Platelet factor XIII increases the fibrinolytic resistance of platelet-rich clots by accelerating the crosslinking of alpha 2-antiplasmin to fibrin

NASA Technical Reports Server (NTRS)

Reed, G. L.; Matsueda, G. R.; Haber, E.

1992-01-01

Platelet clots resist fibrinolysis by plasminogen activators. We hypothesized that platelet factor XIII may enhance the fibrinolytic resistance of platelet-rich clots by catalyzing the crosslinking of alpha 2-antiplasmin (alpha 2AP) to fibrin. Analysis of plasma clot structure by polyacrylamide gel electrophoresis and immunoblotting revealed accelerated alpha 2AP-fibrin crosslinking in platelet-rich compared with platelet-depleted plasma clots. A similar study of clots formed with purified fibrinogen (depleted of factor XIII activity), isolated platelets, and specific factor XIII inhibitors indicated that this accelerated crosslinking was due to the catalytic activity of platelet factor XIII. Moreover, when washed platelets were aggregated by thrombin, there was evidence of platelet factor XIII-mediated crosslinking between platelet alpha 2AP and platelet fibrin(ogen). Specific inhibition (by a monoclonal antibody) of the alpha 2AP associated with washed platelet aggregates accelerated the fibrinolysis of the platelet aggregate. Thus in platelet-rich plasma clots, and in thrombin-induced platelet aggregates, platelet factor XIII actively formed alpha 2AP-fibrin crosslinks, which appeared to enhance the resistance of platelet-rich clots to fibrinolysis.

Three-way parallel independent component analysis for imaging genetics using multi-objective optimization.

PubMed

Ulloa, Alvaro; Jingyu Liu; Vergara, Victor; Jiayu Chen; Calhoun, Vince; Pattichis, Marios

2014-01-01

In the biomedical field, current technology allows for the collection of multiple data modalities from the same subject. In consequence, there is an increasing interest for methods to analyze multi-modal data sets. Methods based on independent component analysis have proven to be effective in jointly analyzing multiple modalities, including brain imaging and genetic data. This paper describes a new algorithm, three-way parallel independent component analysis (3pICA), for jointly identifying genomic loci associated with brain function and structure. The proposed algorithm relies on the use of multi-objective optimization methods to identify correlations among the modalities and maximally independent sources within modality. We test the robustness of the proposed approach by varying the effect size, cross-modality correlation, noise level, and dimensionality of the data. Simulation results suggest that 3p-ICA is robust to data with SNR levels from 0 to 10 dB and effect-sizes from 0 to 3, while presenting its best performance with high cross-modality correlations, and more than one subject per 1,000 variables. In an experimental study with 112 human subjects, the method identified links between a genetic component (pointing to brain function and mental disorder associated genes, including PPP3CC, KCNQ5, and CYP7B1), a functional component related to signal decreases in the default mode network during the task, and a brain structure component indicating increases of gray matter in brain regions of the default mode region. Although such findings need further replication, the simulation and in-vivo results validate the three-way parallel ICA algorithm presented here as a useful tool in biomedical data decomposition applications.

Characterization of carbonic anhydrase XIII in the erythrocytes of the Burmese python, Python molurus bivittatus.

PubMed

Esbaugh, A J; Secor, S M; Grosell, M

2015-09-01

Carbonic anhydrase (CA) is one of the most abundant proteins found in vertebrate erythrocytes with the majority of species expressing a low activity CA I and high activity CA II. However, several phylogenetic gaps remain in our understanding of the expansion of cytoplasmic CA in vertebrate erythrocytes. In particular, very little is known about isoforms from reptiles. The current study sought to characterize the erythrocyte isoforms from two squamate species, Python molurus and Nerodia rhombifer, which was combined with information from recent genome projects to address this important phylogenetic gap. Obtained sequences grouped closely with CA XIII in phylogenetic analyses. CA II mRNA transcripts were also found in erythrocytes, but found at less than half the levels of CA XIII. Structural analysis suggested similar biochemical activity as the respective mammalian isoforms, with CA XIII being a low activity isoform. Biochemical characterization verified that the majority of CA activity in the erythrocytes was due to a high activity CA II-like isoform; however, titration with copper supported the presence of two CA pools. The CA II-like pool accounted for 90 % of the total activity. To assess potential disparate roles of these isoforms a feeding stress was used to up-regulate CO2 excretion pathways. Significant up-regulation of CA II and the anion exchanger was observed; CA XIII was strongly down-regulated. While these results do not provide insight into the role of CA XIII in the erythrocytes, they do suggest that the presence of two isoforms is not simply a case of physiological redundancy. Copyright © 2015. Published by Elsevier Inc.

Effectiveness of multi-component non-pharmacologic delirium interventions: A Meta-analysis

PubMed Central

Hshieh, Tammy T.; Yue, Jirong; Oh, Esther; Puelle, Margaret; Dowal, Sarah; Travison, Thomas; Inouye, Sharon K.

2015-01-01

Importance Delirium, an acute disorder with high morbidity and mortality, is often preventable through multi-component non-pharmacologic strategies. The efficacy of these strategies for preventing subsequent adverse outcomes has been limited to small studies. Objective Evaluate available evidence on multi-component non-pharmacologic delirium interventions in reducing incident delirium and preventing poor outcomes associated with delirium. Data Sources PubMed, Google Scholar, ScienceDirect and Cochrane Database of Systematic Reviews from January 1, 1999–December 31, 2013. Study Selection Studies examining the following outcomes were included: delirium incidence, falls, length of stay, rate of discharge to a long-term care institution, change in functional or cognitive status. Data Extraction and Synthesis Two experienced physician reviewers independently and blindly abstracted data on outcome measures using a standardized approach. The reviewers conducted quality ratings based on the Cochrane Risk of Bias criteria for each study. Main Outcomes and Measures We identified 14 interventional studies. Results for outcomes of delirium, falls, length of stay and institutionalization data were pooled for meta-analysis but heterogeneity limited meta-analysis of results for outcomes of functional and cognitive decline. Overall, eleven studies demonstrated significant reductions in delirium incidence (Odds Ratio 0.47, 95% Confidence Interval 0.38–0.58). The four randomized or matched (RMT) studies reduced delirium incidence by 44% (95% CI 0.42–0.76). Rate of falls decreased significantly among intervention patients in four studies (OR 0.38, 95% CI 0.25–0.60); in the two RMTs, the fall rate was reduced by 64% (95% CI 0.22–0.61). Lengths of stay and institutionalization rates also trended towards decreases in the intervention groups, mean difference −0.16 days shorter (95% CI −0.97–0.64) and odds of institutionalization 5% lower (OR 0.95, 95% CI 0.71–1

Genetics Home Reference: factor XIII deficiency

MedlinePlus

... XIII deficiency tend to have heavy or prolonged menstrual bleeding (menorrhagia) and may experience recurrent pregnancy losses ( ... inheritance, which means that it results when both copies of either the F13A1 gene or the F13B ...

A Multi-Scale, Multi-Physics Optimization Framework for Additively Manufactured Structural Components

NASA Astrophysics Data System (ADS)

El-Wardany, Tahany; Lynch, Mathew; Gu, Wenjiong; Hsu, Arthur; Klecka, Michael; Nardi, Aaron; Viens, Daniel

This paper proposes an optimization framework enabling the integration of multi-scale / multi-physics simulation codes to perform structural optimization design for additively manufactured components. Cold spray was selected as the additive manufacturing (AM) process and its constraints were identified and included in the optimization scheme. The developed framework first utilizes topology optimization to maximize stiffness for conceptual design. The subsequent step applies shape optimization to refine the design for stress-life fatigue. The component weight was reduced by 20% while stresses were reduced by 75% and the rigidity was improved by 37%. The framework and analysis codes were implemented using Altair software as well as an in-house loading code. The optimized design was subsequently produced by the cold spray process.

Multi-component determination and chemometric analysis of Paris polyphylla by ultra high performance liquid chromatography with photodiode array detection.

PubMed

Chen, Pei; Jin, Hong-Yu; Sun, Lei; Ma, Shuang-Cheng

2016-09-01

Multi-source analysis of traditional Chinese medicine is key to ensuring its safety and efficacy. Compared with traditional experimental differentiation, chemometric analysis is a simpler strategy to identify traditional Chinese medicines. Multi-component analysis plays an increasingly vital role in the quality control of traditional Chinese medicines. A novel strategy, based on chemometric analysis and quantitative analysis of multiple components, was proposed to easily and effectively control the quality of traditional Chinese medicines such as Chonglou. Ultra high performance liquid chromatography was more convenient and efficient. Five species of Chonglou were distinguished by chemometric analysis and nine saponins, including Chonglou saponins I, II, V, VI, VII, D, and H, as well as dioscin and gracillin, were determined in 18 min. The method is feasible and credible, and enables to improve quality control of traditional Chinese medicines and natural products. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Factor XIII as a modulator of plasma fibronectin alterations during experimental bacteremia.

PubMed

Kiener, J L; Cho, E; Saba, T M

1986-11-01

Fibronectin is found in plasma as well as in association with connective tissue and cell surfaces. Depletion of plasma fibronectin is often observed in septic trauma and burned patients, while experimental rats often manifest hyperfibronectinemia with sepsis. Since Factor XIII may influence the rate of clearance and deposition of plasma fibronectin into tissues, we evaluated the temporal changes in plasma fibronectin and plasma Factor XIII following bacteremia and RE blockade in rats in an attempt to understand the mechanism leading to elevation of fibronectin levels in bacteremic rats, which is distinct from that observed with RE blockade. Clearance of exogenously administered fibronectin after bacteremia was also determined. Rats received either saline, Pseudomonas aeruginosa (1 X 10(9) organisms), gelatinized RE test lipid emulsion (50 mg/100 gm B.W.), or emulsion followed by Pseudomonas. Plasma fibronectin and Factor XIII were determined at 0, 2, 24, and 48 hours post-blockade or bacteremia. At 24 and 48 hr following bacteremia alone or bacteremia after RE blockade, there was a significant elevation (p less than 0.05) of plasma fibronectin and a concomitant decrease (p less than 0.05) of plasma factor XIII activity. Extractable tissue fibronectin from liver and spleen was also increased at 24 and 48 hours following R.E. blockade plus bacteremia. In addition, the plasma clearance of human fibronectin was significantly prolonged (p less than 0.05) following bacterial challenge. Infusion of activated Factor XIII (20 units/rat) during a period of hyperfibronectinemia (908.0 +/- 55.1 micrograms/ml) resulted in a significant (p less than 0.05) decrease in plasma fibronectin (548.5 +/- 49.9 micrograms/ml) within 30 min. Thus Factor XIII deficiency in rats with bacteremia may contribute to the elevation in plasma fibronectin by altering kinetics associated with the clearance of fibronectin from the blood.

Independent Component Analysis of Textures

NASA Technical Reports Server (NTRS)

Manduchi, Roberto; Portilla, Javier

2000-01-01

A common method for texture representation is to use the marginal probability densities over the outputs of a set of multi-orientation, multi-scale filters as a description of the texture. We propose a technique, based on Independent Components Analysis, for choosing the set of filters that yield the most informative marginals, meaning that the product over the marginals most closely approximates the joint probability density function of the filter outputs. The algorithm is implemented using a steerable filter space. Experiments involving both texture classification and synthesis show that compared to Principal Components Analysis, ICA provides superior performance for modeling of natural and synthetic textures.

Stable expression of recombinant human coagulation factor XIII in protein-free suspension culture of Chinese hamster ovary cells.

PubMed

Chun, B H; Bang, W G; Park, Y K; Woo, S K

2001-11-01

The recombinant a and bsubunits for human coagulation factor XIII were transfected into Chinese hamster ovary (CHO) cells. CHO cells were amplified and selected with methotrexate in adherent cultures containing serum, and CHO 1-62 cells were later selected in protein-free medium. To develop a recombinant factor XIII production process in a suspension culture, we have investigated the growth characteristics of CHO cells and the maintenance of factor XIII expression in the culture medium. Suspension adaptation of CHO cells was performed in protein-free medium, GC-CHO-PI, by two methods, such as serum weaning and direct switching from serum containing media to protein-free media. Although the growth of CHO cells in suspension culture was affected initially by serum depletion, cell specific productivity of factor XIII showed only minor changes by the direct switching to protein-free medium during a suspension culture. As for the long-term stability of factor XIII, CHO 1-62 cells showed a stable expression of factor XIII in protein-free condition for 1000 h. These results indicate that the CHO 1-62cells can be adapted to express recombinant human factor XIII in a stable maimer in suspension culture using a protein-free medium. Our results demonstrate that enhanced cell growth in a continuous manner is achievable for factor XIII production in a protein-free medium when a perfusion bioreactor culture system with a spin filter is employed.

An analysis method for multi-component airfoils in separated flow

NASA Technical Reports Server (NTRS)

Rao, B. M.; Duorak, F. A.; Maskew, B.

1980-01-01

The multi-component airfoil program (Langley-MCARF) for attached flow is modified to accept the free vortex sheet separation-flow model program (Analytical Methods, Inc.-CLMAX). The viscous effects are incorporated into the calculation by representing the boundary layer displacement thickness with an appropriate source distribution. The separation flow model incorporated into MCARF was applied to single component airfoils. Calculated pressure distributions for angles of attack up to the stall are in close agreement with experimental measurements. Even at higher angles of attack beyond the stall, correct trends of separation, decrease in lift coefficients, and increase in pitching moment coefficients are predicted.

Regularized Generalized Structured Component Analysis

ERIC Educational Resources Information Center

Hwang, Heungsun

2009-01-01

Generalized structured component analysis (GSCA) has been proposed as a component-based approach to structural equation modeling. In practice, GSCA may suffer from multi-collinearity, i.e., high correlations among exogenous variables. GSCA has yet no remedy for this problem. Thus, a regularized extension of GSCA is proposed that integrates a ridge…

Using multi-scale entropy and principal component analysis to monitor gears degradation via the motor current signature analysis

NASA Astrophysics Data System (ADS)

Aouabdi, Salim; Taibi, Mahmoud; Bouras, Slimane; Boutasseta, Nadir

2017-06-01

This paper describes an approach for identifying localized gear tooth defects, such as pitting, using phase currents measured from an induction machine driving the gearbox. A new tool of anomaly detection based on multi-scale entropy (MSE) algorithm SampEn which allows correlations in signals to be identified over multiple time scales. The motor current signature analysis (MCSA) in conjunction with principal component analysis (PCA) and the comparison of observed values with those predicted from a model built using nominally healthy data. The Simulation results show that the proposed method is able to detect gear tooth pitting in current signals.

Single-Pulse Multi-Point Multi-Component Interferometric Rayleigh Scattering Velocimeter

NASA Technical Reports Server (NTRS)

Bivolaru, Daniel; Danehy, Paul M.; Lee, Joseph W.; Gaffney, Richard L., Jr.; Cutler, Andrew D.

2006-01-01

A simultaneous multi-point, multi-component velocimeter using interferometric detection of the Doppler shift of Rayleigh, Mie, and Rayleigh-Brillouin scattered light in supersonic flow is described. The system uses up to three sets of collection optics and one beam combiner for the reference laser light to form a single collimated beam. The planar Fabry-Perot interferometer used in the imaging mode for frequency detection preserves the spatial distribution of the signal reasonably well. Single-pulse multi-points measurements of up to two orthogonal and one non-orthogonal components of velocity in a Mach 2 free jet were performed to demonstrate the technique. The average velocity measurements show a close agreement with the CFD calculations using the VULCAN code.

Dynamic Multi-Component Hemiaminal Assembly

PubMed Central

You, Lei; Long, S. Reid; Lynch, Vincent M.

2012-01-01

A simple approach to generating in situ metal templated tris-(2-picolyl)amine-like multi-component assemblies with potential applications in molecular recognition and sensing is reported. The assembly is based on the reversible covalent association between di-(2-picolyl)amine and aldehydes. Zinc ion is the best for inducing assembly among the metal salts investigated, while 2-picolinaldehyde is the best among the heterocyclic aldehydes studied. Although an equilibrium constant of 6.6 * 103 M-1 was measured for the assembly formed by 2-picolinaldehdye, di-(2-picolyl)amine, and zinc triflate, the equilibrium constants for other systems are in the 102 M-1 range. X-ray structural analysis revealed that zinc adopts a trigonal bipyramidal geometry within the assembled ligand. The diversity and equilibrium of the assemblies are readily altered by simply changing concentrations, varying components, or adding counter anions. PMID:21919095

Assessing intervention fidelity in a multi-level, multi-component, multi-site program: the Children's Healthy Living (CHL) program.

PubMed

Butel, Jean; Braun, Kathryn L; Novotny, Rachel; Acosta, Mark; Castro, Rose; Fleming, Travis; Powers, Julianne; Nigg, Claudio R

2015-12-01

Addressing complex chronic disease prevention, like childhood obesity, requires a multi-level, multi-component culturally relevant approach with broad reach. Models are lacking to guide fidelity monitoring across multiple levels, components, and sites engaged in such interventions. The aim of this study is to describe the fidelity-monitoring approach of The Children's Healthy Living (CHL) Program, a multi-level multi-component intervention in five Pacific jurisdictions. A fidelity-monitoring rubric was developed. About halfway during the intervention, community partners were randomly selected and interviewed independently by local CHL staff and by Coordinating Center representatives to assess treatment fidelity. Ratings were compared and discussed by local and Coordinating Center staff. There was good agreement between the teams (Kappa = 0.50, p < 0.001), and intervention improvement opportunities were identified through data review and group discussion. Fidelity for the multi-level, multi-component, multi-site CHL intervention was successfully assessed, identifying adaptations as well as ways to improve intervention delivery prior to the end of the intervention.

Increasing component functionality via multi-process additive manufacturing

NASA Astrophysics Data System (ADS)

Coronel, Jose L.; Fehr, Katherine H.; Kelly, Dominic D.; Espalin, David; Wicker, Ryan B.

2017-05-01

Additively manufactured components, although extensively customizable, are often limited in functionality. Multi-process additive manufacturing (AM) grants the ability to increase the functionality of components via subtractive manufacturing, wire embedding, foil embedding and pick and place. These processes are scalable to include several platforms ranging from desktop to large area printers. The Multi3D System is highlighted, possessing the capability to perform the above mentioned processes, all while transferring a fabricated component with a robotic arm. Work was conducted to fabricate a patent inspired, printed missile seeker. The seeker demonstrated the advantage of multi-process AM via introduction of the pick and place process. Wire embedding was also explored, with the successful interconnect of two layers of embedded wires in different planes. A final demonstration of a printed contour bracket, served to show the reduction of surface roughness on a printed part is 87.5% when subtractive manufacturing is implemented in tandem with AM. Functionality of the components on all the cases was improved. Results included optical components embedded within the printed housing, wires embedded with interconnection, and reduced surface roughness. These results highlight the improved functionality of components through multi-process AM, specifically through work conducted with the Multi3D System.

Multi-component assembly casting

DOEpatents

James, Allister W.

2015-10-13

Multi-component vane segment and method for forming the same. Assembly includes: positioning a pre-formed airfoil component (12) and a preformed shroud heat resistant material (18) in a mold, wherein the airfoil component (12) and the shroud heat resistant material (18) each comprises an interlocking feature (24); preheating the mold; introducing molten structural material (46) into the mold; and solidifying the molten structural material such that it interlocks the pre-formed airfoil component (12) with respect to the preformed shroud heat resistant material (18) and is effective to provide structural support for the shroud heat resistant material (18). Surfaces between the airfoil component (12) and the structural material (46), between the airfoil component (12) and the shroud heat resistant material (18), and between the shroud heat resistant material (18) and the structural material (46) are free of metallurgical bonds.

A calorimetric study on the low temperature dynamics of doped ice V and its reversible phase transition to hydrogen ordered ice XIII.

PubMed

Salzmann, Christoph G; Radaelli, Paolo G; Finney, John L; Mayer, Erwin

2008-11-07

Doped ice V samples made from solutions containing 0.01 M HCl (DCl), HF (DF), or KOH (KOD) in H(2)O (D(2)O) were slow-cooled from 250 to 77 K at 0.5 GPa. The effect of the dopant on the hydrogen disorder --> order transition and formation of hydrogen ordered ice XIII was studied by differential scanning calorimetry (DSC) with samples recovered at 77 K. DSC scans of acid-doped samples are consistent with a reversible ice XIII <--> ice V phase transition at ambient pressure, showing an endothermic peak on heating due to the hydrogen ordered ice XIII --> disordered ice V phase transition, and an exothermic peak on subsequent cooling due to the ice V --> ice XIII phase transition. The equilibrium temperature (T(o)) for the ice V <--> ice XIII phase transition is 112 K for both HCl doped H(2)O and DCl doped D(2)O. From the maximal enthalpy change of 250 J mol(-1) on the ice XIII --> ice V phase transition and T(o) of 112 K, the change in configurational entropy for the ice XIII --> ice V transition is calculated as 2.23 J mol(-1) K(-1) which is 66% of the Pauling entropy. For HCl, the most effective dopant, the influence of HCl concentration on the formation of ice XIII was determined: on decreasing the concentration of HCl from 0.01 to 0.001 M, its effectiveness is only slightly lowered. However, further HCl decrease to 0.0001 M drastically lowered its effectiveness. HF (DF) doping is less effective in inducing formation of ice XIII than HCl (DCl) doping. On heating at a rate of 5 K min(-1), kinetic unfreezing starts in pure ice V at approximately 132 K, whereas in acid doped ice XIII it starts at about 105 K due to acceleration of reorientation of water molecules. KOH doping does not lead to formation of hydrogen ordered ice XIII, a result which is consistent with our powder neutron diffraction study (C. G. Salzmann, P. G. Radaelli, A. Hallbrucker, E. Mayer, J. L. Finney, Science, 2006, 311, 1758). We further conjecture whether or not ice XIII has a stable region in

Principle component analysis and linear discriminant analysis of multi-spectral autofluorescence imaging data for differentiating basal cell carcinoma and healthy skin

NASA Astrophysics Data System (ADS)

Chernomyrdin, Nikita V.; Zaytsev, Kirill I.; Lesnichaya, Anastasiya D.; Kudrin, Konstantin G.; Cherkasova, Olga P.; Kurlov, Vladimir N.; Shikunova, Irina A.; Perchik, Alexei V.; Yurchenko, Stanislav O.; Reshetov, Igor V.

2016-09-01

In present paper, an ability to differentiate basal cell carcinoma (BCC) and healthy skin by combining multi-spectral autofluorescence imaging, principle component analysis (PCA), and linear discriminant analysis (LDA) has been demonstrated. For this purpose, the experimental setup, which includes excitation and detection branches, has been assembled. The excitation branch utilizes a mercury arc lamp equipped with a 365-nm narrow-linewidth excitation filter, a beam homogenizer, and a mechanical chopper. The detection branch employs a set of bandpass filters with the central wavelength of spectral transparency of λ = 400, 450, 500, and 550 nm, and a digital camera. The setup has been used to study three samples of freshly excised BCC. PCA and LDA have been implemented to analyze the data of multi-spectral fluorescence imaging. Observed results of this pilot study highlight the advantages of proposed imaging technique for skin cancer diagnosis.

Dissipative effects in multi-component systems

NASA Astrophysics Data System (ADS)

El, Andrej; Bouras, Ioannis; Xu, Zhe; Greiner, Carsten

2013-05-01

Using a smooth initial condition of Glauber type in the kinetic transport algorithm BAMPS we investigate differences in behavior of a multi-component system and its one-component equivalent with the same η/s value. Flow harmonic coefficients v2 and v4 are shown to have very low sensitivity to the details of microscopic interactions in the system.

A specific colorimetric assay for measuring transglutaminase 1 and factor XIII activities.

PubMed

Hitomi, Kiyotaka; Kitamura, Miyako; Alea, Mileidys Perez; Ceylan, Ismail; Thomas, Vincent; El Alaoui, Saïd

2009-11-15

Transglutaminase (TGase) is an enzyme that catalyzes both isopeptide cross-linking and incorporation of primary amines into proteins. Eight TGases have been identified in humans, and each of these TGases has a unique tissue distribution and physiological significance. Although several assays for TGase enzymatic activity have been reported, it has been difficult to establish an assay for discriminating each of these different TGase activities. Using a random peptide library, we recently identified the preferred substrate sequences for three major TGases: TGase 1, TGase 2, and factor XIII. In this study, we use these substrates in specific tests for measuring the activities of TGase 1 and factor XIII.

Multi-Scale Sizing of Lightweight Multifunctional Spacecraft Structural Components

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.

2005-01-01

This document is the final report for the project entitled, "Multi-Scale Sizing of Lightweight Multifunctional Spacecraft Structural Components," funded under the NRA entitled "Cross-Enterprise Technology Development Program" issued by the NASA Office of Space Science in 2000. The project was funded in 2001, and spanned a four year period from March, 2001 to February, 2005. Through enhancements to and synthesis of unique, state of the art structural mechanics and micromechanics analysis software, a new multi-scale tool has been developed that enables design, analysis, and sizing of advance lightweight composite and smart materials and structures from the full vehicle, to the stiffened structure, to the micro (fiber and matrix) scales. The new software tool has broad, cross-cutting value to current and future NASA missions that will rely on advanced composite and smart materials and structures.

Integrable multi-component generalization of a modified short pulse equation

NASA Astrophysics Data System (ADS)

Matsuno, Yoshimasa

2016-11-01

We propose a multi-component generalization of the modified short pulse (SP) equation which was derived recently as a reduction of Feng's two-component SP equation. Above all, we address the two-component system in depth. We obtain the Lax pair, an infinite number of conservation laws and multisoliton solutions for the system, demonstrating its integrability. Subsequently, we show that the two-component system exhibits cusp solitons and breathers for which the detailed analysis is performed. Specifically, we explore the interaction process of two cusp solitons and derive the formula for the phase shift. While cusp solitons are singular solutions, smooth breather solutions are shown to exist, provided that the parameters characterizing the solutions satisfy certain conditions. Last, we discuss the relation between the proposed system and existing two-component SP equations.

Comparison of five Lonicera flowers by simultaneous determination of multi-components with single reference standard method and principal component analysis.

PubMed

Gao, Wen; Wang, Rui; Li, Dan; Liu, Ke; Chen, Jun; Li, Hui-Jun; Xu, Xiaojun; Li, Ping; Yang, Hua

2016-01-05

The flowers of Lonicera japonica Thunb. were extensively used to treat many diseases. As the demands for L. japonica increased, some related Lonicera plants were often confused or misused. Caffeoylquinic acids were always regarded as chemical markers in the quality control of L. japonica, but they could be found in all Lonicera species. Thus, a simple and reliable method for the evaluation of different Lonicera flowers is necessary to be established. In this work a method based on single standard to determine multi-components (SSDMC) combined with principal component analysis (PCA) for control and distinguish of Lonicera species flowers have been developed. Six components including three caffeoylquinic acids and three iridoid glycosides were assayed simultaneously using chlorogenic acid as the reference standard. The credibility and feasibility of the SSDMC method were carefully validated and the results demonstrated that there were no remarkable differences compared with external standard method. Finally, a total of fifty-one batches covering five Lonicera species were analyzed and PCA was successfully applied to distinguish the Lonicera species. This strategy simplifies the processes in the quality control of multiple-componential herbal medicine which effectively adapted for improving the quality control of those herbs belonging to closely related species. Copyright © 2015 Elsevier B.V. All rights reserved.

[Evaluate drug interaction of multi-components in Morus alba leaves based on α-glucosidase inhibitory activity].

PubMed

Ji, Tao; Su, Shu-Lan; Guo, Sheng; Qian, Da-Wei; Ouyang, Zhen; Duan, Jin-Ao

2016-06-01

Column chromatography was used for enrichment and separation of flavonoids, alkaloids and polysaccharides from the extracts of Morus alba leaves; glucose oxidase method was used with sucrose as the substrate to evaluate the multi-components of M. alba leaves in α-glucosidase inhibitory models; isobole method, Chou-Talalay combination index analysis and isobolographic analysis were used to evaluate the interaction effects and dose-effect characteristics of two components, providing scientific basis for revealing the hpyerglycemic mechanism of M. alba leaves. The components analysis showed that flavonoid content was 5.3%; organic phenolic acids content was 10.8%; DNJ content was 39.4%; and polysaccharide content was 18.9%. Activity evaluation results demonstrated that flavonoids, alkaloids and polysaccharides of M. alba leaves had significant inhibitory effects on α-glucosidase, and the inhibitory rate was increased with the increasing concentration. Alkaloids showed most significant inhibitory effects among these three components. Both compatibility of alkaloids and flavonoids, and the compatibility of alkaloids and polysaccharides demonstrated synergistic effects, but the compatibility of flavonoids and polysaccharides showed no obvious synergistic effects. The results have confirmed the interaction of multi-components from M. alba leaves to regulate blood sugar, and provided scientific basis for revealing hpyerglycemic effectiveness and mechanism of the multi-components from M. alba leaves. Copyright© by the Chinese Pharmaceutical Association.

25 CFR 36.40 - Standard XIII-Library/media program.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 25 Indians 1 2010-04-01 2010-04-01 false Standard XIII-Library/media program. 36.40 Section 36.40... § 36.40 Standard XIII—Library/media program. (a) Each school shall provide a library/media program... objectives have been met. (2) A written policy for the selection of materials and equipment shall be...

25 CFR 36.40 - Standard XIII-Library/media program.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 25 Indians 1 2012-04-01 2011-04-01 true Standard XIII-Library/media program. 36.40 Section 36.40... § 36.40 Standard XIII—Library/media program. (a) Each school shall provide a library/media program... developed by a library committee in collaboration with the librarian and be approved by the school board...

25 CFR 36.40 - Standard XIII-Library/media program.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 25 Indians 1 2014-04-01 2014-04-01 false Standard XIII-Library/media program. 36.40 Section 36.40... § 36.40 Standard XIII—Library/media program. (a) Each school shall provide a library/media program... developed by a library committee in collaboration with the librarian and be approved by the school board...

25 CFR 36.40 - Standard XIII-Library/media program.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 25 Indians 1 2013-04-01 2013-04-01 false Standard XIII-Library/media program. 36.40 Section 36.40... § 36.40 Standard XIII—Library/media program. (a) Each school shall provide a library/media program... developed by a library committee in collaboration with the librarian and be approved by the school board...

Catalysis and Multi-Component Reactions

NASA Astrophysics Data System (ADS)

Shibasaki, Masakatsu; Yus, Miguel; Bremner, Stacy; Comer, Eamon; Shore, Gjergji; Morin, Sylvie; Organ, Michael G.; van der Eycken, Erik; Merkul, Eugen; Dorsch, Dieter; Müller, Thomas J. J.; Ryabukhin, Sergey V.; Ostapchuk, Eugeniy N.; Plaskon, Andrey S.; Volochnyuk, Dmitriy M.; Shivanyuk, Alexander N.; Tolmachev, Andrey A.; Sheibani, Hassan; Babaie, Maryam; Behzadi, Soheila; Dabiri, Minoo; Bahramnejad, Mahboobeh; Bashiribod, Sahareh; Hekmatshoar, Rahim; Sadjadi, Sodeh; Khorasani, Mohammad; Polyakov, Anatoliy I.; Eryomina, Vera A.; Medvedeva, Lidiya A.; Tihonova, Nadezhda I.; Listratova, Anna V.; Voskressensky, Leonid G.; Merkul, Eugen; Dorsch, Dieter; Müller, Thomas J. J.; Sheibani, Hassan; Esfandiarpoor, Zeinab; Behzadi, Soheila; Titova, Julia A.; Fedorova, Olga V.; Ovchinnikova, Irina G.; Valova, Marina S.; Koryakova, Olga V.; Rusinov, Gennady L.; Charushin, Valery N.; Hekmatshoar, Rahim; Sadjadi, Sodeh

We have been studying the development of new asymmetric two-center catalysis using rare earth alkoxides and bifunctional sugar and related ligands. In The Fourth International Conference on Multi-Component Reactions and Related Chemistry (MCR 2009), new catalytic asymmetric reactions using catalysts 1 and 2 and catalytic asymmetric syntheses of ranirestat 3 and tamiflu 4 will be presented.

Multi-band morpho-Spectral Component Analysis Deblending Tool (MuSCADeT): Deblending colourful objects

NASA Astrophysics Data System (ADS)

Joseph, R.; Courbin, F.; Starck, J.-L.

2016-05-01

We introduce a new algorithm for colour separation and deblending of multi-band astronomical images called MuSCADeT which is based on Morpho-spectral Component Analysis of multi-band images. The MuSCADeT algorithm takes advantage of the sparsity of astronomical objects in morphological dictionaries such as wavelets and their differences in spectral energy distribution (SED) across multi-band observations. This allows us to devise a model independent and automated approach to separate objects with different colours. We show with simulations that we are able to separate highly blended objects and that our algorithm is robust against SED variations of objects across the field of view. To confront our algorithm with real data, we use HST images of the strong lensing galaxy cluster MACS J1149+2223 and we show that MuSCADeT performs better than traditional profile-fitting techniques in deblending the foreground lensing galaxies from background lensed galaxies. Although the main driver for our work is the deblending of strong gravitational lenses, our method is fit to be used for any purpose related to deblending of objects in astronomical images. An example of such an application is the separation of the red and blue stellar populations of a spiral galaxy in the galaxy cluster Abell 2744. We provide a python package along with all simulations and routines used in this paper to contribute to reproducible research efforts. Codes can be found at http://lastro.epfl.ch/page-126973.html

[A novel method of multi-channel feature extraction combining multivariate autoregression and multiple-linear principal component analysis].

PubMed

Wang, Jinjia; Zhang, Yanna

2015-02-01

Brain-computer interface (BCI) systems identify brain signals through extracting features from them. In view of the limitations of the autoregressive model feature extraction method and the traditional principal component analysis to deal with the multichannel signals, this paper presents a multichannel feature extraction method that multivariate autoregressive (MVAR) model combined with the multiple-linear principal component analysis (MPCA), and used for magnetoencephalography (MEG) signals and electroencephalograph (EEG) signals recognition. Firstly, we calculated the MVAR model coefficient matrix of the MEG/EEG signals using this method, and then reduced the dimensions to a lower one, using MPCA. Finally, we recognized brain signals by Bayes Classifier. The key innovation we introduced in our investigation showed that we extended the traditional single-channel feature extraction method to the case of multi-channel one. We then carried out the experiments using the data groups of IV-III and IV - I. The experimental results proved that the method proposed in this paper was feasible.

[CoCuMnOx Photocatalyzed Oxidation of Multi-component VOCs and Kinetic Analysis].

PubMed

Meng, Hai-long; Bo, Long-li; Liu, Jia-dong; Gao, Bo; Feng, Qi-qi; Tan, Na; Xie, Shuai

2016-05-15

Solar energy absorption coating CoCuMnOx was prepared by co-precipitation method and applied to photodegrade multi- component VOCs including toluene, ethyl acetate and acetone under visible light irradiation. The photocatalytic oxidation performance of toluene, ethyl acetate and acetone was analyzed and reaction kinetics of VOCs were investigated synchronously. The research indicated that removal rates of single-component toluene, ethyl acetate and acetone were 57%, 62% and 58% respectively under conditions of 400 mg · m⁻³ initial concentration, 120 mm illumination distance, 1 g/350 cm² dosage of CoCuMnOx and 6 h of irradiation time by 100 W tungsten halogen lamp. Due to the competition among different VOCs, removal efficiencies in three-component mixture were reduced by 5%-26% as compared with single VOC. Degradation processes of single-component VOC and three-component VOCs both fitted pseudo first order reaction kinetics, and kinetic constants of toluene, ethyl acetate and acetone were 0.002, 0.002 8 and 0.002 33 min⁻¹ respectively under single-component condition. Reaction rates of VOCs in three-component mixture were 0.49-0.88 times of single components.

Analysis on unevenness of skin color using the melanin and hemoglobin components separated by independent component analysis of skin color image

NASA Astrophysics Data System (ADS)

Ojima, Nobutoshi; Fujiwara, Izumi; Inoue, Yayoi; Tsumura, Norimichi; Nakaguchi, Toshiya; Iwata, Kayoko

2011-03-01

Uneven distribution of skin color is one of the biggest concerns about facial skin appearance. Recently several techniques to analyze skin color have been introduced by separating skin color information into chromophore components, such as melanin and hemoglobin. However, there are not many reports on quantitative analysis of unevenness of skin color by considering type of chromophore, clusters of different sizes and concentration of the each chromophore. We propose a new image analysis and simulation method based on chromophore analysis and spatial frequency analysis. This method is mainly composed of three techniques: independent component analysis (ICA) to extract hemoglobin and melanin chromophores from a single skin color image, an image pyramid technique which decomposes each chromophore into multi-resolution images, which can be used for identifying different sizes of clusters or spatial frequencies, and analysis of the histogram obtained from each multi-resolution image to extract unevenness parameters. As the application of the method, we also introduce an image processing technique to change unevenness of melanin component. As the result, the method showed high capabilities to analyze unevenness of each skin chromophore: 1) Vague unevenness on skin could be discriminated from noticeable pigmentation such as freckles or acne. 2) By analyzing the unevenness parameters obtained from each multi-resolution image for Japanese ladies, agerelated changes were observed in the parameters of middle spatial frequency. 3) An image processing system modulating the parameters was proposed to change unevenness of skin images along the axis of the obtained age-related change in real time.

Multi-Component Current Sheets in the Martian Magnetotail. MAVEN Observations

NASA Astrophysics Data System (ADS)

Grigorenko, E.; Zelenyi, L. M.; Vaisberg, O. L.; Ermakov, V.; Dubinin, E.; Malova, H. V.

2016-12-01

Current sheets (CSs) are the wide-spread objects in space and laboratory plasmas. The capability of CSs to maintain their stability, efficiently store and convert energy is a challenge to space physicists for many decades. Extensive studies of the CSs showed that the presence of multi-component plasma distribution can significantly affect the CS structure and dynamics. Such features like CS thinning, embedding and bifurcation are often related to the anisotropy of particle velocity distribution functions and multi-component ion composition, and they can be a source for generation of plasma instabilities and current disruption/reconnection. The MAVEN mission equipped with comprehensive instrument suite allows the observations of plasma and magnetic field characteristics with a high time resolution and provides an opportunity to study different processes in the Martian plasma environment. In this work we present the analysis of the CSs observed by MAVEN in the Martian magnetotail and discuss the peculiarities of their structure in relation to the thermal/energy characteristics of different plasma components. The relation to the existing CS models is also discussed. This work is supported by Russian Science Foundation (grant Nr.16-42-01103)

The effectiveness of multi-component goal setting interventions for changing physical activity behaviour: a systematic review and meta-analysis.

PubMed

McEwan, Desmond; Harden, Samantha M; Zumbo, Bruno D; Sylvester, Benjamin D; Kaulius, Megan; Ruissen, Geralyn R; Dowd, A Justine; Beauchamp, Mark R

2016-01-01

Drawing from goal setting theory (Latham & Locke, 1991; Locke & Latham, 2002; Locke et al., 1981), the purpose of this study was to conduct a systematic review and meta-analysis of multi-component goal setting interventions for changing physical activity (PA) behaviour. A literature search returned 41,038 potential articles. Included studies consisted of controlled experimental trials wherein participants in the intervention conditions set PA goals and their PA behaviour was compared to participants in a control group who did not set goals. A meta-analysis was ultimately carried out across 45 articles (comprising 52 interventions, 126 effect sizes, n = 5912) that met eligibility criteria using a random-effects model. Overall, a medium, positive effect (Cohen's d(SE) = .552(.06), 95% CI = .43-.67, Z = 9.03, p < .001) of goal setting interventions in relation to PA behaviour was found. Moderator analyses across 20 variables revealed several noteworthy results with regard to features of the study, sample characteristics, PA goal content, and additional goal-related behaviour change techniques. In conclusion, multi-component goal setting interventions represent an effective method of fostering PA across a diverse range of populations and settings. Implications for effective goal setting interventions are discussed.

From supramolecular polymers to multi-component biomaterials.

PubMed

Goor, Olga J G M; Hendrikse, Simone I S; Dankers, Patricia Y W; Meijer, E W

2017-10-30

The most striking and general property of the biological fibrous architectures in the extracellular matrix (ECM) is the strong and directional interaction between biologically active protein subunits. These fibers display rich dynamic behavior without losing their architectural integrity. The complexity of the ECM taking care of many essential properties has inspired synthetic chemists to mimic these properties in artificial one-dimensional fibrous structures with the aim to arrive at multi-component biomaterials. Due to the dynamic character required for interaction with natural tissue, supramolecular biomaterials are promising candidates for regenerative medicine. Depending on the application area, and thereby the design criteria of these multi-component fibrous biomaterials, they are used as elastomeric materials or hydrogel systems. Elastomeric materials are designed to have load bearing properties whereas hydrogels are proposed to support in vitro cell culture. Although the chemical structures and systems designed and studied today are rather simple compared to the complexity of the ECM, the first examples of these functional supramolecular biomaterials reaching the clinic have been reported. The basic concept of many of these supramolecular biomaterials is based on their ability to adapt to cell behavior as a result of dynamic non-covalent interactions. In this review, we show the translation of one-dimensional supramolecular polymers into multi-component functional biomaterials for regenerative medicine applications.

Impact of combined C1 esterase inhibitor/coagulation factor XIII or N-acetylcysteine/tirilazad mesylate administration on leucocyte adherence and cytokine release in experimental endotoxaemia.

PubMed

Birnbaum, J; Klotz, E; Spies, C D; Mueller, J; Vargas Hein, O; Feller, J; Lehmann, C

2008-01-01

We determined the effects of combinations of C1 esterase inhibitor (C1-INH) with factor XIII and of N-acetylcysteine (NAC) with tirilazad mesylate (TM) during lipo-polysaccharide (LPS)-induced endotoxaemia in rats. Forty Wistar rats were divided into four groups: the control (CON) group received no LPS; the LPS, C1-INH + factor XIII and NAC + TM groups received endotoxin infusions (5 mg/kg per h). After 30 min of endotoxaemia, 100 U/kg C1-INH + 50 U/kg factor XIII was administered to the C1-INH + factor XIII group, and 150 mg/kg NAC + 10 mg/kg TM was administered in the NAC + TM group. Administration of C1-INH + factor XIII and NAC + TM both resulted in reduced leucocyte adherence and reduced levels of interleukin-1beta (IL-1beta). The LPS-induced increase in IL-6 levels was amplified by both drug combinations. There was no significant effect on mesenteric plasma extravasation. In conclusion, the administration of C1-INH + factor XIII and NAC + TM reduced endothelial leucocyte adherence and IL-1beta plasma levels, but increased IL-6 levels.

A multi-channel photometric detector for multi-component analysis in flow injection analysis

PubMed Central

Tan, Aimin; Huang, Jialin; Geng, Liudi; Xu, Jinhua; Zhao, Xinna

1994-01-01

The detector, a multi-channel photometric detector, described in this paper was developed using multi-wavelength LEDs (light emitting diode) and phototransistors for absorbance measurement controlled by an Intel 8031 8-bit single chip microcomputer. Up to four flow cells can be attached to the detector. The LEDs and phototransistors are both inexpensive, and reliable. The results given by the detector for simultaneous determination of trace amounts of cobalt and cadmium in zinc sulphate electrolyte are reported. Because of the newly developed detector, this approach employs much less hardware apparatus than by employing conventional photometric detectors. PMID:18924688

A multi-channel photometric detector for multi-component analysis in flow injection analysis.

PubMed

Tan, A; Huang, J; Geng, L; Xu, J; Zhao, X

1994-01-01

The detector, a multi-channel photometric detector, described in this paper was developed using multi-wavelength LEDs (light emitting diode) and phototransistors for absorbance measurement controlled by an Intel 8031 8-bit single chip microcomputer. Up to four flow cells can be attached to the detector. The LEDs and phototransistors are both inexpensive, and reliable. The results given by the detector for simultaneous determination of trace amounts of cobalt and cadmium in zinc sulphate electrolyte are reported. Because of the newly developed detector, this approach employs much less hardware apparatus than by employing conventional photometric detectors.

Dirac R-matrix calculations of photoionization cross sections of Ni XII and atomic structure data of Ni XIII

NASA Astrophysics Data System (ADS)

Nazir, R. T.; Bari, M. A.; Bilal, M.; Sardar, S.; Nasim, M. H.; Salahuddin, M.

2017-02-01

We performed R-matrix calculations for photoionization cross sections of the two ground state configuration 3s23p5 (^2P^o3/2,1/2) levels and 12 excited states of Ni XII using relativistic Dirac Atomic R-matrix Codes (DARC) across the photon energy range between the ionizations thresholds of the corresponding states and well above the thresholds of the last level of the Ni XIII target ion. Generally, a good agreement is obtained between our results and the earlier theoretical photoionization cross sections. Moreover, we have used two independent fully relativistic GRASP and FAC codes to calculate fine-structure energy levels, wavelengths, oscillator strengths, transitions rates among the lowest 48 levels belonging to the configuration (3s23p4, 3s3p5, 3p6, 3s23p33d) in Ni XIII. Additionally, radiative lifetimes of all the excited states of Ni XIII are presented. Our results of the atomic structure of Ni XIII show good agreement with other theoretical and experimental results available in the literature. A good agreement is found between our calculated lifetimes and the experimental ones. Our present results are useful for plasma diagnostic of fusion and astrophysical plasmas.

Numerical investigation of spray ignition of a multi-component fuel surrogate

NASA Astrophysics Data System (ADS)

Backer, Lara; Narayanaswamy, Krithika; Pepiot, Perrine

2014-11-01

Simulating turbulent spray ignition, an important process in engine combustion, is challenging, since it combines the complexity of multi-scale, multiphase turbulent flow modeling with the need for an accurate description of chemical kinetics. In this work, we use direct numerical simulation to investigate the role of the evaporation model on the ignition characteristics of a multi-component fuel surrogate, injected as droplets in a turbulent environment. The fuel is represented as a mixture of several components, each one being representative of a different chemical class. A reduced kinetic scheme for the mixture is extracted from a well-validated detailed chemical mechanism, and integrated into the multiphase turbulent reactive flow solver NGA. Comparisons are made between a single-component evaporation model, in which the evaporating gas has the same composition as the liquid droplet, and a multi-component model, where component segregation does occur. In particular, the corresponding production of radical species, which are characteristic of the ignition of individual fuel components, is thoroughly analyzed.

40 CFR Appendix Xiii to Part 86 - State Requirements Incorporated by Reference in Part 86 of the Code of Federal Regulations

Code of Federal Regulations, 2012 CFR

2012-07-01

... AND IN-USE HIGHWAY VEHICLES AND ENGINES (CONTINUED) Pt. 86, App. XIII Appendix XIII to Part 86—State...-Line Test Procedures for 1983 Through 1997 Model-Year Passenger Cars, Light-Duty Trucks and Medium-Duty...: California Assembly-Line Test Procedures for 1998 and Subsequent Model-Year Passenger Cars, Light-Duty Trucks...

40 CFR Appendix Xiii to Part 86 - State Requirements Incorporated by Reference in Part 86 of the Code of Federal Regulations

Code of Federal Regulations, 2013 CFR

2013-07-01

... AND IN-USE HIGHWAY VEHICLES AND ENGINES (CONTINUED) Pt. 86, App. XIII Appendix XIII to Part 86—State...-Line Test Procedures for 1983 Through 1997 Model-Year Passenger Cars, Light-Duty Trucks and Medium-Duty...: California Assembly-Line Test Procedures for 1998 and Subsequent Model-Year Passenger Cars, Light-Duty Trucks...

40 CFR Appendix Xiii to Part 86 - State Requirements Incorporated by Reference in Part 86 of the Code of Federal Regulations

Code of Federal Regulations, 2011 CFR

2011-07-01

... AND IN-USE HIGHWAY VEHICLES AND ENGINES (CONTINUED) Pt. 86, App. XIII Appendix XIII to Part 86—State...-Line Test Procedures for 1983 Through 1997 Model-Year Passenger Cars, Light-Duty Trucks and Medium-Duty...: California Assembly-Line Test Procedures for 1998 and Subsequent Model-Year Passenger Cars, Light-Duty Trucks...

Multi-Body Analysis of a Tiltrotor Configuration

NASA Technical Reports Server (NTRS)

Ghiringhelli, G. L.; Masarati, P.; Mantegazza, P.; Nixon, M. W.

1997-01-01

The paper describes the aeroelastic analysis of a tiltrotor configuration. The 1/5 scale wind tunnel semispan model of the V-22 tiltrotor aircraft is considered. The analysis is performed by means of a multi-body code, based on an original formulation. The differential equilibrium problem is stated in terms of first order differential equations. The equilibrium equations of every rigid body are written, together with the definitions of the momenta. The bodies are connected by kinematic constraints, applied in form of Lagrangian multipliers. Deformable components are mainly modelled by means of beam elements, based on an original finite volume formulation. Multi-disciplinar problems can be solved by adding user-defined differential equations. In the presented analysis the equations related to the control of the swash-plate of the model are considered. Advantages of a multi-body aeroelastic code over existing comprehensive rotorcraft codes include the exact modelling of the kinematics of the hub, the detailed modelling of the flexibility of critical hub components, and the possibility to simulate steady flight conditions as well as wind-up and maneuvers. The simulations described in the paper include: 1) the analysis of the aeroelastic stability, with particular regard to the proprotor/pylon instability that is peculiar to tiltrotors, 2) the determination of the dynamic behavior of the system and of the loads due to typical maneuvers, with particular regard to the conversion from helicopter to airplane mode, and 3) the stress evaluation in critical components, such as the pitch links and the conversion downstop spring.

Electrostatic twisted modes in multi-component dusty plasmas

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

Ayub, M. K.; National Centre for Physics, Shahdra Valley Road, Quaid-i-Azam University Campus, Islamabad 44000; Pohang University of Sciences and Technology, Pohang, Gyeongbuk 790-784

Various electrostatic twisted modes are re-investigated with finite orbital angular momentum in an unmagnetized collisionless multi-component dusty plasma, consisting of positive/negative charged dust particles, ions, and electrons. For this purpose, hydrodynamical equations are employed to obtain paraxial equations in terms of density perturbations, while assuming the Gaussian and Laguerre-Gaussian (LG) beam solutions. Specifically, approximated solutions for potential problem are studied by using the paraxial approximation and expressed the electric field components in terms of LG functions. The energy fluxes associated with these modes are computed and corresponding expressions for orbital angular momenta are derived. Numerical analyses reveal that radial/angular modemore » numbers as well as dust number density and dust charging states strongly modify the LG potential profiles attributed to different electrostatic modes. Our results are important for understanding particle transport and energy transfer due to wave excitations in multi-component dusty plasmas.« less

Probabilistic Multi-Scale, Multi-Level, Multi-Disciplinary Analysis and Optimization of Engine Structures

NASA Technical Reports Server (NTRS)

Chamis, Christos C.; Abumeri, Galib H.

2000-01-01

Aircraft engines are assemblies of dynamically interacting components. Engine updates to keep present aircraft flying safely and engines for new aircraft are progressively required to operate in more demanding technological and environmental requirements. Designs to effectively meet those requirements are necessarily collections of multi-scale, multi-level, multi-disciplinary analysis and optimization methods and probabilistic methods are necessary to quantify respective uncertainties. These types of methods are the only ones that can formally evaluate advanced composite designs which satisfy those progressively demanding requirements while assuring minimum cost, maximum reliability and maximum durability. Recent research activities at NASA Glenn Research Center have focused on developing multi-scale, multi-level, multidisciplinary analysis and optimization methods. Multi-scale refers to formal methods which describe complex material behavior metal or composite; multi-level refers to integration of participating disciplines to describe a structural response at the scale of interest; multidisciplinary refers to open-ended for various existing and yet to be developed discipline constructs required to formally predict/describe a structural response in engine operating environments. For example, these include but are not limited to: multi-factor models for material behavior, multi-scale composite mechanics, general purpose structural analysis, progressive structural fracture for evaluating durability and integrity, noise and acoustic fatigue, emission requirements, hot fluid mechanics, heat-transfer and probabilistic simulations. Many of these, as well as others, are encompassed in an integrated computer code identified as Engine Structures Technology Benefits Estimator (EST/BEST) or Multi-faceted/Engine Structures Optimization (MP/ESTOP). The discipline modules integrated in MP/ESTOP include: engine cycle (thermodynamics), engine weights, internal fluid mechanics

(n, N) type maintenance policy for multi-component systems with failure interactions

NASA Astrophysics Data System (ADS)

Zhang, Zhuoqi; Wu, Su; Li, Binfeng; Lee, Seungchul

2015-04-01

This paper studies maintenance policies for multi-component systems in which failure interactions and opportunistic maintenance (OM) involve. This maintenance problem can be formulated as a Markov decision process (MDP). However, since an action set and state space in MDP exponentially expand as the number of components increase, traditional approaches are computationally intractable. To deal with curse of dimensionality, we decompose such a multi-component system into mutually influential single-component systems. Each single-component system is formulated as an MDP with the objective of minimising its long-run average maintenance cost. Under some reasonable assumptions, we prove the existence of the optimal (n, N) type policy for a single-component system. An algorithm to obtain the optimal (n, N) type policy is also proposed. Based on the proposed algorithm, we develop an iterative approximation algorithm to obtain an acceptable maintenance policy for a multi-component system. Numerical examples find that failure interactions and OM pose significant effects on a maintenance policy.

[Determination of five naphthaquinones in Arnebia euchroma by quantitative analysis multi-components with single-marker].

PubMed

Zhao, Wen-Wen; Wu, Zhi-Min; Wu, Xia; Zhao, Hai-Yu; Chen, Xiao-Qing

2016-10-01

This study is to determine five naphthaquinones (acetylshikonin, β-acetoxyisovalerylalkannin, isobutylshikonin, β,β'-dimethylacrylalkannin,α-methyl-n-butylshikonin） by quantitative analysis of multi-components with a single marker (QAMS). β,β'-Dimethylacrylalkannin was selected as the internal reference substance, and the relative correlation factors (RCFs) of acetylshikonin, β-acetoxyisovalerylalkannin, isobutylshikonin and α-methyl-n-butylshikonin were calculated. Then the ruggedness of relative correction factors was tested on different instruments and columns. Meanwhile, 16 batches of Arnebia euchroma were analyzed by external standard method (ESM) and QAMS, respectively. The peaks were identifited by LC-MS. The ruggedness of relative correction factors was good. And the analytical results calculated by ESM and QAMS showed no difference. The quantitative method established was feasible and suitable for the quality evaluation of A. euchroma. Copyright© by the Chinese Pharmaceutical Association.

A Multi-Dimensional Functional Principal Components Analysis of EEG Data

PubMed Central

Hasenstab, Kyle; Scheffler, Aaron; Telesca, Donatello; Sugar, Catherine A.; Jeste, Shafali; DiStefano, Charlotte; Şentürk, Damla

2017-01-01

Summary The electroencephalography (EEG) data created in event-related potential (ERP) experiments have a complex high-dimensional structure. Each stimulus presentation, or trial, generates an ERP waveform which is an instance of functional data. The experiments are made up of sequences of multiple trials, resulting in longitudinal functional data and moreover, responses are recorded at multiple electrodes on the scalp, adding an electrode dimension. Traditional EEG analyses involve multiple simplifications of this structure to increase the signal-to-noise ratio, effectively collapsing the functional and longitudinal components by identifying key features of the ERPs and averaging them across trials. Motivated by an implicit learning paradigm used in autism research in which the functional, longitudinal and electrode components all have critical interpretations, we propose a multidimensional functional principal components analysis (MD-FPCA) technique which does not collapse any of the dimensions of the ERP data. The proposed decomposition is based on separation of the total variation into subject and subunit level variation which are further decomposed in a two-stage functional principal components analysis. The proposed methodology is shown to be useful for modeling longitudinal trends in the ERP functions, leading to novel insights into the learning patterns of children with Autism Spectrum Disorder (ASD) and their typically developing peers as well as comparisons between the two groups. Finite sample properties of MD-FPCA are further studied via extensive simulations. PMID:28072468

Microbial ingrowth around single- and multi-component adhesives studied in vitro.

PubMed

Preussker, S; Klimm, W; Pöschmann, M; Koch, R

2003-01-01

The aim of this study was to compare the in vitro microbial leakage in 4 micro-hybrid composites in combination with 4 single-component dental adhesives (Scotchbond 1/Z100 MP = group 1; Syntac Single-Component/Tetric Flow = group 3; OptiBond Solo/XRV Herculite = group 5; Solobond M/Arabesk Top = group 7) and 4 multi-component dental adhesives (Scotchbond Multi-Purpose/Z100 MP = group 2; Syntac/Tetric Flow = group 4; OptiBond FL/XRV Herculite = group 6; Solobond Plus/Arabesk Top = group 8). Ninety-four mixed standardized Class V cavities of human caries-free extracted premolars were filled with eight different composite adhesive systems using a one-layer (groups 1-4) or a two-layer technique (groups 5-8). After thermocycling and incubation in a broth culture of Streptococcus mutans and Lactobacillus acidophilus, followed by decalcification and staining, the extent and the type of microbial leakage were measured histologically. The extent of microbial leakage in the composite restorations was very low in all groups and there were no significant differences between adhesives. Z100 MP in combination with single- and multi-component adhesives showed a significantly higher microbial leakage than Tetric Flow systems (U test: p=0.037). XRV Herculite adhesive systems showed significantly less extensive microbial leakage than Arabesk Top adhesive systems (U test: p<0.001). The single-component dental adhesives achieved a marginal adaptation of composites comparable to that of multi-component adhesives in vitro. Copyright 2003 S. Karger AG, Basel

Energy levels, lifetimes, and transition rates for the selenium isoelectronic sequence Pd XIII-Te XIX, Xe XXI-Nd XXVII, W XLI

NASA Astrophysics Data System (ADS)

Wang, K.; Yang, X.; Chen, Z. B.; Si, R.; Chen, C. Y.; Yan, J.; Zhao, X. H.; Dang, W.

2017-09-01

Energy levels, wavelengths, lifetimes, oscillator strengths, and electric dipole (E1), magnetic dipole (M1), electric quadrupole (E2), magnetic quadrupole (M2) transition rates among the 46 fine structure levels belonging to the ([ Ar ] 3d10) 4s2 4p4, ([ Ar ] 3d10) 4s2 4p3 4 d, and ([ Ar ] 3d10) 4 s 4p5 configurations for the selenium isoelectronic sequence Pd XIII-Te XIX, Xe XXI-Nd XXVII, W XLI are reported. These data are determined in the multi-configuration Dirac-Fock (MCDF) approach, in which relativistic effects, main electron correlations within the n = 7 complex, Breit interaction (BI), and quantum electrodynamic (QED) corrections are included. The many-body perturbation theory (MBPT) method is also employed as an independent calculation to confirm the present accuracy, taking W XLI as an example. Comparisons and analysis are made between the present results and available experimental and theoretical ones, and good agreements are obtained. These accurate data are expected to be useful in nuclear fusion research and astrophysical applications.

A multi-dimensional functional principal components analysis of EEG data.

PubMed

Hasenstab, Kyle; Scheffler, Aaron; Telesca, Donatello; Sugar, Catherine A; Jeste, Shafali; DiStefano, Charlotte; Şentürk, Damla

2017-09-01

The electroencephalography (EEG) data created in event-related potential (ERP) experiments have a complex high-dimensional structure. Each stimulus presentation, or trial, generates an ERP waveform which is an instance of functional data. The experiments are made up of sequences of multiple trials, resulting in longitudinal functional data and moreover, responses are recorded at multiple electrodes on the scalp, adding an electrode dimension. Traditional EEG analyses involve multiple simplifications of this structure to increase the signal-to-noise ratio, effectively collapsing the functional and longitudinal components by identifying key features of the ERPs and averaging them across trials. Motivated by an implicit learning paradigm used in autism research in which the functional, longitudinal, and electrode components all have critical interpretations, we propose a multidimensional functional principal components analysis (MD-FPCA) technique which does not collapse any of the dimensions of the ERP data. The proposed decomposition is based on separation of the total variation into subject and subunit level variation which are further decomposed in a two-stage functional principal components analysis. The proposed methodology is shown to be useful for modeling longitudinal trends in the ERP functions, leading to novel insights into the learning patterns of children with Autism Spectrum Disorder (ASD) and their typically developing peers as well as comparisons between the two groups. Finite sample properties of MD-FPCA are further studied via extensive simulations. © 2017, The International Biometric Society.

Predicting the tensile strength of compacted multi-component mixtures of pharmaceutical powders.

PubMed

Wu, Chuan-Yu; Best, Serena M; Bentham, A Craig; Hancock, Bruno C; Bonfield, William

2006-08-01

Pharmaceutical tablets are generally produced by compacting a mixture of several ingredients, including active drugs and excipients. It is of practical importance if the properties of such tablets can be predicted on the basis of the ones for constituent components. The purpose of this work is to develop a theoretical model which can predict the tensile strength of compacted multi-component pharmaceutical mixtures. The model was derived on the basis of the Ryshkewitch-Duckworth equation that was originally proposed for porous materials. The required input parameters for the model are the relative density or solid fraction (ratio of the volume of solid materials to the total volume of the tablets) of the multi-component tablets and parameters associated with the constituent single-component powders, which are readily accessible. The tensile strength of tablets made of various powder blends at different relative density was also measured using diametrical compression. It has been shown that the tensile strength of the multi-component powder compacts is primarily a function of the solid fraction. Excellent agreement between prediction and experimental data for tablets of binary, ternary and four-component blends of some widely used pharmaceutical excipients was obtained. It has been demonstrated that the proposed model can well predict the tensile strength of multi-component pharmaceutical tablets. Thus, the model will be a useful design tool for formulation engineers in the pharmaceutical industry.

Novel Reagents for Multi-Component Reactions

NASA Astrophysics Data System (ADS)

Wang, Yanguang; Basso, Andrea; Nenajdenko, Valentine G.; Gulevich, Anton V.; Krasavin, Mikhail; Bushkova, Ekaterina; Parchinsky, Vladislav; Banfi, Luca; Basso, Andrea; Cerulli, Valentina; Guanti, Giuseppe; Riva, Renata; Rozentsveig, Igor B.; Rozentsveig, Gulnur N.; Popov, Aleksandr V.; Serykh, Valeriy J.; Levkovskaya, Galina G.; Cao, Song; Shen, Li; Liu, Nianjin; Wu, Jingjing; Li, Lina; Qian, Xuhong; Chen, Xiaopeng; Wang, Hongbo; Feng, Jinwu; Wang, Yanguang; Lu, Ping; Heravi, Majid M.; Sadjadi, Samaheh; Kazemizadeh, Ali Reza; Ramazani, Ali; Kudyakova, Yulia S.; Goryaeva, Marina V.; Burgart, Yanina V.; Saloutin, Victor I.; Mossetti, Riccardo; Pirali, Tracey; Tron, Gian Cesare; Rozhkova, Yulia S.; Mayorova, Olga A.; Shklyaev, Yuriy V.; Zhdanko, Alexander G.; Nenajdenko, Valentine G.; Stryapunina, Olga G.; Plekhanova, Irina V.; Glushkov, Vladimir A.; Shklyaev, Yurii V.

Ketenimines are a class of versatile and highly reactive intermediates that can participate in a variety of organic reactions, such as nucleophilic additions, radical additions, [2 + 2] and [2 + 4] cycloadditions, and sigmatropic rearrangements. In this presentation, we report on a series of multi-component reactions that involve a ketenimine intermediate. These reactions could furnish diverse heterocyclic compounds, including functionalized iminocoumarin, iminodihydroqunolines, iminothiochromens, pyrrolines, isoquinolines, pyridines, β-lactams, imino-1,2-dihydrocoumarins, and benzimidazoles.

AEROFROSH: a shock condition calculator for multi-component fuel aerosol-laden flows

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

Campbell, Matthew Frederick; Haylett, D. R.; Davidson, D. F.

Here, this paper introduces an algorithm that determines the thermodynamic conditions behind incident and reflectedshocksinaerosol-ladenflows.Importantly,the algorithm accounts for the effects of droplet evaporation on post-shock properties. Additionally, this article describes an algorithm for resolving the effects of multiple-component- fuel droplets. This article presents the solution methodology and compares the results to those of another similar shock calculator. It also provides examples to show the impact of droplets on post-shock properties and the impact that multi-component fuel droplets have on shock experimental parameters. Finally, this paper presents a detailed uncertainty analysis of this algorithm’s calculations given typical exper- imental uncertainties

AEROFROSH: a shock condition calculator for multi-component fuel aerosol-laden flows

DOE PAGES

Campbell, Matthew Frederick; Haylett, D. R.; Davidson, D. F.; ...

2015-08-18

Here, this paper introduces an algorithm that determines the thermodynamic conditions behind incident and reflectedshocksinaerosol-ladenflows.Importantly,the algorithm accounts for the effects of droplet evaporation on post-shock properties. Additionally, this article describes an algorithm for resolving the effects of multiple-component- fuel droplets. This article presents the solution methodology and compares the results to those of another similar shock calculator. It also provides examples to show the impact of droplets on post-shock properties and the impact that multi-component fuel droplets have on shock experimental parameters. Finally, this paper presents a detailed uncertainty analysis of this algorithm’s calculations given typical exper- imental uncertainties

Detailed finite element method modeling of evaporating multi-component droplets

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

Diddens, Christian, E-mail: C.Diddens@tue.nl

The evaporation of sessile multi-component droplets is modeled with an axisymmetic finite element method. The model comprises the coupled processes of mixture evaporation, multi-component flow with composition-dependent fluid properties and thermal effects. Based on representative examples of water–glycerol and water–ethanol droplets, regular and chaotic examples of solutal Marangoni flows are discussed. Furthermore, the relevance of the substrate thickness for the evaporative cooling of volatile binary mixture droplets is pointed out. It is shown how the evaporation of the more volatile component can drastically decrease the interface temperature, so that ambient vapor of the less volatile component condenses on the droplet.more » Finally, results of this model are compared with corresponding results of a lubrication theory model, showing that the application of lubrication theory can cause considerable errors even for moderate contact angles of 40°. - Graphical abstract:.« less

Multi-component Wronskian solution to the Kadomtsev-Petviashvili equation

NASA Astrophysics Data System (ADS)

Xu, Tao; Sun, Fu-Wei; Zhang, Yi; Li, Juan

2014-01-01

It is known that the Kadomtsev-Petviashvili (KP) equation can be decomposed into the first two members of the coupled Ablowitz-Kaup-Newell-Segur (AKNS) hierarchy by the binary non-linearization of Lax pairs. In this paper, we construct the N-th iterated Darboux transformation (DT) for the second- and third-order m-coupled AKNS systems. By using together the N-th iterated DT and Cramer's rule, we find that the KPII equation has the unreduced multi-component Wronskian solution and the KPI equation admits a reduced multi-component Wronskian solution. In particular, based on the unreduced and reduced two-component Wronskians, we obtain two families of fully-resonant line-soliton solutions which contain arbitrary numbers of asymptotic solitons as y → ∓∞ to the KPII equation, and the ordinary N-soliton solution to the KPI equation. In addition, we find that the KPI line solitons propagating in parallel can exhibit the bound state at the moment of collision.

Aerosol observation using multi-wavelength Mie-Raman lidars of the Ad-Net and aerosol component analysis

NASA Astrophysics Data System (ADS)

Nishizawa, Tomoaki; Sugimoto, Nobuo; Shimizu, Atsushi; Uno, Itsushi; Hara, Yukari; Kudo, Rei

2018-04-01

We deployed multi-wavelength Mie-Raman lidars (MMRL) at three sites of the AD-Net and have conducted continuous measurements using them since 2013. To analyze the MMRL data and better understand the externally mixing state of main aerosol components (e.g., dust, sea-salt, and black carbon) in the atmosphere, we developed an integrated package of aerosol component retrieval algorithms, which have already been developed or are being developed, to estimate vertical profiles of the aerosol components. This package applies to the other ground-based lidar network data (e.g., EARLINET) and satellite-borne lidar data (e.g., CALIOP/CALIPSO and ATLID/EarthCARE) as well as the other lidar data of the AD-Net.

Simultaneous multi-component seismic denoising and reconstruction via K-SVD

NASA Astrophysics Data System (ADS)

Hou, Sian; Zhang, Feng; Li, Xiangyang; Zhao, Qiang; Dai, Hengchang

2018-06-01

Data denoising and reconstruction play an increasingly significant role in seismic prospecting for their value in enhancing effective signals, dealing with surface obstacles and reducing acquisition costs. In this paper, we propose a novel method to denoise and reconstruct multicomponent seismic data simultaneously. This method lies within the framework of machine learning and the key points are defining a suitable weight function and a modified inner product operator. The purpose of these two processes are to perform missing data machine learning when the random noise deviation is unknown, and building a mathematical relationship for each component to incorporate all the information of multi-component data. Two examples, using synthetic and real multicomponent data, demonstrate that the new method is a feasible alternative for multi-component seismic data processing.

Principal components analysis based control of a multi-DoF underactuated prosthetic hand.

PubMed

Matrone, Giulia C; Cipriani, Christian; Secco, Emanuele L; Magenes, Giovanni; Carrozza, Maria Chiara

2010-04-23

Functionality, controllability and cosmetics are the key issues to be addressed in order to accomplish a successful functional substitution of the human hand by means of a prosthesis. Not only the prosthesis should duplicate the human hand in shape, functionality, sensorization, perception and sense of body-belonging, but it should also be controlled as the natural one, in the most intuitive and undemanding way. At present, prosthetic hands are controlled by means of non-invasive interfaces based on electromyography (EMG). Driving a multi degrees of freedom (DoF) hand for achieving hand dexterity implies to selectively modulate many different EMG signals in order to make each joint move independently, and this could require significant cognitive effort to the user. A Principal Components Analysis (PCA) based algorithm is used to drive a 16 DoFs underactuated prosthetic hand prototype (called CyberHand) with a two dimensional control input, in order to perform the three prehensile forms mostly used in Activities of Daily Living (ADLs). Such Principal Components set has been derived directly from the artificial hand by collecting its sensory data while performing 50 different grasps, and subsequently used for control. Trials have shown that two independent input signals can be successfully used to control the posture of a real robotic hand and that correct grasps (in terms of involved fingers, stability and posture) may be achieved. This work demonstrates the effectiveness of a bio-inspired system successfully conjugating the advantages of an underactuated, anthropomorphic hand with a PCA-based control strategy, and opens up promising possibilities for the development of an intuitively controllable hand prosthesis.

Using independent component analysis for electrical impedance tomography

NASA Astrophysics Data System (ADS)

Yan, Peimin; Mo, Yulong

2004-05-01

Independent component analysis (ICA) is a way to resolve signals into independent components based on the statistical characteristics of the signals. It is a method for factoring probability densities of measured signals into a set of densities that are as statistically independent as possible under the assumptions of a linear model. Electrical impedance tomography (EIT) is used to detect variations of the electric conductivity of the human body. Because there are variations of the conductivity distributions inside the body, EIT presents multi-channel data. In order to get all information contained in different location of tissue it is necessary to image the individual conductivity distribution. In this paper we consider to apply ICA to EIT on the signal subspace (individual conductivity distribution). Using ICA the signal subspace will then be decomposed into statistically independent components. The individual conductivity distribution can be reconstructed by the sensitivity theorem in this paper. Compute simulations show that the full information contained in the multi-conductivity distribution will be obtained by this method.

Two-dimensional multi-component photometric decomposition of CALIFA galaxies

NASA Astrophysics Data System (ADS)

Méndez-Abreu, J.; Ruiz-Lara, T.; Sánchez-Menguiano, L.; de Lorenzo-Cáceres, A.; Costantin, L.; Catalán-Torrecilla, C.; Florido, E.; Aguerri, J. A. L.; Bland-Hawthorn, J.; Corsini, E. M.; Dettmar, R. J.; Galbany, L.; García-Benito, R.; Marino, R. A.; Márquez, I.; Ortega-Minakata, R. A.; Papaderos, P.; Sánchez, S. F.; Sánchez-Blazquez, P.; Spekkens, K.; van de Ven, G.; Wild, V.; Ziegler, B.

2017-02-01

We present a two-dimensional multi-component photometric decomposition of 404 galaxies from the Calar Alto Legacy Integral Field Area data release 3 (CALIFA-DR3). They represent all possible galaxies with no clear signs of interaction and not strongly inclined in the final CALIFA data release. Galaxies are modelled in the g, r, and I Sloan Digital Sky Survey (SDSS) images including, when appropriate, a nuclear point source, bulge, bar, and an exponential or broken disc component. We use a human-supervised approach to determine the optimal number of structures to be included in the fit. The dataset, including the photometric parameters of the CALIFA sample, is released together with statistical errors and a visual analysis of the quality of each fit. The analysis of the photometric components reveals a clear segregation of the structural composition of galaxies with stellar mass. At high masses (log (M⋆/M⊙) > 11), the galaxy population is dominated by galaxies modelled with a single Sérsic or a bulge+disc with a bulge-to-total (B/T) luminosity ratio B/T > 0.2. At intermediate masses (9.5 < log (M⋆/M⊙) < 11), galaxies described with bulge+disc but B/T < 0.2 are preponderant, whereas, at the low mass end (log (M⋆/M⊙) < 9.5), the prevailing population is constituted by galaxies modelled with either purediscs or nuclear point sources+discs (I.e., no discernible bulge). We obtain that 57% of the volume corrected sample of disc galaxies in the CALIFA sample host a bar. This bar fraction shows a significant drop with increasing galaxy mass in the range 9.5 < log (M⋆/M⊙) < 11.5. The analyses of the extended multi-component radial profile result in a volume-corrected distribution of 62%, 28%, and 10% for the so-called Type I (pure exponential), Type II (down-bending), and Type III (up-bending) disc profiles, respectively. These fractions are in discordance with previous findings. We argue that the different methodologies used to detect the breaks are the

Searching for the main anti-bacterial components in artificial Calculus bovis using UPLC and microcalorimetry coupled with multi-linear regression analysis.

PubMed

Zang, Qing-Ce; Wang, Jia-Bo; Kong, Wei-Jun; Jin, Cheng; Ma, Zhi-Jie; Chen, Jing; Gong, Qian-Feng; Xiao, Xiao-He

2011-12-01

The fingerprints of artificial Calculus bovis extracts from different solvents were established by ultra-performance liquid chromatography (UPLC) and the anti-bacterial activities of artificial C. bovis extracts on Staphylococcus aureus (S. aureus) growth were studied by microcalorimetry. The UPLC fingerprints were evaluated using hierarchical clustering analysis. Some quantitative parameters obtained from the thermogenic curves of S. aureus growth affected by artificial C. bovis extracts were analyzed using principal component analysis. The spectrum-effect relationships between UPLC fingerprints and anti-bacterial activities were investigated using multi-linear regression analysis. The results showed that peak 1 (taurocholate sodium), peak 3 (unknown compound), peak 4 (cholic acid), and peak 6 (chenodeoxycholic acid) are more significant than the other peaks with the standard parameter estimate 0.453, -0.166, 0.749, 0.025, respectively. So, compounds cholic acid, taurocholate sodium, and chenodeoxycholic acid might be the major anti-bacterial components in artificial C. bovis. Altogether, this work provides a general model of the combination of UPLC chromatography and anti-bacterial effect to study the spectrum-effect relationships of artificial C. bovis extracts, which can be used to discover the main anti-bacterial components in artificial C. bovis or other Chinese herbal medicines with anti-bacterial effects. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Instabilities in rapid solidification of multi-component alloys

NASA Astrophysics Data System (ADS)

Altieri, Anthony L.; Davis, Stephen H.

2017-10-01

Rapid solidification of multi-component liquids occurs in many modern applications such as additive manufacturing. In the present work the interface departures from equilibrium consist of the segregation coefficient and liquidus slope depending on front speed, the one-sided, frozen-temperature approximation, and the alloy behaving as the superposition of individual components. Linear-stability theory is applied, showing that the cellular and oscillatory instabilities of the binary case are modified. The addition of components tends to destabilize the interface while the addition of a single large-diffusivity material can entirely suppress the oscillatory mode. Multiple minima in the neutral curve for the cellular mode occur.

Dissipative hydrodynamics for multi-component systems

NASA Astrophysics Data System (ADS)

El, Andrej; Bouras, Ioannis; Wesp, Christian; Xu, Zhe; Greiner, Carsten

2012-11-01

Second-order dissipative hydrodynamic equations for each component of a multi-component system are derived using the entropy principle. Comparison of the solutions with kinetic transport results demonstrates validity of the obtained equations. We demonstrate how the shear viscosity of the total system can be calculated in terms of the involved cross-sections and partial densities. The presence of the inter-species interactions leads to a characteristic time dependence of the shear viscosity of the mixture, which also means that the shear viscosity of a mixture cannot be calculated using the Green-Kubo formalism the way it has been done recently. This finding is of interest for understanding of the shear viscosity of a quark-gluon plasma extracted from comparisons of hydrodynamic simulations with experimental results from RHIC and LHC.

Independent component analysis decomposition of hospital emergency department throughput measures

NASA Astrophysics Data System (ADS)

He, Qiang; Chu, Henry

2016-05-01

We present a method adapted from medical sensor data analysis, viz. independent component analysis of electroencephalography data, to health system analysis. Timely and effective care in a hospital emergency department is measured by throughput measures such as median times patients spent before they were admitted as an inpatient, before they were sent home, before they were seen by a healthcare professional. We consider a set of five such measures collected at 3,086 hospitals distributed across the U.S. One model of the performance of an emergency department is that these correlated throughput measures are linear combinations of some underlying sources. The independent component analysis decomposition of the data set can thus be viewed as transforming a set of performance measures collected at a site to a collection of outputs of spatial filters applied to the whole multi-measure data. We compare the independent component sources with the output of the conventional principal component analysis to show that the independent components are more suitable for understanding the data sets through visualizations.

A hierarchical model for probabilistic independent component analysis of multi-subject fMRI studies

PubMed Central

Tang, Li

2014-01-01

Summary An important goal in fMRI studies is to decompose the observed series of brain images to identify and characterize underlying brain functional networks. Independent component analysis (ICA) has been shown to be a powerful computational tool for this purpose. Classic ICA has been successfully applied to single-subject fMRI data. The extension of ICA to group inferences in neuroimaging studies, however, is challenging due to the unavailability of a pre-specified group design matrix. Existing group ICA methods generally concatenate observed fMRI data across subjects on the temporal domain and then decompose multi-subject data in a similar manner to single-subject ICA. The major limitation of existing methods is that they ignore between-subject variability in spatial distributions of brain functional networks in group ICA. In this paper, we propose a new hierarchical probabilistic group ICA method to formally model subject-specific effects in both temporal and spatial domains when decomposing multi-subject fMRI data. The proposed method provides model-based estimation of brain functional networks at both the population and subject level. An important advantage of the hierarchical model is that it provides a formal statistical framework to investigate similarities and differences in brain functional networks across subjects, e.g., subjects with mental disorders or neurodegenerative diseases such as Parkinson’s as compared to normal subjects. We develop an EM algorithm for model estimation where both the E-step and M-step have explicit forms. We compare the performance of the proposed hierarchical model with that of two popular group ICA methods via simulation studies. We illustrate our method with application to an fMRI study of Zen meditation. PMID:24033125

Comparison of common components analysis with principal components analysis and independent components analysis: Application to SPME-GC-MS volatolomic signatures.

PubMed

Bouhlel, Jihéne; Jouan-Rimbaud Bouveresse, Delphine; Abouelkaram, Said; Baéza, Elisabeth; Jondreville, Catherine; Travel, Angélique; Ratel, Jérémy; Engel, Erwan; Rutledge, Douglas N

2018-02-01

The aim of this work is to compare a novel exploratory chemometrics method, Common Components Analysis (CCA), with Principal Components Analysis (PCA) and Independent Components Analysis (ICA). CCA consists in adapting the multi-block statistical method known as Common Components and Specific Weights Analysis (CCSWA or ComDim) by applying it to a single data matrix, with one variable per block. As an application, the three methods were applied to SPME-GC-MS volatolomic signatures of livers in an attempt to reveal volatile organic compounds (VOCs) markers of chicken exposure to different types of micropollutants. An application of CCA to the initial SPME-GC-MS data revealed a drift in the sample Scores along CC2, as a function of injection order, probably resulting from time-related evolution in the instrument. This drift was eliminated by orthogonalization of the data set with respect to CC2, and the resulting data are used as the orthogonalized data input into each of the three methods. Since the first step in CCA is to norm-scale all the variables, preliminary data scaling has no effect on the results, so that CCA was applied only to orthogonalized SPME-GC-MS data, while, PCA and ICA were applied to the "orthogonalized", "orthogonalized and Pareto-scaled", and "orthogonalized and autoscaled" data. The comparison showed that PCA results were highly dependent on the scaling of variables, contrary to ICA where the data scaling did not have a strong influence. Nevertheless, for both PCA and ICA the clearest separations of exposed groups were obtained after autoscaling of variables. The main part of this work was to compare the CCA results using the orthogonalized data with those obtained with PCA and ICA applied to orthogonalized and autoscaled variables. The clearest separations of exposed chicken groups were obtained by CCA. CCA Loadings also clearly identified the variables contributing most to the Common Components giving separations. The PCA Loadings did not

[Simultaneous quantitative analysis of five alkaloids in Sophora flavescens by multi-components assay by single marker].

PubMed

Chen, Jing; Wang, Shu-Mei; Meng, Jiang; Sun, Fei; Liang, Sheng-Wang

2013-05-01

To establish a new method for quality evaluation and validate its feasibilities by simultaneous quantitative assay of five alkaloids in Sophora flavescens. The new quality evaluation method, quantitative analysis of multi-components by single marker (QAMS), was established and validated with S. flavescens. Five main alkaloids, oxymatrine, sophocarpine, matrine, oxysophocarpine and sophoridine, were selected as analytes to evaluate the quality of rhizome of S. flavescens, and the relative correction factor has good repeatibility. Their contents in 21 batches of samples, collected from different areas, were determined by both external standard method and QAMS. The method was evaluated by comparison of the quantitative results between external standard method and QAMS. No significant differences were found in the quantitative results of five alkaloids in 21 batches of S. flavescens determined by external standard method and QAMS. It is feasible and suitable to evaluate the quality of rhizome of S. flavescens by QAMS.

Multi-scale diffuse interface modeling of multi-component two-phase flow with partial miscibility

NASA Astrophysics Data System (ADS)

Kou, Jisheng; Sun, Shuyu

2016-08-01

In this paper, we introduce a diffuse interface model to simulate multi-component two-phase flow with partial miscibility based on a realistic equation of state (e.g. Peng-Robinson equation of state). Because of partial miscibility, thermodynamic relations are used to model not only interfacial properties but also bulk properties, including density, composition, pressure, and realistic viscosity. As far as we know, this effort is the first time to use diffuse interface modeling based on equation of state for modeling of multi-component two-phase flow with partial miscibility. In numerical simulation, the key issue is to resolve the high contrast of scales from the microscopic interface composition to macroscale bulk fluid motion since the interface has a nanoscale thickness only. To efficiently solve this challenging problem, we develop a multi-scale simulation method. At the microscopic scale, we deduce a reduced interfacial equation under reasonable assumptions, and then we propose a formulation of capillary pressure, which is consistent with macroscale flow equations. Moreover, we show that Young-Laplace equation is an approximation of this capillarity formulation, and this formulation is also consistent with the concept of Tolman length, which is a correction of Young-Laplace equation. At the macroscopical scale, the interfaces are treated as discontinuous surfaces separating two phases of fluids. Our approach differs from conventional sharp-interface two-phase flow model in that we use the capillary pressure directly instead of a combination of surface tension and Young-Laplace equation because capillarity can be calculated from our proposed capillarity formulation. A compatible condition is also derived for the pressure in flow equations. Furthermore, based on the proposed capillarity formulation, we design an efficient numerical method for directly computing the capillary pressure between two fluids composed of multiple components. Finally, numerical tests

Analysis of Multi-State Systems with Multi-State Components Using EVMDDs

DTIC Science & Technology

2012-05-01

Fault-Tolerant Computing (FTCS), pp. 249– 258, June 1995. [5] T. Kam, T. Villa, R. K. Brayton , and A. L. Sangiovanni- Vincentelli, “Multi-valued...Shmerko, and R. S. Stankovic, Decision Diagram Techniques for Micro- and Nanoelectronic Design, CRC Press, Taylor & Francis Group, 2006. [16] X. Zang, D

Connected Component Model for Multi-Object Tracking.

PubMed

He, Zhenyu; Li, Xin; You, Xinge; Tao, Dacheng; Tang, Yuan Yan

2016-08-01

In multi-object tracking, it is critical to explore the data associations by exploiting the temporal information from a sequence of frames rather than the information from the adjacent two frames. Since straightforwardly obtaining data associations from multi-frames is an NP-hard multi-dimensional assignment (MDA) problem, most existing methods solve this MDA problem by either developing complicated approximate algorithms, or simplifying MDA as a 2D assignment problem based upon the information extracted only from adjacent frames. In this paper, we show that the relation between associations of two observations is the equivalence relation in the data association problem, based on the spatial-temporal constraint that the trajectories of different objects must be disjoint. Therefore, the MDA problem can be equivalently divided into independent subproblems by equivalence partitioning. In contrast to existing works for solving the MDA problem, we develop a connected component model (CCM) by exploiting the constraints of the data association and the equivalence relation on the constraints. Based upon CCM, we can efficiently obtain the global solution of the MDA problem for multi-object tracking by optimizing a sequence of independent data association subproblems. Experiments on challenging public data sets demonstrate that our algorithm outperforms the state-of-the-art approaches.

[Study on high accuracy detection of multi-component gas in oil-immerse power transformer].

PubMed

Fan, Jie; Chen, Xiao; Huang, Qi-Feng; Zhou, Yu; Chen, Gang

2013-12-01

In order to solve the problem of low accuracy and mutual interference in multi-component gas detection, a kind of multi-component gas detection network with high accuracy was designed. A semiconductor laser with narrow bandwidth was utilized as light source and a novel long-path gas cell was also used in this system. By taking the single sine signal to modulate the spectrum of laser and using space division multiplexing (SDM) and time division multiplexing (TDM) technique, the detection of multi-component gas was achieved. The experiments indicate that the linearity relevance coefficient is 0. 99 and the measurement relative error is less than 4%. The system dynamic response time is less than 15 s, by filling a volume of multi-component gas into the gas cell gradually. The system has advantages of high accuracy and quick response, which can be used in the fault gas on-line monitoring for power transformers in real time.

A new multi-objective optimization model for preventive maintenance and replacement scheduling of multi-component systems

NASA Astrophysics Data System (ADS)

Moghaddam, Kamran S.; Usher, John S.

2011-07-01

In this article, a new multi-objective optimization model is developed to determine the optimal preventive maintenance and replacement schedules in a repairable and maintainable multi-component system. In this model, the planning horizon is divided into discrete and equally-sized periods in which three possible actions must be planned for each component, namely maintenance, replacement, or do nothing. The objective is to determine a plan of actions for each component in the system while minimizing the total cost and maximizing overall system reliability simultaneously over the planning horizon. Because of the complexity, combinatorial and highly nonlinear structure of the mathematical model, two metaheuristic solution methods, generational genetic algorithm, and a simulated annealing are applied to tackle the problem. The Pareto optimal solutions that provide good tradeoffs between the total cost and the overall reliability of the system can be obtained by the solution approach. Such a modeling approach should be useful for maintenance planners and engineers tasked with the problem of developing recommended maintenance plans for complex systems of components.

Treatment of Acute Cough Due to the Common Cold: Multi-component, Multi-symptom Therapy is Preferable to Single-Component, Single-Symptom Therapy--A Pro/Con Debate.

PubMed

Eccles, Ronald; Turner, Ronald B; Dicpinigaitis, Peter V

2016-02-01

Acute viral upper respiratory tract infection, or, the common cold, affects essentially every human being, and cough is reported as its most frequent associated symptom. Billions of dollars are spent worldwide annually by individuals seeking relief from this multi-symptom syndrome. Thousands of non-prescription, over-the-counter products are available worldwide, aimed at relieving the various bothersome symptoms induced by the common cold. Differences of opinion exist as to whether optimal therapy for cough associated with the common cold consists of multi-component, multi-symptom cough/cold preparations, or, whether single-component medications, aimed at relief of specific symptoms, represent the optimal therapeutic approach. The 5th American Cough Conference, held in Washington, D.C. in June, 2015, provided an ideal forum for discussion and debate of this issue between two internationally recognized experts in the field of the common cold and its treatment.

THE SPITZER SURVEY OF STELLAR STRUCTURE IN GALAXIES (S{sup 4}G): MULTI-COMPONENT DECOMPOSITION STRATEGIES AND DATA RELEASE

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

Salo, Heikki; Laurikainen, Eija; Laine, Jarkko

The Spitzer Survey of Stellar Structure in Galaxies (S{sup 4}G) is a deep 3.6 and 4.5 μm imaging survey of 2352 nearby (<40 Mpc) galaxies. We describe the S{sup 4}G data analysis pipeline 4, which is dedicated to two-dimensional structural surface brightness decompositions of 3.6 μm images, using GALFIT3.0. Besides automatic 1-component Sérsic fits, and 2-component Sérsic bulge + exponential disk fits, we present human-supervised multi-component decompositions, which include, when judged appropriate, a central point source, bulge, disk, and bar components. Comparison of the fitted parameters indicates that multi-component models are needed to obtain reliable estimates for the bulge Sérsicmore » index and bulge-to-total light ratio (B/T), confirming earlier results. Here, we describe the preparations of input data done for decompositions, give examples of our decomposition strategy, and describe the data products released via IRSA and via our web page (www.oulu.fi/astronomy/S4G-PIPELINE4/MAIN). These products include all the input data and decomposition files in electronic form, making it easy to extend the decompositions to suit specific science purposes. We also provide our IDL-based visualization tools (GALFIDL) developed for displaying/running GALFIT-decompositions, as well as our mask editing procedure (MASK-EDIT) used in data preparation. A detailed analysis of the bulge, disk, and bar parameters derived from multi-component decompositions will be published separately.« less

Defect Clustering and Nano-Phase Structure Characterization of Multi-Component Rare Earth Oxide Doped Zirconia-Yttria Thermal Barrier Coatings

NASA Technical Reports Server (NTRS)

Zhu, Dongming; Chen, Yuan L.; Miller, Robert A.

2003-01-01

Advanced oxide thermal barrier coatings have been developed by incorporating multi-component rare earth oxide dopants into zirconia-yttria to effectively promote the creation of the thermodynamically stable, immobile oxide defect clusters and/or nano-scale phases within the coating systems. The presence of these nano-sized defect clusters has found to significantly reduce the coating intrinsic thermal conductivity, improve sintering resistance, and maintain long-term high temperature stability. In this paper, the defect clusters and nano-structured phases, which were created by the addition of multi-component rare earth dopants to the plasma-sprayed and electron-beam physical vapor deposited thermal barrier coatings, were characterized by high-resolution transmission electron microscopy (TEM). The defect cluster size, distribution, crystallographic and compositional information were investigated using high-resolution TEM lattice imaging, selected area diffraction (SAD), electron energy-loss spectroscopy (EELS) and energy dispersive spectroscopy (EDS) analysis techniques. The results showed that substantial defect clusters were formed in the advanced multi-component rare earth oxide doped zirconia- yttria systems. The size of the oxide defect clusters and the cluster dopant segregation was typically ranging from 5 to 50 nm. These multi-component dopant induced defect clusters are an important factor for the coating long-term high temperature stability and excellent performance.

Defect Clustering and Nano-Phase Structure Characterization of Multi-Component Rare Earth Oxide Doped Zirconia-Yttria Thermal Barrier Coatings

NASA Technical Reports Server (NTRS)

Zhu, Dongming; Chen, Yuan L.; Miller, Robert A.

1990-01-01

Advanced oxide thermal barrier coatings have been developed by incorporating multi- component rare earth oxide dopants into zirconia-yttria to effectively promote the creation of the thermodynamically stable, immobile oxide defect clusters and/or nano-scale phases within the coating systems. The presence of these nano-sized defect clusters has found to significantly reduce the coating intrinsic thermal conductivity, improve sintering resistance, and maintain long-term high temperature stability. In this paper, the defect clusters and nano-structured phases, which were created by the addition of multi-component rare earth dopants to the plasma- sprayed and electron-beam physical vapor deposited thermal barrier coatings, were characterized by high-resolution transmission electron microscopy (TEM). The defect cluster size, distribution, crystallographic and compositional information were investigated using high-resolution TEM lattice imaging, selected area diffraction (SAD), and energy dispersive spectroscopy (EDS) analysis techniques. The results showed that substantial defect clusters were formed in the advanced multi-component rare earth oxide doped zirconia-yttria systems. The size of the oxide defect clusters and the cluster dopant segregation was typically ranging fiom 5 to 50 nm. These multi-component dopant induced defect clusters are an important factor for the coating long-term high temperature stability and excellent performance.

Improved Holistic Analysis of Rayleigh Waves for Single- and Multi-Offset Data: Joint Inversion of Rayleigh-Wave Particle Motion and Vertical- and Radial-Component Velocity Spectra

NASA Astrophysics Data System (ADS)

Dal Moro, Giancarlo; Moustafa, Sayed S. R.; Al-Arifi, Nassir S.

2018-01-01

Rayleigh waves often propagate according to complex mode excitation so that the proper identification and separation of specific modes can be quite difficult or, in some cases, just impossible. Furthermore, the analysis of a single component (i.e., an inversion procedure based on just one objective function) necessarily prevents solving the problems related to the non-uniqueness of the solution. To overcome these issues and define a holistic analysis of Rayleigh waves, we implemented a procedure to acquire data that are useful to define and efficiently invert the three objective functions defined from the three following "objects": the velocity spectra of the vertical- and radial-components and the Rayleigh-wave particle motion (RPM) frequency-offset data. Two possible implementations are presented. In the first case we consider classical multi-offset (and multi-component) data, while in a second possible approach we exploit the data recorded by a single three-component geophone at a fixed offset from the source. Given the simple field procedures, the method could be particularly useful for the unambiguous geotechnical exploration of large areas, where more complex acquisition procedures, based on the joint acquisition of Rayleigh and Love waves, would not be economically viable. After illustrating the different kinds of data acquisition and the data processing, the results of the proposed methodology are illustrated in a case study. Finally, a series of theoretical and practical aspects are discussed to clarify some issues involved in the overall procedure (data acquisition and processing).

Thermodynamic Modelling of Phase Transformation in a Multi-Component System

NASA Astrophysics Data System (ADS)

Vala, J.

2007-09-01

Diffusion in multi-component alloys can be characterized by the vacancy mechanism for substitutional components, by the existence of sources and sinks for vacancies and by the motion of atoms of interstitial components. The description of diffusive and massive phase transformation of a multi-component system is based on the thermodynamic extremal principle by Onsager; the finite thickness of the interface between both phases is respected. The resulting system of partial differential equations of evolution with integral terms for unknown mole fractions (and additional variables in case of non-ideal sources and sinks for vacancies), can be analyzed using the method of lines and the finite difference technique (or, alternatively, the finite element one) together with the semi-analytic and numerical integration formulae and with certain iteration procedure, making use of the spectral properties of linear operators. The original software code for the numerical evaluation of solutions of such systems, written in MATLAB, offers a chance to simulate various real processes of diffusional phase transformation. Some results for the (nearly) steady-state real processes in substitutional alloys have been published yet. The aim of this paper is to demonstrate that the same approach can handle both substitutional and interstitial components even in case of a general system of evolution.

The Evaluation and Research of Multi-Project Programs: Program Component Analysis.

ERIC Educational Resources Information Center

Baker, Eva L.

1977-01-01

It is difficult to base evaluations on concepts irrelevant to state policy making. Evaluation of a multiproject program requires both time and differentiation of method. Data from the California Early Childhood Program illustrate process variables for program component analysis, and research questions for intraprogram comparison. (CP)

[Absorption and metabolism of Chuanxiong Rhizoma decoction with multi-component sequential metabolism method].

PubMed

Liu, Yang; Luo, Zhi-Qiang; Lv, Bei-Ran; Zhao, Hai-Yu; Dong, Ling

2016-04-01

The multiple components in Chinese herbal medicines (CHMS) will experience complex absorption and metabolism before entering the blood system. Previous studies often lay emphasis on the components in blood. However, the dynamic and sequential absorption and metabolism process following multi-component oral administration has not been studied. In this study, the in situ closed-loop method combined with LC-MS techniques were employed to study the sequential process of Chuanxiong Rhizoma decoction (RCD). A total of 14 major components were identified in RCD. Among them, ferulic acid, senkyunolide J, senkyunolide I, senkyunolide F, senkyunolide G, and butylidenephthalide were detected in all of the samples, indicating that the six components could be absorbed into blood in prototype. Butylphthalide, E-ligustilide, Z-ligustilide, cnidilide, senkyunolide A and senkyunolide Q were not detected in all the samples, suggesting that the six components may not be absorbed or metabolized before entering the hepatic portal vein. Senkyunolide H could be metabolized by the liver, while senkyunolide M could be metabolized by both liver and intestinal flora. This study clearly demonstrated the changes in the absorption and metabolism process following multi-component oral administration of RCD, so as to convert the static multi-component absorption process into a comprehensive dynamic and continuous absorption and metabolism process. Copyright© by the Chinese Pharmaceutical Association.

Multi-scale diffuse interface modeling of multi-component two-phase flow with partial miscibility

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

Kou, Jisheng; Sun, Shuyu, E-mail: shuyu.sun@kaust.edu.sa; School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an 710049

2016-08-01

In this paper, we introduce a diffuse interface model to simulate multi-component two-phase flow with partial miscibility based on a realistic equation of state (e.g. Peng–Robinson equation of state). Because of partial miscibility, thermodynamic relations are used to model not only interfacial properties but also bulk properties, including density, composition, pressure, and realistic viscosity. As far as we know, this effort is the first time to use diffuse interface modeling based on equation of state for modeling of multi-component two-phase flow with partial miscibility. In numerical simulation, the key issue is to resolve the high contrast of scales from themore » microscopic interface composition to macroscale bulk fluid motion since the interface has a nanoscale thickness only. To efficiently solve this challenging problem, we develop a multi-scale simulation method. At the microscopic scale, we deduce a reduced interfacial equation under reasonable assumptions, and then we propose a formulation of capillary pressure, which is consistent with macroscale flow equations. Moreover, we show that Young–Laplace equation is an approximation of this capillarity formulation, and this formulation is also consistent with the concept of Tolman length, which is a correction of Young–Laplace equation. At the macroscopical scale, the interfaces are treated as discontinuous surfaces separating two phases of fluids. Our approach differs from conventional sharp-interface two-phase flow model in that we use the capillary pressure directly instead of a combination of surface tension and Young–Laplace equation because capillarity can be calculated from our proposed capillarity formulation. A compatible condition is also derived for the pressure in flow equations. Furthermore, based on the proposed capillarity formulation, we design an efficient numerical method for directly computing the capillary pressure between two fluids composed of multiple components. Finally

Stationary Wavelet-based Two-directional Two-dimensional Principal Component Analysis for EMG Signal Classification

NASA Astrophysics Data System (ADS)

Ji, Yi; Sun, Shanlin; Xie, Hong-Bo

2017-06-01

Discrete wavelet transform (WT) followed by principal component analysis (PCA) has been a powerful approach for the analysis of biomedical signals. Wavelet coefficients at various scales and channels were usually transformed into a one-dimensional array, causing issues such as the curse of dimensionality dilemma and small sample size problem. In addition, lack of time-shift invariance of WT coefficients can be modeled as noise and degrades the classifier performance. In this study, we present a stationary wavelet-based two-directional two-dimensional principal component analysis (SW2D2PCA) method for the efficient and effective extraction of essential feature information from signals. Time-invariant multi-scale matrices are constructed in the first step. The two-directional two-dimensional principal component analysis then operates on the multi-scale matrices to reduce the dimension, rather than vectors in conventional PCA. Results are presented from an experiment to classify eight hand motions using 4-channel electromyographic (EMG) signals recorded in healthy subjects and amputees, which illustrates the efficiency and effectiveness of the proposed method for biomedical signal analysis.

FE-XIII Infrared / FE-XIV Green Line Ratio Diagnostics (P55)

NASA Astrophysics Data System (ADS)

Srivastava, A. K.; et al.

2006-11-01

aks.astro.itbhu@gmail.com We consider the first 27-level atomic model of Fe XIII (5.9 < log Te < 6.4 K) to estimate its ground level populations, taking account of electron as well as proton collisional excitations and de-excitations, radiative cascades, radiative excitations and de-excitations. Radiative cascade is important but the effect of dilution factor is negligible at higher electron densities. The 3 P1-3P0 and 3P2-3P1 transitions in the ground configuration 3s2 3p2 of Fe XIII result in two forbidden coronal emission lines in the infrared region, namely 10747 Å and 10798 Å., while the 5303 Å green line is formed in the 3s2 3p 2 2 ground configuration of Fe XIV as a result of P3 / 2 - P1 / 2 magnetic dipole transition. The line-widths of appropriate pair of forbidden coronal emission lines observed simultaneously can be useful diagnostic tool to deduce temperature and non-thermal velocity in the large scale coronal structures using intensity ratios of the lines as the temperature signature, instead of assuming ion temperature to be equal to the electron temperature. Since the line intensity ratios IG5303/IIR10747 and IG5303/IIR10798 have very week density dependence, they are ideal monitors of temperature mapping in the solar corona.

Derivative component analysis for mass spectral serum proteomic profiles.

PubMed

Han, Henry

2014-01-01

As a promising way to transform medicine, mass spectrometry based proteomics technologies have seen a great progress in identifying disease biomarkers for clinical diagnosis and prognosis. However, there is a lack of effective feature selection methods that are able to capture essential data behaviors to achieve clinical level disease diagnosis. Moreover, it faces a challenge from data reproducibility, which means that no two independent studies have been found to produce same proteomic patterns. Such reproducibility issue causes the identified biomarker patterns to lose repeatability and prevents it from real clinical usage. In this work, we propose a novel machine-learning algorithm: derivative component analysis (DCA) for high-dimensional mass spectral proteomic profiles. As an implicit feature selection algorithm, derivative component analysis examines input proteomics data in a multi-resolution approach by seeking its derivatives to capture latent data characteristics and conduct de-noising. We further demonstrate DCA's advantages in disease diagnosis by viewing input proteomics data as a profile biomarker via integrating it with support vector machines to tackle the reproducibility issue, besides comparing it with state-of-the-art peers. Our results show that high-dimensional proteomics data are actually linearly separable under proposed derivative component analysis (DCA). As a novel multi-resolution feature selection algorithm, DCA not only overcomes the weakness of the traditional methods in subtle data behavior discovery, but also suggests an effective resolution to overcoming proteomics data's reproducibility problem and provides new techniques and insights in translational bioinformatics and machine learning. The DCA-based profile biomarker diagnosis makes clinical level diagnostic performances reproducible across different proteomic data, which is more robust and systematic than the existing biomarker discovery based diagnosis. Our findings demonstrate

A mesoscopic reaction rate model for shock initiation of multi-component PBX explosives.

PubMed

Liu, Y R; Duan, Z P; Zhang, Z Y; Ou, Z C; Huang, F L

2016-11-05

The primary goal of this research is to develop a three-term mesoscopic reaction rate model that consists of a hot-spot ignition, a low-pressure slow burning and a high-pressure fast reaction terms for shock initiation of multi-component Plastic Bonded Explosives (PBX). Thereinto, based on the DZK hot-spot model for a single-component PBX explosive, the hot-spot ignition term as well as its reaction rate is obtained through a "mixing rule" of the explosive components; new expressions for both the low-pressure slow burning term and the high-pressure fast reaction term are also obtained by establishing the relationships between the reaction rate of the multi-component PBX explosive and that of its explosive components, based on the low-pressure slow burning term and the high-pressure fast reaction term of a mesoscopic reaction rate model. Furthermore, for verification, the new reaction rate model is incorporated into the DYNA2D code to simulate numerically the shock initiation process of the PBXC03 and the PBXC10 multi-component PBX explosives, and the numerical results of the pressure histories at different Lagrange locations in explosive are found to be in good agreements with previous experimental data. Copyright © 2016 Elsevier B.V. All rights reserved.

Newly-recognized roles of factor XIII in thrombosis

PubMed Central

Byrnes, James R.; Wolberg, Alisa S.

2017-01-01

Arterial and venous thrombosis are major contributors to coagulation-associated morbidity and mortality. Greater understanding of mechanisms leading to thrombus formation and stability is expected to lead to improved treatment strategies. Factor XIII (FXIII) is a transglutaminase found in plasma and platelets. During thrombosis, activated FXIII crosslinks fibrin and promotes thrombus stability. Recent studies have provided new information about FXIII activity during coagulation and its effects on clot composition and function. These findings reveal newly-recognized roles for FXIII in thrombosis. Herein, we review published literature on FXIII biology and effects on fibrin structure and stability, epidemiologic data associating FXIII with thrombosis, and evidence from animal models indicating FXIII has an essential role in determining thrombus stability, composition, and size. PMID:27056150

Active region upflows. I. Multi-instrument observations

NASA Astrophysics Data System (ADS)

Vanninathan, K.; Madjarska, M. S.; Galsgaard, K.; Huang, Z.; Doyle, J. G.

2015-12-01

Context. We study upflows at the edges of active regions, called AR outflows, using multi-instrument observations. Aims: This study intends to provide the first direct observational evidence of whether chromospheric jets play an important role in furnishing mass that could sustain coronal upflows. The evolution of the photospheric magnetic field, associated with the footpoints of the upflow region and the plasma properties of active region upflows is investigated with the aim of providing information for benchmarking data-driven modelling of this solar feature. Methods: We spatially and temporally combine multi-instrument observations obtained with the Extreme-ultraviolet Imaging Spectrometer on board the Hinode, the Atmospheric Imaging Assembly and the Helioseismic Magnetic Imager instruments on board the Solar Dynamics Observatory and the Interferometric BI-dimensional Spectro-polarimeter installed at the National Solar Observatory, Sac Peak, to study the plasma parameters of the upflows and the impact of the chromosphere on active region upflows. Results: Our analysis shows that the studied active region upflow presents similarly to those studied previously, i.e. it displays blueshifted emission of 5-20 kms-1 in Fe xii and Fe xiii and its average electron density is 1.8 × 109 cm-3 at 1 MK. The time variation of the density is obtained showing no significant change (in a 3σ error). The plasma density along a single loop is calculated revealing a drop of 50% over a distance of ~20 000 km along the loop. We find a second velocity component in the blue wing of the Fe xii and Fe xiii lines at 105 kms-1 reported only once before. For the first time we study the time evolution of this component at high cadence and find that it is persistent during the whole observing period of 3.5 h with variations of only ±15 kms-1. We also, for the first time, study the evolution of the photospheric magnetic field at high cadence and find that magnetic flux diffusion is

Principal component and spatial correlation analysis of spectroscopic-imaging data in scanning probe microscopy.

PubMed

Jesse, Stephen; Kalinin, Sergei V

2009-02-25

An approach for the analysis of multi-dimensional, spectroscopic-imaging data based on principal component analysis (PCA) is explored. PCA selects and ranks relevant response components based on variance within the data. It is shown that for examples with small relative variations between spectra, the first few PCA components closely coincide with results obtained using model fitting, and this is achieved at rates approximately four orders of magnitude faster. For cases with strong response variations, PCA allows an effective approach to rapidly process, de-noise, and compress data. The prospects for PCA combined with correlation function analysis of component maps as a universal tool for data analysis and representation in microscopy are discussed.

Principal Component Analysis for Enhancement of Infrared Spectra Monitoring

NASA Astrophysics Data System (ADS)

Haney, Ricky Lance

The issue of air quality within the aircraft cabin is receiving increasing attention from both pilot and flight attendant unions. This is due to exposure events caused by poor air quality that in some cases may have contained toxic oil components due to bleed air that flows from outside the aircraft and then through the engines into the aircraft cabin. Significant short and long-term medical issues for aircraft crew have been attributed to exposure. The need for air quality monitoring is especially evident in the fact that currently within an aircraft there are no sensors to monitor the air quality and potentially harmful gas levels (detect-to-warn sensors), much less systems to monitor and purify the air (detect-to-treat sensors) within the aircraft cabin. The specific purpose of this research is to utilize a mathematical technique called principal component analysis (PCA) in conjunction with principal component regression (PCR) and proportionality constant calculations (PCC) to simplify complex, multi-component infrared (IR) spectra data sets into a reduced data set used for determination of the concentrations of the individual components. Use of PCA can significantly simplify data analysis as well as improve the ability to determine concentrations of individual target species in gas mixtures where significant band overlap occurs in the IR spectrum region. Application of this analytical numerical technique to IR spectrum analysis is important in improving performance of commercial sensors that airlines and aircraft manufacturers could potentially use in an aircraft cabin environment for multi-gas component monitoring. The approach of this research is two-fold, consisting of a PCA application to compare simulation and experimental results with the corresponding PCR and PCC to determine quantitatively the component concentrations within a mixture. The experimental data sets consist of both two and three component systems that could potentially be present as air

Multi-Step Deep Reactive Ion Etching Fabrication Process for Silicon-Based Terahertz Components

NASA Technical Reports Server (NTRS)

Reck, Theodore (Inventor); Perez, Jose Vicente Siles (Inventor); Lee, Choonsup (Inventor); Cooper, Ken B. (Inventor); Jung-Kubiak, Cecile (Inventor); Mehdi, Imran (Inventor); Chattopadhyay, Goutam (Inventor); Lin, Robert H. (Inventor); Peralta, Alejandro (Inventor)

2016-01-01

A multi-step silicon etching process has been developed to fabricate silicon-based terahertz (THz) waveguide components. This technique provides precise dimensional control across multiple etch depths with batch processing capabilities. Nonlinear and passive components such as mixers and multipliers waveguides, hybrids, OMTs and twists have been fabricated and integrated into a small silicon package. This fabrication technique enables a wafer-stacking architecture to provide ultra-compact multi-pixel receiver front-ends in the THz range.

Free factor XIII activation peptide (fAP-FXIII) is a regulator of factor XIII activity via factor XIII-B.

PubMed

Dodt, Johannes; Pasternack, Ralf; Seitz, Rainer; Volkers, Peter

2016-02-01

In a factor XIIIa (FXIIIa) generation assay with recombinant FXIII-A2 (rFXIII-A2 ) free FXIII activation peptide (fAP-FXII) prolonged the time to peak (TTP) but did not affect the area under the curve (AUC) or concentration at peak (CP). Addition of recombinant factorXIII-B2 (rFXIII-B2 ) restored the characteristics of the FXIIIa generation parameters (AUC, TTP and CP) to those observed for plasma FXIII (FXIII-A2 B2 ). FXIII-A2 B2 reconstituted from rFXIII-A2 and rFXIII-B2 showed a similar effect on AUC, TTP and CP in the presence of fAP-FXII as observed for plasma FXIII-A2 B2 , indicating a role for FXIII-B in this observation. An effect of fAP-FXIII on thrombin, the proteolytic activator of FXIII, was excluded by thrombin generation assays and clotting experiments. In a purified system, fAP-FXIII did not interfere with the FXIIIa activity development of thrombin-cleaved rFXIII-A2 (rFXIII-A2 ') also excluding direct inhibition of FXIIIa. However, FXIIIa activity development of FXIII-A2 'B2 was inhibited in a concentration-dependent manner by fAP-FXIII, indicating that an interaction between AP-FXIII and FXIII-B2 contributes to the overall stability of FXIII-A2 'B2 . In addition to its well-known role, FXIII-B also contributes to FXIII-A2 B2 stability or dissociation depending on fAP-FXIII and calcium concentrations. © 2015 John Wiley & Sons Ltd.

Seven novel mutations in the factor XIII A-subunit gene causing hereditary factor XIII deficiency in 10 unrelated families.

PubMed

Vysokovsky, A; Saxena, R; Landau, M; Zivelin, A; Eskaraev, R; Rosenberg, N; Seligsohn, U; Inbal, A

2004-10-01

Hereditary factor (F)XIII deficiency is a rare bleeding disorder mostly due to mutations in FXIII A subunit. We studied the molecular basis of FXIII deficiency in patients from 10 unrelated families originating from Israel, India and Tunisia. Exons 2-15 of genomic DNA consisting of coding regions and intron/exon boundaries were amplified and sequenced. Structural analysis of the mutations was undertaken by computer modeling. Seven novel mutations were identified in the FXIIIA gene. The propositus from the Ethiopian-Jewish family was found to be a compound heterozygote for two novel mutations: a 10-bp deletion in exon 12 at nucleotides 1652-1661 (followed by 22 altered amino acids and termination codon) and Ala318Val mutation. The propositus of the Tunisian family was homozygous for C insertion after nucleotide 863 within a stretch of six cytosines of exon 7. This insertion results in generation of eight altered amino acids followed by a termination codon downstream. The propositus from Indian-Jewish origin was found to be homozygous for G to T substitution at IVS 11 [+1] resulting in skipping of exons 10 and 11. In addition to the Ala318Val mutation, three of the novel mutations identified are missense mutations: Arg260Leu, Thr398Asn and Gly210Arg each occurring in a homozygous state in an Israeli-Arab and two Indian families, respectively. Structure-function correlation analysis by computer modeling of the new missense mutations predicted that Gly210Arg will cause protein misfolding, Ala318Val and Thr398Asn will interfere with the catalytic process or protein stability, and Arg260Leu will impair dimerization.

40 CFR 59.506 - How do I demonstrate compliance if I manufacture multi-component kits?

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 5 2010-07-01 2010-07-01 false How do I demonstrate compliance if I manufacture multi-component kits? 59.506 Section 59.506 Protection of Environment ENVIRONMENTAL PROTECTION... § 59.506 How do I demonstrate compliance if I manufacture multi-component kits? (a) If you manufacture...

Modal Identification in an Automotive Multi-Component System Using HS 3D-DIC

PubMed Central

López-Alba, Elías; Felipe-Sesé, Luis; Díaz, Francisco A.

2018-01-01

The modal characterization of automotive lighting systems becomes difficult using sensors due to the light weight of the elements which compose the component as well as the intricate access to allocate them. In experimental modal analysis, high speed 3D digital image correlation (HS 3D-DIC) is attracting the attention since it provides full-field contactless measurements of 3D displacements as main advantage over other techniques. Different methodologies have been published that perform modal identification, i.e., natural frequencies, damping ratios, and mode shapes using the full-field information. In this work, experimental modal analysis has been performed in a multi-component automotive lighting system using HS 3D-DIC. Base motion excitation was applied to simulate operating conditions. A recently validated methodology has been employed for modal identification using transmissibility functions, i.e., the transfer functions from base motion tests. Results make it possible to identify local and global behavior of the different elements of injected polymeric and metallic materials. PMID:29401725

Multi-InDel Analysis for Ancestry Inference of Sub-Populations in China

PubMed Central

Sun, Kuan; Ye, Yi; Luo, Tao; Hou, Yiping

2016-01-01

Ancestry inference is of great interest in diverse areas of scientific researches, including the forensic biology, medical genetics and anthropology. Various methods have been published for distinguishing populations. However, few reports refer to sub-populations (like ethnic groups) within Asian populations for the limitation of markers. Several InDel loci located very tightly in physical positions were treated as one marker by us, which is multi-InDel. The multi-InDel shows potential as Ancestry Inference Marker (AIM). In this study, we performed a genome-wide scan for multi-InDels as AIM. After examining the FST distributions in the 1000 Genomes Database, 12 candidates were selected and validated for eastern Asian populations. A multiplexed assay was developed as a panel to genotype 12 multi-InDel markers simultaneously. Ancestry component analysis with STRUCTURE and principal component analysis (PCA) were employed to estimate its capability for ancestry inference. Furthermore, ancestry assignments of trial individuals were conducted. It proved to be very effective when 210 samples from Han and Tibetan individuals in China were tested. The panel consisting of multi-InDel markers exhibited considerable potency in ancestry inference, and was suggested to be applied in forensic practices and genetic population studies. PMID:28004788

Multi-component ground motion response spectra for coupled horizontal, vertical, angular accelerations, and tilt

USGS Publications Warehouse

Kalkan, E.; Graizer, V.

2007-01-01

Rotational and vertical components of ground motion are almost always ignored in design or in the assessment of structures despite the fact that vertical motion can be twice as much as the horizontal motion and may exceed 2g level, and rotational excitation may reach few degrees in the proximity of fault rupture. Coupling of different components of ground excitation may significantly amplify the seismic demand by introducing additional lateral forces and enhanced P-?? effects. In this paper, a governing equation of motion is postulated to compute the response of a SDOF oscillator under a multi-component excitation. The expanded equation includes secondary P-?? components associated with the combined impacts of tilt and vertical excitations in addition to the inertial forcing terms due to the angular and translational accelerations. The elastic and inelastic spectral ordinates traditionally generated considering the uniaxial input motion are compared at the end with the multi-component response spectra of coupled horizontal, vertical and tilting motions. The proposed multi-component response spectrum reflects kinematic characteristics of the ground motion that are not identifiable by the conventional spectrum itself, at least for the near-fault region where high intensity vertical shaking and rotational excitation are likely to occur.

Intrinsic thermodynamics of ethoxzolamide inhibitor binding to human carbonic anhydrase XIII

PubMed Central

2012-01-01

Background Human carbonic anhydrases (CAs) play crucial role in various physiological processes including carbon dioxide and hydrocarbon transport, acid homeostasis, biosynthetic reactions, and various pathological processes, especially tumor progression. Therefore, CAs are interesting targets for pharmaceutical research. The structure-activity relationships (SAR) of designed inhibitors require detailed thermodynamic and structural characterization of the binding reaction. Unfortunately, most publications list only the observed thermodynamic parameters that are significantly different from the intrinsic parameters. However, only intrinsic parameters could be used in the rational design and SAR of the novel compounds. Results Intrinsic binding parameters for several inhibitors, including ethoxzolamide, trifluoromethanesulfonamide, and acetazolamide, binding to recombinant human CA XIII isozyme were determined. The parameters were the intrinsic Gibbs free energy, enthalpy, entropy, and the heat capacity. They were determined by titration calorimetry and thermal shift assay in a wide pH and temperature range to dissect all linked protonation reaction contributions. Conclusions Precise determination of the inhibitor binding thermodynamics enabled correct intrinsic affinity and enthalpy ranking of the compounds and provided the means for SAR analysis of other rationally designed CA inhibitors. PMID:22676044

Quantitative analysis of multi-component gas mixture based on AOTF-NIR spectroscopy

NASA Astrophysics Data System (ADS)

Hao, Huimin; Zhang, Yong; Liu, Junhua

2007-12-01

Near Infrared (NIR) spectroscopy analysis technology has attracted many eyes and has wide application in many domains in recent years because of its remarkable advantages. But the NIR spectrometer can only be used for liquid and solid analysis by now. In this paper, a new quantitative analysis method of gas mixture by using new generation NIR spectrometer is explored. To collect the NIR spectra of gas mixtures, a vacuumable gas cell was designed and assembled to Luminar 5030-731 Acousto-Optic Tunable Filter (AOTF)-NIR spectrometer. Standard gas samples of methane (CH 4), ethane (C IIH 6) and propane (C 3H 8) are diluted with super pure nitrogen via precision volumetric gas flow controllers to obtain gas mixture samples of different concentrations dynamically. The gas mixtures were injected into the gas cell and the spectra of wavelength between 1100nm-2300nm were collected. The feature components extracted from gas mixture spectra by using Partial Least Squares (PLS) were used as the inputs of the Support Vector Regress Machine (SVR) to establish the quantitative analysis model. The effectiveness of the model is tested by the samples of predicting set. The prediction Root Mean Square Error (RMSE) of CH 4, C IIH 6 and C 3H 8 is respectively 1.27%, 0.89%, and 1.20% when the concentrations of component gas are over 0.5%. It shows that the AOTF-NIR spectrometer with gas cell can be used for gas mixture analysis. PLS combining with SVR has a good performance in NIR spectroscopy analysis. This paper provides the bases for extending the application of NIR spectroscopy analysis to gas detection.

Development of multi-component explosive lenses for arbitrary phase velocity generation

NASA Astrophysics Data System (ADS)

Loiseau, Jason; Huneault, Justin; Petel, Oren; Goroshin, Sam; Frost, David; Higgins, Andrew; Zhang, Fan

2013-06-01

The combination of explosives with different detonation velocities and lens-like geometric shaping is a well-established technique for producing structured detonation waves. This technique can be extended to produce nearly arbitrary detonation phase velocities for the purposes of sequentially imploding pressurized tubes or driving Mach disks through high-density metalized explosives. The current study presents the experimental development of accelerating, multi-component lenses designed using simple geometric optics and idealized front curvature. The fast explosive component is either Composition C4 (VOD = 8 km/s) or Primasheet 1000 (VOD = 7 km/s), while the slow component varies from heavily amine-diluted nitromethane (amine mass fraction exceeding 20%) to packed metal and glass particle beds wetted with amine-sensitized nitromethane. The applicability of the geometric optic analog to such highly heterogeneous explosives is also investigated. The multi-layered lens technique is further developed as a means of generating a directed mass and momentum flux of metal particles via Mach-disk formation and jetting in circular and oval planar lenses.

Extension of a System Level Tool for Component Level Analysis

NASA Technical Reports Server (NTRS)

Majumdar, Alok; Schallhorn, Paul

2002-01-01

This paper presents an extension of a numerical algorithm for network flow analysis code to perform multi-dimensional flow calculation. The one dimensional momentum equation in network flow analysis code has been extended to include momentum transport due to shear stress and transverse component of velocity. Both laminar and turbulent flows are considered. Turbulence is represented by Prandtl's mixing length hypothesis. Three classical examples (Poiseuille flow, Couette flow and shear driven flow in a rectangular cavity) are presented as benchmark for the verification of the numerical scheme.

Extension of a System Level Tool for Component Level Analysis

NASA Technical Reports Server (NTRS)

Majumdar, Alok; Schallhorn, Paul; McConnaughey, Paul K. (Technical Monitor)

2001-01-01

This paper presents an extension of a numerical algorithm for network flow analysis code to perform multi-dimensional flow calculation. The one dimensional momentum equation in network flow analysis code has been extended to include momentum transport due to shear stress and transverse component of velocity. Both laminar and turbulent flows are considered. Turbulence is represented by Prandtl's mixing length hypothesis. Three classical examples (Poiseuille flow, Couette flow, and shear driven flow in a rectangular cavity) are presented as benchmark for the verification of the numerical scheme.

Porous multi-component material for the capture and separation of species of interest

DOEpatents

Addleman, Raymond S.; Chouyyok, Wilaiwan; Li, Xiaohong S.; Cinson, Anthony D.; Gerasimenko, Aleksandr A

2016-06-21

A method and porous multi-component material for the capture, separation or chemical reaction of a species of interest is disclosed. The porous multi-component material includes a substrate and a composite thin film. The composite thin film is formed by combining a porous polymer with a nanostructured material. The nanostructured material may include a surface chemistry for the capture of chemicals or particles. The composite thin film is coupled to the support or device surface. The method and material provides a simple, fast, and chemically and physically benign way to integrate nanostructured materials into devices while preserving their chemical activity.

Structural and Thermodynamic Factors of Suppressed Interdiffusion Kinetics in Multi-component High-entropy Materials

PubMed Central

Chang, Shou-Yi; Li, Chen-En; Huang, Yi-Chung; Hsu, Hsun-Feng; Yeh, Jien-Wei; Lin, Su-Jien

2014-01-01

We report multi-component high-entropy materials as extraordinarily robust diffusion barriers and clarify the highly suppressed interdiffusion kinetics in the multi-component materials from structural and thermodynamic perspectives. The failures of six alloy barriers with different numbers of elements, from unitary Ti to senary TiTaCrZrAlRu, against the interdiffusion of Cu and Si were characterized, and experimental results indicated that, with more elements incorporated, the failure temperature of the barriers increased from 550 to 900°C. The activation energy of Cu diffusion through the alloy barriers was determined to increase from 110 to 163 kJ/mole. Mechanistic analyses suggest that, structurally, severe lattice distortion strains and a high packing density caused by different atom sizes, and, thermodynamically, a strengthened cohesion provide a total increase of 55 kJ/mole in the activation energy of substitutional Cu diffusion, and are believed to be the dominant factors of suppressed interdiffusion kinetics through the multi-component barrier materials. PMID:24561911

Design for robustness of unique, multi-component engineering systems

NASA Astrophysics Data System (ADS)

Shelton, Kenneth A.

2007-12-01

The purpose of this research is to advance the science of conceptual designing for robustness in unique, multi-component engineering systems. Robustness is herein defined as the ability of an engineering system to operate within a desired performance range even if the actual configuration has differences from specifications within specified tolerances. These differences are caused by three sources, namely manufacturing errors, system degradation (operational wear and tear), and parts availability. Unique, multi-component engineering systems are defined as systems produced in unique or very small production numbers. They typically have design and manufacturing costs on the order of billions of dollars, and have multiple, competing performance objectives. Design time for these systems must be minimized due to competition, high manpower costs, long manufacturing times, technology obsolescence, and limited available manpower expertise. Most importantly, design mistakes cannot be easily corrected after the systems are operational. For all these reasons, robustness of these systems is absolutely critical. This research examines the space satellite industry in particular. Although inherent robustness assurance is absolutely critical, it is difficult to achieve in practice. The current state of the art for robustness in the industry is to overdesign components and subsystems with redundancy and margin. The shortfall is that it is not known if the added margins were either necessary or sufficient given the risk management preferences of the designer or engineering system customer. To address this shortcoming, new assessment criteria to evaluate robustness in design concepts have been developed. The criteria are comprised of the "Value Distance", addressing manufacturing errors and system degradation, and "Component Distance", addressing parts availability. They are based on an evolutionary computation format that uses a string of alleles to describe the components in the

Correlation between thyroidal and peripheral blood total T cells, CD8+ T cells, and CD8+ T- regulatory cells and T-cell reactivity to calsequestrin and collagen XIII in patients with Graves' ophthalmopathy.

PubMed

Al-Ansari, Farah; Lahooti, Hooshang; Stokes, Leanne; Edirimanne, Senarath; Wall, Jack

2018-05-22

Purpose/aim of the study: Graves' ophthalmopathy (GO) is closely related to the thyroid autoimmune disorder Graves' disease. Previous studies have suggested roles for thyroidal CD8 +  T cells and autoimmunity against calsequestrin-1 (CASQ)-1 in the link between thyroidal and orbital autoimmune reactions in GO. A role for autoimmunity against CollXIII has also been suggested. In this study, we aimed to investigate correlations between some thyroidal and peripheral blood T-cell subsets and thyroidal T-cell reactivity against CASQ1 and CollXIII in patients with GO. Fresh thyroid tissues were processed by enzyme digestion and density gradient to isolate mononuclear cells (MNCs). Peripheral blood MNCs were also isolated using density gradient. Flow-cytometric analysis was used to identify the various T-cell subsets. T -cell reactivity to CASQ1 and CollXIII was measured by a 5-day culture of the MNCs and BrdU uptake method. We found a positive correlation between thyroidal CD8 +  T cells and CD8 +  T-regulatory (T-reg) cells in patients with GO. Thyroidal T cells from two out of the three patients with GO tested (66.7%) showed a positive response to CASQ1, while thyroidal T cells from none of the six Graves' Disease patients without ophthalmopathy (GD) tested showed a positive response to this antigen. Thyroidal T cells from these patient groups however, showed no significant differences in their response to CollXIII. Our observations provide further evidence for a possible role of thyroidal CD8 +  T cells, CD8 +  T-reg cells and the autoantigen CASQ1 in the link between thyroidal and orbital autoimmune reactions of GO.

Design of a multi-channel free space optical interconnection component

NASA Astrophysics Data System (ADS)

Jia, Da-Gong; Zhang, Pei-Song; Jing, Wen-Cai; Tan, Jun; Zhang, Hong-Xia; Zhang, Yi-Mo

2008-11-01

A multi-channel free space optical interconnection component, fiber optic rotary joint, was designed using a Dove prism. When the Dove prism is rotated an angle of α around the longitudinal axis, the image rotates an angle of 2 α. The optical interconnection component consists of the signal transmission system, Dove prim and driving mechanism. The planetary gears are used to achieve the speed ratio of 2:1 between the total optical interconnection component and the Dove prism. The C-lenses are employed to couple different optical signals in the signal transmission system. The coupling loss between the receiving fiber of stationary part and the transmitting fiber of rotary part is measured.

A component analysis of positive behaviour support plans.

PubMed

McClean, Brian; Grey, Ian

2012-09-01

Positive behaviour support (PBS) emphasises multi-component interventions by natural intervention agents to help people overcome challenging behaviours. This paper investigates which components are most effective and which factors might mediate effectiveness. Sixty-one staff working with individuals with intellectual disability and challenging behaviours completed longitudinal competency-based training in PBS. Each staff participant conducted a functional assessment and developed and implemented a PBS plan for one prioritised individual. A total of 1,272 interventions were available for analysis. Measures of challenging behaviour were taken at baseline, after 6 months, and at an average of 26 months follow-up. There was a significant reduction in the frequency, management difficulty, and episodic severity of challenging behaviour over the duration of the study. Escape was identified by staff as the most common function, accounting for 77% of challenging behaviours. The most commonly implemented components of intervention were setting event changes and quality-of-life-based interventions. Only treatment acceptability was found to be related to decreases in behavioural frequency. No single intervention component was found to have a greater association with reductions in challenging behaviour.

Raman spectroscopic study of hydrogen ordered ice XIII and of its reversible phase transition to disordered ice V.

PubMed

Salzmann, Christoph G; Hallbrucker, Andreas; Finney, John L; Mayer, Erwin

2006-07-14

Raman spectra of recovered ordered H(2)O (D(2)O) ice XIII doped with 0.01 M HCl (DCl) recorded in vacuo at 80 K are reported in the range 3600-200 cm(-1). The bands are assigned to the various types of modes on the basis of isotope ratios. On thermal cycling between 80 and 120 K, the reversible phase transition to disordered ice V is observed. The remarkable effect of HCl (DCl) on orientational ordering in ice V and its phase transition to ordered ice XIII, first reported in a powder neutron diffraction study of DCl doped D(2)O ice V (C. G. Salzmann, P. G. Radaelli, A. Hallbrucker, E. Mayer, J. L. Finney, Science, 2006, 311, 1758), is demonstrated by Raman spectroscopy and discussed. The dopants KOH and HF have only a minor effect on hydrogen ordering in ice V, as shown by the Raman spectra.

Numerical simulation of machining distortions on a forged aerospace component following a one and a multi-step approaches

NASA Astrophysics Data System (ADS)

Prete, Antonio Del; Franchi, Rodolfo; Antermite, Fabrizio; Donatiello, Iolanda

2018-05-01

Residual stresses appear in a component as a consequence of thermo-mechanical processes (e.g. ring rolling process) casting and heat treatments. When machining these kinds of components, distortions arise due to the redistribution of residual stresses due to the foregoing process history inside the material. If distortions are excessive, they can lead to a large number of scrap parts. Since dimensional accuracy can affect directly the engines efficiency, the dimensional control for aerospace components is a non-trivial issue. In this paper, the problem related to the distortions of large thin walled aeroengines components in nickel superalloys has been addressed. In order to estimate distortions on inner diameters after internal turning operations, a 3D Finite Element Method (FEM) analysis has been developed on a real industrial test case. All the process history, has been taken into account by developing FEM models of ring rolling process and heat treatments. Three different strategies of ring rolling process have been studied and the combination of related parameters which allows to obtain the best dimensional accuracy has been found. Furthermore, grain size evolution and recrystallization phenomena during manufacturing process has been numerically investigated using a semi empirical Johnson-Mehl-Avrami-Kohnogorov (JMAK) model. The volume subtractions have been simulated by boolean trimming: a one step and a multi step analysis have been performed. The multi-step procedure has allowed to choose the best material removal sequence in order to reduce machining distortions.

Multilevel Dynamic Generalized Structured Component Analysis for Brain Connectivity Analysis in Functional Neuroimaging Data.

PubMed

Jung, Kwanghee; Takane, Yoshio; Hwang, Heungsun; Woodward, Todd S

2016-06-01

We extend dynamic generalized structured component analysis (GSCA) to enhance its data-analytic capability in structural equation modeling of multi-subject time series data. Time series data of multiple subjects are typically hierarchically structured, where time points are nested within subjects who are in turn nested within a group. The proposed approach, named multilevel dynamic GSCA, accommodates the nested structure in time series data. Explicitly taking the nested structure into account, the proposed method allows investigating subject-wise variability of the loadings and path coefficients by looking at the variance estimates of the corresponding random effects, as well as fixed loadings between observed and latent variables and fixed path coefficients between latent variables. We demonstrate the effectiveness of the proposed approach by applying the method to the multi-subject functional neuroimaging data for brain connectivity analysis, where time series data-level measurements are nested within subjects.

On-line dynamic monitoring automotive exhausts: using BP-ANN for distinguishing multi-components

NASA Astrophysics Data System (ADS)

Zhao, Yudi; Wei, Ruyi; Liu, Xuebin

2017-10-01

Remote sensing-Fourier Transform infrared spectroscopy (RS-FTIR) is one of the most important technologies in atmospheric pollutant monitoring. It is very appropriate for on-line dynamic remote sensing monitoring of air pollutants, especially for the automotive exhausts. However, their absorption spectra are often seriously overlapped in the atmospheric infrared window bands, i.e. MWIR (3 5μm). Artificial Neural Network (ANN) is an algorithm based on the theory of the biological neural network, which simplifies the partial differential equation with complex construction. For its preferable performance in nonlinear mapping and fitting, in this paper we utilize Back Propagation-Artificial Neural Network (BP-ANN) to quantitatively analyze the concentrations of four typical industrial automotive exhausts, including CO, NO, NO2 and SO2. We extracted the original data of these automotive exhausts from the HITRAN database, most of which virtually overlapped, and established a mixed multi-component simulation environment. Based on Beer-Lambert Law, concentrations can be retrieved from the absorbance of spectra. Parameters including learning rate, momentum factor, the number of hidden nodes and iterations were obtained when the BP network was trained with 80 groups of input data. By improving these parameters, the network can be optimized to produce necessarily higher precision for the retrieved concentrations. This BP-ANN method proves to be an effective and promising algorithm on dealing with multi-components analysis of automotive exhausts.

Evidence for enhanced multi-component behaviour in Tourette syndrome - an EEG study.

PubMed

Brandt, Valerie C; Stock, Ann-Kathrin; Münchau, Alexander; Beste, Christian

2017-08-10

Evidence suggests that Tourette syndrome is characterized by an increase in dopamine transmission and structural as well as functional changes in fronto-striatal circuits that might lead to enhanced multi-component behaviour integration. Behavioural and neurophysiological data regarding multi-component behaviour was collected from 15 patients with Tourette syndrome (mean age = 30.40 ± 11.10) and 15 healthy controls (27.07 ± 5.44), using the stop-change task. In this task, participants are asked to sometimes withhold responses to a Go stimulus (stop cue) and change hands to respond to an alternative Go stimulus (change cue). Different onset asynchronies between stop and change cues were implemented (0 and 300 ms) in order to vary task difficulty. Tourette patients responded more accurately than healthy controls when there was no delay between stop and change stimulus, while there was no difference in the 300 ms delay condition. This performance advantage was reflected in a smaller P3 event related potential. Enhanced multi-component behaviour in Tourette syndrome is likely based on an enhanced ability to integrate information from multiple sources and translate it into an appropriate response sequence. This may be a consequence of chronic tic control in these patients, or a known fronto-striatal networks hyperconnectivity in Tourette syndrome.

Improved Cook-off Modeling of Multi-component Cast Explosives

NASA Astrophysics Data System (ADS)

Nichols, Albert

2017-06-01

In order to understand the hazards associated with energetic materials, it is important to understand their behavior in adverse thermal environments. These processes have been relatively well understood for solid explosives, however, the same cannot be said for multi-component melt-cast explosives. Here we describe the continued development of ALE3D, a coupled thermal/chemical/mechanical code, to improve its description of fluid explosives. The improved physics models include: 1) Chemical potential driven species segregation. This model allows us to model the complex flow fields associated with the melting and decomposing Comp-B, where the denser RDX tends to settle and the decomposing gasses rise, 2) Automatically scaled stream-wise diffusion model for thermal, species, and momentum diffusion. These models add sufficient numerical diffusion in the direction of flow to maintain numerical stability when the system is under resolved, as occurs for large systems. And 3) a slurry viscosity model, required to properly define the flow characteristics of the multi-component fluidized system. These models will be demonstrated on a simple Comp-B system. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under contract DE-AC52-07NA27344.

A Component Analysis of Positive Behaviour Support Plans

ERIC Educational Resources Information Center

McClean, Brian; Grey, Ian

2012-01-01

Background: Positive behaviour support (PBS) emphasises multi-component interventions by natural intervention agents to help people overcome challenging behaviours. This paper investigates which components are most effective and which factors might mediate effectiveness. Method: Sixty-one staff working with individuals with intellectual disability…

In-situ AFM measurement of single fibrin fiber stiffness before and after addition of Factor XIII

NASA Astrophysics Data System (ADS)

Houser, John; O'Brien, E. Timothy; Lord, Susan T.; Superfine, Richard; Falvo, Michael R.

2008-10-01

Fibrin fibers are the main structural component of blood clots. Ligation of fibrin by native Factor XIII (FXIII) serves to fine tune the mechanical properties of the clot. Mechanical alteration is important because a clot must be stiff enough to resist forces from blood flow but compliant enough to prevent embolism (fracture). Cone and Plate measurements of fibrin gels, which represent the vast majority of mechanical measurements on fibrin, show that FXIII increases clot stiffness. More recently, measurements on individual fibrin fibers show that they exhibit remarkable extensibility, breaking at strains up to 300%. As of yet, the origin of this extensibility is not fully understood. The different responses of ligated and unligated fibrin fibers can give us clues as to it's mechanism of extension. We use a combined fluorescence/atomic force microscope to stretch individual, isolated, fibrin fibers and then compare force extension curves of the same fiber before and after addition of FXIII. We found up to a 3.5-fold increase in fiber stiffness after addition of FXIII. We also show stiffening of individual fibrin fibers after crosslinking by gluteraldehyde.

Multi-component intrinsic brain activities as a safe, alternative to cortical stimulation for sensori-motor mapping in neurosurgery.

PubMed

Neshige, Shuichiro; Matsuhashi, Masao; Kobayashi, Katsuya; Sakurai, Takeyo; Shimotake, Akihiro; Hitomi, Takefumi; Kikuchi, Takayuki; Yoshida, Kazumichi; Kunieda, Takeharu; Matsumoto, Riki; Takahashi, Ryosuke; Miyamoto, Susumu; Maruyama, Hirofumi; Matsumoto, Masayasu; Ikeda, Akio

2018-06-18

To assess the feasibility of multi-component electrocorticography (ECoG)-based mapping using "wide-spectrum, intrinsic-brain activities" for identifying the primary sensori-motor area (S1-M1) by comparing that using electrical cortical stimulation (ECS). We evaluated 14 epilepsy patients with 1514 subdural electrodes implantation covering the perirolandic cortices at Kyoto University Hospital between 2011 and 2016. We performed multi-component, ECoG-based mapping (band-pass filter, 0.016-300/600 Hz) involving combined analyses of the single components: movement-related cortical potential (<0.5-1 Hz), event-related synchronization (76-200 Hz), and event-related de-synchronization (8-24 Hz) to identify the S1-M1. The feasibility of multi-component mapping was assessed through comparisons with single-component mapping and ECS. Among 54 functional areas evaluation, ECoG-based maps showed significantly higher rate of localization concordances with ECS maps when the three single-component maps were consistent than when those were inconsistent with each other (p < 0.001 in motor, and p = 0.02 in sensory mappings). Multi-component mapping revealed high sensitivity (89-90%) and specificity (94-97%) as compared with ECS. Wide-spectrum, multi-component ECoG-based mapping is feasible, having high sensitivity/specificity relative to ECS. This safe (non-stimulus) mapping strategy, alternative to ECS, would allow clinicians to rule in/out the possibility of brain function prior to resection surgery. Copyright © 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Reverse-time migration for subsurface imaging using single- and multi- frequency components

NASA Astrophysics Data System (ADS)

Ha, J.; Kim, Y.; Kim, S.; Chung, W.; Shin, S.; Lee, D.

2017-12-01

Reverse-time migration is a seismic data processing method for obtaining accurate subsurface structure images from seismic data. This method has been applied to obtain more precise complex geological structure information, including steep dips, by considering wave propagation characteristics based on two-way traveltime. Recently, various studies have reported the characteristics of acquired datasets from different types of media. In particular, because real subsurface media is comprised of various types of structures, seismic data represent various responses. Among them, frequency characteristics can be used as an important indicator for analyzing wave propagation in subsurface structures. All frequency components are utilized in conventional reverse-time migration, but analyzing each component is required because they contain inherent seismic response characteristics. In this study, we propose a reverse-time migration method that utilizes single- and multi- frequency components for analyzing subsurface imaging. We performed a spectral decomposition to utilize the characteristics of non-stationary seismic data. We propose two types of imaging conditions, in which decomposed signals are applied in complex and envelope traces. The SEG/EAGE Overthrust model was used to demonstrate the proposed method, and the 1st derivative Gaussian function with a 10 Hz cutoff was used as the source signature. The results were more accurate and stable when relatively lower frequency components in the effective frequency range were used. By combining the gradient obtained from various frequency components, we confirmed that the results are clearer than the conventional method using all frequency components. Also, further study is required to effectively combine the multi-frequency components.

Multi-component intermetallic electrodes for lithium batteries

DOEpatents

Thackeray, Michael M; Trahey, Lynn; Vaughey, John T

2015-03-10

Multi-component intermetallic negative electrodes prepared by electrochemical deposition for non-aqueous lithium cells and batteries are disclosed. More specifically, the invention relates to composite intermetallic electrodes comprising two or more compounds containing metallic or metaloid elements, at least one element of which can react with lithium to form binary, ternary, quaternary or higher order compounds, these compounds being in combination with one or more other metals that are essentially inactive toward lithium and act predominantly, but not necessarily exclusively, to the electronic conductivity of, and as current collection agent for, the electrode. The invention relates more specifically to negative electrode materials that provide an operating potential between 0.05 and 2.0 V vs. metallic lithium.

An uncontrolled trial of multi-component care for first-episode psychosis: Effects on social cognition.

PubMed

Breitborde, Nicholas J K; Moe, Aubrey M; Woolverton, Cindy; Harrison-Monroe, Patricia; Bell, Emily K

2018-06-01

Growing evidence suggests that specialized, multi-component treatment programmes produce improvements in numerous outcomes among individuals with first-episode psychosis. However, these programmes often lack interventions specifically designed to address deficits in social cognition. This raises questions about the effectiveness of such programmes in addressing deficits in social cognition that accompany psychotic disorders. We investigated the effect of participation in a multi-component treatment programme on social cognition among 71 individuals with first-episode psychosis. Participants experienced gains in emotion processing, social knowledge, social perception and theory of mind. However, after controlling for multiple comparisons, these improvements were limited to theory of mind and recognition of social cues in low emotion interactions. Although our findings should be interpreted cautiously, they raise the possibility that individuals participating in multi-component treatment programmes for first-episode psychosis without interventions specifically targeting social cognition may still experience gains in social cognition. © 2017 John Wiley & Sons Australia, Ltd.

A systematic study on the influencing parameters and improvement of quantitative analysis of multi-component with single marker method using notoginseng as research subject.

PubMed

Wang, Chao-Qun; Jia, Xiu-Hong; Zhu, Shu; Komatsu, Katsuko; Wang, Xuan; Cai, Shao-Qing

2015-03-01

A new quantitative analysis of multi-component with single marker (QAMS) method for 11 saponins (ginsenosides Rg1, Rb1, Rg2, Rh1, Rf, Re and Rd; notoginsenosides R1, R4, Fa and K) in notoginseng was established, when 6 of these saponins were individually used as internal referring substances to investigate the influences of chemical structure, concentrations of quantitative components, and purities of the standard substances on the accuracy of the QAMS method. The results showed that the concentration of the analyte in sample solution was the major influencing parameter, whereas the other parameters had minimal influence on the accuracy of the QAMS method. A new method for calculating the relative correction factors by linear regression was established (linear regression method), which demonstrated to decrease standard method differences of the QAMS method from 1.20%±0.02% - 23.29%±3.23% to 0.10%±0.09% - 8.84%±2.85% in comparison with the previous method. And the differences between external standard method and the QAMS method using relative correction factors calculated by linear regression method were below 5% in the quantitative determination of Rg1, Re, R1, Rd and Fa in 24 notoginseng samples and Rb1 in 21 notoginseng samples. And the differences were mostly below 10% in the quantitative determination of Rf, Rg2, R4 and N-K (the differences of these 4 constituents bigger because their contents lower) in all the 24 notoginseng samples. The results indicated that the contents assayed by the new QAMS method could be considered as accurate as those assayed by external standard method. In addition, a method for determining applicable concentration ranges of the quantitative components assayed by QAMS method was established for the first time, which could ensure its high accuracy and could be applied to QAMS methods of other TCMs. The present study demonstrated the practicability of the application of the QAMS method for the quantitative analysis of multi-component

Insight into the heterogeneous adsorption of humic acid fluorescent components on multi-walled carbon nanotubes by excitation-emission matrix and parallel factor analysis.

PubMed

Yang, Chenghu; Liu, Yangzhi; Cen, Qiulin; Zhu, Yaxian; Zhang, Yong

2018-02-01

The heterogeneous adsorption behavior of commercial humic acid (HA) on pristine and functionalized multi-walled carbon nanotubes (MWCNTs) was investigated by fluorescence excitation-emission matrix and parallel factor (EEM- PARAFAC) analysis. The kinetics, isotherms, thermodynamics and mechanisms of adsorption of HA fluorescent components onto MWCNTs were the focus of the present study. Three humic-like fluorescent components were distinguished, including one carboxylic-like fluorophore C1 (λ ex /λ em = (250, 310) nm/428nm), and two phenolic-like fluorophores, C2 (λ ex /λ em = (300, 460) nm/552nm) and C3 (λ ex /λ em = (270, 375) nm/520nm). The Lagergren pseudo-second-order model can be used to describe the adsorption kinetics of the HA fluorescent components. In addition, both the Freundlich and Langmuir models can be suitably employed to describe the adsorption of the HA fluorescent components onto MWCNTs with significantly high correlation coefficients (R 2 > 0.94, P< 0.05). The dissimilarity in the adsorption affinity (K d ) and nonlinear adsorption degree from the HA fluorescent components to MWCNTs was clearly observed. The adsorption mechanism suggested that the π-π electron donor-acceptor (EDA) interaction played an important role in the interaction between HA fluorescent components and the three MWCNTs. Furthermore, the values of the thermodynamic parameters, including the Gibbs free energy change (ΔG°), enthalpy change (ΔH°) and entropy change (ΔS°), showed that the adsorption of the HA fluorescent components on MWCNTs was spontaneous and exothermic. Copyright © 2017 Elsevier Inc. All rights reserved.

Multi-component nanofibrous scaffolds with tunable properties for bone tissue engineering

NASA Astrophysics Data System (ADS)

Jose, Moncy V.

Bone is a highly complex tissue which is an integral part of vertebrates and hence any damage has a major negative effect on the quality of life. Tissue engineering is regarded as an ideal route to resolve the issues related to the scarcity of tissue and organ for transplantation. Apart from cell line and growth factors, the choice of materials and fabrication technique for scaffold are equally important. The goal of this work was to develop a multi-component nanofibrous scaffold based on a synthetic polymer (poly(lactic-co-glycolide) (PLGA)), a biopolymer (collagen) and a biomineral (nano-hydroxyapatite (nano-HA)) by electrospinning technique, which mimics the nanoscopic, chemical, and anisotropic features of bone. Preliminary studies involved fabrication of nanocomposite scaffolds based on PLGA and nano-HA. Morphological and mechanical characterizations revealed that at low concentrations, nano-HA acted as reinforcements, whereas at higher concentrations the presence of aggregation was detrimental to the scaffold. Hydrolytic degradation studies revealed the scaffold had a little mass loss and the mechanical property was maintained for a period of 6 weeks. This study was followed by evaluation of a blend system based on PLGA and collagen. Collagen addition provides hydrophilicity and the necessary cell binding sites in PLGA. The structural characterization revealed that the blend had limited interactions between the two components. The mechanical characterization revealed that with increasing collagen concentration, there was a decline in mechanical properties. However, crosslinking of the blend system, with carbodiimide (EDC) resulted in improving the mechanical properties of the scaffolds. A multi-component system was developed by adding different concentrations of nano-HA to a fixed PLGA/collagen blend composition (80/20). Morphological and mechanical characterizations revealed properties similar to the PLGA/HA system. Cyto-compatibility studies revealed

Real-time myoelectric control of a multi-fingered hand prosthesis using principal components analysis.

PubMed

Matrone, Giulia C; Cipriani, Christian; Carrozza, Maria Chiara; Magenes, Giovanni

2012-06-15

In spite of the advances made in the design of dexterous anthropomorphic hand prostheses, these sophisticated devices still lack adequate control interfaces which could allow amputees to operate them in an intuitive and close-to-natural way. In this study, an anthropomorphic five-fingered robotic hand, actuated by six motors, was used as a prosthetic hand emulator to assess the feasibility of a control approach based on Principal Components Analysis (PCA), specifically conceived to address this problem. Since it was demonstrated elsewhere that the first two principal components (PCs) can describe the whole hand configuration space sufficiently well, the controller here employed reverted the PCA algorithm and allowed to drive a multi-DoF hand by combining a two-differential channels EMG input with these two PCs. Hence, the novelty of this approach stood in the PCA application for solving the challenging problem of best mapping the EMG inputs into the degrees of freedom (DoFs) of the prosthesis. A clinically viable two DoFs myoelectric controller, exploiting two differential channels, was developed and twelve able-bodied participants, divided in two groups, volunteered to control the hand in simple grasp trials, using forearm myoelectric signals. Task completion rates and times were measured. The first objective (assessed through one group of subjects) was to understand the effectiveness of the approach; i.e., whether it is possible to drive the hand in real-time, with reasonable performance, in different grasps, also taking advantage of the direct visual feedback of the moving hand. The second objective (assessed through a different group) was to investigate the intuitiveness, and therefore to assess statistical differences in the performance throughout three consecutive days. Subjects performed several grasp, transport and release trials with differently shaped objects, by operating the hand with the myoelectric PCA-based controller. Experimental trials showed that

An improved independent component analysis model for 3D chromatogram separation and its solution by multi-areas genetic algorithm

PubMed Central

2014-01-01

Background The 3D chromatogram generated by High Performance Liquid Chromatography-Diode Array Detector (HPLC-DAD) has been researched widely in the field of herbal medicine, grape wine, agriculture, petroleum and so on. Currently, most of the methods used for separating a 3D chromatogram need to know the compounds' number in advance, which could be impossible especially when the compounds are complex or white noise exist. New method which extracts compounds from 3D chromatogram directly is needed. Methods In this paper, a new separation model named parallel Independent Component Analysis constrained by Reference Curve (pICARC) was proposed to transform the separation problem to a multi-parameter optimization issue. It was not necessary to know the number of compounds in the optimization. In order to find all the solutions, an algorithm named multi-areas Genetic Algorithm (mGA) was proposed, where multiple areas of candidate solutions were constructed according to the fitness and distances among the chromosomes. Results Simulations and experiments on a real life HPLC-DAD data set were used to demonstrate our method and its effectiveness. Through simulations, it can be seen that our method can separate 3D chromatogram to chromatogram peaks and spectra successfully even when they severely overlapped. It is also shown by the experiments that our method is effective to solve real HPLC-DAD data set. Conclusions Our method can separate 3D chromatogram successfully without knowing the compounds' number in advance, which is fast and effective. PMID:25474487

An improved independent component analysis model for 3D chromatogram separation and its solution by multi-areas genetic algorithm.

PubMed

Cui, Lizhi; Poon, Josiah; Poon, Simon K; Chen, Hao; Gao, Junbin; Kwan, Paul; Fan, Kei; Ling, Zhihao

2014-01-01

The 3D chromatogram generated by High Performance Liquid Chromatography-Diode Array Detector (HPLC-DAD) has been researched widely in the field of herbal medicine, grape wine, agriculture, petroleum and so on. Currently, most of the methods used for separating a 3D chromatogram need to know the compounds' number in advance, which could be impossible especially when the compounds are complex or white noise exist. New method which extracts compounds from 3D chromatogram directly is needed. In this paper, a new separation model named parallel Independent Component Analysis constrained by Reference Curve (pICARC) was proposed to transform the separation problem to a multi-parameter optimization issue. It was not necessary to know the number of compounds in the optimization. In order to find all the solutions, an algorithm named multi-areas Genetic Algorithm (mGA) was proposed, where multiple areas of candidate solutions were constructed according to the fitness and distances among the chromosomes. Simulations and experiments on a real life HPLC-DAD data set were used to demonstrate our method and its effectiveness. Through simulations, it can be seen that our method can separate 3D chromatogram to chromatogram peaks and spectra successfully even when they severely overlapped. It is also shown by the experiments that our method is effective to solve real HPLC-DAD data set. Our method can separate 3D chromatogram successfully without knowing the compounds' number in advance, which is fast and effective.

Chemical ageing and transformation of diffusivity in semi-solid multi-component organic aerosol particles

NASA Astrophysics Data System (ADS)

Pfrang, C.; Shiraiwa, M.; Pöschl, U.

2011-04-01

Recent experimental evidence underlines the importance of reduced diffusivity in amorphous semi-solid or glassy atmospheric aerosols. This paper investigates the impact of diffusivity on the ageing of multi-component reactive organic particles representative of atmospheric cooking aerosols. We apply and extend the recently developed KM-SUB model in a study of a 12-component mixture containing oleic and palmitoleic acids. We demonstrate that changes in the diffusivity may explain the evolution of chemical loss rates in ageing semi-solid particles, and we resolve surface and bulk processes under transient reaction conditions considering diffusivities altered by oligomerisation. This new model treatment allows prediction of the ageing of mixed organic multi-component aerosols over atmospherically relevant time scales and conditions. We illustrate the impact of changing diffusivity on the chemical half-life of reactive components in semi-solid particles, and we demonstrate how solidification and crust formation at the particle surface can affect the chemical transformation of organic aerosols.

Chemical ageing and transformation of diffusivity in semi-solid multi-component organic aerosol particles

NASA Astrophysics Data System (ADS)

Pfrang, C.; Shiraiwa, M.; Pöschl, U.

2011-07-01

Recent experimental evidence underlines the importance of reduced diffusivity in amorphous semi-solid or glassy atmospheric aerosols. This paper investigates the impact of diffusivity on the ageing of multi-component reactive organic particles approximating atmospheric cooking aerosols. We apply and extend the recently developed KM-SUB model in a study of a 12-component mixture containing oleic and palmitoleic acids. We demonstrate that changes in the diffusivity may explain the evolution of chemical loss rates in ageing semi-solid particles, and we resolve surface and bulk processes under transient reaction conditions considering diffusivities altered by oligomerisation. This new model treatment allows prediction of the ageing of mixed organic multi-component aerosols over atmospherically relevant timescales and conditions. We illustrate the impact of changing diffusivity on the chemical half-life of reactive components in semi-solid particles, and we demonstrate how solidification and crust formation at the particle surface can affect the chemical transformation of organic aerosols.

Evaluation of skin melanoma in spectral range 450-950 nm using principal component analysis

NASA Astrophysics Data System (ADS)

Jakovels, D.; Lihacova, I.; Kuzmina, I.; Spigulis, J.

2013-06-01

Diagnostic potential of principal component analysis (PCA) of multi-spectral imaging data in the wavelength range 450- 950 nm for distant skin melanoma recognition is discussed. Processing of the measured clinical data by means of PCA resulted in clear separation between malignant melanomas and pigmented nevi.

Comparison of multi-subject ICA methods for analysis of fMRI data

PubMed Central

Erhardt, Erik Barry; Rachakonda, Srinivas; Bedrick, Edward; Allen, Elena; Adali, Tülay; Calhoun, Vince D.

2010-01-01

Spatial independent component analysis (ICA) applied to functional magnetic resonance imaging (fMRI) data identifies functionally connected networks by estimating spatially independent patterns from their linearly mixed fMRI signals. Several multi-subject ICA approaches estimating subject-specific time courses (TCs) and spatial maps (SMs) have been developed, however there has not yet been a full comparison of the implications of their use. Here, we provide extensive comparisons of four multi-subject ICA approaches in combination with data reduction methods for simulated and fMRI task data. For multi-subject ICA, the data first undergo reduction at the subject and group levels using principal component analysis (PCA). Comparisons of subject-specific, spatial concatenation, and group data mean subject-level reduction strategies using PCA and probabilistic PCA (PPCA) show that computationally intensive PPCA is equivalent to PCA, and that subject-specific and group data mean subject-level PCA are preferred because of well-estimated TCs and SMs. Second, aggregate independent components are estimated using either noise free ICA or probabilistic ICA (PICA). Third, subject-specific SMs and TCs are estimated using back-reconstruction. We compare several direct group ICA (GICA) back-reconstruction approaches (GICA1-GICA3) and an indirect back-reconstruction approach, spatio-temporal regression (STR, or dual regression). Results show the earlier group ICA (GICA1) approximates STR, however STR has contradictory assumptions and may show mixed-component artifacts in estimated SMs. Our evidence-based recommendation is to use GICA3, introduced here, with subject-specific PCA and noise-free ICA, providing the most robust and accurate estimated SMs and TCs in addition to offering an intuitive interpretation. PMID:21162045

The study of H. pylori putative candidate factors for single- and multi-component vaccine development.

PubMed

Mirzaei, Nasrin; Poursina, Farkhondeh; Moghim, Sharareh; Rashidi, Niloufar; Ghasemian Safaei, Hajieh

2017-09-01

Helicobacter pylori has grown to colonize inside the stomach of nearly half of the world's population, turning into the most prevalent infections in the universe. Medical care failures noticeably confirm the need for a vaccine to hinder or deal with H. pylori. This review is planned to discuss the most known factors as a vaccine candidate, including single (AhpC, BG, CagA, KatA, Fla, Hsp, HWC, Lpp, LPS, NAP, OMP, OMV, SOD, Tpx, Urease, VacA) and multi-component vaccines. Many promising results in the field of single and multivalent vaccine can be seen, but there is no satisfactory outcome and neither a prophylactic nor a therapeutic vaccine to treat or eradicate the infection in human has been acquired. Hence, selecting suitable antigen is an important factor as an appropriate adjuvant. Taken all together, the development of efficient anti-H. pylori vaccines relies on the fully understanding of the interactions between H. pylori and its host immune system. Therefore, more work should be done on epitope mapping, analysis of molecular structure, and determination of the antigen determinant region as well due to design a vaccine, preferably a multi-component vaccine to elicit specific CD4 T-cell responses that are required for H. pylori vaccine efficacy.

EVMDD-Based Analysis and Diagnosis Methods of Multi-State Systems with Multi-State Components

DTIC Science & Technology

2014-01-01

Springer-Verlag New York Inc., 2001. [7] T. Kam, T. Villa, R. K. Brayton , and A. L. Sangiovanni-Vincentelli, “Multi-valued deci- sion diagrams: Theory and...Decision Diagram Techniques for Micro- and Nanoelectronic Design, CRC Press, Taylor & Francis Group, 2006. [22] X. Zang, D. Wang, H. Sun, and K. S. Trivedi

Effectiveness of a worksite mindfulness-based multi-component intervention on lifestyle behaviors

PubMed Central

2014-01-01

Introduction Overweight and obesity are associated with an increased risk of morbidity. Mindfulness training could be an effective strategy to optimize lifestyle behaviors related to body weight gain. The aim of this study was to evaluate the effectiveness of a worksite mindfulness-based multi-component intervention on vigorous physical activity in leisure time, sedentary behavior at work, fruit intake and determinants of these behaviors. The control group received information on existing lifestyle behavior- related facilities that were already available at the worksite. Methods In a randomized controlled trial design (n = 257), 129 workers received a mindfulness training, followed by e-coaching, lunch walking routes and fruit. Outcome measures were assessed at baseline and after 6 and 12 months using questionnaires. Physical activity was also measured using accelerometers. Effects were analyzed using linear mixed effect models according to the intention-to-treat principle. Linear regression models (complete case analyses) were used as sensitivity analyses. Results There were no significant differences in lifestyle behaviors and determinants of these behaviors between the intervention and control group after 6 or 12 months. The sensitivity analyses showed effect modification for gender in sedentary behavior at work at 6-month follow-up, although the main analyses did not. Conclusions This study did not show an effect of a worksite mindfulness-based multi-component intervention on lifestyle behaviors and behavioral determinants after 6 and 12 months. The effectiveness of a worksite mindfulness-based multi-component intervention as a health promotion intervention for all workers could not be established. PMID:24467802

Dynamics of Rotating Multi-component Turbomachinery Systems

NASA Technical Reports Server (NTRS)

Lawrence, Charles

1993-01-01

The ultimate objective of turbomachinery vibration analysis is to predict both the overall, as well as component dynamic response. To accomplish this objective requires complete engine structural models, including multistages of bladed disk assemblies, flexible rotor shafts and bearings, and engine support structures and casings. In the present approach each component is analyzed as a separate structure and boundary information is exchanged at the inter-component connections. The advantage of this tactic is that even though readily available detailed component models are utilized, accurate and comprehensive system response information may be obtained. Sample problems, which include a fixed base rotating blade and a blade on a flexible rotor, are presented.

Methods and Research for Multi-Component Cutting Force Sensing Devices and Approaches in Machining

PubMed Central

Liang, Qiaokang; Zhang, Dan; Wu, Wanneng; Zou, Kunlin

2016-01-01

Multi-component cutting force sensing systems in manufacturing processes applied to cutting tools are gradually becoming the most significant monitoring indicator. Their signals have been extensively applied to evaluate the machinability of workpiece materials, predict cutter breakage, estimate cutting tool wear, control machine tool chatter, determine stable machining parameters, and improve surface finish. Robust and effective sensing systems with capability of monitoring the cutting force in machine operations in real time are crucial for realizing the full potential of cutting capabilities of computer numerically controlled (CNC) tools. The main objective of this paper is to present a brief review of the existing achievements in the field of multi-component cutting force sensing systems in modern manufacturing. PMID:27854322

Methods and Research for Multi-Component Cutting Force Sensing Devices and Approaches in Machining.

PubMed

Liang, Qiaokang; Zhang, Dan; Wu, Wanneng; Zou, Kunlin

2016-11-16

Multi-component cutting force sensing systems in manufacturing processes applied to cutting tools are gradually becoming the most significant monitoring indicator. Their signals have been extensively applied to evaluate the machinability of workpiece materials, predict cutter breakage, estimate cutting tool wear, control machine tool chatter, determine stable machining parameters, and improve surface finish. Robust and effective sensing systems with capability of monitoring the cutting force in machine operations in real time are crucial for realizing the full potential of cutting capabilities of computer numerically controlled (CNC) tools. The main objective of this paper is to present a brief review of the existing achievements in the field of multi-component cutting force sensing systems in modern manufacturing.

Multi-Component T2 Relaxation Studies of the Avian Egg

PubMed Central

Mitsouras, Dimitris; Mulkern, Robert V.; Maier, Stephan E.

2015-01-01

Purpose To investigate the tissue-like multiexponential T2 signal decays in avian eggs. Methods Transverse relaxation studies of raw, soft-boiled and hard-boiled eggs were performed at 3 Tesla using a 3D Carr-Purcell-Meiboom-Gill (CPMG) imaging sequence. Signal decays over a TE range of 11 to 354 ms were fitted assuming single- and multi-component signal decays with up to three separately decaying components. Fat saturation was used to facilitate spectral assignment of observed decay components. Results Egg white, yolk and the centrally located latebra all demonstrate nonmonoexponential T2 decays. Specifically, egg white exhibits two-component decays with intermediate and long T2 times. Meanwhile, yolk and latebra are generally best characterized with triexponential decays, with short, intermediate and very long T2 decay times. Fat saturation revealed that the intermediate component of yolk could be attributed to lipids. Cooking of the egg profoundly altered the decay curves. Conclusion Avian egg T2 decay curves cover a wide range of decay times. Observed T2 components in yolk and latebra as short as 10 ms, may prove valuable for testing clinical sequences designed to measure short T2 components, such as myelin-associated water in the brain. Thus we propose that the egg can be a versatile and widely available MR transverse relaxation phantom. PMID:26037128

[Theoretical modeling and experimental research on direct compaction characteristics of multi-component pharmaceutical powders based on the Kawakita equation].

PubMed

Si, Guo-Ning; Chen, Lan; Li, Bao-Guo

2014-04-01

Base on the Kawakita powder compression equation, a general theoretical model for predicting the compression characteristics of multi-components pharmaceutical powders with different mass ratios was developed. The uniaxial flat-face compression tests of powder lactose, starch and microcrystalline cellulose were carried out, separately. Therefore, the Kawakita equation parameters of the powder materials were obtained. The uniaxial flat-face compression tests of the powder mixtures of lactose, starch, microcrystalline cellulose and sodium stearyl fumarate with five mass ratios were conducted, through which, the correlation between mixture density and loading pressure and the Kawakita equation curves were obtained. Finally, the theoretical prediction values were compared with experimental results. The analysis showed that the errors in predicting mixture densities were less than 5.0% and the errors of Kawakita vertical coordinate were within 4.6%, which indicated that the theoretical model could be used to predict the direct compaction characteristics of multi-component pharmaceutical powders.

Integrated Multi-process Microfluidic Systems for Automating Analysis

PubMed Central

Yang, Weichun; Woolley, Adam T.

2010-01-01

Microfluidic technologies have been applied extensively in rapid sample analysis. Some current challenges for standard microfluidic systems are relatively high detection limits, and reduced resolving power and peak capacity compared to conventional approaches. The integration of multiple functions and components onto a single platform can overcome these separation and detection limitations of microfluidics. Multiplexed systems can greatly increase peak capacity in multidimensional separations and can increase sample throughput by analyzing many samples simultaneously. On-chip sample preparation, including labeling, preconcentration, cleanup and amplification, can all serve to speed up and automate processes in integrated microfluidic systems. This paper summarizes advances in integrated multi-process microfluidic systems for automated analysis, their benefits and areas for needed improvement. PMID:20514343

Generalized Structured Component Analysis

ERIC Educational Resources Information Center

Hwang, Heungsun; Takane, Yoshio

2004-01-01

We propose an alternative method to partial least squares for path analysis with components, called generalized structured component analysis. The proposed method replaces factors by exact linear combinations of observed variables. It employs a well-defined least squares criterion to estimate model parameters. As a result, the proposed method…

[Principal component analysis and cluster analysis of inorganic elements in sea cucumber Apostichopus japonicus].

PubMed

Liu, Xiao-Fang; Xue, Chang-Hu; Wang, Yu-Ming; Li, Zhao-Jie; Xue, Yong; Xu, Jie

2011-11-01

The present study is to investigate the feasibility of multi-elements analysis in determination of the geographical origin of sea cucumber Apostichopus japonicus, and to make choice of the effective tracers in sea cucumber Apostichopus japonicus geographical origin assessment. The content of the elements such as Al, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Mo, Cd, Hg and Pb in sea cucumber Apostichopus japonicus samples from seven places of geographical origin were determined by means of ICP-MS. The results were used for the development of elements database. Cluster analysis(CA) and principal component analysis (PCA) were applied to differentiate the sea cucumber Apostichopus japonicus geographical origin. Three principal components which accounted for over 89% of the total variance were extracted from the standardized data. The results of Q-type cluster analysis showed that the 26 samples could be clustered reasonably into five groups, the classification results were significantly associated with the marine distribution of the sea cucumber Apostichopus japonicus samples. The CA and PCA were the effective methods for elements analysis of sea cucumber Apostichopus japonicus samples. The content of the mineral elements in sea cucumber Apostichopus japonicus samples was good chemical descriptors for differentiating their geographical origins.

Proceedings of the XIII International Symposium on Biological Control of Weeds; September 11-16, 2011; Waikoloa, Hawaii, USA

Treesearch

Yun Wu; Tracy Johnson; Sharlene Sing; S. Raghu; Greg Wheeler; Paul Pratt; Keith Warner; Ted Center; John Goolsby; Richard Reardon

2013-01-01

A total of 208 participants from 78 organizations in 19 countries gathered at the Waikoloa Beach Marriott on the Big Island of Hawaii on September 11-16, 2011 for the XIII International Symposium on Biological Control of Weeds. Following a reception on the first evening, Symposium co-chairs Tracy Johnson and Pat Conant formally welcomed the attendees on the morning of...

The Effects of a Multi-Component Intervention on Preschool Children's Literacy Skills

ERIC Educational Resources Information Center

Dennis, Lindsay R.

2016-01-01

This study examined the effects of a multi-component intervention program (i.e., extended instruction and iPad app technology) on preschool children's vocabulary. Instruction utilizing the intervention program was provided across 6 storybooks, 4 verbs per book, for a total of 24 verbs. Dependent variables included expressive vocabulary,…

Research on The Construction of Flexible Multi-body Dynamics Model based on Virtual Components

NASA Astrophysics Data System (ADS)

Dong, Z. H.; Ye, X.; Yang, F.

2018-05-01

Focus on the harsh operation condition of space manipulator, which cannot afford relative large collision momentum, this paper proposes a new concept and technology, called soft-contact technology. In order to solve the problem of collision dynamics of flexible multi-body system caused by this technology, this paper also proposes the concepts of virtual components and virtual hinges, and constructs flexible dynamic model based on virtual components, and also studies on its solutions. On this basis, this paper uses NX to carry out model and comparison simulation for space manipulator in 3 different modes. The results show that using the model of multi-rigid body + flexible body hinge + controllable damping can make effective control on amplitude for the force and torque caused by target satellite collision.

Recovery of a spectrum based on a compressive-sensing algorithm with weighted principal component analysis

NASA Astrophysics Data System (ADS)

Dafu, Shen; Leihong, Zhang; Dong, Liang; Bei, Li; Yi, Kang

2017-07-01

The purpose of this study is to improve the reconstruction precision and better copy the color of spectral image surfaces. A new spectral reflectance reconstruction algorithm based on an iterative threshold combined with weighted principal component space is presented in this paper, and the principal component with weighted visual features is the sparse basis. Different numbers of color cards are selected as the training samples, a multispectral image is the testing sample, and the color differences in the reconstructions are compared. The channel response value is obtained by a Mega Vision high-accuracy, multi-channel imaging system. The results show that spectral reconstruction based on weighted principal component space is superior in performance to that based on traditional principal component space. Therefore, the color difference obtained using the compressive-sensing algorithm with weighted principal component analysis is less than that obtained using the algorithm with traditional principal component analysis, and better reconstructed color consistency with human eye vision is achieved.

Reducing occupational sitting: Workers' perspectives on participation in a multi-component intervention.

PubMed

Hadgraft, Nyssa T; Willenberg, Lisa; LaMontagne, Anthony D; Malkoski, Keti; Dunstan, David W; Healy, Genevieve N; Moodie, Marj; Eakin, Elizabeth G; Owen, Neville; Lawler, Sheleigh P

2017-05-30

Office workers spend much of their time sitting, which is now understood to be a risk factor for several chronic diseases. This qualitative study examined participants' perspectives following their involvement in a cluster randomised controlled trial of a multi-component intervention targeting prolonged workplace sitting (Stand Up Victoria). The intervention incorporated a sit-stand workstation, individual health coaching and organisational support strategies. The aim of the study was to explore the acceptability of the intervention, barriers and facilitators to reducing workplace sitting, and perceived effects of the intervention on workplace culture, productivity and health-related outcomes. Semi-structured interviews (n = 21 participants) and two focus groups (n = 7) were conducted with intervention participants at the conclusion of the 12 month trial and thematic analysis was used to analyse the data. Questions covered intervention acceptability, overall impact, barriers and facilitators to reducing workplace sitting, and perceived impact on productivity and workplace culture. Overall, participants had positive intervention experiences, perceiving that reductions in workplace sitting were associated with improved health and well-being with limited negative impact on work performance. While sit-stand workstations appeared to be the primary drivers of change, workstation design and limited suitability of standing for some job tasks and situations were perceived as barriers to their use. Social support from team leaders and other participants was perceived to facilitate behavioural changes and a shift in norms towards increased acceptance of standing in the workplace. Multi-component interventions to reduce workplace sitting, incorporating sit-stand workstations, are acceptable and feasible; however, supportive social and environmental conditions are required to support participant engagement. Best practice approaches to reduce workplace sitting should

Single and multi-component adsorption of psychiatric pharmaceuticals onto alternative and commercial carbons.

PubMed

Calisto, Vânia; Jaria, Guilaine; Silva, Carla Patrícia; Ferreira, Catarina I A; Otero, Marta; Esteves, Valdemar I

2017-05-01

This work describes the adsorptive removal of three widely consumed psychiatric pharmaceuticals (carbamazepine, paroxetine and oxazepam) from ultrapure water. Two different adsorbents were used: a commercial activated carbon and a non-activated waste-based carbon (PS800-150-HCl), produced by pyrolysis of primary paper mill sludge. These adsorbents were used in single, binary and ternary batch experiments in order to determine the adsorption kinetics and equilibrium isotherms of the considered pharmaceuticals. For the three drugs and both carbons, the equilibrium was quickly attained (with maximum equilibrium times of 15 and 120 min for the waste-based and the commercial carbons, respectively) even in binary and ternary systems. Single component equilibrium data were adequately described by the Langmuir model, with the commercial carbon registering higher maximum adsorption capacities (between 272 ± 10 and 493 ± 12 μmol g -1 ) than PS800-150-HCl (between 64 ± 2 and 74 ± 1 μmol g -1 ). Multi-component equilibrium data were also best fitted by the single component Langmuir isotherm, followed by the Langmuir competitive model. Overall, competitive effects did not largely affect the performance of both adsorbents. Binary and ternary systems maintained fast kinetics, the individual maximum adsorption capacities were not lower than half of the single component systems and both carbons presented improved total adsorption capacities for multi-component solutions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Protecting wood from mould, decay, and termites with multi-component biocide systems

Treesearch

Carol A. Clausen

2007-01-01

Biocides must be developed for controlling mould establishment on cellulose-based building materials. Accordingly, biocides intended for indoor applications must be non- toxic, non-volatile, odourless, hypoallergenic, and able to provide long-term protection under conditions of high humidity. Multi-component biocide systems were tested in American Wood-Preservers’...

Detection of gear cracks in a complex gearbox of wind turbines using supervised bounded component analysis of vibration signals collected from multi-channel sensors

NASA Astrophysics Data System (ADS)

Li, Zhixiong; Yan, Xinping; Wang, Xuping; Peng, Zhongxiao

2016-06-01

In the complex gear transmission systems, in wind turbines a crack is one of the most common failure modes and can be fatal to the wind turbine power systems. A single sensor may suffer with issues relating to its installation position and direction, resulting in the collection of weak dynamic responses of the cracked gear. A multi-channel sensor system is hence applied in the signal acquisition and the blind source separation (BSS) technologies are employed to optimally process the information collected from multiple sensors. However, literature review finds that most of the BSS based fault detectors did not address the dependence/correlation between different moving components in the gear systems; particularly, the popular used independent component analysis (ICA) assumes mutual independence of different vibration sources. The fault detection performance may be significantly influenced by the dependence/correlation between vibration sources. In order to address this issue, this paper presents a new method based on the supervised order tracking bounded component analysis (SOTBCA) for gear crack detection in wind turbines. The bounded component analysis (BCA) is a state of art technology for dependent source separation and is applied limitedly to communication signals. To make it applicable for vibration analysis, in this work, the order tracking has been appropriately incorporated into the BCA framework to eliminate the noise and disturbance signal components. Then an autoregressive (AR) model built with prior knowledge about the crack fault is employed to supervise the reconstruction of the crack vibration source signature. The SOTBCA only outputs one source signal that has the closest distance with the AR model. Owing to the dependence tolerance ability of the BCA framework, interfering vibration sources that are dependent/correlated with the crack vibration source could be recognized by the SOTBCA, and hence, only useful fault information could be preserved in

Cost component analysis.

PubMed

Lörincz, András; Póczos, Barnabás

2003-06-01

In optimizations the dimension of the problem may severely, sometimes exponentially increase optimization time. Parametric function approximatiors (FAPPs) have been suggested to overcome this problem. Here, a novel FAPP, cost component analysis (CCA) is described. In CCA, the search space is resampled according to the Boltzmann distribution generated by the energy landscape. That is, CCA converts the optimization problem to density estimation. Structure of the induced density is searched by independent component analysis (ICA). The advantage of CCA is that each independent ICA component can be optimized separately. In turn, (i) CCA intends to partition the original problem into subproblems and (ii) separating (partitioning) the original optimization problem into subproblems may serve interpretation. Most importantly, (iii) CCA may give rise to high gains in optimization time. Numerical simulations illustrate the working of the algorithm.

Multi-Enzyme Complexes in the Thermophilic Archaea: The Effects of Temperature on Stability, Catalysis and Enzyme Interactions in a Multi-Component System

DTIC Science & Technology

2012-01-01

COVERED (From - To) 4. TITLE AND SUBTITLE Multi- enzyme complexes in the thermophilic archaea: The effects of temperature on stability, catalysis and... enzyme interactions in a multi- component system 5a. CONTRACT NUMBER 5b. GRANT NUMBER FA9550-07-1-0058 5c. PROGRAM ELEMENT NUMBER 61102F 6...involves cloning of the genes for the relevant lipoylation enzymes , and characterisation of the protein products 15. SUBJECT TERMS 16. SECURITY

Influence of Natural Convection and Thermal Radiation Multi-Component Transport in MOCVD Reactors

NASA Technical Reports Server (NTRS)

Lowry, S.; Krishnan, A.; Clark, I.

1999-01-01

The influence of Grashof and Reynolds number in Metal Organic Chemical Vapor (MOCVD) reactors is being investigated under a combined empirical/numerical study. As part of that research, the deposition of Indium Phosphide in an MOCVD reactor is modeled using the computational code CFD-ACE. The model includes the effects of convection, conduction, and radiation as well as multi-component diffusion and multi-step surface/gas phase chemistry. The results of the prediction are compared with experimental data for a commercial reactor and analyzed with respect to the model accuracy.

Application of multi-tone mask technology in photolithographic fabrication of color filter components in LCD

NASA Astrophysics Data System (ADS)

Takada, Yoshihiro; Fukui, Matoko; Sai, Tsunehiro

2008-11-01

Recent progresses in the photoresists and photolithography for LCD industry applications have been primarily driven by the following two factors: advancement in the material performances (high resolution, high contrast ratio, low dielectric constant) for higher display quality, and cost reduction in the fabrication process. Along with crucial demand for cost competitiveness by improving production efficiency, environmental consciousness has been a major priority at fabrication process design to minimize the amount of waste produced. Having said the above, integration of two or more fabrication processes into a single process by using multi-tone mask technology has been the interest of research, due to its obvious advantage of reducing fabrication processes and cost. For example, multi-tone mask technology application has been widely employed on the TFT side to reduce the different types of photomasks being used. Similar trend has been employed on the CF side as well, where application of multi-tone mask technology is being investigated to integrate fabrication of multiple CF micro-components into a single process. In this presentation, we demonstrate a new approach of fabricating photospacer and peripheral CF components (MVA protrusion, sub-photospacers) in a single integrated process through multi-tone mask technology.

Full-scale evaluation of a multi-component additive for efficient control of activated sludge filamentous bulking.

PubMed

Seka, M A; Van DeWiele, T; Verstraete, W

2002-01-01

A multi-component additive formulated for a more efficient control of activated sludge filamentous bulking was evaluated at a full-scale treatment plant experiencing severe filamentous bulking. It was found that, besides offering an immediate improvement of sludge settling, the multi-component additive was able to eliminate the filamentous bacteria causing the bulking. Hence, contrary to ordinary additives, this novel additive yielded immediate as well as long-term improvements in sludge sedimentation upon a few additions. Preliminary lab-scale toxicity tests showed that the treatment of the sludge by the additive should not impart any toxicity to the resulting effluent.

Gauss Seidel-type methods for energy states of a multi-component Bose Einstein condensate

NASA Astrophysics Data System (ADS)

Chang, Shu-Ming; Lin, Wen-Wei; Shieh, Shih-Feng

2005-01-01

In this paper, we propose two iterative methods, a Jacobi-type iteration (JI) and a Gauss-Seidel-type iteration (GSI), for the computation of energy states of the time-independent vector Gross-Pitaevskii equation (VGPE) which describes a multi-component Bose-Einstein condensate (BEC). A discretization of the VGPE leads to a nonlinear algebraic eigenvalue problem (NAEP). We prove that the GSI method converges locally and linearly to a solution of the NAEP if and only if the associated minimized energy functional problem has a strictly local minimum. The GSI method can thus be used to compute ground states and positive bound states, as well as the corresponding energies of a multi-component BEC. Numerical experience shows that the GSI converges much faster than JI and converges globally within 10-20 steps.

Parallel group independent component analysis for massive fMRI data sets.

PubMed

Chen, Shaojie; Huang, Lei; Qiu, Huitong; Nebel, Mary Beth; Mostofsky, Stewart H; Pekar, James J; Lindquist, Martin A; Eloyan, Ani; Caffo, Brian S

2017-01-01

Independent component analysis (ICA) is widely used in the field of functional neuroimaging to decompose data into spatio-temporal patterns of co-activation. In particular, ICA has found wide usage in the analysis of resting state fMRI (rs-fMRI) data. Recently, a number of large-scale data sets have become publicly available that consist of rs-fMRI scans from thousands of subjects. As a result, efficient ICA algorithms that scale well to the increased number of subjects are required. To address this problem, we propose a two-stage likelihood-based algorithm for performing group ICA, which we denote Parallel Group Independent Component Analysis (PGICA). By utilizing the sequential nature of the algorithm and parallel computing techniques, we are able to efficiently analyze data sets from large numbers of subjects. We illustrate the efficacy of PGICA, which has been implemented in R and is freely available through the Comprehensive R Archive Network, through simulation studies and application to rs-fMRI data from two large multi-subject data sets, consisting of 301 and 779 subjects respectively.

Directing folding pathways for multi-component DNA origami nanostructures with complex topology

NASA Astrophysics Data System (ADS)

Marras, A. E.; Zhou, L.; Kolliopoulos, V.; Su, H.-J.; Castro, C. E.

2016-05-01

Molecular self-assembly has become a well-established technique to design complex nanostructures and hierarchical mesoscale assemblies. The typical approach is to design binding complementarity into nucleotide or amino acid sequences to achieve the desired final geometry. However, with an increasing interest in dynamic nanodevices, the need to design structures with motion has necessitated the development of multi-component structures. While this has been achieved through hierarchical assembly of similar structural units, here we focus on the assembly of topologically complex structures, specifically with concentric components, where post-folding assembly is not feasible. We exploit the ability to direct folding pathways to program the sequence of assembly and present a novel approach of designing the strand topology of intermediate folding states to program the topology of the final structure, in this case a DNA origami slider structure that functions much like a piston-cylinder assembly in an engine. The ability to program the sequence and control orientation and topology of multi-component DNA origami nanostructures provides a foundation for a new class of structures with internal and external moving parts and complex scaffold topology. Furthermore, this work provides critical insight to guide the design of intermediate states along a DNA origami folding pathway and to further understand the details of DNA origami self-assembly to more broadly control folding states and landscapes.

Probabilistic Structural Analysis Methods (PSAM) for select space propulsion system components, part 2

NASA Technical Reports Server (NTRS)

1991-01-01

The technical effort and computer code enhancements performed during the sixth year of the Probabilistic Structural Analysis Methods program are summarized. Various capabilities are described to probabilistically combine structural response and structural resistance to compute component reliability. A library of structural resistance models is implemented in the Numerical Evaluations of Stochastic Structures Under Stress (NESSUS) code that included fatigue, fracture, creep, multi-factor interaction, and other important effects. In addition, a user interface was developed for user-defined resistance models. An accurate and efficient reliability method was developed and was successfully implemented in the NESSUS code to compute component reliability based on user-selected response and resistance models. A risk module was developed to compute component risk with respect to cost, performance, or user-defined criteria. The new component risk assessment capabilities were validated and demonstrated using several examples. Various supporting methodologies were also developed in support of component risk assessment.

Principal component regression analysis with SPSS.

PubMed

Liu, R X; Kuang, J; Gong, Q; Hou, X L

2003-06-01

The paper introduces all indices of multicollinearity diagnoses, the basic principle of principal component regression and determination of 'best' equation method. The paper uses an example to describe how to do principal component regression analysis with SPSS 10.0: including all calculating processes of the principal component regression and all operations of linear regression, factor analysis, descriptives, compute variable and bivariate correlations procedures in SPSS 10.0. The principal component regression analysis can be used to overcome disturbance of the multicollinearity. The simplified, speeded up and accurate statistical effect is reached through the principal component regression analysis with SPSS.

Computerized detection of breast lesions in multi-centre and multi-instrument DCE-MR data using 3D principal component maps and template matching

NASA Astrophysics Data System (ADS)

Ertas, Gokhan; Doran, Simon; Leach, Martin O.

2011-12-01

In this study, we introduce a novel, robust and accurate computerized algorithm based on volumetric principal component maps and template matching that facilitates lesion detection on dynamic contrast-enhanced MR. The study dataset comprises 24 204 contrast-enhanced breast MR images corresponding to 4034 axial slices from 47 women in the UK multi-centre study of MRI screening for breast cancer and categorized as high risk. The scans analysed here were performed on six different models of scanner from three commercial vendors, sited in 13 clinics around the UK. 1952 slices from this dataset, containing 15 benign and 13 malignant lesions, were used for training. The remaining 2082 slices, with 14 benign and 12 malignant lesions, were used for test purposes. To prevent false positives being detected from other tissues and regions of the body, breast volumes are segmented from pre-contrast images using a fast semi-automated algorithm. Principal component analysis is applied to the centred intensity vectors formed from the dynamic contrast-enhanced T1-weighted images of the segmented breasts, followed by automatic thresholding to eliminate fatty tissues and slowly enhancing normal parenchyma and a convolution and filtering process to minimize artefacts from moderately enhanced normal parenchyma and blood vessels. Finally, suspicious lesions are identified through a volumetric sixfold neighbourhood connectivity search and calculation of two morphological features: volume and volumetric eccentricity, to exclude highly enhanced blood vessels, nipples and normal parenchyma and to localize lesions. This provides satisfactory lesion localization. For a detection sensitivity of 100%, the overall false-positive detection rate of the system is 1.02/lesion, 1.17/case and 0.08/slice, comparing favourably with previous studies. This approach may facilitate detection of lesions in multi-centre and multi-instrument dynamic contrast-enhanced breast MR data.

Agreement between factor XIII activity and antigen assays in measurement of factor XIII: A French multicenter study of 147 human plasma samples.

PubMed

Caron, C; Meley, R; Le Cam Duchez, V; Aillaud, M F; Lavenu-Bombled, C; Dutrillaux, F; Flaujac, C; Ryman, A; Ternisien, C; Lasne, D; Galinat, H; Pouplard, C

2017-06-01

Factor XIII (FXIII) deficiency is a rare hemorrhagic disorder whose early diagnosis is crucial for appropriate treatment and prophylactic supplementation in cases of severe deficiency. International guidelines recommend a quantitative FXIII activity assay as first-line screening test. FXIII antigen measurement may be performed to establish the subtype of FXIII deficiency (FXIIID) when activity is decreased. The aim of this multicenter study was to evaluate the analytical and diagnostic levels of performance of a new latex immunoassay, K-Assay ® FXIII reagent from Stago, for first-line measurement of FXIII antigen. Results were compared to those obtained with the Berichrom ® FXIII chromogenic assay for measurement of FXIII activity. Of the 147 patient plasma samples, 138 were selected for analysis. The accuracy was very good, with intercenter reproducibility close to 7%. Five groups were defined on FXIII activity level (<5% (n = 5), 5%-30% (n = 23), 30%-60% (n = 17), 60%-120% (n = 69), above 120% (n = 24)), without statistical differences between activity and antigen levels (P value >0.05). Correlation of the K-Assay ® with the Berichrom ® FXIII activity results was excellent (r = 0.919). Good agreement was established by the Bland and Altman method, with a bias of +9.4% on all samples, and of -1.4% for FXIII levels lower than 30%. One patient with afibrinogenemia showed low levels of Berichrom ® FXIII activity but normal antigen level and clot solubility as expected. The measurement of FXIII antigen using the K-Assay ® is a reliable first-line tool for detection of FXIII deficiency when an activity assay is not available. © 2017 John Wiley & Sons Ltd.

Family, Community and Clinic Collaboration to Treat Overweight and Obese Children: Stanford GOALS -- a Randomized Controlled Trial of a Three-Year, Multi-Component, Multi-Level, Multi-Setting Intervention

PubMed Central

Robinson, Thomas N.; Matheson, Donna; Desai, Manisha; Wilson, Darrell M.; Weintraub, Dana L.; Haskell, William L.; McClain, Arianna; McClure, Samuel; Banda, Jorge; Sanders, Lee M.; Haydel, K. Farish; Killen, Joel D.

2013-01-01

Objective To test the effects of a three-year, community-based, multi-component, multi-level, multi-setting (MMM) approach for treating overweight and obese children. Design Two-arm, parallel group, randomized controlled trial with measures at baseline, 12, 24, and 36 months after randomization. Participants Seven through eleven year old, overweight and obese children (BMI ≥ 85th percentile) and their parents/caregivers recruited from community locations in low-income, primarily Latino neighborhoods in Northern California. Interventions Families are randomized to the MMM intervention versus a community health education active-placebo comparison intervention. Interventions last for three years for each participant. The MMM intervention includes a community-based after school team sports program designed specifically for overweight and obese children, a home-based family intervention to reduce screen time, alter the home food/eating environment, and promote self-regulatory skills for eating and activity behavior change, and a primary care behavioral counseling intervention linked to the community and home interventions. The active-placebo comparison intervention includes semi-annual health education home visits, monthly health education newsletters for children and for parents/guardians, and a series of community-based health education events for families. Main Outcome Measure Body mass index trajectory over the three-year study. Secondary outcome measures include waist circumference, triceps skinfold thickness, accelerometer-measured physical activity, 24-hour dietary recalls, screen time and other sedentary behaviors, blood pressure, fasting lipids, glucose, insulin, hemoglobin A1c, C-reactive protein, alanine aminotransferase, and psychosocial measures. Conclusions The Stanford GOALS trial is testing the efficacy of a novel community-based multi-component, multi-level, multi-setting treatment for childhood overweight and obesity in low-income, Latino families

Family, community and clinic collaboration to treat overweight and obese children: Stanford GOALS-A randomized controlled trial of a three-year, multi-component, multi-level, multi-setting intervention.

PubMed

Robinson, Thomas N; Matheson, Donna; Desai, Manisha; Wilson, Darrell M; Weintraub, Dana L; Haskell, William L; McClain, Arianna; McClure, Samuel; Banda, Jorge A; Sanders, Lee M; Haydel, K Farish; Killen, Joel D

2013-11-01

To test the effects of a three-year, community-based, multi-component, multi-level, multi-setting (MMM) approach for treating overweight and obese children. Two-arm, parallel group, randomized controlled trial with measures at baseline, 12, 24, and 36 months after randomization. Seven through eleven year old, overweight and obese children (BMI ≥ 85th percentile) and their parents/caregivers recruited from community locations in low-income, primarily Latino neighborhoods in Northern California. Families are randomized to the MMM intervention versus a community health education active-placebo comparison intervention. Interventions last for three years for each participant. The MMM intervention includes a community-based after school team sports program designed specifically for overweight and obese children, a home-based family intervention to reduce screen time, alter the home food/eating environment, and promote self-regulatory skills for eating and activity behavior change, and a primary care behavioral counseling intervention linked to the community and home interventions. The active-placebo comparison intervention includes semi-annual health education home visits, monthly health education newsletters for children and for parents/guardians, and a series of community-based health education events for families. Body mass index trajectory over the three-year study. Secondary outcome measures include waist circumference, triceps skinfold thickness, accelerometer-measured physical activity, 24-hour dietary recalls, screen time and other sedentary behaviors, blood pressure, fasting lipids, glucose, insulin, hemoglobin A1c, C-reactive protein, alanine aminotransferase, and psychosocial measures. The Stanford GOALS trial is testing the efficacy of a novel community-based multi-component, multi-level, multi-setting treatment for childhood overweight and obesity in low-income, Latino families. © 2013 Elsevier Inc. All rights reserved.

Single Channel EEG Artifact Identification Using Two-Dimensional Multi-Resolution Analysis.

PubMed

Taherisadr, Mojtaba; Dehzangi, Omid; Parsaei, Hossein

2017-12-13

As a diagnostic monitoring approach, electroencephalogram (EEG) signals can be decoded by signal processing methodologies for various health monitoring purposes. However, EEG recordings are contaminated by other interferences, particularly facial and ocular artifacts generated by the user. This is specifically an issue during continuous EEG recording sessions, and is therefore a key step in using EEG signals for either physiological monitoring and diagnosis or brain-computer interface to identify such artifacts from useful EEG components. In this study, we aim to design a new generic framework in order to process and characterize EEG recording as a multi-component and non-stationary signal with the aim of localizing and identifying its component (e.g., artifact). In the proposed method, we gather three complementary algorithms together to enhance the efficiency of the system. Algorithms include time-frequency (TF) analysis and representation, two-dimensional multi-resolution analysis (2D MRA), and feature extraction and classification. Then, a combination of spectro-temporal and geometric features are extracted by combining key instantaneous TF space descriptors, which enables the system to characterize the non-stationarities in the EEG dynamics. We fit a curvelet transform (as a MRA method) to 2D TF representation of EEG segments to decompose the given space to various levels of resolution. Such a decomposition efficiently improves the analysis of the TF spaces with different characteristics (e.g., resolution). Our experimental results demonstrate that the combination of expansion to TF space, analysis using MRA, and extracting a set of suitable features and applying a proper predictive model is effective in enhancing the EEG artifact identification performance. We also compare the performance of the designed system with another common EEG signal processing technique-namely, 1D wavelet transform. Our experimental results reveal that the proposed method outperforms

Multi-component sorption of Pb(II), Cu(II) and Zn(II) onto low-cost mineral adsorbent.

PubMed

Prasad, Murari; Xu, Huan-yan; Saxena, Sona

2008-06-15

Multi-component sorption studies were carried out for attenuation of divalent heavy metal cations (Pb2+, Cu2+ and Zn2+) by a low-cost mineral adsorbent from the aqueous solution. Kinetic and equilibrium batch-type sorption experiments were conducted under variable conditions for multi-component using low-grade (<12%P2O5) phosphate rock. Percentage of multiple heavy metal species removal increases with decreasing initial metals concentration and particle size. The equilibrium data were well described to a lesser extent by Freundlich model but Langmuir model seemed to be more appropriate with the fixation capacity obtained at room temperature for Pb2+, Cu2+ and Zn2+ was 227.2, 769.2 and 666.6 micromol g(-1), respectively. Two simple kinetic models were tested to investigate the adsorption mechanism. Rate constants have been found nearly constant at all metal concentrations for first order. The comparison of adsorption capacity of low-grade phosphate rock decreases in multi-component system as compared to single component due to ionic interactions. X-ray powder diffraction (XRPD) technique was used to ascertain the formation of new metal phases followed by surface complexation. Used adsorbents have been converted into a value added product by utilizing innovative Zero-waste concept to solve the used adsorbents disposal problem and thus protecting the environment.

Reexamining protein–protein and protein–solvent interactions from Kirkwood-Buff analysis of light scattering in multi-component solutions

PubMed Central

Blanco, Marco A.; Sahin, Erinc; Li, Yi; Roberts, Christopher J.

2011-01-01

The classic analysis of Rayleigh light scattering (LS) is re-examined for multi-component protein solutions, within the context of Kirkwood-Buff (KB) theory as well as a more generalized canonical treatment. Significant differences arise when traditional treatments that approximate constant pressure and neglect concentration fluctuations in one or more (co)solvent∕co-solute species are compared with more rigorous treatments at constant volume and with all species free to fluctuate. For dilute solutions, it is shown that LS can be used to rigorously and unambiguously obtain values for the osmotic second virial coefficient (B22), in contrast with recent arguments regarding protein interactions deduced from LS experiments. For more concentrated solutions, it is shown that conventional analysis over(under)-estimates the magnitude of B22 for significantly repulsive(attractive) conditions, and that protein-protein KB integrals (G22) are the more relevant quantity obtainable from LS. Published data for α–chymotrypsinogen A and a series of monoclonal antibodies at different pH and salt concentrations are re-analyzed using traditional and new treatments. The results illustrate that while traditional analysis may be sufficient if one is interested in only the sign of B22 or G22, the quantitative values can be significantly in error. A simple approach is illustrated for determining whether protein concentration (c2) is sufficiently dilute for B22 to apply, and for correcting B22 values from traditional LS regression at higher c2 values. The apparent molecular weight M2, app obtained from LS is shown to generally not be equal to the true molecular weight, with the differences arising from a combination of protein-solute and protein-cosolute interactions that may, in principle, also be determined from LS. PMID:21682538

Geographical classification of Epimedium based on HPLC fingerprint analysis combined with multi-ingredients quantitative analysis.

PubMed

Xu, Ning; Zhou, Guofu; Li, Xiaojuan; Lu, Heng; Meng, Fanyun; Zhai, Huaqiang

2017-05-01

A reliable and comprehensive method for identifying the origin and assessing the quality of Epimedium has been developed. The method is based on analysis of HPLC fingerprints, combined with similarity analysis, hierarchical cluster analysis (HCA), principal component analysis (PCA) and multi-ingredient quantitative analysis. Nineteen batches of Epimedium, collected from different areas in the western regions of China, were used to establish the fingerprints and 18 peaks were selected for the analysis. Similarity analysis, HCA and PCA all classified the 19 areas into three groups. Simultaneous quantification of the five major bioactive ingredients in the Epimedium samples was also carried out to confirm the consistency of the quality tests. These methods were successfully used to identify the geographical origin of the Epimedium samples and to evaluate their quality. Copyright © 2016 John Wiley & Sons, Ltd.

Exposure to a multi-level multi-component childhood obesity prevention community-randomized controlled trial: patterns, determinants, and implications.

PubMed

Trude, Angela Cristina Bizzotto; Kharmats, Anna Yevgenyevna; Jones-Smith, Jessica C; Gittelsohn, Joel

2018-05-22

For community interventions to be effective in real-world conditions, participants need to have sufficient exposure to the intervention. It is unclear how the dose and intensity of the intervention differ among study participants in low-income areas. We aimed to understand patterns of exposure to different components of a multi-level multi-component obesity prevention program to inform our future impact analyses. B'more Healthy Communities for Kids (BHCK) was a community-randomized controlled trial implemented in 28 low-income zones in Baltimore in two rounds (waves). Exposure to three different intervention components (corner store/carryout restaurants, social media/text messaging, and youth-led nutrition education) was assessed via post-intervention interviews with 385 low-income urban youths and their caregivers. Exposure scores were generated based on self-reported viewing of BHCK materials (posters, handouts, educational displays, and social media posts) and participating in activities, including taste tests during the intervention. For each intervention component, points were assigned for exposure to study materials and activities, then scaled (0-1 range), yielding an overall BHCK exposure score [youths: mean 1.1 (range 0-7.6 points); caregivers: 1.1 (0-6.7), possible highest score: 13]. Ordered logit regression analyses were used to investigate correlates of youths' and caregivers' exposure level (quartile of exposure). Mean intervention exposure scores were significantly higher for intervention than comparison youths (mean 1.6 vs 0.5, p < 0.001) and caregivers (mean 1.6 vs 0.6, p < 0.001). However, exposure scores were low in both groups and 10% of the comparison group was moderately exposed to the intervention. For each 1-year increase in age, there was a 33% lower odds of being highly exposed to the intervention (odds ratio 0.77, 95% confidence interval 0.69; 0.88) in the unadjusted and adjusted model controlling for youths' sex and household

Factor Analysis via Components Analysis

ERIC Educational Resources Information Center

Bentler, Peter M.; de Leeuw, Jan

2011-01-01

When the factor analysis model holds, component loadings are linear combinations of factor loadings, and vice versa. This interrelation permits us to define new optimization criteria and estimation methods for exploratory factor analysis. Although this article is primarily conceptual in nature, an illustrative example and a small simulation show…

MULTI-FREQUENCY, MULTI-EPOCH STUDY OF Mrk 501: HINTS FOR A TWO-COMPONENT NATURE OF THE EMISSION

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

Shukla, A.; Chitnis, V. R.; Singh, B. B.

2015-01-01

Since the detection of very high energy (VHE) γ-rays from Mrk 501, its broadband emission of radiation was mostly and quite effectively modeled using the one zone emission scenario. However, broadband spectral and flux variability studies enabled by the multi-wavelength campaigns carried out during the recent years have revealed the rather complex behavior of Mrk 501. The observed emission from Mrk 501 could be due to a complex superposition of multiple emission zones. Moreover, new evidence of detection of very hard intrinsic γ-ray spectra obtained from Fermi-LAT observations has challenged the theories about the origin of VHE γ-rays. Our studiesmore » based on Fermi-LAT data indicate the existence of two separate components in the spectrum, one for low-energy γ-rays and the other for high-energy γ-rays. Using multi-waveband data from several ground- and space-based instruments, in addition to HAGAR data, the spectral energy distribution of Mrk 501 is obtained for various flux states observed during 2011. In the present work, this observed broadband spectral energy distribution is reproduced with a leptonic, multi-zone synchrotron self-Compton (SSC) model.« less

Multi-component testing using HZ-PAN and AgZ-PAN Sorbents for OSPREY Model validation

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

Garn, Troy G.; Greenhalgh, Mitchell; Lyon, Kevin L.

2015-04-01

In efforts to further develop the capability of the Off-gas SeParation and RecoverY (OSPREY) model, multi-component tests were completed using both HZ-PAN and AgZ-PAN sorbents. The primary purpose of this effort was to obtain multi-component xenon and krypton capacities for comparison to future OSPREY predicted multi-component capacities using previously acquired Langmuir equilibrium parameters determined from single component isotherms. Experimental capacities were determined for each sorbent using two feed gas compositions of 1000 ppmv xenon and 150 ppmv krypton in either a helium or air balance. Test temperatures were consistently held at 220 K and the gas flowrate was 50 sccm.more » Capacities were calculated from breakthrough curves using TableCurve® 2D software by Jandel Scientific. The HZ-PAN sorbent was tested in the custom designed cryostat while the AgZ-PAN was tested in a newly installed cooling apparatus. Previous modeling validation efforts indicated the OSPREY model can be used to effectively predict single component xenon and krypton capacities for both engineered form sorbents. Results indicated good agreement with the experimental and predicted capacity values for both krypton and xenon on the sorbents. Overall, the model predicted slightly elevated capacities for both gases which can be partially attributed to the estimation of the parameters and the uncertainty associated with the experimental measurements. Currently, OSPREY is configured such that one species adsorbs and one does not (i.e. krypton in helium). Modification of OSPREY code is currently being performed to incorporate multiple adsorbing species and non-ideal interactions of gas phase species with the sorbent and adsorbed phases. Once these modifications are complete, the sorbent capacities determined in the present work will be used to validate OSPREY multicomponent adsorption predictions.« less

Multi-component analysis of tetracyclines, sulfonamides and tylosin in swine manure by liquid chromatography-tandem mass spectrometry.

PubMed

Jacobsen, Anne Marie; Halling-Sørensen, Bent

2006-03-01

A multi-component method focussing on thorough sample preparation has been developed for simultaneous analysis of swine manure for three classes of antibiotic-tetracyclines, sulfonamides, and tylosin. Liquid manure was initially freeze-dried and homogenised by pulverization before extraction by pressurised liquid extraction. The extraction was performed at 75 degrees C and 2,500 psig in three steps using two cycles with 0.2 mol L(-1) citric acid buffer (pH 4.7) and one cycle with a mixture of 80% methanol with 0.2 mol L(-1) citric acid (pH 3). After liquid-liquid extraction with heptane to remove lipids, the pH of the manure was adjusted to 3 with formic acid and the sample was vacuum-filtered through 0.6 mum glass-fibre filters. Finally the samples were pre-concentrated by tandem SPE (SAX-HLB). Recoveries were determined for manure samples spiked at three concentrations (50-5,000 microg kg(-1) dry matter); quantification was achieved by matrix-matched calibration. Recoveries were >70% except for oxytetracycline (42-54%), sulfadiazine (59-73%), and tylosin (9-35%) and did not vary with concentration or from day-to-day. Limits of quantification (LOQ) for all compounds, determined as a signal-to-noise ratio of 10, were in the range 10-100 microg kg(-1) dry matter. The suitability of the method was assessed by analysis of swine manure samples from six different pig-production sites, e.g. finishing pigs, sows, or mixed production. Residues of antibiotics were detected in all samples. The largest amounts were found for tetracyclines (up to 30 mg kg(-1) dry matter for the sum of CTC and ECTC). Sulfonamides were detected at concentrations up to 2 mg kg(-1) dry matter (SDZ); tylosin was not detected in any samples.

Efficient and robust relaxation procedures for multi-component mixtures including phase transition

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

Han, Ee, E-mail: eehan@math.uni-bremen.de; Hantke, Maren, E-mail: maren.hantke@ovgu.de; Müller, Siegfried, E-mail: mueller@igpm.rwth-aachen.de

We consider a thermodynamic consistent multi-component model in multi-dimensions that is a generalization of the classical two-phase flow model of Baer and Nunziato. The exchange of mass, momentum and energy between the phases is described by additional source terms. Typically these terms are handled by relaxation procedures. Available relaxation procedures suffer from efficiency and robustness resulting in very costly computations that in general only allow for one-dimensional computations. Therefore we focus on the development of new efficient and robust numerical methods for relaxation processes. We derive exact procedures to determine mechanical and thermal equilibrium states. Further we introduce a novelmore » iterative method to treat the mass transfer for a three component mixture. All new procedures can be extended to an arbitrary number of inert ideal gases. We prove existence, uniqueness and physical admissibility of the resulting states and convergence of our new procedures. Efficiency and robustness of the procedures are verified by means of numerical computations in one and two space dimensions. - Highlights: • We develop novel relaxation procedures for a generalized, thermodynamically consistent Baer–Nunziato type model. • Exact procedures for mechanical and thermal relaxation procedures avoid artificial parameters. • Existence, uniqueness and physical admissibility of the equilibrium states are proven for special mixtures. • A novel iterative method for mass transfer is introduced for a three component mixture providing a unique and admissible equilibrium state.« less

Pilot study of a mindfulness-based, multi-component, in-school group sleep intervention in adolescent girls.

PubMed

Bei, Bei; Byrne, Michelle L; Ivens, Clare; Waloszek, Joanna; Woods, Michael J; Dudgeon, Paul; Murray, Greg; Nicholas, Christian L; Trinder, John; Allen, Nicholas B

2013-05-01

Existing literature links poor sleep and anxiety symptoms in adolescents. This pilot study aimed to develop a practical method through which a program to improve sleep could reach adolescents in need and to examine the feasibility of a mindfulness-based, multi-component group sleep intervention using sleep and anxiety as outcome measures. Sixty-two grade 9 students (aged 13-15) at a girls' school were screened with the Pittsburgh Sleep Quality Index (PSQI) and Spence Children's Anxiety Scale (SCAS). Ten participants with self-reported poor sleep were enrolled into a six-session program based on Bootzin & Stevens, with added stress/anxiety-specific components. Sessions covered key aspects of basic mindfulness concepts and practice, sleep hygiene, sleep scheduling, evening/daytime habits, stimulus control, skills for bedtime worries and healthy attitudes to sleep. Treatment changes were measured by pre-post scores on the PSQI, SCAS and 7-day actigraphy-measured sleep. The program demonstrated high acceptability, with a completion rate of 90%. Based on effect-size analysis, participants showed significant improvement on objective sleep onset latency (SOL), sleep efficiency and total sleep time; actigraphy data also showed significantly earlier bedtime, rise time and smaller day-to-day bedtime variation. Post-intervention global PSQI scores were significantly lower than that of pre-intervention, with significant improvement in subjective SOL, sleep quality and sleep-related daytime dysfunction. There were small improvements on some subscales of the SCAS, but change on its total score was minimal. A mindfulness-based, multi-component, in-school group sleep intervention following brief screening is feasible, and has the potential to improve sleep. Its impact on anxiety needs further investigation. © 2012 Wiley Publishing Asia Pty Ltd.

Darboux transformation of the coupled nonisospectral Gross-Pitaevskii system and its multi-component generalization

NASA Astrophysics Data System (ADS)

Xu, Tao; Chen, Yong

2018-04-01

In this paper, we extend the one-component Gross-Pitaevskii (GP) equation to the two-component coupled GP system including damping term, linear and parabolic density profiles. The Lax pair with nonisospectral parameter and infinitely-many conservation laws of this coupled GP system are presented. Actually, the Darboux transformation (DT) for this kind of nonautonomous system is essentially different from the autonomous case. Consequently, we construct the DT of the coupled GP equations, besides, nonautonomous multi-solitons, one-breather and the first-order rogue wave are also obtained. Various kinds of one-soliton solution are constructed, which include stationary one-soliton and nonautonomous one-soliton propagating along the negative (positive) direction of x-axis. The interaction of two solitons and two-soliton bound state are demonstrated respectively. We get the nonautonomous one-breather on a curved background and this background is completely controlled by the parameter β. Using a limiting process, the nonautonomous first-order rogue wave can be obtained. Furthermore, some dynamic structures of these analytical solutions are discussed in detail. In addition, the multi-component generalization of GP equations are given, then the corresponding Lax pair and DT are also constructed.

MultiMetEval: Comparative and Multi-Objective Analysis of Genome-Scale Metabolic Models

PubMed Central

Gevorgyan, Albert; Kierzek, Andrzej M.; Breitling, Rainer; Takano, Eriko

2012-01-01

Comparative metabolic modelling is emerging as a novel field, supported by the development of reliable and standardized approaches for constructing genome-scale metabolic models in high throughput. New software solutions are needed to allow efficient comparative analysis of multiple models in the context of multiple cellular objectives. Here, we present the user-friendly software framework Multi-Metabolic Evaluator (MultiMetEval), built upon SurreyFBA, which allows the user to compose collections of metabolic models that together can be subjected to flux balance analysis. Additionally, MultiMetEval implements functionalities for multi-objective analysis by calculating the Pareto front between two cellular objectives. Using a previously generated dataset of 38 actinobacterial genome-scale metabolic models, we show how these approaches can lead to exciting novel insights. Firstly, after incorporating several pathways for the biosynthesis of natural products into each of these models, comparative flux balance analysis predicted that species like Streptomyces that harbour the highest diversity of secondary metabolite biosynthetic gene clusters in their genomes do not necessarily have the metabolic network topology most suitable for compound overproduction. Secondly, multi-objective analysis of biomass production and natural product biosynthesis in these actinobacteria shows that the well-studied occurrence of discrete metabolic switches during the change of cellular objectives is inherent to their metabolic network architecture. Comparative and multi-objective modelling can lead to insights that could not be obtained by normal flux balance analyses. MultiMetEval provides a powerful platform that makes these analyses straightforward for biologists. Sources and binaries of MultiMetEval are freely available from https://github.com/PiotrZakrzewski/MetEval/downloads. PMID:23272111

Experimental Researches on the Durability Indicators and the Physiological Comfort of Fabrics using the Principal Component Analysis (PCA) Method

NASA Astrophysics Data System (ADS)

Hristian, L.; Ostafe, M. M.; Manea, L. R.; Apostol, L. L.

2017-06-01

The work pursued the distribution of combed wool fabrics destined to manufacturing of external articles of clothing in terms of the values of durability and physiological comfort indices, using the mathematical model of Principal Component Analysis (PCA). Principal Components Analysis (PCA) applied in this study is a descriptive method of the multivariate analysis/multi-dimensional data, and aims to reduce, under control, the number of variables (columns) of the matrix data as much as possible to two or three. Therefore, based on the information about each group/assortment of fabrics, it is desired that, instead of nine inter-correlated variables, to have only two or three new variables called components. The PCA target is to extract the smallest number of components which recover the most of the total information contained in the initial data.

Provenance Establishment of Stingless Bee Honey Using Multi-element Analysis in Combination with Chemometrics Techniques.

PubMed

Shadan, Aidil Fahmi; Mahat, Naji A; Wan Ibrahim, Wan Aini; Ariffin, Zaiton; Ismail, Dzulkiflee

2018-01-01

As consumption of stingless bee honey has been gaining popularity in many countries including Malaysia, ability to identify accurately its geographical origin proves pertinent for investigating fraudulent activities for consumer protection. Because a chemical signature can be location-specific, multi-element distribution patterns may prove useful for provenancing such product. Using the inductively coupled-plasma optical emission spectrometer as well as principal component analysis (PCA) and linear discriminant analysis (LDA), the distributions of multi-elements in stingless bee honey collected at four different geographical locations (North, West, East, and South) in Johor, Malaysia, were investigated. While cross-validation using PCA demonstrated 87.0% correct classification rate, the same was improved (96.2%) with the use of LDA, indicating that discrimination was possible for the different geographical regions. Therefore, utilization of multi-element analysis coupled with chemometrics techniques for assigning the provenance of stingless bee honeys for forensic applications is supported. © 2017 American Academy of Forensic Sciences.

Extension of lattice Boltzmann flux solver for simulation of compressible multi-component flows

NASA Astrophysics Data System (ADS)

Yang, Li-Ming; Shu, Chang; Yang, Wen-Ming; Wang, Yan

2018-05-01

The lattice Boltzmann flux solver (LBFS), which was presented by Shu and his coworkers for solving compressible fluid flow problems, is extended to simulate compressible multi-component flows in this work. To solve the two-phase gas-liquid problems, the model equations with stiffened gas equation of state are adopted. In this model, two additional non-conservative equations are introduced to represent the material interfaces, apart from the classical Euler equations. We first convert the interface equations into the full conservative form by applying the mass equation. After that, we calculate the numerical fluxes of the classical Euler equations by the existing LBFS and the numerical fluxes of the interface equations by the passive scalar approach. Once all the numerical fluxes at the cell interface are obtained, the conservative variables at cell centers can be updated by marching the equations in time and the material interfaces can be identified via the distributions of the additional variables. The numerical accuracy and stability of present scheme are validated by its application to several compressible multi-component fluid flow problems.

The Multi-component X-ray Emission of 3C 273

NASA Astrophysics Data System (ADS)

Soldi, S.; Türler, M.; Paltani, S.; Courvoisier, T. J.-L.

2009-05-01

3C 273 is the brightest quasar in the sky and among the most extensively observed and studied AGN, therefore one of the most suitable targets for a long-term, multi-frequency study. The superposition of a thermal Comptonisation component, similar to that observed in Seyfert galaxies, and of a non-thermal component, related to the jet emission, seems to explain some of the spectral and timing properties of the X-ray emission of 3C 273. Yet, during some observations this dichotomy has not been observed and the variability properties could also be consistent with a single-component scenario, characterised by two parameters varying independently. In order to understand the nature of the X-ray emission in 3C 273, a series of observations up to 80-100 keV, possibly catching the source in different flux states, are essential. Simbol-X will be able to study the emission of 3C 273 in the broad 0.5-80 keV band with high sensitivity, allowing us to disentangle the emission from different spectral components, with 20-30 ks long observations. In addition, the shape and the origin of the high-energy emission of this quasar will be further constrained thanks to the AGILE and Fermi satellites, monitoring the γ-ray sky in the MeV-GeV energy domain.

Design considerations for multi component molecular-polymeric nonlinear optical materials

NASA Astrophysics Data System (ADS)

Singer, K. D.; Kuzyk, M. G.; Fang, T.; Holland, W. R.; Cahill, P. A.

1990-08-01

We review our work on multi component polymeric nonlinear optical materials. These materials consist of nonlinear optical molecules incorporated in a polymeric host. A cross-linked triazine polymer incorporating a dicyanovinyl terminated azo dye was found to be relatively stable at 85 deg and possess an electro-optic coefficient of 11pm/V. We have also observed the zero dispersion condition in a new anomalous dispersion dye for phase matched second harmonic generation, and expect efficient conversion to the blue. A squarylium dye, ISQ, has been found to possess a large third order nonlinearity, and may display two-level behavior.

3D Printing Multi-Functionality: Embedded RF Antennas and Components

NASA Technical Reports Server (NTRS)

Shemelya, C. M.; Zemba, M.; Liang, M.; Espalin, D.; Kief, C.; Xin, H.; Wicker, R. B.; MacDonald, E. W.

2015-01-01

Significant research and press has recently focused on the fabrication freedom of Additive Manufacturing (AM) to create both conceptual models and final end-use products. This flexibility allows design modifications to be immediately reflected in 3D printed structures, creating new paradigms within the manufacturing process. 3D printed products will inevitably be fabricated locally, with unit-level customization, optimized to unique mission requirements. However, for the technology to be universally adopted, the processes must be enhanced to incorporate additional technologies; such as electronics, actuation, and electromagnetics. Recently, a novel 3D printing platform, Multi3D manufacturing, was funded by the presidential initiative for revitalizing manufacturing in the USA using 3D printing (America Makes - also known as the National Additive Manufacturing Innovation Institute). The Multi3D system specifically targets 3D printed electronics in arbitrary form; and building upon the potential of this system, this paper describes RF antennas and components fabricated through the integration of material extrusion 3D printing with embedded wire, mesh, and RF elements.

Intracellular self-assembly based multi-labeling of key viral components: Envelope, capsid and nucleic acids.

PubMed

Wen, Li; Lin, Yi; Zhang, Zhi-Ling; Lu, Wen; Lv, Cheng; Chen, Zhi-Liang; Wang, Han-Zhong; Pang, Dai-Wen

2016-08-01

Envelope, capsid and nucleic acids are key viral components that are all involved in crucial events during virus infection. Thus simultaneous labeling of these key components is an indispensable prerequisite for monitoring comprehensive virus infection process and dissecting virus infection mechanism. Baculovirus was genetically tagged with biotin on its envelope protein GP64 and enhanced green fluorescent protein (EGFP) on its capsid protein VP39. Spodoptera frugiperda 9 (Sf9) cells were infected by the recombinant baculovirus and subsequently fed with streptavidin-conjugated quantum dots (SA-QDs) and cell-permeable nucleic acids dye SYTO 82. Just by genetic engineering and virus propagation, multi-labeling of envelope, capsid and nucleic acids was spontaneously accomplished during virus inherent self-assembly process, significantly simplifying the labeling process while maintaining virus infectivity. Intracellular dissociation and transportation of all the key viral components, which was barely reported previously, was real-time monitored based on the multi-labeling approach, offering opportunities for deeply understanding virus infection and developing anti-virus treatment. Copyright © 2016 Elsevier Ltd. All rights reserved.

Spin-labelled diketopiperazines and peptide-peptoid chimera by Ugi-multi-component-reactions.

PubMed

Sultani, Haider N; Haeri, Haleh H; Hinderberger, Dariush; Westermann, Bernhard

2016-12-28

For the first time, spin-labelled coumpounds have been obtained by isonitrile-based multi component reactions (IMCRs). The typical IMCR Ugi-protocols offer a simple experimental setup allowing structural variety by which labelled diketopiperazines (DKPs) and peptide-peptoid chimera have been synthesized. The reaction keeps the paramagnetic spin label intact and offers a simple and versatile route to a large variety of new and chemically diverse spin labels.

Independent Component Analysis-motivated Approach to Classificatory Decomposition of Cortical Evoked Potentials

PubMed Central

Smolinski, Tomasz G; Buchanan, Roger; Boratyn, Grzegorz M; Milanova, Mariofanna; Prinz, Astrid A

2006-01-01

Background Independent Component Analysis (ICA) proves to be useful in the analysis of neural activity, as it allows for identification of distinct sources of activity. Applied to measurements registered in a controlled setting and under exposure to an external stimulus, it can facilitate analysis of the impact of the stimulus on those sources. The link between the stimulus and a given source can be verified by a classifier that is able to "predict" the condition a given signal was registered under, solely based on the components. However, the ICA's assumption about statistical independence of sources is often unrealistic and turns out to be insufficient to build an accurate classifier. Therefore, we propose to utilize a novel method, based on hybridization of ICA, multi-objective evolutionary algorithms (MOEA), and rough sets (RS), that attempts to improve the effectiveness of signal decomposition techniques by providing them with "classification-awareness." Results The preliminary results described here are very promising and further investigation of other MOEAs and/or RS-based classification accuracy measures should be pursued. Even a quick visual analysis of those results can provide an interesting insight into the problem of neural activity analysis. Conclusion We present a methodology of classificatory decomposition of signals. One of the main advantages of our approach is the fact that rather than solely relying on often unrealistic assumptions about statistical independence of sources, components are generated in the light of a underlying classification problem itself. PMID:17118151

Visualization techniques to aid in the analysis of multi-spectral astrophysical data sets

NASA Technical Reports Server (NTRS)

Brugel, Edward W.; Domik, Gitta O.; Ayres, Thomas R.

1993-01-01

The goal of this project was to support the scientific analysis of multi-spectral astrophysical data by means of scientific visualization. Scientific visualization offers its greatest value if it is not used as a method separate or alternative to other data analysis methods but rather in addition to these methods. Together with quantitative analysis of data, such as offered by statistical analysis, image or signal processing, visualization attempts to explore all information inherent in astrophysical data in the most effective way. Data visualization is one aspect of data analysis. Our taxonomy as developed in Section 2 includes identification and access to existing information, preprocessing and quantitative analysis of data, visual representation and the user interface as major components to the software environment of astrophysical data analysis. In pursuing our goal to provide methods and tools for scientific visualization of multi-spectral astrophysical data, we therefore looked at scientific data analysis as one whole process, adding visualization tools to an already existing environment and integrating the various components that define a scientific data analysis environment. As long as the software development process of each component is separate from all other components, users of data analysis software are constantly interrupted in their scientific work in order to convert from one data format to another, or to move from one storage medium to another, or to switch from one user interface to another. We also took an in-depth look at scientific visualization and its underlying concepts, current visualization systems, their contributions, and their shortcomings. The role of data visualization is to stimulate mental processes different from quantitative data analysis, such as the perception of spatial relationships or the discovery of patterns or anomalies while browsing through large data sets. Visualization often leads to an intuitive understanding of the

Human Immunity and the Design of Multi-Component, Single Target Vaccines

PubMed Central

Saul, Allan; Fay, Michael P.

2007-01-01

Background Inclusion of multiple immunogens to target a single organism is a strategy being pursued for many experimental vaccines, especially where it is difficult to generate a strongly protective response from a single immunogen. Although there are many human vaccines that contain multiple defined immunogens, in almost every case each component targets a different pathogen. As a consequence, there is little practical experience for deciding where the increased complexity of vaccines with multiple defined immunogens vaccines targeting single pathogens will be justifiable. Methodology/Principal Findings A mathematical model, with immunogenicity parameters derived from a database of human responses to established vaccines, was used to predict the increase in the efficacy and the proportion of the population protected resulting from addition of further immunogens. The gains depended on the relative protection and the range of responses in the population to each immunogen and also to the correlation of the responses between immunogens. In most scenarios modeled, the gain in overall efficacy obtained by adding more immunogens was comparable to gains obtained from a single immunogen through the use of better formulations or adjuvants. Multi-component single target vaccines were more effective at decreasing the proportion of poor responders than increasing the overall efficacy of the vaccine in a population. Conclusions/Significance Inclusion of limited number of antigens in a vaccine aimed at targeting a single organism will increase efficacy, but the gains are relatively modest and for a practical vaccine there are constraints that are likely to limit multi-component single target vaccines to a small number of key antigens. The model predicts that this type of vaccine will be most useful where the critical issue is the reduction in proportion of poor responders. PMID:17786221

Body composition analysis: Cellular level modeling of body component ratios.

PubMed

Wang, Z; Heymsfield, S B; Pi-Sunyer, F X; Gallagher, D; Pierson, R N

2008-01-01

During the past two decades, a major outgrowth of efforts by our research group at St. Luke's-Roosevelt Hospital is the development of body composition models that include cellular level models, models based on body component ratios, total body potassium models, multi-component models, and resting energy expenditure-body composition models. This review summarizes these models with emphasis on component ratios that we believe are fundamental to understanding human body composition during growth and development and in response to disease and treatments. In-vivo measurements reveal that in healthy adults some component ratios show minimal variability and are relatively 'stable', for example total body water/fat-free mass and fat-free mass density. These ratios can be effectively applied for developing body composition methods. In contrast, other ratios, such as total body potassium/fat-free mass, are highly variable in vivo and therefore are less useful for developing body composition models. In order to understand the mechanisms governing the variability of these component ratios, we have developed eight cellular level ratio models and from them we derived simplified models that share as a major determining factor the ratio of extracellular to intracellular water ratio (E/I). The E/I value varies widely among adults. Model analysis reveals that the magnitude and variability of each body component ratio can be predicted by correlating the cellular level model with the E/I value. Our approach thus provides new insights into and improved understanding of body composition ratios in adults.

Multi-component dark matter through a radiative Higgs portal

DOE PAGES

DiFranzo, Anthony; Univ. of California, Irvine, CA; Rutgers Univ., Piscataway, NJ; ...

2017-01-18

Here, we study a multi-component dark matter model where interactions with the Standard Model are primarily via the Higgs boson. The model contains vector-like fermions charged undermore » $$SU(2)_W \\times U(1)_Y$$ and under the dark gauge group, $$U(1)^\\prime$$. This results in two dark matter candidates. A spin-1 and a spin-1/2 candidate, which have loop and tree-level couplings to the Higgs, respectively. We explore the resulting effect on the dark matter relic abundance, while also evaluating constraints on the Higgs invisible width and from direct detection experiments. Generally, we find that this model is highly constrained when the fermionic candidate is the predominant fraction of the dark matter relic abundance.« less

Impact of multi-component diffusion in turbulent combustion using direct numerical simulations

DOE PAGES

Bruno, Claudio; Sankaran, Vaidyanathan; Kolla, Hemanth; ...

2015-08-28

This study presents the results of DNS of a partially premixed turbulent syngas/air flame at atmospheric pressure. The objective was to assess the importance and possible effects of molecular transport on flame behavior and structure. To this purpose DNS were performed at with two proprietary DNS codes and with three different molecular diffusion transport models: fully multi-component, mixture averaged, and imposing the Lewis number of all species to be unity.

Numerical Analysis of Deflections of Multi-Layered Beams

NASA Astrophysics Data System (ADS)

Biliński, Tadeusz; Socha, Tomasz

2015-03-01

The paper concerns the rheological bending problem of wooden beams reinforced with embedded composite bars. A theoretical model of the behaviour of a multi-layered beam is presented. The component materials of this beam are described with equations for the linear viscoelastic five-parameter rheological model. Two numerical analysis methods for the long-term response of wood structures are presented. The first method has been developed with SCILAB software. The second one has been developed with the finite element calculation software ABAQUS and user subroutine UMAT. Laboratory investigations were conducted on sample beams of natural dimensions in order to validate the proposed theoretical model and verify numerical simulations. Good agreement between experimental measurements and numerical results is observed.

CO Component Estimation Based on the Independent Component Analysis

NASA Astrophysics Data System (ADS)

Ichiki, Kiyotomo; Kaji, Ryohei; Yamamoto, Hiroaki; Takeuchi, Tsutomu T.; Fukui, Yasuo

2014-01-01

Fast Independent Component Analysis (FastICA) is a component separation algorithm based on the levels of non-Gaussianity. Here we apply FastICA to the component separation problem of the microwave background, including carbon monoxide (CO) line emissions that are found to contaminate the PLANCK High Frequency Instrument (HFI) data. Specifically, we prepare 100 GHz, 143 GHz, and 217 GHz mock microwave sky maps, which include galactic thermal dust, NANTEN CO line, and the cosmic microwave background (CMB) emissions, and then estimate the independent components based on the kurtosis. We find that FastICA can successfully estimate the CO component as the first independent component in our deflection algorithm because its distribution has the largest degree of non-Gaussianity among the components. Thus, FastICA can be a promising technique to extract CO-like components without prior assumptions about their distributions and frequency dependences.

CO component estimation based on the independent component analysis

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

Ichiki, Kiyotomo; Kaji, Ryohei; Yamamoto, Hiroaki

2014-01-01

Fast Independent Component Analysis (FastICA) is a component separation algorithm based on the levels of non-Gaussianity. Here we apply FastICA to the component separation problem of the microwave background, including carbon monoxide (CO) line emissions that are found to contaminate the PLANCK High Frequency Instrument (HFI) data. Specifically, we prepare 100 GHz, 143 GHz, and 217 GHz mock microwave sky maps, which include galactic thermal dust, NANTEN CO line, and the cosmic microwave background (CMB) emissions, and then estimate the independent components based on the kurtosis. We find that FastICA can successfully estimate the CO component as the first independentmore » component in our deflection algorithm because its distribution has the largest degree of non-Gaussianity among the components. Thus, FastICA can be a promising technique to extract CO-like components without prior assumptions about their distributions and frequency dependences.« less

Principal Components Analysis Studies of Martian Clouds

NASA Astrophysics Data System (ADS)

Klassen, D. R.; Bell, J. F., III

2001-11-01

We present the principal components analysis (PCA) of absolutely calibrated multi-spectral images of Mars as a function of Martian season. The PCA technique is a mathematical rotation and translation of the data from a brightness/wavelength space to a vector space of principal ``traits'' that lie along the directions of maximal variance. The first of these traits, accounting for over 90% of the data variance, is overall brightness and represented by an average Mars spectrum. Interpretation of the remaining traits, which account for the remaining ~10% of the variance, is not always the same and depends upon what other components are in the scene and thus, varies with Martian season. For example, during seasons with large amounts of water ice in the scene, the second trait correlates with the ice and anti-corrlates with temperature. We will investigate the interpretation of the second, and successive important PCA traits. Although these PCA traits are orthogonal in their own vector space, it is unlikely that any one trait represents a singular, mineralogic, spectral end-member. It is more likely that there are many spectral endmembers that vary identically to within the noise level, that the PCA technique will not be able to distinguish them. Another possibility is that similar absorption features among spectral endmembers may be tied to one PCA trait, for example ''amount of 2 \\micron\\ absorption''. We thus attempt to extract spectral endmembers by matching linear combinations of the PCA traits to USGS, JHU, and JPL spectral libraries as aquired through the JPL Aster project. The recovered spectral endmembers are then linearly combined to model the multi-spectral image set. We present here the spectral abundance maps of the water ice/frost endmember which allow us to track Martian clouds and ground frosts. This work supported in part through NASA Planetary Astronomy Grant NAG5-6776. All data gathered at the NASA Infrared Telescope Facility in collaboration with

DARHT Multi-intelligence Seismic and Acoustic Data Analysis

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

Stevens, Garrison Nicole; Van Buren, Kendra Lu; Hemez, Francois M.

The purpose of this report is to document the analysis of seismic and acoustic data collected at the Dual-Axis Radiographic Hydrodynamic Test (DARHT) facility at Los Alamos National Laboratory for robust, multi-intelligence decision making. The data utilized herein is obtained from two tri-axial seismic sensors and three acoustic sensors, resulting in a total of nine data channels. The goal of this analysis is to develop a generalized, automated framework to determine internal operations at DARHT using informative features extracted from measurements collected external of the facility. Our framework involves four components: (1) feature extraction, (2) data fusion, (3) classification, andmore » finally (4) robustness analysis. Two approaches are taken for extracting features from the data. The first of these, generic feature extraction, involves extraction of statistical features from the nine data channels. The second approach, event detection, identifies specific events relevant to traffic entering and leaving the facility as well as explosive activities at DARHT and nearby explosive testing sites. Event detection is completed using a two stage method, first utilizing signatures in the frequency domain to identify outliers and second extracting short duration events of interest among these outliers by evaluating residuals of an autoregressive exogenous time series model. Features extracted from each data set are then fused to perform analysis with a multi-intelligence paradigm, where information from multiple data sets are combined to generate more information than available through analysis of each independently. The fused feature set is used to train a statistical classifier and predict the state of operations to inform a decision maker. We demonstrate this classification using both generic statistical features and event detection and provide a comparison of the two methods. Finally, the concept of decision robustness is presented through a preliminary

Furnace Cyclic Oxidation Behavior of Multi-Component Low Conductivity Thermal Barrier Coatings

NASA Technical Reports Server (NTRS)

Zhu, Dong-Ming; Nesbitt, James A.; Barrett, Charles A.; McCue, Terry R.; Miller, Robert A.

2004-01-01

Ceramic thermal barrier coatings will play an increasingly important role in advanced gas turbine engines because of their ability to further increase engine operating temperatures and reduce cooling, thus helping achieve future engine low emission, high efficiency and improved reliability goals. Advanced multi-component zirconia-based thermal barrier coatings are being developed using an oxide defect clustering design approach to achieve the required coating low thermal conductivity and high temperature stability. Although the new composition coatings were not yet optimized for cyclic durability, an initial durability screening of the candidate coating materials was conducted using conventional furnace cyclic oxidation tests. In this paper, furnace cyclic oxidation behavior of plasma-sprayed zirconia-based defect cluster thermal barrier coatings was investigated at 1163 C using 45 min hot cycles. The ceramic coating failure mechanisms were studied using scanning electron microscopy (SEM) combined with X-ray diffraction (XRD) phase analysis after the furnace tests. The coating cyclic lifetime is also discussed in relation to coating processing, phase structures, dopant concentration, and other thermo-physical properties.

Examining multi-component DNA-templated nanostructures as imaging agents

NASA Astrophysics Data System (ADS)

Jaganathan, Hamsa

2011-12-01

Magnetic resonance imaging (MRI) is the leading non-invasive tool for disease imaging and diagnosis. Although MRI exhibits high spatial resolution for anatomical features, the contrast resolution is low. Imaging agents serve as an aid to distinguish different types of tissues within images. Gadolinium chelates, which are considered first generation designs, can be toxic to health, while ultra-small, superparamagnetic nanoparticles (NPs) have low tissue-targeting efficiency and rapid bio-distribution, resulting to an inadequate detection of the MRI signal and enhancement of image contrast. In order to improve the utility of MRI agents, the challenge in composition and structure needs to be addressed. One-dimensional (1D), superparamagnetic nanostructures have been reported to enhance magnetic and in vivo properties and therefore has a potential to improve contrast enhancement in MRI images. In this dissertation, the structure of 1D, multi-component NP chains, scaffolded on DNA, were pre-clinically examined as potential MRI agents. First, research was focused on characterizing and understanding the mechanism of proton relaxation for DNA-templated NP chains using nuclear magnetic resonance (NMR) spectrometry. Proton relaxation and transverse relaxivity were higher in multi-component NP chains compared to disperse NPs, indicating the arrangement of NPs on a 1D structure improved proton relaxation sensitivity. Second, in vitro evaluation for potential issues in toxicity and contrast efficiency in tissue environments using a 3 Tesla clinical MRI scanner was performed. Cell uptake of DNA-templated NP chains was enhanced after encapsulating the nanostructure with layers of polyelectrolytes and targeting ligands. Compared to dispersed NPs, DNA-templated NP chains improved MRI contrast in both the epithelial basement membrane and colon cancer tumors scaffolds. The last part of the project was focused on developing a novel MRI agent that detects changes in DNA methylation

Side draw control design for a high purity multi-component distillation column.

PubMed

A Udugama, Isuru; Munir, M T; Kirkpatrick, Rob; Young, Brent R; Yu, Wei

2018-05-01

Industrial methanol production involves a multi component feed containing methanol, water and trace levels of ethanol being refined to produce AA grade methanol at high product recovery. Due to practical constraints, the bottoms discharge of the column is primarily water with only trace of methanol impurities. As a result of these constraints, ethanol, which is a non-key middle boiling component gets "trapped" near the side draw of the column forming an ethanol bulge, which in turn results in non-linear, inverse, time and state varying behaviour of the side draw ethanol composition. In this work, we established that the existence of the ethanol bulge creates the complex process behaviour of the side draw ethanol composition and that this bulge needs to be explicitly controlled. This type of explicit composition bulge analysis and subsequent control has not been attempted on methanol distillation columns before. For this purpose a novel, robust and practical side draw control scheme to detect and remedy the excess ethanol bulge movement using override control is presented. The side draw controller, together with other regulatory controllers is shown to maintain on-specification operations of the column. Disturbance rejection tests carried out illustrate that the side draw control scheme will keep the column operating within commercial specification. It is also shown that a traditional DV control structure is unable to achieve this objective. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Optical design of multi-multiple expander structure of laser gas analysis and measurement device

NASA Astrophysics Data System (ADS)

Fu, Xiang; Wei, Biao

2018-03-01

The installation and debugging of optical circuit structure in the application of carbon monoxide distributed laser gas analysis and measurement, there are difficult key technical problems. Based on the three-component expansion theory, multi-multiple expander structure with expansion ratio of 4, 5, 6 and 7 is adopted in the absorption chamber to enhance the adaptability of the installation environment of the gas analysis and measurement device. According to the basic theory of aberration, the optimal design of multi-multiple beam expander structure is carried out. By using image quality evaluation method, the difference of image quality under different magnifications is analyzed. The results show that the optical quality of the optical system with the expanded beam structure is the best when the expansion ratio is 5-7.

Multi-Velocity Component LDV

NASA Technical Reports Server (NTRS)

Johnson, Dennis A. (Inventor)

1996-01-01

A laser doppler velocimeter uses frequency shifting of a laser beam to provide signal information for each velocity component. A composite electrical signal generated by a light detector is digitized and a processor produces a discrete Fourier transform based on the digitized electrical signal. The transform includes two peak frequencies corresponding to the two velocity components.

Segmented frequency-domain fluorescence lifetime measurements: minimizing the effects of photobleaching within a multi-component system.

PubMed

Marwani, Hadi M; Lowry, Mark; Keating, Patrick; Warner, Isiah M; Cook, Robert L

2007-11-01

This study introduces a newly developed frequency segmentation and recombination method for frequency-domain fluorescence lifetime measurements to address the effects of changing fractional contributions over time and minimize the effects of photobleaching within multi-component systems. Frequency segmentation and recombination experiments were evaluated using a two component system consisting of fluorescein and rhodamine B. Comparison of experimental data collected in traditional and segmented fashion with simulated data, generated using different changing fractional contributions, demonstrated the validity of the technique. Frequency segmentation and recombination was also applied to a more complex system consisting of pyrene with Suwannee River fulvic acid reference and was shown to improve recovered lifetimes and fractional intensity contributions. It was observed that photobleaching in both systems led to errors in recovered lifetimes which can complicate the interpretation of lifetime results. Results showed clear evidence that the frequency segmentation and recombination method reduced errors resulting from a changing fractional contribution in a multi-component system, and allowed photobleaching issues to be addressed by commercially available instrumentation.

Improving the psychosocial work environment at multi-ethnic workplaces: a multi-component intervention strategy in the cleaning industry.

PubMed

Smith, Louise Hardman; Hviid, Kirsten; Frydendall, Karen Bo; Flyvholm, Mari-Ann

2013-10-14

Global labour migration has increased in recent years and immigrant workers are often recruited into low status and low paid jobs such as cleaning. Research in a Danish context shows that immigrants working in the cleaning industry often form social networks based on shared languages and backgrounds, and that conflict between different ethnic groups may occur. This paper evaluates the impact of a multi-component intervention on the psychosocial work environment at a multi-ethnic Danish workplace in the cleaning sector. The intervention included Danish lessons, vocational training courses, and activities to improve collaboration across different groups of cleaners. Interviews about the outcome of the intervention were conducted with the cleaners and their supervisor. The Copenhagen Psychosocial Questionnaire was used as a supplement to the interviews. The results suggest that the psychosocial work environment had improved after the intervention. According to the interviews with the cleaners, the intervention had led to improved communication, trust, and collaboration. These findings are supported by the questionnaire where social support from supervisor and colleagues, social community, trust, and teamwork seem to have improved together with meaning of work, rewards, and emotional demands. The design of the intervention may provide inspiration for future psychosocial work environment interventions at multi-ethnic work places.

Improving the Psychosocial Work Environment at Multi-Ethnic Workplaces: A Multi-Component Intervention Strategy in the Cleaning Industry

PubMed Central

Smith, Louise Hardman; Hviid, Kirsten; Frydendall, Karen Bo; Flyvholm, Mari-Ann

2013-01-01

Global labour migration has increased in recent years and immigrant workers are often recruited into low status and low paid jobs such as cleaning. Research in a Danish context shows that immigrants working in the cleaning industry often form social networks based on shared languages and backgrounds, and that conflict between different ethnic groups may occur. This paper evaluates the impact of a multi-component intervention on the psychosocial work environment at a multi-ethnic Danish workplace in the cleaning sector. The intervention included Danish lessons, vocational training courses, and activities to improve collaboration across different groups of cleaners. Interviews about the outcome of the intervention were conducted with the cleaners and their supervisor. The Copenhagen Psychosocial Questionnaire was used as a supplement to the interviews. The results suggest that the psychosocial work environment had improved after the intervention. According to the interviews with the cleaners, the intervention had led to improved communication, trust, and collaboration. These findings are supported by the questionnaire where social support from supervisor and colleagues, social community, trust, and teamwork seem to have improved together with meaning of work, rewards, and emotional demands. The design of the intervention may provide inspiration for future psychosocial work environment interventions at multi-ethnic work places. PMID:24129115

Derivation of Boundary Manikins: A Principal Component Analysis

NASA Technical Reports Server (NTRS)

Young, Karen; Margerum, Sarah; Barr, Abbe; Ferrer, Mike A.; Rajulu, Sudhakar

2008-01-01

When designing any human-system interface, it is critical to provide realistic anthropometry to properly represent how a person fits within a given space. This study aimed to identify a minimum number of boundary manikins or representative models of subjects anthropometry from a target population, which would realistically represent the population. The boundary manikin anthropometry was derived using, Principal Component Analysis (PCA). PCA is a statistical approach to reduce a multi-dimensional dataset using eigenvectors and eigenvalues. The measurements used in the PCA were identified as those measurements critical for suit and cockpit design. The PCA yielded a total of 26 manikins per gender, as well as their anthropometry from the target population. Reduction techniques were implemented to reduce this number further with a final result of 20 female and 22 male subjects. The anthropometry of the boundary manikins was then be used to create 3D digital models (to be discussed in subsequent papers) intended for use by designers to test components of their space suit design, to verify that the requirements specified in the Human Systems Integration Requirements (HSIR) document are met. The end-goal is to allow for designers to generate suits which accommodate the diverse anthropometry of the user population.

A solid-state NMR method to determine domain sizes in multi-component polymer formulations

NASA Astrophysics Data System (ADS)

Schlagnitweit, Judith; Tang, Mingxue; Baias, Maria; Richardson, Sara; Schantz, Staffan; Emsley, Lyndon

2015-12-01

Polymer domain sizes are related to many of the physical properties of polymers. Here we present a solid-state NMR experiment that is capable of measuring domain sizes in multi-component mixtures. The method combines selective excitation of carbon magnetization to isolate a specific component with proton spin diffusion to report on domain size. We demonstrate the method in the context of controlled release formulations, which represents one of today's challenges in pharmaceutical science. We show that we can measure domain sizes of interest in the different components of industrial pharmaceutical formulations at natural isotopic abundance containing various (modified) cellulose derivatives, such as microcrystalline cellulose matrixes that are film-coated with a mixture of ethyl cellulose (EC) and hydroxypropyl cellulose (HPC).

Recent Advances in Multi-component Particles Assembly.

PubMed

Guo, Dan; Song, Yanlin

2018-03-09

Particles assembly and co-assembly have been research frontiers in chemistry and material science in the past few decades. To achieve a large variety of intricate structures and functional materials, remarkable progress has been made in the particle assembly principles and strategies. It can be summarized that the particle assembly is driven by intrinsic interparticle interaction or the external control. In this article, we focus on binary or ternary particles co-assembly and review the principles and feasible strategies. These advances have led to new disciplines of microfabrication technology and material engineering. Although remarked achievement on particle-based structures has been made, it is still challenging to fully develop general and facile strategies to precisely control the one-dimensional (1D) co-assembly. This article reviews the recent development on multi-component particles co-assembly, which significantly increases structural complexity and functional diversity. In particular, we highlight the advances in the particles co-assembly of well-ordered 1D binary superstructures by liquid soft confinement. Finally, prospective outlook for future trends in this field is proposed. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

UNRAVELLING THE COMPONENTS OF A MULTI-THERMAL CORONAL LOOP USING MAGNETOHYDRODYNAMIC SEISMOLOGY

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

Prasad, S. Krishna; Jess, D. B.; Klimchuk, J. A.

Coronal loops, constituting the basic building blocks of the active Sun, serve as primary targets to help understand the mechanisms responsible for maintaining multi-million Kelvin temperatures in the solar and stellar coronae. Despite significant advances in observations and theory, our knowledge on the fundamental properties of these structures is limited. Here, we present unprecedented observations of accelerating slow magnetoacoustic waves along a coronal loop that show differential propagation speeds in two distinct temperature channels, revealing the multi-stranded and multithermal nature of the loop. Utilizing the observed speeds and employing nonlinear force-free magnetic field extrapolations, we derive the actual temperature variationmore » along the loop in both channels, and thus are able to resolve two individual components of the multithermal loop for the first time. The obtained positive temperature gradients indicate uniform heating along the loop, rather than isolated footpoint heating.« less

SCOUSE: Semi-automated multi-COmponent Universal Spectral-line fitting Engine

NASA Astrophysics Data System (ADS)

Henshaw, J. D.; Longmore, S. N.; Kruijssen, J. M. D.; Davies, B.; Bally, J.; Barnes, A.; Battersby, C.; Burton, M.; Cunningham, M. R.; Dale, J. E.; Ginsburg, A.; Immer, K.; Jones, P. A.; Kendrew, S.; Mills, E. A. C.; Molinari, S.; Moore, T. J. T.; Ott, J.; Pillai, T.; Rathborne, J.; Schilke, P.; Schmiedeke, A.; Testi, L.; Walker, D.; Walsh, A.; Zhang, Q.

2016-01-01

The Semi-automated multi-COmponent Universal Spectral-line fitting Engine (SCOUSE) is a spectral line fitting algorithm that fits Gaussian files to spectral line emission. It identifies the spatial area over which to fit the data and generates a grid of spectral averaging areas (SAAs). The spatially averaged spectra are fitted according to user-provided tolerance levels, and the best fit is selected using the Akaike Information Criterion, which weights the chisq of a best-fitting solution according to the number of free-parameters. A more detailed inspection of the spectra can be performed to improve the fit through an iterative process, after which SCOUSE integrates the new solutions into the solution file.

[Best time to administer coagulation factor XIII( Fibrogammin P) for postoperative intractable pancreatic fistula following gastrectomy for gastric cancer].

PubMed

Shoda, Katsutoshi; Komatsu, Shuhei; Ichikawa, Daisuke; Kubota, Takeshi; Okamoto, Kazuma; Arita, Tomohiro; Konishi, Hirotaka; Murayama, Yasutoshi; Shiozaki, Atsushi; Kuriu, Yoshiaki; Ikoma, Hisashi; Nakanishi, Masayoshi; Fujiwara, Hitoshi; Otsuji, Eigo

2013-11-01

Coagulation factor XIII( Fibrogammin P, F XIII) has been used to treat postoperative pancreatic fistulas following gastrectomy for gastric cancer in Japan. However, little is known about the best timing to start this treatment for early recovery. This study was designed to examine the appropriate time to start Fibrogammin P treatment for pancreatic fistulas, based on nutritional and inflammatory parameters. We retrospectively examined 27 consecutive patients with Grade B or C pancreatic fistulas as defined by the International Study Group of Pancreatic Fistula( ISGPF) classification who underwent gastrectomy at our institute between 1997 and 2011. We analyzed data on total protein( TP), albumin (Alb), C-reactive protein( CRP), and hemoglobin( Hb) concentrations and white blood cell( WBC) and lymphocyte counts. We used this information to determine laboratory cut-off values that indicate the most advantageous time to start the administration of Fibrogammin P in order to achieve early recovery within 2 weeks. When Fibrogammin P administration was based on more than 2 cut-off values such as Alb>2.6 g/dL and Hb>9.0 g/dL and WBC<9,000/μL (p= 0.1563), early cure of pancreatic fistulas was achieved. The use of nutritional and inflammatory parameter values to determine the best time to administer Fibrogammin P may shorten the treatment period.

Robust demarcation of basal cell carcinoma by dependent component analysis-based segmentation of multi-spectral fluorescence images.

PubMed

Kopriva, Ivica; Persin, Antun; Puizina-Ivić, Neira; Mirić, Lina

2010-07-02

This study was designed to demonstrate robust performance of the novel dependent component analysis (DCA)-based approach to demarcation of the basal cell carcinoma (BCC) through unsupervised decomposition of the red-green-blue (RGB) fluorescent image of the BCC. Robustness to intensity fluctuation is due to the scale invariance property of DCA algorithms, which exploit spectral and spatial diversities between the BCC and the surrounding tissue. Used filtering-based DCA approach represents an extension of the independent component analysis (ICA) and is necessary in order to account for statistical dependence that is induced by spectral similarity between the BCC and surrounding tissue. This generates weak edges what represents a challenge for other segmentation methods as well. By comparative performance analysis with state-of-the-art image segmentation methods such as active contours (level set), K-means clustering, non-negative matrix factorization, ICA and ratio imaging we experimentally demonstrate good performance of DCA-based BCC demarcation in two demanding scenarios where intensity of the fluorescent image has been varied almost two orders of magnitude. Copyright 2010 Elsevier B.V. All rights reserved.

Measure Projection Analysis: A Probabilistic Approach to EEG Source Comparison and Multi-Subject Inference

PubMed Central

Bigdely-Shamlo, Nima; Mullen, Tim; Kreutz-Delgado, Kenneth; Makeig, Scott

2013-01-01

A crucial question for the analysis of multi-subject and/or multi-session electroencephalographic (EEG) data is how to combine information across multiple recordings from different subjects and/or sessions, each associated with its own set of source processes and scalp projections. Here we introduce a novel statistical method for characterizing the spatial consistency of EEG dynamics across a set of data records. Measure Projection Analysis (MPA) first finds voxels in a common template brain space at which a given dynamic measure is consistent across nearby source locations, then computes local-mean EEG measure values for this voxel subspace using a statistical model of source localization error and between-subject anatomical variation. Finally, clustering the mean measure voxel values in this locally consistent brain subspace finds brain spatial domains exhibiting distinguishable measure features and provides 3-D maps plus statistical significance estimates for each EEG measure of interest. Applied to sufficient high-quality data, the scalp projections of many maximally independent component (IC) processes contributing to recorded high-density EEG data closely match the projection of a single equivalent dipole located in or near brain cortex. We demonstrate the application of MPA to a multi-subject EEG study decomposed using independent component analysis (ICA), compare the results to k-means IC clustering in EEGLAB (sccn.ucsd.edu/eeglab), and use surrogate data to test MPA robustness. A Measure Projection Toolbox (MPT) plug-in for EEGLAB is available for download (sccn.ucsd.edu/wiki/MPT). Together, MPA and ICA allow use of EEG as a 3-D cortical imaging modality with near-cm scale spatial resolution. PMID:23370059

A finite element method based microwave heat transfer modeling of frozen multi-component foods

NASA Astrophysics Data System (ADS)

Pitchai, Krishnamoorthy

Microwave heating is fast and convenient, but is highly non-uniform. Non-uniform heating in microwave cooking affects not only food quality but also food safety. Most food industries develop microwavable food products based on "cook-and-look" approach. This approach is time-consuming, labor intensive and expensive and may not result in optimal food product design that assures food safety and quality. Design of microwavable food can be realized through a simulation model which describes the physical mechanisms of microwave heating in mathematical expressions. The objective of this study was to develop a microwave heat transfer model to predict spatial and temporal profiles of various heterogeneous foods such as multi-component meal (chicken nuggets and mashed potato), multi-component and multi-layered meal (lasagna), and multi-layered food with active packages (pizza) during microwave heating. A microwave heat transfer model was developed by solving electromagnetic and heat transfer equations using finite element method in commercially available COMSOL Multiphysics v4.4 software. The microwave heat transfer model included detailed geometry of the cavity, phase change, and rotation of the food on the turntable. The predicted spatial surface temperature patterns and temporal profiles were validated against the experimental temperature profiles obtained using a thermal imaging camera and fiber-optic sensors. The predicted spatial surface temperature profile of different multi-component foods was in good agreement with the corresponding experimental profiles in terms of hot and cold spot patterns. The root mean square error values of temporal profiles ranged from 5.8 °C to 26.2 °C in chicken nuggets as compared 4.3 °C to 4.7 °C in mashed potatoes. In frozen lasagna, root mean square error values at six locations ranged from 6.6 °C to 20.0 °C for 6 min of heating. A microwave heat transfer model was developed to include susceptor assisted microwave heating of a

Multi-sensor analysis of urban ecosystems

USGS Publications Warehouse

Gallo, Kevin P.; Ji, Lei

2004-01-01

This study examines the synthesis of multiple space-based sensors to characterize the urban environment Single scene data (e.g., ASTER visible and near-IR surface reflectance, and land surface temperature data), multi-temporal data (e.g., one year of 16-day MODIS and AVHRR vegetation index data), and DMSP-OLS nighttime light data acquired in the early 1990s and 2000 were evaluated for urban ecosystem analysis. The advantages of a multi-sensor approach for the analysis of urban ecosystem processes are discussed.

A new pulsed laser deposition technique: scanning multi-component pulsed laser deposition method.

PubMed

Fischer, D; de la Fuente, G F; Jansen, M

2012-04-01

The scanning multi-component pulsed laser deposition (PLD) method realizes uniform depositions of desired coatings by a modified pulsed laser deposition process, preferably with a femto-second laser-system. Multi-component coatings (single or multilayered) are thus deposited onto substrates via laser induced ablation of segmented targets. This is achieved via horizontal line-scanning of a focused laser beam over a uniformly moving target's surface. This process allows to deposit the desired composition of the coating simultaneously, starting from the different segments of the target and adjusting the scan line as a function of target geometry. The sequence and thickness of multilayers can easily be adjusted by target architecture and motion, enabling inter/intra layer concentration gradients and thus functional gradient coatings. This new, simple PLD method enables the achievement of uniform, large-area coatings. Case studies were performed with segmented targets containing aluminum, titanium, and niobium. Under the laser irradiation conditions applied, all three metals were uniformly ablated. The elemental composition within the rough coatings obtained was fixed by the scanned area to Ti-Al-Nb = 1:1:1. Crystalline aluminum, titanium, and niobium were found to coexist side by side at room temperature within the substrate, without alloy formation up to 600 °C. © 2012 American Institute of Physics

Multi-component solid solution alloys having high mixing entropy

DOEpatents

Bei, Hongbin

2015-10-06

A multi-component high-entropy alloy includes a composition selected from the following group: VNbTaTiMoWRe, VNbTaTiMoW, VNbTaTiMoRe, VNbTaTiWRe, VNbTaMoWRe, VNbTiMoWRe, VTaTiMoWRe, NbTaTiMoWRe, VNbTaTiMo, VNbTaTiW, VNbTaMoW, VNbTiMoW, VTaTiMoW, NbTaTiMoW, VNbTaTiRe, VNbTaMoRe, VNbTiMoRe, VTaTiMoRe, NbTaTiMoRe, VNbTaWRe, VNbTiWRe, VTaTiWRe, NbTaTiWRe, VNbMoWRe, VTaMoWRe, NbTaMoWRe, VTiMoWRe, NbTiMoWRe, TaTiMoWRe, wherein relative amounts of each element vary by no more than .+-.15 atomic %.

Nonlinear multi-analysis of agent-based financial market dynamics by epidemic system

NASA Astrophysics Data System (ADS)

Lu, Yunfan; Wang, Jun; Niu, Hongli

2015-10-01

Based on the epidemic dynamical system, we construct a new agent-based financial time series model. In order to check and testify its rationality, we compare the statistical properties of the time series model with the real stock market indices, Shanghai Stock Exchange Composite Index and Shenzhen Stock Exchange Component Index. For analyzing the statistical properties, we combine the multi-parameter analysis with the tail distribution analysis, the modified rescaled range analysis, and the multifractal detrended fluctuation analysis. For a better perspective, the three-dimensional diagrams are used to present the analysis results. The empirical research in this paper indicates that the long-range dependence property and the multifractal phenomenon exist in the real returns and the proposed model. Therefore, the new agent-based financial model can recurrence some important features of real stock markets.

Hydrodynamic model for expansion and collisional relaxation of x-ray laser-excited multi-component nanoplasma

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

Saxena, Vikrant, E-mail: vikrant.saxena@desy.de; Hamburg Center for Ultrafast Imaging, Luruper Chaussee 149, 22761 Hamburg; Ziaja, Beata, E-mail: ziaja@mail.desy.de

The irradiation of an atomic cluster with a femtosecond x-ray free-electron laser pulse results in a nanoplasma formation. This typically occurs within a few hundred femtoseconds. By this time the x-ray pulse is over, and the direct photoinduced processes no longer contributing. All created electrons within the nanoplasma are thermalized. The nanoplasma thus formed is a mixture of atoms, electrons, and ions of various charges. While expanding, it is undergoing electron impact ionization and three-body recombination. Below we present a hydrodynamic model to describe the dynamics of such multi-component nanoplasmas. The model equations are derived by taking the moments ofmore » the corresponding Boltzmann kinetic equations. We include the equations obtained, together with the source terms due to electron impact ionization and three-body recombination, in our hydrodynamic solver. Model predictions for a test case, expanding spherical Ar nanoplasma, are obtained. With this model, we complete the two-step approach to simulate x-ray created nanoplasmas, enabling computationally efficient simulations of their picosecond dynamics. Moreover, the hydrodynamic framework including collisional processes can be easily extended for other source terms and then applied to follow relaxation of any finite non-isothermal multi-component nanoplasma with its components relaxed into local thermodynamic equilibrium.« less

The synergic control of multi-finger force production: Stability of explicit and implicit task components

PubMed Central

Reschechtko, Sasha; Zatsiorsky, Vladimir M.; Latash, Mark L.

2016-01-01

Manipulating objects with the hands requires the accurate production of resultant forces including shear forces; effective control of these shear forces also requires the production of internal forces normal to the surface of the object(s) being manipulated. In the present study, we investigated multi-finger synergies stabilizing shear and normal components of force, as well as drifts in both components of force, during isometric pressing tasks requiring a specific magnitude of shear force production. We hypothesized that shear and normal forces would evolve similarly in time, and also show similar stability properties as assessed by the decomposition of inter-trial variance within the uncontrolled manifold hypothesis. Healthy subjects were required to accurately produce total shear and total normal forces with four fingers of the hand during a steady-state force task (with and without visual feedback) and a self-paced force pulse task. The two force components showed similar time profiles during both shear force pulse production and unintentional drift induced by turning the visual feedback off. Only the explicitly instructed components of force, however, were stabilized with multi-finger synergies. No force-stabilizing synergies and no anticipatory synergy adjustments were seen for the normal force in shear force production trials. These unexpected qualitative differences in the control of the two force components – which are produced by some of the same muscles and show high degree of temporal coupling – are interpreted within the theory of control with referent coordinates for salient variables. These observations suggest the existence of two classes of neural variables: one that translates into shifts of referent coordinates and defines changes in magnitude of salient variables, and the other controlling gains in back-coupling loops that define stability of the salient variables. Only the former are shared between the explicit and implicit task components

Model reduction by weighted Component Cost Analysis

NASA Technical Reports Server (NTRS)

Kim, Jae H.; Skelton, Robert E.

1990-01-01

Component Cost Analysis considers any given system driven by a white noise process as an interconnection of different components, and assigns a metric called 'component cost' to each component. These component costs measure the contribution of each component to a predefined quadratic cost function. A reduced-order model of the given system may be obtained by deleting those components that have the smallest component costs. The theory of Component Cost Analysis is extended to include finite-bandwidth colored noises. The results also apply when actuators have dynamics of their own. Closed-form analytical expressions of component costs are also derived for a mechanical system described by its modal data. This is very useful to compute the modal costs of very high order systems. A numerical example for MINIMAST system is presented.

Self-Assembling Multi-Component Nanofibers for Strong Bioinspired Underwater Adhesives

PubMed Central

Zhong, Chao; Gurry, Thomas; Cheng, Allen A; Downey, Jordan; Deng, Zhengtao; Stultz, Collin M.; Lu, Timothy K

2014-01-01

Many natural underwater adhesives harness hierarchically assembled amyloid nanostructures to achieve strong and robust interfacial adhesion under dynamic and turbulent environments. Despite recent advances, our understanding of the molecular design, self-assembly, and structure-function relationship of those natural amyloid fibers remains limited. Thus, designing biomimetic amyloid-based adhesives remains challenging. Here, we report strong and multi-functional underwater adhesives obtained from fusing mussel foot proteins (Mfps) of Mytilus galloprovincialis with CsgA proteins, the major subunit of Escherichia coli amyloid curli fibers. These hybrid molecular materials hierarchically self-assemble into higher-order structures, in which, according to molecular dynamics simulations, disordered adhesive Mfp domains are exposed on the exterior of amyloid cores formed by CsgA. Our fibers have an underwater adhesion energy approaching 20.9 mJ/m2, which is 1.5 times greater than the maximum of bio-inspired and bio-derived protein-based underwater adhesives reported thus far. Moreover, they outperform Mfps or curli fibers taken on their own at all pHs and exhibit better tolerance to auto-oxidation than Mfps at pH ≥7.0. This work establishes a platform for engineering multi-component self-assembling materials inspired by nature. PMID:25240674

A Principal Component Analysis of 39 Scientific Impact Measures

PubMed Central

Bollen, Johan; Van de Sompel, Herbert

2009-01-01

Background The impact of scientific publications has traditionally been expressed in terms of citation counts. However, scientific activity has moved online over the past decade. To better capture scientific impact in the digital era, a variety of new impact measures has been proposed on the basis of social network analysis and usage log data. Here we investigate how these new measures relate to each other, and how accurately and completely they express scientific impact. Methodology We performed a principal component analysis of the rankings produced by 39 existing and proposed measures of scholarly impact that were calculated on the basis of both citation and usage log data. Conclusions Our results indicate that the notion of scientific impact is a multi-dimensional construct that can not be adequately measured by any single indicator, although some measures are more suitable than others. The commonly used citation Impact Factor is not positioned at the core of this construct, but at its periphery, and should thus be used with caution. PMID:19562078

Simulating the Response of a Composite Honeycomb Energy Absorber. Part 1; Dynamic Crushing of Components and Multi-Terrain Impacts

NASA Technical Reports Server (NTRS)

Jackson, Karen E.; Fasanella, Edwin L.; Polanco, Michael A.

2012-01-01

This paper describes the experimental and analytical evaluation of an externally deployable composite honeycomb structure that is designed to attenuate impact energy during helicopter crashes. The concept, designated the Deployable Energy Absorber (DEA), utilizes an expandable Kevlar (Registered Trademark) honeycomb to dissipate kinetic energy through crushing. The DEA incorporates a unique flexible hinge design that allows the honeycomb to be packaged and stowed until needed for deployment. Experimental evaluation of the DEA included dynamic crush tests of multi-cell components and vertical drop tests of a composite fuselage section, retrofitted with DEA blocks, onto multi-terrain. Finite element models of the test articles were developed and simulations were performed using the transient dynamic code, LSDYNA (Registered Trademark). In each simulation, the DEA was represented using shell elements assigned two different material properties: Mat 24, an isotropic piecewise linear plasticity model, and Mat 58, a continuum damage mechanics model used to represent laminated composite fabrics. DEA model development and test-analysis comparisons are presented.

Spectral decomposition of asteroid Itokawa based on principal component analysis

NASA Astrophysics Data System (ADS)

Koga, Sumire C.; Sugita, Seiji; Kamata, Shunichi; Ishiguro, Masateru; Hiroi, Takahiro; Tatsumi, Eri; Sasaki, Sho

2018-01-01

The heliocentric stratification of asteroid spectral types may hold important information on the early evolution of the Solar System. Asteroid spectral taxonomy is based largely on principal component analysis. However, how the surface properties of asteroids, such as the composition and age, are projected in the principal-component (PC) space is not understood well. We decompose multi-band disk-resolved visible spectra of the Itokawa surface with principal component analysis (PCA) in comparison with main-belt asteroids. The obtained distribution of Itokawa spectra projected in the PC space of main-belt asteroids follows a linear trend linking the Q-type and S-type regions and is consistent with the results of space-weathering experiments on ordinary chondrites and olivine, suggesting that this trend may be a space-weathering-induced spectral evolution track for S-type asteroids. Comparison with space-weathering experiments also yield a short average surface age (< a few million years) for Itokawa, consistent with the cosmic-ray-exposure time of returned samples from Itokawa. The Itokawa PC score distribution exhibits asymmetry along the evolution track, strongly suggesting that space weathering has begun saturated on this young asteroid. The freshest spectrum found on Itokawa exhibits a clear sign for space weathering, indicating again that space weathering occurs very rapidly on this body. We also conducted PCA on Itokawa spectra alone and compared the results with space-weathering experiments. The obtained results indicate that the first principal component of Itokawa surface spectra is consistent with spectral change due to space weathering and that the spatial variation in the degree of space weathering is very large (a factor of three in surface age), which would strongly suggest the presence of strong regional/local resurfacing process(es) on this small asteroid.

Robust Optimization and Sensitivity Analysis with Multi-Objective Genetic Algorithms: Single- and Multi-Disciplinary Applications

DTIC Science & Technology

2007-01-01

multi-disciplinary optimization with uncertainty. Robust optimization and sensitivity analysis is usually used when an optimization model has...formulation is introduced in Section 2.3. We briefly discuss several definitions used in the sensitivity analysis in Section 2.4. Following in...2.5. 2.4 SENSITIVITY ANALYSIS In this section, we discuss several definitions used in Chapter 5 for Multi-Objective Sensitivity Analysis . Inner

Application of principal component analysis to multispectral imaging data for evaluation of pigmented skin lesions

NASA Astrophysics Data System (ADS)

Jakovels, Dainis; Lihacova, Ilze; Kuzmina, Ilona; Spigulis, Janis

2013-11-01

Non-invasive and fast primary diagnostics of pigmented skin lesions is required due to frequent incidence of skin cancer - melanoma. Diagnostic potential of principal component analysis (PCA) for distant skin melanoma recognition is discussed. Processing of the measured clinical multi-spectral images (31 melanomas and 94 nonmalignant pigmented lesions) in the wavelength range of 450-950 nm by means of PCA resulted in 87 % sensitivity and 78 % specificity for separation between malignant melanomas and pigmented nevi.

Multi-Component Profiling of Trace Volatiles in Blood by Gas Chromatography/Mass Spectrometry with Dynamic Headspace Extraction

PubMed Central

Kakuta, Shoji; Yamashita, Toshiyuki; Nishiumi, Shin; Yoshida, Masaru; Fukusaki, Eiichiro; Bamba, Takeshi

2015-01-01

A dynamic headspace extraction method (DHS) with high-pressure injection is described. This dynamic extraction method has superior sensitivity to solid phase micro extraction, SPME and is capable of extracting the entire gas phase by purging the headspace of a vial. Optimization of the DHS parameters resulted in a highly sensitive volatile profiling system with the ability to detect various volatile components including alcohols at nanogram levels. The average LOD for a standard volatile mixture was 0.50 ng mL−1, and the average LOD for alcohols was 0.66 ng mL−1. This method was used for the analysis of volatile components from biological samples and compared with acute and chronic inflammation models. The method permitted the identification of volatiles with the same profile pattern as in vitro oxidized lipid-derived volatiles. In addition, the concentration of alcohols and aldehydes from the acute inflammation model samples were significantly higher than that for the chronic inflammation model samples. The different profiles between these samples could also be identified by this method. Finally, it was possible to analyze alcohols and low-molecular-weight volatiles that are difficult to analyze by SPME in high sensitivity and to show volatile profiling based on multi-volatile simultaneous analysis. PMID:26819905

Multi-Component Profiling of Trace Volatiles in Blood by Gas Chromatography/Mass Spectrometry with Dynamic Headspace Extraction.

PubMed

Kakuta, Shoji; Yamashita, Toshiyuki; Nishiumi, Shin; Yoshida, Masaru; Fukusaki, Eiichiro; Bamba, Takeshi

2015-01-01

A dynamic headspace extraction method (DHS) with high-pressure injection is described. This dynamic extraction method has superior sensitivity to solid phase micro extraction, SPME and is capable of extracting the entire gas phase by purging the headspace of a vial. Optimization of the DHS parameters resulted in a highly sensitive volatile profiling system with the ability to detect various volatile components including alcohols at nanogram levels. The average LOD for a standard volatile mixture was 0.50 ng mL(-1), and the average LOD for alcohols was 0.66 ng mL(-1). This method was used for the analysis of volatile components from biological samples and compared with acute and chronic inflammation models. The method permitted the identification of volatiles with the same profile pattern as in vitro oxidized lipid-derived volatiles. In addition, the concentration of alcohols and aldehydes from the acute inflammation model samples were significantly higher than that for the chronic inflammation model samples. The different profiles between these samples could also be identified by this method. Finally, it was possible to analyze alcohols and low-molecular-weight volatiles that are difficult to analyze by SPME in high sensitivity and to show volatile profiling based on multi-volatile simultaneous analysis.

Feasibility of a multi-component additive for efficient control of activated sludge filamentous bulking.

PubMed

Seka, A M; Van De Wiele, T; Verstraete, W

2001-08-01

Instantaneous improvement of the settling of bulking filamentous activated sludge can be achieved by the addition of a polymer or a large amount (up to 100% of the MLSS concentration) of talc powder to the sludge. Long-term improvement relies on repeated additions, as these additives have no adverse effects on the causative filaments. A multi-component additive was compared to the traditional additives in lab-scale activated sludge units using three highly filamentous sludges from different industrial treatment plants. The study demonstrated that the multi-component additive was superior to the traditional remedies. It was shown that, in the case of severe filamentous bulking, a single addition of the new additive immediately improved sludge settling and exerted a destructive effect on the causative filamentous bacteria. Thus, the latter additive also ensured a long-term sludge sedimentation improvement. The traditional additives exhibited an immediate and short-term effect. The novel additive also retarded sludge rising due to denitrification and it improved sludge dewaterability. The study revealed Nostocoido limicola II, with slightly hydrophobic cell wall, to be somewhat resistant to the quaternary ammonium salt present as biocide in the additive.

Multi-resolution analysis for region of interest extraction in thermographic nondestructive evaluation

NASA Astrophysics Data System (ADS)

Ortiz-Jaramillo, B.; Fandiño Toro, H. A.; Benitez-Restrepo, H. D.; Orjuela-Vargas, S. A.; Castellanos-Domínguez, G.; Philips, W.

2012-03-01

Infrared Non-Destructive Testing (INDT) is known as an effective and rapid method for nondestructive inspection. It can detect a broad range of near-surface structuring flaws in metallic and composite components. Those flaws are modeled as a smooth contour centered at peaks of stored thermal energy, termed Regions of Interest (ROI). Dedicated methodologies must detect the presence of those ROIs. In this paper, we present a methodology for ROI extraction in INDT tasks. The methodology deals with the difficulties due to the non-uniform heating. The non-uniform heating affects low spatial/frequencies and hinders the detection of relevant points in the image. In this paper, a methodology for ROI extraction in INDT using multi-resolution analysis is proposed, which is robust to ROI low contrast and non-uniform heating. The former methodology includes local correlation, Gaussian scale analysis and local edge detection. In this methodology local correlation between image and Gaussian window provides interest points related to ROIs. We use a Gaussian window because thermal behavior is well modeled by Gaussian smooth contours. Also, the Gaussian scale is used to analyze details in the image using multi-resolution analysis avoiding low contrast, non-uniform heating and selection of the Gaussian window size. Finally, local edge detection is used to provide a good estimation of the boundaries in the ROI. Thus, we provide a methodology for ROI extraction based on multi-resolution analysis that is better or equal compared with the other dedicate algorithms proposed in the state of art.

Multi-Component Diffusion with Application To Computational Aerothermodynamics

NASA Technical Reports Server (NTRS)

Sutton, Kenneth; Gnoffo, Peter A.

1998-01-01

The accuracy and complexity of solving multicomponent gaseous diffusion using the detailed multicomponent equations, the Stefan-Maxwell equations, and two commonly used approximate equations have been examined in a two part study. Part I examined the equations in a basic study with specified inputs in which the results are applicable for many applications. Part II addressed the application of the equations in the Langley Aerothermodynamic Upwind Relaxation Algorithm (LAURA) computational code for high-speed entries in Earth's atmosphere. The results showed that the presented iterative scheme for solving the Stefan-Maxwell equations is an accurate and effective method as compared with solutions of the detailed equations. In general, good accuracy with the approximate equations cannot be guaranteed for a species or all species in a multi-component mixture. 'Corrected' forms of the approximate equations that ensured the diffusion mass fluxes sum to zero, as required, were more accurate than the uncorrected forms. Good accuracy, as compared with the Stefan- Maxwell results, were obtained with the 'corrected' approximate equations in defining the heating rates for the three Earth entries considered in Part II.

Multi-Metric Sustainability Analysis

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

Cowlin, Shannon; Heimiller, Donna; Macknick, Jordan

2014-12-01

A readily accessible framework that allows for evaluating impacts and comparing tradeoffs among factors in energy policy, expansion planning, and investment decision making is lacking. Recognizing this, the Joint Institute for Strategic Energy Analysis (JISEA) funded an exploration of multi-metric sustainability analysis (MMSA) to provide energy decision makers with a means to make more comprehensive comparisons of energy technologies. The resulting MMSA tool lets decision makers simultaneously compare technologies and potential deployment locations.

A multi-component evaporation model for beam melting processes

NASA Astrophysics Data System (ADS)

Klassen, Alexander; Forster, Vera E.; Körner, Carolin

2017-02-01

In additive manufacturing using laser or electron beam melting technologies, evaporation losses and changes in chemical composition are known issues when processing alloys with volatile elements. In this paper, a recently described numerical model based on a two-dimensional free surface lattice Boltzmann method is further developed to incorporate the effects of multi-component evaporation. The model takes into account the local melt pool composition during heating and fusion of metal powder. For validation, the titanium alloy Ti-6Al-4V is melted by selective electron beam melting and analysed using mass loss measurements and high-resolution microprobe imaging. Numerically determined evaporation losses and spatial distributions of aluminium compare well with experimental data. Predictions of the melt pool formation in bulk samples provide insight into the competition between the loss of volatile alloying elements from the irradiated surface and their advective redistribution within the molten region.

Multi-Unit Considerations for Human Reliability Analysis

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

St. Germain, S.; Boring, R.; Banaseanu, G.

This paper uses the insights from the Standardized Plant Analysis Risk-Human Reliability Analysis (SPAR-H) methodology to help identify human actions currently modeled in the single unit PSA that may need to be modified to account for additional challenges imposed by a multi-unit accident as well as identify possible new human actions that might be modeled to more accurately characterize multi-unit risk. In identifying these potential human action impacts, the use of the SPAR-H strategy to include both errors in diagnosis and errors in action is considered as well as identifying characteristics of a multi-unit accident scenario that may impact themore » selection of the performance shaping factors (PSFs) used in SPAR-H. The lessons learned from the Fukushima Daiichi reactor accident will be addressed to further help identify areas where improved modeling may be required. While these multi-unit impacts may require modifications to a Level 1 PSA model, it is expected to have much more importance for Level 2 modeling. There is little currently written specifically about multi-unit HRA issues. A review of related published research will be presented. While this paper cannot answer all issues related to multi-unit HRA, it will hopefully serve as a starting point to generate discussion and spark additional ideas towards the proper treatment of HRA in a multi-unit PSA.« less

Continuous Video Modeling to Prompt Completion of Multi-Component Tasks by Adults with Moderate Intellectual Disability

ERIC Educational Resources Information Center

Mechling, Linda C.; Ayres, Kevin M.; Purrazzella, Kaitlin; Purrazzella, Kimberly

2014-01-01

This investigation examined the ability of four adults with moderate intellectual disability to complete multi-component tasks using continuous video modeling. Continuous video modeling, which is a newly researched application of video modeling, presents video in a "looping" format which automatically repeats playing of the video while…

High-resolution detection of adulteration of maize oil using multi-component compound-specific delta13C values of major and minor components and discriminant analysis.

PubMed

Mottram, Hazel R; Woodbury, Simon E; Rossell, J Barry; Evershed, Richard P

2003-01-01

Maize oil commands a premium price and is thus a target for adulteration with cheaper vegetable oils. Detection of this activity presents a particular challenge to the analyst because of the natural variability in the fatty acid composition of maize oils and because of their high sterol and tocopherol contents. This paper describes a method that allows detection of adulteration at concentrations of just 5% (m/m), based on the Mahalanobis distances of the principal component scores of the delta(13)C values of major and minor vegetable oil components. The method makes use of a database consisting of delta(13)C values and relative abundances of the major fatty acyl components of over 150 vegetable oils. The sterols and tocopherols of 16 maize oils and 6 potential adulterant oils were found to be depleted in (13)C by a constant amount relative to the bulk oil. Moreover, since maize oil contains particularly high levels of sterols and tocopherols, their delta(13)C values were not significantly altered when groundnut oil was added up to 20% (m/m) and it is possible to use the values for the minor components to predict the values that would be expected in a pure oil; therefore, comparison of the predicted values with those obtained experimentally allows adulteration to be detected. A refinement involved performing a discriminant analysis on the delta(13)C values of the bulk oil and the major fatty acids (16:0, 18:1 and 18:2) and using the Mahalanobis distances to determine the percentage of adulterant oil present. This approach may be refined further by including the delta(13)C values of the minor components in the discriminant analysis thereby increasing the sensitivity of the approach to concentrations at which adulteration would not be attractive economically. Copyright 2003 John Wiley & Sons, Ltd.

Significance of Shear Wall in Multi-Storey Structure With Seismic Analysis

NASA Astrophysics Data System (ADS)

Bongilwar, Rajat; Harne, V. R.; Chopade, Aditya

2018-03-01

In past decades, shear walls are one of the most appropriate and important structural component in multi-storied building. Therefore, it would be very interesting to study the structural response and their systems in multi-storied structure. Shear walls contribute the stiffness and strength during earthquakes which are often neglected during design of structure and construction. This study shows the effect of shear walls which significantly affect the vulnerability of structures. In order to test this hypothesis, G+8 storey building was considered with and without shear walls and analyzed for various parameters like base shear, storey drift ratio, lateral displacement, bending moment and shear force. Significance of shear wall has been studied with the help of two models. First model is without shear wall i.e. bare frame and other another model is with shear wall considering opening also in it. For modeling and analysis of both the models, FEM based software ETABS 2016 were used. The analysis of all models was done using Equivalent static method. The comparison of results has been done based on same parameters like base shear, storey drift ratio, lateral displacement, bending moment and shear force.

Process evaluation of TXT2BFiT: a multi-component mHealth randomised controlled trial to prevent weight gain in young adults.

PubMed

Partridge, Stephanie R; Allman-Farinelli, Margaret; McGeechan, Kevin; Balestracci, Kate; Wong, Annette T Y; Hebden, Lana; Harris, Mark F; Bauman, Adrian; Phongsavan, Philayrath

2016-01-19

TXT2BFiT was one of the first few innovative mHealth programs designed for young adults (18-35 years) with demonstrated efficacy in weight management. However, research is lacking to understand intervention effectiveness, especially in complex, multi-component mHealth programs. This paper investigates participant perceptions of and engagement with the mHealth program components in the TXT2BFiT to understand program effects. Process evaluation data were collected continuously for the study duration. The TXT2BFiT program was a multi-component lifestyle program delivered intensively for 3-month followed by a 6-month maintenance phase. Program components included personalised coaching calls, text messages, emails, smartphone apps and website access. Process evaluation measures included frequency of use of components and frequency for number of components used (online survey data); dose delivered and engagement with program components (researcher logs and web platform reports); frequency, timing and difficulties experienced with program components (online survey data) and overall perceptions of program components (online survey data and semi-structured telephone interviews). Qualitative data analysis was performed using NVivo10. Over 80% of participants completed post-intervention (3-months, intervention, n = 110, control n = 104) and follow-up surveys (9-months, intervention, n = 96, control n = 104). Thirty intervention participants completed semi-structured telephone interviews. Participants reported high use of coaching calls, text messages and emails and no issues in content delivery from these components. These components were described as helping them to achieve their goals. Website and app use and engagement was low for the duration of the program. Participants would prefer incorporation of the self-monitoring apps and website resources into one smartphone application that can be individualised by entry of their personal data. Our process

Recovering Long-wavelength Velocity Models using Spectrogram Inversion with Single- and Multi-frequency Components

NASA Astrophysics Data System (ADS)

Ha, J.; Chung, W.; Shin, S.

2015-12-01

Many waveform inversion algorithms have been proposed in order to construct subsurface velocity structures from seismic data sets. These algorithms have suffered from computational burden, local minima problems, and the lack of low-frequency components. Computational efficiency can be improved by the application of back-propagation techniques and advances in computing hardware. In addition, waveform inversion algorithms, for obtaining long-wavelength velocity models, could avoid both the local minima problem and the effect of the lack of low-frequency components in seismic data. In this study, we proposed spectrogram inversion as a technique for recovering long-wavelength velocity models. In spectrogram inversion, decomposed frequency components from spectrograms of traces, in the observed and calculated data, are utilized to generate traces with reproduced low-frequency components. Moreover, since each decomposed component can reveal the different characteristics of a subsurface structure, several frequency components were utilized to analyze the velocity features in the subsurface. We performed the spectrogram inversion using a modified SEG/SEGE salt A-A' line. Numerical results demonstrate that spectrogram inversion could also recover the long-wavelength velocity features. However, inversion results varied according to the frequency components utilized. Based on the results of inversion using a decomposed single-frequency component, we noticed that robust inversion results are obtained when a dominant frequency component of the spectrogram was utilized. In addition, detailed information on recovered long-wavelength velocity models was obtained using a multi-frequency component combined with single-frequency components. Numerical examples indicate that various detailed analyses of long-wavelength velocity models can be carried out utilizing several frequency components.

A calibration rig for multi-component internal strain gauge balance using the new design-of-experiment (DOE) approach

NASA Astrophysics Data System (ADS)

Nouri, N. M.; Mostafapour, K.; Kamran, M.

2018-02-01

In a closed water-tunnel circuit, the multi-component strain gauge force and moment sensor (also known as balance) are generally used to measure hydrodynamic forces and moments acting on scaled models. These balances are periodically calibrated by static loading. Their performance and accuracy depend significantly on the rig and the method of calibration. In this research, a new calibration rig was designed and constructed to calibrate multi-component internal strain gauge balances. The calibration rig has six degrees of freedom and six different component-loading structures that can be applied separately and synchronously. The system was designed based on the applicability of formal experimental design techniques, using gravity for balance loading and balance positioning and alignment relative to gravity. To evaluate the calibration rig, a six-component internal balance developed by Iran University of Science and Technology was calibrated using response surface methodology. According to the results, calibration rig met all design criteria. This rig provides the means by which various methods of formal experimental design techniques can be implemented. The simplicity of the rig saves time and money in the design of experiments and in balance calibration while simultaneously increasing the accuracy of these activities.

Simultaneous quantitative analysis of main components in linderae reflexae radix with one single marker.

PubMed

Wang, Li-Li; Zhang, Yun-Bin; Sun, Xiao-Ya; Chen, Sui-Qing

2016-05-08

Establish a quantitative analysis of multi-components by the single marker (QAMS) method for quality evaluation and validate its feasibilities by the simultaneous quantitative assay of four main components in Linderae Reflexae Radix. Four main components of pinostrobin, pinosylvin, pinocembrin, and 3,5-dihydroxy-2-(1- p -mentheneyl)- trans -stilbene were selected as analytes to evaluate the quality by RP-HPLC coupled with a UV-detector. The method was evaluated by a comparison of the quantitative results between the external standard method and QAMS with a different HPLC system. The results showed that no significant differences were found in the quantitative results of the four contents of Linderae Reflexae Radix determined by the external standard method and QAMS (RSD <3%). The contents of four analytes (pinosylvin, pinocembrin, pinostrobin, and Reflexanbene I) in Linderae Reflexae Radix were determined by the single marker of pinosylvin. This fingerprint was the spectra determined by Shimadzu LC-20AT and Waters e2695 HPLC that were equipped with three different columns.

Synthesis of unnatural amino acids via microwave-assisted regio-selective one-pot multi-component reactions of sulfamidates

EPA Science Inventory

Synthesis of triazole-based unnatural amino acids, triazole bisaminoacids and β-amino triazole has been described via stereo and regioselective one-pot multi-component reaction of sulfamidates, sodium azide, and alkynes under MW irradiation conditions. The developed method is app...

Proposal of AAA-battery-size one-shot ATR Fourier spectroscopic imager for on-site analysis: Simultaneous measurement of multi-components with high accuracy

NASA Astrophysics Data System (ADS)

Hosono, Satsuki; Qi, Wei; Sato, Shun; Suzuki, Yo; Fujiwara, Masaru; Hiramatsu, Hiroyuki; Suzuki, Satoru; Abeygunawardhana, P. K. W.; Wada, Kenji; Nishiyama, Akira; Ishimaru, Ichiro

2015-03-01

For simultaneous measurement of multi-components on-site like factories, the ultra-compact (diameter: 9[mm], length: 45[mm], weight: 200[g]) one-shot ATR (Attenuated Total Reflection) Fourier spectroscopic imager was proposed. Because the proposed one-shot Fourier spectroscopic imaging is based on spatial-phase-shift interferometer, interferograms could be obtained with simple optical configurations. We introduced the transmission-type relativeinclined phase-shifter, that was constructed with a cuboid prism and a wedge prism, onto the optical Fourier transform plane of infinity corrected optical systems. And also, small light-sources and cameras in the mid-infrared light region, whose size are several millimeter on a side, are essential components for the ultra-compact spectroscopic configuration. We selected the Graphite light source (light source area: 1.7×1.7[mm], maker: Hawkeye technologies) whose radiation factor was high. Fortunately, in these days we could apply the cost-effective 2-dimensional light receiving device for smartphone (e.g. product name: LEPTON, maker: FLIR, price: around 400USD). In the case of alcoholic drinks factory, conventionally workers measure glucose and ethanol concentrations by bringing liquid solution back to laboratories every day. The high portable spectroscopy will make it possible to measure multi-components simultaneously on manufacturing scene. But we found experimentally that absorption spectrum of glucose and water and ethanol were overlapped each other in near infrared light region. But for mid-infrared light region, we could distinguish specific absorption peaks of glucose (@10.5[μm]) and ethanol (@11.5[μm]) independently from water absorption. We obtained standard curve between absorption (@9.6[μm]) and ethanol concentration with high correlation coefficient 0.98 successfully by ATR imaging-type 2-dimensional Fourier spectroscopy (wavelength resolution: 0.057[μm]) with the graphite light source (maker: Hawkeye

Developing the snow component of a distributed hydrological model: a step-wise approach based on multi-objective analysis

NASA Astrophysics Data System (ADS)

Dunn, S. M.; Colohan, R. J. E.

1999-09-01

A snow component has been developed for the distributed hydrological model, DIY, using an approach that sequentially evaluates the behaviour of different functions as they are implemented in the model. The evaluation is performed using multi-objective functions to ensure that the internal structure of the model is correct. The development of the model, using a sub-catchment in the Cairngorm Mountains in Scotland, demonstrated that the degree-day model can be enhanced for hydroclimatic conditions typical of those found in Scotland, without increasing meteorological data requirements. An important element of the snow model is a function to account for wind re-distribution. This causes large accumulations of snow in small pockets, which are shown to be important in sustaining baseflows in the rivers during the late spring and early summer, long after the snowpack has melted from the bulk of the catchment. The importance of the wind function would not have been identified using a single objective function of total streamflow to evaluate the model behaviour.

A Multi-Component Social Skills Intervention for Children with Asperger Syndrome: The Junior Detective Training Program

ERIC Educational Resources Information Center

Beaumont, Renae; Sofronoff, Kate

2008-01-01

Background: The study aimed to investigate the effectiveness of a new multi-component social skills intervention for children with Asperger syndrome (AS): The Junior Detective Training Program. This 7-week program included a computer game, small group sessions, parent training sessions and teacher handouts. Method: Forty-nine children with AS were…

Multi-mission telecom analysis tool

NASA Technical Reports Server (NTRS)

Hanks, D.; Kordon, M.; Baker, J.

2002-01-01

In the early formulation phase of a mission it is critically important to have fast, easy to use, easy to integrate space vehicle subsystem analysis tools so that engineers can rapidly perform trade studies not only by themselves but in coordination with other subsystem engineers as well. The Multi-Mission Telecom Analysis Tool (MMTAT) is designed for just this purpose.

Clot retraction is mediated by factor XIII-dependent fibrin-αIIbβ3-myosin axis in platelet sphingomyelin-rich membrane rafts.

PubMed

Kasahara, Kohji; Kaneda, Mizuho; Miki, Toshiaki; Iida, Kazuko; Sekino-Suzuki, Naoko; Kawashima, Ikuo; Suzuki, Hidenori; Shimonaka, Motoyuki; Arai, Morio; Ohno-Iwashita, Yoshiko; Kojima, Soichi; Abe, Mitsuhiro; Kobayashi, Toshihide; Okazaki, Toshiro; Souri, Masayoshi; Ichinose, Akitada; Yamamoto, Naomasa

2013-11-07

Membrane rafts are spatially and functionally heterogenous in the cell membrane. We observed that lysenin-positive sphingomyelin (SM)-rich rafts are identified histochemically in the central region of adhered platelets where fibrin and myosin are colocalized on activation by thrombin. The clot retraction of SM-depleted platelets from SM synthase knockout mouse was delayed significantly, suggesting that platelet SM-rich rafts are involved in clot retraction. We found that fibrin converted by thrombin translocated immediately in platelet detergent-resistant membrane (DRM) rafts but that from Glanzmann's thrombasthenic platelets failed. The fibrinogen γ-chain C-terminal (residues 144-411) fusion protein translocated to platelet DRM rafts on thrombin activation, but its mutant that was replaced by A398A399 at factor XIII crosslinking sites (Q398Q399) was inhibited. Furthermore, fibrin translocation to DRM rafts was impaired in factor XIII A subunit-deficient mouse platelets, which show impaired clot retraction. In the cytoplasm, myosin translocated concomitantly with fibrin translocation into the DRM raft of thrombin-stimulated platelets. Furthermore, the disruption of SM-rich rafts by methyl-β-cyclodextrin impaired myosin activation and clot retraction. Thus, we propose that clot retraction takes place in SM-rich rafts where a fibrin-αIIbβ3-myosin complex is formed as a primary axis to promote platelet contraction.

Breath analysis system for early detection of lung diseases based on multi-sensor array

NASA Astrophysics Data System (ADS)

Jeon, Jin-Young; Yu, Joon-Boo; Shin, Jeong-Suk; Byun, Hyung-Gi; Lim, Jeong-Ok

2013-05-01

Expiratory breath contains various VOCs(Volatile Organic Compounds) produced from the human. When a certain disease exists, the exhalation has specific VOCs which may be generated from diseases. Many researchers have been actively working to find different types of biomarkers which are characteristic for particular diseases. Research regarding the identification of specific diseases from exhalation is still in progress. The aim of this research is to implement early detection of lung disease such as lung cancer and COPD(Chronic Obstructive Pulmonary Disease), which was nominated on the 6th of domestic death rate in 2010, based on multi-sensor array system. The system has been used to acquire sampled expiratory gases data and PCA(Principle Component Analysis) technique was applied to analyze signals from multi-sensor array. Throughout the experimental trials, a clearly distinguishable difference between lung disease patients and healthy controls was found from the measurement and analysis of their respective expiratory gases.

Biochemical component identification by plasmonic improved whispering gallery mode optical resonance based sensor

NASA Astrophysics Data System (ADS)

Saetchnikov, Vladimir A.; Tcherniavskaia, Elina A.; Saetchnikov, Anton V.; Schweiger, Gustav; Ostendorf, Andreas

2014-05-01

Experimental data on detection and identification of variety of biochemical agents, such as proteins, microelements, antibiotic of different generation etc. in both single and multi component solutions under varied in wide range concentration analyzed on the light scattering parameters of whispering gallery mode optical resonance based sensor are represented. Multiplexing on parameters and components has been realized using developed fluidic sensor cell with fixed in adhesive layer dielectric microspheres and data processing. Biochemical component identification has been performed by developed network analysis techniques. Developed approach is demonstrated to be applicable both for single agent and for multi component biochemical analysis. Novel technique based on optical resonance on microring structures, plasmon resonance and identification tools has been developed. To improve a sensitivity of microring structures microspheres fixed by adhesive had been treated previously by gold nanoparticle solution. Another technique used thin film gold layers deposited on the substrate below adhesive. Both biomolecule and nanoparticle injections caused considerable changes of optical resonance spectra. Plasmonic gold layers under optimized thickness also improve parameters of optical resonance spectra. Biochemical component identification has been also performed by developed network analysis techniques both for single and for multi component solution. So advantages of plasmon enhancing optical microcavity resonance with multiparameter identification tools is used for development of a new platform for ultra sensitive label-free biomedical sensor.

Enforcing realizability in explicit multi-component species transport

PubMed Central

McDermott, Randall J.; Floyd, Jason E.

2015-01-01

We propose a strategy to guarantee realizability of species mass fractions in explicit time integration of the partial differential equations governing fire dynamics, which is a multi-component transport problem (realizability requires all mass fractions are greater than or equal to zero and that the sum equals unity). For a mixture of n species, the conventional strategy is to solve for n − 1 species mass fractions and to obtain the nth (or “background”) species mass fraction from one minus the sum of the others. The numerical difficulties inherent in the background species approach are discussed and the potential for realizability violations is illustrated. The new strategy solves all n species transport equations and obtains density from the sum of the species mass densities. To guarantee realizability the species mass densities must remain positive (semidefinite). A scalar boundedness correction is proposed that is based on a minimal diffusion operator. The overall scheme is implemented in a publicly available large-eddy simulation code called the Fire Dynamics Simulator. A set of test cases is presented to verify that the new strategy enforces realizability, does not generate spurious mass, and maintains second-order accuracy for transport. PMID:26692634

UTE bi-component analysis of T2* relaxation in articular cartilage

PubMed Central

Shao, H.; Chang, E.Y.; Pauli, C.; Zanganeh, S.; Bae, W.; Chung, C.B.; Tang, G.; Du, J.

2015-01-01

SUMMARY Objectives To determine T2* relaxation in articular cartilage using ultrashort echo time (UTE) imaging and bi-component analysis, with an emphasis on the deep radial and calcified cartilage. Methods Ten patellar samples were imaged using two-dimensional (2D) UTE and Car-Purcell-Meiboom-Gill (CPMG) sequences. UTE images were fitted with a bi-component model to calculate T2* and relative fractions. CPMG images were fitted with a single-component model to calculate T2. The high signal line above the subchondral bone was regarded as the deep radial and calcified cartilage. Depth and orientation dependence of T2*, fraction and T2 were analyzed with histopathology and polarized light microscopy (PLM), confirming normal regions of articular cartilage. An interleaved multi-echo UTE acquisition scheme was proposed for in vivo applications (n = 5). Results The short T2* values remained relatively constant across the cartilage depth while the long T2* values and long T2* fractions tended to increase from subchondral bone to the superficial cartilage. Long T2*s and T2s showed significant magic angle effect for all layers of cartilage from the medial to lateral facets, while the short T2* values and T2* fractions are insensitive to the magic angle effect. The deep radial and calcified cartilage showed a mean short T2* of 0.80 ± 0.05 ms and short T2* fraction of 39.93 ± 3.05% in vitro, and a mean short T2* of 0.93 ± 0.58 ms and short T2* fraction of 35.03 ± 4.09% in vivo. Conclusion UTE bi-component analysis can characterize the short and long T2* values and fractions across the cartilage depth, including the deep radial and calcified cartilage. The short T2* values and T2* fractions are magic angle insensitive. PMID:26382110

[Applications of meta-analysis in multi-omics].

PubMed

Han, Mingfei; Zhu, Yunping

2014-07-01

As a statistical method integrating multi-features and multi-data, meta-analysis was introduced to the field of life science in the 1990s. With the rapid advances in high-throughput technologies, life omics, the core of which are genomics, transcriptomics and proteomics, is becoming the new hot spot of life science. Although the fast output of massive data has promoted the development of omics study, it results in excessive data that are difficult to integrate systematically. In this case, meta-analysis is frequently applied to analyze different types of data and is improved continuously. Here, we first summarize the representative meta-analysis methods systematically, and then study the current applications of meta-analysis in various omics fields, finally we discuss the still-existing problems and the future development of meta-analysis.

Quality assessment of Herba Leonuri based on the analysis of multiple components using normal- and reversed-phase chromatographic methods.

PubMed

Dong, Shuya; He, Jiao; Hou, Huiping; Shuai, Yaping; Wang, Qi; Yang, Wenling; Sun, Zheng; Li, Qing; Bi, Kaishun; Liu, Ran

2017-12-01

A novel, improved, and comprehensive method for quality evaluation and discrimination of Herba Leonuri has been developed and validated based on normal- and reversed-phase chromatographic methods. To identify Herba Leonuri, normal- and reversed-phase high-performance thin-layer chromatography fingerprints were obtained by comparing the colors and R f values of the bands, and reversed-phase high-performance liquid chromatography fingerprints were obtained by using an Agilent Poroshell 120 SB-C18 within 28 min. By similarity analysis and hierarchical clustering analysis, we show that there are similar chromatographic patterns in Herba Leonuri samples, but significant differences in counterfeits and variants. To quantify the bio-active components of Herba Leonuri, reversed-phase high-performance liquid chromatography was performed to analyze syringate, leonurine, quercetin-3-O-robiniaglycoside, hyperoside, rutin, isoquercitrin, wogonin, and genkwanin simultaneously by single standard to determine multi-components method with rutin as internal standard. Meanwhile, normal-phase high-performance liquid chromatography was performed by using an Agilent ZORBAX HILIC Plus within 6 min to determine trigonelline and stachydrine using trigonelline as internal standard. Innovatively, among these compounds, bio-active components of quercetin-3-O-robiniaglycoside and trigonelline were first determined in Herba Leonuri. In general, the method integrating multi-chromatographic analyses offered an efficient way for the standardization and identification of Herba Leonuri. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Improving diabetes care: Multi-component CArdiovascular Disease Risk Reduction Strategies for People with Diabetes in South Asia - The CARRS Multi-center Translation Trial

PubMed Central

Shah, Seema; Singh, Kavita; Ali, Mohammed K.; Mohan, V.; Kadir, Muhammad Masood; Unnikrishnan, A.G.; Sahay, Rakesh Kumar; Varthakavi, Premlata; Dharmalingam, Mala; Viswanathan, Vijay; Masood, Qamar; Bantwal, Ganapathi; Khadgawat, Rajesh; Desai, Ankush; Sethi, Bipin Kumar; Shivashankar, Roopa; Ajay, Vamadevan S; Reddy, K. Srinath; Narayan, K.M. Venkat; Prabhakaran, Dorairaj; Tandon, Nikhil

2012-01-01

Aims Cardiovascular disease (CVD) is the leading cause of morbidity and mortality in people with diabetes in South Asia. The CARRS translation trial tests the effectiveness, cost-effectiveness, and sustainability of a clinic-based multi-component CVD risk reduction intervention among people with diabetes in India and Pakistan. Methods We randomly assigned 1,146 adults with diabetes recruited from 10 urban clinic sites, to receive usual care by physicians or to receive an integrated multi-component CVD risk reduction intervention. The intervention involves electronic health record management, decision-support prompts to the healthcare team, and the support of a care coordinator to actively facilitate patient and provider adherence to evidence-based guidelines. The primary outcome is a composite of multiple CVD risk factor control (blood glucose and either blood pressure or cholesterol, or all three). Other outcomes include control of the individual CVD risk factors, process and patient-centered measures, cost-effectiveness, and acceptability/feasibility. Conclusion The CARRS translation trial tests a low-cost diabetes care delivery model in urban South Asia to achieve comprehensive cardio-metabolic disease case-management of high-risk patients (clinicaltrials.gov number: NCT01212328). PMID:23084280

Variational Bayesian Learning for Wavelet Independent Component Analysis

NASA Astrophysics Data System (ADS)

Roussos, E.; Roberts, S.; Daubechies, I.

2005-11-01

In an exploratory approach to data analysis, it is often useful to consider the observations as generated from a set of latent generators or "sources" via a generally unknown mapping. For the noisy overcomplete case, where we have more sources than observations, the problem becomes extremely ill-posed. Solutions to such inverse problems can, in many cases, be achieved by incorporating prior knowledge about the problem, captured in the form of constraints. This setting is a natural candidate for the application of the Bayesian methodology, allowing us to incorporate "soft" constraints in a natural manner. The work described in this paper is mainly driven by problems in functional magnetic resonance imaging of the brain, for the neuro-scientific goal of extracting relevant "maps" from the data. This can be stated as a `blind' source separation problem. Recent experiments in the field of neuroscience show that these maps are sparse, in some appropriate sense. The separation problem can be solved by independent component analysis (ICA), viewed as a technique for seeking sparse components, assuming appropriate distributions for the sources. We derive a hybrid wavelet-ICA model, transforming the signals into a domain where the modeling assumption of sparsity of the coefficients with respect to a dictionary is natural. We follow a graphical modeling formalism, viewing ICA as a probabilistic generative model. We use hierarchical source and mixing models and apply Bayesian inference to the problem. This allows us to perform model selection in order to infer the complexity of the representation, as well as automatic denoising. Since exact inference and learning in such a model is intractable, we follow a variational Bayesian mean-field approach in the conjugate-exponential family of distributions, for efficient unsupervised learning in multi-dimensional settings. The performance of the proposed algorithm is demonstrated on some representative experiments.

Integration of Advanced Probabilistic Analysis Techniques with Multi-Physics Models

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

Cetiner, Mustafa Sacit; none,; Flanagan, George F.

2014-07-30

An integrated simulation platform that couples probabilistic analysis-based tools with model-based simulation tools can provide valuable insights for reactive and proactive responses to plant operating conditions. The objective of this work is to demonstrate the benefits of a partial implementation of the Small Modular Reactor (SMR) Probabilistic Risk Assessment (PRA) Detailed Framework Specification through the coupling of advanced PRA capabilities and accurate multi-physics plant models. Coupling a probabilistic model with a multi-physics model will aid in design, operations, and safety by providing a more accurate understanding of plant behavior. This represents the first attempt at actually integrating these two typesmore » of analyses for a control system used for operations, on a faster than real-time basis. This report documents the development of the basic communication capability to exchange data with the probabilistic model using Reliability Workbench (RWB) and the multi-physics model using Dymola. The communication pathways from injecting a fault (i.e., failing a component) to the probabilistic and multi-physics models were successfully completed. This first version was tested with prototypic models represented in both RWB and Modelica. First, a simple event tree/fault tree (ET/FT) model was created to develop the software code to implement the communication capabilities between the dynamic-link library (dll) and RWB. A program, written in C#, successfully communicates faults to the probabilistic model through the dll. A systems model of the Advanced Liquid-Metal Reactor–Power Reactor Inherently Safe Module (ALMR-PRISM) design developed under another DOE project was upgraded using Dymola to include proper interfaces to allow data exchange with the control application (ConApp). A program, written in C+, successfully communicates faults to the multi-physics model. The results of the example simulation were successfully plotted.« less

Multibody model reduction by component mode synthesis and component cost analysis

NASA Technical Reports Server (NTRS)

Spanos, J. T.; Mingori, D. L.

1990-01-01

The classical assumed-modes method is widely used in modeling the dynamics of flexible multibody systems. According to the method, the elastic deformation of each component in the system is expanded in a series of spatial and temporal functions known as modes and modal coordinates, respectively. This paper focuses on the selection of component modes used in the assumed-modes expansion. A two-stage component modal reduction method is proposed combining Component Mode Synthesis (CMS) with Component Cost Analysis (CCA). First, each component model is truncated such that the contribution of the high frequency subsystem to the static response is preserved. Second, a new CMS procedure is employed to assemble the system model and CCA is used to further truncate component modes in accordance with their contribution to a quadratic cost function of the system output. The proposed method is demonstrated with a simple example of a flexible two-body system.

Multi-Resolution Analysis of LiDAR data for Characterizing a Stabilized Aeolian Landscape in South Texas

NASA Astrophysics Data System (ADS)

Barrineau, C. P.; Dobreva, I. D.; Bishop, M. P.; Houser, C.

2014-12-01

Aeolian systems are ideal natural laboratories for examining self-organization in patterned landscapes, as certain wind regimes generate certain morphologies. Topographic information and scale dependent analysis offer the opportunity to study such systems and characterize process-form relationships. A statistically based methodology for differentiating aeolian features would enable the quantitative association of certain surface characteristics with certain morphodynamic regimes. We conducted a multi-resolution analysis of LiDAR elevation data to assess scale-dependent morphometric variations in an aeolian landscape in South Texas. For each pixel, mean elevation values are calculated along concentric circles moving outward at 100-meter intervals (i.e. 500 m, 600 m, 700 m from pixel). The calculated average elevation values plotted against distance from the pixel of interest as curves are used to differentiate multi-scalar variations in elevation across the landscape. In this case, it is hypothesized these curves may be used to quantitatively differentiate certain morphometries from others like a spectral signature may be used to classify paved surfaces from natural vegetation, for example. After generating multi-resolution curves for all the pixels in a selected area of interest (AOI), a Principal Components Analysis is used to highlight commonalities and singularities between generated curves from pixels across the AOI. Our findings suggest that the resulting components could be used for identification of discrete aeolian features like open sands, trailing ridges and active dune crests, and, in particular, zones of deflation. This new approach to landscape characterization not only works to mitigate bias introduced when researchers must select training pixels for morphometric investigations, but can also reveal patterning in aeolian landscapes that would not be as obvious without quantitative characterization.

40 CFR 59.506 - How do I demonstrate compliance if I manufacture multi-component kits?

Code of Federal Regulations, 2011 CFR

2011-07-01

... multi-component kits as defined in § 59.503, then the Kit PWR must not exceed the Total Reactivity Limit. (b) You must calculate the Kit PWR and the Total Reactivity Limit as follows: (1) KIT PWR = (PWR(1) × W1) + (PWR(2) × W2) +. ...+ (PWR(n) × Wn) (2) Total Reactivity Limit = (RL1 × W1) + (RL2 × W2...

40 CFR 59.506 - How do I demonstrate compliance if I manufacture multi-component kits?

Code of Federal Regulations, 2014 CFR

2014-07-01

... multi-component kits as defined in § 59.503, then the Kit PWR must not exceed the Total Reactivity Limit. (b) You must calculate the Kit PWR and the Total Reactivity Limit as follows: (1) KIT PWR = (PWR(1) × W1) + (PWR(2) × W2) +. ...+ (PWR(n) × Wn) (2) Total Reactivity Limit = (RL1 × W1) + (RL2 × W2...

40 CFR 59.506 - How do I demonstrate compliance if I manufacture multi-component kits?

Code of Federal Regulations, 2012 CFR

2012-07-01

... multi-component kits as defined in § 59.503, then the Kit PWR must not exceed the Total Reactivity Limit. (b) You must calculate the Kit PWR and the Total Reactivity Limit as follows: (1) KIT PWR = (PWR(1) × W1) + (PWR(2) × W2) +. ...+ (PWR(n) × Wn) (2) Total Reactivity Limit = (RL1 × W1) + (RL2 × W2...

40 CFR 59.506 - How do I demonstrate compliance if I manufacture multi-component kits?

Code of Federal Regulations, 2013 CFR

2013-07-01

... multi-component kits as defined in § 59.503, then the Kit PWR must not exceed the Total Reactivity Limit. (b) You must calculate the Kit PWR and the Total Reactivity Limit as follows: (1) KIT PWR = (PWR(1) × W1) + (PWR(2) × W2) +. ...+ (PWR(n) × Wn) (2) Total Reactivity Limit = (RL1 × W1) + (RL2 × W2...

Development of a Multi-Disciplinary Computing Environment (MDICE)

NASA Technical Reports Server (NTRS)

Kingsley, Gerry; Siegel, John M., Jr.; Harrand, Vincent J.; Lawrence, Charles; Luker, Joel J.

1999-01-01

The growing need for and importance of multi-component and multi-disciplinary engineering analysis has been understood for many years. For many applications, loose (or semi-implicit) coupling is optimal, and allows the use of various legacy codes without requiring major modifications. For this purpose, CFDRC and NASA LeRC have developed a computational environment to enable coupling between various flow analysis codes at several levels of fidelity. This has been referred to as the Visual Computing Environment (VCE), and is being successfully applied to the analysis of several aircraft engine components. Recently, CFDRC and AFRL/VAAC (WL) have extended the framework and scope of VCE to enable complex multi-disciplinary simulations. The chosen initial focus is on aeroelastic aircraft applications. The developed software is referred to as MDICE-AE, an extensible system suitable for integration of several engineering analysis disciplines. This paper describes the methodology, basic architecture, chosen software technologies, salient library modules, and the current status of and plans for MDICE. A fluid-structure interaction application is described in a separate companion paper.

Coated platelets function in platelet-dependent fibrin formation via integrin αIIbβ3 and transglutaminase factor XIII

PubMed Central

Mattheij, Nadine J.A.; Swieringa, Frauke; Mastenbroek, Tom G.; Berny-Lang, Michelle A.; May, Frauke; Baaten, Constance C.F.M.J.; van der Meijden, Paola E.J.; Henskens, Yvonne M.C.; Beckers, Erik A.M.; Suylen, Dennis P.L.; Nolte, Marc W.; Hackeng, Tilman M.; McCarty, Owen J.T.; Heemskerk, Johan W.M.; Cosemans, Judith M.E.M.

2016-01-01

Coated platelets, formed by collagen and thrombin activation, have been characterized in different ways: i) by the formation of a protein coat of α-granular proteins; ii) by exposure of procoagulant phosphatidylserine; or iii) by high fibrinogen binding. Yet, their functional role has remained unclear. Here we used a novel transglutaminase probe, Rhod-A14, to identify a subpopulation of platelets with a cross-linked protein coat, and compared this with other platelet subpopulations using a panel of functional assays. Platelet stimulation with convulxin/thrombin resulted in initial integrin αIIbβ3 activation, the appearance of a platelet population with high fibrinogen binding, (independently of active integrins, but dependent on the presence of thrombin) followed by phosphatidylserine exposure and binding of coagulation factors Va and Xa. A subpopulation of phosphatidylserine-exposing platelets bound Rhod-A14 both in suspension and in thrombi generated on a collagen surface. In suspension, high fibrinogen and Rhod-A14 binding were antagonized by combined inhibition of transglutaminase activity and integrin αIIbβ3. Markedly, in thrombi from mice deficient in transglutaminase factor XIII, platelet-driven fibrin formation and Rhod-A14 binding were abolished by blockage of integrin αIIbβ3. Vice versa, star-like fibrin formation from platelets of a patient with deficiency in αIIbβ3 (Glanzmann thrombasthenia) was abolished upon blockage of transglutaminase activity. We conclude that coated platelets, with initial αIIbβ3 activation and high fibrinogen binding, form a subpopulation of phosphatidylserine-exposing platelets, and function in platelet-dependent star-like fibrin fiber formation via transglutaminase factor XIII and integrin αIIbβ3. PMID:26721892

Pharmacokinetic analysis of multi PEG-theophylline conjugates.

PubMed

Grassi, Mario; Bonora, Gian Maria; Drioli, Sara; Cateni, Francesca; Zacchigna, Marina

2012-10-01

In the attempt of prolonging the effect of drugs, a new branched, high-molecular weight multimeric poly(ethylene glycol) (MultiPEG), synthesized with a simple assembling procedure that devised the introduction of functional groups with divergent and selective reactivity, was employed as drug carrier. In particular, the attention was focused on the study of theophylline (THEO) and THEO-MultiPEG conjugates pharmacokinetic after oral administration in rabbit. Pharmacokinetic behavior was studied according to an ad hoc developed mathematical model accounting for THEO-MultiPEG in vivo absorption and decomposition into drug (THEO) and carrier (MultiPEG). The branched high-molecular weight MultiPEG proved to be a reliable drug delivery system able to prolong theophylline staying in the blood after oral administration of a THEO-MultiPEG solution. The analysis of experimental data by means of the developed mathematical model revealed that the prolongation of THEO effect was essentially due to the low THEO-MultiPEG permeability in comparison to that of pure THEO. Copyright © 2012 Elsevier Ltd. All rights reserved.

Few-mode fiber, splice and SDM component characterization by spatially-diverse optical vector network analysis.

PubMed

Rommel, Simon; Mendinueta, José Manuel Delgado; Klaus, Werner; Sakaguchi, Jun; Olmos, Juan José Vegas; Awaji, Yoshinari; Monroy, Idelfonso Tafur; Wada, Naoya

2017-09-18

This paper discusses spatially diverse optical vector network analysis for space division multiplexing (SDM) component and system characterization, which is becoming essential as SDM is widely considered to increase the capacity of optical communication systems. Characterization of a 108-channel photonic lantern spatial multiplexer, coupled to a 36-core 3-mode fiber, is experimentally demonstrated, extracting the full impulse response and complex transfer function matrices as well as insertion loss (IL) and mode-dependent loss (MDL) data. Moreover, the mode-mixing behavior of fiber splices in the few-mode multi-core fiber and their impact on system IL and MDL are analyzed, finding splices to cause significant mode-mixing and to be non-negligible in system capacity analysis.

Key components of financial-analysis education for clinical nurses.

PubMed

Lim, Ji Young; Noh, Wonjung

2015-09-01

In this study, we identified key components of financial-analysis education for clinical nurses. We used a literature review, focus group discussions, and a content validity index survey to develop key components of financial-analysis education. First, a wide range of references were reviewed, and 55 financial-analysis education components were gathered. Second, two focus group discussions were performed; the participants were 11 nurses who had worked for more than 3 years in a hospital, and nine components were agreed upon. Third, 12 professionals, including professors, nurse executive, nurse managers, and an accountant, participated in the content validity index. Finally, six key components of financial-analysis education were selected. These key components were as follows: understanding the need for financial analysis, introduction to financial analysis, reading and implementing balance sheets, reading and implementing income statements, understanding the concepts of financial ratios, and interpretation and practice of financial ratio analysis. The results of this study will be used to develop an education program to increase financial-management competency among clinical nurses. © 2015 Wiley Publishing Asia Pty Ltd.

Identification and visualization of dominant patterns and anomalies in remotely sensed vegetation phenology using a parallel tool for principal components analysis

Treesearch

Richard Tran Mills; Jitendra Kumar; Forrest M. Hoffman; William W. Hargrove; Joseph P. Spruce; Steven P. Norman

2013-01-01

We investigated the use of principal components analysis (PCA) to visualize dominant patterns and identify anomalies in a multi-year land surface phenology data set (231 m × 231 m normalized difference vegetation index (NDVI) values derived from the Moderate Resolution Imaging Spectroradiometer (MODIS)) used for detecting threats to forest health in the conterminous...

[Data fusion and multi-components quantitative analysis for identification and quality evaluation of Gentiana rigescens from different geographical origins].

PubMed

Wang, Qin-Qin; Shen, Tao; Zuo, Zhi-Tian; Huang, Heng-Yu; Wang, Yuan-Zhong

2018-03-01

The accumulation of secondary metabolites of traditional Chinese medicine (TCM) is closely related to its origins. The identification of origins and multi-components quantitative evaluation are of great significance to ensure the quality of medicinal materials. In this study, the identification of Gentiana rigescens from different geographical origins was conducted by data fusion of Fourier transform infrared (FTIR) spectroscopy and high performance liquid chromatography (HPLC) in combination of partial least squares discriminant analysis; meanwhile quantitative analysis of index components was conducted to provide an accurate and comprehensive identification and quality evaluation strategy for selecting the best production areas of G. rigescens. In this study, the FTIR and HPLC information of 169 G. rigescens samples from Yunnan, Sichuan, Guangxi and Guizhou Provinces were collected. The raw infrared spectra were pre-treated by multiplicative scatter correction, standard normal variate (SNV) and Savitzky-Golay (SG) derivative. Then the performances of FTIR, HPLC, and low-level data fusion and mid-level data fusion for identification were compared, and the contents of gentiopicroside, swertiamarin, loganic acid and sweroside were determined by HPLC. The results showed that the FTIR spectra of G. rigescens from different geographical origins were different, and the best pre-treatment method was SNV+SG-derivative (second derivative, 15 as the window parameter, and 2 as the polynomial order). The results showed that the accuracy rate of low- and mid-level data fusion (96.43%) in prediction set was higher than that of FTIR and HPLC (94.64%) in prediction set. In addition, the accuracy of low-level data fusion (100%) in the training set was higher than that of mid-level data fusion (99.12%) in training set. The contents of the iridoid glycosides in Yunnan were the highest among different provinces. The average content of gentiopicroside, as a bioactive marker in Chinese

Constrained Principal Component Analysis: Various Applications.

ERIC Educational Resources Information Center

Hunter, Michael; Takane, Yoshio

2002-01-01

Provides example applications of constrained principal component analysis (CPCA) that illustrate the method on a variety of contexts common to psychological research. Two new analyses, decompositions into finer components and fitting higher order structures, are presented, followed by an illustration of CPCA on contingency tables and the CPCA of…

EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis.

PubMed

Delorme, Arnaud; Makeig, Scott

2004-03-15

We have developed a toolbox and graphic user interface, EEGLAB, running under the crossplatform MATLAB environment (The Mathworks, Inc.) for processing collections of single-trial and/or averaged EEG data of any number of channels. Available functions include EEG data, channel and event information importing, data visualization (scrolling, scalp map and dipole model plotting, plus multi-trial ERP-image plots), preprocessing (including artifact rejection, filtering, epoch selection, and averaging), independent component analysis (ICA) and time/frequency decompositions including channel and component cross-coherence supported by bootstrap statistical methods based on data resampling. EEGLAB functions are organized into three layers. Top-layer functions allow users to interact with the data through the graphic interface without needing to use MATLAB syntax. Menu options allow users to tune the behavior of EEGLAB to available memory. Middle-layer functions allow users to customize data processing using command history and interactive 'pop' functions. Experienced MATLAB users can use EEGLAB data structures and stand-alone signal processing functions to write custom and/or batch analysis scripts. Extensive function help and tutorial information are included. A 'plug-in' facility allows easy incorporation of new EEG modules into the main menu. EEGLAB is freely available (http://www.sccn.ucsd.edu/eeglab/) under the GNU public license for noncommercial use and open source development, together with sample data, user tutorial and extensive documentation.

Validation of Shared and Specific Independent Component Analysis (SSICA) for Between-Group Comparisons in fMRI

PubMed Central

Maneshi, Mona; Vahdat, Shahabeddin; Gotman, Jean; Grova, Christophe

2016-01-01

Independent component analysis (ICA) has been widely used to study functional magnetic resonance imaging (fMRI) connectivity. However, the application of ICA in multi-group designs is not straightforward. We have recently developed a new method named “shared and specific independent component analysis” (SSICA) to perform between-group comparisons in the ICA framework. SSICA is sensitive to extract those components which represent a significant difference in functional connectivity between groups or conditions, i.e., components that could be considered “specific” for a group or condition. Here, we investigated the performance of SSICA on realistic simulations, and task fMRI data and compared the results with one of the state-of-the-art group ICA approaches to infer between-group differences. We examined SSICA robustness with respect to the number of allowable extracted specific components and between-group orthogonality assumptions. Furthermore, we proposed a modified formulation of the back-reconstruction method to generate group-level t-statistics maps based on SSICA results. We also evaluated the consistency and specificity of the extracted specific components by SSICA. The results on realistic simulated and real fMRI data showed that SSICA outperforms the regular group ICA approach in terms of reconstruction and classification performance. We demonstrated that SSICA is a powerful data-driven approach to detect patterns of differences in functional connectivity across groups/conditions, particularly in model-free designs such as resting-state fMRI. Our findings in task fMRI show that SSICA confirms results of the general linear model (GLM) analysis and when combined with clustering analysis, it complements GLM findings by providing additional information regarding the reliability and specificity of networks. PMID:27729843

Principal component analysis and the locus of the Fréchet mean in the space of phylogenetic trees.

PubMed

Nye, Tom M W; Tang, Xiaoxian; Weyenberg, Grady; Yoshida, Ruriko

2017-12-01

Evolutionary relationships are represented by phylogenetic trees, and a phylogenetic analysis of gene sequences typically produces a collection of these trees, one for each gene in the analysis. Analysis of samples of trees is difficult due to the multi-dimensionality of the space of possible trees. In Euclidean spaces, principal component analysis is a popular method of reducing high-dimensional data to a low-dimensional representation that preserves much of the sample's structure. However, the space of all phylogenetic trees on a fixed set of species does not form a Euclidean vector space, and methods adapted to tree space are needed. Previous work introduced the notion of a principal geodesic in this space, analogous to the first principal component. Here we propose a geometric object for tree space similar to the [Formula: see text]th principal component in Euclidean space: the locus of the weighted Fréchet mean of [Formula: see text] vertex trees when the weights vary over the [Formula: see text]-simplex. We establish some basic properties of these objects, in particular showing that they have dimension [Formula: see text], and propose algorithms for projection onto these surfaces and for finding the principal locus associated with a sample of trees. Simulation studies demonstrate that these algorithms perform well, and analyses of two datasets, containing Apicomplexa and African coelacanth genomes respectively, reveal important structure from the second principal components.

Principal components analysis in clinical studies.

PubMed

Zhang, Zhongheng; Castelló, Adela

2017-09-01

In multivariate analysis, independent variables are usually correlated to each other which can introduce multicollinearity in the regression models. One approach to solve this problem is to apply principal components analysis (PCA) over these variables. This method uses orthogonal transformation to represent sets of potentially correlated variables with principal components (PC) that are linearly uncorrelated. PCs are ordered so that the first PC has the largest possible variance and only some components are selected to represent the correlated variables. As a result, the dimension of the variable space is reduced. This tutorial illustrates how to perform PCA in R environment, the example is a simulated dataset in which two PCs are responsible for the majority of the variance in the data. Furthermore, the visualization of PCA is highlighted.

FAST TRACK COMMUNICATION Multi-component generalizations of the CH equation: geometrical aspects, peakons and numerical examples

NASA Astrophysics Data System (ADS)

Holm, D. D.; Ivanov, R. I.

2010-12-01

The Lax pair formulation of the two-component Camassa-Holm equation (CH2) is generalized to produce an integrable multi-component family, CH(n, k), of equations with n components and 1 <= |k| <= n velocities. All of the members of the CH(n, k) family show fluid-dynamics properties with coherent solitons following particle characteristics. We determine their Lie-Poisson Hamiltonian structures and give numerical examples of their soliton solution behaviour. We concentrate on the CH(2, k) family with one or two velocities, including the CH(2, -1) equation in the Dym position of the CH2 hierarchy. A brief discussion of the CH(3, 1) system reveals the underlying graded Lie-algebraic structure of the Hamiltonian formulation for CH(n, k) when n >= 3. Fondly recalling our late friend Jerry Marsden.

Multi-constituent determination and fingerprint analysis of Scutellaria indica L. using ultra high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry.

PubMed

Liang, Xianrui; Zhao, Cui; Su, Weike

2015-11-01

An ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry method integrating multi-constituent determination and fingerprint analysis has been established for quality assessment and control of Scutellaria indica L. The optimized method possesses the advantages of speediness, efficiency, and allows multi-constituents determination and fingerprint analysis in one chromatographic run within 11 min. 36 compounds were detected, and 23 of them were unequivocally identified or tentatively assigned. The established fingerprint method was applied to the analysis of ten S. indica samples from different geographic locations. The quality assessment was achieved by using principal component analysis. The proposed method is useful and reliable for the characterization of multi-constituents in a complex chemical system and the overall quality assessment of S. indica. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Ionic liquid catalyzed one-pot multi-component synthesis, characterization and antibacterial activity of novel chromeno[2,3-d]pyrimidin-8-amine derivatives

NASA Astrophysics Data System (ADS)

Kanakaraju, Sankari; Prasanna, Bethanamudi; Basavoju, Srinivas; Chandramouli, G. V. P.

2012-06-01

An efficient, simple and convenient method for the one-pot multi-component synthesis of novel chromeno[2,3-d]pyrimidin-8-amine derivatives has been accomplished by starting from α-naphthol, aryl aldehydes, malononitrile and NH4Cl. The reaction has been catalyzed by 1-butyl-3-methylimidazolium tetrafluoroborate [bmim]BF4 ionic liquid. The newly synthesized compounds were characterized by IR, 1H NMR, 13C NMR, mass spectra, and elemental analysis. The structure of compound 4a was confirmed by single-crystal X-ray diffraction. All the synthesized compounds were evaluated for their in vitro antibacterial activity.

Seismic signal time-frequency analysis based on multi-directional window using greedy strategy

NASA Astrophysics Data System (ADS)

Chen, Yingpin; Peng, Zhenming; Cheng, Zhuyuan; Tian, Lin

2017-08-01

Wigner-Ville distribution (WVD) is an important time-frequency analysis technology with a high energy distribution in seismic signal processing. However, it is interfered by many cross terms. To suppress the cross terms of the WVD and keep the concentration of its high energy distribution, an adaptive multi-directional filtering window in the ambiguity domain is proposed. This begins with the relationship of the Cohen distribution and the Gabor transform combining the greedy strategy and the rotational invariance property of the fractional Fourier transform in order to propose the multi-directional window, which extends the one-dimensional, one directional, optimal window function of the optimal fractional Gabor transform (OFrGT) to a two-dimensional, multi-directional window in the ambiguity domain. In this way, the multi-directional window matches the main auto terms of the WVD more precisely. Using the greedy strategy, the proposed window takes into account the optimal and other suboptimal directions, which also solves the problem of the OFrGT, called the local concentration phenomenon, when encountering a multi-component signal. Experiments on different types of both the signal models and the real seismic signals reveal that the proposed window can overcome the drawbacks of the WVD and the OFrGT mentioned above. Finally, the proposed method is applied to a seismic signal's spectral decomposition. The results show that the proposed method can explore the space distribution of a reservoir more precisely.

TREAT Neutronics Analysis and Design Support, Part I: Multi-SERTTA

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

Bess, John D.; Woolstenhulme, Nicolas E.; Hill, Connie M.

2016-08-01

Experiment vehicle design is necessary in preparation for Transient Reactor Test (TREAT) facility restart and the resumption of transient testing to support Accident Tolerant Fuel (ATF) characterization and other future fuels testing requirements. Currently the most mature vehicle design is the Multi-SERTTA (Static Environments Rodlet Transient Test Apparatuses), which can accommodate up to four concurrent rodlet-sized specimens under separate environmental conditions. Robust test vehicle design requires neutronics analyses to support design development, optimization of the power coupling factor (PCF) to efficiently maximize energy generation in the test fuel rodlets, and experiment safety analyses. Calculations were performed to support analysis ofmore » a near-final design of the Multi-SERTTA vehicle, the design process for future TREAT test vehicles, and establish analytical practices for upcoming transient test experiments. Models of the Multi-SERTTA vehicle containing typical PWR-fuel rodlets were prepared and neutronics calculations were performed using MCNP6.1 with ENDF/B-VII.1 nuclear data libraries. Calculation of the PCF for reference conditions of a PWR fuel rodlet in clean water at operational temperature and pressure provided results between 1.10 and 1.74 W/g-MW depending on the location of the four Multi-SERTTA units with the stack. Basic changes to the Multi-SERTTA secondary vessel containment and support have minimal impact on PCF; using materials with less neutron absorption can improve expected PCF values, especially in the primary containment. An optimized balance is needed between structural integrity, experiment safety, and energy deposition in the experiment. Type of medium and environmental conditions within the primary vessel surrounding the fuel rodlet can also have a significant impact on resultant PCF values. The estimated reactivity insertion worth into the TREAT core is impacted more by the primary and secondary Multi-SERTTA vehicle

Rapid discrimination of sea buckthorn berries from different H. rhamnoides subspecies by multi-step IR spectroscopy coupled with multivariate data analysis

NASA Astrophysics Data System (ADS)

Liu, Yue; Zhang, Ying; Zhang, Jing; Fan, Gang; Tu, Ya; Sun, Suqin; Shen, Xudong; Li, Qingzhu; Zhang, Yi

2018-03-01

As an important ethnic medicine, sea buckthorn was widely used to prevent and treat various diseases due to its nutritional and medicinal properties. According to the Chinese Pharmacopoeia, sea buckthorn was originated from H. rhamnoides, which includes five subspecies distributed in China. Confusion and misidentification usually occurred due to their similar morphology, especially in dried and powdered forms. Additionally, these five subspecies have vital differences in quality and physiological efficacy. This paper focused on the quick classification and identification method of sea buckthorn berry powders from five H. rhamnoides subspecies using multi-step IR spectroscopy coupled with multivariate data analysis. The holistic chemical compositions revealed by the FT-IR spectra demonstrated that flavonoids, fatty acids and sugars were the main chemical components. Further, the differences in FT-IR spectra regarding their peaks, positions and intensities were used to identify H. rhamnoides subspecies samples. The discrimination was achieved using principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA). The results showed that the combination of multi-step IR spectroscopy and chemometric analysis offered a simple, fast and reliable method for the classification and identification of the sea buckthorn berry powders from different H. rhamnoides subspecies.

On the direct detection of multi-component dark matter: sensitivity studies and parameter estimation

NASA Astrophysics Data System (ADS)

Herrero-Garcia, Juan; Scaffidi, Andre; White, Martin; Williams, Anthony G.

2017-11-01

We study the case of multi-component dark matter, in particular how direct detection signals are modified in the presence of several stable weakly-interacting-massive particles. Assuming a positive signal in a future direct detection experiment, stemming from two dark matter components, we study the region in parameter space where it is possible to distinguish a one from a two-component dark matter spectrum. First, we leave as free parameters the two dark matter masses and show that the two hypotheses can be significantly discriminated for a range of dark matter masses with their splitting being the critical factor. We then investigate how including the effects of different interaction strengths, local densities or velocity dispersions for the two components modifies these conclusions. We also consider the case of isospin-violating couplings. In all scenarios, we show results for various types of nuclei both for elastic spin-independent and spin-dependent interactions. Finally, assuming that the two-component hypothesis is confirmed, we quantify the accuracy with which the parameters can be extracted and discuss the different degeneracies that occur. This includes studying the case in which only a single experiment observes a signal, and also the scenario of having two signals from two different experiments, in which case the ratios of the couplings to neutrons and protons may also be extracted.

Genetic Factors Influencing Coagulation Factor XIII B-Subunit Contribute to Risk of Ischemic Stroke.

PubMed

Hanscombe, Ken B; Traylor, Matthew; Hysi, Pirro G; Bevan, Stephen; Dichgans, Martin; Rothwell, Peter M; Worrall, Bradford B; Seshadri, Sudha; Sudlow, Cathie; Williams, Frances M K; Markus, Hugh S; Lewis, Cathryn M

2015-08-01

Abnormal coagulation has been implicated in the pathogenesis of ischemic stroke, but how this association is mediated and whether it differs between ischemic stroke subtypes is unknown. We determined the shared genetic risk between 14 coagulation factors and ischemic stroke and its subtypes. Using genome-wide association study results for 14 coagulation factors from the population-based TwinsUK sample (N≈2000 for each factor), meta-analysis results from the METASTROKE consortium ischemic stroke genome-wide association study (12 389 cases, 62 004 controls), and genotype data for 9520 individuals from the WTCCC2 ischemic stroke study (3548 cases, 5972 controls-the largest METASTROKE subsample), we explored shared genetic risk for coagulation and stroke. We performed three analyses: (1) a test for excess concordance (or discordance) in single nucleotide polymorphism effect direction across coagulation and stroke, (2) an estimation of the joint effect of multiple coagulation-associated single nucleotide polymorphisms in stroke, and (3) an evaluation of common genetic risk between coagulation and stroke. One coagulation factor, factor XIII subunit B (FXIIIB), showed consistent effects in the concordance analysis, the estimation of polygenic risk, and the validation with genotype data, with associations specific to the cardioembolic stroke subtype. Effect directions for FXIIIB-associated single nucleotide polymorphisms were significantly discordant with cardioembolic disease (smallest P=5.7×10(-04)); the joint effect of FXIIIB-associated single nucleotide polymorphisms was significantly predictive of ischemic stroke (smallest P=1.8×10(-04)) and the cardioembolic subtype (smallest P=1.7×10(-04)). We found substantial negative genetic covariation between FXIIIB and ischemic stroke (rG=-0.71, P=0.01) and the cardioembolic subtype (rG=-0.80, P=0.03). Genetic markers associated with low FXIIIB levels increase risk of ischemic stroke cardioembolic subtype. © 2015 The

Comparing the effectiveness of a multi-component weight loss intervention in adults with and without intellectual disabilities.

PubMed

Spanos, D; Hankey, C; Boyle, S; Melville, C

2014-02-01

The prevalence of obesity in adults with intellectual disabilities (ID) is rising, although the evidence base for its treatment in this population group is minimal. Weight management interventions that are accessible to adults with ID will reduce the inequalities that they frequently experience in health services. This short report compared the effectiveness of weight management in those with and without ID who completed nine sessions of a multi-component weight management programme. TAKE 5 is a 16-week multi-component weight management intervention for adults with ID and obesity [body mass index (BMI) ≥30 kg m(-2) ]. This intervention is an adaption of the weight management programme provided by the Glasgow & Clyde Weight Management Service (GCWMS) for adults without ID and obesity (National Health Service based). Fifty-two participants of the TAKE 5 programme were individually matched by baseline characteristics (sex, age and BMI) with two participants without ID of the GCWMS programme. Comparisons in terms of weight and BMI change and rate of weight loss were made for those who attended all nine sessions. There were no significant differences between the groups in the amount of weight loss (median: -3.6 versus -3.8 kg, respectively, P = 0.4), change in BMI (median: -1.5 versus -1.4 kg m(-2) , P = 0.9), success of achieving 5% weight loss (41.3% versus 36.8%, P = 0.9) and rate of weight loss across the 16-week intervention. A multi-component weight loss intervention can be equally effective for adults with and without ID and obesity. © 2013 The Authors Journal of Human Nutrition and Dietetics © 2013 The British Dietetic Association Ltd.

Independent component analysis applied to long bunch beams in the Los Alamos Proton Storage Ring

NASA Astrophysics Data System (ADS)

Kolski, Jeffrey S.; Macek, Robert J.; McCrady, Rodney C.; Pang, Xiaoying

2012-11-01

Independent component analysis (ICA) is a powerful blind source separation (BSS) method. Compared to the typical BSS method, principal component analysis, ICA is more robust to noise, coupling, and nonlinearity. The conventional ICA application to turn-by-turn position data from multiple beam position monitors (BPMs) yields information about cross-BPM correlations. With this scheme, multi-BPM ICA has been used to measure the transverse betatron phase and amplitude functions, dispersion function, linear coupling, sextupole strength, and nonlinear beam dynamics. We apply ICA in a new way to slices along the bunch revealing correlations of particle motion within the beam bunch. We digitize beam signals of the long bunch at the Los Alamos Proton Storage Ring with a single device (BPM or fast current monitor) for an entire injection-extraction cycle. ICA of the digitized beam signals results in source signals, which we identify to describe varying betatron motion along the bunch, locations of transverse resonances along the bunch, measurement noise, characteristic frequencies of the digitizing oscilloscopes, and longitudinal beam structure.

Quantitative evaluation of deep and shallow tissue layers' contribution to fNIRS signal using multi-distance optodes and independent component analysis.

PubMed

Funane, Tsukasa; Atsumori, Hirokazu; Katura, Takusige; Obata, Akiko N; Sato, Hiroki; Tanikawa, Yukari; Okada, Eiji; Kiguchi, Masashi

2014-01-15

To quantify the effect of absorption changes in the deep tissue (cerebral) and shallow tissue (scalp, skin) layers on functional near-infrared spectroscopy (fNIRS) signals, a method using multi-distance (MD) optodes and independent component analysis (ICA), referred to as the MD-ICA method, is proposed. In previous studies, when the signal from the shallow tissue layer (shallow signal) needs to be eliminated, it was often assumed that the shallow signal had no correlation with the signal from the deep tissue layer (deep signal). In this study, no relationship between the waveforms of deep and shallow signals is assumed, and instead, it is assumed that both signals are linear combinations of multiple signal sources, which allows the inclusion of a "shared component" (such as systemic signals) that is contained in both layers. The method also assumes that the partial optical path length of the shallow layer does not change, whereas that of the deep layer linearly increases along with the increase of the source-detector (S-D) distance. Deep- and shallow-layer contribution ratios of each independent component (IC) are calculated using the dependence of the weight of each IC on the S-D distance. Reconstruction of deep- and shallow-layer signals are performed by the sum of ICs weighted by the deep and shallow contribution ratio. Experimental validation of the principle of this technique was conducted using a dynamic phantom with two absorbing layers. Results showed that our method is effective for evaluating deep-layer contributions even if there are high correlations between deep and shallow signals. Next, we applied the method to fNIRS signals obtained on a human head with 5-, 15-, and 30-mm S-D distances during a verbal fluency task, a verbal working memory task (prefrontal area), a finger tapping task (motor area), and a tetrametric visual checker-board task (occipital area) and then estimated the deep-layer contribution ratio. To evaluate the signal separation

NGC 3393: multi-component AGN feedback as seen by CHEERS

NASA Astrophysics Data System (ADS)

Maksym, W. Peter; Fabbiano, Giuseppina; Elvis, Martin; Karovska, Margarita; Raymond, John C.; Storchi-Bergmann, Thaisa; Paggi, Alessandro; Wang, Junfeng; Risaliti, Guido

2017-01-01

Due to its low density, moderate ionization, and weak kinematics, the narrow line region (NLR) of active galactic nuclei (AGN) provides poweful diagnostics for investigating AGN feedback. The CHandra Extended Emission line Region Survey (CHEERS) is the ultimate investigation into resolved feedback in the NLR. We present results from our CHEERS investigations of NGC 3393. By imaging extended X-ray line emission of NGC 3393 with Chandra and optical line emission with Hubble's narrow-band filters, we are able to map out the simultaneous impact of photoionization, jets and an AGN disk-wind. When resolved on scales of ~10s of parsecs, the NLR of NGC 3393 shows a complex multi-component medium. Diagnostic line mapping indicates a Low-ionization Emmision Line Region (LINER) cocoon surrounding the outflow-evacuated cavities (in optical) and surrounding the supports the presence of collisional plasma (in X-rays). These physically distinct constituent regions can only be resolved by the high-resolution imaging that Chandra and HST enable.

How Many Separable Sources? Model Selection In Independent Components Analysis

PubMed Central

Woods, Roger P.; Hansen, Lars Kai; Strother, Stephen

2015-01-01

Unlike mixtures consisting solely of non-Gaussian sources, mixtures including two or more Gaussian components cannot be separated using standard independent components analysis methods that are based on higher order statistics and independent observations. The mixed Independent Components Analysis/Principal Components Analysis (mixed ICA/PCA) model described here accommodates one or more Gaussian components in the independent components analysis model and uses principal components analysis to characterize contributions from this inseparable Gaussian subspace. Information theory can then be used to select from among potential model categories with differing numbers of Gaussian components. Based on simulation studies, the assumptions and approximations underlying the Akaike Information Criterion do not hold in this setting, even with a very large number of observations. Cross-validation is a suitable, though computationally intensive alternative for model selection. Application of the algorithm is illustrated using Fisher's iris data set and Howells' craniometric data set. Mixed ICA/PCA is of potential interest in any field of scientific investigation where the authenticity of blindly separated non-Gaussian sources might otherwise be questionable. Failure of the Akaike Information Criterion in model selection also has relevance in traditional independent components analysis where all sources are assumed non-Gaussian. PMID:25811988

Energy Levels and Radiative Rates for Transitions in F-like Sc XIII and Ne-like Sc XII and Y XXX

NASA Astrophysics Data System (ADS)

Aggarwal, Kanti

2018-05-01

Energy levels, radiative rates and lifetimes are reported for F-like Sc~XIII and Ne-like Sc~XII and Y~XXX for which the general-purpose relativistic atomic structure package ({\\sc grasp}) has been adopted. For all three ions limited data exist in the literature but comparisons have been made wherever possible to assess the accuracy of the calculations. In the present work the lowest 102, 125 and 139 levels have been considered for the respective ions. Additionally, calculations have also been performed with the flexible atomic code ({\\sc fac}) to (particularly) confirm the accuracy of energy levels.

Using Multi-Component Consultation to Increase the Integrity with Which Teachers Implement Behavioral Classroom Interventions: A Pilot Study

ERIC Educational Resources Information Center

Owens, Julie Sarno; Coles, Erika K.; Evans, Steven W.; Himawan, Lina K.; Girio-Herrera, Erin; Holdaway, Alex S.; Zoromski, Allison K.; Schamberg, Terah; Schulte, Ann

2017-01-01

The goal of this pilot study was to evaluate the effectiveness of a multi-component consultation package in improving teachers' classroom management skills, particularly among teachers with lower baseline levels of knowledge, skills, and intervention-supportive beliefs. Participants were 58 elementary school teachers (93% female; 50% Non-Hispanic…

Programmable Multi-Chip Module

DOEpatents

Kautz, David; Morgenstern, Howard; Blazek, Roy J.

2005-05-24

A multi-chip module comprising a low-temperature co-fired ceramic substrate having a first side on which are mounted active components and a second side on which are mounted passive components, wherein this segregation of components allows for hermetically sealing the active components with a cover while leaving accessible the passive components, and wherein the passive components are secured using a reflow soldering technique and are removable and replaceable so as to make the multi-chip module substantially programmable with regard to the passive components.

Programmable Multi-Chip Module

DOEpatents

Kautz, David; Morgenstern, Howard; Blazek, Roy J.

2004-11-16

A multi-chip module comprising a low-temperature co-fired ceramic substrate having a first side on which are mounted active components and a second side on which are mounted passive components, wherein this segregation of components allows for hermetically sealing the active components with a cover while leaving accessible the passive components, and wherein the passive components are secured using a reflow soldering technique and are removable and replaceable so as to make the multi-chip module substantially programmable with regard to the passive components.

Programmable multi-chip module

DOEpatents

Kautz, David; Morgenstern, Howard; Blazek, Roy J.

2004-03-02

A multi-chip module comprising a low-temperature co-fired ceramic substrate having a first side on which are mounted active components and a second side on which are mounted passive components, wherein this segregation of components allows for hermetically sealing the active components with a cover while leaving accessible the passive components, and wherein the passive components are secured using a reflow soldering technique and are removable and replaceable so as to make the multi-chip module substantially programmable with regard to the passive components.

Multi-focus and multi-level techniques for visualization and analysis of networks with thematic data

NASA Astrophysics Data System (ADS)

Cossalter, Michele; Mengshoel, Ole J.; Selker, Ted

2013-01-01

Information-rich data sets bring several challenges in the areas of visualization and analysis, even when associated with node-link network visualizations. This paper presents an integration of multi-focus and multi-level techniques that enable interactive, multi-step comparisons in node-link networks. We describe NetEx, a visualization tool that enables users to simultaneously explore different parts of a network and its thematic data, such as time series or conditional probability tables. NetEx, implemented as a Cytoscape plug-in, has been applied to the analysis of electrical power networks, Bayesian networks, and the Enron e-mail repository. In this paper we briefly discuss visualization and analysis of the Enron social network, but focus on data from an electrical power network. Specifically, we demonstrate how NetEx supports the analytical task of electrical power system fault diagnosis. Results from a user study with 25 subjects suggest that NetEx enables more accurate isolation of complex faults compared to an especially designed software tool.

DEVELOPMENT OF MULTI-PHASE AND MULTI-COMPONENT FLOW MODEL WITH REACTION IN POROUS MEDIA FOR RISK ASSESSMENT ON SOIL CONTAMINATION DUE TO MINERAL OIL

NASA Astrophysics Data System (ADS)

Sakamoto, Yasuhide; Nishiwaki, Junko; Hara, Junko; Kawabe, Yoshishige; Sugai, Yuichi; Komai, Takeshi

In late years, soil contamination due to mineral oil in vacant lots of oil factory and oil field has become obvious. Measure for soil contamina tion and risk assessment are neces sary for sustainable development of industrial activity. Especially, in addition to contaminated sites, various exposure paths for human body such as well water, soil and farm crop are supposed. So it is very important to comprehend the transport phenomena of contaminated material under the environments of soil and ground water. In this study, mineral oil as c ontaminated material consisting of mu lti-component such as aliphatic and aromatic series was modeled. Then numerical mode l for transport phenomena in surface soil and aquifer was constructed. On the basis of modeling for mineral oil, our numerical model consists of three-phase (oil, water and gas) forty three-component. This numerical model becomes base program for risk assessment system on soil contamination due to mineral oil. Using this numerical model, we carried out some numerical simulation for a laboratory-scale experiment on oil-water multi-phase flow. Relative permeability that dominate flow behavior in multi-phase condition was formulated and the validity of the numerical model developed in this study was considered.

Multi-level Simulation of a Real Time Vibration Monitoring System Component

NASA Technical Reports Server (NTRS)

Robertson, Bryan A.; Wilkerson, Delisa

2005-01-01

This paper describes the development of a custom built Digital Signal Processing (DSP) printed circuit board designed to implement the Advanced Real Time Vibration Monitoring Subsystem proposed by Marshall Space Flight Center (MSFC) Transportation Directorate in 2000 for the Space Shuttle Main Engine Advanced Health Management System (AHMS). This Real Time Vibration Monitoring System (RTVMS) is being developed for ground use as part of the AHMS Health Management Computer-Integrated Rack Assembly (HMC-IRA). The HMC-IRA RTVMS design contains five DSPs which are highly interconnected through individual communication ports, shared memory, and a unique communication router that allows all the DSPs to receive digitized data fiom two multi-channel analog boards simultaneously. This paper will briefly cover the overall board design but will focus primarily on the state-of-the-art simulation environment within which this board was developed. This 16-layer board with over 1800 components and an additional mezzanine card has been an extremely challenging design. Utilization of a Mentor Graphics simulation environment provided the unique board and system level simulation capability to ascertain any timing or functional concerns before production. By combining VHDL, Synopsys Software and Hardware Models, and the Mentor Design Capture Environment, multiple simulations were developed to verify the RTVMS design. This multi-level simulation allowed the designers to achieve complete operability without error the first time the RTVMS printed circuit board was powered. The HMC-IRA design has completed all engineering and deliverable unit testing. P

Multi-level Simulation of a Real Time Vibration Monitoring System Component

NASA Technical Reports Server (NTRS)

Roberston, Bryan; Wilkerson, DeLisa

2004-01-01

This paper describes the development of a custom built Digital Signal Processing (DSP) printed circuit board designed to implement the Advanced Real Time Vibration Monitoring Subsystem proposed by MSFC Transportation Directorate in 2000 for the Space Shuttle Main Engine Advanced Health Management System (AHMS). This Real Time Vibration Monitoring System (RTVMS) is being developed for ground use as part of the AHMS Health Management Computer-Integrated Rack Assembly (HMC-IRA). The HMC-IRA RTVMS design contains five DSPs which are highly interconnected through individual communication ports, shared memory, and a unique communication router that allows all the DSPs to receive digitized data from two multi-channel analog boards simultaneously. This paper will briefly cover the overall board design but will focus primarily on the state-of-the-art simulation environment within which this board was developed. This 16-layer board with over 1800 components and an additional mezzanine card has been an extremely challenging design. Utilization of a Mentor Graphics simulation environment provided the unique board and system level simulation capability to ascertain any timing or functional concerns before production. By combining VHDL, Synopsys Software and Hardware Models, and the Mentor Design Capture Environment, multiple simulations were developed to verify the RTVMS design. This multi-level simulation allowed the designers to achieve complete operability without error the first time the RTVMS printed circuit board was powered. The HMCIRA design has completed all engineering unit testing and the deliverable unit is currently under development.

Analysis of truss, beam, frame, and membrane components. [composite structures

NASA Technical Reports Server (NTRS)

Knoell, A. C.; Robinson, E. Y.

1975-01-01

Truss components are considered, taking into account composite truss structures, truss analysis, column members, and truss joints. Beam components are discussed, giving attention to composite beams, laminated beams, and sandwich beams. Composite frame components and composite membrane components are examined. A description is given of examples of flat membrane components and examples of curved membrane elements. It is pointed out that composite structural design and analysis is a highly interactive, iterative procedure which does not lend itself readily to characterization by design or analysis function only.-

High Accuracy Passive Magnetic Field-Based Localization for Feedback Control Using Principal Component Analysis.

PubMed

Foong, Shaohui; Sun, Zhenglong

2016-08-12

In this paper, a novel magnetic field-based sensing system employing statistically optimized concurrent multiple sensor outputs for precise field-position association and localization is presented. This method capitalizes on the independence between simultaneous spatial field measurements at multiple locations to induce unique correspondences between field and position. This single-source-multi-sensor configuration is able to achieve accurate and precise localization and tracking of translational motion without contact over large travel distances for feedback control. Principal component analysis (PCA) is used as a pseudo-linear filter to optimally reduce the dimensions of the multi-sensor output space for computationally efficient field-position mapping with artificial neural networks (ANNs). Numerical simulations are employed to investigate the effects of geometric parameters and Gaussian noise corruption on PCA assisted ANN mapping performance. Using a 9-sensor network, the sensing accuracy and closed-loop tracking performance of the proposed optimal field-based sensing system is experimentally evaluated on a linear actuator with a significantly more expensive optical encoder as a comparison.

Construction and Analysis of Multi-Rate Partitioned Runge-Kutta Methods

DTIC Science & Technology

2012-06-01

ANALYSIS OF MULTI-RATE PARTITIONED RUNGE-KUTTA METHODS by Patrick R. Mugg June 2012 Thesis Advisor: Francis Giraldo Second Reader: Hong...COVERED Master’s Thesis 4. TITLE AND SUBTITLE Construction and Analysis of Multi-Rate Partitioned Runge-Kutta Methods 5. FUNDING NUMBERS 6. AUTHOR...The most widely known and used procedure for analyzing stability is the Von Neumann Method , such that Von Neumann’s stability analysis looks at

Multilevel sparse functional principal component analysis.

PubMed

Di, Chongzhi; Crainiceanu, Ciprian M; Jank, Wolfgang S

2014-01-29

We consider analysis of sparsely sampled multilevel functional data, where the basic observational unit is a function and data have a natural hierarchy of basic units. An example is when functions are recorded at multiple visits for each subject. Multilevel functional principal component analysis (MFPCA; Di et al. 2009) was proposed for such data when functions are densely recorded. Here we consider the case when functions are sparsely sampled and may contain only a few observations per function. We exploit the multilevel structure of covariance operators and achieve data reduction by principal component decompositions at both between and within subject levels. We address inherent methodological differences in the sparse sampling context to: 1) estimate the covariance operators; 2) estimate the functional principal component scores; 3) predict the underlying curves. Through simulations the proposed method is able to discover dominating modes of variations and reconstruct underlying curves well even in sparse settings. Our approach is illustrated by two applications, the Sleep Heart Health Study and eBay auctions.

XML Encoding of Features Describing Rule-Based Modeling of Reaction Networks with Multi-Component Molecular Complexes

PubMed Central

Blinov, Michael L.; Moraru, Ion I.

2011-01-01

Multi-state molecules and multi-component complexes are commonly involved in cellular signaling. Accounting for molecules that have multiple potential states, such as a protein that may be phosphorylated on multiple residues, and molecules that combine to form heterogeneous complexes located among multiple compartments, generates an effect of combinatorial complexity. Models involving relatively few signaling molecules can include thousands of distinct chemical species. Several software tools (StochSim, BioNetGen) are already available to deal with combinatorial complexity. Such tools need information standards if models are to be shared, jointly evaluated and developed. Here we discuss XML conventions that can be adopted for modeling biochemical reaction networks described by user-specified reaction rules. These could form a basis for possible future extensions of the Systems Biology Markup Language (SBML). PMID:21464833

Cost Analysis in a Multi-Mission Operations Environment

NASA Technical Reports Server (NTRS)

Felton, Larry; Newhouse, Marilyn; Bornas, Nick; Botts, Dennis; Ijames, Gayleen; Montgomery, Patty; Roth, Karl

2014-01-01

Spacecraft control centers have evolved from dedicated, single-mission or single mission-type support to multi-mission, service-oriented support for operating a variety of mission types. At the same time, available money for projects is shrinking and competition for new missions is increasing. These factors drive the need for an accurate and flexible model to support estimating service costs for new or extended missions; the cost model in turn drives the need for an accurate and efficient approach to service cost analysis. The National Aeronautics and Space Administration (NASA) Huntsville Operations Support Center (HOSC) at Marshall Space Flight Center (MSFC) provides operations services to a variety of customers around the world. HOSC customers range from launch vehicle test flights; to International Space Station (ISS) payloads; to small, short duration missions; and has included long duration flagship missions. The HOSC recently completed a detailed analysis of service costs as part of the development of a complete service cost model. The cost analysis process required the team to address a number of issues. One of the primary issues involves the difficulty of reverse engineering individual mission costs in a highly efficient multi-mission environment, along with a related issue of the value of detailed metrics or data to the cost model versus the cost of obtaining accurate data. Another concern is the difficulty of balancing costs between missions of different types and size and extrapolating costs to different mission types. The cost analysis also had to address issues relating to providing shared, cloud-like services in a government environment, and then assigning an uncertainty or risk factor to cost estimates that are based on current technology, but will be executed using future technology. Finally the cost analysis needed to consider how to validate the resulting cost models taking into account the non-homogeneous nature of the available cost data and

Optimal pattern synthesis for speech recognition based on principal component analysis

NASA Astrophysics Data System (ADS)

Korsun, O. N.; Poliyev, A. V.

2018-02-01

The algorithm for building an optimal pattern for the purpose of automatic speech recognition, which increases the probability of correct recognition, is developed and presented in this work. The optimal pattern forming is based on the decomposition of an initial pattern to principal components, which enables to reduce the dimension of multi-parameter optimization problem. At the next step the training samples are introduced and the optimal estimates for principal components decomposition coefficients are obtained by a numeric parameter optimization algorithm. Finally, we consider the experiment results that show the improvement in speech recognition introduced by the proposed optimization algorithm.

Incorporating principal component analysis into air quality ...

EPA Pesticide Factsheets

The efficacy of standard air quality model evaluation techniques is becoming compromised as the simulation periods continue to lengthen in response to ever increasing computing capacity. Accordingly, the purpose of this paper is to demonstrate a statistical approach called Principal Component Analysis (PCA) with the intent of motivating its use by the evaluation community. One of the main objectives of PCA is to identify, through data reduction, the recurring and independent modes of variations (or signals) within a very large dataset, thereby summarizing the essential information of that dataset so that meaningful and descriptive conclusions can be made. In this demonstration, PCA is applied to a simple evaluation metric – the model bias associated with EPA's Community Multi-scale Air Quality (CMAQ) model when compared to weekly observations of sulfate (SO42−) and ammonium (NH4+) ambient air concentrations measured by the Clean Air Status and Trends Network (CASTNet). The advantages of using this technique are demonstrated as it identifies strong and systematic patterns of CMAQ model bias across a myriad of spatial and temporal scales that are neither constrained to geopolitical boundaries nor monthly/seasonal time periods (a limitation of many current studies). The technique also identifies locations (station–grid cell pairs) that are used as indicators for a more thorough diagnostic evaluation thereby hastening and facilitating understanding of the prob

Evaluation of a multi-component approach to cognitive-behavioral therapy (CBT) using guided visualizations, cranial electrotherapy stimulation, and vibroacoustic sound.

PubMed

Rogers, Donna R B; Ei, Sue; Rogers, Kim R; Cross, Chad L

2007-05-01

This pilot study examines the use of guided visualizations that incorporate both cognitive and behavioral techniques with vibroacoustic therapy and cranial electrotherapy stimulation to form a multi-component therapeutic approach. This multi-component approach to cognitive-behavioral therapy (CBT) was used to treat patients presenting with a range of symptoms including anxiety, depression, and relationship difficulties. Clients completed a pre- and post-session symptom severity scale and CBT skills practice survey. The program consisted of 16 guided visualizations incorporating CBT techniques that were accompanied by vibroacoustic therapy and cranial electrotherapy stimulation. Significant reduction in symptom severity was observed in pre- and post-session scores for anxiety symptoms, relationship difficulties, and depressive symptoms. The majority of the clients (88%) reported use of CBT techniques learned in the guided visualizations at least once per week outside of the sessions.

A Nonparametric Approach to Segmentation of Ladar Images

DTIC Science & Technology

2012-12-01

82 5.3.4 Simulation ...91 6.2.1 Multi-Facet Board Simulation ...Pulse spreading effects are ignored. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63 xiii Figure Page 5.4. Signal pulse energy with

EDITORIAL: XIII Mexican Workshop on Particles and Fields

NASA Astrophysics Data System (ADS)

Barranco, Juan; Contreras, Guillermo; Delepine, David; Napsuciale, Mauro

2012-08-01

Juan Barranco Physics Department, Guanajuato University, Loma del Bosque 103, col. Loma del Campestre, 37150, Leon (Mexico) jbarranc@fisica.ugto.mx Guillermo Contreras Departamento de Fisica Aplicada Centro de Investigacion y de Estudios Avanzados del Instituto Politecnico Nacional, Merida (Mexico) jgcn@mda.cinvestav.mx David Delepine Physics Department, Guanajuato University, Loma del Bosque 103, col. Loma del Campestre, 37150, Leon (Mexico) delepine@fisica.ugto.mx Mauro Napsuciale Physics Department, Guanajuato University, Loma del Bosque 103, col. Loma del Campestre, 37150, Leon (Mexico) mauro@fisica.ugto.mx The XIII Mexican Workshop on Particles and Fields (MWPF) took place from 20-26 October 2011, in the city of León, Guanajuato, México. This is a biennial meeting organized by the Division of Particles and Fields of the Mexican Physical Society designed to gather specialists in different areas of high energy physics to discuss the latest developments in the field. The thirteenth edition of this meeting was hosted by the Department of Cultural Studies of Guanajuato University in a nice environment dedicated to the Arts and Culture. The XIII MWPF was organized by three working groups who organized the corresponding sessions around three topics. The first one was Strings, Cosmology, Astroparticles and Physics Beyond the Standard Model. In this category we included: Cosmic Rays, Gamma Ray Bursts, Physics Beyond the Standard Model (theory and experimental searches), Strings and Cosmology. The working group for this topic was formed by Arnulfo Zepeda, Oscar Loaiza, Axel de la Macorra and Myriam Mondragón. The second topic was Hadronic Matter which included Perturbative QCD, Jets and Diffractive Physics, Hadronic Structure, Soft QCD, Hadron Spectroscopy, Heavy Ion Collisions and Soft Physics at Hadron Colliders, Lattice Results and Instrumentation. The working group for this topic was integrated by Wolfgang Bietenholz and Mariana Kirchbach. The third topic was

Multi-ingredients determination and fingerprint analysis of leaves from Ilex latifolia using ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry.

PubMed

Fan, Chunlin; Deng, Jiewei; Yang, Yunyun; Liu, Junshan; Wang, Ying; Zhang, Xiaoqi; Fai, Kuokchiu; Zhang, Qingwen; Ye, Wencai

2013-10-01

An ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) method integrating multi-ingredients determination and fingerprint analysis has been established for quality assessment and control of leaves from Ilex latifolia. The method possesses the advantages of speediness, efficiency, accuracy, and allows the multi-ingredients determination and fingerprint analysis in one chromatographic run within 13min. Multi-ingredients determination was performed based on the extracted ion chromatograms of the exact pseudo-molecular ions (with a 0.01Da window), and fingerprint analysis was performed based on the base peak chromatograms, obtained by negative-ion electrospray ionization QTOF-MS. The method validation results demonstrated our developed method possessing desirable specificity, linearity, precision and accuracy. The method was utilized to analyze 22 I. latifolia samples from different origins. The quality assessment was achieved by using both similarity analysis (SA) and principal component analysis (PCA), and the results from SA were consistent with those from PCA. Our experimental results demonstrate that the strategy integrated multi-ingredients determination and fingerprint analysis using UPLC-QTOF-MS technique is a useful approach for rapid pharmaceutical analysis, with promising prospects for the differentiation of origin, the determination of authenticity, and the overall quality assessment of herbal medicines. Copyright © 2013 Elsevier B.V. All rights reserved.

The Effectiveness of Modified Multi-Component Cognitive Strategy Instruction in Expository Text Comprehension of Students with Mild Intellectual Disabilities

ERIC Educational Resources Information Center

Bilgi, Arzu Doganay; Özmen, E. Rüya

2018-01-01

This study investigates the effectiveness of Modified Multi-Component Cognitive Strategy Instruction (MMCSI) on expository text comprehension skills of students with mild intellectual disability (ID). Three students participated from inclusion classes of three different secondary schools in Turkey. The study was conducted using a multiple probe…

Nonaqueous Phase Liquid Dissolution in Porous Media: Multi-Scale Effects of Multi-Component Dissolution Kinetics on Cleanup Time

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

McNab, W; Ezzedine, S; Detwiler, R

2007-02-26

Industrial organic solvents such as trichloroethylene (TCE) and tetrachloroethylene (PCE) constitute a principal class of groundwater contaminants. Cleanup of groundwater plume source areas associated with these compounds is problematic, in part, because the compounds often exist in the subsurface as dense nonaqueous phase liquids (DNAPLs). Ganglia (or 'blobs') of DNAPL serve as persistent sources of contaminants that are difficult to locate and remediate (e.g. Fenwick and Blunt, 1998). Current understanding of the physical and chemical processes associated with dissolution of DNAPLs in the subsurface is incomplete and yet is critical for evaluating long-term behavior of contaminant migration, groundwater cleanup, andmore » the efficacy of source area cleanup technologies. As such, a goal of this project has been to contribute to this critical understanding by investigating the multi-phase, multi-component physics of DNAPL dissolution using state-of-the-art experimental and computational techniques. Through this research, we have explored efficient and accurate conceptual and numerical models for source area contaminant transport that can be used to better inform the modeling of source area contaminants, including those at the LLNL Superfund sites, to re-evaluate existing remediation technologies, and to inspire or develop new remediation strategies. The problem of DNAPL dissolution in natural porous media must be viewed in the context of several scales (Khachikian and Harmon, 2000), including the microscopic level at which capillary forces, viscous forces, and gravity/buoyancy forces are manifested at the scale of individual pores (Wilson and Conrad, 1984; Chatzis et al., 1988), the mesoscale where dissolution rates are strongly influenced by the local hydrodynamics, and the field-scale. Historically, the physico-chemical processes associated with DNAPL dissolution have been addressed through the use of lumped mass transfer coefficients which attempt to quantify

Multi-system Component Phenotypes of Bipolar Disorder for Genetic Investigations of Extended Pedigrees

PubMed Central

Fears, Scott C.; Service, Susan K.; Kremeyer, Barbara; Araya, Carmen; Araya, Xinia; Bejarano, Julio; Ramirez, Margarita; Castrillón, Gabriel; Gomez-Franco, Juliana; Lopez, Maria C.; Montoya, Gabriel; Montoya, Patricia; Aldana, Ileana; Teshiba, Terri M.; Abaryan, Zvart; Al-Sharif, Noor B.; Ericson, Marissa; Jalbrzikowski, Maria; Luykx, Jurjen J.; Navarro, Linda; Tishler, Todd A.; Altshuler, Lori; Bartzokis, George; Escobar, Javier; Glahn, David C.; Ospina-Duque, Jorge; Risch, Neil; Ruiz-Linares, Andrés; Thompson, Paul M.; Cantor, Rita M.; Lopez-Jaramillo, Carlos; Macaya, Gabriel; Molina, Julio; Reus, Victor I.; Sabatti, Chiara; Freimer, Nelson B.; Bearden, Carrie E.

2014-01-01

IMPORTANCE Genetic factors contribute to risk for bipolar disorder (BP), yet its pathogenesis remains poorly understood. A focus on measuring multi-system quantitative traits that may be components of BP psychopathology may enable genetic dissection of this complex disorder, and investigation of extended pedigrees from genetically isolated populations may facilitate the detection of specific genetic variants that impact on BP as well as its component phenotypes. OBJECTIVE To identify quantitative neurocognitive, temperament-related, and neuroanatomic phenotypes that appear heritable and associated with severe bipolar disorder (BP-I), and therefore suitable for genetic linkage and association studies aimed at identifying variants contributing to BP-I risk. DESIGN Multi-generational pedigree study in two closely related, genetically isolated populations: the Central Valley of Costa Rica (CVCR) and Antioquia, Colombia (ANT). PARTICIPANTS 738 individuals, all from CVCR and ANT pedigrees, of whom 181 are affected with BP-I. MAIN OUTCOME MEASURE Familial aggregation (heritability) and association with BP-I of 169 quantitative neurocognitive, temperament, magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) phenotypes. RESULTS Seventy-five percent (126) of the phenotypes investigated were significantly heritable, and 31% (53) were associated with BP-I. About 1/4 of the phenotypes, including measures from each phenotype domain, were both heritable and associated with BP-I. Neuroimaging phenotypes, particularly cortical thickness in prefrontal and temporal regions, and volume and microstructural integrity of the corpus callosum, represented the most promising candidate traits for genetic mapping related to BP based on strong heritability and association with disease. Analyses of phenotypic and genetic covariation identified substantial correlations among the traits, at least some of which share a common underlying genetic architecture. CONCLUSIONS AND

Bi-continuous Multi-component Nanocrystal Superlattices for Solar Energy Conversion

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

Kagan, Cherie; Murray, Christopher; Kikkawa, James

2017-06-14

Our SISGR program studied an emerging class of nanomaterials wherein different combinations of semiconductor or semiconductor and plasmonic nanocrystals (NCs) are self-assembled into three-dimensional multi-component superlattices. The NC assemblies were designed to form bicontinuous semiconductor NC sublattices with type-II energy offsets to drive charge separation onto electron and hole transporting sublattices for collection and introduce plasmonic NCs to increase solar absorption and charge separation. Our group is expert in synthesizing and assembling an extraordinary variety of artificial systems by tailoring the NC building blocks and the superlattice unit cell geometry. Under this DOE BES Materials Chemistry program, we introduced chemicalmore » methods to control inter-particle distance and to dope NC assemblies, which enabled our demonstration of strong electronic communication between NCs and the use of NC thin films as electronic materials. We synthesized, assembled and structurally, spectroscopically, and electrically probed NC superlattices to understand and manipulate the flow of energy and charge toward discovering the design rules and optimizing these complex architectures to create materials that efficiently convert solar radiation into electricity.« less

Least Principal Components Analysis (LPCA): An Alternative to Regression Analysis.

ERIC Educational Resources Information Center

Olson, Jeffery E.

Often, all of the variables in a model are latent, random, or subject to measurement error, or there is not an obvious dependent variable. When any of these conditions exist, an appropriate method for estimating the linear relationships among the variables is Least Principal Components Analysis. Least Principal Components are robust, consistent,…

Vlasov Simulation of Electrostatic Solitary Structures in Multi-Component Plasmas

NASA Technical Reports Server (NTRS)

Umeda, Takayuki; Ashour-Abdalla, Maha; Pickett, Jolene S.; Goldstein, Melvyn L.

2012-01-01

Electrostatic solitary structures have been observed in the Earth's magnetosheath by the Cluster spacecraft. Recent theoretical work has suggested that these solitary structures are modeled by electron acoustic solitary waves existing in a four-component plasma system consisting of core electrons, two counter-streaming electron beams, and one species of background ions. In this paper, the excitation of electron acoustic waves and the formation of solitary structures are studied by means of a one-dimensional electrostatic Vlasov simulation. The present result first shows that either electron acoustic solitary waves with negative potential or electron phase-space holes with positive potential are excited in four-component plasma systems. However, these electrostatic solitary structures have longer duration times and higher wave amplitudes than the solitary structures observed in the magnetosheath. The result indicates that a high-speed and small free energy source may be needed as a fifth component. An additional simulation of a five-component plasma consisting of a stable four-component plasma and a weak electron beam shows the generation of small and fast electron phase-space holes by the bump-on-tail instability. The physical properties of the small and fast electron phase-space holes are very similar to those obtained by the previous theoretical analysis. The amplitude and duration time of solitary structures in the simulation are also in agreement with the Cluster observation.

A Real Time System for Multi-Sensor Image Analysis through Pyramidal Segmentation

DTIC Science & Technology

1992-01-30

A Real Time Syte for M~ulti- sensor Image Analysis S. E I0 through Pyramidal Segmentation/ / c •) L. Rudin, S. Osher, G. Koepfler, J.9. Morel 7. ytu...experiments with reconnaissance photography, multi- sensor satellite imagery, medical CT and MRI multi-band data have shown a great practi- cal potential...C ,SF _/ -- / WSM iS-I-0-d41-40450 $tltwt, kw" I (nor.- . Z-97- A real-time system for multi- sensor image analysis through pyramidal segmentation

Extreme Ultraviolet Emission Lines of Iron Fe XI-XIII

NASA Astrophysics Data System (ADS)

Lepson, Jaan; Beiersdorfer, P.; Brown, G. V.; Liedahl, D. A.; Brickhouse, N. S.; Dupree, A. K.

2013-04-01

The extreme ultraviolet (EUV) spectral region (ca. 20--300 Å) is rich in emission lines from low- to mid-Z ions, particularly from the middle charge states of iron. Many of these emission lines are important diagnostics for astrophysical plasmas, providing information on properties such as elemental abundance, temperature, density, and even magnetic field strength. In recent years, strides have been made to understand the complexity of the atomic levels of the ions that emit the lines that contribute to the richness of the EUV region. Laboratory measurements have been made to verify and benchmark the lines. Here, we present laboratory measurements of Fe XI, Fe XII, and Fe XIII between 40-140 Å. The measurements were made at the Lawrence Livermore electron beam ion trap (EBIT) facility, which has been optimized for laboratory astrophysics, and which allows us to select specific charge states of iron to help line identification. We also present new calculations by the Hebrew University - Lawrence Livermore Atomic Code (HULLAC), which we also utilized for line identification. We found that HULLAC does a creditable job of reproducing the forest of lines we observed in the EBIT spectra, although line positions are in need of adjustment, and line intensities often differed from those observed. We identify or confirm a number of new lines for these charge states. This work was supported by the NASA Solar and Heliospheric Program under Contract NNH10AN31I and the DOE General Plasma Science program. Work was performed in part under the auspices of the Department of Energy by Lawrence Livermore National Laboratory under Contract DEAC52-07NA27344.

Recombinant Factor XIII Mitigates Hemorrhagic Shock-Induced Organ Dysfunction

PubMed Central

Zaets, Sergey B.; Xu, Da-Zhong; Lu, Qi; Feketova, Eleonora; Berezina, Tamara L.; Malinina, Inga V.; Deitch, Edwin A.; Olsen, Eva H.

2012-01-01

Background Plasma factor XIII (FXIII) is responsible for stabilization of fibrin clot at the final stage of blood coagulation. Since FXIII has also been shown to modulate inflammation, endothelial permeability, as well as diminish multiple organ dysfunction (MOD) after gut ischemia-reperfusion injury, we hypothesized that FXIII would reduce MOD caused by trauma-hemorrhagic shock (THS). Materials and methods Rats were subjected to a 90 min THS or trauma sham shock (TSS) and treated with either recombinant human FXIII A2 subunit (rFXIII) or placebo immediately after resuscitation with shed blood or at the end of the TSS period. Lung permeability, lung and gut myeloperoxidase (MPO) activity, gut histology, neutrophil respiratory burst, microvascular blood flow in the liver and muscles, and cytokine levels were measured 3 h after the THS or TSS. FXIII levels were measured before THS or TSS and after the 3-h post-shock period. Results THS-induced lung permeability as well as lung and gut MPO activity was significantly lower in rFXIII-treated than in placebo-treated animals. Similarly, rFXIII-treated rats had lower neutrophil respiratory burst activity and less ileal mucosal injury. rFXIII-treated rats also had a higher liver microvascular blood flow compared with the placebo group. Cytokine response was more favorable in rFXIII-treated animals. Trauma-hemorrhagic shock did not cause a drop in FXIII activity during the study period. Conclusions Administration of rFXIII diminishes THS-induced MOD in rats, presumably by preservation of the gut barrier function, limitation of polymorphonuclear leukocyte (PMN) activation, and modulation of the cytokine response. PMID:21276979

Functional factor XIII-A is exposed on the stimulated platelet surface

PubMed Central

Mitchell, Joanne L.; Lionikiene, Ausra S.; Fraser, Steven R.; Whyte, Claire S.; Booth, Nuala A.

2014-01-01

Factor XIII (FXIII) stabilizes thrombi against fibrinolysis by cross-linking α2-antiplasmin (α2AP) to fibrin. Cellular FXIII (FXIII-A) is abundant in platelets, but the extracellular functions of this pool are unclear because it is not released by classical secretion mechanisms. We examined the function of platelet FXIII-A using Chandler model thrombi formed from FXIII-depleted plasma. Platelets stabilized FXIII-depleted thrombi in a transglutaminase-dependent manner. FXIII-A activity on activated platelets was unstable and was rapidly lost over 1 hour. Inhibiting platelet activation abrogated the ability of platelets to stabilize thrombi. Incorporating a neutralizing antibody to α2AP into FXIII-depleted thrombi revealed that the stabilizing effect of platelet FXIII-A on lysis was α2AP dependent. Platelet FXIII-A activity and antigen were associated with the cytoplasm and membrane fraction of unstimulated platelets, and these fractions were functional in stabilizing FXIII-depleted thrombi against lysis. Fluorescence confocal microscopy and flow cytometry revealed exposure of FXIII-A on activated membranes, with maximal signal detected with thrombin and collagen stimulation. FXIII-A was evident in protruding caps on the surface of phosphatidylserine-positive platelets. Our data show a functional role for platelet FXIII-A through exposure on the activated platelet membrane where it exerts antifibrinolytic function by cross-linking α2AP to fibrin. PMID:25331118

Generalized Analysis Tools for Multi-Spacecraft Missions

NASA Astrophysics Data System (ADS)

Chanteur, G. M.

2011-12-01

Analysis tools for multi-spacecraft missions like CLUSTER or MMS have been designed since the end of the 90's to estimate gradients of fields or to characterize discontinuities crossed by a cluster of spacecraft. Different approaches have been presented and discussed in the book "Analysis Methods for Multi-Spacecraft Data" published as Scientific Report 001 of the International Space Science Institute in Bern, Switzerland (G. Paschmann and P. Daly Eds., 1998). On one hand the approach using methods of least squares has the advantage to apply to any number of spacecraft [1] but is not convenient to perform analytical computation especially when considering the error analysis. On the other hand the barycentric approach is powerful as it provides simple analytical formulas involving the reciprocal vectors of the tetrahedron [2] but appears limited to clusters of four spacecraft. Moreover the barycentric approach allows to derive theoretical formulas for errors affecting the estimators built from the reciprocal vectors [2,3,4]. Following a first generalization of reciprocal vectors proposed by Vogt et al [4] and despite the present lack of projects with more than four spacecraft we present generalized reciprocal vectors for a cluster made of any number of spacecraft : each spacecraft is given a positive or nul weight. The non-coplanarity of at least four spacecraft with strictly positive weights is a necessary and sufficient condition for this analysis to be enabled. Weights given to spacecraft allow to minimize the influence of some spacecraft if its location or the quality of its data are not appropriate, or simply to extract subsets of spacecraft from the cluster. Estimators presented in [2] are generalized within this new frame except for the error analysis which is still under investigation. References [1] Harvey, C. C.: Spatial Gradients and the Volumetric Tensor, in: Analysis Methods for Multi-Spacecraft Data, G. Paschmann and P. Daly (eds.), pp. 307-322, ISSI

Generalized Structured Component Analysis with Latent Interactions

ERIC Educational Resources Information Center

Hwang, Heungsun; Ho, Moon-Ho Ringo; Lee, Jonathan

2010-01-01

Generalized structured component analysis (GSCA) is a component-based approach to structural equation modeling. In practice, researchers may often be interested in examining the interaction effects of latent variables. However, GSCA has been geared only for the specification and testing of the main effects of variables. Thus, an extension of GSCA…

Nonlinear Principal Components Analysis: Introduction and Application

ERIC Educational Resources Information Center

Linting, Marielle; Meulman, Jacqueline J.; Groenen, Patrick J. F.; van der Koojj, Anita J.

2007-01-01

The authors provide a didactic treatment of nonlinear (categorical) principal components analysis (PCA). This method is the nonlinear equivalent of standard PCA and reduces the observed variables to a number of uncorrelated principal components. The most important advantages of nonlinear over linear PCA are that it incorporates nominal and ordinal…

Dynamical Friction in Multi-component Evolving Globular Clusters

NASA Astrophysics Data System (ADS)

Alessandrini, Emiliano; Lanzoni, Barbara; Miocchi, Paolo; Ciotti, Luca; Ferraro, Francesco R.

2014-11-01

We use the Chandrasekhar formalism and direct N-body simulations to study the effect of dynamical friction on a test object only slightly more massive than the field stars, orbiting a spherically symmetric background of particles with a mass spectrum. The main goal is to verify whether the dynamical friction time (t DF) develops a non-monotonic radial dependence that could explain the bimodality of the blue straggler radial distributions observed in globular clusters. In these systems, in fact, relaxation effects lead to a mass and velocity radial segregation of the different mass components, so that mass-spectrum effects on t DF are expected to be dependent on radius. We find that in spite of the presence of different masses, t DF is always a monotonic function of radius, at all evolutionary times and independently of the initial concentration of the simulated cluster. This is because the radial dependence of t DF is largely dominated by the total mass density profile of the background stars (which is monotonically decreasing with radius). Hence, a progressive temporal erosion of the blue straggler star (BSS) population at larger and larger distances from the cluster center remains the simplest and the most likely explanation of the shape of the observed BSS radial distributions, as suggested in previous works. We also confirm the theoretical expectation that approximating a multi-mass globular cluster as made of (averaged) equal-mass stars can lead to significant overestimations of t DF within the half-mass radius.

Wavelet decomposition based principal component analysis for face recognition using MATLAB

NASA Astrophysics Data System (ADS)

Sharma, Mahesh Kumar; Sharma, Shashikant; Leeprechanon, Nopbhorn; Ranjan, Aashish

2016-03-01

For the realization of face recognition systems in the static as well as in the real time frame, algorithms such as principal component analysis, independent component analysis, linear discriminate analysis, neural networks and genetic algorithms are used for decades. This paper discusses an approach which is a wavelet decomposition based principal component analysis for face recognition. Principal component analysis is chosen over other algorithms due to its relative simplicity, efficiency, and robustness features. The term face recognition stands for identifying a person from his facial gestures and having resemblance with factor analysis in some sense, i.e. extraction of the principal component of an image. Principal component analysis is subjected to some drawbacks, mainly the poor discriminatory power and the large computational load in finding eigenvectors, in particular. These drawbacks can be greatly reduced by combining both wavelet transform decomposition for feature extraction and principal component analysis for pattern representation and classification together, by analyzing the facial gestures into space and time domain, where, frequency and time are used interchangeably. From the experimental results, it is envisaged that this face recognition method has made a significant percentage improvement in recognition rate as well as having a better computational efficiency.

Multi-mission space vehicle subsystem analysis tools

NASA Technical Reports Server (NTRS)

Kordon, M.; Wood, E.

2003-01-01

Spacecraft engineers often rely on specialized simulation tools to facilitate the analysis, design and operation of space systems. Unfortunately these tools are often designed for one phase of a single mission and cannot be easily adapted to other phases or other misions. The Multi-Mission Pace Vehicle Susbsystem Analysis Tools are designed to provide a solution to this problem.

Multi-Core Processor Memory Contention Benchmark Analysis Case Study

NASA Technical Reports Server (NTRS)

Simon, Tyler; McGalliard, James

2009-01-01

Multi-core processors dominate current mainframe, server, and high performance computing (HPC) systems. This paper provides synthetic kernel and natural benchmark results from an HPC system at the NASA Goddard Space Flight Center that illustrate the performance impacts of multi-core (dual- and quad-core) vs. single core processor systems. Analysis of processor design, application source code, and synthetic and natural test results all indicate that multi-core processors can suffer from significant memory subsystem contention compared to similar single-core processors.

Ranking and averaging independent component analysis by reproducibility (RAICAR).

PubMed

Yang, Zhi; LaConte, Stephen; Weng, Xuchu; Hu, Xiaoping

2008-06-01

Independent component analysis (ICA) is a data-driven approach that has exhibited great utility for functional magnetic resonance imaging (fMRI). Standard ICA implementations, however, do not provide the number and relative importance of the resulting components. In addition, ICA algorithms utilizing gradient-based optimization give decompositions that are dependent on initialization values, which can lead to dramatically different results. In this work, a new method, RAICAR (Ranking and Averaging Independent Component Analysis by Reproducibility), is introduced to address these issues for spatial ICA applied to fMRI. RAICAR utilizes repeated ICA realizations and relies on the reproducibility between them to rank and select components. Different realizations are aligned based on correlations, leading to aligned components. Each component is ranked and thresholded based on between-realization correlations. Furthermore, different realizations of each aligned component are selectively averaged to generate the final estimate of the given component. Reliability and accuracy of this method are demonstrated with both simulated and experimental fMRI data. Copyright 2007 Wiley-Liss, Inc.

Multi-Component, Multi-Point Interferometric Rayleigh/Mie Doppler Velocimeter

NASA Technical Reports Server (NTRS)

Danehy, Paul M.; Lee, Joseph W.; Bivolaru, Daniel

2012-01-01

An interferometric Rayleigh scattering system was developed to enable the measurement of multiple, orthogonal velocity components at several points within very-high-speed or high-temperature flows. The velocity of a gaseous flow can be optically measured by sending laser light into the gas flow, and then measuring the scattered light signal that is returned from matter within the flow. Scattering can arise from either gas molecules within the flow itself, known as Rayleigh scattering, or from particles within the flow, known as Mie scattering. Measuring Mie scattering is the basis of all commercial laser Doppler and particle imaging velocimetry systems, but particle seeding is problematic when measuring high-speed and high-temperature flows. The velocimeter is designed to measure the Doppler shift from only Rayleigh scattering, and does not require, but can also measure, particles within the flow. The system combines a direct-view, large-optic interferometric setup that calculates the Doppler shift from fringe patterns collected with a digital camera, and a subsystem to capture and re-circulate scattered light to maximize signal density. By measuring two orthogonal components of the velocity at multiple positions in the flow volume, the accuracy and usefulness of the flow measurement increase significantly over single or nonorthogonal component approaches.

Nonlinear Dynamics of Multi-Component Bose-Einstein Condensates ---Anti-Gravity Transport and Vortex Chaos---

NASA Astrophysics Data System (ADS)

Nakamura, K.

Bose-Einstein condensate(BEC) provides a nice stage when the nonlinearSchrödinger equation plays a vital role. We study the dynamics of multi-component repulsive BEC in 2 dimensions with harmonic traps by using the nonlinear Schrödinger (or Gross-Pitaevskii) equation. Firstly we consider a driven two-component BEC with each component trapped in different vertical positions. The appropriate tuning of the oscillation frequency of the magnetic field leads to a striking anti-gravity transport of BEC. This phenomenon is a manifestation of macroscopic non-adiabatic tunneling in a system with two internal(electronic) degrees of freedom. The dynamics splits into a fast complex spatio-temporal oscillation of each condensate wavefunctions together with a slow levitation of the total center of mass. Secondly, we examine the three-component repulsive BEC in 2 dimensions in a harmonic trap in the absence of magnetic field, and construct a model of conservative chaos based on a picture of vortex molecules. We obtain an effective nonlinear dynamics for three vortex cores, which represents three charged particles under the uniform magnetic field with the repulsive inter-particle potential quadratic in the inter-vortex distance r_{ij} on short scale and logarithmic in r_{ij} on large scale. The vortices here acquire the inertia in marked contrast to the standard theory of point vortices since Onsager. We then explore ``the chaos in the three-body problem" in the context of vortices with inertia.

Relaxation mode analysis of a peptide system: comparison with principal component analysis.

PubMed

Mitsutake, Ayori; Iijima, Hiromitsu; Takano, Hiroshi

2011-10-28

This article reports the first attempt to apply the relaxation mode analysis method to a simulation of a biomolecular system. In biomolecular systems, the principal component analysis is a well-known method for analyzing the static properties of fluctuations of structures obtained by a simulation and classifying the structures into some groups. On the other hand, the relaxation mode analysis has been used to analyze the dynamic properties of homopolymer systems. In this article, a long Monte Carlo simulation of Met-enkephalin in gas phase has been performed. The results are analyzed by the principal component analysis and relaxation mode analysis methods. We compare the results of both methods and show the effectiveness of the relaxation mode analysis.

Multi-component lightweight gearwheels with deep-drawn wheel body for automotive applications

NASA Astrophysics Data System (ADS)

Benkert, Tim; Hiller, Maria; Volk, Wolfram

2017-09-01

Multi-component gearwheels offer great lightweight opportunities for automotive applications. An assembly of a gear ring and a wheel body joined by press fit replaces the monolithic gearwheel. To save weight, the wheel body uses lightweight design. This lightweight design influences the assembled gearwheel’s mechanical properties like stiffness, weight and torque capacity. Further, the wheel body material influences the mentioned properties as well. In this paper, the effects of the lightweight wheel body manufactured by deep-drawing on the mechanical properties of the assembled gearwheel are investigated. Three different wheel body designs are examined regarding their stiffness and weight compared to a reference gearwheel. Using the best design, the influence of five materials with increasing yield strength on the maximum torque the gearwheel can transmit is studied. All research is done virtually using Abaqus 6.12-3.

Characterization of groups using composite kernels and multi-source fMRI analysis data: application to schizophrenia

PubMed Central

Castro, Eduardo; Martínez-Ramón, Manel; Pearlson, Godfrey; Sui, Jing; Calhoun, Vince D.

2011-01-01

Pattern classification of brain imaging data can enable the automatic detection of differences in cognitive processes of specific groups of interest. Furthermore, it can also give neuroanatomical information related to the regions of the brain that are most relevant to detect these differences by means of feature selection procedures, which are also well-suited to deal with the high dimensionality of brain imaging data. This work proposes the application of recursive feature elimination using a machine learning algorithm based on composite kernels to the classification of healthy controls and patients with schizophrenia. This framework, which evaluates nonlinear relationships between voxels, analyzes whole-brain fMRI data from an auditory task experiment that is segmented into anatomical regions and recursively eliminates the uninformative ones based on their relevance estimates, thus yielding the set of most discriminative brain areas for group classification. The collected data was processed using two analysis methods: the general linear model (GLM) and independent component analysis (ICA). GLM spatial maps as well as ICA temporal lobe and default mode component maps were then input to the classifier. A mean classification accuracy of up to 95% estimated with a leave-two-out cross-validation procedure was achieved by doing multi-source data classification. In addition, it is shown that the classification accuracy rate obtained by using multi-source data surpasses that reached by using single-source data, hence showing that this algorithm takes advantage of the complimentary nature of GLM and ICA. PMID:21723948

Real-space analysis of radiation-induced specific changes with independent component analysis

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

Borek, Dominika; Bromberg, Raquel; Hattne, Johan

A method of analysis is presented that allows for the separation of specific radiation-induced changes into distinct components in real space. The method relies on independent component analysis (ICA) and can be effectively applied to electron density maps and other types of maps, provided that they can be represented as sets of numbers on a grid. Here, for glucose isomerase crystals, ICA was used in a proof-of-concept analysis to separate temperature-dependent and temperature-independent components of specific radiation-induced changes for data sets acquired from multiple crystals across multiple temperatures. ICA identified two components, with the temperature-independent component being responsible for themore » majority of specific radiation-induced changes at temperatures below 130 K. The patterns of specific temperature-independent radiation-induced changes suggest a contribution from the tunnelling of electron holes as a possible explanation. In the second case, where a group of 22 data sets was collected on a single thaumatin crystal, ICA was used in another type of analysis to separate specific radiation-induced effects happening on different exposure-level scales. Here, ICA identified two components of specific radiation-induced changes that likely result from radiation-induced chemical reactions progressing with different rates at different locations in the structure. In addition, ICA unexpectedly identified the radiation-damage state corresponding to reduced disulfide bridges rather than the zero-dose extrapolated state as the highest contrast structure. The application of ICA to the analysis of specific radiation-induced changes in real space and the data pre-processing for ICA that relies on singular value decomposition, which was used previously in data space to validate a two-component physical model of X-ray radiation-induced changes, are discussed in detail. This work lays a foundation for a better understanding of protein-specific radiation

Design and synthesis of single-source molecular precursors to homogeneous multi-component oxide materials

NASA Astrophysics Data System (ADS)

Fujdala, Kyle Lee

This dissertation describes the syntheses of single-source molecular precursors to multi-component oxide materials. These molecules possess a core metal or element with various combinations of -OSi(O tBu)3, -O2P(OtBu) 2, and -OB[OSi(OtBu)3] 2 ligands. Such molecules decompose under mild thermolytic conditions (<200°C) to provide homogeneous carbon-free materials via the elimination of isobutylene and water. A gel is formed when thermolyses are performed in non-polar solvents, and subsequent drying of the gel in a conventional manner yields high surface area xerogels. This thermolytic molecular precursor (TMP) approach has been utilized to provide a variety of oxide materials with tailored properties. In addition, the oxygen rich environment of the molecular precursors coupled with the presence of M-O-E heterolinkages permits use of them as models for oxide-supported metal species and multi-component oxides. Significantly, the first complexes to contain three or more heteroelements suitable for use in the TMP method have been synthesized. Compounds for use as single-source molecular precursors have been synthesized containing Al, B, Cr, Hf, Mo, V, W, and Zr, and their thermal transformations have been examined. Heterogeneous catalytic reactions have been examined for selected materials. Also, cothermolyses of molecular precursors and additional molecules (i.e., metal alkoxides) have been utilized to provide materials with several components for potential use as catalysts or catalyst supports. Reactions of one and two equivs of HOSi(OtBu) 3 with Cr(OtBu)4 afforded the first Cr(IV) alkoxysiloxy complexes (tBuO) 3CrOSi(OtBu)3 and ( tBuO)2Cr[OSi(OtBu) 3]2, respectively. The high-yielding, convenient synthesis of (tBuO)3CrOSi(O tBu)3 make this complex a useful single-source molecular precursor, via the TMP method, to Cr/Si/O materials. The thermal transformations of (tBuO)3CrOSi(O tBu)3 and (tBuO) 2Cr[OSi(OtBu)3]2 to chromia-silica materials occurr at low temperatures

A Dimensionality Reduction-Based Multi-Step Clustering Method for Robust Vessel Trajectory Analysis

PubMed Central

Liu, Jingxian; Wu, Kefeng

2017-01-01

The Shipboard Automatic Identification System (AIS) is crucial for navigation safety and maritime surveillance, data mining and pattern analysis of AIS information have attracted considerable attention in terms of both basic research and practical applications. Clustering of spatio-temporal AIS trajectories can be used to identify abnormal patterns and mine customary route data for transportation safety. Thus, the capacities of navigation safety and maritime traffic monitoring could be enhanced correspondingly. However, trajectory clustering is often sensitive to undesirable outliers and is essentially more complex compared with traditional point clustering. To overcome this limitation, a multi-step trajectory clustering method is proposed in this paper for robust AIS trajectory clustering. In particular, the Dynamic Time Warping (DTW), a similarity measurement method, is introduced in the first step to measure the distances between different trajectories. The calculated distances, inversely proportional to the similarities, constitute a distance matrix in the second step. Furthermore, as a widely-used dimensional reduction method, Principal Component Analysis (PCA) is exploited to decompose the obtained distance matrix. In particular, the top k principal components with above 95% accumulative contribution rate are extracted by PCA, and the number of the centers k is chosen. The k centers are found by the improved center automatically selection algorithm. In the last step, the improved center clustering algorithm with k clusters is implemented on the distance matrix to achieve the final AIS trajectory clustering results. In order to improve the accuracy of the proposed multi-step clustering algorithm, an automatic algorithm for choosing the k clusters is developed according to the similarity distance. Numerous experiments on realistic AIS trajectory datasets in the bridge area waterway and Mississippi River have been implemented to compare our proposed method with

Factor XIII stiffens fibrin clots by causing fiber compaction.

PubMed

Kurniawan, N A; Grimbergen, J; Koopman, J; Koenderink, G H

2014-10-01

Factor XIII-induced cross-linking has long been associated with the ability of fibrin blood clots to resist mechanical deformation, but how FXIII can directly modulate clot stiffness is unknown. We hypothesized that FXIII affects the self-assembly of fibrin fibers by altering the lateral association between protofibrils. To test this hypothesis, we studied the cross-linking kinetics and the structural evolution of the fibers and clots during the formation of plasma-derived and recombinant fibrins by using light scattering, and the response of the clots to mechanical stresses by using rheology. We show that the lateral aggregation of fibrin protofibrils initially results in the formation of floppy fibril bundles, which then compact to form tight and more rigid fibers. The first stage is reflected in a fast (10 min) increase in clot stiffness, whereas the compaction phase is characterized by a slow (hours) development of clot stiffness. Inhibition of FXIII completely abrogates the slow compaction. FXIII strongly increases the linear elastic modulus of the clots, but does not affect the non-linear response at large deformations. We propose a multiscale structural model whereby FXIII-mediated cross-linking tightens the coupling between the protofibrils within a fibrin fiber, thus making the fiber stiffer and less porous. At small strains, fiber stiffening enhances clot stiffness, because the clot response is governed by the entropic elasticity of the fibers, but once the clot is sufficiently stressed, the modulus is independent of protofibril coupling, because clot stiffness is governed by individual protofibril stretching. © 2014 International Society on Thrombosis and Haemostasis.

The Veggie Project: a case study of a multi-component farmers' market intervention.

PubMed

Freedman, Darcy A; Bell, Bethany A; Collins, Leslie V

2011-08-01

This case study provides an in-depth examination of process and feasibility factors associated with the development of a multi-component environmental intervention designed to increase access to fresh fruits and vegetables in four low-income, minority, urban communities with few healthy food retail outlets. The intervention, the Veggie Project, included three components: (a) onsite farmers' markets, (b) a Super Shopper voucher program, and (c) a Youth Leader Board. We analyzed receipts from sales transactions at the farmers' markets, close-ended surveys with participants, in-depth interviews with project stakeholders, and journal entries completed by youth participants. Thirty-four farmers' markets occurred, resulting in 1,101 sales transactions. Financial vouchers were used to purchased 63% of the produce. All of the youth Super Shoppers came to the market at least once and made significantly more purchase transactions than adults. The farmers' markets were never accessed by 38% of the adult Super Shoppers. The Veggie Project increased access to healthy foods, particularly among youth. More research is warranted to examine the relationship between market use and dietary behaviors as well as other factors (i.e., besides physical and economic) influencing food access among adults.

The multi-level perspective analysis: Indonesia geothermal energy transition study

NASA Astrophysics Data System (ADS)

Wisaksono, A.; Murphy, J.; Sharp, J. H.; Younger, P. L.

2018-01-01

The study adopts a multi-level perspective in technology transition to analyse how the transition process in the development of geothermal energy in Indonesia is able to compete against the incumbent fossil-fuelled energy sources. Three levels of multi-level perspective are socio-technical landscape (ST-landscape), socio-technical regime (ST-regime) and niche innovations in Indonesia geothermal development. The identification, mapping and analysis of the dynamic relationship between each level are the important pillars of the multi-level perspective framework. The analysis considers the set of rules, actors and controversies that may arise in the technological transition process. The identified geothermal resource risks are the basis of the emerging geothermal technological innovations in Indonesian geothermal. The analysis of this study reveals the transition pathway, which yields a forecast for the Indonesian geothermal technology transition in the form of scenarios and probable impacts.

Component Cost Analysis of Large Scale Systems

NASA Technical Reports Server (NTRS)

Skelton, R. E.; Yousuff, A.

1982-01-01

The ideas of cost decomposition is summarized to aid in the determination of the relative cost (or 'price') of each component of a linear dynamic system using quadratic performance criteria. In addition to the insights into system behavior that are afforded by such a component cost analysis CCA, these CCA ideas naturally lead to a theory for cost-equivalent realizations.

BaTMAn: Bayesian Technique for Multi-image Analysis

NASA Astrophysics Data System (ADS)

Casado, J.; Ascasibar, Y.; García-Benito, R.; Guidi, G.; Choudhury, O. S.; Bellocchi, E.; Sánchez, S. F.; Díaz, A. I.

2016-12-01

Bayesian Technique for Multi-image Analysis (BaTMAn) characterizes any astronomical dataset containing spatial information and performs a tessellation based on the measurements and errors provided as input. The algorithm iteratively merges spatial elements as long as they are statistically consistent with carrying the same information (i.e. identical signal within the errors). The output segmentations successfully adapt to the underlying spatial structure, regardless of its morphology and/or the statistical properties of the noise. BaTMAn identifies (and keeps) all the statistically-significant information contained in the input multi-image (e.g. an IFS datacube). The main aim of the algorithm is to characterize spatially-resolved data prior to their analysis.

Simultaneously extracting multiple parameters via multi-distance and multi-exposure diffuse speckle contrast analysis

PubMed Central

Liu, Jialin; Zhang, Hongchao; Lu, Jian; Ni, Xiaowu; Shen, Zhonghua

2017-01-01

Recent advancements in diffuse speckle contrast analysis (DSCA) have opened the path for noninvasive acquisition of deep tissue microvasculature blood flow. In fact, in addition to blood flow index αDB, the variations of tissue optical absorption μa, reduced scattering coefficients μs′, as well as coherence factor β can modulate temporal fluctuations of speckle patterns. In this study, we use multi-distance and multi-exposure DSCA (MDME-DSCA) to simultaneously extract multiple parameters such as μa, μs′, αDB, and β. The validity of MDME-DSCA has been validated by the simulated data and phantoms experiments. Moreover, as a comparison, the results also show that it is impractical to simultaneously obtain multiple parameters by multi-exposure DSCA (ME-DSCA). PMID:29082083

Satellite image fusion based on principal component analysis and high-pass filtering.

PubMed

Metwalli, Mohamed R; Nasr, Ayman H; Allah, Osama S Farag; El-Rabaie, S; Abd El-Samie, Fathi E

2010-06-01

This paper presents an integrated method for the fusion of satellite images. Several commercial earth observation satellites carry dual-resolution sensors, which provide high spatial resolution or simply high-resolution (HR) panchromatic (pan) images and low-resolution (LR) multi-spectral (MS) images. Image fusion methods are therefore required to integrate a high-spectral-resolution MS image with a high-spatial-resolution pan image to produce a pan-sharpened image with high spectral and spatial resolutions. Some image fusion methods such as the intensity, hue, and saturation (IHS) method, the principal component analysis (PCA) method, and the Brovey transform (BT) method provide HR MS images, but with low spectral quality. Another family of image fusion methods, such as the high-pass-filtering (HPF) method, operates on the basis of the injection of high frequency components from the HR pan image into the MS image. This family of methods provides less spectral distortion. In this paper, we propose the integration of the PCA method and the HPF method to provide a pan-sharpened MS image with superior spatial resolution and less spectral distortion. The experimental results show that the proposed fusion method retains the spectral characteristics of the MS image and, at the same time, improves the spatial resolution of the pan-sharpened image.

Cost-effectiveness Analysis in R Using a Multi-state Modeling Survival Analysis Framework: A Tutorial.

PubMed

Williams, Claire; Lewsey, James D; Briggs, Andrew H; Mackay, Daniel F

2017-05-01

This tutorial provides a step-by-step guide to performing cost-effectiveness analysis using a multi-state modeling approach. Alongside the tutorial, we provide easy-to-use functions in the statistics package R. We argue that this multi-state modeling approach using a package such as R has advantages over approaches where models are built in a spreadsheet package. In particular, using a syntax-based approach means there is a written record of what was done and the calculations are transparent. Reproducing the analysis is straightforward as the syntax just needs to be run again. The approach can be thought of as an alternative way to build a Markov decision-analytic model, which also has the option to use a state-arrival extended approach. In the state-arrival extended multi-state model, a covariate that represents patients' history is included, allowing the Markov property to be tested. We illustrate the building of multi-state survival models, making predictions from the models and assessing fits. We then proceed to perform a cost-effectiveness analysis, including deterministic and probabilistic sensitivity analyses. Finally, we show how to create 2 common methods of visualizing the results-namely, cost-effectiveness planes and cost-effectiveness acceptability curves. The analysis is implemented entirely within R. It is based on adaptions to functions in the existing R package mstate to accommodate parametric multi-state modeling that facilitates extrapolation of survival curves.

MultiSpec—a tool for multispectral hyperspectral image data analysis

NASA Astrophysics Data System (ADS)

Biehl, Larry; Landgrebe, David

2002-12-01

MultiSpec is a multispectral image data analysis software application. It is intended to provide a fast, easy-to-use means for analysis of multispectral image data, such as that from the Landsat, SPOT, MODIS or IKONOS series of Earth observational satellites, hyperspectral data such as that from the Airborne Visible-Infrared Imaging Spectrometer (AVIRIS) and EO-1 Hyperion satellite system or the data that will be produced by the next generation of Earth observational sensors. The primary purpose for the system was to make new, otherwise complex analysis tools available to the general Earth science community. It has also found use in displaying and analyzing many other types of non-space related digital imagery, such as medical image data and in K-12 and university level educational activities. MultiSpec has been implemented for both the Apple Macintosh ® and Microsoft Windows ® operating systems (OS). The effort was first begun on the Macintosh OS in 1988. The GLOBE ( http://www.globe.gov) program supported the development of a subset of MultiSpec for the Windows OS in 1995. Since then most (but not all) of the features in the Macintosh OS version have been ported to the Windows OS version. Although copyrighted, MultiSpec with its documentation is distributed without charge. The Macintosh and Windows versions and documentation on its use are available from the World Wide Web at URL: http://dynamo.ecn.purdue.edu/˜biehl/MultiSpec/ MultiSpec is copyrighted (1991-2001) by Purdue Research Foundation, West Lafayette, Indiana 47907.

Meta-Analysis of Mathematic Basic-Fact Fluency Interventions: A Component Analysis

ERIC Educational Resources Information Center

Codding, Robin S.; Burns, Matthew K.; Lukito, Gracia

2011-01-01

Mathematics fluency is a critical component of mathematics learning yet few attempts have been made to synthesize this research base. Seventeen single-case design studies with 55 participants were reviewed using meta-analytic procedures. A component analysis of practice elements was conducted and treatment intensity and feasibility were examined.…

EXTRACTING PRINCIPLE COMPONENTS FOR DISCRIMINANT ANALYSIS OF FMRI IMAGES.

PubMed

Liu, Jingyu; Xu, Lai; Caprihan, Arvind; Calhoun, Vince D

2008-05-12

This paper presents an approach for selecting optimal components for discriminant analysis. Such an approach is useful when further detailed analyses for discrimination or characterization requires dimensionality reduction. Our approach can accommodate a categorical variable such as diagnosis (e.g. schizophrenic patient or healthy control), or a continuous variable like severity of the disorder. This information is utilized as a reference for measuring a component's discriminant power after principle component decomposition. After sorting each component according to its discriminant power, we extract the best components for discriminant analysis. An application of our reference selection approach is shown using a functional magnetic resonance imaging data set in which the sample size is much less than the dimensionality. The results show that the reference selection approach provides an improved discriminant component set as compared to other approaches. Our approach is general and provides a solid foundation for further discrimination and classification studies.

Multi-criteria analysis for PM10 planning

NASA Astrophysics Data System (ADS)

Pisoni, Enrico; Carnevale, Claudio; Volta, Marialuisa

To implement sound air quality policies, Regulatory Agencies require tools to evaluate outcomes and costs associated to different emission reduction strategies. These tools are even more useful when considering atmospheric PM10 concentrations due to the complex nonlinear processes that affect production and accumulation of the secondary fraction of this pollutant. The approaches presented in the literature (Integrated Assessment Modeling) are mainly cost-benefit and cost-effective analysis. In this work, the formulation of a multi-objective problem to control particulate matter is proposed. The methodology defines: (a) the control objectives (the air quality indicator and the emission reduction cost functions); (b) the decision variables (precursor emission reductions); (c) the problem constraints (maximum feasible technology reductions). The cause-effect relations between air quality indicators and decision variables are identified tuning nonlinear source-receptor models. The multi-objective problem solution provides to the decision maker a set of not-dominated scenarios representing the efficient trade-off between the air quality benefit and the internal costs (emission reduction technology costs). The methodology has been implemented for Northern Italy, often affected by high long-term exposure to PM10. The source-receptor models used in the multi-objective analysis are identified processing long-term simulations of GAMES multiphase modeling system, performed in the framework of CAFE-Citydelta project.

Least-dependent-component analysis based on mutual information

NASA Astrophysics Data System (ADS)

Stögbauer, Harald; Kraskov, Alexander; Astakhov, Sergey A.; Grassberger, Peter

2004-12-01

We propose to use precise estimators of mutual information (MI) to find the least dependent components in a linearly mixed signal. On the one hand, this seems to lead to better blind source separation than with any other presently available algorithm. On the other hand, it has the advantage, compared to other implementations of “independent” component analysis (ICA), some of which are based on crude approximations for MI, that the numerical values of the MI can be used for (i) estimating residual dependencies between the output components; (ii) estimating the reliability of the output by comparing the pairwise MIs with those of remixed components; and (iii) clustering the output according to the residual interdependencies. For the MI estimator, we use a recently proposed k -nearest-neighbor-based algorithm. For time sequences, we combine this with delay embedding, in order to take into account nontrivial time correlations. After several tests with artificial data, we apply the resulting MILCA (mutual-information-based least dependent component analysis) algorithm to a real-world dataset, the ECG of a pregnant woman.

[A case of pancreatic and duodenal fistula after total gastrectomy successfully treated with coagulation factor XIII].

PubMed

Nishino, Hitoe; Kojima, Kazuhiro; Oshima, Hirokazu; Nakagawa, Koji; Fumura, Masao; Kikuchi, Norio

2013-11-01

Pancreatic fistula( PF) is a challenging postoperative complication. We report a case of PF following gastrectomy successfully treated using intravenous coagulation factor XIII( FXIII).A 78-year-old man with early gastric cancer underwent total gastrectomy with Roux-en-Y reconstruction. PF developed postoperatively, following which, leakage from the duodenal stump was observed. Percutaneous drainage and re-operative surgery were performed. A somatostatin analogue, antibiotic drugs, and gabexate mesilate were administrated along with nutritional support. The pancreatic and duodenal fistula had been producing duodenal juice for over 30 days since the re-operative surgery. As suspected, reduced FXIII activity was confirmed in the patient. After administering FXIII for 5 days, the amount of duodenal juice from the fistula markedly reduced, and the fistula closed immediately afterwards. The results of our study suggest that administration of FXIII could be a reasonable and effective treatment for patients with pancreatic or/and enterocutaneous fistula who are resistant to standard treatments.

Photogrammetric Deflection Measurements for the Tiltrotor Test Rig (TTR) Multi-Component Rotor Balance Calibration

NASA Technical Reports Server (NTRS)

Solis, Eduardo; Meyn, Larry

2016-01-01

Calibrating the internal, multi-component balance mounted in the Tiltrotor Test Rig (TTR) required photogrammetric measurements to determine the location and orientation of forces applied to the balance. The TTR, with the balance and calibration hardware attached, was mounted in a custom calibration stand. Calibration loads were applied using eleven hydraulic actuators, operating in tension only, that were attached to the forward frame of the calibration stand and the TTR calibration hardware via linkages with in-line load cells. Before the linkages were installed, photogrammetry was used to determine the location of the linkage attachment points on the forward frame and on the TTR calibration hardware. Photogrammetric measurements were used to determine the displacement of the linkage attachment points on the TTR due to deflection of the hardware under applied loads. These measurements represent the first photogrammetric deflection measurements to be made to support 6-component rotor balance calibration. This paper describes the design of the TTR and the calibration hardware, and presents the development, set-up and use of the photogrammetry system, along with some selected measurement results.

Technical Note: Introduction of variance component analysis to setup error analysis in radiotherapy

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

Matsuo, Yukinori, E-mail: ymatsuo@kuhp.kyoto-u.ac.

Purpose: The purpose of this technical note is to introduce variance component analysis to the estimation of systematic and random components in setup error of radiotherapy. Methods: Balanced data according to the one-factor random effect model were assumed. Results: Analysis-of-variance (ANOVA)-based computation was applied to estimate the values and their confidence intervals (CIs) for systematic and random errors and the population mean of setup errors. The conventional method overestimates systematic error, especially in hypofractionated settings. The CI for systematic error becomes much wider than that for random error. The ANOVA-based estimation can be extended to a multifactor model considering multiplemore » causes of setup errors (e.g., interpatient, interfraction, and intrafraction). Conclusions: Variance component analysis may lead to novel applications to setup error analysis in radiotherapy.« less

Evolution of optical fibre cabling components at CERN: Performance and technology trends analysis

NASA Astrophysics Data System (ADS)

Shoaie, Mohammad Amin; Meroli, Stefano; Machado, Simao; Ricci, Daniel

2018-05-01

CERN optical fibre infrastructure has been growing constantly over the past decade due to ever increasing connectivity demands. The provisioning plan and fibre installation of this vast laboratory is performed by Fibre Optics and Cabling Section at Engineering Department. In this paper we analyze the procurement data for essential fibre cabling components during a five-year interval to extract the existing trends and anticipate future directions. The analysis predicts high contribution of LC connector and an increasing usage of multi-fibre connectors. It is foreseen that single-mode fibres become the main fibre type for mid and long-range installations while air blowing would be the major installation technique. Performance assessment of various connectors shows that the expanded beam ferrule is favored for emerging on-board optical interconnections thanks to its scalable density and stable return-loss.

Factor XIII deficiency in Iran: a comprehensive review of the literature.

PubMed

Dorgalaleh, Akbar; Naderi, Majid; Hosseini, Maryam Sadat; Alizadeh, Shaban; Hosseini, Soudabeh; Tabibian, Shadi; Eshghi, Peyman

2015-04-01

Factor XIII deficiency (FXIIID) is a rare bleeding disorder with an estimated prevalence of 1 in 2-million population worldwide. In Iran, a Middle Eastern country with a high rate of consanguineous marriages, there are approximately 473 patients afflicted with FXIIID. An approximately 12-fold higher prevalence of FXIIID is estimated in Iran in comparison with overall worldwide frequency. In this study, we have undertaken a comprehensive review on different aspects of FXIIID in the Iranian population. The distribution of this disease in different regions of Iran reveals that Sistan and Baluchestan Province has not only the highest number of patients with FXIIID in Iran but the highest global incidence of this condition. Among Iranian patients, umbilical cord bleeding, hematoma, and prolonged wound bleeding are the most frequent clinical manifestations. There are several disease causing mutations in Iranian patients with FXIIID, with Trp187Arg being the most common mutation in FXIIID in Iran. Traditionally, the management of FXIIID in Iran was only based on administration of fresh frozen plasma or cryoprecipitate, until 2009 when FXIII concentrate became available for patient management. Various studies have evaluated the efficacy and safety of prophylactic regimens in different situations with valuable findings. Although the focus of this study is on Iran, it offers considerable insight into FXIIID, which can be applied more extensively to improve the management and quality of life in all affected patients. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Cost Analysis In A Multi-Mission Operations Environment

NASA Technical Reports Server (NTRS)

Newhouse, M.; Felton, L.; Bornas, N.; Botts, D.; Roth, K.; Ijames, G.; Montgomery, P.

2014-01-01

Spacecraft control centers have evolved from dedicated, single-mission or single missiontype support to multi-mission, service-oriented support for operating a variety of mission types. At the same time, available money for projects is shrinking and competition for new missions is increasing. These factors drive the need for an accurate and flexible model to support estimating service costs for new or extended missions; the cost model in turn drives the need for an accurate and efficient approach to service cost analysis. The National Aeronautics and Space Administration (NASA) Huntsville Operations Support Center (HOSC) at Marshall Space Flight Center (MSFC) provides operations services to a variety of customers around the world. HOSC customers range from launch vehicle test flights; to International Space Station (ISS) payloads; to small, short duration missions; and has included long duration flagship missions. The HOSC recently completed a detailed analysis of service costs as part of the development of a complete service cost model. The cost analysis process required the team to address a number of issues. One of the primary issues involves the difficulty of reverse engineering individual mission costs in a highly efficient multimission environment, along with a related issue of the value of detailed metrics or data to the cost model versus the cost of obtaining accurate data. Another concern is the difficulty of balancing costs between missions of different types and size and extrapolating costs to different mission types. The cost analysis also had to address issues relating to providing shared, cloud-like services in a government environment, and then assigning an uncertainty or risk factor to cost estimates that are based on current technology, but will be executed using future technology. Finally the cost analysis needed to consider how to validate the resulting cost models taking into account the non-homogeneous nature of the available cost data and the

Multi-stage decoding for multi-level block modulation codes

NASA Technical Reports Server (NTRS)

Lin, Shu

1991-01-01

In this paper, we investigate various types of multi-stage decoding for multi-level block modulation codes, in which the decoding of a component code at each stage can be either soft-decision or hard-decision, maximum likelihood or bounded-distance. Error performance of codes is analyzed for a memoryless additive channel based on various types of multi-stage decoding, and upper bounds on the probability of an incorrect decoding are derived. Based on our study and computation results, we find that, if component codes of a multi-level modulation code and types of decoding at various stages are chosen properly, high spectral efficiency and large coding gain can be achieved with reduced decoding complexity. In particular, we find that the difference in performance between the suboptimum multi-stage soft-decision maximum likelihood decoding of a modulation code and the single-stage optimum decoding of the overall code is very small: only a fraction of dB loss in SNR at the probability of an incorrect decoding for a block of 10(exp -6). Multi-stage decoding of multi-level modulation codes really offers a way to achieve the best of three worlds, bandwidth efficiency, coding gain, and decoding complexity.

Dynamic Multi-Component Covalent Assembly for the Reversible Binding of Secondary Alcohols and Chirality Sensing

PubMed Central

You, Lei; Berman, Jeffrey S.; Anslyn, Eric V.

2011-01-01

Reversible covalent bonding is often employed for the creation of novel supramolecular structures, multi-component assemblies, and sensing ensembles. In spite of remarkable success of dynamic covalent systems, the reversible binding of a mono-alcohol with high strength is challenging. Here we show that a strategy of carbonyl activation and hemiaminal ether stabilization can be embodied in a four-component reversible assembly that creates a tetradentate ligand and incorporates secondary alcohols with exceptionally high affinity. Evidence is presented that the intermediate leading to binding and exchange of alcohols is an iminium ion. Further, to demonstrate the use of this assembly process we explored chirality sensing and enantiomeric excess determinations. An induced twist in the ligand by a chiral mono-ol results in large Cotton effects in the circular dichroism spectra indicative of the alcohol’s handedness. The strategy revealed in this study should prove broadly applicable for the incorporation of alcohols into supramolecular architecture construction. PMID:22109274

Effect of Substrate Wetting on the Morphology and Dynamics of Phase Separating Multi-Component Mixture

NASA Astrophysics Data System (ADS)

Goyal, Abheeti; Toschi, Federico; van der Schoot, Paul

2017-11-01

We study the morphological evolution and dynamics of phase separation of multi-component mixture in thin film constrained by a substrate. Specifically, we have explored the surface-directed spinodal decomposition of multicomponent mixture numerically by Free Energy Lattice Boltzmann (LB) simulations. The distinguishing feature of this model over the Shan-Chen (SC) model is that we have explicit and independent control over the free energy functional and EoS of the system. This vastly expands the ambit of physical systems that can be realistically simulated by LB simulations. We investigate the effect of composition, film thickness and substrate wetting on the phase morphology and the mechanism of growth in the vicinity of the substrate. The phase morphology and averaged size in the vicinity of the substrate fluctuate greatly due to the wetting of the substrate in both the parallel and perpendicular directions. Additionally, we also describe how the model presented here can be extended to include an arbitrary number of fluid components.

Rapid quantification of multi-components in alcohol precipitation liquid of Codonopsis Radix using near infrared spectroscopy (NIRS).

PubMed

Luo, Yu; Li, Wen-Long; Huang, Wen-Hua; Liu, Xue-Hua; Song, Yan-Gang; Qu, Hai-Bin

2017-05-01

A near infrared spectroscopy (NIRS) approach was established for quality control of the alcohol precipitation liquid in the manufacture of Codonopsis Radix. By applying NIRS with multivariate analysis, it was possible to build variation into the calibration sample set, and the Plackett-Burman design, Box-Behnken design, and a concentrating-diluting method were used to obtain the sample set covered with sufficient fluctuation of process parameters and extended concentration information. NIR data were calibrated to predict the four quality indicators using partial least squares regression (PLSR). In the four calibration models, the root mean squares errors of prediction (RMSEPs) were 1.22 μg/ml, 10.5 μg/ml, 1.43 μg/ml, and 0.433% for lobetyolin, total flavonoids, pigments, and total solid contents, respectively. The results indicated that multi-components quantification of the alcohol precipitation liquid of Codonopsis Radix could be achieved with an NIRS-based method, which offers a useful tool for real-time release testing (RTRT) of intermediates in the manufacture of Codonopsis Radix.

Self-gravito-acoustic shock structures in a self-gravitating, strongly coupled, multi-component, degenerate quantum plasma system

NASA Astrophysics Data System (ADS)

Mamun, A. A.

2017-10-01

The existence of self-gravito-acoustic (SGA) shock structures (SSs) associated with negative self-gravitational potential in a self-gravitating, strongly coupled, multi-component, degenerate quantum plasma (SGSCMCDQP) system is predicted for the first time. The modified Burgers (MB) equation, which is valid for both planar and non-planar (spherical) geometries, is derived analytically, and solved numerically. It is shown that the longitudinal viscous force acting on inertial plasma species of the plasma system is the source of dissipation and is responsible for the formation of these SGA SSs in the plasma system. The time evolution of these SGA SSs is also shown for different values (viz., 0.5, 1, and 2) of Γ, where Γ is the ratio of the nonlinear coefficient to the dissipative coefficient in the MB equation. The SGSCMCDQP model and the numerical analysis of the MB equation presented here are so general that they can be applied in any type of SGSCMCDQP systems like astrophysical compact objects having planar or non-planar (spherical) shape.

From Research to Practice: The Effect of Multi-Component Vocabulary Instruction on Increasing Vocabulary and Comprehension Performance in Social Studies

ERIC Educational Resources Information Center

Graham, Lori; Graham, Anna; West, Courtney

2015-01-01

This study was designed to demonstrate the effect of implementing multi-component vocabulary strategy instruction in fourth grade social studies. Curriculum was designed for a six-week period and was intended to actively engage students and reinforce retention of word meanings in isolation and in context. Teachers were randomly chosen for…

Pilot Integration of HIV Screening and Healthcare Settings with Multi- Component Social Network and Partner Testing for HIV Detection.

PubMed

Rentz, Michael F; Ruffner, Andrew H; Ancona, Rachel M; Hart, Kimberly W; Kues, John R; Barczak, Christopher M; Lindsell, Christopher J; Fichtenbaum, Carl J; Lyons, Michael S

2017-11-23

Healthcare settings screen broadly for HIV. Public health settings use social network and partner testing ("Transmission Network Targeting (TNT)") to select high-risk individuals based on their contacts. HIV screening and TNT systems are not integrated, and healthcare settings have not implemented TNT. The study aimed to evaluate pilot implementation of multi-component, multi-venue TNT in conjunction with HIV screening by a healthcare setting. Our urban, academic health center implemented a TNT program in collaboration with the local health department for five months during 2011. High-risk or HIV positive patients of the infectious diseases clinic and emergency department HIV screening program were recruited to access social and partner networks via compensated peer-referral, testing of companions present with them, and partner notification services. Contacts became the next-generation index cases in a snowball recruitment strategy. The pilot TNT program yielded 485 HIV tests for 482 individuals through eight generations of recruitment with five (1.0%; 95% CI = 0.4%, 2.3%) new diagnoses. Of these, 246 (51.0%; 95% CI = 46.6%, 55.5%) reported that they had not been tested for HIV within the last 12 months and 383 (79.5%; 95% CI = 75.7%, 82.9%) had not been tested by the existing ED screening program within the last five years. TNT complements population screening by more directly targeting high-risk individuals and by expanding the population receiving testing. Information from existing healthcare services could be used to seed TNT programs, or TNT could be implemented within healthcare settings. Research evaluating multi-component, multi-venue HIV detection is necessary to maximize complementary approaches while minimizing redundancy. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

SVM-Based Spectral Analysis for Heart Rate from Multi-Channel WPPG Sensor Signals.

PubMed

Xiong, Jiping; Cai, Lisang; Wang, Fei; He, Xiaowei

2017-03-03

Although wrist-type photoplethysmographic (hereafter referred to as WPPG) sensor signals can measure heart rate quite conveniently, the subjects' hand movements can cause strong motion artifacts, and then the motion artifacts will heavily contaminate WPPG signals. Hence, it is challenging for us to accurately estimate heart rate from WPPG signals during intense physical activities. The WWPG method has attracted more attention thanks to the popularity of wrist-worn wearable devices. In this paper, a mixed approach called Mix-SVM is proposed, it can use multi-channel WPPG sensor signals and simultaneous acceleration signals to measurement heart rate. Firstly, we combine the principle component analysis and adaptive filter to remove a part of the motion artifacts. Due to the strong relativity between motion artifacts and acceleration signals, the further denoising problem is regarded as a sparse signals reconstruction problem. Then, we use a spectrum subtraction method to eliminate motion artifacts effectively. Finally, the spectral peak corresponding to heart rate is sought by an SVM-based spectral analysis method. Through the public PPG database in the 2015 IEEE Signal Processing Cup, we acquire the experimental results, i.e., the average absolute error was 1.01 beat per minute, and the Pearson correlation was 0.9972. These results also confirm that the proposed Mix-SVM approach has potential for multi-channel WPPG-based heart rate estimation in the presence of intense physical exercise.

Multi-segmental movement patterns reflect juggling complexity and skill level.

PubMed

Zago, Matteo; Pacifici, Ilaria; Lovecchio, Nicola; Galli, Manuela; Federolf, Peter Andreas; Sforza, Chiarella

2017-08-01

The juggling action of six experts and six intermediates jugglers was recorded with a motion capture system and decomposed into its fundamental components through Principal Component Analysis. The aim was to quantify trends in movement dimensionality, multi-segmental patterns and rhythmicity as a function of proficiency level and task complexity. Dimensionality was quantified in terms of Residual Variance, while the Relative Amplitude was introduced to account for individual differences in movement components. We observed that: experience-related modifications in multi-segmental actions exist, such as the progressive reduction of error-correction movements, especially in complex task condition. The systematic identification of motor patterns sensitive to the acquisition of specific experience could accelerate the learning process. Copyright © 2017 Elsevier B.V. All rights reserved.

MultiElec: A MATLAB Based Application for MEA Data Analysis.

PubMed

Georgiadis, Vassilis; Stephanou, Anastasis; Townsend, Paul A; Jackson, Thomas R

2015-01-01

We present MultiElec, an open source MATLAB based application for data analysis of microelectrode array (MEA) recordings. MultiElec displays an extremely user-friendly graphic user interface (GUI) that allows the simultaneous display and analysis of voltage traces for 60 electrodes and includes functions for activation-time determination, the production of activation-time heat maps with activation time and isoline display. Furthermore, local conduction velocities are semi-automatically calculated along with their corresponding vector plots. MultiElec allows ad hoc signal suppression, enabling the user to easily and efficiently handle signal artefacts and for incomplete data sets to be analysed. Voltage traces and heat maps can be simply exported for figure production and presentation. In addition, our platform is able to produce 3D videos of signal progression over all 60 electrodes. Functions are controlled entirely by a single GUI with no need for command line input or any understanding of MATLAB code. MultiElec is open source under the terms of the GNU General Public License as published by the Free Software Foundation, version 3. Both the program and source code are available to download from http://www.cancer.manchester.ac.uk/MultiElec/.

Comparing Independent Component Analysis with Principle Component Analysis in Detecting Alterations of Porphyry Copper Deposit (case Study: Ardestan Area, Central Iran)

NASA Astrophysics Data System (ADS)

Mahmoudishadi, S.; Malian, A.; Hosseinali, F.

2017-09-01

The image processing techniques in transform domain are employed as analysis tools for enhancing the detection of mineral deposits. The process of decomposing the image into important components increases the probability of mineral extraction. In this study, the performance of Principal Component Analysis (PCA) and Independent Component Analysis (ICA) has been evaluated for the visible and near-infrared (VNIR) and Shortwave infrared (SWIR) subsystems of ASTER data. Ardestan is located in part of Central Iranian Volcanic Belt that hosts many well-known porphyry copper deposits. This research investigated the propylitic and argillic alteration zones and outer mineralogy zone in part of Ardestan region. The two mentioned approaches were applied to discriminate alteration zones from igneous bedrock using the major absorption of indicator minerals from alteration and mineralogy zones in spectral rang of ASTER bands. Specialized PC components (PC2, PC3 and PC6) were used to identify pyrite and argillic and propylitic zones that distinguish from igneous bedrock in RGB color composite image. Due to the eigenvalues, the components 2, 3 and 6 account for 4.26% ,0.9% and 0.09% of the total variance of the data for Ardestan scene, respectively. For the purpose of discriminating the alteration and mineralogy zones of porphyry copper deposit from bedrocks, those mentioned percentages of data in ICA independent components of IC2, IC3 and IC6 are more accurately separated than noisy bands of PCA. The results of ICA method conform to location of lithological units of Ardestan region, as well.

System diagnostics using qualitative analysis and component functional classification

DOEpatents

Reifman, J.; Wei, T.Y.C.

1993-11-23

A method for detecting and identifying faulty component candidates during off-normal operations of nuclear power plants involves the qualitative analysis of macroscopic imbalances in the conservation equations of mass, energy and momentum in thermal-hydraulic control volumes associated with one or more plant components and the functional classification of components. The qualitative analysis of mass and energy is performed through the associated equations of state, while imbalances in momentum are obtained by tracking mass flow rates which are incorporated into a first knowledge base. The plant components are functionally classified, according to their type, as sources or sinks of mass, energy and momentum, depending upon which of the three balance equations is most strongly affected by a faulty component which is incorporated into a second knowledge base. Information describing the connections among the components of the system forms a third knowledge base. The method is particularly adapted for use in a diagnostic expert system to detect and identify faulty component candidates in the presence of component failures and is not limited to use in a nuclear power plant, but may be used with virtually any type of thermal-hydraulic operating system. 5 figures.

System diagnostics using qualitative analysis and component functional classification

DOEpatents

Reifman, Jaques; Wei, Thomas Y. C.

1993-01-01

A method for detecting and identifying faulty component candidates during off-normal operations of nuclear power plants involves the qualitative analysis of macroscopic imbalances in the conservation equations of mass, energy and momentum in thermal-hydraulic control volumes associated with one or more plant components and the functional classification of components. The qualitative analysis of mass and energy is performed through the associated equations of state, while imbalances in momentum are obtained by tracking mass flow rates which are incorporated into a first knowledge base. The plant components are functionally classified, according to their type, as sources or sinks of mass, energy and momentum, depending upon which of the three balance equations is most strongly affected by a faulty component which is incorporated into a second knowledge base. Information describing the connections among the components of the system forms a third knowledge base. The method is particularly adapted for use in a diagnostic expert system to detect and identify faulty component candidates in the presence of component failures and is not limited to use in a nuclear power plant, but may be used with virtually any type of thermal-hydraulic operating system.

Integration and initial operation of the multi-component large ring laser structure ROMY

NASA Astrophysics Data System (ADS)

Schreiber, Karl Ulrich; Igel, Heiner; Wassermann, Joachim; Gebauer, André; Simonelli, Andrea; Bernauer, Felix; Donner, Stefanie; Hadziioannou, Celine; Egdorf, Sven; Wells, Jon-Paul

2017-04-01

Rotation sensing for the geosciences requires a high sensor resolution of the order of 10 pico- radians per second or even less. An optical Sagnac interferometer offers this sensitivity, provided that the scale factor can be made very large. We have designed and built a multi- component ring laser system, consisting of 4 individual large ring lasers, each covering an area of more than 62 square m. The rings are orientated in the shape of a tetrahedron, so that all 3 spatial directions are covered, allowing also for some redundancy. We report on the initial operation of the free running gyroscopes in their underground facility in order to establish a performance estimate for the ROMY ring laser structure. Preliminary results suggest that the quantum noise limit is lower than that of the G ring laser.

Failure analysis of aluminum alloy components

NASA Technical Reports Server (NTRS)

Johari, O.; Corvin, I.; Staschke, J.

1973-01-01

Analysis of six service failures in aluminum alloy components which failed in aerospace applications is reported. Identification of fracture surface features from fatigue and overload modes was straightforward, though the specimens were not always in a clean, smear-free condition most suitable for failure analysis. The presence of corrosion products and of chemically attacked or mechanically rubbed areas here hindered precise determination of the cause of crack initiation, which was then indirectly inferred from the scanning electron fractography results. In five failures the crack propagation was by fatigue, though in each case the fatigue crack initiated from a different cause. Some of these causes could be eliminated in future components by better process control. In one failure, the cause was determined to be impact during a crash; the features of impact fracture were distinguished from overload fractures by direct comparisons of the received specimens with laboratory-generated failures.

A unified framework for group independent component analysis for multi-subject fMRI data

PubMed Central

Guo, Ying; Pagnoni, Giuseppe

2008-01-01

Independent component analysis (ICA) is becoming increasingly popular for analyzing functional magnetic resonance imaging (fMRI) data. While ICA has been successfully applied to single-subject analysis, the extension of ICA to group inferences is not straightforward and remains an active topic of research. Current group ICA models, such as the GIFT (Calhoun et al., 2001) and tensor PICA (Beckmann and Smith, 2005), make different assumptions about the underlying structure of the group spatio-temporal processes and are thus estimated using algorithms tailored for the assumed structure, potentially leading to diverging results. To our knowledge, there are currently no methods for assessing the validity of different model structures in real fMRI data and selecting the most appropriate one among various choices. In this paper, we propose a unified framework for estimating and comparing group ICA models with varying spatio-temporal structures. We consider a class of group ICA models that can accommodate different group structures and include existing models, such as the GIFT and tensor PICA, as special cases. We propose a maximum likelihood (ML) approach with a modified Expectation-Maximization (EM) algorithm for the estimation of the proposed class of models. Likelihood ratio tests (LRT) are presented to compare between different group ICA models. The LRT can be used to perform model comparison and selection, to assess the goodness-of-fit of a model in a particular data set, and to test group differences in the fMRI signal time courses between subject subgroups. Simulation studies are conducted to evaluate the performance of the proposed method under varying structures of group spatio-temporal processes. We illustrate our group ICA method using data from an fMRI study that investigates changes in neural processing associated with the regular practice of Zen meditation. PMID:18650105

Multi-allelic haplotype model based on genetic partition for genomic prediction and variance component estimation using SNP markers.

PubMed

Da, Yang

2015-12-18

The amount of functional genomic information has been growing rapidly but remains largely unused in genomic selection. Genomic prediction and estimation using haplotypes in genome regions with functional elements such as all genes of the genome can be an approach to integrate functional and structural genomic information for genomic selection. Towards this goal, this article develops a new haplotype approach for genomic prediction and estimation. A multi-allelic haplotype model treating each haplotype as an 'allele' was developed for genomic prediction and estimation based on the partition of a multi-allelic genotypic value into additive and dominance values. Each additive value is expressed as a function of h - 1 additive effects, where h = number of alleles or haplotypes, and each dominance value is expressed as a function of h(h - 1)/2 dominance effects. For a sample of q individuals, the limit number of effects is 2q - 1 for additive effects and is the number of heterozygous genotypes for dominance effects. Additive values are factorized as a product between the additive model matrix and the h - 1 additive effects, and dominance values are factorized as a product between the dominance model matrix and the h(h - 1)/2 dominance effects. Genomic additive relationship matrix is defined as a function of the haplotype model matrix for additive effects, and genomic dominance relationship matrix is defined as a function of the haplotype model matrix for dominance effects. Based on these results, a mixed model implementation for genomic prediction and variance component estimation that jointly use haplotypes and single markers is established, including two computing strategies for genomic prediction and variance component estimation with identical results. The multi-allelic genetic partition fills a theoretical gap in genetic partition by providing general formulations for partitioning multi-allelic genotypic values and provides a haplotype

The effects of a multi-component dyadic intervention on the psychological distress of family caregivers providing care to people with dementia: a randomized controlled trial.

PubMed

Prick, Anna-Eva; de Lange, Jacomine; Twisk, Jos; Pot, Anne Margriet

2015-12-01

Earlier research showed that multi-component dyadic interventions - including a combination of intervention strategies and addressing both the person with dementia and caregiver - have a beneficial impact on the mental and physical health of people with dementia and their family caregivers. A randomized controlled trial (RCT) of a multi-component dyadic intervention, which is a translated and adapted version of an intervention that has been shown to be effective in the US by Teri et al. (2003), was performed. The effects on caregivers' mood (primary outcome), burden, general health, and salivary cortisol levels (secondary outcomes) were studied. Community-dwelling people with dementia and their family caregivers (N = 111 dyads) were randomly assigned. The experimental group received eight home visits during three months, combining physical exercise and support (psycho-education, communication skills training, and planning of pleasant activities). Both the physical exercise and support component were directed at both the person with dementia and the caregiver. The comparison group received monthly information bulletins and phone calls. There were three measurements at baseline (prior to the intervention), at three months, and at six months into the intervention. Data were analyzed with Generalized Estimating Equations (GEE) based on an intention-to-treat analysis of all available data. All analyses showed no benefits of the intervention over time on any of the outcomes. The negative results might be explained by the translation and adaptation of the intervention that has been shown to be effective in the US: the intervention was shortened and did not include cognitive reframing. However, only the health effects on people with dementia and not on caregivers were studied in the US. Several other factors might also have played a role, which are important for future studies to take into account. These are: the usual health care in the country or region of implementation

Multi-criteria multi-stakeholder decision analysis using a fuzzy-stochastic approach for hydrosystem management

NASA Astrophysics Data System (ADS)

Subagadis, Y. H.; Schütze, N.; Grundmann, J.

2014-09-01

The conventional methods used to solve multi-criteria multi-stakeholder problems are less strongly formulated, as they normally incorporate only homogeneous information at a time and suggest aggregating objectives of different decision-makers avoiding water-society interactions. In this contribution, Multi-Criteria Group Decision Analysis (MCGDA) using a fuzzy-stochastic approach has been proposed to rank a set of alternatives in water management decisions incorporating heterogeneous information under uncertainty. The decision making framework takes hydrologically, environmentally, and socio-economically motivated conflicting objectives into consideration. The criteria related to the performance of the physical system are optimized using multi-criteria simulation-based optimization, and fuzzy linguistic quantifiers have been used to evaluate subjective criteria and to assess stakeholders' degree of optimism. The proposed methodology is applied to find effective and robust intervention strategies for the management of a coastal hydrosystem affected by saltwater intrusion due to excessive groundwater extraction for irrigated agriculture and municipal use. Preliminary results show that the MCGDA based on a fuzzy-stochastic approach gives useful support for robust decision-making and is sensitive to the decision makers' degree of optimism.

Using Semantic Components to Represent Dynamics of an Interdisciplinary Healthcare Team in a Multi-Agent Decision Support System.

PubMed

Wilk, Szymon; Kezadri-Hamiaz, Mounira; Rosu, Daniela; Kuziemsky, Craig; Michalowski, Wojtek; Amyot, Daniel; Carrier, Marc

2016-02-01

In healthcare organizations, clinical workflows are executed by interdisciplinary healthcare teams (IHTs) that operate in ways that are difficult to manage. Responding to a need to support such teams, we designed and developed the MET4 multi-agent system that allows IHTs to manage patients according to presentation-specific clinical workflows. In this paper, we describe a significant extension of the MET4 system that allows for supporting rich team dynamics (understood as team formation, management and task-practitioner allocation), including selection and maintenance of the most responsible physician and more complex rules of selecting practitioners for the workflow tasks. In order to develop this extension, we introduced three semantic components: (1) a revised ontology describing concepts and relations pertinent to IHTs, workflows, and managed patients, (2) a set of behavioral rules describing the team dynamics, and (3) an instance base that stores facts corresponding to instances of concepts from the ontology and to relations between these instances. The semantic components are represented in first-order logic and they can be automatically processed using theorem proving and model finding techniques. We employ these techniques to find models that correspond to specific decisions controlling the dynamics of IHT. In the paper, we present the design of extended MET4 with a special focus on the new semantic components. We then describe its proof-of-concept implementation using the WADE multi-agent platform and the Z3 solver (theorem prover/model finder). We illustrate the main ideas discussed in the paper with a clinical scenario of an IHT managing a patient with chronic kidney disease.

Multi-block analysis coupled to laser-induced breakdown spectroscopy for sorting geological materials from caves.

PubMed

Ammari, Faten; Bassel, Léna; Ferrier, Catherine; Lacanette, Delphine; Chapoulie, Rémy; Bousquet, Bruno

2016-10-01

In this study, multi-block analysis was applied for the first time to LIBS spectra provided by a portable LIBS system (IVEA Solution, France) equipped with three compact Czerny-Turner spectrometers covering the spectral ranges 200-397nm, 398-571nm and 572-1000nm. 41 geological samples taken from a laboratory-cave situated in the "Vézère valley", an area rich with prehistoric sites and decorated caves listed as a UNESCO world heritage in the south west of France, were analyzed. They were composed of limestone and clay considered as underlying supports and of two types of alterations referred as moonmilk and coralloid. Common Components and Specific Weights Analysis (CCSWA) allowed sorting moonmilk and coralloid samples. The loadings revealed higher amounts of magnesium, silicon, aluminum and strontium in coralloids and the saliences emphasized that among the three spectrometers installed in the LIBS instrument used in this work; that covering the range 572-1000nm was less contributive. This new approach for processing LIBS data not only provides good results for sorting geological materials but also clearly reveals which spectral range contains most of the information. This specific advantage of multi-block analysis could lead for some applications to simplify the design and to reduce the size of LIBS instruments. Copyright © 2016 Elsevier B.V. All rights reserved.

Exploring the molecular mechanisms of Traditional Chinese Medicine components using gene expression signatures and connectivity map.

PubMed

Yoo, Minjae; Shin, Jimin; Kim, Hyunmin; Kim, Jihye; Kang, Jaewoo; Tan, Aik Choon

2018-04-04

Traditional Chinese Medicine (TCM) has been practiced over thousands of years in China and other Asian countries for treating various symptoms and diseases. However, the underlying molecular mechanisms of TCM are poorly understood, partly due to the "multi-component, multi-target" nature of TCM. To uncover the molecular mechanisms of TCM, we perform comprehensive gene expression analysis using connectivity map. We interrogated gene expression signatures obtained 102 TCM components using the next generation Connectivity Map (CMap) resource. We performed systematic data mining and analysis on the mechanism of action (MoA) of these TCM components based on the CMap results. We clustered the 102 TCM components into four groups based on their MoAs using next generation CMap resource. We performed gene set enrichment analysis on these components to provide additional supports for explaining these molecular mechanisms. We also provided literature evidence to validate the MoAs identified through this bioinformatics analysis. Finally, we developed the Traditional Chinese Medicine Drug Repurposing Hub (TCM Hub) - a connectivity map resource to facilitate the elucidation of TCM MoA for drug repurposing research. TCMHub is freely available in http://tanlab.ucdenver.edu/TCMHub. Molecular mechanisms of TCM could be uncovered by using gene expression signatures and connectivity map. Through this analysis, we identified many of the TCM components possess diverse MoAs, this may explain the applications of TCM in treating various symptoms and diseases. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Multi-viewpoint clustering analysis

NASA Technical Reports Server (NTRS)

Mehrotra, Mala; Wild, Chris

1993-01-01

In this paper, we address the feasibility of partitioning rule-based systems into a number of meaningful units to enhance the comprehensibility, maintainability and reliability of expert systems software. Preliminary results have shown that no single structuring principle or abstraction hierarchy is sufficient to understand complex knowledge bases. We therefore propose the Multi View Point - Clustering Analysis (MVP-CA) methodology to provide multiple views of the same expert system. We present the results of using this approach to partition a deployed knowledge-based system that navigates the Space Shuttle's entry. We also discuss the impact of this approach on verification and validation of knowledge-based systems.

Influence of disintegrants in different substrate physical form on dimensional recovery of multi-component tablet.

PubMed

Sarkar, Srimanta; Ooi, Shing Ming; Liew, Celine Valeria; Tan, Bing Xun; Heng, Paul Wan Sia

2014-11-20

This study investigated the influence of different disintegrants, present in different substrate physical forms, on dimensional recovery of multi-component tablets prepared at different compression pressures. Formulations containing model drug, metformin, (10%, w/w), different disintegrants (10%, w/w), and lactose (80%, w/w) were compressed directly or after granulation using polyvinyl pyrrolidone (1%, w/w) as binder, into tablets (350 mg, 10mm diameter) at 150, 200, and 250 N/mm(2) compression pressures. Tablets were characterized for immediate dimensional recovery (IR) after ejection from the die, latent dimensional recovery (LR) over 24 h, tensile strength, and disintegration. The IR was predominantly contributed by crystalline components whereas LR was brought about by polymeric materials. With increased compression pressure, higher degree of plastic deformation of the polymeric disintegrants resulted in tablet with lower LR and higher tensile strength. Presence of polyvinyl pyrrolidone in the granules contributed considerably to plastic deformation, and the tablets produced had lower LR, higher tensile strength, and longer disintegration time. This study indicated that use of granules as the feed substrate physical form and a prudent selection of components may enable the coating of resultant tablets immediately after compression without the risk of coat damage due to LR. Copyright © 2014 Elsevier B.V. All rights reserved.

The Use of Multi-Component Statistical Techniques in Understanding Subduction Zone Arc Granitic Geochemical Data Sets

NASA Astrophysics Data System (ADS)

Pompe, L.; Clausen, B. L.; Morton, D. M.

2015-12-01

Multi-component statistical techniques and GIS visualization are emerging trends in understanding large data sets. Our research applies these techniques to a large igneous geochemical data set from southern California to better understand magmatic and plate tectonic processes. A set of 480 granitic samples collected by Baird from this area were analyzed for 39 geochemical elements. Of these samples, 287 are from the Peninsular Ranges Batholith (PRB) and 164 from part of the Transverse Ranges (TR). Principal component analysis (PCA) summarized the 39 variables into 3 principal components (PC) by matrix multiplication and for the PRB are interpreted as follows: PC1 with about 30% of the variation included mainly compatible elements and SiO2 and indicates extent of differentation; PC2 with about 20% of the variation included HFS elements and may indicate crustal contamination as usually identified by Sri; PC3 with about 20% of the variation included mainly HRE elements and may indicate magma source depth as often diplayed using REE spider diagrams and possibly Sr/Y. Several elements did not fit well in any of the three components: Cr, Ni, U, and Na2O.For the PRB, the PC1 correlation with SiO2 was r=-0.85, the PC2 correlation with Sri was r=0.80, and the PC3 correlation with Gd/Yb was r=-0.76 and with Sr/Y was r=-0.66 . Extending this method to the TR, correlations were r=-0.85, -0.21, -0.06, and -0.64, respectively. A similar extent of correlation for both areas was visually evident using GIS interpolation.PC1 seems to do well at indicating differentiation index for both the PRB and TR and correlates very well with SiO2, Al2O3, MgO, FeO*, CaO, K2O, Sc, V, and Co, but poorly with Na2O and Cr. If the crustal component is represented by Sri, PC2 correlates well and less expesively with this indicator in the PRB, but not in the TR. Source depth has been related to the slope on REE spidergrams, and PC3 based on only the HREE and using the Sr/Y ratios gives a reasonable

Design component method for sensitivity analysis of built-up structures

NASA Technical Reports Server (NTRS)

Choi, Kyung K.; Seong, Hwai G.

1986-01-01

A 'design component method' that provides a unified and systematic organization of design sensitivity analysis for built-up structures is developed and implemented. Both conventional design variables, such as thickness and cross-sectional area, and shape design variables of components of built-up structures are considered. It is shown that design of components of built-up structures can be characterized and system design sensitivity expressions obtained by simply adding contributions from each component. The method leads to a systematic organization of computations for design sensitivity analysis that is similar to the way in which computations are organized within a finite element code.

The Component Packaging Problem: A Vehicle for the Development of Multidisciplinary Design and Analysis Methodologies

NASA Technical Reports Server (NTRS)

Fadel, Georges; Bridgewood, Michael; Figliola, Richard; Greenstein, Joel; Kostreva, Michael; Nowaczyk, Ronald; Stevenson, Steve

1999-01-01

This report summarizes academic research which has resulted in an increased appreciation for multidisciplinary efforts among our students, colleagues and administrators. It has also generated a number of research ideas that emerged from the interaction between disciplines. Overall, 17 undergraduate students and 16 graduate students benefited directly from the NASA grant: an additional 11 graduate students were impacted and participated without financial support from NASA. The work resulted in 16 theses (with 7 to be completed in the near future), 67 papers or reports mostly published in 8 journals and/or presented at various conferences (a total of 83 papers, presentations and reports published based on NASA inspired or supported work). In addition, the faculty and students presented related work at many meetings, and continuing work has been proposed to NSF, the Army, Industry and other state and federal institutions to continue efforts in the direction of multidisciplinary and recently multi-objective design and analysis. The specific problem addressed is component packing which was solved as a multi-objective problem using iterative genetic algorithms and decomposition. Further testing and refinement of the methodology developed is presently under investigation. Teaming issues research and classes resulted in the publication of a web site, (http://design.eng.clemson.edu/psych4991) which provides pointers and techniques to interested parties. Specific advantages of using iterative genetic algorithms, hurdles faced and resolved, and institutional difficulties associated with multi-discipline teaming are described in some detail.

Structural reliability analysis of laminated CMC components

NASA Technical Reports Server (NTRS)

Duffy, Stephen F.; Palko, Joseph L.; Gyekenyesi, John P.

1991-01-01

For laminated ceramic matrix composite (CMC) materials to realize their full potential in aerospace applications, design methods and protocols are a necessity. The time independent failure response of these materials is focussed on and a reliability analysis is presented associated with the initiation of matrix cracking. A public domain computer algorithm is highlighted that was coupled with the laminate analysis of a finite element code and which serves as a design aid to analyze structural components made from laminated CMC materials. Issues relevant to the effect of the size of the component are discussed, and a parameter estimation procedure is presented. The estimation procedure allows three parameters to be calculated from a failure population that has an underlying Weibull distribution.

Multi-scale statistical analysis of coronal solar activity

DOE PAGES

Gamborino, Diana; del-Castillo-Negrete, Diego; Martinell, Julio J.

2016-07-08

Multi-filter images from the solar corona are used to obtain temperature maps that are analyzed using techniques based on proper orthogonal decomposition (POD) in order to extract dynamical and structural information at various scales. Exploring active regions before and after a solar flare and comparing them with quiet regions, we show that the multi-scale behavior presents distinct statistical properties for each case that can be used to characterize the level of activity in a region. Information about the nature of heat transport is also to be extracted from the analysis.

Automated multivariate analysis of multi-sensor data submitted online: Real-time environmental monitoring.

PubMed

Eide, Ingvar; Westad, Frank

2018-01-01

A pilot study demonstrating real-time environmental monitoring with automated multivariate analysis of multi-sensor data submitted online has been performed at the cabled LoVe Ocean Observatory located at 258 m depth 20 km off the coast of Lofoten-Vesterålen, Norway. The major purpose was efficient monitoring of many variables simultaneously and early detection of changes and time-trends in the overall response pattern before changes were evident in individual variables. The pilot study was performed with 12 sensors from May 16 to August 31, 2015. The sensors provided data for chlorophyll, turbidity, conductivity, temperature (three sensors), salinity (calculated from temperature and conductivity), biomass at three different depth intervals (5-50, 50-120, 120-250 m), and current speed measured in two directions (east and north) using two sensors covering different depths with overlap. A total of 88 variables were monitored, 78 from the two current speed sensors. The time-resolution varied, thus the data had to be aligned to a common time resolution. After alignment, the data were interpreted using principal component analysis (PCA). Initially, a calibration model was established using data from May 16 to July 31. The data on current speed from two sensors were subject to two separate PCA models and the score vectors from these two models were combined with the other 10 variables in a multi-block PCA model. The observations from August were projected on the calibration model consecutively one at a time and the result was visualized in a score plot. Automated PCA of multi-sensor data submitted online is illustrated with an attached time-lapse video covering the relative short time period used in the pilot study. Methods for statistical validation, and warning and alarm limits are described. Redundant sensors enable sensor diagnostics and quality assurance. In a future perspective, the concept may be used in integrated environmental monitoring.

Two-Step Multi-Physics Analysis of an Annular Linear Induction Pump for Fission Power Systems

NASA Technical Reports Server (NTRS)

Geng, Steven M.; Reid, Terry V.

2016-01-01

One of the key technologies associated with fission power systems (FPS) is the annular linear induction pump (ALIP). ALIPs are used to circulate liquid-metal fluid for transporting thermal energy from the nuclear reactor to the power conversion device. ALIPs designed and built to date for FPS project applications have not performed up to expectations. A unique, two-step approach was taken toward the multi-physics examination of an ALIP using ANSYS Maxwell 3D and Fluent. This multi-physics approach was developed so that engineers could investigate design variations that might improve pump performance. Of interest was to determine if simple geometric modifications could be made to the ALIP components with the goal of increasing the Lorentz forces acting on the liquid-metal fluid, which in turn would increase pumping capacity. The multi-physics model first calculates the Lorentz forces acting on the liquid metal fluid in the ALIP annulus. These forces are then used in a computational fluid dynamics simulation as (a) internal boundary conditions and (b) source functions in the momentum equations within the Navier-Stokes equations. The end result of the two-step analysis is a predicted pump pressure rise that can be compared with experimental data.

Integrative analysis of multi-omics data for identifying multi-markers for diagnosing pancreatic cancer

PubMed Central

2015-01-01

Background microRNA (miRNA) expression plays an influential role in cancer classification and malignancy, and miRNAs are feasible as alternative diagnostic markers for pancreatic cancer, a highly aggressive neoplasm with silent early symptoms, high metastatic potential, and resistance to conventional therapies. Methods In this study, we evaluated the benefits of multi-omics data analysis by integrating miRNA and mRNA expression data in pancreatic cancer. Using support vector machine (SVM) modelling and leave-one-out cross validation (LOOCV), we evaluated the diagnostic performance of single- or multi-markers based on miRNA and mRNA expression profiles from 104 PDAC tissues and 17 benign pancreatic tissues. For selecting even more reliable and robust markers, we performed validation by independent datasets from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) data depositories. For validation, miRNA activity was estimated by miRNA-target gene interaction and mRNA expression datasets in pancreatic cancer. Results Using a comprehensive identification approach, we successfully identified 705 multi-markers having powerful diagnostic performance for PDAC. In addition, these marker candidates annotated with cancer pathways using gene ontology analysis. Conclusions Our prediction models have strong potential for the diagnosis of pancreatic cancer. PMID:26328610

EXTRACTING PRINCIPLE COMPONENTS FOR DISCRIMINANT ANALYSIS OF FMRI IMAGES

PubMed Central

Liu, Jingyu; Xu, Lai; Caprihan, Arvind; Calhoun, Vince D.

2009-01-01

This paper presents an approach for selecting optimal components for discriminant analysis. Such an approach is useful when further detailed analyses for discrimination or characterization requires dimensionality reduction. Our approach can accommodate a categorical variable such as diagnosis (e.g. schizophrenic patient or healthy control), or a continuous variable like severity of the disorder. This information is utilized as a reference for measuring a component’s discriminant power after principle component decomposition. After sorting each component according to its discriminant power, we extract the best components for discriminant analysis. An application of our reference selection approach is shown using a functional magnetic resonance imaging data set in which the sample size is much less than the dimensionality. The results show that the reference selection approach provides an improved discriminant component set as compared to other approaches. Our approach is general and provides a solid foundation for further discrimination and classification studies. PMID:20582334

Strategies for the structural analysis of multi-protein complexes: lessons from the 3D-Repertoire project.

PubMed

Collinet, B; Friberg, A; Brooks, M A; van den Elzen, T; Henriot, V; Dziembowski, A; Graille, M; Durand, D; Leulliot, N; Saint André, C; Lazar, N; Sattler, M; Séraphin, B; van Tilbeurgh, H

2011-08-01

Structural studies of multi-protein complexes, whether by X-ray diffraction, scattering, NMR spectroscopy or electron microscopy, require stringent quality control of the component samples. The inability to produce 'keystone' subunits in a soluble and correctly folded form is a serious impediment to the reconstitution of the complexes. Co-expression of the components offers a valuable alternative to the expression of single proteins as a route to obtain sufficient amounts of the sample of interest. Even in cases where milligram-scale quantities of purified complex of interest become available, there is still no guarantee that good quality crystals can be obtained. At this step, protein engineering of one or more components of the complex is frequently required to improve solubility, yield or the ability to crystallize the sample. Subsequent characterization of these constructs may be performed by solution techniques such as Small Angle X-ray Scattering and Nuclear Magnetic Resonance to identify 'well behaved' complexes. Herein, we recount our experiences gained at protein production and complex assembly during the European 3D Repertoire project (3DR). The goal of this consortium was to obtain structural information on multi-protein complexes from yeast by combining crystallography, electron microscopy, NMR and in silico modeling methods. We present here representative set case studies of complexes that were produced and analyzed within the 3DR project. Our experience provides useful insight into strategies that are more generally applicable for structural analysis of protein complexes. Copyright © 2011 Elsevier Inc. All rights reserved.

Modeling complex and multi-component food systems in molecular dynamics simulations on the example of chocolate conching.

PubMed

Greiner, Maximilian; Sonnleitner, Bettina; Mailänder, Markus; Briesen, Heiko

2014-02-01

Additional benefits of foods are an increasing factor in the consumer's purchase. To produce foods with the properties the consumer demands, understanding the micro- and nanostructure is becoming more important in food research today. We present molecular dynamics (MD) simulations as a tool to study complex and multi-component food systems on the example of chocolate conching. The process of conching is chosen because of the interesting challenges it provides: the components (fats, emulsifiers and carbohydrates) contain diverse functional groups, are naturally fluctuating in their chemical composition, and have a high number of internal degrees of freedom. Further, slow diffusion in the non-aqueous medium is expected. All of these challenges are typical to food systems in general. Simulation results show the suitability of present force fields to correctly model the liquid and crystal density of cocoa butter and sucrose, respectively. Amphiphilic properties of emulsifiers are observed by micelle formation in water. For non-aqueous media, pulling simulations reveal high energy barriers for motion in the viscous cocoa butter. The work for detachment of an emulsifier from the sucrose crystal is calculated and matched with detachment of the head and tail groups separately. Hydrogen bonding is shown to be the dominant interaction between the emulsifier and the crystal surface. Thus, MD simulations are suited to model the interaction between the emulsifier and sugar crystal interface in non-aqueous media, revealing detailed information about the structuring and interactions on a molecular level. With interaction parameters being available for a wide variety of chemical groups, MD simulations are a valuable tool to understand complex and multi-component food systems in general. MD simulations provide a substantial benefit to researchers to verify their hypothesis in dynamic simulations with an atomistic resolution. Rapid rise of computational resources successively

Dynamics of lumps and dark-dark solitons in the multi-component long-wave-short-wave resonance interaction system.

PubMed

Rao, Jiguang; Porsezian, Kuppuswamy; He, Jingsong; Kanna, Thambithurai

2018-01-01

General semi-rational solutions of an integrable multi-component (2+1)-dimensional long-wave-short-wave resonance interaction system comprising multiple short waves and a single long wave are obtained by employing the bilinear method. These solutions describe the interactions between various types of solutions, including line rogue waves, lumps, breathers and dark solitons. We only focus on the dynamical behaviours of the interactions between lumps and dark solitons in this paper. Our detailed study reveals two different types of excitation phenomena: fusion and fission. It is shown that the fundamental (simplest) semi-rational solutions can exhibit fission of a dark soliton into a lump and a dark soliton or fusion of one lump and one dark soliton into a dark soliton. The non-fundamental semi-rational solutions are further classified into three subclasses: higher-order, multi- and mixed-type semi-rational solutions. The higher-order semi-rational solutions show the process of annihilation (production) of two or more lumps into (from) one dark soliton. The multi-semi-rational solutions describe N ( N ≥2) lumps annihilating into or producing from N -dark solitons. The mixed-type semi-rational solutions are a hybrid of higher-order semi-rational solutions and multi-semi-rational solutions. For the mixed-type semi-rational solutions, we demonstrate an interesting dynamical behaviour that is characterized by partial suppression or creation of lumps from the dark solitons.

Dynamics of lumps and dark-dark solitons in the multi-component long-wave-short-wave resonance interaction system

NASA Astrophysics Data System (ADS)

Rao, Jiguang; Porsezian, Kuppuswamy; He, Jingsong; Kanna, Thambithurai

2018-01-01

General semi-rational solutions of an integrable multi-component (2+1)-dimensional long-wave-short-wave resonance interaction system comprising multiple short waves and a single long wave are obtained by employing the bilinear method. These solutions describe the interactions between various types of solutions, including line rogue waves, lumps, breathers and dark solitons. We only focus on the dynamical behaviours of the interactions between lumps and dark solitons in this paper. Our detailed study reveals two different types of excitation phenomena: fusion and fission. It is shown that the fundamental (simplest) semi-rational solutions can exhibit fission of a dark soliton into a lump and a dark soliton or fusion of one lump and one dark soliton into a dark soliton. The non-fundamental semi-rational solutions are further classified into three subclasses: higher-order, multi- and mixed-type semi-rational solutions. The higher-order semi-rational solutions show the process of annihilation (production) of two or more lumps into (from) one dark soliton. The multi-semi-rational solutions describe N(N≥2) lumps annihilating into or producing from N-dark solitons. The mixed-type semi-rational solutions are a hybrid of higher-order semi-rational solutions and multi-semi-rational solutions. For the mixed-type semi-rational solutions, we demonstrate an interesting dynamical behaviour that is characterized by partial suppression or creation of lumps from the dark solitons.

Engine structures analysis software: Component Specific Modeling (COSMO)

NASA Astrophysics Data System (ADS)

McKnight, R. L.; Maffeo, R. J.; Schwartz, S.

1994-08-01

A component specific modeling software program has been developed for propulsion systems. This expert program is capable of formulating the component geometry as finite element meshes for structural analysis which, in the future, can be spun off as NURB geometry for manufacturing. COSMO currently has geometry recipes for combustors, turbine blades, vanes, and disks. Component geometry recipes for nozzles, inlets, frames, shafts, and ducts are being added. COSMO uses component recipes that work through neutral files with the Technology Benefit Estimator (T/BEST) program which provides the necessary base parameters and loadings. This report contains the users manual for combustors, turbine blades, vanes, and disks.

Engine Structures Analysis Software: Component Specific Modeling (COSMO)

NASA Technical Reports Server (NTRS)

Mcknight, R. L.; Maffeo, R. J.; Schwartz, S.

1994-01-01

A component specific modeling software program has been developed for propulsion systems. This expert program is capable of formulating the component geometry as finite element meshes for structural analysis which, in the future, can be spun off as NURB geometry for manufacturing. COSMO currently has geometry recipes for combustors, turbine blades, vanes, and disks. Component geometry recipes for nozzles, inlets, frames, shafts, and ducts are being added. COSMO uses component recipes that work through neutral files with the Technology Benefit Estimator (T/BEST) program which provides the necessary base parameters and loadings. This report contains the users manual for combustors, turbine blades, vanes, and disks.

Strategies for Multi-Modal Analysis

NASA Astrophysics Data System (ADS)

Hexemer, Alexander; Wang, Cheng; Pandolfi, Ronald; Kumar, Dinesh; Venkatakrishnan, Singanallur; Sethian, James; Camera Team

This section on soft materials will be dedicated to discuss the extraction of the chemical distribution and spatial arrangement of constituent elements and functional groups at multiple length scales and, thus, the examination of collective dynamics, transport, and electronic ordering phenomena. Traditional measures of structure in soft materials have relied heavily on scattering and imaging based techniques due to their capacity to measure nanoscale dimensions and their capacity to monitor structure under conditions of dynamic stress loading. Special attentions are planned to focus on the application of resonant x-ray scattering, contrast-varied neutron scattering, analytical transmission electron microscopy, and their combinations. This session aims to bring experts in both scattering and electron microscope fields to discuss recent advances in selectively characterizing structural architectures of complex soft materials, which have often multi-components with a wide range of length scales and multiple functionalities, and thus hopes to foster novel ideas to decipher a higher level of structural complexity in soft materials in future. CAMERA, Early Career Award.

Statistical Projections for Multi-resolution, Multi-dimensional Visual Data Exploration and Analysis

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

Hoa T. Nguyen; Stone, Daithi; E. Wes Bethel

2016-01-01

An ongoing challenge in visual exploration and analysis of large, multi-dimensional datasets is how to present useful, concise information to a user for some specific visualization tasks. Typical approaches to this problem have proposed either reduced-resolution versions of data, or projections of data, or both. These approaches still have some limitations such as consuming high computation or suffering from errors. In this work, we explore the use of a statistical metric as the basis for both projections and reduced-resolution versions of data, with a particular focus on preserving one key trait in data, namely variation. We use two different casemore » studies to explore this idea, one that uses a synthetic dataset, and another that uses a large ensemble collection produced by an atmospheric modeling code to study long-term changes in global precipitation. The primary findings of our work are that in terms of preserving the variation signal inherent in data, that using a statistical measure more faithfully preserves this key characteristic across both multi-dimensional projections and multi-resolution representations than a methodology based upon averaging.« less

Multi-stage decoding for multi-level block modulation codes

NASA Technical Reports Server (NTRS)

Lin, Shu; Kasami, Tadao

1991-01-01

Various types of multistage decoding for multilevel block modulation codes, in which the decoding of a component code at each stage can be either soft decision or hard decision, maximum likelihood or bounded distance are discussed. Error performance for codes is analyzed for a memoryless additive channel based on various types of multi-stage decoding, and upper bounds on the probability of an incorrect decoding are derived. It was found that, if component codes of a multi-level modulation code and types of decoding at various stages are chosen properly, high spectral efficiency and large coding gain can be achieved with reduced decoding complexity. It was found that the difference in performance between the suboptimum multi-stage soft decision maximum likelihood decoding of a modulation code and the single stage optimum decoding of the overall code is very small, only a fraction of dB loss in SNR at the probability of an incorrect decoding for a block of 10(exp -6). Multi-stage decoding of multi-level modulation codes really offers a way to achieve the best of three worlds, bandwidth efficiency, coding gain, and decoding complexity.

Scaling Bulk Data Analysis with Mapreduce

DTIC Science & Technology

2017-09-01

Submitted in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE IN COMPUTER SCIENCE from the NAVAL POSTGRADUATE SCHOOL September...2017 Approved by: Michael McCarrin Thesis Co-Advisor Marcus S. Stefanou Thesis Co-Advisor Peter J. Denning Chair, Department of Computer Science iii...98 xiii THIS PAGE INTENTIONALLY LEFT BLANK xiv List of Acronyms and Abbreviations CART Computer Analysis and Response Team DELV Distributed Environment

Eccentric versus traditional resistance exercise for older adult fallers in the community: a randomized trial within a multi-component fall reduction program.

PubMed

LaStayo, Paul; Marcus, Robin; Dibble, Leland; Wong, Bob; Pepper, Ginette

2017-07-17

Addressing muscle deficits within a multi-component exercise fall reduction program is a priority, especially for the highest risk older adults, i.e., those who have fallen previously. Eccentric resistance exercise with its high-force producing potential, at a low energetic cost, may be ideally-suited to address muscle impairments in this population. The purpose of this study was to compare the effects of resistance exercise via negative, eccentrically-induced, work (RENEW) versus traditional (TRAD) resistance exercise on mobility, balance confidence, muscle power and cross sectional area, as well as the number of days high fall risk older adults survived without a fall event over a 1 year period. Randomized, two group, four time point (over 1 year) clinical trial testing RENEW versus TRAD as part of a 3 month multi-component exercise fall reduction program (MCEFRP). Primary outcomes of mobility, balance confidence, muscle power output and cross sectional area were analyzed using mixed effects modeling. The secondary outcomes of days to fall and days to near-fall were analyzed using survival analysis. The MCEFRP did have an effect on fall risk factors considered reversible with exercise interventions though there was no differential effect of RENEW versus TRAD (p = 0.896) on mobility, balance confidence, muscle power and cross sectional area. There were also no group differences in the number of days survived without a fall (p = 0.565) or near-fall (p = 0.678). Despite 100% of participants having at least one fall in the year prior to the MCEFRP, however, after 3 months of exercise and 9 months of follow-up <50% had experienced a fall or near fall. There were no differential effects of RENEW or TRAD as components of a MCEFRP on the primary or secondary outcomes. The two modes of resistance exercise had identical effects on fall risk and fall-free survival. NCT01080196 ; March 2, 2010 (retrospectively registered).

Multi-Omics Factor Analysis-a framework for unsupervised integration of multi-omics data sets.

PubMed

Argelaguet, Ricard; Velten, Britta; Arnol, Damien; Dietrich, Sascha; Zenz, Thorsten; Marioni, John C; Buettner, Florian; Huber, Wolfgang; Stegle, Oliver

2018-06-20

Multi-omics studies promise the improved characterization of biological processes across molecular layers. However, methods for the unsupervised integration of the resulting heterogeneous data sets are lacking. We present Multi-Omics Factor Analysis (MOFA), a computational method for discovering the principal sources of variation in multi-omics data sets. MOFA infers a set of (hidden) factors that capture biological and technical sources of variability. It disentangles axes of heterogeneity that are shared across multiple modalities and those specific to individual data modalities. The learnt factors enable a variety of downstream analyses, including identification of sample subgroups, data imputation and the detection of outlier samples. We applied MOFA to a cohort of 200 patient samples of chronic lymphocytic leukaemia, profiled for somatic mutations, RNA expression, DNA methylation and ex vivo drug responses. MOFA identified major dimensions of disease heterogeneity, including immunoglobulin heavy-chain variable region status, trisomy of chromosome 12 and previously underappreciated drivers, such as response to oxidative stress. In a second application, we used MOFA to analyse single-cell multi-omics data, identifying coordinated transcriptional and epigenetic changes along cell differentiation. © 2018 The Authors. Published under the terms of the CC BY 4.0 license.

Phenomenology of mixed states: a principal component analysis study.

PubMed

Bertschy, G; Gervasoni, N; Favre, S; Liberek, C; Ragama-Pardos, E; Aubry, J-M; Gex-Fabry, M; Dayer, A

2007-12-01

To contribute to the definition of external and internal limits of mixed states and study the place of dysphoric symptoms in the psychopathology of mixed states. One hundred and sixty-five inpatients with major mood episodes were diagnosed as presenting with either pure depression, mixed depression (depression plus at least three manic symptoms), full mixed state (full depression and full mania), mixed mania (mania plus at least three depressive symptoms) or pure mania, using an adapted version of the Mini International Neuropsychiatric Interview (DSM-IV version). They were evaluated using a 33-item inventory of depressive, manic and mixed affective signs and symptoms. Principal component analysis without rotation yielded three components that together explained 43.6% of the variance. The first component (24.3% of the variance) contrasted typical depressive symptoms with typical euphoric, manic symptoms. The second component, labeled 'dysphoria', (13.8%) had strong positive loadings for irritability, distressing sensitivity to light and noise, impulsivity and inner tension. The third component (5.5%) included symptoms of insomnia. Median scores for the first component significantly decreased from the pure depression group to the pure mania group. For the dysphoria component, scores were highest among patients with full mixed states and decreased towards both patients with pure depression and those with pure mania. Principal component analysis revealed that dysphoria represents an important dimension of mixed states.

Furnace Cyclic Behavior of Plasma-Sprayed Zirconia-Yttria and Multi-Component Rare Earth Oxide Doped Thermal Barrier Coatings

NASA Technical Reports Server (NTRS)

Zhu, Dongming; Nesbitt, James A.; McCue, Terry R.; Barrett, Charles A.; Miller, Robert A.

2002-01-01

Ceramic thermal barrier coatings will play an increasingly important role in advanced gas turbine engines because of their ability to enable further increases in engine temperatures. However, the coating performance and durability become a major concern under the increasingly harsh thermal cycling conditions. Advanced zirconia- and hafnia-based cluster oxide thermal barrier coatings with lower thermal conductivity and improved thermal stability are being developed using a high-heat-flux laser-rig based test approach. Although the new composition coatings were not yet optimized for cyclic durability, an initial durability screening of numerous candidate coating materials was carried out using conventional furnace cyclic tests. In this paper, furnace thermal cyclic behavior of the advanced plasma-sprayed zirconia-yttria-based thermal barrier coatings that were co-doped with multi-component rare earth oxides was investigated at 1163 C using 45 min hot cycles. The ceramic coating failure mechanisms were studied by using scanning electron microscopy combined with X-ray diffraction phase analysis after the furnace tests. The coating cyclic lifetime will be discussed in relation to coating phase structures, total dopant concentrations, and other properties.

Lattice thermal conductivity of multi-component alloys

DOE PAGES

Caro, Magdalena; Béland, Laurent K.; Samolyuk, German D.; ...

2015-06-12

High entropy alloys (HEA) have unique properties including the potential to be radiation tolerant. These materials with extreme disorder could resist damage because disorder, stabilized by entropy, is the equilibrium thermodynamic state. Disorder also reduces electron and phonon conductivity keeping the damage energy longer at the deposition locations, eventually favoring defect recombination. In the short time-scales related to thermal spikes induced by collision cascades, phonons become the relevant energy carrier. In this paper, we perform a systematic study of phonon thermal conductivity in multiple component solid solutions represented by Lennard-Jones (LJ) potentials. We explore the conditions that minimize phonon meanmore » free path via extreme alloy complexity, by varying the composition and the elements (differing in mass, atomic radii, and cohesive energy). We show that alloy complexity can be tailored to modify the scattering mechanisms that control energy transport in the phonon subsystem. Finally, our analysis provides a qualitative guidance for the selection criteria used in the design of HEA alloys with low phonon thermal conductivity.« less

Local variance for multi-scale analysis in geomorphometry.

PubMed

Drăguţ, Lucian; Eisank, Clemens; Strasser, Thomas

2011-07-15

Increasing availability of high resolution Digital Elevation Models (DEMs) is leading to a paradigm shift regarding scale issues in geomorphometry, prompting new solutions to cope with multi-scale analysis and detection of characteristic scales. We tested the suitability of the local variance (LV) method, originally developed for image analysis, for multi-scale analysis in geomorphometry. The method consists of: 1) up-scaling land-surface parameters derived from a DEM; 2) calculating LV as the average standard deviation (SD) within a 3 × 3 moving window for each scale level; 3) calculating the rate of change of LV (ROC-LV) from one level to another, and 4) plotting values so obtained against scale levels. We interpreted peaks in the ROC-LV graphs as markers of scale levels where cells or segments match types of pattern elements characterized by (relatively) equal degrees of homogeneity. The proposed method has been applied to LiDAR DEMs in two test areas different in terms of roughness: low relief and mountainous, respectively. For each test area, scale levels for slope gradient, plan, and profile curvatures were produced at constant increments with either resampling (cell-based) or image segmentation (object-based). Visual assessment revealed homogeneous areas that convincingly associate into patterns of land-surface parameters well differentiated across scales. We found that the LV method performed better on scale levels generated through segmentation as compared to up-scaling through resampling. The results indicate that coupling multi-scale pattern analysis with delineation of morphometric primitives is possible. This approach could be further used for developing hierarchical classifications of landform elements.

Local variance for multi-scale analysis in geomorphometry

PubMed Central

Drăguţ, Lucian; Eisank, Clemens; Strasser, Thomas

2011-01-01

Increasing availability of high resolution Digital Elevation Models (DEMs) is leading to a paradigm shift regarding scale issues in geomorphometry, prompting new solutions to cope with multi-scale analysis and detection of characteristic scales. We tested the suitability of the local variance (LV) method, originally developed for image analysis, for multi-scale analysis in geomorphometry. The method consists of: 1) up-scaling land-surface parameters derived from a DEM; 2) calculating LV as the average standard deviation (SD) within a 3 × 3 moving window for each scale level; 3) calculating the rate of change of LV (ROC-LV) from one level to another, and 4) plotting values so obtained against scale levels. We interpreted peaks in the ROC-LV graphs as markers of scale levels where cells or segments match types of pattern elements characterized by (relatively) equal degrees of homogeneity. The proposed method has been applied to LiDAR DEMs in two test areas different in terms of roughness: low relief and mountainous, respectively. For each test area, scale levels for slope gradient, plan, and profile curvatures were produced at constant increments with either resampling (cell-based) or image segmentation (object-based). Visual assessment revealed homogeneous areas that convincingly associate into patterns of land-surface parameters well differentiated across scales. We found that the LV method performed better on scale levels generated through segmentation as compared to up-scaling through resampling. The results indicate that coupling multi-scale pattern analysis with delineation of morphometric primitives is possible. This approach could be further used for developing hierarchical classifications of landform elements. PMID:21779138

Probabilistic Approaches for Multi-Hazard Risk Assessment of Structures and Systems

NASA Astrophysics Data System (ADS)

Kwag, Shinyoung

Performance assessment of structures, systems, and components for multi-hazard scenarios has received significant attention in recent years. However, the concept of multi-hazard analysis is quite broad in nature and the focus of existing literature varies across a wide range of problems. In some cases, such studies focus on hazards that either occur simultaneously or are closely correlated with each other. For example, seismically induced flooding or seismically induced fires. In other cases, multi-hazard studies relate to hazards that are not dependent or correlated but have strong likelihood of occurrence at different times during the lifetime of a structure. The current approaches for risk assessment need enhancement to account for multi-hazard risks. It must be able to account for uncertainty propagation in a systems-level analysis, consider correlation among events or failure modes, and allow integration of newly available information from continually evolving simulation models, experimental observations, and field measurements. This dissertation presents a detailed study that proposes enhancements by incorporating Bayesian networks and Bayesian updating within a performance-based probabilistic framework. The performance-based framework allows propagation of risk as well as uncertainties in the risk estimates within a systems analysis. Unlike conventional risk assessment techniques such as a fault-tree analysis, a Bayesian network can account for statistical dependencies and correlations among events/hazards. The proposed approach is extended to develop a risk-informed framework for quantitative validation and verification of high fidelity system-level simulation tools. Validation of such simulations can be quite formidable within the context of a multi-hazard risk assessment in nuclear power plants. The efficiency of this approach lies in identification of critical events, components, and systems that contribute to the overall risk. Validation of any event or

Variability Extraction and Synthesis via Multi-Resolution Analysis using Distribution Transformer High-Speed Power Data

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

Chamana, Manohar; Mather, Barry A

A library of load variability classes is created to produce scalable synthetic data sets using historical high-speed raw data. These data are collected from distribution monitoring units connected at the secondary side of a distribution transformer. Because of the irregular patterns and large volume of historical high-speed data sets, the utilization of current load characterization and modeling techniques are challenging. Multi-resolution analysis techniques are applied to extract the necessary components and eliminate the unnecessary components from the historical high-speed raw data to create the library of classes, which are then utilized to create new synthetic load data sets. A validationmore » is performed to ensure that the synthesized data sets contain the same variability characteristics as the training data sets. The synthesized data sets are intended to be utilized in quasi-static time-series studies for distribution system planning studies on a granular scale, such as detailed PV interconnection studies.« less

Multi-body Dynamic Contact Analysis Tool for Transmission Design

DTIC Science & Technology

2003-04-01

frequencies were computed in COSMIC NASTRAN, and were validated against the published experimental modal analysis [17]. • Using assumed time domain... modal superposition. • Results from the structural analysis (mode shapes or forced response) were converted into IDEAS universal format (dataset 55...ARMY RESEARCH LABORATORY Multi-body Dynamic Contact Analysis Tool for Transmission Design SBIR Phase II Final Report by

Multi-stage decoding of multi-level modulation codes

NASA Technical Reports Server (NTRS)

Lin, Shu; Kasami, Tadao; Costello, Daniel J., Jr.

1991-01-01

Various types of multi-stage decoding for multi-level modulation codes are investigated. It is shown that if the component codes of a multi-level modulation code and types of decoding at various stages are chosen properly, high spectral efficiency and large coding gain can be achieved with reduced decoding complexity. Particularly, it is shown that the difference in performance between the suboptimum multi-stage soft-decision maximum likelihood decoding of a modulation code and the single-stage optimum soft-decision decoding of the code is very small, only a fraction of dB loss in signal to noise ratio at a bit error rate (BER) of 10(exp -6).

Relevance between SV and components based on water quality inspection by gas plumes

NASA Astrophysics Data System (ADS)

Nakanishi, A.; Aoyama, C.; Fukuoka, H.; Tajima, H.; Kumagai, H.; Takahashi, A.

2017-12-01

Gas and hydrate seeping from the seafloor into ocean water can be monitored on board, as images on echogram (acoustic equipment display inboard) by utilizing acoustic measurement equipment such as multi-beam sonars. Colors and shades of these images displayed on the monitor vary depending on the acoustic impedance. Backscattering strength (hereinafter referred as SV) depends on the type and density of plume components. Therefore, plume components should not be determined only by examining volume scattering density. By standardizing the relevance between gas plume SV and the components, types of plume components can be presumed just by calculating plume SV based on multi-beam data.Data from the following explorations will be utilized to perform the analysis of metal sensor, CTD measurement, and sampling. July, 2017 KAIYO-MARU2 (KAIYO ENGINEERING CO., LTD) @ Sea of Japan July, 2017 SIHNYO MARU (Tokyo University of Marine Science and Technology) @ Sea of Japan. And Chemical data obtained through YK16-07 cruise is also to be discussed.

Independent component analysis for automatic note extraction from musical trills

NASA Astrophysics Data System (ADS)

Brown, Judith C.; Smaragdis, Paris

2004-05-01

The method of principal component analysis, which is based on second-order statistics (or linear independence), has long been used for redundancy reduction of audio data. The more recent technique of independent component analysis, enforcing much stricter statistical criteria based on higher-order statistical independence, is introduced and shown to be far superior in separating independent musical sources. This theory has been applied to piano trills and a database of trill rates was assembled from experiments with a computer-driven piano, recordings of a professional pianist, and commercially available compact disks. The method of independent component analysis has thus been shown to be an outstanding, effective means of automatically extracting interesting musical information from a sea of redundant data.

Non-targeted multi-component analytical surveillance of plastic food contact materials: Identification of substances not included in EU positive lists and their risk assessment.

PubMed

Skjevrak, Ingun; Brede, Cato; Steffensen, Inger-Lise; Mikalsen, Arne; Alexander, Jan; Fjeldal, Per; Herikstad, Hallgeir

2005-10-01

A procedure used by the Norwegian Food Safety Authority for surveillance of contaminants from plastic food contact materials (polyolefin drinking bottles, water boilers, polyamide cooking utensils and plastic multi-layer materials) is described. It is based on gas chromatographic-mass spectrometric (GC/MS) analysis of food simulants exposed to plastic materials. Most migrants were substances not-intentionally added to the plastic (degradation products, impurities) or originated from non-plastic components, such as printing inks, adhesives, not-listed additives, solvents and coatings. Hence, the majority of the identified migrants were regulated by the general statements in the EU Framework Regulation, which neither specify limits nor requirements regarding risk assessment, rather than by specific migration controls. Risk assessment has been carried out for selected non-authorized substances. The analysis and the management of these substances and materials with respect to safety represents a challenge to the food authorities.

Design and analysis of optical systems for the Stanford/MSFC Multi-Spectral Solar Telescope Array

NASA Astrophysics Data System (ADS)

Hadaway, James B.; Johnson, R. Barry; Hoover, Richard B.; Lindblom, Joakim F.; Walker, Arthur B. C., Jr.

1989-07-01

This paper reports on the design and the theoretical ray trace analysis of the optical systems which will comprise the primary imaging components for the Stanford/MSFC Multi-Spectral Solar Telescope Array (MSSTA). This instrument is being developed for ultra-high resolution investigations of the sun from a sounding rocket. Doubly reflecting systems of sphere-sphere, ellipsoid-sphere (Dall-Kirkham), paraboloid-hyperboloid (Cassegrain), and hyperboloid-hyperboloid (Ritchey-Chretien) configurations were analyzed. For these mirror systems, ray trace analysis was performed and through-focus spot diagrams, point spread function plots, and geometrical and diffraction MTFs were generated. The results of these studies are presented along with the parameters of the Ritchey-Chretien optical system selected for the MSSTA flight. The payload, which incorporates seven of these Ritchey-Chretien systems, is now being prepared for launch in late September 1989.

Design and analysis of optical systems for the Stanford/MSFC Multi-Spectral Solar Telescope Array

NASA Technical Reports Server (NTRS)

Hadaway, James B.; Johnson, R. Barry; Hoover, Richard B.; Lindblom, Joakim F.; Walker, Arthur B. C., Jr.

1989-01-01

This paper reports on the design and the theoretical ray trace analysis of the optical systems which will comprise the primary imaging components for the Stanford/MSFC Multi-Spectral Solar Telescope Array (MSSTA). This instrument is being developed for ultra-high resolution investigations of the sun from a sounding rocket. Doubly reflecting systems of sphere-sphere, ellipsoid-sphere (Dall-Kirkham), paraboloid-hyperboloid (Cassegrain), and hyperboloid-hyperboloid (Ritchey-Chretien) configurations were analyzed. For these mirror systems, ray trace analysis was performed and through-focus spot diagrams, point spread function plots, and geometrical and diffraction MTFs were generated. The results of these studies are presented along with the parameters of the Ritchey-Chretien optical system selected for the MSSTA flight. The payload, which incorporates seven of these Ritchey-Chretien systems, is now being prepared for launch in late September 1989.

Improvement of Binary Analysis Components in Automated Malware Analysis Framework

DTIC Science & Technology

2017-02-21

analyze malicious software (malware) with minimum human interaction. The system autonomously analyze malware samples by analyzing malware binary program...AFRL-AFOSR-JP-TR-2017-0018 Improvement of Binary Analysis Components in Automated Malware Analysis Framework Keiji Takeda KEIO UNIVERSITY Final...currently valid OMB control number . PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ORGANIZATION. 1. REPORT DATE (DD-MM-YYYY)      21-02-2017 2. REPORT

Iterative development of Stand Up Australia: a multi-component intervention to reduce workplace sitting

PubMed Central

2014-01-01

Background Sitting, particularly in prolonged, unbroken bouts, is widespread within the office workplace, yet few interventions have addressed this newly-identified health risk behaviour. This paper describes the iterative development process and resulting intervention procedures for the Stand Up Australia research program focusing on a multi-component workplace intervention to reduce sitting time. Methods The development of Stand Up Australia followed three phases. 1) Conceptualisation: Stand Up Australia was based on social cognitive theory and social ecological model components. These were operationalised via a taxonomy of intervention strategies and designed to target multiple levels of influence including: organisational structures (e.g. via management consultation), the physical work environment (via provision of height-adjustable workstations), and individual employees (e.g. via face-to-face coaching). 2) Formative research: Intervention components were separately tested for their feasibility and acceptability. 3) Pilot studies: Stand Up Comcare tested the integrated intervention elements in a controlled pilot study examining efficacy, feasibility and acceptability. Stand Up UQ examined the additional value of the organisational- and individual-level components over height-adjustable workstations only in a three-arm controlled trial. In both pilot studies, office workers’ sitting time was measured objectively using activPAL3 devices and the intervention was refined based on qualitative feedback from managers and employees. Results Results and feedback from participants and managers involved in the intervention development phases suggest high efficacy, acceptance, and feasibility of all intervention components. The final version of the Stand Up Australia intervention includes strategies at the organisational (senior management consultation, representatives consultation workshop, team champions, staff information and brainstorming session with information

Automatic Denoising of Functional MRI Data: Combining Independent Component Analysis and Hierarchical Fusion of Classifiers

PubMed Central

Salimi-Khorshidi, Gholamreza; Douaud, Gwenaëlle; Beckmann, Christian F; Glasser, Matthew F; Griffanti, Ludovica; Smith, Stephen M

2014-01-01

Many sources of fluctuation contribute to the fMRI signal, and this makes identifying the effects that are truly related to the underlying neuronal activity difficult. Independent component analysis (ICA) - one of the most widely used techniques for the exploratory analysis of fMRI data - has shown to be a powerful technique in identifying various sources of neuronally-related and artefactual fluctuation in fMRI data (both with the application of external stimuli and with the subject “at rest”). ICA decomposes fMRI data into patterns of activity (a set of spatial maps and their corresponding time series) that are statistically independent and add linearly to explain voxel-wise time series. Given the set of ICA components, if the components representing “signal” (brain activity) can be distinguished form the “noise” components (effects of motion, non-neuronal physiology, scanner artefacts and other nuisance sources), the latter can then be removed from the data, providing an effective cleanup of structured noise. Manual classification of components is labour intensive and requires expertise; hence, a fully automatic noise detection algorithm that can reliably detect various types of noise sources (in both task and resting fMRI) is desirable. In this paper, we introduce FIX (“FMRIB’s ICA-based X-noiseifier”), which provides an automatic solution for denoising fMRI data via accurate classification of ICA components. For each ICA component FIX generates a large number of distinct spatial and temporal features, each describing a different aspect of the data (e.g., what proportion of temporal fluctuations are at high frequencies). The set of features is then fed into a multi-level classifier (built around several different Classifiers). Once trained through the hand-classification of a sufficient number of training datasets, the classifier can then automatically classify new datasets. The noise components can then be subtracted from (or regressed out of

The long-term benefits of a multi-component exercise intervention to balance and mobility in healthy older adults.

PubMed

Bird, M; Hill, K D; Ball, M; Hetherington, S; Williams, A D

2011-01-01

We examined the long-term effects of a multi-component exercise program on balance, mobility and exercise behavior. The benefits of a community-based resistance and flexibility exercise intervention in a group of healthy older (60-75 years) individuals were recorded 12 months after completion of the randomized control intervention. Differences between those participants who continued to exercise and those who discontinued were investigated. Significant improvements from baseline in sit to stand (p<0.001), timed up and go (p=0.001), and sway (p<0.001) remained at follow up in the exercise intervention group, with a control group unchanged. Participants who continued exercising had significantly greater improvements in strength immediately after the intervention, compared to those who discontinued (p=0.004). Those who continued regular resistance training performed better in the step test at 12-month follow up (p=0.009) and believed that the program was of more benefit to their physical activity (p<0.001) than those who discontinued exercising. Benefits to balance and mobility persist 1 year after participation in a multi-component exercise program, due in part to some continuing participation in resistance training. Motivation to continue resistance training may be related real and perceived benefits attained from the intervention as well as the environmental context of the intervention. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Using 3D spatial correlations to improve the noise robustness of multi component analysis of 3D multi echo quantitative T2 relaxometry data.

PubMed

Kumar, Dushyant; Hariharan, Hari; Faizy, Tobias D; Borchert, Patrick; Siemonsen, Susanne; Fiehler, Jens; Reddy, Ravinder; Sedlacik, Jan

2018-05-12

We present a computationally feasible and iterative multi-voxel spatially regularized algorithm for myelin water fraction (MWF) reconstruction. This method utilizes 3D spatial correlations present in anatomical/pathological tissues and underlying B1 + -inhomogeneity or flip angle inhomogeneity to enhance the noise robustness of the reconstruction while intrinsically accounting for stimulated echo contributions using T2-distribution data alone. Simulated data and in vivo data acquired using 3D non-selective multi-echo spin echo (3DNS-MESE) were used to compare the reconstruction quality of the proposed approach against those of the popular algorithm (the method by Prasloski et al.) and our previously proposed 2D multi-slice spatial regularization spatial regularization approach. We also investigated whether the inter-sequence correlations and agreements improved as a result of the proposed approach. MWF-quantifications from two sequences, 3DNS-MESE vs 3DNS-gradient and spin echo (3DNS-GRASE), were compared for both reconstruction approaches to assess correlations and agreements between inter-sequence MWF-value pairs. MWF values from whole-brain data of six volunteers and two multiple sclerosis patients are being reported as well. In comparison with competing approaches such as Prasloski's method or our previously proposed 2D multi-slice spatial regularization method, the proposed method showed better agreements with simulated truths using regression analyses and Bland-Altman analyses. For 3DNS-MESE data, MWF-maps reconstructed using the proposed algorithm provided better depictions of white matter structures in subcortical areas adjoining gray matter which agreed more closely with corresponding contrasts on T2-weighted images than MWF-maps reconstructed with the method by Prasloski et al. We also achieved a higher level of correlations and agreements between inter-sequence (3DNS-MESE vs 3DNS-GRASE) MWF-value pairs. The proposed algorithm provides more noise

Lattice Independent Component Analysis for Mobile Robot Localization

NASA Astrophysics Data System (ADS)

Villaverde, Ivan; Fernandez-Gauna, Borja; Zulueta, Ekaitz

This paper introduces an approach to appearance based mobile robot localization using Lattice Independent Component Analysis (LICA). The Endmember Induction Heuristic Algorithm (EIHA) is used to select a set of Strong Lattice Independent (SLI) vectors, which can be assumed to be Affine Independent, and therefore candidates to be the endmembers of the data. Selected endmembers are used to compute the linear unmixing of the robot's acquired images. The resulting mixing coefficients are used as feature vectors for view recognition through classification. We show on a sample path experiment that our approach can recognise the localization of the robot and we compare the results with the Independent Component Analysis (ICA).

Characterizing Heterogeneity within Head and Neck Lesions Using Cluster Analysis of Multi-Parametric MRI Data.

PubMed

Borri, Marco; Schmidt, Maria A; Powell, Ceri; Koh, Dow-Mu; Riddell, Angela M; Partridge, Mike; Bhide, Shreerang A; Nutting, Christopher M; Harrington, Kevin J; Newbold, Katie L; Leach, Martin O

2015-01-01

To describe a methodology, based on cluster analysis, to partition multi-parametric functional imaging data into groups (or clusters) of similar functional characteristics, with the aim of characterizing functional heterogeneity within head and neck tumour volumes. To evaluate the performance of the proposed approach on a set of longitudinal MRI data, analysing the evolution of the obtained sub-sets with treatment. The cluster analysis workflow was applied to a combination of dynamic contrast-enhanced and diffusion-weighted imaging MRI data from a cohort of squamous cell carcinoma of the head and neck patients. Cumulative distributions of voxels, containing pre and post-treatment data and including both primary tumours and lymph nodes, were partitioned into k clusters (k = 2, 3 or 4). Principal component analysis and cluster validation were employed to investigate data composition and to independently determine the optimal number of clusters. The evolution of the resulting sub-regions with induction chemotherapy treatment was assessed relative to the number of clusters. The clustering algorithm was able to separate clusters which significantly reduced in voxel number following induction chemotherapy from clusters with a non-significant reduction. Partitioning with the optimal number of clusters (k = 4), determined with cluster validation, produced the best separation between reducing and non-reducing clusters. The proposed methodology was able to identify tumour sub-regions with distinct functional properties, independently separating clusters which were affected differently by treatment. This work demonstrates that unsupervised cluster analysis, with no prior knowledge of the data, can be employed to provide a multi-parametric characterization of functional heterogeneity within tumour volumes.

Multimodal and Multi-tissue Measures of Connectivity Revealed by Joint Independent Component Analysis.

PubMed

Franco, Alexandre R; Ling, Josef; Caprihan, Arvind; Calhoun, Vince D; Jung, Rex E; Heileman, Gregory L; Mayer, Andrew R

2008-12-01

The human brain functions as an efficient system where signals arising from gray matter are transported via white matter tracts to other regions of the brain to facilitate human behavior. However, with a few exceptions, functional and structural neuroimaging data are typically optimized to maximize the quantification of signals arising from a single source. For example, functional magnetic resonance imaging (FMRI) is typically used as an index of gray matter functioning whereas diffusion tensor imaging (DTI) is typically used to determine white matter properties. While it is likely that these signals arising from different tissue sources contain complementary information, the signal processing algorithms necessary for the fusion of neuroimaging data across imaging modalities are still in a nascent stage. In the current paper we present a data-driven method for combining measures of functional connectivity arising from gray matter sources (FMRI resting state data) with different measures of white matter connectivity (DTI). Specifically, a joint independent component analysis (J-ICA) was used to combine these measures of functional connectivity following intensive signal processing and feature extraction within each of the individual modalities. Our results indicate that one of the most predominantly used measures of functional connectivity (activity in the default mode network) is highly dependent on the integrity of white matter connections between the two hemispheres (corpus callosum) and within the cingulate bundles. Importantly, the discovery of this complex relationship of connectivity was entirely facilitated by the signal processing and fusion techniques presented herein and could not have been revealed through separate analyses of both data types as is typically performed in the majority of neuroimaging experiments. We conclude by discussing future applications of this technique to other areas of neuroimaging and examining potential limitations of the

BioVLAB-mCpG-SNP-EXPRESS: A system for multi-level and multi-perspective analysis and exploration of DNA methylation, sequence variation (SNPs), and gene expression from multi-omics data.

PubMed

Chae, Heejoon; Lee, Sangseon; Seo, Seokjun; Jung, Daekyoung; Chang, Hyeonsook; Nephew, Kenneth P; Kim, Sun

2016-12-01

Measuring gene expression, DNA sequence variation, and DNA methylation status is routinely done using high throughput sequencing technologies. To analyze such multi-omics data and explore relationships, reliable bioinformatics systems are much needed. Existing systems are either for exploring curated data or for processing omics data in the form of a library such as R. Thus scientists have much difficulty in investigating relationships among gene expression, DNA sequence variation, and DNA methylation using multi-omics data. In this study, we report a system called BioVLAB-mCpG-SNP-EXPRESS for the integrated analysis of DNA methylation, sequence variation (SNPs), and gene expression for distinguishing cellular phenotypes at the pairwise and multiple phenotype levels. The system can be deployed on either the Amazon cloud or a publicly available high-performance computing node, and the data analysis and exploration of the analysis result can be conveniently done using a web-based interface. In order to alleviate analysis complexity, all the process are fully automated, and graphical workflow system is integrated to represent real-time analysis progression. The BioVLAB-mCpG-SNP-EXPRESS system works in three stages. First, it processes and analyzes multi-omics data as input in the form of the raw data, i.e., FastQ files. Second, various integrated analyses such as methylation vs. gene expression and mutation vs. methylation are performed. Finally, the analysis result can be explored in a number of ways through a web interface for the multi-level, multi-perspective exploration. Multi-level interpretation can be done by either gene, gene set, pathway or network level and multi-perspective exploration can be explored from either gene expression, DNA methylation, sequence variation, or their relationship perspective. The utility of the system is demonstrated by performing analysis of phenotypically distinct 30 breast cancer cell line data set. BioVLAB-mCpG-SNP-EXPRESS is

Single and multi-component adsorption of salicylic acid, clofibric acid, carbamazepine and caffeine from water onto transition metal modified and partially calcined inorganic-organic pillared clay fixed beds.

PubMed

Cabrera-Lafaurie, Wilman A; Román, Félix R; Hernández-Maldonado, Arturo J

2015-01-23

Fixed-beds of transition metal (Co(2+), Ni(2+) or Cu(2+)) inorganic-organic pillared clays (IOCs) were prepared to study single- and multi-component non-equilibrium adsorption of a set of pharmaceutical and personal care products (PPCPs: salicylic acid, clofibric acid, carbamazepine and caffeine) from water. Adsorption capacities for single components revealed that the copper(II) IOCs have better affinity toward salicylic and clofibric acid. However, multi-component adsorption tests showed a considerable decrease in adsorption capacity for the acids and an unusual selectivity toward carbamazepine depending on the transition metal. This was attributed to a combination of competition between PPCPs for adsorption sites, adsorbate-adsorbate interactions, and plausible pore blocking caused by carbamazepine. The cobalt(II) IOC bed that was partially calcined to fractionate the surfactant moiety showcased the best selectivity toward caffeine, even during multi-component adsorption. This was due to a combination of a mildly hydrophobic surface and interaction between the PPCP and cobalt(II). In general, the tests suggest that these IOCs may be a potential solution for the removal of PPCPs if employed in a layered-bed configuration, to take care of families of adsorbates in a sequence that would produce sharpened concentration wavefronts. Copyright © 2014 Elsevier B.V. All rights reserved.

Principal component analysis for designed experiments.

PubMed

Konishi, Tomokazu

2015-01-01

Principal component analysis is used to summarize matrix data, such as found in transcriptome, proteome or metabolome and medical examinations, into fewer dimensions by fitting the matrix to orthogonal axes. Although this methodology is frequently used in multivariate analyses, it has disadvantages when applied to experimental data. First, the identified principal components have poor generality; since the size and directions of the components are dependent on the particular data set, the components are valid only within the data set. Second, the method is sensitive to experimental noise and bias between sample groups. It cannot reflect the experimental design that is planned to manage the noise and bias; rather, it estimates the same weight and independence to all the samples in the matrix. Third, the resulting components are often difficult to interpret. To address these issues, several options were introduced to the methodology. First, the principal axes were identified using training data sets and shared across experiments. These training data reflect the design of experiments, and their preparation allows noise to be reduced and group bias to be removed. Second, the center of the rotation was determined in accordance with the experimental design. Third, the resulting components were scaled to unify their size unit. The effects of these options were observed in microarray experiments, and showed an improvement in the separation of groups and robustness to noise. The range of scaled scores was unaffected by the number of items. Additionally, unknown samples were appropriately classified using pre-arranged axes. Furthermore, these axes well reflected the characteristics of groups in the experiments. As was observed, the scaling of the components and sharing of axes enabled comparisons of the components beyond experiments. The use of training data reduced the effects of noise and bias in the data, facilitating the physical interpretation of the principal axes

Principal components analysis of Jupiter VIMS spectra

USGS Publications Warehouse

Bellucci, G.; Formisano, V.; D'Aversa, E.; Brown, R.H.; Baines, K.H.; Bibring, J.-P.; Buratti, B.J.; Capaccioni, F.; Cerroni, P.; Clark, R.N.; Coradini, A.; Cruikshank, D.P.; Drossart, P.; Jaumann, R.; Langevin, Y.; Matson, D.L.; McCord, T.B.; Mennella, V.; Nelson, R.M.; Nicholson, P.D.; Sicardy, B.; Sotin, Christophe; Chamberlain, M.C.; Hansen, G.; Hibbits, K.; Showalter, M.; Filacchione, G.

2004-01-01

During Cassini - Jupiter flyby occurred in December 2000, Visual-Infrared mapping spectrometer (VIMS) instrument took several image cubes of Jupiter at different phase angles and distances. We have analysed the spectral images acquired by the VIMS visual channel by means of a principal component analysis technique (PCA). The original data set consists of 96 spectral images in the 0.35-1.05 ??m wavelength range. The product of the analysis are new PC bands, which contain all the spectral variance of the original data. These new components have been used to produce a map of Jupiter made of seven coherent spectral classes. The map confirms previously published work done on the Great Red Spot by using NIMS data. Some other new findings, presently under investigation, are presented. ?? 2004 Published by Elsevier Ltd on behalf of COSPAR.

The Non-catalytic B Subunit of Coagulation Factor XIII Accelerates Fibrin Cross-linking*

PubMed Central

Souri, Masayoshi; Osaki, Tsukasa; Ichinose, Akitada

2015-01-01

Covalent cross-linking of fibrin chains is required for stable blood clot formation, which is catalyzed by coagulation factor XIII (FXIII), a proenzyme of plasma transglutaminase consisting of catalytic A (FXIII-A) and non-catalytic B subunits (FXIII-B). Herein, we demonstrate that FXIII-B accelerates fibrin cross-linking. Depletion of FXIII-B from normal plasma supplemented with a physiological level of recombinant FXIII-A resulted in delayed fibrin cross-linking, reduced incorporation of FXIII-A into fibrin clots, and impaired activation peptide cleavage by thrombin; the addition of recombinant FXIII-B restored normal fibrin cross-linking, FXIII-A incorporation into fibrin clots, and activation peptide cleavage by thrombin. Immunoprecipitation with an anti-fibrinogen antibody revealed an interaction between the FXIII heterotetramer and fibrinogen mediated by FXIII-B and not FXIII-A. FXIII-B probably binds the γ-chain of fibrinogen with its D-domain, which is near the fibrin polymerization pockets, and dissociates from fibrin during or after cross-linking between γ-chains. Thus, FXIII-B plays important roles in the formation of a ternary complex between proenzyme FXIII, prosubstrate fibrinogen, and activator thrombin. Accordingly, congenital or acquired FXIII-B deficiency may result in increased bleeding tendency through impaired fibrin stabilization due to decreased FXIII-A activation by thrombin and secondary FXIII-A deficiency arising from enhanced circulatory clearance. PMID:25809477

Functional Generalized Structured Component Analysis.

PubMed

Suk, Hye Won; Hwang, Heungsun

2016-12-01

An extension of Generalized Structured Component Analysis (GSCA), called Functional GSCA, is proposed to analyze functional data that are considered to arise from an underlying smooth curve varying over time or other continua. GSCA has been geared for the analysis of multivariate data. Accordingly, it cannot deal with functional data that often involve different measurement occasions across participants and a large number of measurement occasions that exceed the number of participants. Functional GSCA addresses these issues by integrating GSCA with spline basis function expansions that represent infinite-dimensional curves onto a finite-dimensional space. For parameter estimation, functional GSCA minimizes a penalized least squares criterion by using an alternating penalized least squares estimation algorithm. The usefulness of functional GSCA is illustrated with gait data.

Estimation and Psychometric Analysis of Component Profile Scores via Multivariate Generalizability Theory

ERIC Educational Resources Information Center

Grochowalski, Joseph H.

2015-01-01

Component Universe Score Profile analysis (CUSP) is introduced in this paper as a psychometric alternative to multivariate profile analysis. The theoretical foundations of CUSP analysis are reviewed, which include multivariate generalizability theory and constrained principal components analysis. Because CUSP is a combination of generalizability…

Exploring functional data analysis and wavelet principal component analysis on ecstasy (MDMA) wastewater data.

PubMed

Salvatore, Stefania; Bramness, Jørgen G; Røislien, Jo

2016-07-12

Wastewater-based epidemiology (WBE) is a novel approach in drug use epidemiology which aims to monitor the extent of use of various drugs in a community. In this study, we investigate functional principal component analysis (FPCA) as a tool for analysing WBE data and compare it to traditional principal component analysis (PCA) and to wavelet principal component analysis (WPCA) which is more flexible temporally. We analysed temporal wastewater data from 42 European cities collected daily over one week in March 2013. The main temporal features of ecstasy (MDMA) were extracted using FPCA using both Fourier and B-spline basis functions with three different smoothing parameters, along with PCA and WPCA with different mother wavelets and shrinkage rules. The stability of FPCA was explored through bootstrapping and analysis of sensitivity to missing data. The first three principal components (PCs), functional principal components (FPCs) and wavelet principal components (WPCs) explained 87.5-99.6 % of the temporal variation between cities, depending on the choice of basis and smoothing. The extracted temporal features from PCA, FPCA and WPCA were consistent. FPCA using Fourier basis and common-optimal smoothing was the most stable and least sensitive to missing data. FPCA is a flexible and analytically tractable method for analysing temporal changes in wastewater data, and is robust to missing data. WPCA did not reveal any rapid temporal changes in the data not captured by FPCA. Overall the results suggest FPCA with Fourier basis functions and common-optimal smoothing parameter as the most accurate approach when analysing WBE data.

Appliance of Independent Component Analysis to System Intrusion Analysis

NASA Astrophysics Data System (ADS)

Ishii, Yoshikazu; Takagi, Tarou; Nakai, Kouji

In order to analyze the output of the intrusion detection system and the firewall, we evaluated the applicability of ICA(independent component analysis). We developed a simulator for evaluation of intrusion analysis method. The simulator consists of the network model of an information system, the service model and the vulnerability model of each server, and the action model performed on client and intruder. We applied the ICA for analyzing the audit trail of simulated information system. We report the evaluation result of the ICA on intrusion analysis. In the simulated case, ICA separated two attacks correctly, and related an attack and the abnormalities of the normal application produced under the influence of the attach.

Patient-reported benefit of ReSTOR multi-focal intraocular lenses after cataract surgery: results of principal component analysis on clinical trial data.

PubMed

Berdeaux, Gilles; Viala, Muriel; Roborel de Climens, Aude; Arnould, Benoit

2008-01-24

Restoration of functional distance and near vision independently of additional correction remains a goal for cataract surgery. ReSTOR, a new multi-focal intraocular lens (IOL) addresses this issue with an improvement in both distance and near vision, often without need for glasses. This analysis attempted to discuss the patient-reported benefit of ReSTOR using a full but organised representation of data. Two non-randomised, open-label clinical trials conducted in Europe and the United-States were conducted to compare the efficacy of ReSTOR to AcrySof mono-focal IOLs. A total of 710 patients in need of bilateral cataract extraction were included in the pooled study. The TyPE, a patient questionnaire, was fully completed by 672 of them before and after each eye surgery. The TyPE, composed of 67 items measuring overall visual functioning in both conditions (with and without wearing glasses), evaluates limitations, troubles and satisfaction in distance and near vision. A principal component analysis (PCA) of the TyPE questionnaire was performed on pooled data from baseline and post-surgery observations in order to fully represent the change in the TyPE data over time. ReSTOR and mono-focal groups were used as illustrative variables. The coordinates of the first 2 factors were compared between visits and between IOLs (ReSTOR vs. mono-focal), using paired t-tests and t-tests, respectively. The first factor of the PCA explained 55% of the variance and represented 'visual functioning and patient satisfaction'. The second factor explained 6% of the variance and was interpreted as 'independence from glasses'. An overall difference in factorial coordinates in both factors was seen between baseline and the first eye surgery, and between the first and the second eye surgery. No difference between ReSTOR and mono-focal IOL groups was observed at baseline. After surgery, ReSTOR treated-patients had higher coordinates on both "visual functioning and satisfaction" and "independence

Optical CDMA components requirements

NASA Astrophysics Data System (ADS)

Chan, James K.

1998-08-01

Optical CDMA is a complementary multiple access technology to WDMA. Optical CDMA potentially provides a large number of virtual optical channels for IXC, LEC and CLEC or supports a large number of high-speed users in LAN. In a network, it provides asynchronous, multi-rate, multi-user communication with network scalability, re-configurability (bandwidth on demand), and network security (provided by inherent CDMA coding). However, optical CDMA technology is less mature in comparison to WDMA. The components requirements are also different from WDMA. We have demonstrated a video transport/switching system over a distance of 40 Km using discrete optical components in our laboratory. We are currently pursuing PIC implementation. In this paper, we will describe the optical CDMA concept/features, the demonstration system, and the requirements of some critical optical components such as broadband optical source, broadband optical amplifier, spectral spreading/de- spreading, and fixed/programmable mask.