the appropriate monoenergy processing channel is determined using a confidence interval condition-based discriminator for the energy amplitude and interarrival time and parameter estimates are used to update a measured probability density function estimate for a target radionuclide. A sequential likelihood ratio test is then used to determine one of two threshold conditions signifying that the EMS is either identified as the target radionuclide or not, and if not, then repeating the process for the next sequential photon event of the EMS until one of the two threshold conditions is satisfied.

A Comparison of Galaxy Bulge+Disk Decomposition Between Pan-STARRS and SDSS

NASA Astrophysics Data System (ADS)

Lokken, Martine Elena; McPartland, Conor; Sanders, David B.

2018-01-01

Measurements of the size and shape of bulges in galaxies provide key constraints for models of galaxy evolution. A comprehensive catalog of bulge measurements for Sloan Digital Sky Survey (SDSS) DR7 galaxies is currently available to the public. However, the Pan-STARRS1 (PS1) 3π survey now covers the same region with ~1-2 mag deeper photometry, a ~10-30% smaller PSF, and additional coverage in y-band. To test how much improvement in galaxy parameter measurements (e.g. bulge + disk) can be achieved using the new PS1 data, we make use of ultra-deep imaging data from the Hyper Suprime-Cam (HSC) Subaru Strategic Program (SSP). We fit bulge+disk models to images of 372 bright (mi < 18.5) galaxies detected in all three surveys. Comparison of galaxy parameters derived from SDSS and PS1 images with those measured from HSC-SSP images shows a tighter correlation between PS1 and SSP measurements for both bulge and disk parameters. Bulge parameters, such as bulge-to-total fraction and bulge radius, show the strongest improvement. However, measurements of all parameters degrade for galaxies with total r-band magnitude below the SDSS spectroscopic limit, mr = 17.7. We plan to use the PS1 3π survey data to produce an updated catalog of bulge+disk decomposition measurements for the entire SDSS DR7 spectroscopic galaxy sample.

Soil C and N availability determine the priming effect: microbial N mining and stoichiometric decomposition theories.

PubMed

Chen, Ruirui; Senbayram, Mehmet; Blagodatsky, Sergey; Myachina, Olga; Dittert, Klaus; Lin, Xiangui; Blagodatskaya, Evgenia; Kuzyakov, Yakov

2014-07-01

The increasing input of anthropogenically derived nitrogen (N) to ecosystems raises a crucial question: how does available N modify the decomposer community and thus affects the mineralization of soil organic matter (SOM). Moreover, N input modifies the priming effect (PE), that is, the effect of fresh organics on the microbial decomposition of SOM. We studied the interactive effects of C and N on SOM mineralization (by natural (13) C labelling adding C4 -sucrose or C4 -maize straw to C3 -soil) in relation to microbial growth kinetics and to the activities of five hydrolytic enzymes. This encompasses the groups of parameters governing two mechanisms of priming effects - microbial N mining and stoichiometric decomposition theories. In sole C treatments, positive PE was accompanied by a decrease in specific microbial growth rates, confirming a greater contribution of K-strategists to the decomposition of native SOM. Sucrose addition with N significantly accelerated mineralization of native SOM, whereas mineral N added with plant residues accelerated decomposition of plant residues. This supports the microbial mining theory in terms of N limitation. Sucrose addition with N was accompanied by accelerated microbial growth, increased activities of β-glucosidase and cellobiohydrolase, and decreased activities of xylanase and leucine amino peptidase. This indicated an increased contribution of r-strategists to the PE and to decomposition of cellulose but the decreased hemicellulolytic and proteolytic activities. Thus, the acceleration of the C cycle was primed by exogenous organic C and was controlled by N. This confirms the stoichiometric decomposition theory. Both K- and r-strategists were beneficial for priming effects, with an increasing contribution of K-selected species under N limitation. Thus, the priming phenomenon described in 'microbial N mining' theory can be ascribed to K-strategists. In contrast, 'stoichiometric decomposition' theory, that is, accelerated OM mineralization due to balanced microbial growth, is explained by domination of r-strategists. © 2013 John Wiley & Sons Ltd.

Soil C and N availability determine the priming effect: microbial N mining and stoichiometric decomposition theories

NASA Astrophysics Data System (ADS)

Chen, Ruirui; Senbayram, Mehmet; Blagodatsky, Sergey; Dittert, Klaus; Lin, Xiangui; Blagodatskaya, Evgenia; Kuzyakov, Yakov

2014-05-01

The increasing input of anthropogenically derived nitrogen (N) to ecosystems raises a crucial question: how does available N modify the decomposer community and thus affects the mineralization of soil organic matter (SOM). Moreover, N input modifies the priming effect (PE), that is, the effect of fresh organics on the microbial decomposition of SOM. We studied the interactive effects of C and N on SOM mineralization (by natural 13C labelling adding C4-sucrose or C4-maize straw to C3-soil) in relation to microbial growth kinetics and to the activities of five hydrolytic enzymes. This encompasses the groups of parameters governing two mechanisms of priming effects - microbial N mining and stoichiometric decomposition theories. In sole C treatments, positive PE was accompanied by a decrease in specific microbial growth rates, confirming a greater contribution of K-strategists to the decomposition of native SOM. Sucrose addition with N significantly accelerated mineralization of native SOM, whereas mineral N added with plant residues accelerated decomposition of plant residues. This supports the microbial mining theory in terms of N limitation. Sucrose addition with N was accompanied by accelerated microbial growth, increased activities of β-glucosidase and cellobiohydrolase, and decreased activities of xylanase and leucine amino peptidase. This indicated an increased contribution of r-strategists to the PE and to decomposition of cellulose but the decreased hemicellulolytic and proteolytic activities. Thus, the acceleration of the C cycle was primed by exogenous organic C and was controlled by N. This confirms the stoichiometric decomposition theory. Both K- and r-strategists were beneficial for priming effects, with an increasing contribution of K-selected species under N limitation. Thus, the priming phenomenon described in 'microbial N mining' theory can be ascribed to K-strategists. In contrast, 'stoichiometric decomposition' theory, that is, accelerated OM mineralization due to balanced microbial growth, is explained by domination of r-strategists.

Eutrophication triggers contrasting multilevel feedbacks on litter accumulation and decomposition in fens.

PubMed

Emsens, W-J; Aggenbach, C J S; Grootjans, A P; Nfor, E E; Schoelynck, J; Struyf, E; van Diggelen, R

2016-10-01

Eutrophication is a major threat for the persistence of nutrient-poor fens, as multilevel feedbacks on decomposition rates could trigger carbon loss and increase nutrient cycling. Here, we experimentally investigate the effects of macronutrient (NPK) enrichment on litter quality of six species of sedge (Carex sp.), which we relate to litter decomposition rates in a nutrient-poor and nutrient-rich environment. Our research focused on four levels: we examined how eutrophication alters (1) fresh litter production ("productivity shift"), (2) litter stoichiometry within the same species ("intraspecific shift"), (3) overall litter stoichiometry of the vegetation under the prediction that low-competitive species are outcompeted by fast-growing competitors ("interspecific shift"), and (4) litter decomposition rates due to an altered external environment (e.g., shifts in microbial activity; "exogenous shift"). Eutrophication triggered a strong increase in fresh litter production. Moreover, individuals of the same species produced litter with lower C:N and C:P ratios, higher K contents, and lower lignin, Ca and Mg contents (intraspecific shift), which increased litter decomposability. In addition, species typical for eutrophic conditions produced more easily degradable litter than did species typical for nutrient-poor conditions (interspecific shift). However, the effects of nutrient loading of the external environment (exogenous shift) were contradictory. Here, interactions between litter type and ambient nutrient level indicate that the (exogenous) effects of eutrophication on litter decomposition rates are strongly dependent of litter quality. Moreover, parameters of litter quality only correlated with decomposition rates for litter incubated in nutrient-poor environments, but not in eutrophic environments. This suggests that rates of litter decomposition can be uncoupled from litter stoichiometry under eutrophic conditions. In conclusion, our results show that eutrophication affects litter accumulation and -decomposition at multiple levels, in which stimulatory and inhibitory effects interact. The cumulative effect of these interactions ultimately determine whether peatlands remain sinks or become sources of carbon under eutrophic conditions. © 2016 by the Ecological Society of America.

Comparing the Scoring of Human Decomposition from Digital Images to Scoring Using On-site Observations.

PubMed

Dabbs, Gretchen R; Bytheway, Joan A; Connor, Melissa

2017-09-01

When in forensic casework or empirical research in-person assessment of human decomposition is not possible, the sensible substitution is color photographic images. To date, no research has confirmed the utility of color photographic images as a proxy for in situ observation of the level of decomposition. Sixteen observers scored photographs of 13 human cadavers in varying decomposition stages (PMI 2-186 days) using the Total Body Score system (total n = 929 observations). The on-site TBS was compared with recorded observations from digital color images using a paired samples t-test. The average difference between on-site and photographic observations was -0.20 (t = -1.679, df = 928, p = 0.094). Individually, only two observers, both students with <1 year of experience, demonstrated TBS statistically significantly different than the on-site value, suggesting that with experience, observations of human decomposition based on digital images can be substituted for assessments based on observation of the corpse in situ, when necessary. © 2017 American Academy of Forensic Sciences.

Augmenting the decomposition of EMG signals using supervised feature extraction techniques.

PubMed

Parsaei, Hossein; Gangeh, Mehrdad J; Stashuk, Daniel W; Kamel, Mohamed S

2012-01-01

Electromyographic (EMG) signal decomposition is the process of resolving an EMG signal into its constituent motor unit potential trains (MUPTs). In this work, the possibility of improving the decomposing results using two supervised feature extraction methods, i.e., Fisher discriminant analysis (FDA) and supervised principal component analysis (SPCA), is explored. Using the MUP labels provided by a decomposition-based quantitative EMG system as a training data for FDA and SPCA, the MUPs are transformed into a new feature space such that the MUPs of a single MU become as close as possible to each other while those created by different MUs become as far as possible. The MUPs are then reclassified using a certainty-based classification algorithm. Evaluation results using 10 simulated EMG signals comprised of 3-11 MUPTs demonstrate that FDA and SPCA on average improve the decomposition accuracy by 6%. The improvement for the most difficult-to-decompose signal is about 12%, which shows the proposed approach is most beneficial in the decomposition of more complex signals.

Algorithms for Spectral Decomposition with Applications to Optical Plume Anomaly Detection

NASA Technical Reports Server (NTRS)

Srivastava, Askok N.; Matthews, Bryan; Das, Santanu

2008-01-01

The analysis of spectral signals for features that represent physical phenomenon is ubiquitous in the science and engineering communities. There are two main approaches that can be taken to extract relevant features from these high-dimensional data streams. The first set of approaches relies on extracting features using a physics-based paradigm where the underlying physical mechanism that generates the spectra is used to infer the most important features in the data stream. We focus on a complementary methodology that uses a data-driven technique that is informed by the underlying physics but also has the ability to adapt to unmodeled system attributes and dynamics. We discuss the following four algorithms: Spectral Decomposition Algorithm (SDA), Non-Negative Matrix Factorization (NMF), Independent Component Analysis (ICA) and Principal Components Analysis (PCA) and compare their performance on a spectral emulator which we use to generate artificial data with known statistical properties. This spectral emulator mimics the real-world phenomena arising from the plume of the space shuttle main engine and can be used to validate the results that arise from various spectral decomposition algorithms and is very useful for situations where real-world systems have very low probabilities of fault or failure. Our results indicate that methods like SDA and NMF provide a straightforward way of incorporating prior physical knowledge while NMF with a tuning mechanism can give superior performance on some tests. We demonstrate these algorithms to detect potential system-health issues on data from a spectral emulator with tunable health parameters.

Robust/optimal temperature profile control of a high-speed aerospace vehicle using neural networks.

PubMed

Yadav, Vivek; Padhi, Radhakant; Balakrishnan, S N

2007-07-01

An approximate dynamic programming (ADP)-based suboptimal neurocontroller to obtain desired temperature for a high-speed aerospace vehicle is synthesized in this paper. A 1-D distributed parameter model of a fin is developed from basic thermal physics principles. "Snapshot" solutions of the dynamics are generated with a simple dynamic inversion-based feedback controller. Empirical basis functions are designed using the "proper orthogonal decomposition" (POD) technique and the snapshot solutions. A low-order nonlinear lumped parameter system to characterize the infinite dimensional system is obtained by carrying out a Galerkin projection. An ADP-based neurocontroller with a dual heuristic programming (DHP) formulation is obtained with a single-network-adaptive-critic (SNAC) controller for this approximate nonlinear model. Actual control in the original domain is calculated with the same POD basis functions through a reverse mapping. Further contribution of this paper includes development of an online robust neurocontroller to account for unmodeled dynamics and parametric uncertainties inherent in such a complex dynamic system. A neural network (NN) weight update rule that guarantees boundedness of the weights and relaxes the need for persistence of excitation (PE) condition is presented. Simulation studies show that in a fairly extensive but compact domain, any desired temperature profile can be achieved starting from any initial temperature profile. Therefore, the ADP and NN-based controllers appear to have the potential to become controller synthesis tools for nonlinear distributed parameter systems.

Partial differential equation-based approach for empirical mode decomposition: application on image analysis.

PubMed

Niang, Oumar; Thioune, Abdoulaye; El Gueirea, Mouhamed Cheikh; Deléchelle, Eric; Lemoine, Jacques

2012-09-01

The major problem with the empirical mode decomposition (EMD) algorithm is its lack of a theoretical framework. So, it is difficult to characterize and evaluate this approach. In this paper, we propose, in the 2-D case, the use of an alternative implementation to the algorithmic definition of the so-called "sifting process" used in the original Huang's EMD method. This approach, especially based on partial differential equations (PDEs), was presented by Niang in previous works, in 2005 and 2007, and relies on a nonlinear diffusion-based filtering process to solve the mean envelope estimation problem. In the 1-D case, the efficiency of the PDE-based method, compared to the original EMD algorithmic version, was also illustrated in a recent paper. Recently, several 2-D extensions of the EMD method have been proposed. Despite some effort, 2-D versions for EMD appear poorly performing and are very time consuming. So in this paper, an extension to the 2-D space of the PDE-based approach is extensively described. This approach has been applied in cases of both signal and image decomposition. The obtained results confirm the usefulness of the new PDE-based sifting process for the decomposition of various kinds of data. Some results have been provided in the case of image decomposition. The effectiveness of the approach encourages its use in a number of signal and image applications such as denoising, detrending, or texture analysis.

On the reliable and flexible solution of practical subset regression problems

NASA Technical Reports Server (NTRS)

Verhaegen, M. H.

1987-01-01

A new algorithm for solving subset regression problems is described. The algorithm performs a QR decomposition with a new column-pivoting strategy, which permits subset selection directly from the originally defined regression parameters. This, in combination with a number of extensions of the new technique, makes the method a very flexible tool for analyzing subset regression problems in which the parameters have a physical meaning.

Denoising of Raman spectroscopy for biological samples based on empirical mode decomposition

NASA Astrophysics Data System (ADS)

León-Bejarano, Fabiola; Ramírez-Elías, Miguel; Mendez, Martin O.; Dorantes-Méndez, Guadalupe; Rodríguez-Aranda, Ma. Del Carmen; Alba, Alfonso

Raman spectroscopy of biological samples presents undesirable noise and fluorescence generated by the biomolecular excitation. The reduction of these types of noise is a fundamental task to obtain the valuable information of the sample under analysis. This paper proposes the application of the empirical mode decomposition (EMD) for noise elimination. EMD is a parameter-free and adaptive signal processing method useful for the analysis of nonstationary signals. EMD performance was compared with the commonly used Vancouver algorithm (VRA) through artificial data (Teflon), synthetic (Vitamin E and paracetamol) and biological (Mouse brain and human nails) Raman spectra. The correlation coefficient (ρ) was used as performance measure. Results on synthetic data showed a better performance of EMD (ρ=0.52) at high noise levels compared with VRA (ρ=0.19). The methods with simulated fluorescence added to artificial material exhibited a similar shape of fluorescence in both cases (ρ=0.95 for VRA and ρ=0.93 for EMD). For synthetic data, Raman spectra of vitamin E were used and the results showed a good performance comparing both methods (ρ=0.95 for EMD and ρ=0.99 for VRA). Finally, in biological data, EMD and VRA displayed a similar behavior (ρ=0.85 for EMD and ρ=0.96 for VRA), but with the advantage that EMD maintains small amplitude Raman peaks. The results suggest that EMD could be an effective method for denoising biological Raman spectra, EMD is able to retain information and correctly eliminates the fluorescence without parameter tuning.

Co-pyrolysis of biomass and plastic wastes: investigation of apparent kinetic parameters and stability of pyrolysis oils

NASA Astrophysics Data System (ADS)

Fekhar, B.; Miskolczi, N.; Bhaskar, T.; Kumar, J.; Dhyani, V.

2018-05-01

This work is dedicated to the co-pyrolysis of real waste high density polyethylene (HDPE) and biomass (rice straw) obtained from agriculture. Mixtures of raw materials were pyrolyzed in their 0%/100%, 30%/70%, 50%/50%, 70%/30%, 100%/0% ratios using a thermograph. The atmosphere was nitrogen, and a constant heating rate was used. Based on weight loss and DTG curves, the apparent reaction kinetic parameters (e.g., activation energy) were calculated using first-order kinetic approach and Arrhenius equation. It was found that decomposition of pure plastic has approximately 280 kJ/mol activation energy, while that of was considerably less in case of biomass. Furthermore, HDPE decomposition takes by one stage, while that of biomass was three stages. The larger amount of raw materials (100 g) were also pyrolyzed in the batch rig at 550°C to obtain products for analysis focussing to their long-term application. Pyrolysis oils were investigated by Fourier transformed infrared spectroscopy and standardized methods, such as density, viscosity, boiling range determination. It was concluded, that higher plastic ratio in raw material had the advantageous effect to the pyrolysis oil long-term application. E.g., the concentration of oxygenated compounds, such as aldehydes, ketones, carboxylic acids or even phenol and its derivate could be significantly decreased, which had an advantageous effect to their corrosion property. Lower average molecular weight, viscosity, and density were measured as a function of plastic content.

Global sensitivity analysis for fuzzy inputs based on the decomposition of fuzzy output entropy

NASA Astrophysics Data System (ADS)

Shi, Yan; Lu, Zhenzhou; Zhou, Yicheng

2018-06-01

To analyse the component of fuzzy output entropy, a decomposition method of fuzzy output entropy is first presented. After the decomposition of fuzzy output entropy, the total fuzzy output entropy can be expressed as the sum of the component fuzzy entropy contributed by fuzzy inputs. Based on the decomposition of fuzzy output entropy, a new global sensitivity analysis model is established for measuring the effects of uncertainties of fuzzy inputs on the output. The global sensitivity analysis model can not only tell the importance of fuzzy inputs but also simultaneously reflect the structural composition of the response function to a certain degree. Several examples illustrate the validity of the proposed global sensitivity analysis, which is a significant reference in engineering design and optimization of structural systems.

A novel ECG data compression method based on adaptive Fourier decomposition

NASA Astrophysics Data System (ADS)

Tan, Chunyu; Zhang, Liming

2017-12-01

This paper presents a novel electrocardiogram (ECG) compression method based on adaptive Fourier decomposition (AFD). AFD is a newly developed signal decomposition approach, which can decompose a signal with fast convergence, and hence reconstruct ECG signals with high fidelity. Unlike most of the high performance algorithms, our method does not make use of any preprocessing operation before compression. Huffman coding is employed for further compression. Validated with 48 ECG recordings of MIT-BIH arrhythmia database, the proposed method achieves the compression ratio (CR) of 35.53 and the percentage root mean square difference (PRD) of 1.47% on average with N = 8 decomposition times and a robust PRD-CR relationship. The results demonstrate that the proposed method has a good performance compared with the state-of-the-art ECG compressors.

Integrated Network Decompositions and Dynamic Programming for Graph Optimization (INDDGO)

DOE Office of Scientific and Technical Information (OSTI.GOV)

The INDDGO software package offers a set of tools for finding exact solutions to graph optimization problems via tree decompositions and dynamic programming algorithms. Currently the framework offers serial and parallel (distributed memory) algorithms for finding tree decompositions and solving the maximum weighted independent set problem. The parallel dynamic programming algorithm is implemented on top of the MADNESS task-based runtime.

An inductance Fourier decomposition-based current-hysteresis control strategy for switched reluctance motors

NASA Astrophysics Data System (ADS)

Hua, Wei; Qi, Ji; Jia, Meng

2017-05-01

Switched reluctance machines (SRMs) have attracted extensive attentions due to the inherent advantages, including simple and robust structure, low cost, excellent fault-tolerance and wide speed range, etc. However, one of the bottlenecks limiting the SRMs for further applications is its unfavorable torque ripple, and consequently noise and vibration due to the unique doubly-salient structure and pulse-current-based power supply method. In this paper, an inductance Fourier decomposition-based current-hysteresis-control (IFD-CHC) strategy is proposed to reduce torque ripple of SRMs. After obtaining a nonlinear inductance-current-position model based Fourier decomposition, reference currents can be calculated by reference torque and the derived inductance model. Both the simulations and experimental results confirm the effectiveness of the proposed strategy.

Defect Detection in Textures through the Use of Entropy as a Means for Automatically Selecting the Wavelet Decomposition Level.

PubMed

Navarro, Pedro J; Fernández-Isla, Carlos; Alcover, Pedro María; Suardíaz, Juan

2016-07-27

This paper presents a robust method for defect detection in textures, entropy-based automatic selection of the wavelet decomposition level (EADL), based on a wavelet reconstruction scheme, for detecting defects in a wide variety of structural and statistical textures. Two main features are presented. One of the new features is an original use of the normalized absolute function value (NABS) calculated from the wavelet coefficients derived at various different decomposition levels in order to identify textures where the defect can be isolated by eliminating the texture pattern in the first decomposition level. The second is the use of Shannon's entropy, calculated over detail subimages, for automatic selection of the band for image reconstruction, which, unlike other techniques, such as those based on the co-occurrence matrix or on energy calculation, provides a lower decomposition level, thus avoiding excessive degradation of the image, allowing a more accurate defect segmentation. A metric analysis of the results of the proposed method with nine different thresholding algorithms determined that selecting the appropriate thresholding method is important to achieve optimum performance in defect detection. As a consequence, several different thresholding algorithms depending on the type of texture are proposed.

Dominant modal decomposition method

NASA Astrophysics Data System (ADS)

Dombovari, Zoltan

2017-03-01

The paper deals with the automatic decomposition of experimental frequency response functions (FRF's) of mechanical structures. The decomposition of FRF's is based on the Green function representation of free vibratory systems. After the determination of the impulse dynamic subspace, the system matrix is formulated and the poles are calculated directly. By means of the corresponding eigenvectors, the contribution of each element of the impulse dynamic subspace is determined and the sufficient decomposition of the corresponding FRF is carried out. With the presented dominant modal decomposition (DMD) method, the mode shapes, the modal participation vectors and the modal scaling factors are identified using the decomposed FRF's. Analytical example is presented along with experimental case studies taken from machine tool industry.

About decomposition approach for solving the classification problem

NASA Astrophysics Data System (ADS)

Andrianova, A. A.

2016-11-01

This article describes the features of the application of an algorithm with using of decomposition methods for solving the binary classification problem of constructing a linear classifier based on Support Vector Machine method. Application of decomposition reduces the volume of calculations, in particular, due to the emerging possibilities to build parallel versions of the algorithm, which is a very important advantage for the solution of problems with big data. The analysis of the results of computational experiments conducted using the decomposition approach. The experiment use known data set for binary classification problem.

Data-Driven H∞ Control for Nonlinear Distributed Parameter Systems.

PubMed

Luo, Biao; Huang, Tingwen; Wu, Huai-Ning; Yang, Xiong

2015-11-01

The data-driven H∞ control problem of nonlinear distributed parameter systems is considered in this paper. An off-policy learning method is developed to learn the H∞ control policy from real system data rather than the mathematical model. First, Karhunen-Loève decomposition is used to compute the empirical eigenfunctions, which are then employed to derive a reduced-order model (ROM) of slow subsystem based on the singular perturbation theory. The H∞ control problem is reformulated based on the ROM, which can be transformed to solve the Hamilton-Jacobi-Isaacs (HJI) equation, theoretically. To learn the solution of the HJI equation from real system data, a data-driven off-policy learning approach is proposed based on the simultaneous policy update algorithm and its convergence is proved. For implementation purpose, a neural network (NN)- based action-critic structure is developed, where a critic NN and two action NNs are employed to approximate the value function, control, and disturbance policies, respectively. Subsequently, a least-square NN weight-tuning rule is derived with the method of weighted residuals. Finally, the developed data-driven off-policy learning approach is applied to a nonlinear diffusion-reaction process, and the obtained results demonstrate its effectiveness.

Exploring Patterns of Soil Organic Matter Decomposition with Students through the Global Decomposition Project (GDP) and the Interactive Model of Leaf Decomposition (IMOLD)

NASA Astrophysics Data System (ADS)

Steiner, S. M.; Wood, J. H.

2015-12-01

As decomposition rates are affected by climate change, understanding crucial soil interactions that affect plant growth and decomposition becomes a vital part of contributing to the students' knowledge base. The Global Decomposition Project (GDP) is designed to introduce and educate students about soil organic matter and decomposition through a standardized protocol for collecting, reporting, and sharing data. The Interactive Model of Leaf Decomposition (IMOLD) utilizes animations and modeling to learn about the carbon cycle, leaf anatomy, and the role of microbes in decomposition. Paired together, IMOLD teaches the background information and allows simulation of numerous scenarios, and the GDP is a data collection protocol that allows students to gather usable measurements of decomposition in the field. Our presentation will detail how the GDP protocol works, how to obtain or make the materials needed, and how results will be shared. We will also highlight learning objectives from the three animations of IMOLD, and demonstrate how students can experiment with different climates and litter types using the interactive model to explore a variety of decomposition scenarios. The GDP demonstrates how scientific methods can be extended to educate broader audiences, and data collected by students can provide new insight into global patterns of soil decomposition. Using IMOLD, students will gain a better understanding of carbon cycling in the context of litter decomposition, as well as learn to pose questions they can answer with an authentic computer model. Using the GDP protocols and IMOLD provide a pathway for scientists and educators to interact and reach meaningful education and research goals.

TE/TM decomposition of electromagnetic sources

NASA Technical Reports Server (NTRS)

Lindell, Ismo V.

1988-01-01

Three methods are given by which bounded EM sources can be decomposed into two parts radiating transverse electric (TE) and transverse magnetic (TM) fields with respect to a given constant direction in space. The theory applies source equivalence and nonradiating source concepts, which lead to decomposition methods based on a recursive formula or two differential equations for the determination of the TE and TM components of the original source. Decompositions for a dipole in terms of point, line, and plane sources are studied in detail. The planar decomposition is seen to match to an earlier result given by Clemmow (1963). As an application of the point decomposition method, it is demonstrated that the general exact image expression for the Sommerfeld half-space problem, previously derived through heuristic reasoning, can be more straightforwardly obtained through the present decomposition method.

Waveform inversion for orthorhombic anisotropy with P waves: feasibility and resolution

NASA Astrophysics Data System (ADS)

Kazei, Vladimir; Alkhalifah, Tariq

2018-05-01

Various parametrizations have been suggested to simplify inversions of first arrivals, or P waves, in orthorhombic anisotropic media, but the number and type of retrievable parameters have not been decisively determined. We show that only six parameters can be retrieved from the dynamic linearized inversion of P waves. These parameters are different from the six parameters needed to describe the kinematics of P waves. Reflection-based radiation patterns from the P-P scattered waves are remapped into the spectral domain to allow for our resolution analysis based on the effective angle of illumination concept. Singular value decomposition of the spectral sensitivities from various azimuths, offset coverage scenarios and data bandwidths allows us to quantify the resolution of different parametrizations, taking into account the signal-to-noise ratio in a given experiment. According to our singular value analysis, when the primary goal of inversion is determining the velocity of the P waves, gradually adding anisotropy of lower orders (isotropic, vertically transversally isotropic and orthorhombic) in hierarchical parametrization is the best choice. Hierarchical parametrization reduces the trade-off between the parameters and makes gradual introduction of lower anisotropy orders straightforward. When all the anisotropic parameters affecting P-wave propagation need to be retrieved simultaneously, the classic parametrization of orthorhombic medium with elastic stiffness matrix coefficients and density is a better choice for inversion. We provide estimates of the number and set of parameters that can be retrieved from surface seismic data in different acquisition scenarios. To set up an inversion process, the singular values determine the number of parameters that can be inverted and the resolution matrices from the parametrizations can be used to ascertain the set of parameters that can be resolved.

Thermal Decomposition Behavior of Hydroxytyrosol (HT) in Nitrogen Atmosphere Based on TG-FTIR Methods.

PubMed

Tu, Jun-Ling; Yuan, Jiao-Jiao

2018-02-13

The thermal decomposition behavior of olive hydroxytyrosol (HT) was first studied using thermogravimetry (TG). Cracked chemical bond and evolved gas analysis during the thermal decomposition process of HT were also investigated using thermogravimetry coupled with infrared spectroscopy (TG-FTIR). Thermogravimetry-Differential thermogravimetry (TG-DTG) curves revealed that the thermal decomposition of HT began at 262.8 °C and ended at 409.7 °C with a main mass loss. It was demonstrated that a high heating rate (over 20 K·min -1 ) restrained the thermal decomposition of HT, resulting in an obvious thermal hysteresis. Furthermore, a thermal decomposition kinetics investigation of HT indicated that the non-isothermal decomposition mechanism was one-dimensional diffusion (D1), integral form g ( x ) = x ², and differential form f ( x ) = 1/(2 x ). The four combined approaches were employed to calculate the activation energy ( E = 128.50 kJ·mol -1 ) and Arrhenius preexponential factor (ln A = 24.39 min -1 ). In addition, a tentative mechanism of HT thermal decomposition was further developed. The results provide a theoretical reference for the potential thermal stability of HT.

Double Bounce Component in Cross-Polarimetric SAR from a New Scattering Target Decomposition

NASA Astrophysics Data System (ADS)

Hong, Sang-Hoon; Wdowinski, Shimon

2013-08-01

Common vegetation scattering theories assume that the Synthetic Aperture Radar (SAR) cross-polarization (cross-pol) signal represents solely volume scattering. We found this assumption incorrect based on SAR phase measurements acquired over the south Florida Everglades wetlands indicating that the cross-pol radar signal often samples the water surface beneath the vegetation. Based on these new observations, we propose that the cross-pol measurement consists of both volume scattering and double bounce components. The simplest multi-bounce scattering mechanism that generates cross-pol signal occurs by rotated dihedrals. Thus, we use the rotated dihedral mechanism with probability density function to revise some of the vegetation scattering theories and develop a three- component decomposition algorithm with single bounce, double bounce from both co-pol and cross-pol, and volume scattering components. We applied the new decomposition analysis to both urban and rural environments using Radarsat-2 quad-pol datasets. The decomposition of the San Francisco's urban area shows higher double bounce scattering and reduced volume scattering compared to other common three-component decomposition. The decomposition of the rural Everglades area shows that the relations between volume and cross-pol double bounce depend on the vegetation density. The new decomposition can be useful to better understand vegetation scattering behavior over the various surfaces and the estimation of above ground biomass using SAR observations.

Aging-driven decomposition in zolpidem hemitartrate hemihydrate and the single-crystal structure of its decomposition products.

PubMed

Vega, Daniel R; Baggio, Ricardo; Roca, Mariana; Tombari, Dora

2011-04-01

The "aging-driven" decomposition of zolpidem hemitartrate hemihydrate (form A) has been followed by X-ray powder diffraction (XRPD), and the crystal and molecular structures of the decomposition products studied by single-crystal methods. The process is very similar to the "thermally driven" one, recently described in the literature for form E (Halasz and Dinnebier. 2010. J Pharm Sci 99(2): 871-874), resulting in a two-phase system: the neutral free base (common to both decomposition processes) and, in the present case, a novel zolpidem tartrate monohydrate, unique to the "aging-driven" decomposition. Our room-temperature single-crystal analysis gives for the free base comparable results as the high-temperature XRPD ones already reported by Halasz and Dinnebier: orthorhombic, Pcba, a = 9.6360(10) Å, b = 18.2690(5) Å, c = 18.4980(11) Å, and V = 3256.4(4) Å(3) . The unreported zolpidem tartrate monohydrate instead crystallizes in monoclinic P21 , which, for comparison purposes, we treated in the nonstandard setting P1121 with a = 20.7582(9) Å, b = 15.2331(5) Å, c = 7.2420(2) Å, γ = 90.826(2)°, and V = 2289.73(14) Å(3) . The structure presents two complete moieties in the asymmetric unit (z = 4, z' = 2). The different phases obtained in both decompositions are readily explained, considering the diverse genesis of both processes. Copyright © 2010 Wiley-Liss, Inc.

Computational Benefits Using an Advanced Concatenation Scheme Based on Reduced Order Models for RF Structures

NASA Astrophysics Data System (ADS)

Heller, Johann; Flisgen, Thomas; van Rienen, Ursula

The computation of electromagnetic fields and parameters derived thereof for lossless radio frequency (RF) structures filled with isotropic media is an important task for the design and operation of particle accelerators. Unfortunately, these computations are often highly demanding with regard to computational effort. The entire computational demand of the problem can be reduced using decomposition schemes in order to solve the field problems on standard workstations. This paper presents one of the first detailed comparisons between the recently proposed state-space concatenation approach (SSC) and a direct computation for an accelerator cavity with coupler-elements that break the rotational symmetry.

Spectral, coordination and thermal properties of 5-arylidene thiobarbituric acids

NASA Astrophysics Data System (ADS)

Masoud, Mamdouh S.; El-Marghany, Adel; Orabi, Adel; Ali, Alaa E.; Sayed, Reham

2013-04-01

Synthesis of 5-arylidine thiobarbituric acids containing different functional groups with variable electronic characters were described and their Co2+, Ni2+ and Cu2+ complexes. The stereochemistry and mode of bonding of 5-(substituted benzylidine)-2-TBA complexes were achieved based on elemental analysis, spectral (UV-VIS, IR, 1H NMR, MS), magnetic susceptibility and conductivity measurements. The ligands were of bidentate and tridentate bonding through S, N and O of pyrimidine nucleolus. All complexes were of octahedral configuration. The thermal data of the complexes pointed to their stability. The mechanism of the thermal decomposition is discussed. The thermodynamic parameters of the dissociation steps were evaluated and discussed.

Assessing the effect of different treatments on decomposition rate of dairy manure.

PubMed

Khalil, Tariq M; Higgins, Stewart S; Ndegwa, Pius M; Frear, Craig S; Stöckle, Claudio O

2016-11-01

Confined animal feeding operations (CAFOs) contribute to greenhouse gas emission, but the magnitude of these emissions as a function of operation size, infrastructure, and manure management are difficult to assess. Modeling is a viable option to estimate gaseous emission and nutrient flows from CAFOs. These models use a decomposition rate constant for carbon mineralization. However, this constant is usually determined assuming a homogenous mix of manure, ignoring the effects of emerging manure treatments. The aim of this study was to measure and compare the decomposition rate constants of dairy manure in single and three-pool decomposition models, and to develop an empirical model based on chemical composition of manure for prediction of a decomposition rate constant. Decomposition rate constants of manure before and after an anaerobic digester (AD), following coarse fiber separation, and fine solids removal were determined under anaerobic conditions for single and three-pool decomposition models. The decomposition rates of treated manure effluents differed significantly from untreated manure for both single and three-pool decomposition models. In the single-pool decomposition model, AD effluent containing only suspended solids had a relatively high decomposition rate of 0.060 d(-1), while liquid with coarse fiber and fine solids removed had the lowest rate of 0.013 d(-1). In the three-pool decomposition model, fast and slow decomposition rate constants (0.25 d(-1) and 0.016 d(-1) respectively) of untreated AD influent were also significantly different from treated manure fractions. A regression model to predict the decomposition rate of treated dairy manure fitted well (R(2) = 0.83) to observed data. Copyright © 2016 Elsevier Ltd. All rights reserved.

Thermal explosion analysis of methyl ethyl ketone peroxide by non-isothermal and isothermal calorimetric applications.

PubMed

Chi, Jen-Hao; Wu, Sheng-Hung; Shu, Chi-Min

2009-11-15

In the past, process incidents attributed to organic peroxides (OPs) that involved near misses, over-pressures, runaway reactions, and thermal explosions occurred because of poor training, human error, incorrect kinetic assumptions, insufficient change management, and inadequate chemical knowledge in the manufacturing process. Calorimetric applications were employed broadly to test organic peroxides on a small-scale because of their thermal hazards, such as exothermic behavior and self-accelerating decomposition in the laboratory. In essence, methyl ethyl ketone peroxide (MEKPO) is highly reactive and exothermically unstable. In recent years, it has undergone many thermal explosions and runaway reaction incidents in the manufacturing process. Differential scanning calorimetry (DSC), vent sizing package 2 (VSP2), and thermal activity monitor (TAM) were employed to analyze thermokinetic parameters and safety index. The intent of the analyses was to facilitate the use of various auto-alarm equipments to detect over-pressure, over-temperature, and hazardous materials leaks for a wide spectrum of operations. Results indicated that MEKPO decomposition is detected at low temperatures (30-40 degrees C), and the rate of decomposition was shown to exponentially increase with temperature and pressure. Determining time to maximum rate (TMR), self-accelerating decomposition temperature (SADT), maximum temperature (T(max)), exothermic onset temperature (T(0)), and heat of decomposition (DeltaH(d)) was essential for identifying early-stage runaway reactions effectively for industries.

Synthesis, characterization, thermal and explosive properties of potassium salts of trinitrophloroglucinol.

PubMed

Wang, Liqiong; Chen, Hongyan; Zhang, Tonglai; Zhang, Jianguo; Yang, Li

2007-08-17

Three different substituted potassium salts of trinitrophloroglucinol (H(3)TNPG) were prepared and characterized. The salts are all hydrates, and thermogravimetric analysis (TG) and elemental analysis confirmed that these salts contain crystal H2O and that the amount crystal H2O in potassium salts of H3TNPG is 1.0 hydrate for mono-substituted potassium salts of H3TNPG [K(H2TNPG)] and di-substituted potassium salt of H3TNPG [K2(HTNPG)], and 2.0 hydrate for tri-substituted potassium salt of H3TNPG [K3(TNPG)]. Their thermal decomposition mechanisms and kinetic parameters from 50 to 500 degrees C were studied under a linear heating rate by differential scanning calorimetry (DSC). Their thermal decomposition mechanisms undergo dehydration stage and intensive exothermic decomposition stage. FT-IR and TG studies verify that their final residua of decomposition are potassium cyanide or potassium carbonate. According to the onset temperature of the first exothermic decomposition process of dehydrated salts, the order of the thermal stability from low to high is from K(H2TNPG) and K2(HTNPG) to K3(TNPG), which is conform to the results of apparent activation energy calculated by Kissinger's and Ozawa-Doyle's method. Sensitivity test results showed that potassium salts of H3TNPG demonstrated higher sensitivity properties and had greater explosive probabilities.

A highly efficient autothermal microchannel reactor for ammonia decomposition: Analysis of hydrogen production in transient and steady-state regimes

NASA Astrophysics Data System (ADS)

Engelbrecht, Nicolaas; Chiuta, Steven; Bessarabov, Dmitri G.

2018-05-01

The experimental evaluation of an autothermal microchannel reactor for H2 production from NH3 decomposition is described. The reactor design incorporates an autothermal approach, with added NH3 oxidation, for coupled heat supply to the endothermic decomposition reaction. An alternating catalytic plate arrangement is used to accomplish this thermal coupling in a cocurrent flow strategy. Detailed analysis of the transient operating regime associated with reactor start-up and steady-state results is presented. The effects of operating parameters on reactor performance are investigated, specifically, the NH3 decomposition flow rate, NH3 oxidation flow rate, and fuel-oxygen equivalence ratio. Overall, the reactor exhibits rapid response time during start-up; within 60 min, H2 production is approximately 95% of steady-state values. The recommended operating point for steady-state H2 production corresponds to an NH3 decomposition flow rate of 6 NL min-1, NH3 oxidation flow rate of 4 NL min-1, and fuel-oxygen equivalence ratio of 1.4. Under these flows, NH3 conversion of 99.8% and H2 equivalent fuel cell power output of 0.71 kWe is achieved. The reactor shows good heat utilization with a thermal efficiency of 75.9%. An efficient autothermal reactor design is therefore demonstrated, which may be upscaled to a multi-kW H2 production system for commercial implementation.

Effect of Isomorphous Substitution on the Thermal Decomposition Mechanism of Hydrotalcites

PubMed Central

Crosby, Sergio; Tran, Doanh; Cocke, David; Duraia, El-Shazly M.; Beall, Gary W.

2014-01-01

Hydrotalcites have many important applications in catalysis, wastewater treatment, gene delivery and polymer stabilization, all depending on preparation history and treatment scenarios. In catalysis and polymer stabilization, thermal decomposition is of great importance. Hydrotalcites form easily with atmospheric carbon dioxide and often interfere with the study of other anion containing systems, particularly if formed at room temperature. The dehydroxylation and decomposition of carbonate occurs simultaneously, making it difficult to distinguish the dehydroxylation mechanisms directly. To date, the majority of work on understanding the decomposition mechanism has utilized hydrotalcite precipitated at room temperature. In this study, evolved gas analysis combined with thermal analysis has been used to show that CO2 contamination is problematic in materials being formed at RT that are poorly crystalline. This has led to some dispute as to the nature of the dehydroxylation mechanism. In this paper, data for the thermal decomposition of the chloride form of hydrotalcite are reported. In addition, carbonate-free hydrotalcites have been synthesized with different charge densities and at different growth temperatures. This combination of parameters has allowed a better understanding of the mechanism of dehydroxylation and the role that isomorphous substitution plays in these mechanisms to be delineated. In addition, the effect of anion type on thermal stability is also reported. A stepwise dehydroxylation model is proposed that is mediated by the level of aluminum substitution. PMID:28788231

Comparative evaluation of thermal decomposition behavior and thermal stability of powdered ammonium nitrate under different atmosphere conditions.

PubMed

Yang, Man; Chen, Xianfeng; Wang, Yujie; Yuan, Bihe; Niu, Yi; Zhang, Ying; Liao, Ruoyu; Zhang, Zumin

2017-09-05

In order to analyze the thermal decomposition characteristics of ammonium nitrate (AN), its thermal behavior and stability under different conditions are studied, including different atmospheres, heating rates and gas flow rates. The evolved decomposition gases of AN in air and nitrogen are analyzed with a quadrupole mass spectrometer. Thermal stability of AN at different heating rates and gas flow rates are studied by differential scanning calorimetry, thermogravimetric analysis, paired comparison method and safety parameter evaluation. Experimental results show that the major evolved decomposition gases in air are H 2 O, NH 3 , N 2 O, NO, NO 2 and HNO 3 , while in nitrogen, H 2 O, NH 3 , NO and HNO 3 are major components. Compared with nitrogen atmosphere, lower initial and end temperatures, higher heat flux and broader reaction temperature range are obtained in air. Meanwhile, higher air gas flow rate tends to achieve lower reaction temperature and to reduce thermal stability of AN. Self-accelerating decomposition temperature of AN in air is much lower than that in nitrogen. It is considered that thermostability of AN is influenced by atmosphere, heating rate and gas flow rate, thus changes of boundary conditions will influence its thermostability, which is helpful to its safe production, storage, transportation and utilization. Copyright © 2017 Elsevier B.V. All rights reserved.

A simple numerical model for predicting organic matter decomposition in a fed-batch composting operation.

PubMed

Nakasaki, Kiyohiko; Ohtaki, Akihito

2002-01-01

Using dog food as a model of the organic waste that comprises composting raw material, the degradation pattern of organic materials was examined by continuously measuring the quantity of CO2 evolved during the composting process in both batch and fed-batch operations. A simple numerical model was made on the basis of three suppositions for describing the organic matter decomposition in the batch operation. First, a certain quantity of carbon in the dog food was assumed to be recalcitrant to degradation in the composting reactor within the retention time allowed. Second, it was assumed that the decomposition rate of carbon is proportional to the quantity of easily degradable carbon, that is, the carbon recalcitrant to degradation was subtracted from the total carbon remaining in the dog food. Third, a certain lag time is assumed to occur before the start of active decomposition of organic matter in the dog food; this lag corresponds to the time required for microorganisms to proliferate and become active. It was then ascertained that the decomposition pattern for the organic matter in the dog food during the fed-batch operation could be predicted by the numerical model with the parameters obtained from the batch operation. This numerical model was modified so that the change in dry weight of composting materials could be obtained. The modified model was found suitable for describing the organic matter decomposition pattern in an actual fed-batch composting operation of the garbage obtained from a restaurant, approximately 10 kg d(-1) loading for 60 d.

Parametric studies of diethyl phosphoramidate photocatalytic decomposition over TiO2.

PubMed

Sun, Bo; Vorontsov, Alexander V; Smirniotis, Panagiotis G

2011-02-28

The present study is focused on influences of parameters including pH, temperature, TiO(2) catalyst concentration, and reactant concentration on the rate of photocatalytic diethyl phosphoramidate (DEPA) decomposition with Hombikat UV 100 (HK) and Degussa P25 (P25) TiO(2). Total mineralization of DEPA is observed. Two regimes of pH, namely in acid and near-neutral environments were found where maximum total carbon (TC) decomposition was observed. The electrostatic effects on adsorption over the TiO(2) surface explain the above phenomena. The maximum rate is observed for P25 at DEPA concentration 1.3 mM whereas the rate grows continuously with DEPA concentration rise for HK. The temperature dependence of TC decomposition rate in the range of 15-63°C with both HK and P25 follows the Arrhenius equation. The activation energy for total carbon decomposition with HK and P25 are 29.5±1.0 and 24.3±3.1 kJ/mol, respectively. The decomposition rate of DEPA is larger over P25 than over HK. The rate over P25 increases faster than that with HK for each unit of the titania added when the TiO(2) concentration is less than 375 mg/l. The higher light absorption and particles aggregation of P25 are responsible for the decrease of reaction rate we observed at catalyst concentration above a certain level. In contrast, the rate over HK increases monotonically with the concentration of the photocatalyst used. Copyright © 2010 Elsevier B.V. All rights reserved.

Influence of growth conditions on subsequent submonolayer oxide decomposition on Si(111)

NASA Astrophysics Data System (ADS)

Shklyaev, A. A.; Aono, Masakazu; Suzuki, Takanori

1996-10-01

The decomposition kinetics of oxide with a coverage between 0.1 and 0.5 ML, grown by oxidation of the Si(111)-7×7 surface at temperatures between 550 and 800 °C for oxygen pressures (Pox) between 3×10-8 and 2×10-6 Torr, is investigated with optical second-harmonic generation. Through the analysis of the pressure dependence of the initial oxide-growth rate, we separate the conditions for a slow oxide growth at Pox near Ptr(T) and for a rapid oxide growth at Pox>3Ptr(T), where Ptr(T) is the transition pressure to Si-etching regime without oxide growth. For the rapidly grown oxide, the oxide decomposition rate decreases with increasing oxide coverage, whereas the activation energy of about 3 eV does not change significantly. While in the case when the oxide is desorbed at the same temperature as are used for oxide growth, the oxide decomposition is described by an apparent activation energy of 1.5 eV. For the slowly grown oxide of 0.1 ML coverage, the oxide desorption kinetics shows a rapid decomposition stage followed by a slow stage. For the slowly grown oxide of 0.3 ML coverage, the slow stage with a large activation energy of 4.1 eV becomes dominant in the latter part of decomposition. The dependence of the desorption kinetics on the oxide-growth conditions described here could be a reason for the scattering of the kinetic parameters in the literature for O2 interaction with silicon at elevated temperatures.

Multi-tissue analysis of co-expression networks by higher-order generalized singular value decomposition identifies functionally coherent transcriptional modules.

PubMed

Xiao, Xiaolin; Moreno-Moral, Aida; Rotival, Maxime; Bottolo, Leonardo; Petretto, Enrico

2014-01-01

Recent high-throughput efforts such as ENCODE have generated a large body of genome-scale transcriptional data in multiple conditions (e.g., cell-types and disease states). Leveraging these data is especially important for network-based approaches to human disease, for instance to identify coherent transcriptional modules (subnetworks) that can inform functional disease mechanisms and pathological pathways. Yet, genome-scale network analysis across conditions is significantly hampered by the paucity of robust and computationally-efficient methods. Building on the Higher-Order Generalized Singular Value Decomposition, we introduce a new algorithmic approach for efficient, parameter-free and reproducible identification of network-modules simultaneously across multiple conditions. Our method can accommodate weighted (and unweighted) networks of any size and can similarly use co-expression or raw gene expression input data, without hinging upon the definition and stability of the correlation used to assess gene co-expression. In simulation studies, we demonstrated distinctive advantages of our method over existing methods, which was able to recover accurately both common and condition-specific network-modules without entailing ad-hoc input parameters as required by other approaches. We applied our method to genome-scale and multi-tissue transcriptomic datasets from rats (microarray-based) and humans (mRNA-sequencing-based) and identified several common and tissue-specific subnetworks with functional significance, which were not detected by other methods. In humans we recapitulated the crosstalk between cell-cycle progression and cell-extracellular matrix interactions processes in ventricular zones during neocortex expansion and further, we uncovered pathways related to development of later cognitive functions in the cortical plate of the developing brain which were previously unappreciated. Analyses of seven rat tissues identified a multi-tissue subnetwork of co-expressed heat shock protein (Hsp) and cardiomyopathy genes (Bag3, Cryab, Kras, Emd, Plec), which was significantly replicated using separate failing heart and liver gene expression datasets in humans, thus revealing a conserved functional role for Hsp genes in cardiovascular disease.

Reparametrization-based estimation of genetic parameters in multi-trait animal model using Integrated Nested Laplace Approximation.

PubMed

Mathew, Boby; Holand, Anna Marie; Koistinen, Petri; Léon, Jens; Sillanpää, Mikko J

2016-02-01

A novel reparametrization-based INLA approach as a fast alternative to MCMC for the Bayesian estimation of genetic parameters in multivariate animal model is presented. Multi-trait genetic parameter estimation is a relevant topic in animal and plant breeding programs because multi-trait analysis can take into account the genetic correlation between different traits and that significantly improves the accuracy of the genetic parameter estimates. Generally, multi-trait analysis is computationally demanding and requires initial estimates of genetic and residual correlations among the traits, while those are difficult to obtain. In this study, we illustrate how to reparametrize covariance matrices of a multivariate animal model/animal models using modified Cholesky decompositions. This reparametrization-based approach is used in the Integrated Nested Laplace Approximation (INLA) methodology to estimate genetic parameters of multivariate animal model. Immediate benefits are: (1) to avoid difficulties of finding good starting values for analysis which can be a problem, for example in Restricted Maximum Likelihood (REML); (2) Bayesian estimation of (co)variance components using INLA is faster to execute than using Markov Chain Monte Carlo (MCMC) especially when realized relationship matrices are dense. The slight drawback is that priors for covariance matrices are assigned for elements of the Cholesky factor but not directly to the covariance matrix elements as in MCMC. Additionally, we illustrate the concordance of the INLA results with the traditional methods like MCMC and REML approaches. We also present results obtained from simulated data sets with replicates and field data in rice.

A Ternary Brain-Computer Interface Based on Single-Trial Readiness Potentials of Self-initiated Fine Movements: A Diversified Classification Scheme

PubMed Central

Abou Zeid, Elias; Rezazadeh Sereshkeh, Alborz; Schultz, Benjamin; Chau, Tom

2017-01-01

In recent years, the readiness potential (RP), a type of pre-movement neural activity, has been investigated for asynchronous electroencephalogram (EEG)-based brain-computer interfaces (BCIs). Since the RP is attenuated for involuntary movements, a BCI driven by RP alone could facilitate intentional control amid a plethora of unintentional movements. Previous studies have mainly attempted binary single-trial classification of RP. An RP-based BCI with three or more states would expand the options for functional control. Here, we propose a ternary BCI based on single-trial RPs. This BCI classifies amongst an idle state, a left hand and a right hand self-initiated fine movement. A pipeline of spatio-temporal filtering with per participant parameter optimization was used for feature extraction. The ternary classification was decomposed into binary classifications using a decision-directed acyclic graph (DDAG). For each class pair in the DDAG structure, an ordered diversified classifier system (ODCS-DDAG) was used to select the best among various classification algorithms or to combine the results of different classification algorithms. Using EEG data from 14 participants performing self-initiated left or right key presses, punctuated with rest periods, we compared the performance of ODCS-DDAG to a ternary classifier and four popular multiclass decomposition methods using only a single classification algorithm. ODCS-DDAG had the highest performance (0.769 Cohen's Kappa score) and was significantly better than the ternary classifier and two of the four multiclass decomposition methods. Our work supports further study of RP-based BCI for intuitive asynchronous environmental control or augmentative communication. PMID:28596725

Waveform LiDAR processing: comparison of classic approaches and optimized Gold deconvolution to characterize vegetation structure and terrain elevation

NASA Astrophysics Data System (ADS)

Zhou, T.; Popescu, S. C.; Krause, K.

2016-12-01

Waveform Light Detection and Ranging (LiDAR) data have advantages over discrete-return LiDAR data in accurately characterizing vegetation structure. However, we lack a comprehensive understanding of waveform data processing approaches under different topography and vegetation conditions. The objective of this paper is to highlight a novel deconvolution algorithm, the Gold algorithm, for processing waveform LiDAR data with optimal deconvolution parameters. Further, we present a comparative study of waveform processing methods to provide insight into selecting an approach for a given combination of vegetation and terrain characteristics. We employed two waveform processing methods: 1) direct decomposition, 2) deconvolution and decomposition. In method two, we utilized two deconvolution algorithms - the Richardson Lucy (RL) algorithm and the Gold algorithm. The comprehensive and quantitative comparisons were conducted in terms of the number of detected echoes, position accuracy, the bias of the end products (such as digital terrain model (DTM) and canopy height model (CHM)) from discrete LiDAR data, along with parameter uncertainty for these end products obtained from different methods. This study was conducted at three study sites that include diverse ecological regions, vegetation and elevation gradients. Results demonstrate that two deconvolution algorithms are sensitive to the pre-processing steps of input data. The deconvolution and decomposition method is more capable of detecting hidden echoes with a lower false echo detection rate, especially for the Gold algorithm. Compared to the reference data, all approaches generate satisfactory accuracy assessment results with small mean spatial difference (<1.22 m for DTMs, < 0.77 m for CHMs) and root mean square error (RMSE) (<1.26 m for DTMs, < 1.93 m for CHMs). More specifically, the Gold algorithm is superior to others with smaller root mean square error (RMSE) (< 1.01m), while the direct decomposition approach works better in terms of the percentage of spatial difference within 0.5 and 1 m. The parameter uncertainty analysis demonstrates that the Gold algorithm outperforms other approaches in dense vegetation areas, with the smallest RMSE, and the RL algorithm performs better in sparse vegetation areas in terms of RMSE.

The recognition of ocean red tide with hyper-spectral-image based on EMD

NASA Astrophysics Data System (ADS)

Zhao, Wencang; Wei, Hongli; Shi, Changjiang; Ji, Guangrong

2008-05-01

A new technique is introduced in this paper regarding red tide recognition with remotely sensed hyper-spectral images based on empirical mode decomposition (EMD), from an artificial red tide experiment in the East China Sea in 2002. A set of characteristic parameters that describe absorbing crest and reflecting crest of the red tide and its recognition methods are put forward based on general picture data, with which the spectral information of certain non-dominant alga species of a red tide occurrence is analyzed for establishing the foundation to estimate the species. Comparative experiments have proved that the method is effective. Meanwhile, the transitional area between red-tide zone and non-red-tide zone can be detected with the information of thickness of algae influence, with which a red tide can be forecast.

Chemical reaction mechanisms in solution from brute force computational Arrhenius plots.

PubMed

Kazemi, Masoud; Åqvist, Johan

2015-06-01

Decomposition of activation free energies of chemical reactions, into enthalpic and entropic components, can provide invaluable signatures of mechanistic pathways both in solution and in enzymes. Owing to the large number of degrees of freedom involved in such condensed-phase reactions, the extensive configurational sampling needed for reliable entropy estimates is still beyond the scope of quantum chemical calculations. Here we show, for the hydrolytic deamination of cytidine and dihydrocytidine in water, how direct computer simulations of the temperature dependence of free energy profiles can be used to extract very accurate thermodynamic activation parameters. The simulations are based on empirical valence bond models, and we demonstrate that the energetics obtained is insensitive to whether these are calibrated by quantum mechanical calculations or experimental data. The thermodynamic activation parameters are in remarkable agreement with experiment results and allow discrimination among alternative mechanisms, as well as rationalization of their different activation enthalpies and entropies.

Chemical reaction mechanisms in solution from brute force computational Arrhenius plots

PubMed Central

Kazemi, Masoud; Åqvist, Johan

2015-01-01

Decomposition of activation free energies of chemical reactions, into enthalpic and entropic components, can provide invaluable signatures of mechanistic pathways both in solution and in enzymes. Owing to the large number of degrees of freedom involved in such condensed-phase reactions, the extensive configurational sampling needed for reliable entropy estimates is still beyond the scope of quantum chemical calculations. Here we show, for the hydrolytic deamination of cytidine and dihydrocytidine in water, how direct computer simulations of the temperature dependence of free energy profiles can be used to extract very accurate thermodynamic activation parameters. The simulations are based on empirical valence bond models, and we demonstrate that the energetics obtained is insensitive to whether these are calibrated by quantum mechanical calculations or experimental data. The thermodynamic activation parameters are in remarkable agreement with experiment results and allow discrimination among alternative mechanisms, as well as rationalization of their different activation enthalpies and entropies. PMID:26028237

Better Decomposition Heuristics for the Maximum-Weight Connected Graph Problem Using Betweenness Centrality

NASA Astrophysics Data System (ADS)

Yamamoto, Takanori; Bannai, Hideo; Nagasaki, Masao; Miyano, Satoru

We present new decomposition heuristics for finding the optimal solution for the maximum-weight connected graph problem, which is known to be NP-hard. Previous optimal algorithms for solving the problem decompose the input graph into subgraphs using heuristics based on node degree. We propose new heuristics based on betweenness centrality measures, and show through computational experiments that our new heuristics tend to reduce the number of subgraphs in the decomposition, and therefore could lead to the reduction in computational time for finding the optimal solution. The method is further applied to analysis of biological pathway data.

A copyright protection scheme for digital images based on shuffled singular value decomposition and visual cryptography.

PubMed

Devi, B Pushpa; Singh, Kh Manglem; Roy, Sudipta

2016-01-01

This paper proposes a new watermarking algorithm based on the shuffled singular value decomposition and the visual cryptography for copyright protection of digital images. It generates the ownership and identification shares of the image based on visual cryptography. It decomposes the image into low and high frequency sub-bands. The low frequency sub-band is further divided into blocks of same size after shuffling it and then the singular value decomposition is applied to each randomly selected block. Shares are generated by comparing one of the elements in the first column of the left orthogonal matrix with its corresponding element in the right orthogonal matrix of the singular value decomposition of the block of the low frequency sub-band. The experimental results show that the proposed scheme clearly verifies the copyright of the digital images, and is robust to withstand several image processing attacks. Comparison with the other related visual cryptography-based algorithms reveals that the proposed method gives better performance. The proposed method is especially resilient against the rotation attack.

In Situ Probes of Capture and Decomposition of Chemical Warfare Agent Simulants by Zr-Based Metal Organic Frameworks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Plonka, Anna M.; Wang, Qi; Gordon, Wesley O.

Recently, Zr-based metal organic frameworks (MOFs) were shown to be among the fastest catalysts of nerve-agent hydrolysis in solution. Here, we report a detailed study of the adsorption and decomposition of a nerve-agent simulant, dimethyl methylphosphonate (DMMP), on UiO-66, UiO-67, MOF-808, and NU-1000 using synchrotron-based X-ray powder diffraction, X-ray absorption, and infrared spectroscopy, which reveals key aspects of the reaction mechanism. The diffraction measurements indicate that all four MOFs adsorb DMMP (introduced at atmospheric pressures through a flow of helium or air) within the pore space. In addition, the combination of X-ray absorption and infrared spectra suggests direct coordination ofmore » DMMP to the Zr6 cores of all MOFs, which ultimately leads to decomposition to phosphonate products. Our experimental probes into the mechanism of adsorption and decomposition of chemical warfare agent simulants on Zr-based MOFs open new opportunities in rational design of new and superior decontamination materials.« less

In Situ Probes of Capture and Decomposition of Chemical Warfare Agent Simulants by Zr-Based Metal Organic Frameworks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Plonka, Anna M.; Wang, Qi; Gordon, Wesley O.

Zr-based metal organic frameworks (MOFs) have been recently shown to be among the fastest catalysts of nerve-agent hydrolysis in solution. We report a detailed study of the adsorption and decomposition of a nerve-agent simulant, dimethyl methylphosphonate (DMMP), on UiO-66, UiO-67, MOF-808, and NU-1000 using synchrotron-based X-ray powder diffraction, X-ray absorption, and infrared spectroscopy, which reveals key aspects of the reaction mechanism. The diffraction measurements indicate that all four MOFs adsorb DMMP (introduced at atmospheric pressures through a flow of helium or air) within the pore space. In addition, the combination of X-ray absorption and infrared spectra suggests direct coordination ofmore » DMMP to the Zr6 cores of all MOFs, which ultimately leads to decomposition to phosphonate products. These experimental probes into the mechanism of adsorption and decomposition of chemical warfare agent simulants on Zr-based MOFs open new opportunities in rational design of new and superior decontamination materials.« less

Phase unwrapping with graph cuts optimization and dual decomposition acceleration for 3D high-resolution MRI data.

PubMed

Dong, Jianwu; Chen, Feng; Zhou, Dong; Liu, Tian; Yu, Zhaofei; Wang, Yi

2017-03-01

Existence of low SNR regions and rapid-phase variations pose challenges to spatial phase unwrapping algorithms. Global optimization-based phase unwrapping methods are widely used, but are significantly slower than greedy methods. In this paper, dual decomposition acceleration is introduced to speed up a three-dimensional graph cut-based phase unwrapping algorithm. The phase unwrapping problem is formulated as a global discrete energy minimization problem, whereas the technique of dual decomposition is used to increase the computational efficiency by splitting the full problem into overlapping subproblems and enforcing the congruence of overlapping variables. Using three dimensional (3D) multiecho gradient echo images from an agarose phantom and five brain hemorrhage patients, we compared this proposed method with an unaccelerated graph cut-based method. Experimental results show up to 18-fold acceleration in computation time. Dual decomposition significantly improves the computational efficiency of 3D graph cut-based phase unwrapping algorithms. Magn Reson Med 77:1353-1358, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

In Situ Probes of Capture and Decomposition of Chemical Warfare Agent Simulants by Zr-Based Metal Organic Frameworks

DOE PAGES

Plonka, Anna M.; Wang, Qi; Gordon, Wesley O.; ...

2016-12-30

Recently, Zr-based metal organic frameworks (MOFs) were shown to be among the fastest catalysts of nerve-agent hydrolysis in solution. Here, we report a detailed study of the adsorption and decomposition of a nerve-agent simulant, dimethyl methylphosphonate (DMMP), on UiO-66, UiO-67, MOF-808, and NU-1000 using synchrotron-based X-ray powder diffraction, X-ray absorption, and infrared spectroscopy, which reveals key aspects of the reaction mechanism. The diffraction measurements indicate that all four MOFs adsorb DMMP (introduced at atmospheric pressures through a flow of helium or air) within the pore space. In addition, the combination of X-ray absorption and infrared spectra suggests direct coordination ofmore » DMMP to the Zr6 cores of all MOFs, which ultimately leads to decomposition to phosphonate products. Our experimental probes into the mechanism of adsorption and decomposition of chemical warfare agent simulants on Zr-based MOFs open new opportunities in rational design of new and superior decontamination materials.« less

A Novel Multilevel-SVD Method to Improve Multistep Ahead Forecasting in Traffic Accidents Domain.

PubMed

Barba, Lida; Rodríguez, Nibaldo

2017-01-01

Here is proposed a novel method for decomposing a nonstationary time series in components of low and high frequency. The method is based on Multilevel Singular Value Decomposition (MSVD) of a Hankel matrix. The decomposition is used to improve the forecasting accuracy of Multiple Input Multiple Output (MIMO) linear and nonlinear models. Three time series coming from traffic accidents domain are used. They represent the number of persons with injuries in traffic accidents of Santiago, Chile. The data were continuously collected by the Chilean Police and were weekly sampled from 2000:1 to 2014:12. The performance of MSVD is compared with the decomposition in components of low and high frequency of a commonly accepted method based on Stationary Wavelet Transform (SWT). SWT in conjunction with the Autoregressive model (SWT + MIMO-AR) and SWT in conjunction with an Autoregressive Neural Network (SWT + MIMO-ANN) were evaluated. The empirical results have shown that the best accuracy was achieved by the forecasting model based on the proposed decomposition method MSVD, in comparison with the forecasting models based on SWT.

A Novel Multilevel-SVD Method to Improve Multistep Ahead Forecasting in Traffic Accidents Domain

PubMed Central

Rodríguez, Nibaldo

2017-01-01

Here is proposed a novel method for decomposing a nonstationary time series in components of low and high frequency. The method is based on Multilevel Singular Value Decomposition (MSVD) of a Hankel matrix. The decomposition is used to improve the forecasting accuracy of Multiple Input Multiple Output (MIMO) linear and nonlinear models. Three time series coming from traffic accidents domain are used. They represent the number of persons with injuries in traffic accidents of Santiago, Chile. The data were continuously collected by the Chilean Police and were weekly sampled from 2000:1 to 2014:12. The performance of MSVD is compared with the decomposition in components of low and high frequency of a commonly accepted method based on Stationary Wavelet Transform (SWT). SWT in conjunction with the Autoregressive model (SWT + MIMO-AR) and SWT in conjunction with an Autoregressive Neural Network (SWT + MIMO-ANN) were evaluated. The empirical results have shown that the best accuracy was achieved by the forecasting model based on the proposed decomposition method MSVD, in comparison with the forecasting models based on SWT. PMID:28261267

Fast decomposition of two ultrasound longitudinal waves in cancellous bone using a phase rotation parameter for bone quality assessment: Simulation study.

PubMed

Taki, Hirofumi; Nagatani, Yoshiki; Matsukawa, Mami; Kanai, Hiroshi; Izumi, Shin-Ichi

2017-10-01

Ultrasound signals that pass through cancellous bone may be considered to consist of two longitudinal waves, which are called fast and slow waves. Accurate decomposition of these fast and slow waves is considered to be highly beneficial in determination of the characteristics of cancellous bone. In the present study, a fast decomposition method using a wave transfer function with a phase rotation parameter was applied to received signals that have passed through bovine bone specimens with various bone volume to total volume (BV/TV) ratios in a simulation study, where the elastic finite-difference time-domain method is used and the ultrasound wave propagated parallel to the bone axes. The proposed method succeeded to decompose both fast and slow waves accurately; the normalized residual intensity was less than -19.5 dB when the specimen thickness ranged from 4 to 7 mm and the BV/TV value ranged from 0.144 to 0.226. There was a strong relationship between the phase rotation value and the BV/TV value. The ratio of the peak envelope amplitude of the decomposed fast wave to that of the slow wave increased monotonically with increasing BV/TV ratio, indicating the high performance of the proposed method in estimation of the BV/TV value in cancellous bone.

On the hadron mass decomposition

NASA Astrophysics Data System (ADS)

Lorcé, Cédric

2018-02-01

We argue that the standard decompositions of the hadron mass overlook pressure effects, and hence should be interpreted with great care. Based on the semiclassical picture, we propose a new decomposition that properly accounts for these pressure effects. Because of Lorentz covariance, we stress that the hadron mass decomposition automatically comes along with a stability constraint, which we discuss for the first time. We show also that if a hadron is seen as made of quarks and gluons, one cannot decompose its mass into more than two contributions without running into trouble with the consistency of the physical interpretation. In particular, the so-called quark mass and trace anomaly contributions appear to be purely conventional. Based on the current phenomenological values, we find that in average quarks exert a repulsive force inside nucleons, balanced exactly by the gluon attractive force.

Primary decomposition of zero-dimensional ideals over finite fields

NASA Astrophysics Data System (ADS)

Gao, Shuhong; Wan, Daqing; Wang, Mingsheng

2009-03-01

A new algorithm is presented for computing primary decomposition of zero-dimensional ideals over finite fields. Like Berlekamp's algorithm for univariate polynomials, the new method is based on the invariant subspace of the Frobenius map acting on the quotient algebra. The dimension of the invariant subspace equals the number of primary components, and a basis of the invariant subspace yields a complete decomposition. Unlike previous approaches for decomposing multivariate polynomial systems, the new method does not need primality testing nor any generic projection, instead it reduces the general decomposition problem directly to root finding of univariate polynomials over the ground field. Also, it is shown how Groebner basis structure can be used to get partial primary decomposition without any root finding.

Algorithm For Solution Of Subset-Regression Problems

NASA Technical Reports Server (NTRS)

Verhaegen, Michel

1991-01-01

Reliable and flexible algorithm for solution of subset-regression problem performs QR decomposition with new column-pivoting strategy, enables selection of subset directly from originally defined regression parameters. This feature, in combination with number of extensions, makes algorithm very flexible for use in analysis of subset-regression problems in which parameters have physical meanings. Also extended to enable joint processing of columns contaminated by noise with those free of noise, without using scaling techniques.

Repeated decompositions reveal the stability of infomax decomposition of fMRI data

PubMed Central

Duann, Jeng-Ren; Jung, Tzyy-Ping; Sejnowski, Terrence J.; Makeig, Scott

2010-01-01

In this study, we decomposed 12 fMRI data sets from six subjects each 101 times using the infomax algorithm. The first decomposition was taken as a reference decomposition; the others were used to form a component matrix of 100 by 100 components. Equivalence relations between components in this matrix, defined as maximum spatial correlations to the components of the reference decomposition, were found by the Hungarian sorting method and used to form 100 equivalence classes for each data set. We then tested the reproducibility of the matched components in the equivalence classes using uncertainty measures based on component distributions, time courses, and ROC curves. Infomax ICA rarely failed to derive nearly the same components in different decompositions. Very few components per data set were poorly reproduced, even using vector angle uncertainty measures stricter than correlation and detection theory measures. PMID:17281453

A density functional theory study of the decomposition mechanism of nitroglycerin.

PubMed

Pei, Liguan; Dong, Kehai; Tang, Yanhui; Zhang, Bo; Yu, Chang; Li, Wenzuo

2017-08-21

The detailed decomposition mechanism of nitroglycerin (NG) in the gas phase was studied by examining reaction pathways using density functional theory (DFT) and canonical variational transition state theory combined with a small-curvature tunneling correction (CVT/SCT). The mechanism of NG autocatalytic decomposition was investigated at the B3LYP/6-31G(d,p) level of theory. Five possible decomposition pathways involving NG were identified and the rate constants for the pathways at temperatures ranging from 200 to 1000 K were calculated using CVT/SCT. There was found to be a lower energy barrier to the β-H abstraction reaction than to the α-H abstraction reaction during the initial step in the autocatalytic decomposition of NG. The decomposition pathways for CHOCOCHONO 2 (a product obtained following the abstraction of three H atoms from NG by NO 2 ) include O-NO 2 cleavage or isomer production, meaning that the autocatalytic decomposition of NG has two reaction pathways, both of which are exothermic. The rate constants for these two reaction pathways are greater than the rate constants for the three pathways corresponding to unimolecular NG decomposition. The overall process of NG decomposition can be divided into two stages based on the NO 2 concentration, which affects the decomposition products and reactions. In the first stage, the reaction pathway corresponding to O-NO 2 cleavage is the main pathway, but the rates of the two autocatalytic decomposition pathways increase with increasing NO 2 concentration. However, when a threshold NO 2 concentration is reached, the NG decomposition process enters its second stage, with the two pathways for NG autocatalytic decomposition becoming the main and secondary reaction pathways.

Image fusion method based on regional feature and improved bidimensional empirical mode decomposition

NASA Astrophysics Data System (ADS)

Qin, Xinqiang; Hu, Gang; Hu, Kai

2018-01-01

The decomposition of multiple source images using bidimensional empirical mode decomposition (BEMD) often produces mismatched bidimensional intrinsic mode functions, either by their number or their frequency, making image fusion difficult. A solution to this problem is proposed using a fixed number of iterations and a union operation in the sifting process. By combining the local regional features of the images, an image fusion method has been developed. First, the source images are decomposed using the proposed BEMD to produce the first intrinsic mode function (IMF) and residue component. Second, for the IMF component, a selection and weighted average strategy based on local area energy is used to obtain a high-frequency fusion component. Third, for the residue component, a selection and weighted average strategy based on local average gray difference is used to obtain a low-frequency fusion component. Finally, the fused image is obtained by applying the inverse BEMD transform. Experimental results show that the proposed algorithm provides superior performance over methods based on wavelet transform, line and column-based EMD, and complex empirical mode decomposition, both in terms of visual quality and objective evaluation criteria.

An efficient computational approach to model statistical correlations in photon counting x-ray detectors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Faby, Sebastian; Maier, Joscha; Sawall, Stefan

2016-07-15

Purpose: To introduce and evaluate an increment matrix approach (IMA) describing the signal statistics of energy-selective photon counting detectors including spatial–spectral correlations between energy bins of neighboring detector pixels. The importance of the occurring correlations for image-based material decomposition is studied. Methods: An IMA describing the counter increase patterns in a photon counting detector is proposed. This IMA has the potential to decrease the number of required random numbers compared to Monte Carlo simulations by pursuing an approach based on convolutions. To validate and demonstrate the IMA, an approximate semirealistic detector model is provided, simulating a photon counting detector inmore » a simplified manner, e.g., by neglecting count rate-dependent effects. In this way, the spatial–spectral correlations on the detector level are obtained and fed into the IMA. The importance of these correlations in reconstructed energy bin images and the corresponding detector performance in image-based material decomposition is evaluated using a statistically optimal decomposition algorithm. Results: The results of IMA together with the semirealistic detector model were compared to other models and measurements using the spectral response and the energy bin sensitivity, finding a good agreement. Correlations between the different reconstructed energy bin images could be observed, and turned out to be of weak nature. These correlations were found to be not relevant in image-based material decomposition. An even simpler simulation procedure based on the energy bin sensitivity was tested instead and yielded similar results for the image-based material decomposition task, as long as the fact that one incident photon can increase multiple counters across neighboring detector pixels is taken into account. Conclusions: The IMA is computationally efficient as it required about 10{sup 2} random numbers per ray incident on a detector pixel instead of an estimated 10{sup 8} random numbers per ray as Monte Carlo approaches would need. The spatial–spectral correlations as described by IMA are not important for the studied image-based material decomposition task. Respecting the absolute photon counts and thus the multiple counter increases by a single x-ray photon, the same material decomposition performance could be obtained with a simpler detector description using the energy bin sensitivity.« less

Two statistics for evaluating parameter identifiability and error reduction

USGS Publications Warehouse

Doherty, John; Hunt, Randall J.

2009-01-01

Two statistics are presented that can be used to rank input parameters utilized by a model in terms of their relative identifiability based on a given or possible future calibration dataset. Identifiability is defined here as the capability of model calibration to constrain parameters used by a model. Both statistics require that the sensitivity of each model parameter be calculated for each model output for which there are actual or presumed field measurements. Singular value decomposition (SVD) of the weighted sensitivity matrix is then undertaken to quantify the relation between the parameters and observations that, in turn, allows selection of calibration solution and null spaces spanned by unit orthogonal vectors. The first statistic presented, "parameter identifiability", is quantitatively defined as the direction cosine between a parameter and its projection onto the calibration solution space. This varies between zero and one, with zero indicating complete non-identifiability and one indicating complete identifiability. The second statistic, "relative error reduction", indicates the extent to which the calibration process reduces error in estimation of a parameter from its pre-calibration level where its value must be assigned purely on the basis of prior expert knowledge. This is more sophisticated than identifiability, in that it takes greater account of the noise associated with the calibration dataset. Like identifiability, it has a maximum value of one (which can only be achieved if there is no measurement noise). Conceptually it can fall to zero; and even below zero if a calibration problem is poorly posed. An example, based on a coupled groundwater/surface-water model, is included that demonstrates the utility of the statistics. ?? 2009 Elsevier B.V.

Research on rolling element bearing fault diagnosis based on genetic algorithm matching pursuit

NASA Astrophysics Data System (ADS)

Rong, R. W.; Ming, T. F.

2017-12-01

In order to solve the problem of slow computation speed, matching pursuit algorithm is applied to rolling bearing fault diagnosis, and the improvement are conducted from two aspects that are the construction of dictionary and the way to search for atoms. To be specific, Gabor function which can reflect time-frequency localization characteristic well is used to construct the dictionary, and the genetic algorithm to improve the searching speed. A time-frequency analysis method based on genetic algorithm matching pursuit (GAMP) algorithm is proposed. The way to set property parameters for the improvement of the decomposition results is studied. Simulation and experimental results illustrate that the weak fault feature of rolling bearing can be extracted effectively by this proposed method, at the same time, the computation speed increases obviously.

Fourier transform wavefront control with adaptive prediction of the atmosphere.

PubMed

Poyneer, Lisa A; Macintosh, Bruce A; Véran, Jean-Pierre

2007-09-01

Predictive Fourier control is a temporal power spectral density-based adaptive method for adaptive optics that predicts the atmosphere under the assumption of frozen flow. The predictive controller is based on Kalman filtering and a Fourier decomposition of atmospheric turbulence using the Fourier transform reconstructor. It provides a stable way to compensate for arbitrary numbers of atmospheric layers. For each Fourier mode, efficient and accurate algorithms estimate the necessary atmospheric parameters from closed-loop telemetry and determine the predictive filter, adjusting as conditions change. This prediction improves atmospheric rejection, leading to significant improvements in system performance. For a 48x48 actuator system operating at 2 kHz, five-layer prediction for all modes is achievable in under 2x10(9) floating-point operations/s.

Uncertainty Analysis of Decomposing Polyurethane Foam

NASA Technical Reports Server (NTRS)

Hobbs, Michael L.; Romero, Vicente J.

2000-01-01

Sensitivity/uncertainty analyses are necessary to determine where to allocate resources for improved predictions in support of our nation's nuclear safety mission. Yet, sensitivity/uncertainty analyses are not commonly performed on complex combustion models because the calculations are time consuming, CPU intensive, nontrivial exercises that can lead to deceptive results. To illustrate these ideas, a variety of sensitivity/uncertainty analyses were used to determine the uncertainty associated with thermal decomposition of polyurethane foam exposed to high radiative flux boundary conditions. The polyurethane used in this study is a rigid closed-cell foam used as an encapsulant. Related polyurethane binders such as Estane are used in many energetic materials of interest to the JANNAF community. The complex, finite element foam decomposition model used in this study has 25 input parameters that include chemistry, polymer structure, and thermophysical properties. The response variable was selected as the steady-state decomposition front velocity calculated as the derivative of the decomposition front location versus time. An analytical mean value sensitivity/uncertainty (MV) analysis was used to determine the standard deviation by taking numerical derivatives of the response variable with respect to each of the 25 input parameters. Since the response variable is also a derivative, the standard deviation was essentially determined from a second derivative that was extremely sensitive to numerical noise. To minimize the numerical noise, 50-micrometer element dimensions and approximately 1-msec time steps were required to obtain stable uncertainty results. As an alternative method to determine the uncertainty and sensitivity in the decomposition front velocity, surrogate response surfaces were generated for use with a constrained Latin Hypercube Sampling (LHS) technique. Two surrogate response surfaces were investigated: 1) a linear surrogate response surface (LIN) and 2) a quadratic response surface (QUAD). The LHS techniques do not require derivatives of the response variable and are subsequently relatively insensitive to numerical noise. To compare the LIN and QUAD methods to the MV method, a direct LHS analysis (DLHS) was performed using the full grid and timestep resolved finite element model. The surrogate response models (LIN and QUAD) are shown to give acceptable values of the mean and standard deviation when compared to the fully converged DLHS model.

Analysis of Self-Excited Combustion Instabilities Using Decomposition Techniques

DTIC Science & Technology

2016-07-05

are evaluated for the study of self-excited longitudinal combustion instabilities in laboratory-scaled single-element gas turbine and rocket...Air Force Base, California 93524 DOI: 10.2514/1.J054557 Proper orthogonal decomposition and dynamic mode decomposition are evaluated for the study of...instabilities. In addition, we also evaluate the capabilities of the methods to deal with data sets of different spatial extents and temporal resolution

An Integrated Chemical Reactor-Heat Exchanger Based on Ammonium Carbamate (POSTPRINT)

DTIC Science & Technology

2012-10-01

With the scrubber and exhaust operating, the test cell ammonia concentration remains below 5 ppm. To further reduce NH3 release into the test cell...material has a high decomposition enthalpy and exhibits decomposition over a wide range of temperatures. AC decomposition produces ammonia and carbon...installation due to toxic gas ( ammonia ) generation during operation. Therefore, the experiment is intended to be remotely operated. A secondary control

Thermal Decomposition Behaviors and Burning Characteristics of AN/Nitramine-Based Composite Propellant

NASA Astrophysics Data System (ADS)

Naya, Tomoki; Kohga, Makoto

2015-04-01

Ammonium nitrate (AN) has attracted much attention due to its clean burning nature as an oxidizer. However, an AN-based composite propellant has the disadvantages of low burning rate and poor ignitability. In this study, we added nitramine of cyclotrimethylene trinitramine (RDX) or cyclotetramethylene tetranitramine (HMX) as a high-energy material to AN propellants to overcome these disadvantages. The thermal decomposition and burning rate characteristics of the prepared propellants were examined as the ratio of AN and nitramine was varied. In the thermal decomposition process, AN/RDX propellants showed unique mass loss peaks in the lower temperature range that were not observed for AN or RDX propellants alone. AN and RDX decomposed continuously as an almost single oxidizer in the AN/RDX propellant. In contrast, AN/HMX propellants exhibited thermal decomposition characteristics similar to those of AN and HMX, which decomposed almost separately in the thermal decomposition of the AN/HMX propellant. The ignitability was improved and the burning rate increased by the addition of nitramine for both AN/RDX and AN/HMX propellants. The increased burning rates of AN/RDX propellants were greater than those of AN/HMX. The difference in the thermal decomposition and burning characteristics was caused by the interaction between AN and RDX.

Phase History Decomposition for efficient Scatterer Classification in SAR Imagery

DTIC Science & Technology

2011-09-15

frequency. Professor Rick Martin provided key advice on frequency parameter estimation and the relationship between likelihood ratio testing and the least...132 6.1.1 Imaging Error Due to Interpolation . . . . . . . . . . . . . . . . . . . . . . . . 135 6.2 Subwindow Design and Weighting... test . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 MF matched filter

Optimizing LX-17 Thermal Decomposition Model Parameters with Evolutionary Algorithms

NASA Astrophysics Data System (ADS)

Moore, Jason; McClelland, Matthew; Tarver, Craig; Hsu, Peter; Springer, H. Keo

2017-06-01

We investigate and model the cook-off behavior of LX-17 because this knowledge is critical to understanding system response in abnormal thermal environments. Thermal decomposition of LX-17 has been explored in conventional ODTX (One-Dimensional Time-to-eXplosion), PODTX (ODTX with pressure-measurement), TGA (thermogravimetric analysis), and DSC (differential scanning calorimetry) experiments using varied temperature profiles. These experimental data are the basis for developing multiple reaction schemes with coupled mechanics in LLNL's multi-physics hydrocode, ALE3D (Arbitrary Lagrangian-Eulerian code in 2D and 3D). We employ evolutionary algorithms to optimize reaction rate parameters on high performance computing clusters. Once experimentally validated, this model will be scalable to a number of applications involving LX-17 and can be used to develop more sophisticated experimental methods. Furthermore, the optimization methodology developed herein should be applicable to other high explosive materials. This work was performed under the auspices of the U.S. DOE by LLNL under contract DE-AC52-07NA27344. LLNS, LLC.

A general range-separated double-hybrid density-functional theory

NASA Astrophysics Data System (ADS)

Kalai, Cairedine; Toulouse, Julien

2018-04-01

A range-separated double-hybrid (RSDH) scheme which generalizes the usual range-separated hybrids and double hybrids is developed. This scheme consistently uses a two-parameter Coulomb-attenuating-method (CAM)-like decomposition of the electron-electron interaction for both exchange and correlation in order to combine Hartree-Fock exchange and second-order Møller-Plesset (MP2) correlation with a density functional. The RSDH scheme relies on an exact theory which is presented in some detail. Several semi-local approximations are developed for the short-range exchange-correlation density functional involved in this scheme. After finding optimal values for the two parameters of the CAM-like decomposition, the RSDH scheme is shown to have a relatively small basis dependence and to provide atomization energies, reaction barrier heights, and weak intermolecular interactions globally more accurate or comparable to range-separated MP2 or standard MP2. The RSDH scheme represents a new family of double hybrids with minimal empiricism which could be useful for general chemical applications.

Smoothing spline ANOVA frailty model for recurrent event data.

PubMed

Du, Pang; Jiang, Yihua; Wang, Yuedong

2011-12-01

Gap time hazard estimation is of particular interest in recurrent event data. This article proposes a fully nonparametric approach for estimating the gap time hazard. Smoothing spline analysis of variance (ANOVA) decompositions are used to model the log gap time hazard as a joint function of gap time and covariates, and general frailty is introduced to account for between-subject heterogeneity and within-subject correlation. We estimate the nonparametric gap time hazard function and parameters in the frailty distribution using a combination of the Newton-Raphson procedure, the stochastic approximation algorithm (SAA), and the Markov chain Monte Carlo (MCMC) method. The convergence of the algorithm is guaranteed by decreasing the step size of parameter update and/or increasing the MCMC sample size along iterations. Model selection procedure is also developed to identify negligible components in a functional ANOVA decomposition of the log gap time hazard. We evaluate the proposed methods with simulation studies and illustrate its use through the analysis of bladder tumor data. © 2011, The International Biometric Society.

[Technology of composting].

PubMed

Jäger, B

1983-09-01

The technology of composting must guarantee the material-chemical, biological and physical-technical reaction conditions essential for the rotting process. In this, the constituents of the input material and the C/N ratio play an important role. Maintaining optimum decomposition conditions is rendered difficult by the fact that the physical-technical reaction parameters partly exclude each other. These are: optimum humidity, adequate air/oxygen supply, large active surface, loose structure with sufficient decomposition volume. The processing of the raw refuse required to maintain the physical-technical reaction parameters can be carried out either by the conventional method of preliminary fragmentizing, sieving and mixing or else in conjunction with separating recycling in adapted systems. The latter procedure obviates some drawbacks which mainly result from the high expenditure required for preliminary fragmentation of the raw refuse. Moreover, presorting affords the possibility of reducing the heavy-metal content of the organic composing fraction and this approaches a solution to the noxa disposal problem which at present stands in the way of being accepted as an ecological waste disposal method.

Thermal decomposition of multiply charged T-rich oligonucleotide anions in the gas phase. Influence of internal solvation on the arrhenius parameters for neutral base loss.

PubMed

Daneshfar, Rambod; Klassen, John S

2006-09-01

Arrhenius activation parameters (E(a), A) for the loss of neutral nucleobases from a series of T-rich, doubly and triply deprotonated 15- and 20-mer oligodeoxynucleotides (ODN) containing a single reactive base (X = A or C) with the sequence, XT14, XT19 and T19X, have been determined using the blackbody infrared radiative dissociation technique. The A-containing anions are significantly more reactive (> or =3000 times) than the C-containing ions over the temperature range investigated. Importantly, the Arrhenius parameters for the loss of AH exhibit a strong dependence on size of the ODN and, to some extent, the charge state; the Arrhenius parameters increase with size and charge (Ea = 29-39 kcal mol(-1), A = 10(15)-10(20) s(-1)). In contrast, the parameters for the loss of CH are much less sensitive to size (Ea = 35-39 kcal mol(-1), A = 10(14)-10(17) s(-1)). The results are consistent with a greater contribution from the internal solvation of the reactive base to the Arrhenius parameters for the loss of A, compared with C, from the 15- and 20-mers. To further probe differences in internal solvation of A and C, hydrogen/deuterium exchange was carried out on AT19(-3), T19A(-3), CT19(-3) and T19C(-3) using D2O as the exchange reagent. However, the H/D exchange results did not reveal any differences in internal solvation within the ODN anions. Arrhenius parameters for the dissociation of noncovalent complexes of T20(-3) and the neutral nucleobase AH or CH have also been determined. Differences in the parameters indicate differences in the nature of the intermolecular interactions. It is proposed that neutral A-T interactions (i.e., base-base), which originate in solution, dominate in the case of (T20 + AH)(-3), while charge solvation, involving CH and a deprotonated phosphate group, is present for (T20 + CH)(-3).

A graph decomposition-based approach for water distribution network optimization

NASA Astrophysics Data System (ADS)

Zheng, Feifei; Simpson, Angus R.; Zecchin, Aaron C.; Deuerlein, Jochen W.

2013-04-01

A novel optimization approach for water distribution network design is proposed in this paper. Using graph theory algorithms, a full water network is first decomposed into different subnetworks based on the connectivity of the network's components. The original whole network is simplified to a directed augmented tree, in which the subnetworks are substituted by augmented nodes and directed links are created to connect them. Differential evolution (DE) is then employed to optimize each subnetwork based on the sequence specified by the assigned directed links in the augmented tree. Rather than optimizing the original network as a whole, the subnetworks are sequentially optimized by the DE algorithm. A solution choice table is established for each subnetwork (except for the subnetwork that includes a supply node) and the optimal solution of the original whole network is finally obtained by use of the solution choice tables. Furthermore, a preconditioning algorithm is applied to the subnetworks to produce an approximately optimal solution for the original whole network. This solution specifies promising regions for the final optimization algorithm to further optimize the subnetworks. Five water network case studies are used to demonstrate the effectiveness of the proposed optimization method. A standard DE algorithm (SDE) and a genetic algorithm (GA) are applied to each case study without network decomposition to enable a comparison with the proposed method. The results show that the proposed method consistently outperforms the SDE and GA (both with tuned parameters) in terms of both the solution quality and efficiency.

Passive simulation of the nonlinear port-Hamiltonian modeling of a Rhodes Piano

NASA Astrophysics Data System (ADS)

Falaize, Antoine; Hélie, Thomas

2017-03-01

This paper deals with the time-domain simulation of an electro-mechanical piano: the Fender Rhodes. A simplified description of this multi-physical system is considered. It is composed of a hammer (nonlinear mechanical component), a cantilever beam (linear damped vibrating component) and a pickup (nonlinear magneto-electronic transducer). The approach is to propose a power-balanced formulation of the complete system, from which a guaranteed-passive simulation is derived to generate physically-based realistic sound synthesis. Theses issues are addressed in four steps. First, a class of Port-Hamiltonian Systems is introduced: these input-to-output systems fulfill a power balance that can be decomposed into conservative, dissipative and source parts. Second, physical models are proposed for each component and are recast in the port-Hamiltonian formulation. In particular, a finite-dimensional model of the cantilever beam is derived, based on a standard modal decomposition applied to the Euler-Bernoulli model. Third, these systems are interconnected, providing a nonlinear finite-dimensional Port-Hamiltonian System of the piano. Fourth, a passive-guaranteed numerical method is proposed. This method is built to preserve the power balance in the discrete-time domain, and more precisely, its decomposition structured into conservative, dissipative and source parts. Finally, simulations are performed for a set of physical parameters, based on empirical but realistic values. They provide a variety of audio signals which are perceptively relevant and qualitatively similar to some signals measured on a real instrument.

[Progress in Raman spectroscopic measurement of methane hydrate].

PubMed

Xu, Feng; Zhu, Li-hua; Wu, Qiang; Xu, Long-jun

2009-09-01

Complex thermodynamics and kinetics problems are involved in the methane hydrate formation and decomposition, and these problems are crucial to understanding the mechanisms of hydrate formation and hydrate decomposition. However, it was difficult to accurately obtain such information due to the difficulty of measurement since methane hydrate is only stable under low temperature and high pressure condition, and until recent years, methane hydrate has been measured in situ using Raman spectroscopy. Raman spectroscopy, a non-destructive and non-invasive technique, is used to study vibrational modes of molecules. Studies of methane hydrate using Raman spectroscopy have been developed over the last decade. The Raman spectra of CH4 in vapor phase and in hydrate phase are presented in this paper. The progress in the research on methane hydrate formation thermodynamics, formation kinetics, decomposition kinetics and decomposition mechanism based on Raman spectroscopic measurements in the laboratory and deep sea are reviewed. Formation thermodynamic studies, including in situ observation of formation condition of methane hydrate, analysis of structure, and determination of hydrate cage occupancy and hydration numbers by using Raman spectroscopy, are emphasized. In the aspect of formation kinetics, research on variation in hydrate cage amount and methane concentration in water during the growth of hydrate using Raman spectroscopy is also introduced. For the methane hydrate decomposition, the investigation associated with decomposition mechanism, the mutative law of cage occupancy ratio and the formulation of decomposition rate in porous media are described. The important aspects for future hydrate research based on Raman spectroscopy are discussed.

Electron beam technology for multipollutant emissions control from heavy fuel oil-fired boiler.

PubMed

Chmielewski, Andrzej G; Ostapczuk, Anna; Licki, Janusz

2010-08-01

The electron beam treatment technology for purification of exhaust gases from the burning of heavy fuel oil (HFO) mazout with sulfur content approximately 3 wt % was tested at the Institute of Nuclear Chemistry and Technology laboratory plant. The parametric study was conducted to determine the sulfur dioxide (SO2), oxides of nitrogen (NO(x)), and polycyclic aromatic hydrocarbon (PAH) removal efficiency as a function of temperature and humidity of irradiated gases, absorbed irradiation dose, and ammonia stoichiometry process parameters. In the test performed under optimal conditions with an irradiation dose of 12.4 kGy, simultaneous removal efficiencies of approximately 98% for SO2, and 80% for NO(x) were recorded. The simultaneous decrease of PAH and one-ringed aromatic hydrocarbon (benzene, toluene, and xylenes [BTX]) concentrations was observed in the irradiated flue gas. Overall removal efficiencies of approximately 42% for PAHs and 86% for BTXs were achieved with an irradiation dose 5.3 kGy. The decomposition ratio of these compounds increased with an increase of absorbed dose. The decrease of PAH and BTX concentrations was followed by the increase of oxygen-containing aromatic hydrocarbon concentrations. The PAH and BTX decomposition process was initialized through the reaction with hydroxyl radicals that formed in the electron beam irradiated flue gas. Their decomposition process is based on similar principles as the primary reaction concerning SO2 and NO(x) removal; that is, free radicals attack organic compound chains or rings, causing volatile organic compound decomposition. Thus, the electron beam flue gas treatment (EBFGT) technology ensures simultaneous removal of acid (SO2 and NO(x)) and organic (PAH and BTX) pollutants from flue gas emitted from burning of HFO. This technology is a multipollutant emission control technology that can be applied for treatment of flue gas emitted from coal-, lignite-, and HFO-fired boilers. Other thermal processes such as metallurgy and municipal waste incinerators are potential candidates for this technology application.

Application of spectral decomposition algorithm for mapping water quality in a turbid lake (Lake Kasumigaura, Japan) from Landsat TM data

NASA Astrophysics Data System (ADS)

Oyama, Youichi; Matsushita, Bunkei; Fukushima, Takehiko; Matsushige, Kazuo; Imai, Akio

The remote sensing of Case 2 water has been far less successful than that of Case 1 water, due mainly to the complex interactions among optically active substances (e.g., phytoplankton, suspended sediments, colored dissolved organic matter, and water) in the former. To address this problem, we developed a spectral decomposition algorithm (SDA), based on a spectral linear mixture modeling approach. Through a tank experiment, we found that the SDA-based models were superior to conventional empirical models (e.g. using single band, band ratio, or arithmetic calculation of band) for accurate estimates of water quality parameters. In this paper, we develop a method for applying the SDA to Landsat-5 TM data on Lake Kasumigaura, a eutrophic lake in Japan characterized by high concentrations of suspended sediment, for mapping chlorophyll-a (Chl-a) and non-phytoplankton suspended sediment (NPSS) distributions. The results show that the SDA-based estimation model can be obtained by a tank experiment. Moreover, by combining this estimation model with satellite-SRSs (standard reflectance spectra: i.e., spectral end-members) derived from bio-optical modeling, we can directly apply the model to a satellite image. The same SDA-based estimation model for Chl-a concentration was applied to two Landsat-5 TM images, one acquired in April 1994 and the other in February 2006. The average Chl-a estimation error between the two was 9.9%, a result that indicates the potential robustness of the SDA-based estimation model. The average estimation error of NPSS concentration from the 2006 Landsat-5 TM image was 15.9%. The key point for successfully applying the SDA-based estimation model to satellite data is the method used to obtain a suitable satellite-SRS for each end-member.

Analytically derived switching functions for exact H2+ eigenstates

NASA Astrophysics Data System (ADS)

Thorson, W. R.; Kimura, M.; Choi, J. H.; Knudson, S. K.

1981-10-01

Electron translation factors (ETF's) appropriate for slow atomic collisions may be constructed using switching functions. In this paper we derive a set of switching functions for the H2+ system by an analytical "two-center decomposition" of the exact molecular eigenstates. These switching functions are closely approximated by the simple form f=bη, where η is the "angle variable" of prolate spheroidal coordinates. For given united atom angular momentum quantum numbers (l,m), the characteristic parameter blm depends only on the quantity c2=-ɛR22, where ɛ is the electronic binding energy and R the internuclear distance in a.u. The resulting parameters are in excellent agreement with those found in our earlier work by a heuristic "optimization" scheme based on a study of coupling matrix-element behavior for a number of H2+ states. An approximate extension to asymmetric cases (HeH2+) has also been made. Nonadiabatic couplings based on these switching functions have been used in recent close-coupling calculations for H+-H(1s) collisions and He2+-H(1s) collisions at energies 1.0-20 keV.

Decomposition Theory in the Teaching of Elementary Linear Algebra.

ERIC Educational Resources Information Center

London, R. R.; Rogosinski, H. P.

1990-01-01

Described is a decomposition theory from which the Cayley-Hamilton theorem, the diagonalizability of complex square matrices, and functional calculus can be developed. The theory and its applications are based on elementary polynomial algebra. (KR)

Adaptive variational mode decomposition method for signal processing based on mode characteristic

NASA Astrophysics Data System (ADS)

Lian, Jijian; Liu, Zhuo; Wang, Haijun; Dong, Xiaofeng

2018-07-01

Variational mode decomposition is a completely non-recursive decomposition model, where all the modes are extracted concurrently. However, the model requires a preset mode number, which limits the adaptability of the method since a large deviation in the number of mode set will cause the discard or mixing of the mode. Hence, a method called Adaptive Variational Mode Decomposition (AVMD) was proposed to automatically determine the mode number based on the characteristic of intrinsic mode function. The method was used to analyze the simulation signals and the measured signals in the hydropower plant. Comparisons have also been conducted to evaluate the performance by using VMD, EMD and EWT. It is indicated that the proposed method has strong adaptability and is robust to noise. It can determine the mode number appropriately without modulation even when the signal frequencies are relatively close.

Native conflict awared layout decomposition in triple patterning lithography using bin-based library matching method

NASA Astrophysics Data System (ADS)

Ke, Xianhua; Jiang, Hao; Lv, Wen; Liu, Shiyuan

2016-03-01

Triple patterning (TP) lithography becomes a feasible technology for manufacturing as the feature size further scale down to sub 14/10 nm. In TP, a layout is decomposed into three masks followed with exposures and etches/freezing processes respectively. Previous works mostly focus on layout decomposition with minimal conflicts and stitches simultaneously. However, since any existence of native conflict will result in layout re-design/modification and reperforming the time-consuming decomposition, the effective method that can be aware of native conflicts (NCs) in layout is desirable. In this paper, a bin-based library matching method is proposed for NCs detection and layout decomposition. First, a layout is divided into bins and the corresponding conflict graph in each bin is constructed. Then, we match the conflict graph in a prebuilt colored library, and as a result the NCs can be located and highlighted quickly.

Breast composition measurement with a cadmium-zinc-telluride based spectral computed tomography system

PubMed Central

Ding, Huanjun; Ducote, Justin L.; Molloi, Sabee

2012-01-01

Purpose: To investigate the feasibility of breast tissue composition in terms of water, lipid, and protein with a cadmium-zinc-telluride (CZT) based computed tomography (CT) system to help better characterize suspicious lesions. Methods: Simulations and experimental studies were performed using a spectral CT system equipped with a CZT-based photon-counting detector with energy resolution. Simulations of the figure-of-merit (FOM), the signal-to-noise ratio (SNR) of the dual energy image with respect to the square root of mean glandular dose (MGD), were performed to find the optimal configuration of the experimental acquisition parameters. A calibration phantom 3.175 cm in diameter was constructed from polyoxymethylene plastic with cylindrical holes that were filled with water and oil. Similarly, sized samples of pure adipose and pure lean bovine tissues were used for the three-material decomposition. Tissue composition results computed from the images were compared to the chemical analysis data of the tissue samples. Results: The beam energy was selected to be 100 kVp with a splitting energy of 40 keV. The tissue samples were successfully decomposed into water, lipid, and protein contents. The RMS error of the volumetric percentage for the three-material decomposition, as compared to data from the chemical analysis, was estimated to be approximately 5.7%. Conclusions: The results of this study suggest that the CZT-based photon-counting detector may be employed in the CT system to quantify the water, lipid, and protein mass densities in tissue with a relatively good agreement. PMID:22380361

Automatic P-S phase picking procedure based on Kurtosis: Vanuatu region case study

NASA Astrophysics Data System (ADS)

Baillard, C.; Crawford, W. C.; Ballu, V.; Hibert, C.

2012-12-01

Automatic P and S phase picking is indispensable for large seismological data sets. Robust algorithms, based on short term and long term average ratio comparison (Allen, 1982), are commonly used for event detection, but further improvements can be made in phase identification and picking. We present a picking scheme using consecutively Kurtosis-derived Characteristic Functions (CF) and Eigenvalue decompositions on 3-component seismic data to independently pick P and S arrivals. When computed over a sliding window of the signal, a sudden increase in the CF reveals a transition from a gaussian to a non-gaussian distribution, characterizing the phase onset (Saragiotis, 2002). One advantage of the method is that it requires much fewer adjustable parameters than competing methods. We modified the Kurtosis CF to improve pick precision, by computing the CF over several frequency bandwidths, window sizes and smoothing parameters. Once phases were picked, we determined the onset type (P or S) using polarization parameters (rectilinearity, azimuth and dip) calculated using Eigenvalue decompositions of the covariance matrix (Cichowicz, 1993). Finally, we removed bad picks using a clustering procedure and the signal-to-noise ratio (SNR). The pick quality index was also assigned based on the SNR value. Amplitude calculation is integrated into the procedure to enable automatic magnitude calculation. We applied this procedure to data from a network of 30 wideband seismometers (including 10 oceanic bottom seismometers) in Vanuatu that ran for 10 months from May 2008 to February 2009. We manually picked the first 172 events of June, whose local magnitudes range from 0.7 to 3.7. We made a total of 1601 picks, 1094 P and 507 S. We then applied our automatic picking to the same dataset. 70% of the manually picked onsets were picked automatically. For P-picks, the difference between manual and automatic picks is 0.01 ± 0.08 s overall; for the best quality picks (quality index 0: 64% of the P-picks) the difference is -0.01 ± 0.07 s. For S-picks, the difference is -0.09 ± 0.26 s overall and -0.06 ± 0.14 s for good quality picks (index 1: 26% of the S-picks). Residuals showed no dependence on the event magnitudes. The method independently picks S and P waves with good precision and only a few parameters to adjust for relatively small earthquakes (mostly ≤ 2 Ml). The automatic procedure was then applied to the whole dataset. Earthquake locations obtained by inverting onset arrivals revealed clustering and lineations that helped us to constrain the subduction plane. Those key parameters will be integrated to a 3D finite-difference modeling and compared to GPS data in order to better understand the complex geodynamics behavior of the Vanuatu region.

Thermochemistry, Tautomerism, and Thermal Decomposition of 1,5-Diaminotetrazole: A High-Level ab Initio Study.

PubMed

Shakhova, Margarita V; Muravyev, Nikita V; Gritsan, Nina P; Kiselev, Vitaly G

2018-04-19

Thermochemistry, kinetics, and mechanism of thermal decomposition of 1,5-diaminotetrazole (DAT), a widely used "building block" of nitrogen-rich energetic compounds, were studied theoretically at a high and reliable level of theory (viz., using the explicitly correlated CCSD(T)-F12/aug-cc-pVTZ procedure). Quantum chemical calculations provided detailed insight into the thermolysis mechanism of DAT missing in the existing literature. Moreover, several contradictory assumptions on the mechanism and key intermediates of thermolysis were resolved. The unimolecular primary decomposition reactions of the seven isomers of DAT were studied in the gas phase and in the melt using a simplified model of the latter. The two-step reaction of N 2 elimination from the diamino tautomer was found to be the primary decomposition process of DAT in the gas phase and melt. The effective Arrhenius parameters of this process were calculated to be E a = 43.4 kcal mol -1 and log( A/s -1 ) = 15.2 in a good agreement with the experimental values. Contrary to the existing literature data, all other decomposition channels of DAT isomers turned out to be kinetically unimportant. Apart from this, a new primary decomposition channel yielding N 2 , cyanamide, and 1,1-diazene was found for some H-bonded dimers of DAT. We also determined a reliable and mutually consistent set of thermochemical values for DAT (Δ f H solid 0 = 74.5 ± 1.5 kcal·mol -1 ) by combining theoretically calculated (W1 multilevel procedure along with an isodesmic reaction) gas phase enthalpy of formation (Δ f H gas 0 = 100.7 ± 1.0 kcal·mol -1 ) and experimentally measured sublimation enthalpy (Δ sub H 0 = 26.2 ± 0.5 kcal·mol -1 ).

Microbial decomposition is highly sensitive to leaf litter emersion in a permanent temperate stream.

PubMed

Mora-Gómez, Juanita; Duarte, Sofia; Cássio, Fernanda; Pascoal, Cláudia; Romaní, Anna M

2018-04-15

Drought frequency and intensity in some temperate regions are forecasted to increase under the ongoing global change, which might expose permanent streams to intermittence and have severe repercussions on stream communities and ecosystem processes. In this study, we investigated the effect of drought duration on microbial decomposition of Populus nigra leaf litter in a temperate permanent stream (Oliveira, NW Portugal). Specifically, we measured the response of the structural (assemblage composition, bacterial and fungal biomass) and functional (leaf litter decomposition, extracellular enzyme activities (EEA), and fungal sporulation) parameters of fungal and bacterial communities on leaf litter exposed to emersion during different time periods (7, 14 and 21d). Emersion time affected microbial assemblages and litter decomposition, but the response differed among variables. Leaf decomposition rates and the activity of β-glucosidase, cellobiohydrolase and phosphatase were gradually reduced with increasing emersion time, while β-xylosidase reduction was similar when emersion last for 7 or more days, and the phenol oxidase reduction was similar at 14 and 21days of leaf emersion. Microbial biomass and fungal sporulation were reduced after 21days of emersion. The structure of microbial assemblages was affected by the duration of the emersion period. The shifts in fungal assemblages were correlated with a decreased microbial capacity to degrade lignin and hemicellulose in leaf litter exposed to emersion. Additionally, some resilience was observed in leaf litter mass loss, bacterial biomass, some enzyme activities and structure of fungal assemblages. Our study shows that drought can strongly alter structural and functional aspects of microbial decomposers. Therefore, the exposure of leaf litter to increasing emersion periods in temperate streams is expected to affect decomposer communities and overall decomposition of plant material by decelerating carbon cycling in streams. Copyright © 2017 Elsevier B.V. All rights reserved.

Two Dimensional Finite Element Based Magnetotelluric Inversion using Singular Value Decomposition Method on Transverse Electric Mode

NASA Astrophysics Data System (ADS)

Tjong, Tiffany; Yihaa’ Roodhiyah, Lisa; Nurhasan; Sutarno, Doddy

2018-04-01

In this work, an inversion scheme was performed using a vector finite element (VFE) based 2-D magnetotelluric (MT) forward modelling. We use an inversion scheme with Singular value decomposition (SVD) method toimprove the accuracy of MT inversion.The inversion scheme was applied to transverse electric (TE) mode of MT. SVD method was used in this inversion to decompose the Jacobian matrices. Singular values which obtained from the decomposition process were analyzed. This enabled us to determine the importance of data and therefore to define a threshold for truncation process. The truncation of singular value in inversion processcould improve the resulted model.

Analysis of weld geometry and liquid flow in laser transmission welding between polyethylene terephthalate (PET) and Ti6Al4V based on numerical simulation

NASA Astrophysics Data System (ADS)

Ai, Yuewei; Zheng, Kang; Shin, Yung C.; Wu, Benxin

2018-07-01

The laser transmission welding of polyethylene terephthalate (PET) and titanium alloy Ti6Al4V involving the evaluating of the resultant geometry and quality of welds is investigated using a fiber laser in this paper. A 3D transient numerical model considering the melting and fluid flow is developed to predict the weld geometry and porosity formation. The temperature field, molten pool and liquid flow are simulated with varying laser power and welding speed based on the model. It is observed that the weld geometry predictions from the numerical simulation are in good agreement with the experimental data. The results show that the porosity consistently appears in the high temperature region due to the decomposition of PET. In addition, it has also been found that the molten pool with a vortex flow pattern is formed only in the PET layer and the welding processing parameters have significant effects on the fluid flow, which eventually affects the heat transfer, molten pool geometry and weld formation. Consequently, it is shown adopting appropriate welding processing parameters based on the proposed model is essential for the sound weld without defects.

Rapid perfusion quantification using Welch-Satterthwaite approximation and analytical spectral filtering

NASA Astrophysics Data System (ADS)

Krishnan, Karthik; Reddy, Kasireddy V.; Ajani, Bhavya; Yalavarthy, Phaneendra K.

2017-02-01

CT and MR perfusion weighted imaging (PWI) enable quantification of perfusion parameters in stroke studies. These parameters are calculated from the residual impulse response function (IRF) based on a physiological model for tissue perfusion. The standard approach for estimating the IRF is deconvolution using oscillatory-limited singular value decomposition (oSVD) or Frequency Domain Deconvolution (FDD). FDD is widely recognized as the fastest approach currently available for deconvolution of CT Perfusion/MR PWI. In this work, three faster methods are proposed. The first is a direct (model based) crude approximation to the final perfusion quantities (Blood flow, Blood volume, Mean Transit Time and Delay) using the Welch-Satterthwaite approximation for gamma fitted concentration time curves (CTC). The second method is a fast accurate deconvolution method, we call Analytical Fourier Filtering (AFF). The third is another fast accurate deconvolution technique using Showalter's method, we call Analytical Showalter's Spectral Filtering (ASSF). Through systematic evaluation on phantom and clinical data, the proposed methods are shown to be computationally more than twice as fast as FDD. The two deconvolution based methods, AFF and ASSF, are also shown to be quantitatively accurate compared to FDD and oSVD.

Reaction behaviors of decomposition of monocrotophos in aqueous solution by UV and UV/O processes.

PubMed

Ku, Y; Wang, W; Shen, Y S

2000-02-01

The decomposition of monocrotophos (cis-3-dimethoxyphosphinyloxy-N-methyl-crotonamide) in aqueous solution by UV and UV/O(3) processes was studied. The experiments were carried out under various solution pH values to investigate the decomposition efficiencies of the reactant and organic intermediates in order to determine the completeness of decomposition. The photolytic decomposition rate of monocrotophos was increased with increasing solution pH because the solution pH affects the distribution and light absorbance of monocrotophos species. The combination of O(3) with UV light apparently promoted the decomposition and mineralization of monocrotophos in aqueous solution. For the UV/O(3) process, the breakage of the >C=C< bond of monocrotophos by ozone molecules was found to occur first, followed by mineralization by hydroxyl radicals to generate CO(3)(2-), PO4(3-), and NO(3)(-) anions in sequence. The quasi-global kinetics based on a simplified consecutive-parallel reaction scheme was developed to describe the temporal behavior of monocrotophos decomposition in aqueous solution by the UV/O(3) process.

Nonlinear dimensionality reduction of data lying on the multicluster manifold.

PubMed

Meng, Deyu; Leung, Yee; Fung, Tung; Xu, Zongben

2008-08-01

A new method, which is called decomposition-composition (D-C) method, is proposed for the nonlinear dimensionality reduction (NLDR) of data lying on the multicluster manifold. The main idea is first to decompose a given data set into clusters and independently calculate the low-dimensional embeddings of each cluster by the decomposition procedure. Based on the intercluster connections, the embeddings of all clusters are then composed into their proper positions and orientations by the composition procedure. Different from other NLDR methods for multicluster data, which consider associatively the intracluster and intercluster information, the D-C method capitalizes on the separate employment of the intracluster neighborhood structures and the intercluster topologies for effective dimensionality reduction. This, on one hand, isometrically preserves the rigid-body shapes of the clusters in the embedding process and, on the other hand, guarantees the proper locations and orientations of all clusters. The theoretical arguments are supported by a series of experiments performed on the synthetic and real-life data sets. In addition, the computational complexity of the proposed method is analyzed, and its efficiency is theoretically analyzed and experimentally demonstrated. Related strategies for automatic parameter selection are also examined.

Weaker soil carbon-climate feedbacks resulting from microbial and abiotic interactions

NASA Astrophysics Data System (ADS)

Tang, Jinyun; Riley, William J.

2015-01-01

The large uncertainty in soil carbon-climate feedback predictions has been attributed to the incorrect parameterization of decomposition temperature sensitivity (Q10; ref. ) and microbial carbon use efficiency. Empirical experiments have found that these parameters vary spatiotemporally, but such variability is not included in current ecosystem models. Here we use a thermodynamically based decomposition model to test the hypothesis that this observed variability arises from interactions between temperature, microbial biogeochemistry, and mineral surface sorptive reactions. We show that because mineral surfaces interact with substrates, enzymes and microbes, both Q10 and microbial carbon use efficiency are hysteretic (so that neither can be represented by a single static function) and the conventional labile and recalcitrant substrate characterization with static temperature sensitivity is flawed. In a 4-K temperature perturbation experiment, our fully dynamic model predicted more variable but weaker soil carbon-climate feedbacks than did the static Q10 and static carbon use efficiency model when forced with yearly, daily and hourly variable temperatures. These results imply that current Earth system models probably overestimate the response of soil carbon stocks to global warming. Future ecosystem models should therefore consider the dynamic interactions between sorptive mineral surfaces, substrates and microbial processes.

Catalytic and inhibiting effects of lithium peroxide and hydroxide on sodium chlorate decomposition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cannon, J.C.; Zhang, Y.

1995-09-01

Chemical oxygen generators based on sodium chlorate and lithium perchlorate are used in airplanes, submarines, diving, and mine rescue. Catalytic decomposition of sodium chlorate in the presence of cobalt oxide, lithium peroxide, and lithium hydroxide is studied using thermal gravimetric analysis. Lithium peroxide and hydroxide are both moderately active catalysts for the decomposition of sodium chlorate when used alone, and inhibitors when used with the more active catalyst cobalt oxide.

The Variance of Intraclass Correlations in Three- and Four-Level Models

ERIC Educational Resources Information Center

Hedges, Larry V.; Hedberg, E. C.; Kuyper, Arend M.

2012-01-01

Intraclass correlations are used to summarize the variance decomposition in populations with multilevel hierarchical structure. There has recently been considerable interest in estimating intraclass correlations from surveys or designed experiments to provide design parameters for planning future large-scale randomized experiments. The large…

The Variance of Intraclass Correlations in Three and Four Level

ERIC Educational Resources Information Center

Hedges, Larry V.; Hedberg, Eric C.; Kuyper, Arend M.

2012-01-01

Intraclass correlations are used to summarize the variance decomposition in popula- tions with multilevel hierarchical structure. There has recently been considerable interest in estimating intraclass correlations from surveys or designed experiments to provide design parameters for planning future large-scale randomized experiments. The large…

Thermal stability of tungsten sub-nitride thin film prepared by reactive magnetron sputtering

NASA Astrophysics Data System (ADS)

Zhang, X. X.; Wu, Y. Z.; Mu, B.; Qiao, L.; Li, W. X.; Li, J. J.; Wang, P.

2017-03-01

Tungsten sub-nitride thin films deposited on silicon samples by reactive magnetron sputtering were used as a model system to study the phase stability and microstructural evolution during thermal treatments. XRD, SEM&FIB, XPS, RBS and TDS were applied to investigate the stability of tungsten nitride films after heating up to 1473 K in vacuum. At the given experimental parameters a 920 nm thick crystalline film with a tungsten and nitrogen stoichiometry of 2:1 were achieved. The results showed that no phase and microstructure change occurred due to W2N film annealing in vacuum up to 973 K. Heating up to 1073 K led to a partial decomposition of the W2N phase and the formation of a W enrichment layer at the surface. Increasing the annealing time at the same temperature, the further decomposition of the W2N phase was negligible. The complete decomposition of W2N film happened as the temperature reached up to 1473 K.

ZnO twin-cones: synthesis, photoluminescence, and catalytic decomposition of ammonium perchlorate.

PubMed

Sun, Xuefei; Qiu, Xiaoqing; Li, Liping; Li, Guangshe

2008-05-19

ZnO twin-cones, a new member to the ZnO family, were prepared directly by a solvothermal method using a mixed solution of zinc nitrate and ethanol. The reaction and growth mechanisms of ZnO twin-cones were investigated by X-ray diffraction, UV-visible spectra, infrared and ion trap mass spectra, and transmission electron microscopy. All as-prepared ZnO cones consisted of tiny single crystals with lengths of several micrometers. With prolonging of the reaction time from 1.5 h to 7 days, the twin-cone shape did not change at all, while the lattice parameters increased slightly and the emission peak of photoluminescence shifted from the green region to the near orange region. ZnO twin-cones are also explored as an additive to promote the thermal decomposition of ammonium perchlorate. The variations of photoluminescence spectra and catalytic roles in ammonium perchlorate decomposition were discussed in terms of the defect structure of ZnO twin-cones.

Theoretical investigation of HNgNH{sub 3}{sup +} ions (Ng = He, Ne, Ar, Kr, and Xe)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gao, Kunqi; Sheng, Li, E-mail: shengli@hit.edu.cn

2015-04-14

The equilibrium geometries, harmonic frequencies, and dissociation energies of HNgNH{sub 3}{sup +} ions (Ng = He, Ne, Ar, Kr, and Xe) were investigated using the following method: Becke-3-parameter-Lee-Yang-Parr (B3LYP), Boese-Matrin for Kinetics (BMK), second-order Møller-Plesset perturbation theory (MP2), and coupled-cluster with single and double excitations as well as perturbative inclusion of triples (CCSD(T)). The results indicate that HHeNH{sub 3}{sup +}, HArNH{sub 3}{sup +}, HKrNH{sub 3}{sup +}, and HXeNH{sub 3}{sup +} ions are metastable species that are protected from decomposition by high energy barriers, whereas the HNeNH{sub 3}{sup +} ion is unstable because of its relatively small energy barrier for decomposition.more » The bonding nature of noble-gas atoms in HNgNH{sub 3}{sup +} was also analyzed using the atoms in molecules approach, natural energy decomposition analysis, and natural bond orbital analysis.« less

Fluidized-bed reactor modeling for production of silicon by silane pyrolysis

NASA Technical Reports Server (NTRS)

Dudukovic, M. P.; Ramachandran, P. A.; Lai, S.

1986-01-01

An ideal backmixed reactor model (CSTR) and a fluidized bed bubbling reactor model (FBBR) were developed for silane pyrolysis. Silane decomposition is assumed to occur via two pathways: homogeneous decomposition and heterogeneous chemical vapor deposition (CVD). Both models account for homogeneous and heterogeneous silane decomposition, homogeneous nucleation, coagulation and growth by diffusion of fines, scavenging of fines by large particles, elutriation of fines and CVD growth of large seed particles. At present the models do not account for attrition. The preliminary comparison of the model predictions with experimental results shows reasonable agreement. The CSTR model with no adjustable parameter yields a lower bound on fines formed and upper estimate on production rates. The FBBR model overpredicts the formation of fines but could be matched to experimental data by adjusting the unkown jet emulsion exchange efficients. The models clearly indicate that in order to suppress the formation of fines (smoke) good gas-solid contacting in the grid region must be achieved and the formation of the bubbles suppressed.

Decomposition mechanisms and kinetics of novel energetic molecules BNFF-1 and ANFF-1: quantum-chemical modeling.

PubMed

Tsyshevsky, Roman V; Kuklja, Maija M

2013-07-18

Decomposition mechanisms, activation barriers, Arrhenius parameters, and reaction kinetics of the novel explosive compounds, 3,4-bis(4-nitro-1,2,5-oxadiazol-3-yl)-1,2,5-oxadiazole (BNFF-1), and 3-(4-amino-1,2,5-oxadiazol-3-yl)-4-(4-nitro-1,2,5-oxadiazol-3-yl)-1,2,5-oxadiazole (ANFF-1) were explored by means of density functional theory with a range of functionals combined with variational transition state theory. BNFF-1 and ANFF-1 were recently suggested to be good candidates for insensitive high energy density materials. Our modeling reveals that the decomposition initiation in both BNFF-1 and ANFF-1 molecules is triggered by ring cleavage reactions while the further process is defined by a competition between two major pathways, the fast C-NO₂ homolysis and slow nitro-nitrite isomerization releasing NO. We discuss insights on design of new energetic materials with targeted properties gained from our modeling.

Thermal degradation of Shredded Oil Palm Empty Fruit Bunches (SOPEFB) embedded with Cobalt catalyst by Thermogravimetric Analysis (TGA)

NASA Astrophysics Data System (ADS)

Alias, R.; Hamid, N. H.; Jaapar, J.; Musa, M.; Alwi, H.; Halim, K. H. Ku

2018-03-01

Thermal behavior and decomposition kinetics of shredded oil palm empty fruit bunches (SOPEFB) were investigated in this study by using thermogravimetric analysis (TGA). The SOPEFB were analyzed under conditions of temperature 30 °C to 900 °C with nitrogen gas flow at 50 ml/min. The SOPEFB were embedded with cobalt (II) nitrate solution with concentration 5%, 10%, 15% and 20%. The TG/DTG curves shows the degradation behavior of SOPEFB following with char production for each heating rate and each concentration of cobalt catalyst. Thermal degradation occurred in three phases, water drying phase, decomposition of hemicellulose and cellulose phase, and lignin decomposition phase. The kinetic equation with relevant parameters described the activation energy required for thermal degradation at the temperature regions of 200 °C to 350 °C. Activation energy (E) for different heating rate with SOPEFB embedded with different concentration of cobalt catalyst showing that the lowest E required was at SOPEFB with 20% concentration of cobalt catalyst..

[Influence of decomposition of Cladophora sp. on phosphorus concentrations and forms in the overlying water].

PubMed

Hou, Jin-Zhi; Wei, Quan; Gao, Li; Sun, Wei-Ming

2013-06-01

Sediments were sampled in the dominated zone of Cladophora sp. in Rongcheng Swan Lake, and cultivated with algae in the laboratory to reveal the influence of Cladophora decomposition on concentrations and forms of phosphorus in the overlying water. Concentrations of total phosphorus (TP), dissolved total phosphorus (DTP), soluble reactive phosphorus (SRP), particulate phosphorus (PP) and dissolved organic phosphorus (DOP) in overlying water were investigated, and some physicochemical parameters, such as dissolved oxygen (DO), pH and conductivity were monitored during the experiment. In addition, the influence of algae decomposition on P release from sediments was analyzed. Due to the decomposition of Cladophora, DO concentration in the overlying water declined remarkably and reached the anoxic condition (0-0.17 mg x L(-1)). The pH value of different treatments also decreased, and treatments with algae reduced by about 1 unit. Concentrations of TP and different P forms all increased obviously, and the increasing extent was larger with the adding algae amount. TP concentrations of different treatments varied from 0.04 mg x L(-1) to 1.34 mg x L(-1). DOP and PP were the main P forms in the overlying water in algae without sediments treatments, but SRP concentrations became much higher in algae with sediments treatments. The result showed that P forms released from decomposing Cladophora were mainly DOP and PP, and the Cladophora decomposition could also promote the sediments to release P into the overlying water.

Information theoretic methods for image processing algorithm optimization

NASA Astrophysics Data System (ADS)

Prokushkin, Sergey F.; Galil, Erez

2015-01-01

Modern image processing pipelines (e.g., those used in digital cameras) are full of advanced, highly adaptive filters that often have a large number of tunable parameters (sometimes > 100). This makes the calibration procedure for these filters very complex, and the optimal results barely achievable in the manual calibration; thus an automated approach is a must. We will discuss an information theory based metric for evaluation of algorithm adaptive characteristics ("adaptivity criterion") using noise reduction algorithms as an example. The method allows finding an "orthogonal decomposition" of the filter parameter space into the "filter adaptivity" and "filter strength" directions. This metric can be used as a cost function in automatic filter optimization. Since it is a measure of a physical "information restoration" rather than perceived image quality, it helps to reduce the set of the filter parameters to a smaller subset that is easier for a human operator to tune and achieve a better subjective image quality. With appropriate adjustments, the criterion can be used for assessment of the whole imaging system (sensor plus post-processing).