Dynamics of acoustic-convective drying of sunflower cake

NASA Astrophysics Data System (ADS)

Zhilin, A. A.

2017-10-01

The dynamics of drying sunflower cake by a new acoustic-convective method has been studied. Unlike the conventional (thermal-convective) method, the proposed method allows moisture to be extracted from porous materials without applying heat to the sample to be dried. Kinetic curves of drying by the thermal-convective and acoustic-convective methods were obtained and analyzed. The advantages of the acoustic-convective extraction of moisture over the thermal-convective method are discussed. The relaxation times of drying were determined for both drying methods. An intermittent drying mode which improves the efficiency of acoustic-convective extraction of moisture is considered.

Will a Category Cue Attract You? Motor Output Reveals Dynamic Competition across Person Construal

ERIC Educational Resources Information Center

Freeman, Jonathan B.; Ambady, Nalini; Rule, Nicholas O.; Johnson, Kerri L.

2008-01-01

People use social categories to perceive others, extracting category cues to glean membership. Growing evidence for continuous dynamics in real-time cognition suggests, contrary to prevailing social psychological accounts, that person construal may involve dynamic competition between simultaneously active representations. To test this, the authors…

Kinetics from Replica Exchange Molecular Dynamics Simulations.

PubMed

Stelzl, Lukas S; Hummer, Gerhard

2017-08-08

Transitions between metastable states govern many fundamental processes in physics, chemistry and biology, from nucleation events in phase transitions to the folding of proteins. The free energy surfaces underlying these processes can be obtained from simulations using enhanced sampling methods. However, their altered dynamics makes kinetic and mechanistic information difficult or impossible to extract. Here, we show that, with replica exchange molecular dynamics (REMD), one can not only sample equilibrium properties but also extract kinetic information. For systems that strictly obey first-order kinetics, the procedure to extract rates is rigorous. For actual molecular systems whose long-time dynamics are captured by kinetic rate models, accurate rate coefficients can be determined from the statistics of the transitions between the metastable states at each replica temperature. We demonstrate the practical applicability of the procedure by constructing master equation (Markov state) models of peptide and RNA folding from REMD simulations.

Flow-through dynamic microextraction system for automatic in vitro assessment of chyme bioaccessibility in food commodities.

PubMed

Souza, Lais A; Rosende, María; Korn, Maria Graças A; Miró, Manuel

2018-10-05

An automatic flow-through dynamic extraction method is proposed for the first time for in vitro exploration, with high temporal resolution, of the transit of the chyme from the gastric to the duodenal compartment using the Versantvoort's fed-state physiologically relevant extraction test. The flow manifold was coupled on-line to an inductively coupled plasma optical emission spectrometer (ICP OES) for real-time elucidation of the bioaccessible elemental fraction of micronutrients (viz., Cu, Fe and Mn) in food commodities across the gastrointestinal tract. The simulated intestinal and bile biofluid (added to the gastric phase) was successively pumped at 1.0 mL min -1 through a large-bore column (maintained at 37.0 ± 2.0 °C) initially loaded with a weighed amount of linseed (250 mg) using a PVDF filter membrane (5.0 μm pore size) for retaining of the solid sample and in-line filtration of the extracts. The lack of bias (trueness) of the on-line gastrointestinal extraction method coupled to ICP OES was confirmed using mass balance validation following microwave assisted digestion of the residual (non-bioaccessible) elemental fraction. Mass balance validation yielded absolute recoveries spanning from 79 to 121% for the overall analytes and samples. On-line dynamic extraction was critically appraised against batch counterparts for both gastric and gastrointestinal compartments. Due to the lack of consensus in the literature regarding the agitation method for batch oral bioaccessibility testing, several extraction approaches (viz., magnetic stirring, end-over-end rotation and orbital shaking) were evaluated. Improved gastric extractability of Fe along with bioaccessible data comparable to the dynamic counterpart based on the continuous displacement of the extraction equilibrium was obtained with batchwise magnetic stirring, which is deemed most appropriate for ascertaining worst-case/maximum bioaccessibility scenarios. Copyright © 2018 Elsevier B.V. All rights reserved.

[Study on condition for extraction of arctiin from fruits of Arctium lappa using supercritical fluid extraction].

PubMed

Dong, Wen-hong; Liu, Ben

2006-08-01

To study the feasibility of supercritical fluid extraction (SFE) for arctiin from the fruits of Arctium lappa. The extracts were analyzed by HPLC, optimum extraction conditions were studied by orthogonal tests. The optimal extraction conditions were: pressure 40 MPa, temperature 70 degrees C, using methanol as modifier carrier at the rate of 0.55 mL x min(-1), static extraction time 5 min, dynamic extraction 30 min, flow rate of CO2 2 L x min(-1). SFE has the superiority of adjustable polarity, and has the ability of extracting arctiin.

Supercritical carbon dioxide extraction of seed oil from winter melon (Benincasa hispida) and its antioxidant activity and fatty acid composition.

PubMed

Bimakr, Mandana; Rahman, Russly Abdul; Taip, Farah Saleena; Adzahan, Noranizan Mohd; Sarker, Md Zaidul Islam; Ganjloo, Ali

2013-01-15

In the present study, supercritical carbon dioxide (SC-CO(2)) extraction of seed oil from winter melon (Benincasa hispida) was investigated. The effects of process variables namely pressure (150-300 bar), temperature (40-50 °C) and dynamic extraction time (60-120 min) on crude extraction yield (CEY) were studied through response surface methodology (RSM). The SC-CO(2) extraction process was modified using ethanol (99.9%) as co-solvent. Perturbation plot revealed the significant effect of all process variables on the CEY. A central composite design (CCD) was used to optimize the process conditions to achieve maximum CEY. The optimum conditions were 244 bar pressure, 46 °C temperature and 97 min dynamic extraction time. Under these optimal conditions, the CEY was predicted to be 176.30 mg-extract/g-dried sample. The validation experiment results agreed with the predicted value. The antioxidant activity and fatty acid composition of crude oil obtained under optimized conditions were determined and compared with published results using Soxhlet extraction (SE) and ultrasound assisted extraction (UAE). It was found that the antioxidant activity of the extract obtained by SC-CO(2) extraction was strongly higher than those obtained by SE and UAE. Identification of fatty acid composition using gas chromatography (GC) showed that all the extracts were rich in unsaturated fatty acids with the most being linoleic acid. In contrast, the amount of saturated fatty acids extracted by SE was higher than that extracted under optimized SC-CO(2) extraction conditions.

A New Strategy for Analyzing Time-Series Data Using Dynamic Networks: Identifying Prospective Biomarkers of Hepatocellular Carcinoma.

PubMed

Huang, Xin; Zeng, Jun; Zhou, Lina; Hu, Chunxiu; Yin, Peiyuan; Lin, Xiaohui

2016-08-31

Time-series metabolomics studies can provide insight into the dynamics of disease development and facilitate the discovery of prospective biomarkers. To improve the performance of early risk identification, a new strategy for analyzing time-series data based on dynamic networks (ATSD-DN) in a systematic time dimension is proposed. In ATSD-DN, the non-overlapping ratio was applied to measure the changes in feature ratios during the process of disease development and to construct dynamic networks. Dynamic concentration analysis and network topological structure analysis were performed to extract early warning information. This strategy was applied to the study of time-series lipidomics data from a stepwise hepatocarcinogenesis rat model. A ratio of lyso-phosphatidylcholine (LPC) 18:1/free fatty acid (FFA) 20:5 was identified as the potential biomarker for hepatocellular carcinoma (HCC). It can be used to classify HCC and non-HCC rats, and the area under the curve values in the discovery and external validation sets were 0.980 and 0.972, respectively. This strategy was also compared with a weighted relative difference accumulation algorithm (wRDA), multivariate empirical Bayes statistics (MEBA) and support vector machine-recursive feature elimination (SVM-RFE). The better performance of ATSD-DN suggests its potential for a more complete presentation of time-series changes and effective extraction of early warning information.

A New Strategy for Analyzing Time-Series Data Using Dynamic Networks: Identifying Prospective Biomarkers of Hepatocellular Carcinoma

NASA Astrophysics Data System (ADS)

Huang, Xin; Zeng, Jun; Zhou, Lina; Hu, Chunxiu; Yin, Peiyuan; Lin, Xiaohui

2016-08-01

Time-series metabolomics studies can provide insight into the dynamics of disease development and facilitate the discovery of prospective biomarkers. To improve the performance of early risk identification, a new strategy for analyzing time-series data based on dynamic networks (ATSD-DN) in a systematic time dimension is proposed. In ATSD-DN, the non-overlapping ratio was applied to measure the changes in feature ratios during the process of disease development and to construct dynamic networks. Dynamic concentration analysis and network topological structure analysis were performed to extract early warning information. This strategy was applied to the study of time-series lipidomics data from a stepwise hepatocarcinogenesis rat model. A ratio of lyso-phosphatidylcholine (LPC) 18:1/free fatty acid (FFA) 20:5 was identified as the potential biomarker for hepatocellular carcinoma (HCC). It can be used to classify HCC and non-HCC rats, and the area under the curve values in the discovery and external validation sets were 0.980 and 0.972, respectively. This strategy was also compared with a weighted relative difference accumulation algorithm (wRDA), multivariate empirical Bayes statistics (MEBA) and support vector machine-recursive feature elimination (SVM-RFE). The better performance of ATSD-DN suggests its potential for a more complete presentation of time-series changes and effective extraction of early warning information.

Forest canopy growth dynamic modeling based on remote sensing prodcuts and meteorological data in Daxing'anling of Northeast China

NASA Astrophysics Data System (ADS)

Wu, Qiaoli; Song, Jinling; Wang, Jindi; Xiao, Zhiqiang

2014-11-01

Leaf Area Index (LAI) is an important biophysical variable for vegetation. Compared with vegetation indexes like NDVI and EVI, LAI is more capable of monitoring forest canopy growth quantitatively. GLASS LAI is a spatially complete and temporally continuous product derived from AVHRR and MODIS reflectance data. In this paper, we present the approach to build dynamic LAI growth models for young and mature Larix gmelinii forest in north Daxing'anling in Inner Mongolia of China using the Dynamic Harmonic Regression (DHR) model and Double Logistic (D-L) model respectively, based on the time series extracted from multi-temporal GLASS LAI data. Meanwhile we used the dynamic threshold method to attract the key phenological phases of Larix gmelinii forest from the simulated time series. Then, through the relationship analysis between phenological phases and the meteorological factors, we found that the annual peak LAI and the annual maximum temperature have a good correlation coefficient. The results indicate this forest canopy growth dynamic model to be very effective in predicting forest canopy LAI growth and extracting forest canopy LAI growth dynamic.

Development and characterization of a green procedure for apigenin extraction from Scutellaria barbata D. Don.

PubMed

Yang, Yu-Chiao; Wei, Ming-Chi

2018-06-30

This study compared the use of ultrasound-assisted supercritical CO 2 (USC-CO 2 ) extraction to obtain apigenin-rich extracts from Scutellaria barbata D. Don with that of conventional supercritical CO 2 (SC-CO 2 ) extraction and heat-reflux extraction (HRE), conducted in parallel. This green procedure yielded 20.1% and 31.6% more apigenin than conventional SC-CO 2 extraction and HRE, respectively. Moreover, the extraction time required by the USC-CO 2 procedure, which used milder conditions, was approximately 1.9 times and 2.4 times shorter than that required by conventional SC-CO 2 extraction and HRE, respectively. Furthermore, the theoretical solubility of apigenin in the supercritical fluid system was obtained from the USC-CO 2 dynamic extraction curves and was in good agreement with the calculated values for the three empirical density-based models. The second-order kinetics model was further applied to evaluate the kinetics of USC-CO 2 extraction. The results demonstrated that the selected model allowed the evaluation of the extraction rate and extent of USC-CO 2 extraction. Copyright © 2017 Elsevier Ltd. All rights reserved.

Symbolic dynamic filtering and language measure for behavior identification of mobile robots.

PubMed

Mallapragada, Goutham; Ray, Asok; Jin, Xin

2012-06-01

This paper presents a procedure for behavior identification of mobile robots, which requires limited or no domain knowledge of the underlying process. While the features of robot behavior are extracted by symbolic dynamic filtering of the observed time series, the behavior patterns are classified based on language measure theory. The behavior identification procedure has been experimentally validated on a networked robotic test bed by comparison with commonly used tools, namely, principal component analysis for feature extraction and Bayesian risk analysis for pattern classification.

Waveform fitting and geometry analysis for full-waveform lidar feature extraction

NASA Astrophysics Data System (ADS)

Tsai, Fuan; Lai, Jhe-Syuan; Cheng, Yi-Hsiu

2016-10-01

This paper presents a systematic approach that integrates spline curve fitting and geometry analysis to extract full-waveform LiDAR features for land-cover classification. The cubic smoothing spline algorithm is used to fit the waveform curve of the received LiDAR signals. After that, the local peak locations of the waveform curve are detected using a second derivative method. According to the detected local peak locations, commonly used full-waveform features such as full width at half maximum (FWHM) and amplitude can then be obtained. In addition, the number of peaks, time difference between the first and last peaks, and the average amplitude are also considered as features of LiDAR waveforms with multiple returns. Based on the waveform geometry, dynamic time-warping (DTW) is applied to measure the waveform similarity. The sum of the absolute amplitude differences that remain after time-warping can be used as a similarity feature in a classification procedure. An airborne full-waveform LiDAR data set was used to test the performance of the developed feature extraction method for land-cover classification. Experimental results indicate that the developed spline curve- fitting algorithm and geometry analysis can extract helpful full-waveform LiDAR features to produce better land-cover classification than conventional LiDAR data and feature extraction methods. In particular, the multiple-return features and the dynamic time-warping index can improve the classification results significantly.

Dynamic ultrasonic nebulisation extraction coupled with headspace ionic liquid-based single-drop microextraction for the analysis of the essential oil in Forsythia suspensa.

PubMed

Yang, Jinjuan; Wei, Hongmin; Teng, Xiane; Zhang, Hanqi; Shi, Yuhua

2014-01-01

Ionic liquids have attracted much attention as an extraction solvent instead of traditional organic solvent in single-drop microextraction. However, non-volatile ionic liquids are difficult to couple with gas chromatography. Thus, the following injection system for the determination of organic compounds is described. To establish an environmentally friendly, simple, and effective extraction method for preparation and analysis of the essential oil from aromatic plants. The dynamic ultrasonic nebulisation extraction was coupled with headspace ionic liquid-based single-drop microextraction(UNE-HS/IL/SDME)for the extraction of essential oils from Forsythia suspense fruits. After 13 min of extraction for 50 mg sample, the extracts in ionic liquid were evaporated rapidly in the gas chromatography injector through a thermal desorption unit (5 s). The traditional extraction method was carried out for comparative study. The optimum conditions were: 3 μL of 1-methyl-3-octylimidazolium hexafluorophosphate was selected as the extraction solvent, the sample amount was 50 mg, the flow rate of purging gas was 200 mL/min, the extraction time was 13 min, the injection volume was 2 μL, and the thermal desorption temperature and time were 240 °C and 5 s respectively. Comparing with hydrodistillation (HD), the proposed method was environment friendly and efficient. The proposed method is environmentally friendly, time saving, with high efficiency and low consumption. It would extend the application range of the HS/SDME and would be useful especially for aromatic plants analysis. Copyright © 2013 John Wiley & Sons, Ltd.

Dynamic microwave assisted extraction coupled with dispersive micro-solid-phase extraction of herbicides in soybeans.

PubMed

Li, Na; Wu, Lijie; Nian, Li; Song, Ying; Lei, Lei; Yang, Xiao; Wang, Kun; Wang, Zhibing; Zhang, Liyuan; Zhang, Hanqi; Yu, Aimin; Zhang, Ziwei

2015-09-01

Non-polar solvent dynamic microwave assisted extraction was firstly applied to the treatment of high-fat soybean samples. In the dispersive micro-solid-phase extraction (D-µ-SPE), the herbicides in the high-fat extract were directly adsorbed on metal-organic frameworks MIL-101(Cr). The effects of several experimental parameters, including extraction solvent, microwave absorption medium, microwave power, volume and flow rate of extraction solvent, amount of MIL-101(Cr), and D-µ-SPE time, were investigated. At the optimal conditions, the limits of detection for the herbicides ranged from 1.56 to 2.00 μg kg(-1). The relative recoveries of the herbicides were in the range of 91.1-106.7%, and relative standard deviations were equal to or lower than 6.7%. The present method was simple, rapid and effective. A large amount of fat was also removed. This method was demonstrated to be suitable for treatment of high-fat samples. Copyright © 2015 Elsevier B.V. All rights reserved.

[Mass Transfer Kinetics Model of Ultrasonic Extraction of Pomegranate Peel Polyphenols].

PubMed

Wang, Zhan-yi; Zhang, Li-hua; Wang, Yu-hai; Zhang, Yuan-hu; Ma, Li; Zheng, Dan-dan

2015-05-01

The dynamic mathematical model of ultrasonic extraction of polyphenols from pomegranate peel was constructed with the Fick's second law as the theoretical basis. The spherical model was selected, with mass concentrations of pomegranate peel polyphenols as the index, 50% ethanol as the extraction solvent and ultrasonic extraction as the extraction method. In different test conditions including the liquid ratio, extraction temperature and extraction time, a series of kinetic parameters were solved, such as the extraction process (k), relative raffinate rate, surface diffusion coefficient(D(S)), half life (t½) and the apparent activation energy (E(a)). With the extraction temperature increasing, k and D(S) were gradually increased with t½ decreasing,which indicated that the elevated temperature was favorable to the extraction of pomegranate peel polyphenols. The exponential equation of relative raffinate rate showed that the established numerical dynamics model fitted the extraction of pomegranate peel polyphenols, and the relationship between the reaction conditions and pomegranate peel polyphenols concentration was well reflected by the model. Based on the experimental results, a feasible and reliable kinetic model for ultrasonic extraction of polyphenols from pomegranate peel is established, which can be used for the optimization control of engineering magnifying production.

Parallel processing of real-time dynamic systems simulation on OSCAR (Optimally SCheduled Advanced multiprocessoR)

NASA Technical Reports Server (NTRS)

Kasahara, Hironori; Honda, Hiroki; Narita, Seinosuke

1989-01-01

Parallel processing of real-time dynamic systems simulation on a multiprocessor system named OSCAR is presented. In the simulation of dynamic systems, generally, the same calculation are repeated every time step. However, we cannot apply to Do-all or the Do-across techniques for parallel processing of the simulation since there exist data dependencies from the end of an iteration to the beginning of the next iteration and furthermore data-input and data-output are required every sampling time period. Therefore, parallelism inside the calculation required for a single time step, or a large basic block which consists of arithmetic assignment statements, must be used. In the proposed method, near fine grain tasks, each of which consists of one or more floating point operations, are generated to extract the parallelism from the calculation and assigned to processors by using optimal static scheduling at compile time in order to reduce large run time overhead caused by the use of near fine grain tasks. The practicality of the scheme is demonstrated on OSCAR (Optimally SCheduled Advanced multiprocessoR) which has been developed to extract advantageous features of static scheduling algorithms to the maximum extent.

Ballistic missile precession frequency extraction by spectrogram's texture

NASA Astrophysics Data System (ADS)

Wu, Longlong; Xu, Shiyou; Li, Gang; Chen, Zengping

2013-10-01

In order to extract precession frequency, an crucial parameter in ballistic target recognition, which reflected the kinematical characteristics as well as structural and mass distribution features, we developed a dynamic RCS signal model for a conical ballistic missile warhead, with a log-norm multiplicative noise, substituting the familiar additive noise, derived formulas of micro-Doppler induced by precession motion, and analyzed time-varying micro-Doppler features utilizing time-frequency transforms, extracted precession frequency by measuring the spectrogram's texture, verified them by computer simulation studies. Simulation demonstrates the excellent performance of the method proposed in extracting the precession frequency, especially in the case of low SNR.

Extracting Leading Nonlinear Modes of Changing Climate From Global SST Time Series

NASA Astrophysics Data System (ADS)

Mukhin, D.; Gavrilov, A.; Loskutov, E. M.; Feigin, A. M.; Kurths, J.

2017-12-01

Data-driven modeling of climate requires adequate principal variables extracted from observed high-dimensional data. For constructing such variables it is needed to find spatial-temporal patterns explaining a substantial part of the variability and comprising all dynamically related time series from the data. The difficulties of this task rise from the nonlinearity and non-stationarity of the climate dynamical system. The nonlinearity leads to insufficiency of linear methods of data decomposition for separating different processes entangled in the observed time series. On the other hand, various forcings, both anthropogenic and natural, make the dynamics non-stationary, and we should be able to describe the response of the system to such forcings in order to separate the modes explaining the internal variability. The method we present is aimed to overcome both these problems. The method is based on the Nonlinear Dynamical Mode (NDM) decomposition [1,2], but takes into account external forcing signals. An each mode depends on hidden, unknown a priori, time series which, together with external forcing time series, are mapped onto data space. Finding both the hidden signals and the mapping allows us to study the evolution of the modes' structure in changing external conditions and to compare the roles of the internal variability and forcing in the observed behavior. The method is used for extracting of the principal modes of SST variability on inter-annual and multidecadal time scales accounting the external forcings such as CO2, variations of the solar activity and volcanic activity. The structure of the revealed teleconnection patterns as well as their forecast under different CO2 emission scenarios are discussed.[1] Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510. [2] Gavrilov, A., Mukhin, D., Loskutov, E., Volodin, E., Feigin, A., & Kurths, J. (2016). Method for reconstructing nonlinear modes with adaptive structure from multidimensional data. Chaos: An Interdisciplinary Journal of Nonlinear Science, 26(12), 123101.

Tracking vortices in superconductors: Extracting singularities from a discretized complex scalar field evolving in time

DOE PAGES

Phillips, Carolyn L.; Guo, Hanqi; Peterka, Tom; ...

2016-02-19

In type-II superconductors, the dynamics of magnetic flux vortices determine their transport properties. In the Ginzburg-Landau theory, vortices correspond to topological defects in the complex order parameter field. Earlier, we introduced a method for extracting vortices from the discretized complex order parameter field generated by a large-scale simulation of vortex matter. With this method, at a fixed time step, each vortex [simplistically, a one-dimensional (1D) curve in 3D space] can be represented as a connected graph extracted from the discretized field. Here we extend this method as a function of time as well. A vortex now corresponds to a 2Dmore » space-time sheet embedded in 4D space time that can be represented as a connected graph extracted from the discretized field over both space and time. Vortices that interact by merging or splitting correspond to disappearance and appearance of holes in the connected graph in the time direction. This method of tracking vortices, which makes no assumptions about the scale or behavior of the vortices, can track the vortices with a resolution as good as the discretization of the temporally evolving complex scalar field. In addition, even details of the trajectory between time steps can be reconstructed from the connected graph. With this form of vortex tracking, the details of vortex dynamics in a model of a superconducting materials can be understood in greater detail than previously possible.« less

HOTS: A Hierarchy of Event-Based Time-Surfaces for Pattern Recognition.

PubMed

Lagorce, Xavier; Orchard, Garrick; Galluppi, Francesco; Shi, Bertram E; Benosman, Ryad B

2017-07-01

This paper describes novel event-based spatio-temporal features called time-surfaces and how they can be used to create a hierarchical event-based pattern recognition architecture. Unlike existing hierarchical architectures for pattern recognition, the presented model relies on a time oriented approach to extract spatio-temporal features from the asynchronously acquired dynamics of a visual scene. These dynamics are acquired using biologically inspired frameless asynchronous event-driven vision sensors. Similarly to cortical structures, subsequent layers in our hierarchy extract increasingly abstract features using increasingly large spatio-temporal windows. The central concept is to use the rich temporal information provided by events to create contexts in the form of time-surfaces which represent the recent temporal activity within a local spatial neighborhood. We demonstrate that this concept can robustly be used at all stages of an event-based hierarchical model. First layer feature units operate on groups of pixels, while subsequent layer feature units operate on the output of lower level feature units. We report results on a previously published 36 class character recognition task and a four class canonical dynamic card pip task, achieving near 100 percent accuracy on each. We introduce a new seven class moving face recognition task, achieving 79 percent accuracy.This paper describes novel event-based spatio-temporal features called time-surfaces and how they can be used to create a hierarchical event-based pattern recognition architecture. Unlike existing hierarchical architectures for pattern recognition, the presented model relies on a time oriented approach to extract spatio-temporal features from the asynchronously acquired dynamics of a visual scene. These dynamics are acquired using biologically inspired frameless asynchronous event-driven vision sensors. Similarly to cortical structures, subsequent layers in our hierarchy extract increasingly abstract features using increasingly large spatio-temporal windows. The central concept is to use the rich temporal information provided by events to create contexts in the form of time-surfaces which represent the recent temporal activity within a local spatial neighborhood. We demonstrate that this concept can robustly be used at all stages of an event-based hierarchical model. First layer feature units operate on groups of pixels, while subsequent layer feature units operate on the output of lower level feature units. We report results on a previously published 36 class character recognition task and a four class canonical dynamic card pip task, achieving near 100 percent accuracy on each. We introduce a new seven class moving face recognition task, achieving 79 percent accuracy.

Time dependent calibration of a sediment extraction scheme.

PubMed

Roychoudhury, Alakendra N

2006-04-01

Sediment extraction methods to quantify metal concentration in aquatic sediments usually present limitations in accuracy and reproducibility because metal concentration in the supernatant is controlled to a large extent by the physico-chemical properties of the sediment that result in a complex interplay between the solid and the solution phase. It is suggested here that standardization of sediment extraction methods using pure mineral phases or reference material is futile and instead the extraction processes should be calibrated using site-specific sediments before their application. For calibration, time dependent release of metals should be observed for each leachate to ascertain the appropriate time for a given extraction step. Although such an approach is tedious and time consuming, using iron extraction as an example, it is shown here that apart from quantitative data such an approach provides additional information on factors that play an intricate role in metal dynamics in the environment. Single step ascorbate, HCl, oxalate and dithionite extractions were used for targeting specific iron phases from saltmarsh sediments and their response was observed over time in order to calibrate the extraction times for each extractant later to be used in a sequential extraction. For surficial sediments, an extraction time of 24 h, 1 h, 2 h and 3 h was ascertained for ascorbate, HCl, oxalate and dithionite extractions, respectively. Fluctuations in iron concentration in the supernatant over time were ubiquitous. The adsorption-desorption behavior is possibly controlled by the sediment organic matter, formation or consumption of active exchange sites during extraction and the crystallinity of iron mineral phase present in the sediments.

Extracting Lyapunov exponents from the echo dynamics of Bose-Einstein condensates on a lattice

NASA Astrophysics Data System (ADS)

Tarkhov, Andrei E.; Wimberger, Sandro; Fine, Boris V.

2017-08-01

We propose theoretically an experimentally realizable method to demonstrate the Lyapunov instability and to extract the value of the largest Lyapunov exponent for a chaotic many-particle interacting system. The proposal focuses specifically on a lattice of coupled Bose-Einstein condensates in the classical regime describable by the discrete Gross-Pitaevskii equation. We suggest to use imperfect time reversal of the system's dynamics known as the Loschmidt echo, which can be realized experimentally by reversing the sign of the Hamiltonian of the system. The routine involves tracking and then subtracting the noise of virtually any observable quantity before and after the time reversal. We support the theoretical analysis by direct numerical simulations demonstrating that the largest Lyapunov exponent can indeed be extracted from the Loschmidt echo routine. We also discuss possible values of experimental parameters required for implementing this proposal.

Biomechanics of milk extraction during breast-feeding.

PubMed

Elad, David; Kozlovsky, Pavel; Blum, Omry; Laine, Andrew F; Po, Ming Jack; Botzer, Eyal; Dollberg, Shaul; Zelicovich, Mabel; Ben Sira, Liat

2014-04-08

How do infants extract milk during breast-feeding? We have resolved a century-long scientific controversy, whether it is sucking of the milk by subatmospheric pressure or mouthing of the nipple-areola complex to induce a peristaltic-like extraction mechanism. Breast-feeding is a dynamic process, which requires coupling between periodic motions of the infant's jaws, undulation of the tongue, and the breast milk ejection reflex. The physical mechanisms executed by the infant have been intriguing topics. We used an objective and dynamic analysis of ultrasound (US) movie clips acquired during breast-feeding to explore the tongue dynamic characteristics. Then, we developed a new 3D biophysical model of the breast and lactiferous tubes that enables the mimicking of dynamic characteristics observed in US imaging during breast-feeding, and thereby, exploration of the biomechanical aspects of breast-feeding. We have shown, for the first time to our knowledge, that latch-on to draw the nipple-areola complex into the infant mouth, as well as milk extraction during breast-feeding, require development of time-varying subatmospheric pressures within the infant's oral cavity. Analysis of the US movies clearly demonstrated that tongue motility during breast-feeding was fairly periodic. The anterior tongue, which is wedged between the nipple-areola complex and the lower lips, moves as a rigid body with the cycling motion of the mandible, while the posterior section of the tongue undulates in a pattern similar to a propagating peristaltic wave, which is essential for swallowing.

Biomechanics of milk extraction during breast-feeding

PubMed Central

Elad, David; Kozlovsky, Pavel; Blum, Omry; Laine, Andrew F.; Po, Ming Jack; Botzer, Eyal; Dollberg, Shaul; Zelicovich, Mabel; Ben Sira, Liat

2014-01-01

How do infants extract milk during breast-feeding? We have resolved a century-long scientific controversy, whether it is sucking of the milk by subatmospheric pressure or mouthing of the nipple–areola complex to induce a peristaltic-like extraction mechanism. Breast-feeding is a dynamic process, which requires coupling between periodic motions of the infant’s jaws, undulation of the tongue, and the breast milk ejection reflex. The physical mechanisms executed by the infant have been intriguing topics. We used an objective and dynamic analysis of ultrasound (US) movie clips acquired during breast-feeding to explore the tongue dynamic characteristics. Then, we developed a new 3D biophysical model of the breast and lactiferous tubes that enables the mimicking of dynamic characteristics observed in US imaging during breast-feeding, and thereby, exploration of the biomechanical aspects of breast-feeding. We have shown, for the first time to our knowledge, that latch-on to draw the nipple–areola complex into the infant mouth, as well as milk extraction during breast-feeding, require development of time-varying subatmospheric pressures within the infant’s oral cavity. Analysis of the US movies clearly demonstrated that tongue motility during breast-feeding was fairly periodic. The anterior tongue, which is wedged between the nipple–areola complex and the lower lips, moves as a rigid body with the cycling motion of the mandible, while the posterior section of the tongue undulates in a pattern similar to a propagating peristaltic wave, which is essential for swallowing. PMID:24706845

Determination of volatile organic hydrocarbons in water samples by solid-phase dynamic extraction.

PubMed

Jochmann, Maik A; Yuan, Xue; Schmidt, Torsten C

2007-03-01

In the present study a headspace solid-phase dynamic extraction method coupled to gas chromatography-mass spectrometry (HS-SPDE-GC/MS) for the trace determination of volatile halogenated hydrocarbons and benzene from groundwater samples was developed and evaluated. As target compounds, benzene as well as 11 chlorinated and brominated hydrocarbons (vinyl chloride, dichloromethane, cis-1,2-dichloroethylene, trans-1,2-dichloroethylene, carbon tetrachloride, chloroform, trichloroethylene, tetrachloroethylene, bromoform) of environmental and toxicological concern were included in this study. The analytes were extracted using a SPDE needle device, coated with a poly(dimethylsiloxane) with 10% embedded activated carbon phase (50-microm film thickness and 56-mm film length) and were analyzed by GC/MS in full-scan mode. Parameters that affect the extraction yield such as extraction and desorption temperature, salting-out, extraction and desorption flow rate, extraction volume and desorption volume, the number of extraction cycles, and the pre-desorption time have been evaluated and optimized. The linearity of the HS-SPDE-GC/MS method was established over several orders of magnitude. Method detection limits (MDLs) for the compounds investigated ranged between 12 ng/L for cis-dichloroethylene and trans-dichloroethylene and 870 ng/L for vinyl chloride. The method was thoroughly validated, and the precision at two concentration levels (0.1 mg/L and a concentration 5 times above the MDL) was between 3.1 and 16% for the analytes investigated. SPDE provides high sensitivity, short sample preparation and extraction times and a high sample throughput because of full automation. Finally, the applicability to real environmental samples is shown exemplarily for various groundwater samples from a former waste-oil recycling facility. Groundwater from the site showed a complex contamination with chlorinated volatile organic compounds and aromatic hydrocarbons.

Hierarchic spatio-temporal dynamics in glycolysis

NASA Astrophysics Data System (ADS)

Shinjyo, Takahiro; Nakagawa, Yoshiyuki; Ueda, Tetsuo

Yeast extracts exhibit oscillations when the glycolytic system is far away from equilibrium. Spatio-temporal dynamics in this system was studied in the newly developed gel as well as in the solution. Small regions (about 10 um) with very complex shape with high or low concentrations of NADH appeared, and upon these small structures large-scale dynamics were superimposed. Concentration waves propagated, and the source of wave was induced by contact with high ADP. Sink of waves was generated by contacting the reaction gel to two small gels rich in ADP. Upon these spatio-temporal dynamics were superimposed much slower global oscillations throughout the system with a period of about 40 min. Similar dynamics was seen in a solution of yeast extract, but the size of domains was about ten times larger than that in the gel. In this way, the multi-enzyme system of glycolysis exhibits self-organization of hierarchy in spatio-temporal dynamics.

Evaluation of human dynamic balance in Grassmann manifold

NASA Astrophysics Data System (ADS)

Michalczuk, Agnieszka; Wereszczyński, Kamil; Mucha, Romualda; Świtoński, Adam; Josiński, Henryk; Wojciechowski, Konrad

2017-07-01

The authors present an application of Grassmann manifold to the evaluation of human dynamic balance based on the time series representing movements of hip, knee and ankle joints in the sagittal, frontal and transverse planes. Time series were extracted from gait sequences which were recorded in the Human Motion Laboratory (HML) of the Polish-Japanese Academy of Information Technology in Bytom, Poland using the Vicon system.

Validation for Vegetation Green-up Date Extracted from GIMMS NDVI and NDVI3g Using Variety of Methods

NASA Astrophysics Data System (ADS)

Chang, Q.; Jiao, W.

2017-12-01

Phenology is a sensitive and critical feature of vegetation change that has regarded as a good indicator in climate change studies. So far, variety of remote sensing data sources and phenology extraction methods from satellite datasets have been developed to study the spatial-temporal dynamics of vegetation phenology. However, the differences between vegetation phenology results caused by the varies satellite datasets and phenology extraction methods are not clear, and the reliability for different phenology results extracted from remote sensing datasets is not verified and compared using the ground observation data. Based on three most popular remote sensing phenology extraction methods, this research calculated the Start of the growing season (SOS) for each pixels in the Northern Hemisphere for two kinds of long time series satellite datasets: GIMMS NDVIg (SOSg) and GIMMS NDVI3g (SOS3g). The three methods used in this research are: maximum increase method, dynamic threshold method and midpoint method. Then, this study used SOS calculated from NEE datasets (SOS_NEE) monitored by 48 eddy flux tower sites in global flux website to validate the reliability of six phenology results calculated from remote sensing datasets. Results showed that both SOSg and SOS3g extracted by maximum increase method are not correlated with ground observed phenology metrics. SOSg and SOS3g extracted by the dynamic threshold method and midpoint method are both correlated with SOS_NEE significantly. Compared with SOSg extracted by the dynamic threshold method, SOSg extracted by the midpoint method have a stronger correlation with SOS_NEE. And, the same to SOS3g. Additionally, SOSg showed stronger correlation with SOS_NEE than SOS3g extracted by the same method. SOS extracted by the midpoint method from GIMMS NDVIg datasets seemed to be the most reliable results when validated with SOS_NEE. These results can be used as reference for data and method selection in future's phenology study.

When Interpolation-Induced Reflection Artifact Meets Time-Frequency Analysis.

PubMed

Lin, Yu-Ting; Flandrin, Patrick; Wu, Hau-Tieng

2016-10-01

While extracting the temporal dynamical features based on the time-frequency analyses, like the reassignment and synchrosqueezing transform, attracts more and more interest in biomedical data analysis, we should be careful about artifacts generated by interpolation schemes, in particular when the sampling rate is not significantly higher than the frequency of the oscillatory component we are interested in. We formulate the problem called the reflection effect and provide a theoretical justification of the statement. We also show examples in the anesthetic depth analysis with clear but undesirable artifacts. The artifact associated with the reflection effect exists not only theoretically but practically as well. Its influence is pronounced when we apply the time-frequency analyses to extract the time-varying dynamics hidden inside the signal. We have to carefully deal with the artifact associated with the reflection effect by choosing a proper interpolation scheme.

Application of snakes and dynamic programming optimisation technique in modeling of buildings in informal settlement areas

NASA Astrophysics Data System (ADS)

Rüther, Heinz; Martine, Hagai M.; Mtalo, E. G.

This paper presents a novel approach to semiautomatic building extraction in informal settlement areas from aerial photographs. The proposed approach uses a strategy of delineating buildings by optimising their approximate building contour position. Approximate building contours are derived automatically by locating elevation blobs in digital surface models. Building extraction is then effected by means of the snakes algorithm and the dynamic programming optimisation technique. With dynamic programming, the building contour optimisation problem is realized through a discrete multistage process and solved by the "time-delayed" algorithm, as developed in this work. The proposed building extraction approach is a semiautomatic process, with user-controlled operations linking fully automated subprocesses. Inputs into the proposed building extraction system are ortho-images and digital surface models, the latter being generated through image matching techniques. Buildings are modeled as "lumps" or elevation blobs in digital surface models, which are derived by altimetric thresholding of digital surface models. Initial windows for building extraction are provided by projecting the elevation blobs centre points onto an ortho-image. In the next step, approximate building contours are extracted from the ortho-image by region growing constrained by edges. Approximate building contours thus derived are inputs into the dynamic programming optimisation process in which final building contours are established. The proposed system is tested on two study areas: Marconi Beam in Cape Town, South Africa, and Manzese in Dar es Salaam, Tanzania. Sixty percent of buildings in the study areas have been extracted and verified and it is concluded that the proposed approach contributes meaningfully to the extraction of buildings in moderately complex and crowded informal settlement areas.

Quantitative Analysis of Bioactive Compounds from Aromatic Plants by Means of Dynamic Headspace Extraction and Multiple Headspace Extraction-Gas Chromatography-Mass Spectrometry.

PubMed

Omar, Jone; Olivares, Maitane; Alonso, Ibone; Vallejo, Asier; Aizpurua-Olaizola, Oier; Etxebarria, Nestor

2016-04-01

Seven monoterpenes in 4 aromatic plants (sage, cardamom, lavender, and rosemary) were quantified in liquid extracts and directly in solid samples by means of dynamic headspace-gas chromatography-mass spectrometry (DHS-GC-MS) and multiple headspace extraction-gas chromatography-mass spectrometry (MHSE), respectively. The monoterpenes were 1st extracted by means of supercritical fluid extraction (SFE) and analyzed by an optimized DHS-GC-MS. The optimization of the dynamic extraction step and the desorption/cryo-focusing step were tackled independently by experimental design assays. The best working conditions were set at 30 °C for the incubation temperature, 5 min of incubation time, and 40 mL of purge volume for the dynamic extraction step of these bioactive molecules. The conditions of the desorption/cryo-trapping step from the Tenax TA trap were set at follows: the temperature was increased from 30 to 300 °C at 150 °C/min, although the cryo-trapping was maintained at -70 °C. In order to estimate the efficiency of the SFE process, the analysis of monoterpenes in the 4 aromatic plants was directly carried out by means of MHSE because it did not require any sample preparation. Good linearity (r2) > 0.99) and reproducibility (relative standard deviation % <12) was obtained for solid and liquid quantification approaches, in the ranges of 0.5 to 200 ng and 10 to 500 ng/mL, respectively. The developed methods were applied to analyze the concentration of 7 monoterpenes in aromatic plants obtaining concentrations in the range of 2 to 6000 ng/g and 0.25 to 110 μg/mg, respectively. © 2016 Institute of Food Technologists®

Reversal time of jump-noise magnetization dynamics in nanomagnets via Monte Carlo simulations

NASA Astrophysics Data System (ADS)

Parthasarathy, Arun; Rakheja, Shaloo

2018-06-01

The jump-noise is a nonhomogeneous Poisson process which models thermal effects in magnetization dynamics, with special applications in low temperature escape rate phenomena. In this work, we develop improved numerical methods for Monte Carlo simulation of the jump-noise dynamics and validate the method by comparing the stationary distribution obtained empirically against the Boltzmann distribution. In accordance with the Néel-Brown theory, the jump-noise dynamics display an exponential relaxation toward equilibrium with a characteristic reversal time, which we extract for nanomagnets with uniaxial and cubic anisotropy. We relate the jump-noise dynamics to the equivalent Landau-Lifshitz dynamics up to second order correction for a general energy landscape and obtain the analogous Néel-Brown theory's solution of the reversal time. We find that the reversal time of jump-noise dynamics is characterized by Néel-Brown theory's solution at the energy saddle point for small noise. For large noise, the magnetization reversal due to jump-noise dynamics phenomenologically represents macroscopic tunneling of magnetization.

A method of ECG template extraction for biometrics applications.

PubMed

Zhou, Xiang; Lu, Yang; Chen, Meng; Bao, Shu-Di; Miao, Fen

2014-01-01

ECG has attracted widespread attention as one of the most important non-invasive physiological signals in healthcare-system related biometrics for its characteristics like ease-of-monitoring, individual uniqueness as well as important clinical value. This study proposes a method of dynamic threshold setting to extract the most stable ECG waveform as the template for the consequent ECG identification process. With the proposed method, the accuracy of ECG biometrics using the dynamic time wraping for difference measures has been significantly improved. Analysis results with the self-built electrocardiogram database show that the deployment of the proposed method was able to reduce the half total error rate of the ECG biometric system from 3.35% to 1.45%. Its average running time on the platform of android mobile terminal was around 0.06 seconds, and thus demonstrates acceptable real-time performance.

Modelling Nonlinear Dynamic Textures using Hybrid DWT-DCT and Kernel PCA with GPU

NASA Astrophysics Data System (ADS)

Ghadekar, Premanand Pralhad; Chopade, Nilkanth Bhikaji

2016-12-01

Most of the real-world dynamic textures are nonlinear, non-stationary, and irregular. Nonlinear motion also has some repetition of motion, but it exhibits high variation, stochasticity, and randomness. Hybrid DWT-DCT and Kernel Principal Component Analysis (KPCA) with YCbCr/YIQ colour coding using the Dynamic Texture Unit (DTU) approach is proposed to model a nonlinear dynamic texture, which provides better results than state-of-art methods in terms of PSNR, compression ratio, model coefficients, and model size. Dynamic texture is decomposed into DTUs as they help to extract temporal self-similarity. Hybrid DWT-DCT is used to extract spatial redundancy. YCbCr/YIQ colour encoding is performed to capture chromatic correlation. KPCA is applied to capture nonlinear motion. Further, the proposed algorithm is implemented on Graphics Processing Unit (GPU), which comprise of hundreds of small processors to decrease time complexity and to achieve parallelism.

Photoionization of NaK molecule with a double-well potential in femtosecond pump probe pulse laser fields

NASA Astrophysics Data System (ADS)

Yu, Jie; Wang, Sen-Ming; Yuan, Kai-Jun; Cong, Shu-Lin

2006-09-01

The method of time-dependent quantum wave packet dynamics is used to calculate the femtosecond pump-probe photoelectron spectra and study the wave packet dynamic processes of the double-minimum potential state 61Σ+ of NaK in intense laser fields. The evolutions of the wave packet and the photoelectron energy spectra with time and internuclear distance are described in detail. The wave packet dynamic information of the 61Σ+ state can be extracted from the photoelectron energy spectra.

On solitons: the biomolecular nonlinear transmission line models with constant and time variable coefficients

NASA Astrophysics Data System (ADS)

Raza, Nauman; Murtaza, Isma Ghulam; Sial, Sultan; Younis, Muhammad

2018-07-01

The article studies the dynamics of solitons in electrical microtubule ? model, which describes the propagation of waves in nonlinear dynamical system. Microtubules are not only a passive support of a cell but also they have highly dynamic structures involved in cell motility, intracellular transport and signaling. The underlying model has been considered with constant and variable coefficients of time function. The solitary wave ansatz has been applied successfully to extract these solitons. The corresponding integrability criteria, also known as constraint conditions, naturally emerge from the analysis of these models.

Rapid Solid-Liquid Dynamic Extraction (RSLDE): a New Rapid and Greener Method for Extracting Two Steviol Glycosides (Stevioside and Rebaudioside A) from Stevia Leaves.

PubMed

Gallo, Monica; Vitulano, Manuela; Andolfi, Anna; DellaGreca, Marina; Conte, Esterina; Ciaravolo, Martina; Naviglio, Daniele

2017-06-01

Stevioside and rebaudioside A are the main diterpene glycosides present in the leaves of the Stevia rebaudiana plant, which is used in the production of foods and low-calorie beverages. The difficulties associated with their extraction and purification are currently a problem for the food processing industries. The objective of this study was to develop an effective and economically viable method to obtain a high-quality product while trying to overcome the disadvantages derived from the conventional transformation processes. For this reason, extractions were carried out using a conventional maceration (CM) and a cyclically pressurized extraction known as rapid solid-liquid dynamic extraction (RSLDE) by the Naviglio extractor (NE). After only 20 min of extraction using the NE, a quantity of rebaudioside A and stevioside equal to 1197.8 and 413.6 mg/L was obtained, respectively, while for the CM, the optimum time was 90 min. From the results, it can be stated that the extraction process by NE and its subsequent purification developed in this study is a simple, economical, environmentally friendly method for producing steviol glycosides. Therefore, this method constitutes a valid alternative to conventional extraction by reducing the extraction time and the consumption of toxic solvents and favouring the use of the extracted metabolites as food additives and/or nutraceuticals. As an added value and of local interest, the experiment was carried out on stevia leaves from the Benevento area (Italy), where a high content of rebaudioside A was observed, which exhibits a sweet taste compared to stevioside, which has a significant bitter aftertaste.

A data-driven dynamics simulation framework for railway vehicles

NASA Astrophysics Data System (ADS)

Nie, Yinyu; Tang, Zhao; Liu, Fengjia; Chang, Jian; Zhang, Jianjun

2018-03-01

The finite element (FE) method is essential for simulating vehicle dynamics with fine details, especially for train crash simulations. However, factors such as the complexity of meshes and the distortion involved in a large deformation would undermine its calculation efficiency. An alternative method, the multi-body (MB) dynamics simulation provides satisfying time efficiency but limited accuracy when highly nonlinear dynamic process is involved. To maintain the advantages of both methods, this paper proposes a data-driven simulation framework for dynamics simulation of railway vehicles. This framework uses machine learning techniques to extract nonlinear features from training data generated by FE simulations so that specific mesh structures can be formulated by a surrogate element (or surrogate elements) to replace the original mechanical elements, and the dynamics simulation can be implemented by co-simulation with the surrogate element(s) embedded into a MB model. This framework consists of a series of techniques including data collection, feature extraction, training data sampling, surrogate element building, and model evaluation and selection. To verify the feasibility of this framework, we present two case studies, a vertical dynamics simulation and a longitudinal dynamics simulation, based on co-simulation with MATLAB/Simulink and Simpack, and a further comparison with a popular data-driven model (the Kriging model) is provided. The simulation result shows that using the legendre polynomial regression model in building surrogate elements can largely cut down the simulation time without sacrifice in accuracy.

Rapid acquisition of data dense solid-state CPMG NMR spectral sets using multi-dimensional statistical analysis

DOE PAGES

Mason, H. E.; Uribe, E. C.; Shusterman, J. A.

2018-01-01

Tensor-rank decomposition methods have been applied to variable contact time 29 Si{ 1 H} CP/CPMG NMR data sets to extract NMR dynamics information and dramatically decrease conventional NMR acquisition times.

Rapid acquisition of data dense solid-state CPMG NMR spectral sets using multi-dimensional statistical analysis

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

Mason, H. E.; Uribe, E. C.; Shusterman, J. A.

Tensor-rank decomposition methods have been applied to variable contact time 29 Si{ 1 H} CP/CPMG NMR data sets to extract NMR dynamics information and dramatically decrease conventional NMR acquisition times.

Collective Langevin dynamics of conformational motions in proteins

NASA Astrophysics Data System (ADS)

Lange, Oliver F.; Grubmüller, Helmut

2006-06-01

Functionally relevant slow conformational motions of proteins are, at present, in most cases inaccessible to molecular dynamics (MD) simulations. The main reason is that the major part of the computational effort is spend for the accurate description of a huge number of high frequency motions of the protein and the surrounding solvent. The accumulated influence of these fluctuations is crucial for a correct treatment of the conformational dynamics; however, their details can be considered irrelevant for most purposes. To accurately describe long time protein dynamics we here propose a reduced dimension approach, collective Langevin dynamics (CLD), which evolves the dynamics of the system within a small subspace of relevant collective degrees of freedom. The dynamics within the low-dimensional conformational subspace is evolved via a generalized Langevin equation which accounts for memory effects via memory kernels also extracted from short explicit MD simulations. To determine the memory kernel with differing levels of regularization, we propose and evaluate two methods. As a first test, CLD is applied to describe the conformational motion of the peptide neurotensin. A drastic dimension reduction is achieved by considering one single curved conformational coordinate. CLD yielded accurate thermodynamical and dynamical behaviors. In particular, the rate of transitions between two conformational states agreed well with a rate obtained from a 150ns reference molecular dynamics simulation, despite the fact that the time scale of the transition (˜50ns) was much longer than the 1ns molecular dynamics simulation from which the memory kernel was extracted.

Temporal dynamics of 2D motion integration for ocular following in macaque monkeys.

PubMed

Barthélemy, Fréderic V; Fleuriet, Jérome; Masson, Guillaume S

2010-03-01

Several recent studies have shown that extracting pattern motion direction is a dynamical process where edge motion is first extracted and pattern-related information is encoded with a small time lag by MT neurons. A similar dynamics was found for human reflexive or voluntary tracking. Here, we bring an essential, but still missing, piece of information by documenting macaque ocular following responses to gratings, unikinetic plaids, and barber-poles. We found that ocular tracking was always initiated first in the grating motion direction with ultra-short latencies (approximately 55 ms). A second component was driven only 10-15 ms later, rotating tracking toward pattern motion direction. At the end the open-loop period, tracking direction was aligned with pattern motion direction (plaids) or the average of the line-ending motion directions (barber-poles). We characterized the dependency on contrast of each component. Both timing and direction of ocular following were quantitatively very consistent with the dynamics of neuronal responses reported by others. Overall, we found a remarkable consistency between neuronal dynamics and monkey behavior, advocating for a direct link between the neuronal solution of the aperture problem and primate perception and action.

Interdisciplinary Modeling and Dynamics of Archipelago Straits

DTIC Science & Technology

2009-01-01

modeling, tidal modeling and multi-dynamics nested domains and non-hydrostatic modeling WORK COMPLETED Realistic Multiscale Simulations, Real-time...six state variables (chlorophyll, nitrate , ammonium, detritus, phytoplankton, and zooplankton) were needed to initialize simulations. Using biological...parameters from literature, climatology from World Ocean Atlas data for nitrate and chlorophyll profiles extracted from satellite data, a first

Comparison between 2 methods of solid-liquid extraction for the production of Cinchona calisaya elixir: an experimental kinetics and numerical modeling approach.

PubMed

Naviglio, Daniele; Formato, Andrea; Gallo, Monica

2014-09-01

The purpose of this study is to compare the extraction process for the production of China elixir starting from the same vegetable mixture, as performed by conventional maceration or a cyclically pressurized extraction process (rapid solid-liquid dynamic extraction) using the Naviglio Extractor. Dry residue was used as a marker for the kinetics of the extraction process because it was proportional to the amount of active principles extracted and, therefore, to their total concentration in the solution. UV spectra of the hydroalcoholic extracts allowed for the identification of the predominant chemical species in the extracts, while the organoleptic tests carried out on the final product provided an indication of the acceptance of the beverage and highlighted features that were not detectable by instrumental analytical techniques. In addition, a numerical simulation of the process has been performed, obtaining useful information about the timing of the process (time history) as well as its mathematical description. © 2014 Institute of Food Technologists®

Dynamic cardiac PET imaging: extraction of time-activity curves using ICA and a generalized Gaussian distribution model.

PubMed

Mabrouk, Rostom; Dubeau, François; Bentabet, Layachi

2013-01-01

Kinetic modeling of metabolic and physiologic cardiac processes in small animals requires an input function (IF) and a tissue time-activity curves (TACs). In this paper, we present a mathematical method based on independent component analysis (ICA) to extract the IF and the myocardium's TACs directly from dynamic positron emission tomography (PET) images. The method assumes a super-Gaussian distribution model for the blood activity, and a sub-Gaussian distribution model for the tissue activity. Our appreach was applied on 22 PET measurement sets of small animals, which were obtained from the three most frequently used cardiac radiotracers, namely: desoxy-fluoro-glucose ((18)F-FDG), [(13)N]-ammonia, and [(11)C]-acetate. Our study was extended to PET human measurements obtained with the Rubidium-82 ((82) Rb) radiotracer. The resolved mathematical IF values compare favorably to those derived from curves extracted from regions of interest (ROI), suggesting that the procedure presents a reliable alternative to serial blood sampling for small-animal cardiac PET studies.

Analysis of potential dynamic concealed factors in the difficulty of lower third molar extraction.

PubMed

Singh, P; Ajmera, D-H; Xiao, S-S; Yang, X-Z; Liu, X; Peng, B

2016-11-01

The purpose of this study was to identify potential concealed variables associated with the difficulty of lower third molar (M3) extractions. To address the research purpose, we implemented a prospective study and enrolled a sample of subjects presenting for M3 removal. Predictor variables were categorized into Group-I and Group-II, based on predetermined criteria. The primary outcome variable was the difficulty of extraction, measured as extraction time. Appropriate univariate and multivariate statistics were computed using ordinal logistic regression. The sample comprised of 1235 subjects with a mean age of 29.49 +/- 8.92 years in Group-I and 26.20 +/- 11.55 years in Group-II subjects. The mean operating time per M3 extraction was 21.24 +/- 12.80 and 20.24 +/- 12.50 minutes for Group-I and Group-II subjects respectively. Three linear parameters including B-M2 height (distance between imaginary point B on the inferior border of mandibular body, and M2), lingual cortical thickness, bone density and one angular parameter including Rc-Cs angle (angle between ramus curvature and curve of spee), in addition to patient's age, profile type, facial type, cant of occlusal plane, and decreased overbite, were found to be statistically associated ( p < or = 0.05) with extraction difficulty under regression models. In conclusion, our study indicates that the difficulty of lower M3 extractions is possibly governed by morphological and biomechanical factors with substantial influence of myofunctional factors. Preoperative evaluation of dynamic concealed factors may not only help in envisaging the difficulty and planning of surgical approach but might also help in better time management in clinical practice.

The community dynamics of major bioleaching microorganisms during chalcopyrite leaching under the effect of organics.

PubMed

Li, Qihou; Tian, Ye; Fu, Xian; Yin, Huaqun; Zhou, Zhijun; Liang, Yiting; Qiu, Guanzhou; Liu, Jie; Liu, Hongwei; Liang, Yili; Shen, Li; Cong, Jing; Liu, Xueduan

2011-08-01

To determine the effect of organics (yeast extract) on microbial community during chalcopyrite bioleaching at different temperature, real-time polymerase chain reaction (PCR) was employed to analyze community dynamics of major bacteria applied in bioleaching. The results showed that yeast extract exerted great impact on microbial community, and therefore influencing bioleaching rate. To be specific, yeast extract was adverse to this bioleaching process at 30°C due to decreased proportion of important chemolithotrophs such as Acidithiobacillus ferrooxidans and Acidithiobacillus thiooxidans. However, yeast extract could promote bioleaching rate at 40°C on account of the increased number and enhanced work of Ferroplasma thermophilum, a kind of facultative bacteria. Similarly, bioleaching rate was enhanced under the effect of yeast extract at 50°C owing to the work of Acidianus brierleyi. At 60°C, bioleaching rate was close to 100% and temperature was the dominant factor determining bioleaching rate. Interestingly, the existence of yeast extract greatly enhanced the relative competitiveness of Ferroplasma thermophilum in this complex bioleaching microbial community.

Extracting cardiac shapes and motion of the chick embryo heart outflow tract from four-dimensional optical coherence tomography images

NASA Astrophysics Data System (ADS)

Yin, Xin; Liu, Aiping; Thornburg, Kent L.; Wang, Ruikang K.; Rugonyi, Sandra

2012-09-01

Recent advances in optical coherence tomography (OCT), and the development of image reconstruction algorithms, enabled four-dimensional (4-D) (three-dimensional imaging over time) imaging of the embryonic heart. To further analyze and quantify the dynamics of cardiac beating, segmentation procedures that can extract the shape of the heart and its motion are needed. Most previous studies analyzed cardiac image sequences using manually extracted shapes and measurements. However, this is time consuming and subject to inter-operator variability. Automated or semi-automated analyses of 4-D cardiac OCT images, although very desirable, are also extremely challenging. This work proposes a robust algorithm to semi automatically detect and track cardiac tissue layers from 4-D OCT images of early (tubular) embryonic hearts. Our algorithm uses a two-dimensional (2-D) deformable double-line model (DLM) to detect target cardiac tissues. The detection algorithm uses a maximum-likelihood estimator and was successfully applied to 4-D in vivo OCT images of the heart outflow tract of day three chicken embryos. The extracted shapes captured the dynamics of the chick embryonic heart outflow tract wall, enabling further analysis of cardiac motion.

Neutron star dynamics under time-dependent external torques

NASA Astrophysics Data System (ADS)

Gügercinoǧlu, Erbil; Alpar, M. Ali

2017-11-01

The two-component model describes neutron star dynamics incorporating the response of the superfluid interior. Conventional solutions and applications involve constant external torques, as appropriate for radio pulsars on dynamical time-scales. We present the general solution of two-component dynamics under arbitrary time-dependent external torques, with internal torques that are linear in the rotation rates, or with the extremely non-linear internal torques due to vortex creep. The two-component model incorporating the response of linear or non-linear internal torques can now be applied not only to radio pulsars but also to magnetars and to neutron stars in binary systems, with strong observed variability and noise in the spin-down or spin-up rates. Our results allow the extraction of the time-dependent external torques from the observed spin-down (or spin-up) time series, \\dot{Ω }(t). Applications are discussed.

The dynamics of discrete-time computation, with application to recurrent neural networks and finite state machine extraction.

PubMed

Casey, M

1996-08-15

Recurrent neural networks (RNNs) can learn to perform finite state computations. It is shown that an RNN performing a finite state computation must organize its state space to mimic the states in the minimal deterministic finite state machine that can perform that computation, and a precise description of the attractor structure of such systems is given. This knowledge effectively predicts activation space dynamics, which allows one to understand RNN computation dynamics in spite of complexity in activation dynamics. This theory provides a theoretical framework for understanding finite state machine (FSM) extraction techniques and can be used to improve training methods for RNNs performing FSM computations. This provides an example of a successful approach to understanding a general class of complex systems that has not been explicitly designed, e.g., systems that have evolved or learned their internal structure.

4D motion modeling of the coronary arteries from CT images for robotic assisted minimally invasive surgery

NASA Astrophysics Data System (ADS)

Zhang, Dong Ping; Edwards, Eddie; Mei, Lin; Rueckert, Daniel

2009-02-01

In this paper, we present a novel approach for coronary artery motion modeling from cardiac Computed Tomography( CT) images. The aim of this work is to develop a 4D motion model of the coronaries for image guidance in robotic-assisted totally endoscopic coronary artery bypass (TECAB) surgery. To utilize the pre-operative cardiac images to guide the minimally invasive surgery, it is essential to have a 4D cardiac motion model to be registered with the stereo endoscopic images acquired intraoperatively using the da Vinci robotic system. In this paper, we are investigating the extraction of the coronary arteries and the modelling of their motion from a dynamic sequence of cardiac CT. We use a multi-scale vesselness filter to enhance vessels in the cardiac CT images. The centerlines of the arteries are extracted using a ridge traversal algorithm. Using this method the coronaries can be extracted in near real-time as only local information is used in vessel tracking. To compute the deformation of the coronaries due to cardiac motion, the motion is extracted from a dynamic sequence of cardiac CT. Each timeframe in this sequence is registered to the end-diastole timeframe of the sequence using a non-rigid registration algorithm based on free-form deformations. Once the images have been registered a dynamic motion model of the coronaries can be obtained by applying the computed free-form deformations to the extracted coronary arteries. To validate the accuracy of the motion model we compare the actual position of the coronaries in each time frame with the predicted position of the coronaries as estimated from the non-rigid registration. We expect that this motion model of coronaries can facilitate the planning of TECAB surgery, and through the registration with real-time endoscopic video images it can reduce the conversion rate from TECAB to conventional procedures.

Ares I-X In-Flight Modal Identification

NASA Technical Reports Server (NTRS)

Bartkowicz, Theodore J.; James, George H., III

2011-01-01

Operational modal analysis is a procedure that allows the extraction of modal parameters of a structure in its operating environment. It is based on the idealized premise that input to the structure is white noise. In some cases, when free decay responses are corrupted by unmeasured random disturbances, the response data can be processed into cross-correlation functions that approximate free decay responses. Modal parameters can be computed from these functions by time domain identification methods such as the Eigenvalue Realization Algorithm (ERA). The extracted modal parameters have the same characteristics as impulse response functions of the original system. Operational modal analysis is performed on Ares I-X in-flight data. Since the dynamic system is not stationary due to propellant mass loss, modal identification is only possible by analyzing the system as a series of linearized models over short periods of time via a sliding time-window of short time intervals. A time-domain zooming technique was also employed to enhance the modal parameter extraction. Results of this study demonstrate that free-decay time domain modal identification methods can be successfully employed for in-flight launch vehicle modal extraction.

Coherent fifth-order visible-infrared spectroscopies: ultrafast nonequilibrium vibrational dynamics in solution.

PubMed

Lynch, Michael S; Slenkamp, Karla M; Cheng, Mark; Khalil, Munira

2012-07-05

Obtaining a detailed description of photochemical reactions in solution requires measuring time-evolving structural dynamics of transient chemical species on ultrafast time scales. Time-resolved vibrational spectroscopies are sensitive probes of molecular structure and dynamics in solution. In this work, we develop doubly resonant fifth-order nonlinear visible-infrared spectroscopies to probe nonequilibrium vibrational dynamics among coupled high-frequency vibrations during an ultrafast charge transfer process using a heterodyne detection scheme. The method enables the simultaneous collection of third- and fifth-order signals, which respectively measure vibrational dynamics occurring on electronic ground and excited states on a femtosecond time scale. Our data collection and analysis strategy allows transient dispersed vibrational echo (t-DVE) and dispersed pump-probe (t-DPP) spectra to be extracted as a function of electronic and vibrational population periods with high signal-to-noise ratio (S/N > 25). We discuss how fifth-order experiments can measure (i) time-dependent anharmonic vibrational couplings, (ii) nonequilibrium frequency-frequency correlation functions, (iii) incoherent and coherent vibrational relaxation and transfer dynamics, and (iv) coherent vibrational and electronic (vibronic) coupling as a function of a photochemical reaction.

Identification of degradation products in loxoprofen sodium adhesive tapes by liquid chromatography-mass spectrometry and dynamic pressurized liquid extraction-solid-phase extraction coupled to liquid chromatography-nuclear magnetic resonance spectroscopy.

PubMed

Murakami, Tomonori; Kawasaki, Takao; Takemura, Akira; Fukutsu, Naoto; Kishi, Naoyuki; Kusu, Fumiyo

2008-10-24

Rapid and unambiguous identification of three degradation products (DP-1, DP-2 and DP-3) found in heat-stressed loxoprofen sodium adhesive tapes (Loxonin tapes) was achieved by LC-MS and dynamic pressurized liquid extraction (PLE)-solid-phase extraction (SPE) coupled to LC-NMR without complicated isolation or purification processes. The molecular formulae of the degradation products were determined by accurate mass measurements and product ion analyses and on-line hydrogen/deuterium (H/D) exchange experiments provided information about changes in the degradation of loxoprofen. To compensate for the low sensitivity of NMR, on-line dynamic PLE-SPE was employed and higher concentrations of degradation products trapped on the SPE column were afforded in a shorter time than they would be in such time-consuming sample preparations as pre-concentration after extraction. The loop-storage procedure was used in the LC-NMR analysis to allow the acquisition of the (1)H spectra of the three degradation products in one chromatographic run without affecting the peak separation and to avoid the carry-over of previously eluted DP-1 of high concentration by washing the NMR detection cell prior to the measurement of the DP-2 spectrum. Based on the resulting (1)H NMR spectra in combination with the MS results, DP-1 was successfully identified as an oxidation product having an oxodicarboxylic acid structure formed by the cleavage of the cyclopentanone ring of loxoprofen, DP-2 as a cyclopentanone ring-hydroxylated loxoprofen and DP-3 as a loxoprofen l-menthol ester.

Optimization of supercritical carbon dioxide extraction of essential oil from Dracocephalum kotschyi Boiss: An endangered medicinal plant in Iran.

PubMed

Nejad-Sadeghi, Masoud; Taji, Saeed; Goodarznia, Iraj

2015-11-27

Extraction of the essential oil from a medicinal plant called Dracocephalum kotschyi Boiss was performed by green technology of supercritical carbon dioxide (SC-CO2) extraction. A Taguchi orthogonal array design with an OA16 (4(5)) matrix was used to evaluate the effects of five extraction variables: pressure of 150-310bar, temperature of 40-60°C, average particle size of 250-1000μm, CO2 flow rate of 2-10ml/s and dynamic extraction time of 30-100min. The optimal conditions to obtain the maximum extraction yield were at 240bar, 60°C, 500μm, 10ml/s and 100min. The extraction yield under the above conditions was 2.72% (w/w) which is more than two times the maximum extraction yield that has been reported for this plant in the literature using traditional extraction techniques. Results from analysis of variance (ANOVA) indicated that the CO2 flow rate and the extraction time were the most significant factors on the extraction yield by percentage contribution of 44.27 and 28.86, respectively. Finally, the chemical composition of the essential oil was evaluated by using gas chromatography-mass spectroscopy (GC-MS). Citral, p-mentha-1,3,8-triene, D-3-carene and methyl geranate were the major components identified. Copyright © 2015. Published by Elsevier B.V.

Automated smoother for the numerical decoupling of dynamics models.

PubMed

Vilela, Marco; Borges, Carlos C H; Vinga, Susana; Vasconcelos, Ana Tereza R; Santos, Helena; Voit, Eberhard O; Almeida, Jonas S

2007-08-21

Structure identification of dynamic models for complex biological systems is the cornerstone of their reverse engineering. Biochemical Systems Theory (BST) offers a particularly convenient solution because its parameters are kinetic-order coefficients which directly identify the topology of the underlying network of processes. We have previously proposed a numerical decoupling procedure that allows the identification of multivariate dynamic models of complex biological processes. While described here within the context of BST, this procedure has a general applicability to signal extraction. Our original implementation relied on artificial neural networks (ANN), which caused slight, undesirable bias during the smoothing of the time courses. As an alternative, we propose here an adaptation of the Whittaker's smoother and demonstrate its role within a robust, fully automated structure identification procedure. In this report we propose a robust, fully automated solution for signal extraction from time series, which is the prerequisite for the efficient reverse engineering of biological systems models. The Whittaker's smoother is reformulated within the context of information theory and extended by the development of adaptive signal segmentation to account for heterogeneous noise structures. The resulting procedure can be used on arbitrary time series with a nonstationary noise process; it is illustrated here with metabolic profiles obtained from in-vivo NMR experiments. The smoothed solution that is free of parametric bias permits differentiation, which is crucial for the numerical decoupling of systems of differential equations. The method is applicable in signal extraction from time series with nonstationary noise structure and can be applied in the numerical decoupling of system of differential equations into algebraic equations, and thus constitutes a rather general tool for the reverse engineering of mechanistic model descriptions from multivariate experimental time series.

Automatic flow-through dynamic extraction: A fast tool to evaluate char-based remediation of multi-element contaminated mine soils.

PubMed

Rosende, María; Beesley, Luke; Moreno-Jimenez, Eduardo; Miró, Manuel

2016-02-01

An automatic in-vitro bioaccessibility test based upon dynamic microcolumn extraction in a programmable flow setup is herein proposed as a screening tool to evaluate bio-char based remediation of mine soils contaminated with trace elements as a compelling alternative to conventional phyto-availability tests. The feasibility of the proposed system was evaluated by extracting the readily bioaccessible pools of As, Pb and Zn in two contaminated mine soils before and after the addition of two biochars (9% (w:w)) of diverse source origin (pine and olive). Bioaccessible fractions under worst-case scenarios were measured using 0.001 mol L(-1) CaCl2 as extractant for mimicking plant uptake, and analysis of the extracts by inductively coupled optical emission spectrometry. The t-test of comparison of means revealed an efficient metal (mostly Pb and Zn) immobilization by the action of olive pruning-based biochar against the bare (control) soil at the 0.05 significance level. In-vitro flow-through bioaccessibility tests are compared for the first time with in-vivo phyto-toxicity assays in a microcosm soil study. By assessing seed germination and shoot elongation of Lolium perenne in contaminated soils with and without biochar amendments the dynamic flow-based bioaccessibility data proved to be in good agreement with the phyto-availability tests. Experimental results indicate that the dynamic extraction method is a viable and economical in-vitro tool in risk assessment explorations to evaluate the feasibility of a given biochar amendment for revegetation and remediation of metal contaminated soils in a mere 10 min against 4 days in case of phyto-toxicity assays. Copyright © 2015 Elsevier B.V. All rights reserved.

Automated dynamic hollow fiber liquid-liquid-liquid microextraction combined with capillary electrophoresis for speciation of mercury in biological and environmental samples.

PubMed

Li, Pingjing; He, Man; Chen, Beibei; Hu, Bin

2015-10-09

A simple home-made automatic dynamic hollow fiber based liquid-liquid-liquid microextraction (AD-HF-LLLME) device was designed and constructed for the simultaneous extraction of organomercury and inorganic mercury species with the assistant of a programmable flow injection analyzer. With 18-crown-6 as the complexing reagent, mercury species including methyl-, ethyl-, phenyl- and inorganic mercury were extracted into the organic phase (chlorobenzene), and then back-extracted into the acceptor phase of 0.1% (m/v) 3-mercapto-1-propanesulfonic acid (MPS) aqueous solution. Compared with automatic static (AS)-HF-LLLME system, the extraction equilibrium of target mercury species was obtained in shorter time with higher extraction efficiency in AD-HF-LLLME system. Based on it, a new method of AD-HF-LLLME coupled with large volume sample stacking (LVSS)-capillary electrophoresis (CE)/UV detection was developed for the simultaneous analysis of methyl-, phenyl- and inorganic mercury species in biological samples and environmental water. Under the optimized conditions, AD-HF-LLLME provided high enrichment factors (EFs) of 149-253-fold within relatively short extraction equilibrium time (25min) and good precision with RSD between 3.8 and 8.1%. By combining AD-HF-LLLME with LVSS-CE/UV, EFs were magnified up to 2195-fold and the limits of detection (at S/N=3) for target mercury species were improved to be sub ppb level. Copyright © 2015 Elsevier B.V. All rights reserved.

Studying Climate Response to Forcing by the Nonlinear Dynamical Mode Decomposition

NASA Astrophysics Data System (ADS)

Mukhin, Dmitry; Gavrilov, Andrey; Loskutov, Evgeny; Feigin, Alexander

2017-04-01

An analysis of global climate response to external forcing, both anthropogenic (mainly, CO2 and aerosol) and natural (solar and volcanic), is needed for adequate predictions of global climate change. Being complex dynamical system, the climate reacts to external perturbations exciting feedbacks (both positive and negative) making the response non-trivial and poorly predictable. Thus an extraction of internal modes of climate system, investigation of their interaction with external forcings and further modeling and forecast of their dynamics, are all the problems providing the success of climate modeling. In the report the new method for principal mode extraction from climate data is presented. The method is based on the Nonlinear Dynamical Mode (NDM) expansion [1,2], but takes into account a number of external forcings applied to the system. Each NDM is represented by hidden time series governing the observed variability, which, together with external forcing time series, are mapped onto data space. While forcing time series are considered to be known, the hidden unknown signals underlying the internal climate dynamics are extracted from observed data by the suggested method. In particular, it gives us an opportunity to study the evolution of principal system's mode structure in changing external conditions and separate the internal climate variability from trends forced by external perturbations. Furthermore, the modes so obtained can be extrapolated beyond the observational time series, and long-term prognosis of modes' structure including characteristics of interconnections and responses to external perturbations, can be carried out. In this work the method is used for reconstructing and studying the principal modes of climate variability on inter-annual and decadal time scales accounting the external forcings such as anthropogenic emissions, variations of the solar activity and volcanic activity. The structure of the obtained modes as well as their response to external factors, e.g. forecast their change in 21 century under different CO2 emission scenarios, are discussed. [1] Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510. http://doi.org/10.1038/srep15510 [2] Gavrilov, A., Mukhin, D., Loskutov, E., Volodin, E., Feigin, A., & Kurths, J. (2016). Method for reconstructing nonlinear modes with adaptive structure from multidimensional data. Chaos: An Interdisciplinary Journal of Nonlinear Science, 26(12), 123101. http://doi.org/10.1063/1.4968852

Transition from lognormal to χ2-superstatistics for financial time series

NASA Astrophysics Data System (ADS)

Xu, Dan; Beck, Christian

2016-07-01

Share price returns on different time scales can be well modelled by a superstatistical dynamics. Here we provide an investigation which type of superstatistics is most suitable to properly describe share price dynamics on various time scales. It is shown that while χ2-superstatistics works well on a time scale of days, on a much smaller time scale of minutes the price changes are better described by lognormal superstatistics. The system dynamics thus exhibits a transition from lognormal to χ2 superstatistics as a function of time scale. We discuss a more general model interpolating between both statistics which fits the observed data very well. We also present results on correlation functions of the extracted superstatistical volatility parameter, which exhibits exponential decay for returns on large time scales, whereas for returns on small time scales there are long-range correlations and power-law decay.

Effects of pyrite and sphalerite on population compositions, dynamics and copper extraction efficiency in chalcopyrite bioleaching process.

PubMed

Xiao, Yunhua; Liu, Xueduan; Dong, Weiling; Liang, Yili; Niu, Jiaojiao; Gu, Yabing; Ma, Liyuan; Hao, Xiaodong; Zhang, Xian; Xu, Zhen; Yin, Huaqun

2017-07-01

This study used an artificial microbial community with four known moderately thermophilic acidophiles (three bacteria including Acidithiobacillus caldus S1, Sulfobacillus thermosulfidooxidans ST and Leptospirillum ferriphilum YSK, and one archaea, Ferroplasma thermophilum L1) to explore the variation of microbial community structure, composition, dynamics and function (e.g., copper extraction efficiency) in chalcopyrite bioleaching (C) systems with additions of pyrite (CP) or sphalerite (CS). The community compositions and dynamics in the solution and on the ore surface were investigated by real-time quantitative PCR (qPCR). The results showed that the addition of pyrite or sphalerite changed the microbial community composition and dynamics dramatically during the chalcopyrite bioleaching process. For example, A. caldus (above 60%) was the dominant species at the initial stage in three groups, and at the middle stage, still dominated C group (above 70%), but it was replaced by L. ferriphilum (above 60%) in CP and CS groups; at the final stage, L. ferriphilum dominated C group, while F. thermophilum dominated CP group on the ore surface. Furthermore, the additions of pyrite or sphalerite both made the increase of redox potential (ORP) and the concentrations of Fe 3+ and H + , which would affect the microbial community compositions and copper extraction efficiency. Additionally, pyrite could enhance copper extraction efficiency (e.g., improving around 13.2% on day 6) during chalcopyrite bioleaching; on the contrary, sphalerite restrained it.

Towards DMD-Based Estimation and Control of Flow Separation using an Array of Surface Pressure Sensors

NASA Astrophysics Data System (ADS)

Deem, Eric; Cattafesta, Louis; Zhang, Hao; Rowley, Clancy

2016-11-01

Closed-loop control of flow separation requires the spatio-temporal states of the flow to be fed back through the controller in real time. Previously, static and dynamic estimation methods have been employed that provide reduced-order model estimates of the POD-coefficients of the flow velocity using surface pressure measurements. However, this requires a "learning" dataset a priori. This approach is effective as long as the dynamics during control do not stray from the learning dataset. Since only a few dynamical features are required for feedback control of flow separation, many of the details provided by full-field snapshots are superfluous. This motivates a state-observation technique that extracts key dynamical features directly from surface pressure, without requiring PIV snapshots. The results of identifying DMD modes of separated flow through an array of surface pressure sensors in real-time are presented. This is accomplished by employing streaming DMD "on the fly" to surface pressure snapshots. These modal characteristics exhibit striking similarities to those extracted from PIV data and the pressure field obtained via solving Poisson's equation. Progress towards closed-loop separation control based on the dynamic modes of surface pressure will be discussed. Supported by AFOSR Grant FA9550-14-1-0289.

Network structure of multivariate time series.

PubMed

Lacasa, Lucas; Nicosia, Vincenzo; Latora, Vito

2015-10-21

Our understanding of a variety of phenomena in physics, biology and economics crucially depends on the analysis of multivariate time series. While a wide range tools and techniques for time series analysis already exist, the increasing availability of massive data structures calls for new approaches for multidimensional signal processing. We present here a non-parametric method to analyse multivariate time series, based on the mapping of a multidimensional time series into a multilayer network, which allows to extract information on a high dimensional dynamical system through the analysis of the structure of the associated multiplex network. The method is simple to implement, general, scalable, does not require ad hoc phase space partitioning, and is thus suitable for the analysis of large, heterogeneous and non-stationary time series. We show that simple structural descriptors of the associated multiplex networks allow to extract and quantify nontrivial properties of coupled chaotic maps, including the transition between different dynamical phases and the onset of various types of synchronization. As a concrete example we then study financial time series, showing that a multiplex network analysis can efficiently discriminate crises from periods of financial stability, where standard methods based on time-series symbolization often fail.

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

Phillips, Carolyn L.; Guo, Hanqi; Peterka, Tom

In type-II superconductors, the dynamics of magnetic flux vortices determine their transport properties. In the Ginzburg-Landau theory, vortices correspond to topological defects in the complex order parameter field. Earlier, in Phillips et al. [Phys. Rev. E 91, 023311 (2015)], we introduced a method for extracting vortices from the discretized complex order parameter field generated by a large-scale simulation of vortex matter. With this method, at a fixed time step, each vortex [simplistically, a one-dimensional (1D) curve in 3D space] can be represented as a connected graph extracted from the discretized field. Here we extend this method as a function ofmore » time as well. A vortex now corresponds to a 2D space-time sheet embedded in 4D space time that can be represented as a connected graph extracted from the discretized field over both space and time. Vortices that interact by merging or splitting correspond to disappearance and appearance of holes in the connected graph in the time direction. This method of tracking vortices, which makes no assumptions about the scale or behavior of the vortices, can track the vortices with a resolution as good as the discretization of the temporally evolving complex scalar field. Additionally, even details of the trajectory between time steps can be reconstructed from the connected graph. With this form of vortex tracking, the details of vortex dynamics in a model of a superconducting materials can be understood in greater detail than previously possible.« less

Determination of volatile organic compounds in pen inks by a dynamic headspace needle trap device combined with gas chromatography-mass spectrometry.

PubMed

Zang, Xiaohuan; Liang, Weiqian; Chang, Qingyun; Wu, Tong; Wang, Chun; Wang, Zhi

2017-09-01

Some harmful volatile organic compounds (VOCs), such as methylbenzene, ethylbenzene, xylene, chlorobenzene and bromobenzene, are the commonly found chemicals in pen inks. In this work, a dynamic headspace needle-trap device (D-HS-NTD) with a ZIF-8-derived nanoporous carbon (ZIF-8-NPC) as the adsorbent was developed for the extraction of some VOCs in different pen inks prior to GC-MS detection. The main important influencing experimental parameters including the flow rate of the purge gas N 2 , extraction temperature, extraction time, desorption temperature and desorption time for the extraction were optimized to obtain a high extraction efficiency. Under the optimized conditions, a good linearity was obtained in the concentration range of 0.1-400μgkg -1 with the correlation coefficients (r) ranging from 0.9911 to 0.9990 for the eleven VOCs. The LODs at a signal-to-noise ratio of 3 (S/N=3) were measured to be 10-20ngkg -1 for the VOCs. The developed method was applied to determine the VOCs from 20 pen inks. The recoveries of the VOCs for the method at the spiking levels of 0.5 and 20.0μgkg -1 fell in the range from 80.0% to 108%. Copyright © 2017. Published by Elsevier B.V.

Molecular dynamics in principal component space.

PubMed

Michielssens, Servaas; van Erp, Titus S; Kutzner, Carsten; Ceulemans, Arnout; de Groot, Bert L

2012-07-26

A molecular dynamics algorithm in principal component space is presented. It is demonstrated that sampling can be improved without changing the ensemble by assigning masses to the principal components proportional to the inverse square root of the eigenvalues. The setup of the simulation requires no prior knowledge of the system; a short initial MD simulation to extract the eigenvectors and eigenvalues suffices. Independent measures indicated a 6-7 times faster sampling compared to a regular molecular dynamics simulation.

Using Time Evolution of the Bunch Structure to Extract the Muon Momentum Distribution in the Fermilab Muon g-2 Experiment

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

Wu, W.; Quinn, B.; Crnkovic, J. D.

Beam dynamics plays an important role in achieving the unprecedented precision on measurement of the muon anomalous magnetic moment in the Fermilab Muon g-2 Experiment. It needs to find the muon momentum distribution in the storage ring in order to evaluate the electric field correction to muon anomalous precession frequency. We will show how to use time evolution of the beam bunch structure to extract the muon momentum distribution by applying a fast rotation analysis on the decay electron signals.

From fuzzy recurrence plots to scalable recurrence networks of time series

NASA Astrophysics Data System (ADS)

Pham, Tuan D.

2017-04-01

Recurrence networks, which are derived from recurrence plots of nonlinear time series, enable the extraction of hidden features of complex dynamical systems. Because fuzzy recurrence plots are represented as grayscale images, this paper presents a variety of texture features that can be extracted from fuzzy recurrence plots. Based on the notion of fuzzy recurrence plots, defuzzified, undirected, and unweighted recurrence networks are introduced. Network measures can be computed for defuzzified recurrence networks that are scalable to meet the demand for the network-based analysis of big data.

[Study on the dynamic model with supercritical CO2 fluid extracting the lipophilic components in Panax notoginseng].

PubMed

Duan, Xian-Chun; Wang, Yong-Zhong; Zhang, Jun-Ru; Luo, Huan; Zhang, Heng; Xia, Lun-Zhu

2011-08-01

To establish a dynamics model for extracting the lipophilic components in Panax notoginseng with supercritical carbon dioxide (CO2). Based on the theory of counter-flow mass transfer and the molecular mass transfer between the material and the supercritical CO2 fluid under differential mass-conservation equation, a dynamics model was established and computed to compare forecasting result with the experiment process. A dynamics model has been established for supercritical CO2 to extract the lipophilic components in Panax notoginseng, the computed result of this model was consistent with the experiment process basically. The supercritical fluid extract dynamics model established in this research can expound the mechanism in the extract process of which lipophilic components of Panax notoginseng dissolve the mass transfer and is tallied with the actual extract process. This provides certain instruction for the supercritical CO2 fluid extract' s industrialization enlargement.

Optimization of Process Parameters and Kinetic Model of Enzymatic Extraction of Polyphenols from Lonicerae Flos

PubMed Central

Kong, Fansheng; Yu, Shujuan; Bi, Yongguang; Huang, Xiaojun; Huang, Mengqian

2016-01-01

Objective: To optimize and verify the cellulase extraction of polyphenols from honeysuckle and provide a reference for enzymatic extracting polyphenols from honeysuckle. Materials and Methods: The uniform design was used According to Fick's first law and kinetic model, fitting analysis of the dynamic process of enzymatic extracting polyphenols was conducted. Results: The optimum enzymatic extraction parameters for polyphenols from honeysuckle are found to be 80% (v/v) of alcohol, 35:1 (mL/g) of liquid-solid ratio, 80°C of extraction temperature, 8.5 of pH, 6.0 mg of enzyme levels, and 130 min of extraction time. Under the optimal conditions, the extraction rate of polyphenols was 3.03%. The kinetic experiments indicated kinetic equation had a good linear relationship with t even under the conditions of different levels of enzyme and temperature, which means fitting curve tallies well with the experimental values. Conclusion: The results of quantification showed that the results provide a reference for enzymatic extracting polyphenols from honeysuckle. SUMMARY Lonicerae flos (Lonicera japonica Thunb.) is a material of traditional Chinese medicine and healthy drinks, of which active compounds mainly is polyphenols. At present, plant polyphenols are the hotspots centents of food, cosmetic and medicine, because it has strong bioactivity. Several traditional methods are available for the extraction of plant polyphenols including impregnation, solvent extraction, ultrasonic extraction, hot-water extraction, alkaline dilute alcohol or alkaline water extraction, microwave extraction and Supercritical CO2 extraction. But now, an increasing number of research on using cellulase to extract active ingredients from plants. Enzymatic method is widely used for enzyme have excellent properties of high reaction efficiency and specificity, moderate reaction conditions, shorter extraction time and easier to control, less damage to the active ingredient. At present, the enzymatic extraction of polyphenols from honeysuckle and dynamic had not been reported. In this study, using cellulase to extract polyphenols from honeysuckle is first applied. Moreover, uniform design was used to optimize process and kinetic model of extraction was established to analyze the characteristics of enzymatic extraction, in order to improve the yield of polyphenols from honeysuckle and make maximum use of Lonicerae flos, which provide references for industrial production. PMID:27018039

In situ analysis of dynamic laminar flow extraction using surface-enhanced Raman spectroscopy

NASA Astrophysics Data System (ADS)

Wang, Fei; Wang, Hua-Lin; Qiu, Yang; Chang, Yu-Long; Long, Yi-Tao

2015-12-01

In this study, we performed micro-scale dynamic laminar flow extraction and site-specific in situ chloride concentration measurements. Surface-enhanced Raman spectroscopy was utilized to investigate the diffusion process of chloride ions from an oil phase to a water phase under laminar flow. In contrast to common logic, we used SERS intensity gradients of Rhodamine 6G to quantitatively calculate the concentration of chloride ions at specific positions on a microfluidic chip. By varying the fluid flow rates, we achieved different extraction times and therefore different chloride concentrations at specific positions along the microchannel. SERS spectra from the water phase were recorded at these different positions, and the spatial distribution of the SERS signals was used to map the degree of nanoparticle aggregation. The concentration of chloride ions in the channel could therefore be obtained. We conclude that this method can be used to explore the extraction behaviour and efficiency of some ions or molecules that enhance the SERS intensity in water or oil by inducing nanoparticle aggregation.

Quantum Jarzynski equality of measurement-based work extraction

NASA Astrophysics Data System (ADS)

Morikuni, Yohei; Tajima, Hiroyasu; Hatano, Naomichi

2017-03-01

Many studies of quantum-size heat engines assume that the dynamics of an internal system is unitary and that the extracted work is equal to the energy loss of the internal system. Both assumptions, however, should be under scrutiny. In the present paper, we analyze quantum-scale heat engines, employing the measurement-based formulation of the work extraction recently introduced by Hayashi and Tajima [M. Hayashi and H. Tajima, arXiv:1504.06150]. We first demonstrate the inappropriateness of the unitary time evolution of the internal system (namely, the first assumption above) using a simple two-level system; we show that the variance of the energy transferred to an external system diverges when the dynamics of the internal system is approximated to a unitary time evolution. Second, we derive the quantum Jarzynski equality based on the formulation of Hayashi and Tajima as a relation for the work measured by an external macroscopic apparatus. The right-hand side of the equality reduces to unity for "natural" cyclic processes but fluctuates wildly for noncyclic ones, exceeding unity often. This fluctuation should be detectable in experiments and provide evidence for the present formulation.

Quantum Jarzynski equality of measurement-based work extraction.

PubMed

Morikuni, Yohei; Tajima, Hiroyasu; Hatano, Naomichi

2017-03-01

Many studies of quantum-size heat engines assume that the dynamics of an internal system is unitary and that the extracted work is equal to the energy loss of the internal system. Both assumptions, however, should be under scrutiny. In the present paper, we analyze quantum-scale heat engines, employing the measurement-based formulation of the work extraction recently introduced by Hayashi and Tajima [M. Hayashi and H. Tajima, arXiv:1504.06150]. We first demonstrate the inappropriateness of the unitary time evolution of the internal system (namely, the first assumption above) using a simple two-level system; we show that the variance of the energy transferred to an external system diverges when the dynamics of the internal system is approximated to a unitary time evolution. Second, we derive the quantum Jarzynski equality based on the formulation of Hayashi and Tajima as a relation for the work measured by an external macroscopic apparatus. The right-hand side of the equality reduces to unity for "natural" cyclic processes but fluctuates wildly for noncyclic ones, exceeding unity often. This fluctuation should be detectable in experiments and provide evidence for the present formulation.

Quasi-elastic neutron scattering studies of the slow dynamics of supercooled and glassy aspirin

NASA Astrophysics Data System (ADS)

Zhang, Yang; Tyagi, Madhusudan; Mamontov, Eugene; Chen, Sow-Hsin

2012-02-01

Aspirin, also known as acetylsalicylic acid (ASA), is not only a wonderful drug, but also a good glass former. Therefore, it serves as an important molecular system to study the near-arrest and arrested phenomena. In this paper, a high-resolution quasi-elastic neutron scattering (QENS) technique is used to investigate the slow dynamics of supercooled liquid and glassy aspirin from 410 down to 350 K. The measured QENS spectra can be analyzed with a stretched exponential model. We find that (i) the stretched exponent β(Q) is independent of the wavevector transfer Q in the measured Q range and (ii) the structural relaxation time τ(Q) follows a power-law dependence on Q. Consequently, the Q-independent structural relaxation time τ0 can be extracted for each temperature to characterize the slow dynamics of aspirin. The temperature dependence of τ0 can be fitted with the mode-coupling power law, the Vogel-Fulcher-Tammann equation and a universal equation for fragile glass forming liquids recently proposed by Tokuyama in the measured temperature range. The calculated dynamic response function χT(Q, t) using the experimentally determined self-intermediate scattering function of the hydrogen atoms of aspirin shows direct evidence of the enhanced dynamic fluctuations as the aspirin is increasingly supercooled, in agreement with the fixed-time mean squared displacement langx2rang and the non-Gaussian parameter α2 extracted from the elastic scattering.

Quasi-Elastic Neutron Scattering Studies of the Slow Dynamics of Supercooled and Glassy Aspirin

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

Zhang, Yang; Tyagi, M.; Mamontov, Eugene

Aspirin, also known as acetylsalicylic acid (ASA), is not only a wonderful drug, but also a good glass former. Therefore, it serves as an important molecular system to study the near-arrest and arrested phenomena. In this paper, a high-resolution quasi-elastic neutron scattering (QENS) technique is used to investigate the slow dynamics of supercooled liquid and glassy aspirin from 410 K down to 350 K. The measured QENS spectra can be analyzed with a stretched exponential model. We find that (i) the stretched exponent (Q) is independent of the wave vector transfer Q in the measured Q-range, and (ii) the structuralmore » relaxation time (Q) follows a power law dependence on Q. Consequently, the Q-independent structural relaxation time 0 can be extracted for each temperature to characterize the slow dynamics of aspirin. The temperature dependence of 0 can be fitted with the mode coupling power law, the Vogel-Fulcher-Tammann equation and a universal equation for fragile glass forming liquids recently proposed by M. Tokuyama in the measured temperature range. The calculated dynamic response function T(Q,t) using the experimentally determined self-intermediate scattering function of the hydrogen atoms of aspirin shows a direct evidence of the enhanced dynamic fluctuations as the aspirin is increasingly supercooled, in agreement with the fixed-time mean squared displacement x2 and non-Gaussian parameter 2 extracted from the elastic scattering.« less

Variability of normal vocal fold dynamics for different vocal loading in one healthy subject investigated by phonovibrograms.

PubMed

Doellinger, Michael; Lohscheller, Joerg; McWhorter, Andrew; Kunduk, Melda

2009-03-01

We investigate the potential of high-speed digital imaging technique (HSI) and the phonovibrogram (PVG) analysis in normal vocal fold dynamics by studying the effects of continuous voice use (vocal loading) during the workday. One healthy subject was recorded at sustained phonation 13 times within 2 consecutive days in the morning before and in the afternoon after vocal loading, respectively. Vocal fold dynamics were extracted and visualized by PVGs. The characteristic PVG patterns were extracted representing vocal fold vibration types. The parameter values were then analyzed by statistics regarding vocal load, left-right PVG asymmetries, anterior-posterior PVG asymmetries, and opening-closing differences. For the first time, the direct impact of vocal load could be determined by analyzing vocal fold dynamics. For same vocal loading conditions, equal dynamical behavior of the vocal folds were confirmed. Comparison of recordings performed in the morning with the recordings after work revealed significant changes in vibration behavior, indicating impact of occurring vocal load. Left-right asymmetries in vocal fold dynamics were found confirming earlier assumptions. Different dynamics between opening and closing procedure as well as for anterior and posterior parts were found. Constant voice usage stresses the vocal folds even in healthy subjects and can be detected by applying the PVG technique. Furthermore, left-right PVG asymmetries do occur in healthy voice to a certain extent. HSI in combination with PVG analysis seems to be a promising tool for investigation of vocal fold fatigue and pathologies resulting in small forms of dynamical changes.

A Surrogate for Debye-Waller Factors from Dynamic Stokes Shifts

PubMed Central

Zhong, Qin; Johnson, Jerainne; Aamer, Khaled A.; Tyagi, Madhusudan

2011-01-01

We show that the short-time behavior of time-resolved fluorescence Stokes shifts (TRSS) are similar to that of the intermediate scattering function obtained from neutron scattering at q near the peak in the static structure factor for glycerol. This allows us to extract a Debye-Waller (DW) factor analog from TRSS data at times as short as 1 ps in a relatively simple way. Using the time-domain relaxation data obtained by this method we show that DW factors evaluated at times ≥ 40 ps can be directly influenced by α relaxation and thus should be used with caution when evaluating relationships between fast and slow dynamics in glassforming systems. PMID:21701673

2,4-Dichlorophenoxyacetic acid (2,4-D) sorption and degradation dynamics in three agricultural soils.

PubMed

Boivin, Arnaud; Amellal, Samira; Schiavon, Michel; van Genuchten, Martinus Th

2005-11-01

The fate and transport of 2,4-dichlorophenoxyacetic acid (2,4-D) in the subsurface is affected by a complex, time-dependent interplay between sorption and mineralization processes. 2,4-D is biodegradable in soils, while adsorption/desorption is influenced by both soil organic matter content and soil pH. In order to assess the dynamic interactions between sorption and mineralization, 2,4-D mineralization experiments were carried using three different soils (clay, loam and sand) assuming different contact times. Mineralization appeared to be the main process limiting 2,4-D availability, with each soil containing its own 2,4-D decomposers. For the clay and the loamy soils, 45 and 48% of the applied dose were mineralized after 10 days. By comparison, mineralization in the sandy soil proceeded initially much slower because of longer lag times. While 2,4-D residues immediately after application were readily available (>93% was extractable), the herbicide was present in a mostly unavailable state (<2% extractable) in all three soils after incubation for 60 days. We found that the total amount of bound residue decreased between 30 and 60 incubation days. Bioaccumulation may have led to reversible immobilization, with some residues later becoming more readily available again to extraction and/or mineralization.

Nonstationary Dynamics Data Analysis with Wavelet-SVD Filtering

NASA Technical Reports Server (NTRS)

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

2001-01-01

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

Sequential visibility-graph motifs

NASA Astrophysics Data System (ADS)

Iacovacci, Jacopo; Lacasa, Lucas

2016-04-01

Visibility algorithms transform time series into graphs and encode dynamical information in their topology, paving the way for graph-theoretical time series analysis as well as building a bridge between nonlinear dynamics and network science. In this work we introduce and study the concept of sequential visibility-graph motifs, smaller substructures of n consecutive nodes that appear with characteristic frequencies. We develop a theory to compute in an exact way the motif profiles associated with general classes of deterministic and stochastic dynamics. We find that this simple property is indeed a highly informative and computationally efficient feature capable of distinguishing among different dynamics and robust against noise contamination. We finally confirm that it can be used in practice to perform unsupervised learning, by extracting motif profiles from experimental heart-rate series and being able, accordingly, to disentangle meditative from other relaxation states. Applications of this general theory include the automatic classification and description of physical, biological, and financial time series.

Trajectory phase transitions and dynamical Lee-Yang zeros of the Glauber-Ising chain.

PubMed

Hickey, James M; Flindt, Christian; Garrahan, Juan P

2013-07-01

We examine the generating function of the time-integrated energy for the one-dimensional Glauber-Ising model. At long times, the generating function takes on a large-deviation form and the associated cumulant generating function has singularities corresponding to continuous trajectory (or "space-time") phase transitions between paramagnetic trajectories and ferromagnetically or antiferromagnetically ordered trajectories. In the thermodynamic limit, the singularities make up a whole curve of critical points in the complex plane of the counting field. We evaluate analytically the generating function by mapping the generator of the biased dynamics to a non-Hermitian Hamiltonian of an associated quantum spin chain. We relate the trajectory phase transitions to the high-order cumulants of the time-integrated energy which we use to extract the dynamical Lee-Yang zeros of the generating function. This approach offers the possibility to detect continuous trajectory phase transitions from the finite-time behavior of measurable quantities.

Automated Fluid Feature Extraction from Transient Simulations

NASA Technical Reports Server (NTRS)

Haimes, Robert; Lovely, David

1999-01-01

In the past, feature extraction and identification were interesting concepts, but not required to understand the underlying physics of a steady flow field. This is because the results of the more traditional tools like iso-surfaces, cuts and streamlines were more interactive and easily abstracted so they could be represented to the investigator. These tools worked and properly conveyed the collected information at the expense of much interaction. For unsteady flow-fields, the investigator does not have the luxury of spending time scanning only one "snap-shot" of the simulation. Automated assistance is required in pointing out areas of potential interest contained within the flow. This must not require a heavy compute burden (the visualization should not significantly slow down the solution procedure for co-processing environments like pV3). And methods must be developed to abstract the feature and display it in a manner that physically makes sense. The following is a list of the important physical phenomena found in transient (and steady-state) fluid flow: (1) Shocks, (2) Vortex cores, (3) Regions of recirculation, (4) Boundary layers, (5) Wakes. Three papers and an initial specification for the (The Fluid eXtraction tool kit) FX Programmer's guide were included. The papers, submitted to the AIAA Computational Fluid Dynamics Conference, are entitled : (1) Using Residence Time for the Extraction of Recirculation Regions, (2) Shock Detection from Computational Fluid Dynamics results and (3) On the Velocity Gradient Tensor and Fluid Feature Extraction.

Determination of Oleanolic and Ursolic Acids in Hedyotis diffusa Using Hyphenated Ultrasound-Assisted Supercritical Carbon Dioxide Extraction and Chromatography

PubMed Central

Hong, Show-Jen

2015-01-01

Oleanolic acid (OA) and ursolic acid (UA) were extracted from Hedyotis diffusa using a hyphenated procedure of ultrasound-assisted and supercritical carbon dioxide (HSC–CO2) extraction at different temperatures, pressures, cosolvent percentages, and SC–CO2 flow rates. The results indicated that these parameters significantly affected the extraction yield. The maximal yields of OA (0.917 mg/g of dry plant) and UA (3.540 mg/g of dry plant) were obtained at a dynamic extraction time of 110 min, a static extraction time of 15 min, 28.2 MPa, and 56°C with a 12.5% (v/v) cosolvent (ethanol/water = 82/18, v/v) and SC–CO2 flowing at 2.3 mL/min (STP). The extracted yields were then analyzed by high performance liquid chromatography (HPLC) to quantify the OA and UA. The present findings revealed that H. diffusa is a potential source of OA and UA. In addition, using the hyphenated procedure for extraction is a promising and alternative process for recovering OA and UA from H. diffusa at high concentrations. PMID:26089939

Molecular dynamics: deciphering the data.

PubMed

Dauber-Osguthorpe, P; Maunder, C M; Osguthorpe, D J

1996-06-01

The dynamic behaviour of molecules is important in determining their activity. Molecular dynamics (MD) simulations give a detailed description of motion, from small fluctuations to conformational transitions, and can include solvent effects. However, extracting useful information about conformational motion from a trajectory is not trivial. We have used digital signal-processing techniques to characterise the motion in MD simulations, including: calculating the frequency distribution, applying filtering functions, and extraction of vectors defining the characteristic motion for each frequency in an MD simulation. We describe here some typical results obtained for peptides and proteins. The nature of the low-frequency modes of motion, as obtained from MD and normal mode (NM) analysis, of Ace-(Ala)31-Nma and of a proline mutant is discussed. Low-frequency modes extracted from the MD trajectories of Rop protein and phospholipase A2 reveal characteristic motions of secondary structure elements, as well as concerned motions that are of significance to the protein's biological activity. MD simulations are also used frequently as a tool for conformational searches and for investigating protein folding/unfolding. We have developed a novel method that uses time-domain filtering to channel energy into conformational motion and thus enhance conformational transitions. The selectively enhanced molecular dynamics method is tested on the small molecule hexane.

Molecular dynamics: Deciphering the data

NASA Astrophysics Data System (ADS)

Dauber-Osguthorpe, Pnina; Maunder, Colette M.; Osguthorpe, David J.

1996-06-01

The dynamic behaviour of molecules is important in determining their activity. Molecular dynamics (MD) simulations give a detailed description of motion, from small fluctuations to conformational transitions, and can include solvent effects. However, extracting useful information about conformational motion from a trajectory is not trivial. We have used digital signal-processing techniques to characterise the motion in MD simulations, including: calculating the frequency distribution, applying filtering functions, and extraction of vectors defining the characteristic motion for each frequency in an MD simulation. We describe here some typical results obtained for peptides and proteins. The nature of the low-frequency modes of motion, as obtained from MD and normal mode (NM) analysis, of Ace-(Ala)31-Nma and of a proline mutant is discussed. Low-frequency modes extracted from the MD trajectories of Rop protein and phospholipase A2 reveal characteristic motions of secondary structure elements, as well as concerted motions that are of significance to the protein's biological activity. MD simulations are also used frequently as a tool for conformational searches and for investigating protein folding/unfolding. We have developed a novel method that uses time-domain filtering to channel energy into conformational motion and thus enhance conformational transitions. The selectively enhanced molecular dynamics method is tested on the small molecule hexane.

Determination of major aromatic constituents in vanilla using an on-line supercritical fluid extraction coupled with supercritical fluid chromatography.

PubMed

Liang, Yanshan; Liu, Jiaqi; Zhong, Qisheng; Shen, Lingling; Yao, Jinting; Huang, Taohong; Zhou, Ting

2018-04-01

An on-line supercritical fluid extraction coupled with supercritical fluid chromatography method was developed for the determination of four major aromatic constituents in vanilla. The parameters of supercritical fluid extraction were systematically investigated using single factor optimization experiments and response surface methodology by a Box-Behnken design. The modifier ratio, split ratio, and the extraction temperature and pressure were the major parameters which have significant effects on the extraction. While the static extraction time, dynamic extraction time, and recycle time had little influence on the compounds with low polarity. Under the optimized conditions, the relative extraction efficiencies of all the constituents reached 89.0-95.1%. The limits of quantification were in the range of 1.123-4.747 μg. The limits of detection were in the range of 0.3368-1.424 μg. The recoveries of the four analytes were in the range of 76.1-88.9%. The relative standard deviations of intra- and interday precision ranged from 4.2 to 7.6%. Compared with other off-line methods, the present method obtained higher extraction yields for all four aromatic constituents. Finally, this method has been applied to the analysis of vanilla from different sources. On the basis of the results, the on-line supercritical fluid extraction-supercritical fluid chromatography method shows great promise in the analysis of aromatic constituents in natural products. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Feature extraction of micro-motion frequency and the maximum wobble angle in a small range of missile warhead based on micro-Doppler effect

NASA Astrophysics Data System (ADS)

Li, M.; Jiang, Y. S.

2014-11-01

Micro-Doppler effect is induced by the micro-motion dynamics of the radar target itself or any structure on the target. In this paper, a simplified cone-shaped model for ballistic missile warhead with micro-nutation is established, followed by the theoretical formula of micro-nutation is derived. It is confirmed that the theoretical results are identical to simulation results by using short-time Fourier transform. Then we propose a new method for nutation period extraction via signature maximum energy fitting based on empirical mode decomposition and short-time Fourier transform. The maximum wobble angle is also extracted by distance approximate approach in a small range of wobble angle, which is combined with the maximum likelihood estimation. By the simulation studies, it is shown that these two feature extraction methods are both valid even with low signal-to-noise ratio.

Extraction and preconcentration of residual solvents in pharmaceuticals using dynamic headspace-liquid phase microextraction and their determination by gas chromatography-flame ionization detection.

PubMed

Farajzadeh, Mir Ali; Dehghani, Hamideh; Yadeghari, Adeleh; Khoshmaram, Leila

2017-02-01

The present study describes a microextraction and determination method for analyzing residual solvents in pharmaceutical products using dynamic headspace-liquid phase microextraction technique followed by gas chromatography-flame ionization detection. In this method dimethyl sulfoxide (μL level) placed into a GC liner-shaped extraction vessel is used as a collection/extraction solvent. Then the liner is exposed to the headspace of a vial containing the sample solution. The effect of different parameters influencing the microextraction procedure including collection/extraction solvent type and its volume, ionic strength, extraction time, extraction temperature and concentration of NaOH solution used in dissolving the studied pharmaceuticals are investigated and optimized. Under the optimum extraction conditions, the method showed wide linear ranges between 0.5 and 5000 mg L -1 . The other analytical parameters were obtained in the following ranges: enrichment factors 240-327, extraction recoveries 72-98% and limits of detection 0.1-0.8 mg L -1 in solution and 0.6-3.2 μg g -1 in solid. Relative standard deviations for the extraction of 100 mg L -1 of each analyte were obtained in the ranges of 4-7 and 5-8% for intra-day (n = 6) and inter-day (n = 4) respectively. Finally the target analytes were determined in different samples such as erythromycin, azithromycin, cefalexin, amoxicillin and co-amoxiclav by the proposed method. Copyright © 2016 John Wiley & Sons, Ltd.

Fast Algorithms for Mining Co-evolving Time Series

DTIC Science & Technology

2011-09-01

Keogh et al., 2001, 2004] and (b) forecasting, like an autoregressive integrated moving average model ( ARIMA ) and related meth- ods [Box et al., 1994...computing hardware? We develop models to mine time series with missing values, to extract compact representation from time sequences, to segment the...sequences, and to do forecasting. For large scale data, we propose algorithms for learning time series models , in particular, including Linear Dynamical

Thermally induced magnetic relaxation in square artificial spin ice.

PubMed

Andersson, M S; Pappas, S D; Stopfel, H; Östman, E; Stein, A; Nordblad, P; Mathieu, R; Hjörvarsson, B; Kapaklis, V

2016-11-24

The properties of natural and artificial assemblies of interacting elements, ranging from Quarks to Galaxies, are at the heart of Physics. The collective response and dynamics of such assemblies are dictated by the intrinsic dynamical properties of the building blocks, the nature of their interactions and topological constraints. Here we report on the relaxation dynamics of the magnetization of artificial assemblies of mesoscopic spins. In our model nano-magnetic system - square artificial spin ice - we are able to control the geometrical arrangement and interaction strength between the magnetically interacting building blocks by means of nano-lithography. Using time resolved magnetometry we show that the relaxation process can be described using the Kohlrausch law and that the extracted temperature dependent relaxation times of the assemblies follow the Vogel-Fulcher law. The results provide insight into the relaxation dynamics of mesoscopic nano-magnetic model systems, with adjustable energy and time scales, and demonstrates that these can serve as an ideal playground for the studies of collective dynamics and relaxations.

Thermally induced magnetic relaxation in square artificial spin ice

NASA Astrophysics Data System (ADS)

Andersson, M. S.; Pappas, S. D.; Stopfel, H.; Östman, E.; Stein, A.; Nordblad, P.; Mathieu, R.; Hjörvarsson, B.; Kapaklis, V.

2016-11-01

The properties of natural and artificial assemblies of interacting elements, ranging from Quarks to Galaxies, are at the heart of Physics. The collective response and dynamics of such assemblies are dictated by the intrinsic dynamical properties of the building blocks, the nature of their interactions and topological constraints. Here we report on the relaxation dynamics of the magnetization of artificial assemblies of mesoscopic spins. In our model nano-magnetic system - square artificial spin ice - we are able to control the geometrical arrangement and interaction strength between the magnetically interacting building blocks by means of nano-lithography. Using time resolved magnetometry we show that the relaxation process can be described using the Kohlrausch law and that the extracted temperature dependent relaxation times of the assemblies follow the Vogel-Fulcher law. The results provide insight into the relaxation dynamics of mesoscopic nano-magnetic model systems, with adjustable energy and time scales, and demonstrates that these can serve as an ideal playground for the studies of collective dynamics and relaxations.

A biphasic parameter estimation method for quantitative analysis of dynamic renal scintigraphic data

NASA Astrophysics Data System (ADS)

Koh, T. S.; Zhang, Jeff L.; Ong, C. K.; Shuter, B.

2006-06-01

Dynamic renal scintigraphy is an established method in nuclear medicine, commonly used for the assessment of renal function. In this paper, a biphasic model fitting method is proposed for simultaneous estimation of both vascular and parenchymal parameters from renal scintigraphic data. These parameters include the renal plasma flow, vascular and parenchymal mean transit times, and the glomerular extraction rate. Monte Carlo simulation was used to evaluate the stability and confidence of the parameter estimates obtained by the proposed biphasic method, before applying the method on actual patient study cases to compare with the conventional fitting approach and other established renal indices. The various parameter estimates obtained using the proposed method were found to be consistent with the respective pathologies of the study cases. The renal plasma flow and extraction rate estimated by the proposed method were in good agreement with those previously obtained using dynamic computed tomography and magnetic resonance imaging.

Dynamics of water confined in lyotropic liquid crystals: Molecular dynamics simulations of the dynamic structure factor

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

Mantha, Sriteja; Yethiraj, Arun

2016-02-24

The properties of water under confinement are of practical and fundamental interest. Here in this work we study the properties of water in the self-assembled lyotropic phases of gemini surfactants with a focus on testing the standard analysis of quasi-elastic neutron scattering (QENS) experiments. In QENS experiments the dynamic structure factor is measured and fit to models to extract the translational diffusion constant, D T , and rotational relaxation time, τ R. We test this procedure by using simulation results for the dynamic structure factor, extracting the dynamic parameters from the fit as is typically done in experiments, and comparingmore » the values to those directly measured in the simulations. We find that the decoupling approximation, where the intermediate scattering function is assumed to be a product of translational and rotational contributions, is quite accurate. The jump-diffusion and isotropic rotation models, however, are not accurate when the degree of confinement is high. In particular, the exponential approximations for the intermediate scattering function fail for highly confined water and the values of D T and τ R can differ from the measured value by as much as a factor of two. Other models have more fit parameters, however, and with the range of energies and wave-vectors accessible to QENS, the typical analysis appears to be the best choice. In the most confined lamellar phase, the dynamics are sufficiently slow that QENS does not access a large enough time scale and neutron spin echo measurements would be a valuable technique in addition to QENS.« less

Scaling analysis of bilateral hand tremor movements in essential tremor patients.

PubMed

Blesic, S; Maric, J; Dragasevic, N; Milanovic, S; Kostic, V; Ljubisavljevic, Milos

2011-08-01

Recent evidence suggests that the dynamic-scaling behavior of the time-series of signals extracted from separate peaks of tremor spectra may reveal existence of multiple independent sources of tremor. Here, we have studied dynamic characteristics of the time-series of hand tremor movements in essential tremor (ET) patients using the detrended fluctuation analysis method. Hand accelerometry was recorded with (500 g) and without weight loading under postural conditions in 25 ET patients and 20 normal subjects. The time-series comprising peak-to-peak (PtP) intervals were extracted from regions around the first three main frequency components of power spectra (PwS) of the recorded tremors. The data were compared between the load and no-load condition on dominant (related to tremor severity) and non-dominant tremor side and with the normal (physiological) oscillations in healthy subjects. Our analysis shows that, in ET, the dynamic characteristics of the main frequency component of recorded tremors exhibit scaling behavior. Furthermore, they show that the two main components of ET tremor frequency spectra, otherwise indistinguishable without load, become significantly different after inertial loading and that they differ between the tremor sides (related to tremor severity). These results show that scaling, a time-domain analysis, helps revealing tremor features previously not revealed by frequency-domain analysis and suggest that distinct oscillatory central circuits may generate the tremor in ET patients.

Real-time high-resolution heterodyne-based measurements of spectral dynamics in fibre lasers

PubMed Central

Sugavanam, Srikanth; Fabbri, Simon; Le, Son Thai; Lobach, Ivan; Kablukov, Sergey; Khorev, Serge; Churkin, Dmitry

2016-01-01

Conventional tools for measurement of laser spectra (e.g. optical spectrum analysers) capture data averaged over a considerable time period. However, the generation spectrum of many laser types may involve spectral dynamics whose relatively fast time scale is determined by their cavity round trip period, calling for instrumentation featuring both high temporal and spectral resolution. Such real-time spectral characterisation becomes particularly challenging if the laser pulses are long, or they have continuous or quasi-continuous wave radiation components. Here we combine optical heterodyning with a technique of spatio-temporal intensity measurements that allows the characterisation of such complex sources. Fast, round-trip-resolved spectral dynamics of cavity-based systems in real-time are obtained, with temporal resolution of one cavity round trip and frequency resolution defined by its inverse (85 ns and 24 MHz respectively are demonstrated). We also show how under certain conditions for quasi-continuous wave sources, the spectral resolution could be further increased by a factor of 100 by direct extraction of phase information from the heterodyned dynamics or by using double time scales within the spectrogram approach. PMID:26984634

Dynamics and causalities of atmospheric and oceanic data identified by complex networks and Granger causality analysis

NASA Astrophysics Data System (ADS)

Charakopoulos, A. K.; Katsouli, G. A.; Karakasidis, T. E.

2018-04-01

Understanding the underlying processes and extracting detailed characteristics of spatiotemporal dynamics of ocean and atmosphere as well as their interaction is of significant interest and has not been well thoroughly established. The purpose of this study was to examine the performance of two main additional methodologies for the identification of spatiotemporal underlying dynamic characteristics and patterns among atmospheric and oceanic variables from Seawatch buoys from Aegean and Ionian Sea, provided by the Hellenic Center for Marine Research (HCMR). The first approach involves the estimation of cross correlation analysis in an attempt to investigate time-lagged relationships, and further in order to identify the direction of interactions between the variables we performed the Granger causality method. According to the second approach the time series are converted into complex networks and then the main topological network properties such as degree distribution, average path length, diameter, modularity and clustering coefficient are evaluated. Our results show that the proposed analysis of complex network analysis of time series can lead to the extraction of hidden spatiotemporal characteristics. Also our findings indicate high level of positive and negative correlations and causalities among variables, both from the same buoy and also between buoys from different stations, which cannot be determined from the use of simple statistical measures.

Possibility of the real-time dynamic strain field monitoring deduced from GNSS data: case study of the 2016 Kumamoto earthquake sequence

NASA Astrophysics Data System (ADS)

Ohta, Y.; Ohzono, M.; Takahashi, H.; Kawamoto, S.; Hino, R.

2017-12-01

A large and destructive earthquake (Mjma 7.3) occurred on April 15, 2016 in Kumamoto region, southwestern Japan. This earthquake was accompanied approximately 32 s later by an M 6 earthquake in central Oita region, which hypocenter located 80 km northeast from the hypocenter of the mainshock of the Kumamoto earthquake. This triggered earthquake also had the many aftershocks in and around the Oita region. It is important to understand how to occur such chain-reacted earthquake sequences. We used the 1Hz dual-frequency phase and range data from GEONET in Kyushu island. The data were processed using GIPSY-OASIS (version 6.4). We adopoted kinematic PPP strategy for the coordinate estimation. The reference GPS satellite orbit and 5 s clock information were obtained using the CODE product. We also applied simple sidereal filter technique for the estimated time series. Based on the obtained 1Hz GNSS time series, we estimated the areal strain and principle strain field using the method of the Shen et al. (1996). For the assessment of the dynamic strain, firstly we calculated the averaged absolute value of areal strain field between 60-85s after the origin time of the mainshock of the Kumamoto earthquake which was used as the "reference" static strain field. Secondly, we estimated the absolute value of areal strain in each time step. Finally, we calculated the strain ratio in each time step relative to the "reference". Based on this procedure, we can extract the spatial and temporal characteristic of the dynamic strain in each time step. Extracted strain ratio clearly shows the spatial and temporal dynamic strain characteristic. When an attention is paid to a region of triggered Oita earthquake, the timing of maximum dynamic strain ratio in the epicenter just corresponds to the origin time of the triggered event. It strongly suggested that the large dynamic strain may trigger the Oita event. The epicenter of the triggered earthquake located within the geothermal region. In the geothermal region, the crustal materials are more sensitive to stress perturbations, and the earthquakes are more easily triggered compared with other typical regions. Our result also suggested that the real-time strain field monitoring may be useful information for the understanding of the possibility of the remotely triggered earthquake in the future.

Photo-generated carriers lose energy during extraction from polymer-fullerene solar cells

PubMed Central

Melianas, Armantas; Etzold, Fabian; Savenije, Tom J.; Laquai, Frédéric; Inganäs, Olle; Kemerink, Martijn

2015-01-01

In photovoltaic devices, the photo-generated charge carriers are typically assumed to be in thermal equilibrium with the lattice. In conventional materials, this assumption is experimentally justified as carrier thermalization completes before any significant carrier transport has occurred. Here, we demonstrate by unifying time-resolved optical and electrical experiments and Monte Carlo simulations over an exceptionally wide dynamic range that in the case of organic photovoltaic devices, this assumption is invalid. As the photo-generated carriers are transported to the electrodes, a substantial amount of their energy is lost by continuous thermalization in the disorder broadened density of states. Since thermalization occurs downward in energy, carrier motion is boosted by this process, leading to a time-dependent carrier mobility as confirmed by direct experiments. We identify the time and distance scales relevant for carrier extraction and show that the photo-generated carriers are extracted from the operating device before reaching thermal equilibrium. PMID:26537357

Linear modeling of human hand-arm dynamics relevant to right-angle torque tool interaction.

PubMed

Ay, Haluk; Sommerich, Carolyn M; Luscher, Anthony F

2013-10-01

A new protocol was evaluated for identification of stiffness, mass, and damping parameters employing a linear model for human hand-arm dynamics relevant to right-angle torque tool use. Powered torque tools are widely used to tighten fasteners in manufacturing industries. While these tools increase accuracy and efficiency of tightening processes, operators are repetitively exposed to impulsive forces, posing risk of upper extremity musculoskeletal injury. A novel testing apparatus was developed that closely mimics biomechanical exposure in torque tool operation. Forty experienced torque tool operators were tested with the apparatus to determine model parameters and validate the protocol for physical capacity assessment. A second-order hand-arm model with parameters extracted in the time domain met model accuracy criterion of 5% for time-to-peak displacement error in 93% of trials (vs. 75% for frequency domain). Average time-to-peak handle displacement and relative peak handle force errors were 0.69 ms and 0.21%, respectively. Model parameters were significantly affected by gender and working posture. Protocol and numerical calculation procedures provide an alternative method for assessing mechanical parameters relevant to right-angle torque tool use. The protocol more closely resembles tool use, and calculation procedures demonstrate better performance of parameter extraction using time domain system identification methods versus frequency domain. Potential future applications include parameter identification for in situ torque tool operation and equipment development for human hand-arm dynamics simulation under impulsive forces that could be used for assessing torque tools based on factors relevant to operator health (handle dynamics and hand-arm reaction force).

Imaging Cellular Dynamics with Spectral Relaxation Imaging Microscopy: Distinct Spectral Dynamics in Golgi Membranes of Living Cells.

PubMed

Lajevardipour, Alireza; Chon, James W M; Chattopadhyay, Amitabha; Clayton, Andrew H A

2016-11-22

Spectral relaxation from fluorescent probes is a useful technique for determining the dynamics of condensed phases. To this end, we have developed a method based on wide-field spectral fluorescence lifetime imaging microscopy to extract spectral relaxation correlation times of fluorescent probes in living cells. We show that measurement of the phase and modulation of fluorescence from two wavelengths permit the identification and determination of excited state lifetimes and spectral relaxation correlation times at a single modulation frequency. For NBD fluorescence in glycerol/water mixtures, the spectral relaxation correlation time determined by our approach exhibited good agreement with published dielectric relaxation measurements. We applied this method to determine the spectral relaxation dynamics in membranes of living cells. Measurements of the Golgi-specific C 6 -NBD-ceramide probe in living HeLa cells revealed sub-nanosecond spectral dynamics in the intracellular Golgi membrane and slower nanosecond spectral dynamics in the extracellular plasma membrane. We interpret the distinct spectral dynamics as a result of structural plasticity of the Golgi membrane relative to more rigid plasma membranes. To the best of our knowledge, these results constitute one of the first measurements of Golgi rotational dynamics.

In situ analysis of dynamic laminar flow extraction using surface-enhanced Raman spectroscopy

PubMed Central

Wang, Fei; Wang, Hua-Lin; Qiu, Yang; Chang, Yu-Long; Long, Yi-Tao

2015-01-01

In this study, we performed micro-scale dynamic laminar flow extraction and site-specific in situ chloride concentration measurements. Surface-enhanced Raman spectroscopy was utilized to investigate the diffusion process of chloride ions from an oil phase to a water phase under laminar flow. In contrast to common logic, we used SERS intensity gradients of Rhodamine 6G to quantitatively calculate the concentration of chloride ions at specific positions on a microfluidic chip. By varying the fluid flow rates, we achieved different extraction times and therefore different chloride concentrations at specific positions along the microchannel. SERS spectra from the water phase were recorded at these different positions, and the spatial distribution of the SERS signals was used to map the degree of nanoparticle aggregation. The concentration of chloride ions in the channel could therefore be obtained. We conclude that this method can be used to explore the extraction behaviour and efficiency of some ions or molecules that enhance the SERS intensity in water or oil by inducing nanoparticle aggregation. PMID:26687436

Changes in the Coherent Dynamics of Nanoconfined Room Temperature Ionic Liquids

NASA Astrophysics Data System (ADS)

Vallejo, Kevin; Cano, Melissa; Li, Song; Rotner, Gernot; Faraone, Antonio; Banuelos, Jose

Confinement and temperature effects on the coherent dynamics of the room temperature ionic liquid (RTIL) [C10MPy+] [Tf2N-] were investigated using neutron spin-echo (NSE) in two silica matrices with different pore size. Several intermolecular forces give rise to the bulk molecular structure between anions and cations. NSE provided dynamics (via the coherent intermediate scattering function) in the time range of 0.004 to 10 ns, and at Q-values corresponding to intermediate range ordering and inter- and intra-molecular length scales of the RTIL. Pore wall effects were delineated by comparing bulk RTIL dynamics with those of the confined fluid in 2.8 nm and 8 nm pores. Analytical models were applied to the experimental data to extract decay times and amplitudes of each component. We find a fast relaxation outside the experiment time window, a primary relaxation, and slow, surface-induced dynamics, which all speed up with increased temperature, however, the temperature dependence differs between bulk and confinement. This study sheds light on the structure and dynamics of RTILs and is relevant to the optimization of RTILs for green technologies and applications.

Comparative Analysis of Volcanic Inflation—Deflation Cycles

NASA Astrophysics Data System (ADS)

Walwer, D.; Ghil, M.; Calais, E.

2016-12-01

GPS geodetic data together with INSAR images are often used to formulate kinematic models of the sources of volcanic deformations. The increasing amount of data now available allows one to produce time series that are several years long and thus capture continuously the history of volcanic deformations, in particular their nonlinear behavior. This information is highly valuable in helping understand the dynamics of volcanic systems.Nonlinear deformation signals are, however, difficult to extract from the background noise inherent in the GPS time series. It is also arduous to unravel the signal of interest from other nonlinear signals, such as the seasonal oscillations associated with mass variations in the atmosphere, the ocean, and the hydrological reservoirs. Here we use Multichannel Singular Spectrum Analysis (M-SSA) — an advanced, data-adaptive method for time series analysis that exploits simultaneously the temporal and spatial correlations of geophysical fields — to extract such deformation signals.We apply M-SSA to GPS data sets from four volcanoes: Akutan, Alaska; Okmok, Alaska; Westdahl, Alaska; and Piton de la Fournaise, La Reunion. Our analyses show that all four volcanoes share similar features in their deformation history, suggesting similarities in the dynamics that generate the inflation-deflation cycles. In particular, all four volcanic systems exhibit sawtooth-shaped oscillations with slow inflations followed by slower deflations, with time scales that vary from 6 months to 4 years. This relation of dynamical similarity is further highlighted by the phase portrait reconstruction of the four systems in the plane of deformation vs. rate-of-deformation, as obtained from the deformation signals extracted from the GPS time series using M-SSA.The inflating phase of these oscillations is followed by eruptions at Okmok volcano and at Piton de la Fournaise. These analysis results suggest that these volcanic inflation—deflation cycles are associated with the destabilization of a volcanic system and may lead to the identification of premonitory signals for an eruptive regime.

Online flow cytometry reveals microbial dynamics influenced by concurrent natural and operational events in groundwater used for drinking water treatment.

PubMed

Besmer, Michael D; Epting, Jannis; Page, Rebecca M; Sigrist, Jürg A; Huggenberger, Peter; Hammes, Frederik

2016-12-07

Detailed measurements of physical, chemical and biological dynamics in groundwater are key to understanding the important processes in place and their influence on water quality - particularly when used for drinking water. Measuring temporal bacterial dynamics at high frequency is challenging due to the limitations in automation of sampling and detection of the conventional, cultivation-based microbial methods. In this study, fully automated online flow cytometry was applied in a groundwater system for the first time in order to monitor microbial dynamics in a groundwater extraction well. Measurements of bacterial concentrations every 15 minutes during 14 days revealed both aperiodic and periodic dynamics that could not be detected previously, resulting in total cell concentration (TCC) fluctuations between 120 and 280 cells μL -1 . The aperiodic dynamic was linked to river water contamination following precipitation events, while the (diurnal) periodic dynamic was attributed to changes in hydrological conditions as a consequence of intermittent groundwater extraction. Based on the high number of measurements, the two patterns could be disentangled and quantified separately. This study i) increases the understanding of system performance, ii) helps to optimize monitoring strategies, and iii) opens the possibility for more sophisticated (quantitative) microbial risk assessment of drinking water treatment systems.

Online flow cytometry reveals microbial dynamics influenced by concurrent natural and operational events in groundwater used for drinking water treatment

PubMed Central

Besmer, Michael D.; Epting, Jannis; Page, Rebecca M.; Sigrist, Jürg A.; Huggenberger, Peter; Hammes, Frederik

2016-01-01

Detailed measurements of physical, chemical and biological dynamics in groundwater are key to understanding the important processes in place and their influence on water quality – particularly when used for drinking water. Measuring temporal bacterial dynamics at high frequency is challenging due to the limitations in automation of sampling and detection of the conventional, cultivation-based microbial methods. In this study, fully automated online flow cytometry was applied in a groundwater system for the first time in order to monitor microbial dynamics in a groundwater extraction well. Measurements of bacterial concentrations every 15 minutes during 14 days revealed both aperiodic and periodic dynamics that could not be detected previously, resulting in total cell concentration (TCC) fluctuations between 120 and 280 cells μL−1. The aperiodic dynamic was linked to river water contamination following precipitation events, while the (diurnal) periodic dynamic was attributed to changes in hydrological conditions as a consequence of intermittent groundwater extraction. Based on the high number of measurements, the two patterns could be disentangled and quantified separately. This study i) increases the understanding of system performance, ii) helps to optimize monitoring strategies, and iii) opens the possibility for more sophisticated (quantitative) microbial risk assessment of drinking water treatment systems. PMID:27924920

Polytetrafluorethylene film-based liquid-three phase micro extraction coupled with differential pulse voltammetry for the determination of atorvastatin calcium.

PubMed

Ensafi, Ali A; Khoddami, Elaheh; Rezaei, Behzad

2013-01-01

In this paper, we describe a new combination method based on polytetrafluorethylene (PTFE) film-based liquid three-phase micro extraction coupled with differential pulse voltammetry (DPV) for the micro extraction and quantification of atorvastatin calcium (ATC) at the ultra-trace level. Different factors affecting the liquid-three phases micro extraction of atorvastatin calcium, including organic solvent, pH of the donor and acceptor phases, concentration of salt, extraction time, stirring rate and electrochemical factors, were investigated, and the optimal extraction conditions were established. The final stable signal was achieved after a 50 min extraction time, which was used for analytical applications. An enrichment factor of 21 was achieved, and the relative standard deviation (RSD) of the method was 4.5% (n = 4). Differential pulse voltammetry exhibited two wide linear dynamic ranges of 20.0-1000.0 pmol L(-1) and 0.001-11.0 µmol L(-1) of ATC. The detection limit was found to be 8.1 pmol L(-1) ATC. Finally, the proposed method was used as a new combination method for the determination of atorvastatin calcium in real samples, such as human urine and plasma.

Development of Mackintosh Probe Extractor

NASA Astrophysics Data System (ADS)

Rahman, Noor Khazanah A.; Kaamin, Masiri; Suwandi, Amir Khan; Sahat, Suhaila; Jahaya Kesot, Mohd

2016-11-01

Dynamic probing is a continuous soil investigation technique, which is one of the simplest soil penetration test. It basically consist of repeatedly driving a metal tipped probe into the ground using a drop weight of fixed mass and travel. Testing was carried out continuously from ground level to the final penetration depth. Once the soil investigation work done, it is difficult to pull out the probe rod from the ground, due to strong soil structure grip against probe cone and prevent the probe rod out from the ground. Thus, in this case, a tool named Extracting Probe was created to assist in the process of retracting the probe rod from the ground. In addition, Extracting Probe also can reduce the time to extract the probe rod from the ground compare with the conventional method. At the same time, it also can reduce manpower cost because only one worker involve to handle this tool compare with conventional method used two or more workers. From experiment that have been done we found that the time difference between conventional tools and extracting probe is significant, average time difference is 155 minutes. In addition the extracting probe can reduce manpower usage, and also labour cost for operating the tool. With all these advantages makes this tool has the potential to be marketed.

Slow dynamics in protein fluctuations revealed by time-structure based independent component analysis: The case of domain motions

NASA Astrophysics Data System (ADS)

Naritomi, Yusuke; Fuchigami, Sotaro

2011-02-01

Protein dynamics on a long time scale was investigated using all-atom molecular dynamics (MD) simulation and time-structure based independent component analysis (tICA). We selected the lysine-, arginine-, ornithine-binding protein (LAO) as a target protein and focused on its domain motions in the open state. A MD simulation of the LAO in explicit water was performed for 600 ns, in which slow and large-amplitude domain motions of the LAO were observed. After extracting domain motions by rigid-body domain analysis, the tICA was applied to the obtained rigid-body trajectory, yielding slow modes of the LAO's domain motions in order of decreasing time scale. The slowest mode detected by the tICA represented not a closure motion described by a largest-amplitude mode determined by the principal component analysis but a twist motion with a time scale of tens of nanoseconds. The slow dynamics of the LAO were well described by only the slowest mode and were characterized by transitions between two basins. The results show that tICA is promising for describing and analyzing slow dynamics of proteins.

Slow dynamics in protein fluctuations revealed by time-structure based independent component analysis: the case of domain motions.

PubMed

Naritomi, Yusuke; Fuchigami, Sotaro

2011-02-14

Protein dynamics on a long time scale was investigated using all-atom molecular dynamics (MD) simulation and time-structure based independent component analysis (tICA). We selected the lysine-, arginine-, ornithine-binding protein (LAO) as a target protein and focused on its domain motions in the open state. A MD simulation of the LAO in explicit water was performed for 600 ns, in which slow and large-amplitude domain motions of the LAO were observed. After extracting domain motions by rigid-body domain analysis, the tICA was applied to the obtained rigid-body trajectory, yielding slow modes of the LAO's domain motions in order of decreasing time scale. The slowest mode detected by the tICA represented not a closure motion described by a largest-amplitude mode determined by the principal component analysis but a twist motion with a time scale of tens of nanoseconds. The slow dynamics of the LAO were well described by only the slowest mode and were characterized by transitions between two basins. The results show that tICA is promising for describing and analyzing slow dynamics of proteins.

Improved parameter extraction and classification for dynamic contrast enhanced MRI of prostate

NASA Astrophysics Data System (ADS)

Haq, Nandinee Fariah; Kozlowski, Piotr; Jones, Edward C.; Chang, Silvia D.; Goldenberg, S. Larry; Moradi, Mehdi

2014-03-01

Magnetic resonance imaging (MRI), particularly dynamic contrast enhanced (DCE) imaging, has shown great potential in prostate cancer diagnosis and prognosis. The time course of the DCE images provides measures of the contrast agent uptake kinetics. Also, using pharmacokinetic modelling, one can extract parameters from the DCE-MR images that characterize the tumor vascularization and can be used to detect cancer. A requirement for calculating the pharmacokinetic DCE parameters is estimating the Arterial Input Function (AIF). One needs an accurate segmentation of the cross section of the external femoral artery to obtain the AIF. In this work we report a semi-automatic method for segmentation of the cross section of the femoral artery, using circular Hough transform, in the sequence of DCE images. We also report a machine-learning framework to combine pharmacokinetic parameters with the model-free contrast agent uptake kinetic parameters extracted from the DCE time course into a nine-dimensional feature vector. This combination of features is used with random forest and with support vector machine classi cation for cancer detection. The MR data is obtained from patients prior to radical prostatectomy. After the surgery, wholemount histopathology analysis is performed and registered to the DCE-MR images as the diagnostic reference. We show that the use of a combination of pharmacokinetic parameters and the model-free empirical parameters extracted from the time course of DCE results in improved cancer detection compared to the use of each group of features separately. We also validate the proposed method for calculation of AIF based on comparison with the manual method.

Momentum-imaging apparatus for the study of dissociative electron attachment dynamics

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

Moradmand, A.; Williams, J. B.; Landers, A. L.

An ion-momentum spectrometer is used to study the dissociative dynamics of electron attachment to molecules. A skimmed, supersonic gas jet is crossed with a pulsed beam of low-energy electrons, and the resulting negative ions are extracted toward a time- and position-sensitive detector. Calculations of the momentum in three dimensions may be used to determine the angular dependence of dissociative attachment as well as the energetics of the reaction.

Near infrared spectroscopy based monitoring of extraction processes of raw material with the help of dynamic predictive modeling

NASA Astrophysics Data System (ADS)

Wang, Haixia; Suo, Tongchuan; Wu, Xiaolin; Zhang, Yue; Wang, Chunhua; Yu, Heshui; Li, Zheng

2018-03-01

The control of batch-to-batch quality variations remains a challenging task for pharmaceutical industries, e.g., traditional Chinese medicine (TCM) manufacturing. One difficult problem is to produce pharmaceutical products with consistent quality from raw material of large quality variations. In this paper, an integrated methodology combining the near infrared spectroscopy (NIRS) and dynamic predictive modeling is developed for the monitoring and control of the batch extraction process of licorice. With the spectra data in hand, the initial state of the process is firstly estimated with a state-space model to construct a process monitoring strategy for the early detection of variations induced by the initial process inputs such as raw materials. Secondly, the quality property of the end product is predicted at the mid-course during the extraction process with a partial least squares (PLS) model. The batch-end-time (BET) is then adjusted accordingly to minimize the quality variations. In conclusion, our study shows that with the help of the dynamic predictive modeling, NIRS can offer the past and future information of the process, which enables more accurate monitoring and control of process performance and product quality.

Dynamical Structure of Madden-Julian Oscillation over Malay Peninsula

NASA Astrophysics Data System (ADS)

Djamil, Y. S.; Koh, T. Y.; Chandimala, J.; Teo, C. K.

2014-12-01

Madden-Julian Oscillation (MJO) is the dominant weather event in the intraseasonal time scale over Malay Peninsula region. The MJO signals are represented by the first two modes of radiosonde records extracted using Extended Empirical Orthogonal Function (EEOF) analyses which we label as Local Multivariate MJO (LMM). LMM is able to capture the spatio-temporal profile of MJO along the global tropics in all seasons. With the help of LMM, we clarify the dynamical and thermodynamical structure of the MJO over Malay Peninsula, including the unique "boomerang-shaped" feature in the time-height temperature profile identified in previous literature.

Revealing the ultrafast charge carrier dynamics in organo metal halide perovskite solar cell materials using time resolved THz spectroscopy

NASA Astrophysics Data System (ADS)

Ponseca, C. S., Jr.; Sundström, V.

2016-03-01

Ultrafast charge carrier dynamics in organo metal halide perovskite has been probed using time resolved terahertz (THz) spectroscopy (TRTS). Current literature on its early time characteristics is unanimous: sub-ps charge carrier generation, highly mobile charges and very slow recombination rationalizing the exceptionally high power conversion efficiency for a solution processed solar cell material. Electron injection from MAPbI3 to nanoparticles (NP) of TiO2 is found to be sub-ps while Al2O3 NPs do not alter charge dynamics. Charge transfer to organic electrodes, Spiro-OMeTAD and PCBM, is sub-ps and few hundreds of ps respectively, which is influenced by the alignment of energy bands. It is surmised that minimizing defects/trap states is key in optimizing charge carrier extraction from these materials.

Detecting transitions in protein dynamics using a recurrence quantification analysis based bootstrap method.

PubMed

Karain, Wael I

2017-11-28

Proteins undergo conformational transitions over different time scales. These transitions are closely intertwined with the protein's function. Numerous standard techniques such as principal component analysis are used to detect these transitions in molecular dynamics simulations. In this work, we add a new method that has the ability to detect transitions in dynamics based on the recurrences in the dynamical system. It combines bootstrapping and recurrence quantification analysis. We start from the assumption that a protein has a "baseline" recurrence structure over a given period of time. Any statistically significant deviation from this recurrence structure, as inferred from complexity measures provided by recurrence quantification analysis, is considered a transition in the dynamics of the protein. We apply this technique to a 132 ns long molecular dynamics simulation of the β-Lactamase Inhibitory Protein BLIP. We are able to detect conformational transitions in the nanosecond range in the recurrence dynamics of the BLIP protein during the simulation. The results compare favorably to those extracted using the principal component analysis technique. The recurrence quantification analysis based bootstrap technique is able to detect transitions between different dynamics states for a protein over different time scales. It is not limited to linear dynamics regimes, and can be generalized to any time scale. It also has the potential to be used to cluster frames in molecular dynamics trajectories according to the nature of their recurrence dynamics. One shortcoming for this method is the need to have large enough time windows to insure good statistical quality for the recurrence complexity measures needed to detect the transitions.

A modal parameter extraction procedure applicable to linear time-invariant dynamic systems

NASA Technical Reports Server (NTRS)

Kurdila, A. J.; Craig, R. R., Jr.

1985-01-01

Modal analysis has emerged as a valuable tool in many phases of the engineering design process. Complex vibration and acoustic problems in new designs can often be remedied through use of the method. Moreover, the technique has been used to enhance the conceptual understanding of structures by serving to verify analytical models. A new modal parameter estimation procedure is presented. The technique is applicable to linear, time-invariant systems and accommodates multiple input excitations. In order to provide a background for the derivation of the method, some modal parameter extraction procedures currently in use are described. Key features implemented in the new technique are elaborated upon.

Substituting root numbers for length: Improving the use of minirhizotrons to study fine root dynamics

Treesearch

Tracey L. Crocker; Ron L. Hendrick; Roger W. Ruess; Kurt S. Pregitzer; Andrew J. Burton; Michael F. Allen; Jianping Shan; Lawrence A. Morris

2003-01-01

Minirhizotrons provide a unique way to repeatedly measure the production and fate of individual root segments, while minimizing soil disturbance and the confounding of spatial-temporal variation. However, the time associated with processing videotaped minirhizotron images limits the amount of data that can be extracted in a reasonable amount of time. We found that this...

Cluster Morphology-Polymer Dynamics Correlations in Sulfonated Polystyrene Melts: Computational Study

DOE PAGES

Agrawal, Anupriya; Perahia, Dvora; Grest, Gary S.

2016-04-11

Reaching exceptionally long times up to 500 ns in equilibrium and nonequilibrium molecular dynamics simulations studies, we have attained a fundamental molecular understanding of the correlation of ionomer clusters structure and multiscale dynamics, providing new insight into one critical, long-standing challenge in ionic polymer physics. The cluster structure in melts of sulfonated polystyrene with Na + and Mg 2+ counterions are resolved and correlated with the dynamics on multiple length and time scales extracted from measurements of the dynamic structure factor and shear rheology. We find that as the morphology of the ionic clusters changes from ladderlike for Na +more » to disordered structures for Mg 2+, the dynamic structure factor is affected on the length scale corresponding to the ionic clusters. Lastly, rheology studies show that the viscosity for Mg 2+ melts is higher than for Na + ones for all shear rates, which is well correlated with the larger ionic clusters’ size for the Mg 2+ melts.« less

Novel Fluorinated Tensioactive Extractant Combined with Flotation for Decontamination of Extractant Residual during Solvent Extraction

NASA Astrophysics Data System (ADS)

Wu, Xue; Chang, Zhidong; Liu, Yao; Choe, Chol Ryong

2017-12-01

Solvent-extraction is widely used in chemical industry. Due to the amphiphilic character, a large amount of extractant remains in water phase, which causes not only loss of reagent, but also secondary contamination in water phase. Novel fluorinated extractants with ultra-low solubility in water were regarded as effective choice to reduce extractant loss in aqueous phase. However, trace amount of extractant still remained in water. Based on the high tensioactive aptitude of fluorinated solvent, flotation was applied to separate fluorinated extractant remaining in raffinate. According to the data of surface tension measurement, the surface tension of solution was obviously decreased with the addition of fluorinated extractant tris(2,2,3,3,4,4,5,5-octafluoropentyl) phosphate (FTAP). After flotation, the FTAP dissolved in water can be removed as much as 70%, which proved the feasibility of this key idea. The effects of operation time, gas velocity, pH and salinity of bulk solution on flotation performance were discussed. The optimum operating parameters were determined as gas velocity of 12ml/min, operating time of 15min, pH of 8.7, and NaCl volume concentration of 1.5%, respectively. Moreover, adsorption process of FTAP on bubble surface was simulated by ANSYS VOF model using SIMPLE algorithm. The dynamic mechanism of flotation was also theoretically investigated, which can be considered as supplement to the experimental results.

De-biasing the dynamic mode decomposition for applied Koopman spectral analysis of noisy datasets

NASA Astrophysics Data System (ADS)

Hemati, Maziar S.; Rowley, Clarence W.; Deem, Eric A.; Cattafesta, Louis N.

2017-08-01

The dynamic mode decomposition (DMD)—a popular method for performing data-driven Koopman spectral analysis—has gained increased popularity for extracting dynamically meaningful spatiotemporal descriptions of fluid flows from snapshot measurements. Often times, DMD descriptions can be used for predictive purposes as well, which enables informed decision-making based on DMD model forecasts. Despite its widespread use and utility, DMD can fail to yield accurate dynamical descriptions when the measured snapshot data are imprecise due to, e.g., sensor noise. Here, we express DMD as a two-stage algorithm in order to isolate a source of systematic error. We show that DMD's first stage, a subspace projection step, systematically introduces bias errors by processing snapshots asymmetrically. To remove this systematic error, we propose utilizing an augmented snapshot matrix in a subspace projection step, as in problems of total least-squares, in order to account for the error present in all snapshots. The resulting unbiased and noise-aware total DMD (TDMD) formulation reduces to standard DMD in the absence of snapshot errors, while the two-stage perspective generalizes the de-biasing framework to other related methods as well. TDMD's performance is demonstrated in numerical and experimental fluids examples. In particular, in the analysis of time-resolved particle image velocimetry data for a separated flow, TDMD outperforms standard DMD by providing dynamical interpretations that are consistent with alternative analysis techniques. Further, TDMD extracts modes that reveal detailed spatial structures missed by standard DMD.

Multiscale analysis of heart rate dynamics: entropy and time irreversibility measures.

PubMed

Costa, Madalena D; Peng, Chung-Kang; Goldberger, Ary L

2008-06-01

Cardiovascular signals are largely analyzed using traditional time and frequency domain measures. However, such measures fail to account for important properties related to multiscale organization and non-equilibrium dynamics. The complementary role of conventional signal analysis methods and emerging multiscale techniques, is, therefore, an important frontier area of investigation. The key finding of this presentation is that two recently developed multiscale computational tools--multiscale entropy and multiscale time irreversibility--are able to extract information from cardiac interbeat interval time series not contained in traditional methods based on mean, variance or Fourier spectrum (two-point correlation) techniques. These new methods, with careful attention to their limitations, may be useful in diagnostics, risk stratification and detection of toxicity of cardiac drugs.

Two-dimensional model of resonant electron collisions with diatomic molecules and molecular cations

NASA Astrophysics Data System (ADS)

Vana, Martin; Hvizdos, David; Houfek, Karel; Curik, Roman; Greene, Chris H.; Rescigno, Thomas N.; McCurdy, C. William

2016-05-01

A simple model for resonant collisions of electrons with diatomic molecules with one electronic and one nuclear degree of freedom (2D model) which was solved numerically exactly within the time-independent approach was used to probe the local complex potential approximation and nonlocal approximation to nuclear dynamics of these collisions. This model was reformulated in the time-dependent picture and extended to model also electron collisions with molecular cations, especially with H2+.This model enables an assessment of approximate methods, such as the boomerang model or the frame transformation theory. We will present both time-dependent and time-independent results and show how we can use the model to extract deeper insight into the dynamics of the resonant collisions.

Multiscale Analysis of Heart Rate Dynamics: Entropy and Time Irreversibility Measures

PubMed Central

Peng, Chung-Kang; Goldberger, Ary L.

2016-01-01

Cardiovascular signals are largely analyzed using traditional time and frequency domain measures. However, such measures fail to account for important properties related to multiscale organization and nonequilibrium dynamics. The complementary role of conventional signal analysis methods and emerging multiscale techniques, is, therefore, an important frontier area of investigation. The key finding of this presentation is that two recently developed multiscale computational tools— multiscale entropy and multiscale time irreversibility—are able to extract information from cardiac interbeat interval time series not contained in traditional methods based on mean, variance or Fourier spectrum (two-point correlation) techniques. These new methods, with careful attention to their limitations, may be useful in diagnostics, risk stratification and detection of toxicity of cardiac drugs. PMID:18172763

Extraction of α-humulene-enriched oil from clove using ultrasound-assisted supercritical carbon dioxide extraction and studies of its fictitious solubility.

PubMed

Wei, Ming-Chi; Xiao, Jianbo; Yang, Yu-Chiao

2016-11-01

Clove buds are used as a spice and food flavoring. In this study, clove oil and α-humulene was extracted from cloves using supercritical carbon dioxide extraction with and without ultrasound assistance (USC-CO2 and SC-CO2, respectively) at different temperatures (32-50°C) and pressures (9.0-25.0MPa). The results of these extractions were compared with those of heat reflux extraction and steam distillation methods conducted in parallel. The extracts obtained using these four techniques were analyzed using gas chromatography and gas chromatography/mass spectrometry (GC/MS). The results demonstrated that the USC-CO2 extraction procedure may extract clove oil and α-humulene from clove buds with better yields and shorter extraction times than conventional extraction techniques while utilizing less severe operating parameters. Furthermore, the experimental fictitious solubility data obtained using the dynamic method were well correlated with density-based models, including the Chrastil model, the Bartle model and the Kumar and Johnston model. Copyright © 2016 Elsevier Ltd. All rights reserved.

Analysis of Instantaneous Linear, Nonlinear and Complex Cardiovascular Dynamics from Videophotoplethysmography.

PubMed

Valenza, Gaetano; Iozzia, Luca; Cerina, Luca; Mainardi, Luca; Barbieri, Riccardo

2018-05-01

There is a fast growing interest in the use of non-contact devices for health and performance assessment in humans. In particular, the use of non-contact videophotoplethysmography (vPPG) has been recently demonstrated as a feasible way to extract cardiovascular information. Nevertheless, proper validation of vPPG-derived heartbeat dynamics is still missing. We aim to an in-depth validation of time-varying, linear and nonlinear/complex dynamics of the pulse rate variability extracted from vPPG. We apply inhomogeneous pointprocess nonlinear models to assess instantaneous measures defined in the time, frequency, and bispectral domains as estimated through vPPG and standard ECG. Instantaneous complexity measures, such as the instantaneous Lyapunov exponents and the recently defined inhomogeneous point-process approximate and sample entropy, were estimated as well. Video recordings were processed using our recently proposed method based on zerophase principal component analysis. Experimental data were gathered from 60 young healthy subjects (age: 24±3 years) undergoing postural changes (rest-to-stand maneuver). Group averaged results show that there is an overall agreement between linear and nonlinear/complexity indices computed from ECG and vPPG during resting state conditions. However, important differences are found, particularly in the bispectral and complexity domains, in recordings where the subjects has been instructed to stand up. Although significant differences exist between cardiovascular estimates from vPPG and ECG, it is very promising that instantaneous sympathovagal changes, as well as time-varying complex dynamics, were correctly identified, especially during resting state. In addition to a further improvement of the video signal quality, more research is advocated towards a more precise estimation of cardiovascular dynamics by a comprehensive nonlinear/complex paradigm specifically tailored to the non-contact quantification. Schattauer GmbH.

Sex differences in the oxygen delivery, extraction, and uptake during moderate-walking exercise transition.

PubMed

Beltrame, Thomas; Villar, Rodrigo; Hughson, Richard L

2017-09-01

Previous studies in children and older adults demonstrated faster oxygen uptake (V̇O 2 ) kinetics in males compared with females, but young healthy adults have not been studied. We hypothesized that young men would have faster aerobic system dynamics in response to the onset of exercise than women. Interactions between oxygen supply and utilization were characterized by the dynamics of V̇O 2 , deoxyhemoglobin (HHb), tissue saturation index (TSI), cardiac output (Q̇), and calculated arteriovenous O 2 difference (a-vO 2 diff ) in women and men. Eighteen healthy active young women and men (9 of each sex) with similar aerobic fitness levels volunteered for this study. Participants performed an incremental cardiopulmonary treadmill exercise test and 3 moderate-intensity treadmill exercise tests (at 80% V̇O 2 of gas exchange threshold). Data related to the moderate exercise were submitted to exponential data modelling to obtain parameters related to the aerobic system dynamics. The time constants of V̇O 2 , a-vO 2 diff , HHb, and TSI (30 ± 6, 29 ± 1, 16 ± 1, and 15 ± 2 s, respectively) in women were statistically (p < 0.05) faster than the time constants in men (42 ± 10, 49 ± 21, 19 ± 3, and 20 ± 4 s, respectively). Although Q̇ dynamics were not statistically different (p = 0.06) between groups, there was a trend to slower Q̇ dynamics in men corresponding with the slower V̇O 2 kinetics. These results indicated that the peripheral and pulmonary oxygen extraction dynamics were remarkably faster in women. Thus, contrary to the hypothesis, V̇O 2 dynamics measured at the mouth at the onset of submaximal treadmill walking were faster in women compared with men.

Thermal annihilation of photo-induced radicals following dynamic nuclear polarization to produce transportable frozen hyperpolarized 13C-substrates

PubMed Central

Capozzi, Andrea; Cheng, Tian; Boero, Giovanni; Roussel, Christophe; Comment, Arnaud

2017-01-01

Hyperpolarization via dynamic nuclear polarization (DNP) is pivotal for boosting magnetic resonance imaging (MRI) sensitivity and dissolution DNP can be used to perform in vivo real-time 13C MRI. The type of applications is however limited by the relatively fast decay time of the hyperpolarized spin state together with the constraint of having to polarize the 13C spins in a dedicated apparatus nearby but separated from the MRI magnet. We herein demonstrate that by polarizing 13C with photo-induced radicals, which can be subsequently annihilated using a thermalization process that maintains the sample temperature below its melting point, hyperpolarized 13C-substrates can be extracted from the DNP apparatus in the solid form, while maintaining the enhanced 13C polarization. The melting procedure necessary to transform the frozen solid into an injectable solution containing the hyperpolarized 13C-substrates can therefore be performed ex situ, up to several hours after extraction and storage of the polarized solid. PMID:28569840

Cardiorespiratory and cardiovascular interactions in cardiomyopathy patients using joint symbolic dynamic analysis.

PubMed

Giraldo, Beatriz F; Rodriguez, Javier; Caminal, Pere; Bayes-Genis, Antonio; Voss, Andreas

2015-01-01

Cardiovascular diseases are the first cause of death in developed countries. Using electrocardiographic (ECG), blood pressure (BP) and respiratory flow signals, we obtained parameters for classifying cardiomyopathy patients. 42 patients with ischemic (ICM) and dilated (DCM) cardiomyopathies were studied. The left ventricular ejection fraction (LVEF) was used to stratify patients with low risk (LR: LVEF>35%, 14 patients) and high risk (HR: LVEF≤ 35%, 28 patients) of heart attack. RR, SBP and TTot time series were extracted from the ECG, BP and respiratory flow signals, respectively. The time series were transformed to a binary space and then analyzed using Joint Symbolic Dynamic with a word length of three, characterizing them by the probability of occurrence of the words. Extracted parameters were then reduced using correlation and statistical analysis. Principal component analysis and support vector machines methods were applied to characterize the cardiorespiratory and cardiovascular interactions in ICM and DCM cardiomyopathies, obtaining an accuracy of 85.7%.

Simultaneous measurement of temperature and emissivity of lunar regolith simulant using dual-channel millimeter-wave radiometry.

PubMed

McCloy, J S; Sundaram, S K; Matyas, J; Woskov, P P

2011-05-01

Millimeter wave (MMW) radiometry can be used for simultaneous measurement of emissivity and temperature of materials under extreme environments (high temperature, pressure, and corrosive environments). The state-of-the-art dual channel MMW passive radiometer with active interferometric capabilities at 137 GHz described here allows for radiometric measurements of sample temperature and emissivity up to at least 1600 °C with simultaneous measurement of sample surface dynamics. These capabilities have been used to demonstrate dynamic measurement of melting of powders of simulated lunar regolith and static measurement of emissivity of solid samples. The paper presents the theoretical background and basis for the dual-receiver system, describes the hardware in detail, and demonstrates the data analysis. Post-experiment analysis of emissivity versus temperature allows further extraction from the radiometric data of millimeter wave viewing beam coupling factors, which provide corroboratory evidence to the interferometric data of the process dynamics observed. These results show the promise of the MMW system for extracting quantitative and qualitative process parameters for industrial processes and access to real-time dynamics of materials behavior in extreme environments.

GPU-accelerated phase extraction algorithm for interferograms: a real-time application

NASA Astrophysics Data System (ADS)

Zhu, Xiaoqiang; Wu, Yongqian; Liu, Fengwei

2016-11-01

Optical testing, having the merits of non-destruction and high sensitivity, provides a vital guideline for optical manufacturing. But the testing process is often computationally intensive and expensive, usually up to a few seconds, which is sufferable for dynamic testing. In this paper, a GPU-accelerated phase extraction algorithm is proposed, which is based on the advanced iterative algorithm. The accelerated algorithm can extract the right phase-distribution from thirteen 1024x1024 fringe patterns with arbitrary phase shifts in 233 milliseconds on average using NVIDIA Quadro 4000 graphic card, which achieved a 12.7x speedup ratio than the same algorithm executed on CPU and 6.6x speedup ratio than that on Matlab using DWANING W5801 workstation. The performance improvement can fulfill the demand of computational accuracy and real-time application.

A tool for NDVI time series extraction from wide-swath remotely sensed images

NASA Astrophysics Data System (ADS)

Li, Zhishan; Shi, Runhe; Zhou, Cong

2015-09-01

Normalized Difference Vegetation Index (NDVI) is one of the most widely used indicators for monitoring the vegetation coverage in land surface. The time series features of NDVI are capable of reflecting dynamic changes of various ecosystems. Calculating NDVI via Moderate Resolution Imaging Spectrometer (MODIS) and other wide-swath remotely sensed images provides an important way to monitor the spatial and temporal characteristics of large-scale NDVI. However, difficulties are still existed for ecologists to extract such information correctly and efficiently because of the problems in several professional processes on the original remote sensing images including radiometric calibration, geometric correction, multiple data composition and curve smoothing. In this study, we developed an efficient and convenient online toolbox for non-remote sensing professionals who want to extract NDVI time series with a friendly graphic user interface. It is based on Java Web and Web GIS technically. Moreover, Struts, Spring and Hibernate frameworks (SSH) are integrated in the system for the purpose of easy maintenance and expansion. Latitude, longitude and time period are the key inputs that users need to provide, and the NDVI time series are calculated automatically.

Assessing pharmacokinetics of indocyanine green-loaded nanoparticle in tumor with a dynamic diffuse fluorescence tomography system

NASA Astrophysics Data System (ADS)

Zhang, Yanqi; Yin, Guoyan; Zhao, Huijuan; Ma, Wenjuan; Gao, Feng; Zhang, Limin

2018-02-01

Real-time and continuous monitoring of drug release in vivo is an important task in pharmaceutical development. Here, we devoted to explore a real-time continuous study of the pharmacokinetics of free indocyanine green (ICG) and ICG loaded in the shell-sheddable nanoparticles in tumor based on a dynamic diffuse fluorescence tomography (DFT) system: A highly-sensitive dynamic DFT system of CT-scanning mode generates informative and instantaneous sampling datasets; An analysis procedure extracts the pharmacokinetic parameters from the reconstructed time curves of the mean ICG concentration in tumor, using the Gauss-Newton scheme based on two-compartment model. Compared with the pharmacokinetic parameters of free ICG in tumor, the ICG loaded in the shell-sheddable nanoparticles shows efficient accumulation in tumor. The results demonstrate our proposed dynamic-DFT can provide an integrated and continuous view of the drug delivery of the injected agents in different formulations, which is helpful for the development of diagnosis and therapy for tumors.

Detection of internal cracks in rubber composite structures using an impact acoustic modality

NASA Astrophysics Data System (ADS)

Shen, Q.; Kurfess, T. R.; Omar, M.; Gramling, F.

2014-01-01

The objective of this study is to investigate the use of impact acoustic signals to non-intrusively inspect rubber composite structures for the presence of internal cracks, such as those found in an automobile tyre. Theoretical contact dynamic models for both integral and defective rubber structures are developed based on Hertz's impact model, further modified for rubber composite materials. The model generates the prediction of major impact dynamic quantities, namely the maximum impact force, impact duration and contact deformation; such parameters are also theoretically proven to be correlated with the presence of internal cracks. The tyre structures are simplified into cubic rubber blocks, to mitigate complexity for analytical modelling. Both impact force and impact sound signals are measured experimentally, and extraction of useful features from both signals for defect identification is achieved. The impact force produces two direct measurements of theoretical impact dynamic quantities. A good correlation between these experimental discriminators and the theoretical dynamic quantities provide validation for the contact dynamics models. Defect discriminators extracted from the impact sound are dependent on both time- and frequency-domain analyses. All the discriminators are closely connected with the theoretical dynamic quantities and experimentally verified as good indicators of internal cracks in rubber composite structures.

Extracting neuronal functional network dynamics via adaptive Granger causality analysis.

PubMed

Sheikhattar, Alireza; Miran, Sina; Liu, Ji; Fritz, Jonathan B; Shamma, Shihab A; Kanold, Patrick O; Babadi, Behtash

2018-04-24

Quantifying the functional relations between the nodes in a network based on local observations is a key challenge in studying complex systems. Most existing time series analysis techniques for this purpose provide static estimates of the network properties, pertain to stationary Gaussian data, or do not take into account the ubiquitous sparsity in the underlying functional networks. When applied to spike recordings from neuronal ensembles undergoing rapid task-dependent dynamics, they thus hinder a precise statistical characterization of the dynamic neuronal functional networks underlying adaptive behavior. We develop a dynamic estimation and inference paradigm for extracting functional neuronal network dynamics in the sense of Granger, by integrating techniques from adaptive filtering, compressed sensing, point process theory, and high-dimensional statistics. We demonstrate the utility of our proposed paradigm through theoretical analysis, algorithm development, and application to synthetic and real data. Application of our techniques to two-photon Ca 2+ imaging experiments from the mouse auditory cortex reveals unique features of the functional neuronal network structures underlying spontaneous activity at unprecedented spatiotemporal resolution. Our analysis of simultaneous recordings from the ferret auditory and prefrontal cortical areas suggests evidence for the role of rapid top-down and bottom-up functional dynamics across these areas involved in robust attentive behavior.

Thermally induced magnetic relaxation in square artificial spin ice

DOE PAGES

Andersson, M. S.; Pappas, S. D.; Stopfel, H.; ...

2016-11-24

The properties of natural and artificial assemblies of interacting elements, ranging from Quarks to Galaxies, are at the heart of Physics. The collective response and dynamics of such assemblies are dictated by the intrinsic dynamical properties of the building blocks, the nature of their interactions and topological constraints. Here in this paper, we report on the relaxation dynamics of the magnetization of artificial assemblies of mesoscopic spins. In our model nano-magnetic system $-$ square artificial spin ice $-$ we are able to control the geometrical arrangement and interaction strength between the magnetically interacting building blocks by means of nano-lithography. Usingmore » time resolved magnetometry we show that the relaxation process can be described using the Kohlrausch law and that the extracted temperature dependent relaxation times of the assemblies follow the Vogel-Fulcher law. The results provide insight into the relaxation dynamics of mesoscopic nano-magnetic model systems, with adjustable energy and time scales, and demonstrates that these can serve as an ideal playground for the studies of collective dynamics and relaxations.« less

Thermally induced magnetic relaxation in square artificial spin ice

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

Andersson, M. S.; Pappas, S. D.; Stopfel, H.

The properties of natural and artificial assemblies of interacting elements, ranging from Quarks to Galaxies, are at the heart of Physics. The collective response and dynamics of such assemblies are dictated by the intrinsic dynamical properties of the building blocks, the nature of their interactions and topological constraints. Here in this paper, we report on the relaxation dynamics of the magnetization of artificial assemblies of mesoscopic spins. In our model nano-magnetic system $-$ square artificial spin ice $-$ we are able to control the geometrical arrangement and interaction strength between the magnetically interacting building blocks by means of nano-lithography. Usingmore » time resolved magnetometry we show that the relaxation process can be described using the Kohlrausch law and that the extracted temperature dependent relaxation times of the assemblies follow the Vogel-Fulcher law. The results provide insight into the relaxation dynamics of mesoscopic nano-magnetic model systems, with adjustable energy and time scales, and demonstrates that these can serve as an ideal playground for the studies of collective dynamics and relaxations.« less

Effective Information Extraction Framework for Heterogeneous Clinical Reports Using Online Machine Learning and Controlled Vocabularies

PubMed Central

Zheng, Shuai; Ghasemzadeh, Nima; Hayek, Salim S; Quyyumi, Arshed A

2017-01-01

Background Extracting structured data from narrated medical reports is challenged by the complexity of heterogeneous structures and vocabularies and often requires significant manual effort. Traditional machine-based approaches lack the capability to take user feedbacks for improving the extraction algorithm in real time. Objective Our goal was to provide a generic information extraction framework that can support diverse clinical reports and enables a dynamic interaction between a human and a machine that produces highly accurate results. Methods A clinical information extraction system IDEAL-X has been built on top of online machine learning. It processes one document at a time, and user interactions are recorded as feedbacks to update the learning model in real time. The updated model is used to predict values for extraction in subsequent documents. Once prediction accuracy reaches a user-acceptable threshold, the remaining documents may be batch processed. A customizable controlled vocabulary may be used to support extraction. Results Three datasets were used for experiments based on report styles: 100 cardiac catheterization procedure reports, 100 coronary angiographic reports, and 100 integrated reports—each combines history and physical report, discharge summary, outpatient clinic notes, outpatient clinic letter, and inpatient discharge medication report. Data extraction was performed by 3 methods: online machine learning, controlled vocabularies, and a combination of these. The system delivers results with F1 scores greater than 95%. Conclusions IDEAL-X adopts a unique online machine learning–based approach combined with controlled vocabularies to support data extraction for clinical reports. The system can quickly learn and improve, thus it is highly adaptable. PMID:28487265

A data mining framework for time series estimation.

PubMed

Hu, Xiao; Xu, Peng; Wu, Shaozhi; Asgari, Shadnaz; Bergsneider, Marvin

2010-04-01

Time series estimation techniques are usually employed in biomedical research to derive variables less accessible from a set of related and more accessible variables. These techniques are traditionally built from systems modeling approaches including simulation, blind decovolution, and state estimation. In this work, we define target time series (TTS) and its related time series (RTS) as the output and input of a time series estimation process, respectively. We then propose a novel data mining framework for time series estimation when TTS and RTS represent different sets of observed variables from the same dynamic system. This is made possible by mining a database of instances of TTS, its simultaneously recorded RTS, and the input/output dynamic models between them. The key mining strategy is to formulate a mapping function for each TTS-RTS pair in the database that translates a feature vector extracted from RTS to the dissimilarity between true TTS and its estimate from the dynamic model associated with the same TTS-RTS pair. At run time, a feature vector is extracted from an inquiry RTS and supplied to the mapping function associated with each TTS-RTS pair to calculate a dissimilarity measure. An optimal TTS-RTS pair is then selected by analyzing these dissimilarity measures. The associated input/output model of the selected TTS-RTS pair is then used to simulate the TTS given the inquiry RTS as an input. An exemplary implementation was built to address a biomedical problem of noninvasive intracranial pressure assessment. The performance of the proposed method was superior to that of a simple training-free approach of finding the optimal TTS-RTS pair by a conventional similarity-based search on RTS features. 2009 Elsevier Inc. All rights reserved.

Synthesis and characterization of novel silver nanoparticles using Chamaemelum nobile extract for antibacterial application

NASA Astrophysics Data System (ADS)

Erjaee, Hoda; Rajaian, Hamid; Nazifi, Saeed

2017-06-01

The present study reports green synthesis of silver nanoparticles (AgNPs) at room temperature using aqueous Chamaemelum nobile extract for the first time. The effect of silver nitrate concentration, quantity of the plant extract and the reaction time on particle size was optimized and studied by UV-Vis spectroscopy and dynamic light scattering. The appearance of brownish color with λ max of 422 nm confirmed the formation of AgNPs. Synthesized nanoparticles were further characterized by Fourier transform infrared spectroscopy, x-ray diffraction and transmission electron microscopy. In addition, antimicrobial activity of the AgNPs against Escherichia coli, Salmonella typhimurium, Staphylococcus aureus and Bacillus subtilis was evaluated based on the inhibition zone using the disc-diffusion assay and measurement of minimal inhibition concentration and minimal bactericidal concentration by standard microdilution method. In conclusion, synthesis of nanoparticle with aqueous Chamaemelum nobile extract is simple, rapid, environmentally benign and inexpensive. Moreover, these synthesized nanoparticles exhibit significant antibacterial activity.

Automatic Contour Extraction of Facial Organs for Frontal Facial Images with Various Facial Expressions

NASA Astrophysics Data System (ADS)

Kobayashi, Hiroshi; Suzuki, Seiji; Takahashi, Hisanori; Tange, Akira; Kikuchi, Kohki

This study deals with a method to realize automatic contour extraction of facial features such as eyebrows, eyes and mouth for the time-wise frontal face with various facial expressions. Because Snakes which is one of the most famous methods used to extract contours, has several disadvantages, we propose a new method to overcome these issues. We define the elastic contour model in order to hold the contour shape and then determine the elastic energy acquired by the amount of modification of the elastic contour model. Also we utilize the image energy obtained by brightness differences of the control points on the elastic contour model. Applying the dynamic programming method, we determine the contour position where the total value of the elastic energy and the image energy becomes minimum. Employing 1/30s time-wise facial frontal images changing from neutral to one of six typical facial expressions obtained from 20 subjects, we have estimated our method and find it enables high accuracy automatic contour extraction of facial features.

Method optimization for non-equilibrium solid phase microextraction sampling of HAPs for GC/MS analysis

NASA Astrophysics Data System (ADS)

Zawadowicz, M. A.; Del Negro, L. A.

2010-12-01

Hazardous air pollutants (HAPs) are usually present in the atmosphere at pptv-level, requiring measurements with high sensitivity and minimal contamination. Commonly used evacuated canister methods require an overhead in space, money and time that often is prohibitive to primarily-undergraduate institutions. This study optimized an analytical method based on solid-phase microextraction (SPME) of ambient gaseous matrix, which is a cost-effective technique of selective VOC extraction, accessible to an unskilled undergraduate. Several approaches to SPME extraction and sample analysis were characterized and several extraction parameters optimized. Extraction time, temperature and laminar air flow velocity around the fiber were optimized to give highest signal and efficiency. Direct, dynamic extraction of benzene from a moving air stream produced better precision (±10%) than sampling of stagnant air collected in a polymeric bag (±24%). Using a low-polarity chromatographic column in place of a standard (5%-Phenyl)-methylpolysiloxane phase decreased the benzene detection limit from 2 ppbv to 100 pptv. The developed method is simple and fast, requiring 15-20 minutes per extraction and analysis. It will be field-validated and used as a field laboratory component of various undergraduate Chemistry and Environmental Studies courses.

Thermal degradation of the solvent employed in the next-generation caustic-side solvent extraction process and its effect on the extraction, scrubbing, and stripping of cesium

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

Roach, Benjamin D.; Williams, Neil J.; Moyer, Bruce A.

As part of the ongoing development of the Next-Generation Caustic-Side Solvent Extraction (NGS) process, the thermal stability of the process solvent was investigated and shown to be adequate for industrial application. The solvent was thermally treated at 35 C over a period of 13 months whilst in dynamic contact with each of the aqueous phases of the current NGS process, namely SRS 15 (a highly caustic waste simulant), sodium hydroxide scrub solution (0.025 M), and boric acid strip solution (0.01 M). The effect of thermal treatment was evaluated by assessing batch extract/scrub/strip performance as a function of time, by monitoringmore » the sodium extraction capacity of the solvent, and by analysis of the solvent using electrospray mass spectrometry. Current studies indicate that the NGS solvent should be thermally robust for a period of XXX months at the Modular Caustic-Side Solvent Extraction Unit (MCU) pilot plant located at Savannah River Site. Furthermore, the guanidine suppressor appears to be the solvent component most significantly impacted by thermal treatment of the solvent, showing significant degradation over time.« less

Thermal degradation of the solvent employed in the next-generation caustic-side solvent extraction process and its effect on the extraction, scrubbing, and stripping of cesium

DOE PAGES

Roach, Benjamin D.; Williams, Neil J.; Moyer, Bruce A.

2015-09-02

As part of the ongoing development of the Next-Generation Caustic-Side Solvent Extraction (NGS) process, the thermal stability of the process solvent was investigated and shown to be adequate for industrial application. The solvent was thermally treated at 35 C over a period of 13 months whilst in dynamic contact with each of the aqueous phases of the current NGS process, namely SRS 15 (a highly caustic waste simulant), sodium hydroxide scrub solution (0.025 M), and boric acid strip solution (0.01 M). The effect of thermal treatment was evaluated by assessing batch extract/scrub/strip performance as a function of time, by monitoringmore » the sodium extraction capacity of the solvent, and by analysis of the solvent using electrospray mass spectrometry. Current studies indicate that the NGS solvent should be thermally robust for a period of XXX months at the Modular Caustic-Side Solvent Extraction Unit (MCU) pilot plant located at Savannah River Site. Furthermore, the guanidine suppressor appears to be the solvent component most significantly impacted by thermal treatment of the solvent, showing significant degradation over time.« less

Phonon-magnon interaction in low dimensional quantum magnets observed by dynamic heat transport measurements.

PubMed

Montagnese, Matteo; Otter, Marian; Zotos, Xenophon; Fishman, Dmitry A; Hlubek, Nikolai; Mityashkin, Oleg; Hess, Christian; Saint-Martin, Romuald; Singh, Surjeet; Revcolevschi, Alexandre; van Loosdrecht, Paul H M

2013-04-05

Thirty-five years ago, Sanders and Walton [Phys. Rev. B 15, 1489 (1977)] proposed a method to measure the phonon-magnon interaction in antiferromagnets through thermal transport which so far has not been verified experimentally. We show that a dynamical variant of this approach allows direct extraction of the phonon-magnon equilibration time, yielding 400 μs for the cuprate spin-ladder system Ca(9)La(5)Cu(24)O(41). The present work provides a general method to directly address the spin-phonon interaction by means of dynamical transport experiments.

Multiobjective Optimization of Low-Energy Trajectories Using Optimal Control on Dynamical Channels

NASA Technical Reports Server (NTRS)

Coffee, Thomas M.; Anderson, Rodney L.; Lo, Martin W.

2011-01-01

We introduce a computational method to design efficient low-energy trajectories by extracting initial solutions from dynamical channels formed by invariant manifolds, and improving these solutions through variational optimal control. We consider trajectories connecting two unstable periodic orbits in the circular restricted 3-body problem (CR3BP). Our method leverages dynamical channels to generate a range of solutions, and approximates the areto front for impulse and time of flight through a multiobjective optimization of these solutions based on primer vector theory. We demonstrate the application of our method to a libration orbit transfer in the Earth-Moon system.

The optimization of essential oils supercritical CO2 extraction from Lavandula hybrida through static-dynamic steps procedure and semi-continuous technique using response surface method

PubMed Central

Kamali, Hossein; Aminimoghadamfarouj, Noushin; Golmakani, Ebrahim; Nematollahi, Alireza

2015-01-01

Aim: The aim of this study was to examine and evaluate crucial variables in essential oils extraction process from Lavandula hybrida through static-dynamic and semi-continuous techniques using response surface method. Materials and Methods: Essential oil components were extracted from Lavandula hybrida (Lavandin) flowers using supercritical carbon dioxide via static-dynamic steps (SDS) procedure, and semi-continuous (SC) technique. Results: Using response surface method the optimum extraction yield (4.768%) was obtained via SDS at 108.7 bar, 48.5°C, 120 min (static: 8×15), 24 min (dynamic: 8×3 min) in contrast to the 4.620% extraction yield for the SC at 111.6 bar, 49.2°C, 14 min (static), 121.1 min (dynamic). Conclusion: The results indicated that a substantial reduction (81.56%) solvent usage (kg CO2/g oil) is observed in the SDS method versus the conventional SC method. PMID:25598636

Velocity measurements of heterogeneous RBC flow in capillary vessels using dynamic laser speckle signal.

PubMed

Li, Chenxi; Wang, Ruikang

2017-04-01

We propose an approach to measure heterogeneous velocities of red blood cells (RBCs) in capillary vessels using full-field time-varying dynamic speckle signals. The approach utilizes a low coherent laser speckle imaging system to record the instantaneous speckle pattern, followed by an eigen-decomposition-based filtering algorithm to extract dynamic speckle signal due to the moving RBCs. The velocity of heterogeneous RBC flows is determined by cross-correlating the temporal dynamic speckle signals obtained at adjacent locations. We verify the approach by imaging mouse pinna in vivo, demonstrating its capability for full-field RBC flow mapping and quantifying flow pattern with high resolution. It is expected to investigate the dynamic action of RBCs flow in capillaries under physiological changes.

Interstitial and Interlayer Ion Diffusion Geometry Extraction in Graphitic Nanosphere Battery Materials.

PubMed

Gyulassy, Attila; Knoll, Aaron; Lau, Kah Chun; Wang, Bei; Bremer, Peer-Timo; Papka, Michael E; Curtiss, Larry A; Pascucci, Valerio

2016-01-01

Large-scale molecular dynamics (MD) simulations are commonly used for simulating the synthesis and ion diffusion of battery materials. A good battery anode material is determined by its capacity to store ion or other diffusers. However, modeling of ion diffusion dynamics and transport properties at large length and long time scales would be impossible with current MD codes. To analyze the fundamental properties of these materials, therefore, we turn to geometric and topological analysis of their structure. In this paper, we apply a novel technique inspired by discrete Morse theory to the Delaunay triangulation of the simulated geometry of a thermally annealed carbon nanosphere. We utilize our computed structures to drive further geometric analysis to extract the interstitial diffusion structure as a single mesh. Our results provide a new approach to analyze the geometry of the simulated carbon nanosphere, and new insights into the role of carbon defect size and distribution in determining the charge capacity and charge dynamics of these carbon based battery materials.

Interstitial and Interlayer Ion Diffusion Geometry Extraction in Graphitic Nanosphere Battery Materials

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

Gyulassy, Attila; Knoll, Aaron; Lau, Kah Chun

2016-01-01

Large-scale molecular dynamics (MD) simulations are commonly used for simulating the synthesis and ion diffusion of battery materials. A good battery anode material is determined by its capacity to store ion or other diffusers. However, modeling of ion diffusion dynamics and transport properties at large length and long time scales would be impossible with current MD codes. To analyze the fundamental properties of these materials, therefore, we turn to geometric and topological analysis of their structure. In this paper, we apply a novel technique inspired by discrete Morse theory to the Delaunay triangulation of the simulated geometry of a thermallymore » annealed carbon nanosphere. We utilize our computed structures to drive further geometric analysis to extract the interstitial diffusion structure as a single mesh. Our results provide a new approach to analyze the geometry of the simulated carbon nanosphere, and new insights into the role of carbon defect size and distribution in determining the charge capacity and charge dynamics of these carbon based battery materials.« less

Interstitial and interlayer ion diffusion geometry extraction in graphitic nanosphere battery materials

DOE PAGES

Gyulassy, Attila; Knoll, Aaron; Lau, Kah Chun; ...

2016-01-31

Large-scale molecular dynamics (MD) simulations are commonly used for simulating the synthesis and ion diffusion of battery materials. A good battery anode material is determined by its capacity to store ion or other diffusers. However, modeling of ion diffusion dynamics and transport properties at large length and long time scales would be impossible with current MD codes. To analyze the fundamental properties of these materials, therefore, we turn to geometric and topological analysis of their structure. In this paper, we apply a novel technique inspired by discrete Morse theory to the Delaunay triangulation of the simulated geometry of a thermallymore » annealed carbon nanosphere. We utilize our computed structures to drive further geometric analysis to extract the interstitial diffusion structure as a single mesh. Lastly, our results provide a new approach to analyze the geometry of the simulated carbon nanosphere, and new insights into the role of carbon defect size and distribution in determining the charge capacity and charge dynamics of these carbon based battery materials.« less

U(VI) Reduction by Biogenic and Abiotic Hydroxycarbonate Green Rusts: Impacts on U(IV) Speciation and Stability Over Time

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

Yan, Sen; Boyanov, Maxim I.; Mishra, Bhoopesh

Green rusts (GRs) are redox active Fe II-Fe III minerals that form in the environment via various biotic and abiotic processes. Although both biogenic (BioGR) and abiotic (ChemGR) GRs have been shown to reduce U VI, the dynamics of the transformations and the speciation and stability of the resulting U IV phases are poorly understood. We used carbonate extraction and XAFS spectroscopy to investigate the products of U VI reduction by BioGR and ChemGR. The results show that both GRs can rapidly remove U VI from synthetic groundwater via reduction to U IV. The initial products in the ChemGR systemmore » are solids-associated U IV-carbonate complexes that gradually transform to nanocrystalline uraninite over time, leading to a decrease in the proportion of carbonate-extractable U from ~95% to ~10%. In contrast, solid-phase U IV atoms in the BioGR system remain relatively extractable, non-uraninite U IV species over the same reaction period. The presence of calcium and carbonate in groundwater significantly increase the extractability of U IV in the BioGR system. Furthermore, these data provide new insights into the transformations of U under anoxic conditions in groundwater that contains calcium and carbonate, and have major implications for predicting uranium stability within redox dynamic environments and designing approaches for the remediation of uranium-contaminated groundwater.« less

U(VI) Reduction by Biogenic and Abiotic Hydroxycarbonate Green Rusts: Impacts on U(IV) Speciation and Stability Over Time

DOE PAGES

Yan, Sen; Boyanov, Maxim I.; Mishra, Bhoopesh; ...

2018-04-09

Green rusts (GRs) are redox active Fe II-Fe III minerals that form in the environment via various biotic and abiotic processes. Although both biogenic (BioGR) and abiotic (ChemGR) GRs have been shown to reduce U VI, the dynamics of the transformations and the speciation and stability of the resulting U IV phases are poorly understood. We used carbonate extraction and XAFS spectroscopy to investigate the products of U VI reduction by BioGR and ChemGR. The results show that both GRs can rapidly remove U VI from synthetic groundwater via reduction to U IV. The initial products in the ChemGR systemmore » are solids-associated U IV-carbonate complexes that gradually transform to nanocrystalline uraninite over time, leading to a decrease in the proportion of carbonate-extractable U from ~95% to ~10%. In contrast, solid-phase U IV atoms in the BioGR system remain relatively extractable, non-uraninite U IV species over the same reaction period. The presence of calcium and carbonate in groundwater significantly increase the extractability of U IV in the BioGR system. Furthermore, these data provide new insights into the transformations of U under anoxic conditions in groundwater that contains calcium and carbonate, and have major implications for predicting uranium stability within redox dynamic environments and designing approaches for the remediation of uranium-contaminated groundwater.« less

A combinatorial framework to quantify peak/pit asymmetries in complex dynamics.

PubMed

Hasson, Uri; Iacovacci, Jacopo; Davis, Ben; Flanagan, Ryan; Tagliazucchi, Enzo; Laufs, Helmut; Lacasa, Lucas

2018-02-23

We explore a combinatorial framework which efficiently quantifies the asymmetries between minima and maxima in local fluctuations of time series. We first showcase its performance by applying it to a battery of synthetic cases. We find rigorous results on some canonical dynamical models (stochastic processes with and without correlations, chaotic processes) complemented by extensive numerical simulations for a range of processes which indicate that the methodology correctly distinguishes different complex dynamics and outperforms state of the art metrics in several cases. Subsequently, we apply this methodology to real-world problems emerging across several disciplines including cases in neurobiology, finance and climate science. We conclude that differences between the statistics of local maxima and local minima in time series are highly informative of the complex underlying dynamics and a graph-theoretic extraction procedure allows to use these features for statistical learning purposes.

Dimensionless embedding for nonlinear time series analysis

NASA Astrophysics Data System (ADS)

Hirata, Yoshito; Aihara, Kazuyuki

2017-09-01

Recently, infinite-dimensional delay coordinates (InDDeCs) have been proposed for predicting high-dimensional dynamics instead of conventional delay coordinates. Although InDDeCs can realize faster computation and more accurate short-term prediction, it is still not well-known whether InDDeCs can be used in other applications of nonlinear time series analysis in which reconstruction is needed for the underlying dynamics from a scalar time series generated from a dynamical system. Here, we give theoretical support for justifying the use of InDDeCs and provide numerical examples to show that InDDeCs can be used for various applications for obtaining the recurrence plots, correlation dimensions, and maximal Lyapunov exponents, as well as testing directional couplings and extracting slow-driving forces. We demonstrate performance of the InDDeCs using the weather data. Thus, InDDeCs can eventually realize "dimensionless embedding" while we enjoy faster and more reliable computations.

Low-dimensional dynamical characterization of human performance of cancer patients using motion data.

PubMed

Hasnain, Zaki; Li, Ming; Dorff, Tanya; Quinn, David; Ueno, Naoto T; Yennu, Sriram; Kolatkar, Anand; Shahabi, Cyrus; Nocera, Luciano; Nieva, Jorge; Kuhn, Peter; Newton, Paul K

2018-05-18

Biomechanical characterization of human performance with respect to fatigue and fitness is relevant in many settings, however is usually limited to either fully qualitative assessments or invasive methods which require a significant experimental setup consisting of numerous sensors, force plates, and motion detectors. Qualitative assessments are difficult to standardize due to their intrinsic subjective nature, on the other hand, invasive methods provide reliable metrics but are not feasible for large scale applications. Presented here is a dynamical toolset for detecting performance groups using a non-invasive system based on the Microsoft Kinect motion capture sensor, and a case study of 37 cancer patients performing two clinically monitored tasks before and after therapy regimens. Dynamical features are extracted from the motion time series data and evaluated based on their ability to i) cluster patients into coherent fitness groups using unsupervised learning algorithms and to ii) predict Eastern Cooperative Oncology Group performance status via supervised learning. The unsupervised patient clustering is comparable to clustering based on physician assigned Eastern Cooperative Oncology Group status in that they both have similar concordance with change in weight before and after therapy as well as unexpected hospitalizations throughout the study. The extracted dynamical features can predict physician, coordinator, and patient Eastern Cooperative Oncology Group status with an accuracy of approximately 80%. The non-invasive Microsoft Kinect sensor and the proposed dynamical toolset comprised of data preprocessing, feature extraction, dimensionality reduction, and machine learning offers a low-cost and general method for performance segregation and can complement existing qualitative clinical assessments. Copyright © 2018 Elsevier Ltd. All rights reserved.

Optimal estimation of recurrence structures from time series

NASA Astrophysics Data System (ADS)

beim Graben, Peter; Sellers, Kristin K.; Fröhlich, Flavio; Hutt, Axel

2016-05-01

Recurrent temporal dynamics is a phenomenon observed frequently in high-dimensional complex systems and its detection is a challenging task. Recurrence quantification analysis utilizing recurrence plots may extract such dynamics, however it still encounters an unsolved pertinent problem: the optimal selection of distance thresholds for estimating the recurrence structure of dynamical systems. The present work proposes a stochastic Markov model for the recurrent dynamics that allows for the analytical derivation of a criterion for the optimal distance threshold. The goodness of fit is assessed by a utility function which assumes a local maximum for that threshold reflecting the optimal estimate of the system's recurrence structure. We validate our approach by means of the nonlinear Lorenz system and its linearized stochastic surrogates. The final application to neurophysiological time series obtained from anesthetized animals illustrates the method and reveals novel dynamic features of the underlying system. We propose the number of optimal recurrence domains as a statistic for classifying an animals' state of consciousness.

Dynamic Stability Analysis of Linear Time-varying Systems via an Extended Modal Identification Approach

NASA Astrophysics Data System (ADS)

Ma, Zhisai; Liu, Li; Zhou, Sida; Naets, Frank; Heylen, Ward; Desmet, Wim

2017-03-01

The problem of linear time-varying(LTV) system modal analysis is considered based on time-dependent state space representations, as classical modal analysis of linear time-invariant systems and current LTV system modal analysis under the "frozen-time" assumption are not able to determine the dynamic stability of LTV systems. Time-dependent state space representations of LTV systems are first introduced, and the corresponding modal analysis theories are subsequently presented via a stability-preserving state transformation. The time-varying modes of LTV systems are extended in terms of uniqueness, and are further interpreted to determine the system's stability. An extended modal identification is proposed to estimate the time-varying modes, consisting of the estimation of the state transition matrix via a subspace-based method and the extraction of the time-varying modes by the QR decomposition. The proposed approach is numerically validated by three numerical cases, and is experimentally validated by a coupled moving-mass simply supported beam experimental case. The proposed approach is capable of accurately estimating the time-varying modes, and provides a new way to determine the dynamic stability of LTV systems by using the estimated time-varying modes.

Combined non-parametric and parametric approach for identification of time-variant systems

NASA Astrophysics Data System (ADS)

Dziedziech, Kajetan; Czop, Piotr; Staszewski, Wieslaw J.; Uhl, Tadeusz

2018-03-01

Identification of systems, structures and machines with variable physical parameters is a challenging task especially when time-varying vibration modes are involved. The paper proposes a new combined, two-step - i.e. non-parametric and parametric - modelling approach in order to determine time-varying vibration modes based on input-output measurements. Single-degree-of-freedom (SDOF) vibration modes from multi-degree-of-freedom (MDOF) non-parametric system representation are extracted in the first step with the use of time-frequency wavelet-based filters. The second step involves time-varying parametric representation of extracted modes with the use of recursive linear autoregressive-moving-average with exogenous inputs (ARMAX) models. The combined approach is demonstrated using system identification analysis based on the experimental mass-varying MDOF frame-like structure subjected to random excitation. The results show that the proposed combined method correctly captures the dynamics of the analysed structure, using minimum a priori information on the model.

Polymeric ionic liquid modified graphene oxide-grafted silica for solid-phase extraction to analyze the excretion-dynamics of flavonoids in urine by Box-Behnken statistical design.

PubMed

Hou, Xiudan; Liu, Shujuan; Zhou, Panpan; Li, Jin; Liu, Xia; Wang, Licheng; Guo, Yong

2016-07-22

A solid-phase extraction method for the efficient analysis of the excretion-dynamics of flavonoids in urine was established and described. In this work, in situ surface radical chain-transfer polymerization and in situ anion exchange were utilized to tune the extraction performance of poly(1-vinyl-3-hexylimidazolium bromide)-graphene oxide-grafted silica (poly(VHIm(+)Br(-))@GO@Sil). Graphene oxide (GO) was first coated onto the silica using a layer-by-layer fabrication method, and then the anion of poly(VHIm(+)Br(-))@GO@Sil was changed into hexafluorophosphate (PF6(-)) by in situ anion exchange. The interaction energies between two PILs and four flavonoids were calculated with the Gaussian09 suite of programs. A Box-Behnken design was used for the optimization of four greatly influential parameters after single-factor experiments to obtain more accurate and precise results. Coupled to high performance liquid chromatography, the poly(VHIm(+)PF6(-))@GO@Sil method showed acceptable extraction recoveries for the four flavonoids, with limits of detection in the range of 0.1-0.5μgL(-1), and wide linear ranges with correlation coefficients (R) ranging from 0.9935 to 0.9987. Under the optimum conditions, the proposed method was applied to analyze the urines collected from a healthy volunteer. The excretion amount-time profiles revealed that 4-15h was the main excretion time for the detected flavonoids. The results indicated that the newly developed method offered the advantages of being feasible, green and cost-effective, and could be successfully applied to the extraction and enrichment of flavonoids in human body systems allowing the study of the metabolic kinetics. Copyright © 2016. Published by Elsevier B.V.

Analysis of spike-wave discharges in rats using discrete wavelet transform.

PubMed

Ubeyli, Elif Derya; Ilbay, Gül; Sahin, Deniz; Ateş, Nurbay

2009-03-01

A feature is a distinctive or characteristic measurement, transform, structural component extracted from a segment of a pattern. Features are used to represent patterns with the goal of minimizing the loss of important information. The discrete wavelet transform (DWT) as a feature extraction method was used in representing the spike-wave discharges (SWDs) records of Wistar Albino Glaxo/Rijswijk (WAG/Rij) rats. The SWD records of WAG/Rij rats were decomposed into time-frequency representations using the DWT and the statistical features were calculated to depict their distribution. The obtained wavelet coefficients were used to identify characteristics of the signal that were not apparent from the original time domain signal. The present study demonstrates that the wavelet coefficients are useful in determining the dynamics in the time-frequency domain of SWD records.

Investigation of Time Series Representations and Similarity Measures for Structural Damage Pattern Recognition

PubMed Central

Swartz, R. Andrew

2013-01-01

This paper investigates the time series representation methods and similarity measures for sensor data feature extraction and structural damage pattern recognition. Both model-based time series representation and dimensionality reduction methods are studied to compare the effectiveness of feature extraction for damage pattern recognition. The evaluation of feature extraction methods is performed by examining the separation of feature vectors among different damage patterns and the pattern recognition success rate. In addition, the impact of similarity measures on the pattern recognition success rate and the metrics for damage localization are also investigated. The test data used in this study are from the System Identification to Monitor Civil Engineering Structures (SIMCES) Z24 Bridge damage detection tests, a rigorous instrumentation campaign that recorded the dynamic performance of a concrete box-girder bridge under progressively increasing damage scenarios. A number of progressive damage test case datasets and damage test data with different damage modalities are used. The simulation results show that both time series representation methods and similarity measures have significant impact on the pattern recognition success rate. PMID:24191136

Evaluating Dynamic Bivariate Correlations in Resting-state fMRI: A comparison study and a new approach

PubMed Central

Lindquist, Martin A.; Xu, Yuting; Nebel, Mary Beth; Caffo, Brain S.

2014-01-01

To date, most functional Magnetic Resonance Imaging (fMRI) studies have assumed that the functional connectivity (FC) between time series from distinct brain regions is constant across time. However, recently, there has been increased interest in quantifying possible dynamic changes in FC during fMRI experiments, as it is thought this may provide insight into the fundamental workings of brain networks. In this work we focus on the specific problem of estimating the dynamic behavior of pair-wise correlations between time courses extracted from two different regions of the brain. We critique the commonly used sliding-windows technique, and discuss some alternative methods used to model volatility in the finance literature that could also prove useful in the neuroimaging setting. In particular, we focus on the Dynamic Conditional Correlation (DCC) model, which provides a model-based approach towards estimating dynamic correlations. We investigate the properties of several techniques in a series of simulation studies and find that DCC achieves the best overall balance between sensitivity and specificity in detecting dynamic changes in correlations. We also investigate its scalability beyond the bivariate case to demonstrate its utility for studying dynamic correlations between more than two brain regions. Finally, we illustrate its performance in an application to test-retest resting state fMRI data. PMID:24993894

Charge carrier recombination dynamics in perovskite and polymer solar cells

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

Paulke, Andreas; Kniepert, Juliane; Kurpiers, Jona

2016-03-14

Time-delayed collection field experiments are applied to planar organometal halide perovskite (CH{sub 3}NH{sub 3}PbI{sub 3}) based solar cells to investigate charge carrier recombination in a fully working solar cell at the nanosecond to microsecond time scale. Recombination of mobile (extractable) charges is shown to follow second-order recombination dynamics for all fluences and time scales tested. Most importantly, the bimolecular recombination coefficient is found to be time-dependent, with an initial value of ca. 10{sup −9} cm{sup 3}/s and a progressive reduction within the first tens of nanoseconds. Comparison to the prototypical organic bulk heterojunction device PTB7:PC{sub 71}BM yields important differences with regardmore » to the mechanism and time scale of free carrier recombination.« less

The Impact of Ozone Treatment in Dynamic Bed Parameters on Changes in Biologically Active Substances of Juniper Berries

PubMed Central

Brodowska, Agnieszka Joanna; Śmigielski, Krzysztof; Nowak, Agnieszka; Czyżowska, Agata; Otlewska, Anna

2015-01-01

The development of the parameters of ozone decontamination method assuring the least possible losses of biologically active substances (essential oils and polyphenols) and their activity in common juniper (Juniperus communis (L.)) berries was studied. Ozone treatment in dynamic bed was conducted 9 times. The process was conducted under different ozone concentrations (100.0; 130.0; 160.0 g O3/m3) and times (30, 60, 90 min). After each decontamination, the microbiological profile of the juniper berries was studied, and the contaminating microflora was identified. Next to the microbiological profile, the phenolic profile, as well as antioxidant activity of extracts and essential oils were determined. The total polyphenol content (TPC), composition of essential oils, free radical-scavenging capacity, total antioxidant capacity, ferric-reducing antioxidant power (FRAP), beta-carotene bleaching test (BCB) and LC-MS polyphenol analysis were carried out. The study reveals that during short ozone contact times, higher amounts of TPC, 15.47 and 12.91 mg CE/g of extract, for samples 100/30 and 130/30, respectively, were demonstrated. Whereas samples 100/60, 130/60, 100/90, and 160/90 exhibited the lowest amount of phenolics. The highest antioxidant activity was found in the methanol extract obtained from ozonated berries which exhibited the lowest IC50 in all the antioxidant assays, such as DPPH, FRAP, and BCB assays. Ozone treatment showed noteworthy potential and its usage in food manufacturing and as an alternative decontamination method should be considered. PMID:26659905

The Impact of Ozone Treatment in Dynamic Bed Parameters on Changes in Biologically Active Substances of Juniper Berries.

PubMed

Brodowska, Agnieszka Joanna; Śmigielski, Krzysztof; Nowak, Agnieszka; Czyżowska, Agata; Otlewska, Anna

2015-01-01

The development of the parameters of ozone decontamination method assuring the least possible losses of biologically active substances (essential oils and polyphenols) and their activity in common juniper (Juniperus communis (L.)) berries was studied. Ozone treatment in dynamic bed was conducted 9 times. The process was conducted under different ozone concentrations (100.0; 130.0; 160.0 g O3/m3) and times (30, 60, 90 min). After each decontamination, the microbiological profile of the juniper berries was studied, and the contaminating microflora was identified. Next to the microbiological profile, the phenolic profile, as well as antioxidant activity of extracts and essential oils were determined. The total polyphenol content (TPC), composition of essential oils, free radical-scavenging capacity, total antioxidant capacity, ferric-reducing antioxidant power (FRAP), beta-carotene bleaching test (BCB) and LC-MS polyphenol analysis were carried out. The study reveals that during short ozone contact times, higher amounts of TPC, 15.47 and 12.91 mg CE/g of extract, for samples 100/30 and 130/30, respectively, were demonstrated. Whereas samples 100/60, 130/60, 100/90, and 160/90 exhibited the lowest amount of phenolics. The highest antioxidant activity was found in the methanol extract obtained from ozonated berries which exhibited the lowest IC50 in all the antioxidant assays, such as DPPH, FRAP, and BCB assays. Ozone treatment showed noteworthy potential and its usage in food manufacturing and as an alternative decontamination method should be considered.

In situ Orbit Extraction from Live, High Precision Collisionless Simulations of Systems Formed by Cold Collapse

NASA Astrophysics Data System (ADS)

Noriega-Mendoza, H.; Aguilar, L. A.

2018-04-01

We performed high precision, N-body simulations of the cold collapse of initially spherical, collisionless systems using the GYRFALCON code of Dehnen (2000). The collapses produce very prolate spheroidal configurations. After the collapse, the systems are simulated for 85 and 170 half-mass radius dynamical timescales, during which energy conservation is better than 0.005%. We use this period to extract individual particle orbits directly from the simulations. We then use the TAXON code of Carpintero and Aguilar (1998) to classify 1 to 1.5% of the extracted orbits from our final, relaxed configurations: less than 15% are chaotic orbits, 30% are box orbits and 60% are tube orbits (long and short axis). Our goal has been to prove that direct orbit extraction is feasible, and that there is no need to "freeze" the final N-body system configuration to extract a time-independent potential.

Data Analysis Approaches for the Risk-Informed Safety Margins Characterization Toolkit

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

Mandelli, Diego; Alfonsi, Andrea; Maljovec, Daniel P.

2016-09-01

In the past decades, several numerical simulation codes have been employed to simulate accident dynamics (e.g., RELAP5-3D, RELAP-7, MELCOR, MAAP). In order to evaluate the impact of uncertainties into accident dynamics, several stochastic methodologies have been coupled with these codes. These stochastic methods range from classical Monte-Carlo and Latin Hypercube sampling to stochastic polynomial methods. Similar approaches have been introduced into the risk and safety community where stochastic methods (such as RAVEN, ADAPT, MCDET, ADS) have been coupled with safety analysis codes in order to evaluate the safety impact of timing and sequencing of events. These approaches are usually calledmore » Dynamic PRA or simulation-based PRA methods. These uncertainties and safety methods usually generate a large number of simulation runs (database storage may be on the order of gigabytes or higher). The scope of this paper is to present a broad overview of methods and algorithms that can be used to analyze and extract information from large data sets containing time dependent data. In this context, “extracting information” means constructing input-output correlations, finding commonalities, and identifying outliers. Some of the algorithms presented here have been developed or are under development within the RAVEN statistical framework.« less

Automated headspace solid-phase dynamic extraction to analyse the volatile fraction of food matrices.

PubMed

Bicchi, Carlo; Cordero, Chiara; Liberto, Erica; Rubiolo, Patrizia; Sgorbini, Barbara

2004-01-23

High concentration capacity headspace techniques (headspace solid-phase microextraction (HS-SPME) and headspace sorptive extraction (HSSE)) are a bridge between static and dynamic headspace, since they give high concentration factors as does dynamic headspace (D-HS), and are as easy to apply and as reproducible as static headspace (S-HS). In 2000, Chromtech (Idstein, Germany) introduced an inside-needle technique for vapour and liquid sampling, solid-phase dynamic extraction (SPDE), also known as "the magic needle". In SPDE, analytes are concentrated on a 50 microm film of polydimethylsiloxane (PDMS) and activated carbon (10%) coated onto the inside wall of the stainless steel needle (5 cm) of a 2.5 ml gas tight syringe. When SPDE is used for headspace sampling (HS-SPDE), a fixed volume of the headspace of the sample under investigation is sucked up an appropriate number of times with the gas tight syringe and an analyte amount suitable for a reliable GC or GC-MS analysis accumulates in the polymer coating the needle wall. This article describes the preliminary results of both a study on the optimisation of sampling parameters conditioning HS-SPDE recovery, through the analysis of a standard mixture of highly volatile compounds (beta-pinene, isoamyl acetate and linalool) and of the HS-SPDE-GC-MS analyses of aromatic plants and food matrices. This study shows that HS-SPDE is a successful technique for HS-sampling with high concentration capability, good repeatability and intermediate precision, also when it is compared to HS-SPME.

Effective Information Extraction Framework for Heterogeneous Clinical Reports Using Online Machine Learning and Controlled Vocabularies.

PubMed

Zheng, Shuai; Lu, James J; Ghasemzadeh, Nima; Hayek, Salim S; Quyyumi, Arshed A; Wang, Fusheng

2017-05-09

Extracting structured data from narrated medical reports is challenged by the complexity of heterogeneous structures and vocabularies and often requires significant manual effort. Traditional machine-based approaches lack the capability to take user feedbacks for improving the extraction algorithm in real time. Our goal was to provide a generic information extraction framework that can support diverse clinical reports and enables a dynamic interaction between a human and a machine that produces highly accurate results. A clinical information extraction system IDEAL-X has been built on top of online machine learning. It processes one document at a time, and user interactions are recorded as feedbacks to update the learning model in real time. The updated model is used to predict values for extraction in subsequent documents. Once prediction accuracy reaches a user-acceptable threshold, the remaining documents may be batch processed. A customizable controlled vocabulary may be used to support extraction. Three datasets were used for experiments based on report styles: 100 cardiac catheterization procedure reports, 100 coronary angiographic reports, and 100 integrated reports-each combines history and physical report, discharge summary, outpatient clinic notes, outpatient clinic letter, and inpatient discharge medication report. Data extraction was performed by 3 methods: online machine learning, controlled vocabularies, and a combination of these. The system delivers results with F1 scores greater than 95%. IDEAL-X adopts a unique online machine learning-based approach combined with controlled vocabularies to support data extraction for clinical reports. The system can quickly learn and improve, thus it is highly adaptable. ©Shuai Zheng, James J Lu, Nima Ghasemzadeh, Salim S Hayek, Arshed A Quyyumi, Fusheng Wang. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 09.05.2017.

Non-Gaussian lineshapes and dynamics of time-resolved linear and nonlinear (correlation) spectra.

PubMed

Dinpajooh, Mohammadhasan; Matyushov, Dmitry V

2014-07-17

Signatures of nonlinear and non-Gaussian dynamics in time-resolved linear and nonlinear (correlation) 2D spectra are analyzed in a model considering a linear plus quadratic dependence of the spectroscopic transition frequency on a Gaussian nuclear coordinate of the thermal bath (quadratic coupling). This new model is contrasted to the commonly assumed linear dependence of the transition frequency on the medium nuclear coordinates (linear coupling). The linear coupling model predicts equality between the Stokes shift and equilibrium correlation functions of the transition frequency and time-independent spectral width. Both predictions are often violated, and we are asking here the question of whether a nonlinear solvent response and/or non-Gaussian dynamics are required to explain these observations. We find that correlation functions of spectroscopic observables calculated in the quadratic coupling model depend on the chromophore's electronic state and the spectral width gains time dependence, all in violation of the predictions of the linear coupling models. Lineshape functions of 2D spectra are derived assuming Ornstein-Uhlenbeck dynamics of the bath nuclear modes. The model predicts asymmetry of 2D correlation plots and bending of the center line. The latter is often used to extract two-point correlation functions from 2D spectra. The dynamics of the transition frequency are non-Gaussian. However, the effect of non-Gaussian dynamics is limited to the third-order (skewness) time correlation function, without affecting the time correlation functions of higher order. The theory is tested against molecular dynamics simulations of a model polar-polarizable chromophore dissolved in a force field water.

Modelling opinion formation driven communities in social networks

NASA Astrophysics Data System (ADS)

Iñiguez, Gerardo; Barrio, Rafael A.; Kertész, János; Kaski, Kimmo K.

2011-09-01

In a previous paper we proposed a model to study the dynamics of opinion formation in human societies by a co-evolution process involving two distinct time scales of fast transaction and slower network evolution dynamics. In the transaction dynamics we take into account short range interactions as discussions between individuals and long range interactions to describe the attitude to the overall mood of society. The latter is handled by a uniformly distributed parameter α, assigned randomly to each individual, as quenched personal bias. The network evolution dynamics is realised by rewiring the societal network due to state variable changes as a result of transaction dynamics. The main consequence of this complex dynamics is that communities emerge in the social network for a range of values in the ratio between time scales. In this paper we focus our attention on the attitude parameter α and its influence on the conformation of opinion and the size of the resulting communities. We present numerical studies and extract interesting features of the model that can be interpreted in terms of social behaviour.

Effects of removal of different chemical components on moisture sorption property of Populus euramericana Cv. under dynamic hygrothermal conditions

NASA Astrophysics Data System (ADS)

Yang, Tiantian; Zhou, Haizhen; Ma, Erni; Wang, Jiamin

2018-09-01

Effects of chemical components on wood sorption property under dynamic condition were investigated for the first time. Hemicellulose, lignin and extractive (denoted as DHC, DL and DE, respectively) were removed from Populus euramericana Cv., 20 mm in radial (R) and tangential (T) directions with thickness of 4 mm along the grain, then the wood was subjected to cyclic tests where relative humidity (RH) varied from 45% to 75% sinusoidally at 25 °C. Based on measured data automatically, the results showed that, various chemical components had different effects on dynamic sorption behaviors of wood. The DL exhibited the largest moisture content and diffusion coefficient, followed by the DE, Control and DHC. This indicated lignin or extractive removal accelerated the dynamic sorption process and improved hygroscopicity of wood, while hemicellulose removal caused opposite effects. Theoretical sorption model was further applied and the modeled curves fitted satisfactorily with experimental data. Dynamic moisture gradient distribution inside the different treated wood was investigated and amplitude of moisture showed negative relation with wood element depth, while phase lag presented an opposite trend. Amplitude of DL was the largest while its phase lag was the least. Conditioning thickness for RH was greatest for DHC, about twice as much as the minimum of DL.

Supercritical Carbon Dioxide Extraction of Bioactive Compounds from Ampelopsis grossedentata Stems: Process Optimization and Antioxidant Activity

PubMed Central

Wang, Yuefei; Ying, Le; Sun, Da; Zhang, Shikang; Zhu, Yuejin; Xu, Ping

2011-01-01

Supercritical carbon dioxide (SC-CO2) extraction of bioactive compounds including flavonoids and phenolics from Ampelopsis grossedentata stems was carried out. Extraction parameters such as pressure, temperature, dynamic time and modifier, were optimized using an orthogonal array design of L9 (34), and antioxidant activities of the extracts were evaluated by 2,2-diphenyl-1-picrylhydrazyl (DPPH) free radical scavenging assay and ferrous ion chelating (FIC) assay. The best conditions obtained for SC-CO2 extraction of flavonoids was 250 bar, 40 °C, 50 min, and with a modifier of methanol/ethanol (1:3, v/v), and that for phenolics extraction was 250 bar, 40 °C, 50 min, and with a modifier of methanol/ethanol (1:1, v/v). Meantime, flavonoids and phenolics were found to be mainly responsible for the DPPH scavenging activity of the extracts, but not for the chelating activity on ferrous ion according to Pearson correlation analysis. Furthermore, several unreported flavonoids such as apigenin, vitexin, luteolin, etc., have been detected in the extracts from A. grossedentata stems. PMID:22072923

Velocity measurements of heterogeneous RBC flow in capillary vessels using dynamic laser speckle signal

PubMed Central

Li, Chenxi; Wang, Ruikang

2017-01-01

Abstract. We propose an approach to measure heterogeneous velocities of red blood cells (RBCs) in capillary vessels using full-field time-varying dynamic speckle signals. The approach utilizes a low coherent laser speckle imaging system to record the instantaneous speckle pattern, followed by an eigen-decomposition-based filtering algorithm to extract dynamic speckle signal due to the moving RBCs. The velocity of heterogeneous RBC flows is determined by cross-correlating the temporal dynamic speckle signals obtained at adjacent locations. We verify the approach by imaging mouse pinna in vivo, demonstrating its capability for full-field RBC flow mapping and quantifying flow pattern with high resolution. It is expected to investigate the dynamic action of RBCs flow in capillaries under physiological changes. PMID:28384709

A modeling technique for STOVL ejector and volume dynamics

NASA Technical Reports Server (NTRS)

Drummond, C. K.; Barankiewicz, W. S.

1990-01-01

New models for thrust augmenting ejector performance prediction and feeder duct dynamic analysis are presented and applied to a proposed Short Take Off and Vertical Landing (STOVL) aircraft configuration. Central to the analysis is the nontraditional treatment of the time-dependent volume integrals in the otherwise conventional control-volume approach. In the case of the thrust augmenting ejector, the analysis required a new relationship for transfer of kinetic energy from the primary flow to the secondary flow. Extraction of the required empirical corrections from current steady-state experimental data is discussed; a possible approach for modeling insight through Computational Fluid Dynamics (CFD) is presented.

Bifunctional ultrasound assisted extraction and determination of Elettaria cardamomum Maton essential oil.

PubMed

Sereshti, Hassan; Rohanifar, Ahmad; Bakhtiari, Sadjad; Samadi, Soheila

2012-05-18

A new hyphenated extraction method composed of ultrasound assisted extraction (UAE)-optimized ultrasound assisted emulsification microextraction (USAEME) was developed for the extraction and preconcentration of the essential oil of Elettaria cardamomum Maton. The essential oil was analyzed by gas chromatography-mass spectrometry (GC-MS) and optimization was performed using gas chromatography-flame ionization detection (GC-FID). Ultrasound played two different roles in the extraction of the essential oil. First, as a source of sufficient energy to break the oil-containing glands in order to release the oil, and second as an emulsifier to disperse the organic phase within water. The effective parameters (factors) of USAEME including volume of extraction solvent (C(2)H(4)Cl(2)), extraction temperature and ultrasonic time were optimized by using a central composite design (CCD). The optimal conditions were 120 μL for extraction solvent volume, 32.5 °C for temperature and 10.5 min for ultrasonic time. The linear dynamic ranges (LDRs) were 0.01-50 mg L(-1) with the determination coefficients in the range of 0.9990-0.9999. The limits of detection (LODs) and the relative standard deviations (RSDs) were 0.001-0.007 mg L(-1) and 3.6-6.3%, respectively. The enrichment factors were 93-98. The main components of the extracted essential oil were α-terpenyl acetate (46.0%), 1,8-cineole (27.7%), linalool (5.3%), α-terpineol (4.0%), linalyl acetate (3.5%). Copyright © 2012 Elsevier B.V. All rights reserved.

Simultaneous measurement of temperature and emissivity of lunar regolith simulant using dual-channel millimeter-wave radiometry

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

McCloy, J. S.; Sundaram, S. K.; Matyas, J.

Millimeter wave (MMW) radiometry can be used for simultaneous measurement of emissivity and temperature of materials under extreme environments (high temperature, pressure, and corrosive environments). The state-of-the-art dual channel MMW passive radiometer with active interferometric capabilities at 137 GHz described here allows for radiometric measurements of sample temperature and emissivity up to at least 1600 °C with simultaneous measurement of sample surface dynamics. These capabilities have been used to demonstrate dynamic measurement of melting of powders of simulated lunar regolith and static measurement of emissivity of solid samples. The paper presents the theoretical background and basis for the dual-receiver system,more » describes the hardware in detail, and demonstrates the data analysis. Post-experiment analysis of emissivity versus temperature allows further extraction from the radiometric data of millimeter wave viewing beam coupling factors, which provide corroboratory evidence to the interferometric data of the process dynamics observed. Finally, these results show the promise of the MMW system for extracting quantitative and qualitative process parameters for industrial processes and access to real-time dynamics of materials behavior in extreme environments.« less

Assessing oral bioaccessibility of trace elements in soils under worst-case scenarios by automated in-line dynamic extraction as a front end to inductively coupled plasma atomic emission spectrometry.

PubMed

Rosende, María; Magalhães, Luis M; Segundo, Marcela A; Miró, Manuel

2014-09-09

A novel biomimetic extraction procedure that allows for the in-line handing of ≥400 mg solid substrates is herein proposed for automatic ascertainment of trace element (TE) bioaccessibility in soils under worst-case conditions as per recommendations of ISO norms. A unified bioaccessibility/BARGE method (UBM)-like physiological-based extraction test is evaluated for the first time in a dynamic format for accurate assessment of in-vitro bioaccessibility of Cr, Cu, Ni, Pb and Zn in forest and residential-garden soils by on-line coupling of a hybrid flow set-up to inductively coupled plasma atomic emission spectrometry. Three biologically relevant operational extraction modes mimicking: (i) gastric juice extraction alone; (ii) saliva and gastric juice composite in unidirectional flow extraction format and (iii) saliva and gastric juice composite in a recirculation mode were thoroughly investigated. The extraction profiles of the three configurations using digestive fluids were proven to fit a first order reaction kinetic model for estimating the maximum TE bioaccessibility, that is, the actual worst-case scenario in human risk assessment protocols. A full factorial design, in which the sample amount (400-800 mg), the extractant flow rate (0.5-1.5 mL min(-1)) and the extraction temperature (27-37°C) were selected as variables for the multivariate optimization studies in order to obtain the maximum TE extractability. Two soils of varied physicochemical properties were analysed and no significant differences were found at the 0.05 significance level between the summation of leached concentrations of TE in gastric juice plus the residual fraction and the total concentration of the overall assayed metals determined by microwave digestion. These results showed the reliability and lack of bias (trueness) of the automatic biomimetic extraction approach using digestive juices. Copyright © 2014 Elsevier B.V. All rights reserved.

Exploring the Dynamics of Dyadic Interactions via Hierarchical Segmentation

ERIC Educational Resources Information Center

Hsieh, Fushing; Ferrer, Emilio; Chen, Shu-Chun; Chow, Sy-Miin

2010-01-01

In this article we present an exploratory tool for extracting systematic patterns from multivariate data. The technique, hierarchical segmentation (HS), can be used to group multivariate time series into segments with similar discrete-state recurrence patterns and it is not restricted by the stationarity assumption. We use a simulation study to…

Quantifying heterogeneity of lesion uptake in dynamic contrast enhanced MRI for breast cancer diagnosis

NASA Astrophysics Data System (ADS)

Karahaliou, A.; Vassiou, K.; Skiadopoulos, S.; Kanavou, T.; Yiakoumelos, A.; Costaridou, L.

2009-07-01

The current study investigates whether texture features extracted from lesion kinetics feature maps can be used for breast cancer diagnosis. Fifty five women with 57 breast lesions (27 benign, 30 malignant) were subjected to dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) on 1.5T system. A linear-slope model was fitted pixel-wise to a representative lesion slice time series and fitted parameters were used to create three kinetic maps (wash out, time to peak enhancement and peak enhancement). 28 grey level co-occurrence matrices features were extracted from each lesion kinetic map. The ability of texture features per map in discriminating malignant from benign lesions was investigated using a Probabilistic Neural Network classifier. Additional classification was performed by combining classification outputs of most discriminating feature subsets from the three maps, via majority voting. The combined scheme outperformed classification based on individual maps achieving area under Receiver Operating Characteristics curve 0.960±0.029. Results suggest that heterogeneity of breast lesion kinetics, as quantified by texture analysis, may contribute to computer assisted tissue characterization in DCE-MRI.

Ultrafast carrier dynamics in the large-magnetoresistance material WTe 2

DOE PAGES

Dai, Y. M.; Bowlan, J.; Li, H.; ...

2015-10-07

In this study, ultrafast optical pump-probe spectroscopy is used to track carrier dynamics in the large-magnetoresistance material WTe 2. Our experiments reveal a fast relaxation process occurring on a subpicosecond time scale that is caused by electron-phonon thermalization, allowing us to extract the electron-phonon coupling constant. An additional slower relaxation process, occurring on a time scale of ~5–15 ps, is attributed to phonon-assisted electron-hole recombination. As the temperature decreases from 300 K, the time scale governing this process increases due to the reduction of the phonon population. However, below ~50 K, an unusual decrease of the recombination time sets in,more » most likely due to a change in the electronic structure that has been linked to the large magnetoresistance observed in this material.« less

Andreev Bound States Formation and Quasiparticle Trapping in Quench Dynamics Revealed by Time-Dependent Counting Statistics.

PubMed

Souto, R Seoane; Martín-Rodero, A; Yeyati, A Levy

2016-12-23

We analyze the quantum quench dynamics in the formation of a phase-biased superconducting nanojunction. We find that in the absence of an external relaxation mechanism and for very general conditions the system gets trapped in a metastable state, corresponding to a nonequilibrium population of the Andreev bound states. The use of the time-dependent full counting statistics analysis allows us to extract information on the asymptotic population of even and odd many-body states, demonstrating that a universal behavior, dependent only on the Andreev state energy, is reached in the quantum point contact limit. These results shed light on recent experimental observations on quasiparticle trapping in superconducting atomic contacts.

Exploration of laser-driven electron-multirescattering dynamics in high-order harmonic generation

DOE PAGES

Li, Peng -Cheng; Sheu, Yae -Lin; Jooya, Hossein Z.; ...

2016-09-06

Multiple rescattering processes play an important role in high-order harmonic generation (HHG) in an intense laser field. However, the underlying multi-rescattering dynamics are still largely unexplored. Here we investigate the dynamical origin of multiple rescattering processes in HHG associated with the odd and even number of returning times of the electron to the parent ion. We perform fully ab initio quantum calculations and extend the empirical mode decomposition method to extract the individual multiple scattering contributions in HHG. We find that the tunneling ionization regime is responsible for the odd number times of rescattering and the corresponding short trajectories aremore » dominant. On the other hand, the multiphoton ionization regime is responsible for the even number times of rescattering and the corresponding long trajectories are dominant. Moreover, we discover that the multiphoton- and tunneling-ionization regimes in multiple rescattering processes occur alternatively. Our results uncover the dynamical origin of multiple rescattering processes in HHG for the first time. As a result, it also provides new insight regarding the control of the multiple rescattering processes for the optimal generation of ultrabroad band supercontinuum spectra and the production of single ultrashort attosecond laser pulse.« less

Exploration of laser-driven electron-multirescattering dynamics in high-order harmonic generation

PubMed Central

Li, Peng-Cheng; Sheu, Yae-Lin; Jooya, Hossein Z.; Zhou, Xiao-Xin; Chu, Shih-I

2016-01-01

Multiple rescattering processes play an important role in high-order harmonic generation (HHG) in an intense laser field. However, the underlying multi-rescattering dynamics are still largely unexplored. Here we investigate the dynamical origin of multiple rescattering processes in HHG associated with the odd and even number of returning times of the electron to the parent ion. We perform fully ab initio quantum calculations and extend the empirical mode decomposition method to extract the individual multiple scattering contributions in HHG. We find that the tunneling ionization regime is responsible for the odd number times of rescattering and the corresponding short trajectories are dominant. On the other hand, the multiphoton ionization regime is responsible for the even number times of rescattering and the corresponding long trajectories are dominant. Moreover, we discover that the multiphoton- and tunneling-ionization regimes in multiple rescattering processes occur alternatively. Our results uncover the dynamical origin of multiple rescattering processes in HHG for the first time. It also provides new insight regarding the control of the multiple rescattering processes for the optimal generation of ultrabroad band supercontinuum spectra and the production of single ultrashort attosecond laser pulse. PMID:27596056

Exploration of laser-driven electron-multirescattering dynamics in high-order harmonic generation.

PubMed

Li, Peng-Cheng; Sheu, Yae-Lin; Jooya, Hossein Z; Zhou, Xiao-Xin; Chu, Shih-I

2016-09-06

Multiple rescattering processes play an important role in high-order harmonic generation (HHG) in an intense laser field. However, the underlying multi-rescattering dynamics are still largely unexplored. Here we investigate the dynamical origin of multiple rescattering processes in HHG associated with the odd and even number of returning times of the electron to the parent ion. We perform fully ab initio quantum calculations and extend the empirical mode decomposition method to extract the individual multiple scattering contributions in HHG. We find that the tunneling ionization regime is responsible for the odd number times of rescattering and the corresponding short trajectories are dominant. On the other hand, the multiphoton ionization regime is responsible for the even number times of rescattering and the corresponding long trajectories are dominant. Moreover, we discover that the multiphoton- and tunneling-ionization regimes in multiple rescattering processes occur alternatively. Our results uncover the dynamical origin of multiple rescattering processes in HHG for the first time. It also provides new insight regarding the control of the multiple rescattering processes for the optimal generation of ultrabroad band supercontinuum spectra and the production of single ultrashort attosecond laser pulse.

Development and application of stir bar sorptive extraction with polyurethane foams for the determination of testosterone and methenolone in urine matrices.

PubMed

Sequeiros, R C P; Neng, N R; Portugal, F C M; Pinto, M L; Pires, J; Nogueira, J M F

2011-04-01

This work describes the development, validation, and application of a novel methodology for the determination of testosterone and methenolone in urine matrices by stir bar sorptive extraction using polyurethane foams [SBSE(PU)] followed by liquid desorption and high-performance liquid chromatography with diode array detection. The methodology was optimized in terms of extraction time, agitation speed, pH, ionic strength and organic modifier, as well as back-extraction solvent and desorption time. Under optimized experimental conditions, convenient accuracy were achieved with average recoveries of 49.7 8.6% for testosterone and 54.2 ± 4.7% for methenolone. Additionally, the methodology showed good precision (<9%), excellent linear dynamic ranges (>0.9963) and convenient detection limits (0.2-0.3 μg/L). When comparing the efficiency obtained by SBSE(PU) and with the conventional polydimethylsiloxane phase [SBSE(PDMS)], yields up to four-fold higher are attained for the former, under the same experimental conditions. The application of the proposed methodology for the analysis of testosterone and methenolone in urine matrices showed negligible matrix effects and good analytical performance.

Advanced spectral methods for climatic time series

USGS Publications Warehouse

Ghil, M.; Allen, M.R.; Dettinger, M.D.; Ide, K.; Kondrashov, D.; Mann, M.E.; Robertson, A.W.; Saunders, A.; Tian, Y.; Varadi, F.; Yiou, P.

2002-01-01

The analysis of univariate or multivariate time series provides crucial information to describe, understand, and predict climatic variability. The discovery and implementation of a number of novel methods for extracting useful information from time series has recently revitalized this classical field of study. Considerable progress has also been made in interpreting the information so obtained in terms of dynamical systems theory. In this review we describe the connections between time series analysis and nonlinear dynamics, discuss signal- to-noise enhancement, and present some of the novel methods for spectral analysis. The various steps, as well as the advantages and disadvantages of these methods, are illustrated by their application to an important climatic time series, the Southern Oscillation Index. This index captures major features of interannual climate variability and is used extensively in its prediction. Regional and global sea surface temperature data sets are used to illustrate multivariate spectral methods. Open questions and further prospects conclude the review.

A combined basalt and peridotite perspective on 14 million years of melt generation at the Atlantis Bank segment of the Southwest Indian Ridge: Evidence for temporal changes in mantle dynamics?

USGS Publications Warehouse

Coogan, L.A.; Thompson, G.M.; MacLeod, C.J.; Dick, H.J.B.; Edwards, S.J.; Hosford, Scheirer A.; Barry, T.L.

2004-01-01

Little is known about temporal variations in melt generation and extraction at midocean ridges largely due to the paucity of sampling along flow lines. Here we present new whole-rock major and trace element data, and mineral and glass major element data, for 71 basaltic samples (lavas and dykes) and 23 peridotites from the same ridge segment (the Atlantis Bank segment of the Southwest Indian Ridge). These samples span an age range of almost 14 My and, in combination with the large amount of published data from this area, allow temporal variations in melting processes to be investigated. Basalts show systematic changes in incompatible trace element ratios with the older samples (from ???8-14 Ma) having more depleted incompatible trace element ratios than the younger ones. There is, however, no corresponding change in peridotite compositions. Peridotites come from the top of the melting column, where the extent of melting is highest, suggesting that the maximum degree of melting did not change over this interval of time. New and published Nd isotopic ratios of basalts, dykes and gabbros from this segment suggest that the average source composition has been approximately constant over this time interval. These data are most readily explained by a model in which the average source composition and temperature have not changed over the last 14 My, but the dynamics of mantle flow (active-to-passive) or melt extraction (less-to-more efficient extraction from the 'wings' of the melting column) has changed significantly. This hypothesised change in mantle dynamics occurs at roughly the same time as a change from a period of detachment faulting to 'normal' crustal accretion. We speculate that active mantle flow may impart sufficient shear stress on the base of the lithosphere to rotate the regional stress field and promote the formation of low angle normal faults. ?? 2004 Elsevier B.V. All rights reserved.

Stimulus and Response-Locked P3 Activity in a Dynamic Rapid Serial Visual Presentation (RSVP) Task

DTIC Science & Technology

2013-01-01

Perception and Psychophysics 1973, 14, 265–272. Touryan, J.; Gibson, L.; Horne, J. H.; Weber, P. Real-Time Classification of Neural Signals ...execution. 15. SUBJECT TERMS P300, RSVP, EEG, target recognition, reaction time, ERP 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT...applications and as an input signal in many brain computer interactive technologies (BCITs) for both patients and healthy individuals. ERPs are extracted

Classification of small lesions in dynamic breast MRI: Eliminating the need for precise lesion segmentation through spatio-temporal analysis of contrast enhancement over time.

PubMed

Nagarajan, Mahesh B; Huber, Markus B; Schlossbauer, Thomas; Leinsinger, Gerda; Krol, Andrzej; Wismüller, Axel

2013-10-01

Characterizing the dignity of breast lesions as benign or malignant is specifically difficult for small lesions; they don't exhibit typical characteristics of malignancy and are harder to segment since margins are harder to visualize. Previous attempts at using dynamic or morphologic criteria to classify small lesions (mean lesion diameter of about 1 cm) have not yielded satisfactory results. The goal of this work was to improve the classification performance in such small diagnostically challenging lesions while concurrently eliminating the need for precise lesion segmentation. To this end, we introduce a method for topological characterization of lesion enhancement patterns over time. Three Minkowski Functionals were extracted from all five post-contrast images of sixty annotated lesions on dynamic breast MRI exams. For each Minkowski Functional, topological features extracted from each post-contrast image of the lesions were combined into a high-dimensional texture feature vector. These feature vectors were classified in a machine learning task with support vector regression. For comparison, conventional Haralick texture features derived from gray-level co-occurrence matrices (GLCM) were also used. A new method for extracting thresholded GLCM features was also introduced and investigated here. The best classification performance was observed with Minkowski Functionals area and perimeter , thresholded GLCM features f8 and f9, and conventional GLCM features f4 and f6. However, both Minkowski Functionals and thresholded GLCM achieved such results without lesion segmentation while the performance of GLCM features significantly deteriorated when lesions were not segmented ( p < 0.05). This suggests that such advanced spatio-temporal characterization can improve the classification performance achieved in such small lesions, while simultaneously eliminating the need for precise segmentation.

Electron Dynamics in Nanostructures in Strong Laser Fields

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

Kling, Matthias

2014-09-11

The goal of our research was to gain deeper insight into the collective electron dynamics in nanosystems in strong, ultrashort laser fields. The laser field strengths will be strong enough to extract and accelerate electrons from the nanoparticles and to transiently modify the materials electronic properties. We aimed to observe, with sub-cycle resolution reaching the attosecond time domain, how collective electronic excitations in nanoparticles are formed, how the strong field influences the optical and electrical properties of the nanomaterial, and how the excitations in the presence of strong fields decay.

A signal processing framework for simultaneous detection of multiple environmental contaminants

NASA Astrophysics Data System (ADS)

Chakraborty, Subhadeep; Manahan, Michael P.; Mench, Matthew M.

2013-11-01

The possibility of large-scale attacks using chemical warfare agents (CWAs) has exposed the critical need for fundamental research enabling the reliable, unambiguous and early detection of trace CWAs and toxic industrial chemicals. This paper presents a unique approach for the identification and classification of simultaneously present multiple environmental contaminants by perturbing an electrochemical (EC) sensor with an oscillating potential for the extraction of statistically rich information from the current response. The dynamic response, being a function of the degree and mechanism of contamination, is then processed with a symbolic dynamic filter for the extraction of representative patterns, which are then classified using a trained neural network. The approach presented in this paper promises to extend the sensing power and sensitivity of these EC sensors by augmenting and complementing sensor technology with state-of-the-art embedded real-time signal processing capabilities.

Transition Characteristic Analysis of Traffic Evolution Process for Urban Traffic Network

PubMed Central

Chen, Hong; Li, Yang

2014-01-01

The characterization of the dynamics of traffic states remains fundamental to seeking for the solutions of diverse traffic problems. To gain more insights into traffic dynamics in the temporal domain, this paper explored temporal characteristics and distinct regularity in the traffic evolution process of urban traffic network. We defined traffic state pattern through clustering multidimensional traffic time series using self-organizing maps and construct a pattern transition network model that is appropriate for representing and analyzing the evolution progress. The methodology is illustrated by an application to data flow rate of multiple road sections from Network of Shenzhen's Nanshan District, China. Analysis and numerical results demonstrated that the methodology permits extracting many useful traffic transition characteristics including stability, preference, activity, and attractiveness. In addition, more information about the relationships between these characteristics was extracted, which should be helpful in understanding the complex behavior of the temporal evolution features of traffic patterns. PMID:24982969

Principal component analysis of dynamic fluorescence images for diagnosis of diabetic vasculopathy

NASA Astrophysics Data System (ADS)

Seo, Jihye; An, Yuri; Lee, Jungsul; Ku, Taeyun; Kang, Yujung; Ahn, Chulwoo; Choi, Chulhee

2016-04-01

Indocyanine green (ICG) fluorescence imaging has been clinically used for noninvasive visualizations of vascular structures. We have previously developed a diagnostic system based on dynamic ICG fluorescence imaging for sensitive detection of vascular disorders. However, because high-dimensional raw data were used, the analysis of the ICG dynamics proved difficult. We used principal component analysis (PCA) in this study to extract important elements without significant loss of information. We examined ICG spatiotemporal profiles and identified critical features related to vascular disorders. PCA time courses of the first three components showed a distinct pattern in diabetic patients. Among the major components, the second principal component (PC2) represented arterial-like features. The explained variance of PC2 in diabetic patients was significantly lower than in normal controls. To visualize the spatial pattern of PCs, pixels were mapped with red, green, and blue channels. The PC2 score showed an inverse pattern between normal controls and diabetic patients. We propose that PC2 can be used as a representative bioimaging marker for the screening of vascular diseases. It may also be useful in simple extractions of arterial-like features.

Chromosomal locus tracking with proper accounting of static and dynamic errors

PubMed Central

Backlund, Mikael P.; Joyner, Ryan; Moerner, W. E.

2015-01-01

The mean-squared displacement (MSD) and velocity autocorrelation (VAC) of tracked single particles or molecules are ubiquitous metrics for extracting parameters that describe the object’s motion, but they are both corrupted by experimental errors that hinder the quantitative extraction of underlying parameters. For the simple case of pure Brownian motion, the effects of localization error due to photon statistics (“static error”) and motion blur due to finite exposure time (“dynamic error”) on the MSD and VAC are already routinely treated. However, particles moving through complex environments such as cells, nuclei, or polymers often exhibit anomalous diffusion, for which the effects of these errors are less often sufficiently treated. We present data from tracked chromosomal loci in yeast that demonstrate the necessity of properly accounting for both static and dynamic error in the context of an anomalous diffusion that is consistent with a fractional Brownian motion (FBM). We compare these data to analytical forms of the expected values of the MSD and VAC for a general FBM in the presence of these errors. PMID:26172745

Generalized composite multiscale permutation entropy and Laplacian score based rolling bearing fault diagnosis

NASA Astrophysics Data System (ADS)

Zheng, Jinde; Pan, Haiyang; Yang, Shubao; Cheng, Junsheng

2018-01-01

Multiscale permutation entropy (MPE) is a recently proposed nonlinear dynamic method for measuring the randomness and detecting the nonlinear dynamic change of time series and can be used effectively to extract the nonlinear dynamic fault feature from vibration signals of rolling bearing. To solve the drawback of coarse graining process in MPE, an improved MPE method called generalized composite multiscale permutation entropy (GCMPE) was proposed in this paper. Also the influence of parameters on GCMPE and its comparison with the MPE are studied by analyzing simulation data. GCMPE was applied to the fault feature extraction from vibration signal of rolling bearing and then based on the GCMPE, Laplacian score for feature selection and the Particle swarm optimization based support vector machine, a new fault diagnosis method for rolling bearing was put forward in this paper. Finally, the proposed method was applied to analyze the experimental data of rolling bearing. The analysis results show that the proposed method can effectively realize the fault diagnosis of rolling bearing and has a higher fault recognition rate than the existing methods.

Phase correlation imaging of unlabeled cell dynamics

NASA Astrophysics Data System (ADS)

Ma, Lihong; Rajshekhar, Gannavarpu; Wang, Ru; Bhaduri, Basanta; Sridharan, Shamira; Mir, Mustafa; Chakraborty, Arindam; Iyer, Rajashekar; Prasanth, Supriya; Millet, Larry; Gillette, Martha U.; Popescu, Gabriel

2016-09-01

We present phase correlation imaging (PCI) as a novel approach to study cell dynamics in a spatially-resolved manner. PCI relies on quantitative phase imaging time-lapse data and, as such, functions in label-free mode, without the limitations associated with exogenous markers. The correlation time map outputted in PCI informs on the dynamics of the intracellular mass transport. Specifically, we show that PCI can extract quantitatively the diffusion coefficient map associated with live cells, as well as standard Brownian particles. Due to its high sensitivity to mass transport, PCI can be applied to studying the integrity of actin polymerization dynamics. Our results indicate that the cyto-D treatment blocking the actin polymerization has a dominant effect at the large spatial scales, in the region surrounding the cell. We found that PCI can distinguish between senescent and quiescent cells, which is extremely difficult without using specific markers currently. We anticipate that PCI will be used alongside established, fluorescence-based techniques to enable valuable new studies of cell function.

Detecting intrinsic dynamics of traffic flow with recurrence analysis and empirical mode decomposition

NASA Astrophysics Data System (ADS)

Xiong, Hui; Shang, Pengjian; Bian, Songhan

2017-05-01

In this paper, we apply the empirical mode decomposition (EMD) method to the recurrence plot (RP) and recurrence quantification analysis (RQA), to evaluate the frequency- and time-evolving dynamics of the traffic flow. Based on the cumulative intrinsic mode functions extracted by the EMD, the frequency-evolving RP regarding different oscillation of modes suggests that apparent dynamics of the data considered are mainly dominated by its components of medium- and low-frequencies while severely affected by fast oscillated noises contained in the signal. Noises are then eliminated to analyze the intrinsic dynamics and consequently, the denoised time-evolving RQA diversely characterizes the properties of the signal and marks crucial points more accurately where white bands in the RP occur, whereas a strongly qualitative agreement exists between all the non-denoised RQA measures. Generally, the EMD combining with the recurrence analysis sheds more reliable, abundant and inherent lights into the traffic flow, which is meaningful to the empirical analysis of complex systems.

hctsa: A Computational Framework for Automated Time-Series Phenotyping Using Massive Feature Extraction.

PubMed

Fulcher, Ben D; Jones, Nick S

2017-11-22

Phenotype measurements frequently take the form of time series, but we currently lack a systematic method for relating these complex data streams to scientifically meaningful outcomes, such as relating the movement dynamics of organisms to their genotype or measurements of brain dynamics of a patient to their disease diagnosis. Previous work addressed this problem by comparing implementations of thousands of diverse scientific time-series analysis methods in an approach termed highly comparative time-series analysis. Here, we introduce hctsa, a software tool for applying this methodological approach to data. hctsa includes an architecture for computing over 7,700 time-series features and a suite of analysis and visualization algorithms to automatically select useful and interpretable time-series features for a given application. Using exemplar applications to high-throughput phenotyping experiments, we show how hctsa allows researchers to leverage decades of time-series research to quantify and understand informative structure in time-series data. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Nanoscale Characterization of Carrier Dynamic and Surface Passivation in InGaN/GaN Multiple Quantum Wells on GaN Nanorods.

PubMed

Chen, Weijian; Wen, Xiaoming; Latzel, Michael; Heilmann, Martin; Yang, Jianfeng; Dai, Xi; Huang, Shujuan; Shrestha, Santosh; Patterson, Robert; Christiansen, Silke; Conibeer, Gavin

2016-11-23

Using advanced two-photon excitation confocal microscopy, associated with time-resolved spectroscopy, we characterize InGaN/GaN multiple quantum wells on nanorod heterostructures and demonstrate the passivation effect of a KOH treatment. High-quality InGaN/GaN nanorods were fabricated using nanosphere lithography as a candidate material for light-emitting diode devices. The depth- and time-resolved characterization at the nanoscale provides detailed carrier dynamic analysis helpful for understanding the optical properties. The nanoscale spatially resolved images of InGaN quantum well and defects were acquired simultaneously. We demonstrate that nanorod etching improves light extraction efficiency, and a proper KOH treatment has been found to reduce the surface defects efficiently and enhance the luminescence. The optical characterization techniques provide depth-resolved and time-resolved carrier dynamics with nanoscale spatially resolved mapping, which is crucial for a comprehensive and thorough understanding of nanostructured materials and provides novel insight into the improvement of materials fabrication and applications.

Quantitative analysis of backbone dynamics in a crystalline protein from nitrogen-15 spin-lattice relaxation.

PubMed

Giraud, Nicolas; Blackledge, Martin; Goldman, Maurice; Böckmann, Anja; Lesage, Anne; Penin, François; Emsley, Lyndon

2005-12-28

A detailed analysis of nitrogen-15 longitudinal relaxation times in microcrystalline proteins is presented. A theoretical model to quantitatively interpret relaxation times is developed in terms of motional amplitude and characteristic time scale. Different averaging schemes are examined in order to propose an analysis of relaxation curves that takes into account the specificity of MAS experiments. In particular, it is shown that magic angle spinning averages the relaxation rate experienced by a single spin over one rotor period, resulting in individual relaxation curves that are dependent on the orientation of their corresponding carousel with respect to the rotor axis. Powder averaging thus leads to a nonexponential behavior in the observed decay curves. We extract dynamic information from experimental decay curves, using a diffusion in a cone model. We apply this study to the analysis of spin-lattice relaxation rates of the microcrystalline protein Crh at two different fields and determine differential dynamic parameters for several residues in the protein.

Kinetics and dynamic evaluation of specific immunotherapy.

PubMed

Pereira, C; Botelho, F; Tavares, B; Lourenço, C; Baeta, C; Palma-Carlos, A G; Lima, J; Chieira, C

2004-12-01

Specific immunotherapy (SIT) is frequently used in the treatment of allergic diseases. However, the mechanisms by which SIT achieves clinical improvement remained unclear. We decided to study the in vivo kinetics of this therapy, using a nuclear medicine approach (leukocytes labelled with 99mTc-HMPAO) in patients on maintenance doses of specific immunotherapy with confirmed clinical efficacy. We studied 13 allergic patients grouped according to different treatment schedules: subcutaneous aqueous allergenic extract (3 latex and 2 hymenoptera venom), subcutaneous depot extract (2 house dust mite and 2 pollens), subcutaneous modified allergens (2 pollens), sublingual extract (2 house dust mites). The control group included two allergic patients submitted to subcutaneous injections of bacterial extract (1 patient--positive control), and aqueous solution (1 patient). At the same time that the therapeutic allergen was administered subcutaneously, the autologous labelled white cells were injected intravenously in a peripheral vein in the contralateral arm. A thoracic dynamic acquisition of 60 mins, 64x64 matrix, 2 frame/min, in anterior view was performed. Static acquisition for 256x256 matrix, during 5 mins each at 60, 90, 120, 180, 240, 300 and 360 mins after the administration of the radiolabelled leukocytes, in thoracic (anterior and posterior), and abdominal view were performed. During the examination, the local erythema was monitored. A similar procedure was undertaken for Sublingual administration of immunotherapy. The inflammatory activity at the site of SIT injection (aqueous depot extract) started in the first hour and the increase was time related. For modified allergen extract and sublingual SIT the activity was present since the beginning of the administration. The ascendant lymphatic drainage, which was directed to the homolateral axillary region, to the lymphoid tissue of the upper mediastinum and to the anterior region of the neck began earlier. Thoracic focalisations were present for all the patients, whereas bowel focalisations were only observed for the subcutaneous route of administration. Sublingual SIT did not induce axillary or intestinal inflammatory focalisations, even though the patients had swallowed the allergenic extract. The uptake coefficient in individualized areas corrected to the uptake coefficient background was also studied. For the subcutaneous route of administration, except for glutaraldehyde-modified allergen, the local inflammatory activity at the allergenic injection site was significantly higher in depth and was time dependent, maintaining activity even after complete disappearance of the erythema and/or wheal. These results express a prompt inflammatory involvement of the immune system with this allergenic therapy, which was unexpected until now. We also observed differences concerning allergic diseases, the type of allergenic extracts and routes of administration.

Impact of anisotropy on the structure and dynamics of ionic liquids: A computational study of 1-butyl-3-methyl-imidazolium trifluoroacetate

NASA Astrophysics Data System (ADS)

Schröder, C.; Rudas, T.; Neumayr, G.; Gansterer, W.; Steinhauser, O.

2007-07-01

The complex ionic network of 1-butyl-3-methyl-imidazolium trifluoroacetate was simulated by means of the molecular dynamics methods over a time period of 100ns. The influence of the anisotropy of the shape and charge distribution of both the cations and the anions on the local (molecular) and global (collective) structure and dynamics is analyzed. The distance-dependent g coefficients of the orientational probability function g(r,Ω) were found to be an excellent way to interpret local structure. Thereby, the combination and interrelation of individual g coefficients elucidate the mutual orientation. Dynamics at the molecular level is characterized by the time correlation function of the center-of-mass corrected molecular dipole moment μcm. Upon uniting the set of molecular dipoles to a single collective rotational dipole moment, MD, dynamics on a global level is studied. Decomposing into subsets of cations and anions respective self terms as well as the prominent cross term can be extracted. This decomposition also enables a detailed peak assignment in dielectric spectra.

Impact of anisotropy on the structure and dynamics of ionic liquids: a computational study of 1-butyl-3-methyl-imidazolium trifluoroacetate.

PubMed

Schröder, C; Rudas, T; Neumayr, G; Gansterer, W; Steinhauser, O

2007-07-28

The complex ionic network of 1-butyl-3-methyl-imidazolium trifluoroacetate was simulated by means of the molecular dynamics methods over a time period of 100 ns. The influence of the anisotropy of the shape and charge distribution of both the cations and the anions on the local (molecular) and global (collective) structure and dynamics is analyzed. The distance-dependent g coefficients of the orientational probability function g(r,Omega) were found to be an excellent way to interpret local structure. Thereby, the combination and interrelation of individual g coefficients elucidate the mutual orientation. Dynamics at the molecular level is characterized by the time correlation function of the center-of-mass corrected molecular dipole moment mucm. Upon uniting the set of molecular dipoles to a single collective rotational dipole moment, MD, dynamics on a global level is studied. Decomposing into subsets of cations and anions respective self terms as well as the prominent cross term can be extracted. This decomposition also enables a detailed peak assignment in dielectric spectra.

Target Detection and Classification Using Seismic and PIR Sensors

DTIC Science & Technology

2012-06-01

time series analysis via wavelet - based partitioning,” Signal Process...regard, this paper presents a wavelet - based method for target detection and classification. The proposed method has been validated on data sets of...The work reported in this paper makes use of a wavelet - based feature extraction method , called Symbolic Dynamic Filtering (SDF) [12]–[14]. The

Effects of dietary tannins on total and extractable nutrients from manure

USDA-ARS?s Scientific Manuscript database

The effects of condensed tannins on N dynamics in ruminants have been a topic of research for some time, but much less work has focused on their impacts on other nutrients in manure A 4 × 4 Latin square sheep trial was used to determine if intake of sericea lespedeza (Lespedeza cuneata; SL; a conde...

Fault diagnosis of rolling bearings based on multifractal detrended fluctuation analysis and Mahalanobis distance criterion

NASA Astrophysics Data System (ADS)

Lin, Jinshan; Chen, Qian

2013-07-01

Vibration data of faulty rolling bearings are usually nonstationary and nonlinear, and contain fairly weak fault features. As a result, feature extraction of rolling bearing fault data is always an intractable problem and has attracted considerable attention for a long time. This paper introduces multifractal detrended fluctuation analysis (MF-DFA) to analyze bearing vibration data and proposes a novel method for fault diagnosis of rolling bearings based on MF-DFA and Mahalanobis distance criterion (MDC). MF-DFA, an extension of monofractal DFA, is a powerful tool for uncovering the nonlinear dynamical characteristics buried in nonstationary time series and can capture minor changes of complex system conditions. To begin with, by MF-DFA, multifractality of bearing fault data was quantified with the generalized Hurst exponent, the scaling exponent and the multifractal spectrum. Consequently, controlled by essentially different dynamical mechanisms, the multifractality of four heterogeneous bearing fault data is significantly different; by contrast, controlled by slightly different dynamical mechanisms, the multifractality of homogeneous bearing fault data with different fault diameters is significantly or slightly different depending on different types of bearing faults. Therefore, the multifractal spectrum, as a set of parameters describing multifractality of time series, can be employed to characterize different types and severity of bearing faults. Subsequently, five characteristic parameters sensitive to changes of bearing fault conditions were extracted from the multifractal spectrum and utilized to construct fault features of bearing fault data. Moreover, Hilbert transform based envelope analysis, empirical mode decomposition (EMD) and wavelet transform (WT) were utilized to study the same bearing fault data. Also, the kurtosis and the peak levels of the EMD or the WT component corresponding to the bearing tones in the frequency domain were carefully checked and used as the bearing fault features. Next, MDC was used to classify the bearing fault features extracted by EMD, WT and MF-DFA in the time domain and assess the abilities of the three methods to extract fault features from bearing fault data. The results show that MF-DFA seems to outperform each of envelope analysis, statistical parameters, EMD and WT in feature extraction of bearing fault data and then the proposed method in this paper delivers satisfactory performances in distinguishing different types and severity of bearing faults. Furthermore, to further ascertain the nature causing the multifractality of bearing vibration data, the generalized Hurst exponents of the original bearing vibration data were compared with those of the shuffled and the surrogated data. Consequently, the long-range correlations for small and large fluctuations of data seem to be chiefly responsible for the multifractality of bearing vibration data.

Suitable conditions for liquid-phase microextraction using solidification of a floating drop for extraction of fat-soluble vitamins established using an orthogonal array experimental design.

PubMed

Sobhi, Hamid Reza; Yamini, Yadollah; Esrafili, Ali; Abadi, Reza Haji Hosseini Baghdad

2008-07-04

A simple, rapid and efficient microextraction method for the extraction and determination of some fat-soluble vitamins (A, D2, D3) in aqueous samples was developed. For the first time orthogonal array designs (OADs) were employed to screen the liquid-phase microextraction (LPME) method in which few microliters of 1-undecanol were delivered to the surface of the aqueous sample and it was agitated for a selected time. Then sample vial was cooled by inserting it into an ice bath for 5 min. The solidified solvent was transferred into a suitable vial and immediately melted. Then, the extract was directly injected into a high-performance liquid chromatography (HPLC) for analysis. Several factors affecting the microextraction efficiency such as sample solution temperature, stirring speed, volume of the organic solvent, ionic strength and extraction time were investigated and screened using an OA16 (4(5)) matrix. Under the best conditions (temperature, 55 degrees C; stirring speed, 1000 rpm; the volume of extracting solvent, 15.0 microL; no salt addition and extraction time, 60 min), detection limits of the method were in the range of 1.0-3.5 microgL(-1). The relative standard deviations (RSDs) to determine the vitamins at microg L(-1) levels by applying the proposed method varied in the range of 5.1-10.7%. Dynamic linear ranges of 5-500 mugL(-1) with good correlation coefficients (0.9984

Classification of Two Class Motor Imagery Tasks Using Hybrid GA-PSO Based K-Means Clustering.

PubMed

Suraj; Tiwari, Purnendu; Ghosh, Subhojit; Sinha, Rakesh Kumar

2015-01-01

Transferring the brain computer interface (BCI) from laboratory condition to meet the real world application needs BCI to be applied asynchronously without any time constraint. High level of dynamism in the electroencephalogram (EEG) signal reasons us to look toward evolutionary algorithm (EA). Motivated by these two facts, in this work a hybrid GA-PSO based K-means clustering technique has been used to distinguish two class motor imagery (MI) tasks. The proposed hybrid GA-PSO based K-means clustering is found to outperform genetic algorithm (GA) and particle swarm optimization (PSO) based K-means clustering techniques in terms of both accuracy and execution time. The lesser execution time of hybrid GA-PSO technique makes it suitable for real time BCI application. Time frequency representation (TFR) techniques have been used to extract the feature of the signal under investigation. TFRs based features are extracted and relying on the concept of event related synchronization (ERD) and desynchronization (ERD) feature vector is formed.

Classification of Two Class Motor Imagery Tasks Using Hybrid GA-PSO Based K-Means Clustering

PubMed Central

Suraj; Tiwari, Purnendu; Ghosh, Subhojit; Sinha, Rakesh Kumar

2015-01-01

Transferring the brain computer interface (BCI) from laboratory condition to meet the real world application needs BCI to be applied asynchronously without any time constraint. High level of dynamism in the electroencephalogram (EEG) signal reasons us to look toward evolutionary algorithm (EA). Motivated by these two facts, in this work a hybrid GA-PSO based K-means clustering technique has been used to distinguish two class motor imagery (MI) tasks. The proposed hybrid GA-PSO based K-means clustering is found to outperform genetic algorithm (GA) and particle swarm optimization (PSO) based K-means clustering techniques in terms of both accuracy and execution time. The lesser execution time of hybrid GA-PSO technique makes it suitable for real time BCI application. Time frequency representation (TFR) techniques have been used to extract the feature of the signal under investigation. TFRs based features are extracted and relying on the concept of event related synchronization (ERD) and desynchronization (ERD) feature vector is formed. PMID:25972896

Statistical Frequency-Dependent Analysis of Trial-to-Trial Variability in Single Time Series by Recurrence Plots.

PubMed

Tošić, Tamara; Sellers, Kristin K; Fröhlich, Flavio; Fedotenkova, Mariia; Beim Graben, Peter; Hutt, Axel

2015-01-01

For decades, research in neuroscience has supported the hypothesis that brain dynamics exhibits recurrent metastable states connected by transients, which together encode fundamental neural information processing. To understand the system's dynamics it is important to detect such recurrence domains, but it is challenging to extract them from experimental neuroscience datasets due to the large trial-to-trial variability. The proposed methodology extracts recurrent metastable states in univariate time series by transforming datasets into their time-frequency representations and computing recurrence plots based on instantaneous spectral power values in various frequency bands. Additionally, a new statistical inference analysis compares different trial recurrence plots with corresponding surrogates to obtain statistically significant recurrent structures. This combination of methods is validated by applying it to two artificial datasets. In a final study of visually-evoked Local Field Potentials in partially anesthetized ferrets, the methodology is able to reveal recurrence structures of neural responses with trial-to-trial variability. Focusing on different frequency bands, the δ-band activity is much less recurrent than α-band activity. Moreover, α-activity is susceptible to pre-stimuli, while δ-activity is much less sensitive to pre-stimuli. This difference in recurrence structures in different frequency bands indicates diverse underlying information processing steps in the brain.

Statistical Frequency-Dependent Analysis of Trial-to-Trial Variability in Single Time Series by Recurrence Plots

PubMed Central

Tošić, Tamara; Sellers, Kristin K.; Fröhlich, Flavio; Fedotenkova, Mariia; beim Graben, Peter; Hutt, Axel

2016-01-01

For decades, research in neuroscience has supported the hypothesis that brain dynamics exhibits recurrent metastable states connected by transients, which together encode fundamental neural information processing. To understand the system's dynamics it is important to detect such recurrence domains, but it is challenging to extract them from experimental neuroscience datasets due to the large trial-to-trial variability. The proposed methodology extracts recurrent metastable states in univariate time series by transforming datasets into their time-frequency representations and computing recurrence plots based on instantaneous spectral power values in various frequency bands. Additionally, a new statistical inference analysis compares different trial recurrence plots with corresponding surrogates to obtain statistically significant recurrent structures. This combination of methods is validated by applying it to two artificial datasets. In a final study of visually-evoked Local Field Potentials in partially anesthetized ferrets, the methodology is able to reveal recurrence structures of neural responses with trial-to-trial variability. Focusing on different frequency bands, the δ-band activity is much less recurrent than α-band activity. Moreover, α-activity is susceptible to pre-stimuli, while δ-activity is much less sensitive to pre-stimuli. This difference in recurrence structures in different frequency bands indicates diverse underlying information processing steps in the brain. PMID:26834580

Spatio-Temporal Dynamics of Impulse Responses to Figure Motion in Optic Flow Neurons

PubMed Central

Lee, Yu-Jen; Jönsson, H. Olof; Nordström, Karin

2015-01-01

White noise techniques have been used widely to investigate sensory systems in both vertebrates and invertebrates. White noise stimuli are powerful in their ability to rapidly generate data that help the experimenter decipher the spatio-temporal dynamics of neural and behavioral responses. One type of white noise stimuli, maximal length shift register sequences (m-sequences), have recently become particularly popular for extracting response kernels in insect motion vision. We here use such m-sequences to extract the impulse responses to figure motion in hoverfly lobula plate tangential cells (LPTCs). Figure motion is behaviorally important and many visually guided animals orient towards salient features in the surround. We show that LPTCs respond robustly to figure motion in the receptive field. The impulse response is scaled down in amplitude when the figure size is reduced, but its time course remains unaltered. However, a low contrast stimulus generates a slower response with a significantly longer time-to-peak and half-width. Impulse responses in females have a slower time-to-peak than males, but are otherwise similar. Finally we show that the shapes of the impulse response to a figure and a widefield stimulus are very similar, suggesting that the figure response could be coded by the same input as the widefield response. PMID:25955416

One-dimensional terahertz imaging of surfactant-stabilized dodecane-brine emulsion

NASA Astrophysics Data System (ADS)

Nickel, Daniel Vincent

Terahertz line-images of surfactant-stabilized dodecane(C12H 26)-brine emulsions are obtained by translating the emulsified region through the focus of a terahertz time-domain spectrometer, capturing a time-domain waveform at each vertical position. From these images, relative dodecane content, emulsion size, and stability can be extracted to evaluate the efficacy of the surfactant in solvating the dodecane. In addition, the images provide insight into the dynamics of concentrated emulsions after mixing.

Realization of a Quantum Integer-Spin Chain with Controllable Interactions

DTIC Science & Technology

2015-06-17

site participate in the dynamics. We observe the time evolution of the system and verify its coherence by entangling a pair of effective three-level...states generated by the XY Hamiltonian, we can verify entangle - ment between a pair of three-level systems with fidelities of up to 86%. Adding a time...3(b) shows an example of the measured parity curve used to extract the amplitude A and verify entanglement between the qutrit pair . Such measurements

A graph-based approach to detect spatiotemporal dynamics in satellite image time series

NASA Astrophysics Data System (ADS)

Guttler, Fabio; Ienco, Dino; Nin, Jordi; Teisseire, Maguelonne; Poncelet, Pascal

2017-08-01

Enhancing the frequency of satellite acquisitions represents a key issue for Earth Observation community nowadays. Repeated observations are crucial for monitoring purposes, particularly when intra-annual process should be taken into account. Time series of images constitute a valuable source of information in these cases. The goal of this paper is to propose a new methodological framework to automatically detect and extract spatiotemporal information from satellite image time series (SITS). Existing methods dealing with such kind of data are usually classification-oriented and cannot provide information about evolutions and temporal behaviors. In this paper we propose a graph-based strategy that combines object-based image analysis (OBIA) with data mining techniques. Image objects computed at each individual timestamp are connected across the time series and generates a set of evolution graphs. Each evolution graph is associated to a particular area within the study site and stores information about its temporal evolution. Such information can be deeply explored at the evolution graph scale or used to compare the graphs and supply a general picture at the study site scale. We validated our framework on two study sites located in the South of France and involving different types of natural, semi-natural and agricultural areas. The results obtained from a Landsat SITS support the quality of the methodological approach and illustrate how the framework can be employed to extract and characterize spatiotemporal dynamics.

Price dynamics in political prediction markets

PubMed Central

Majumder, Saikat Ray; Diermeier, Daniel; Rietz, Thomas A.; Amaral, Luís A. Nunes

2009-01-01

Prediction markets, in which contract prices are used to forecast future events, are increasingly applied to various domains ranging from political contests to scientific breakthroughs. However, the dynamics of such markets are not well understood. Here, we study the return dynamics of the oldest, most data-rich prediction markets, the Iowa Electronic Presidential Election “winner-takes-all” markets. As with other financial markets, we find uncorrelated returns, power-law decaying volatility correlations, and, usually, power-law decaying distributions of returns. However, unlike other financial markets, we find conditional diverging volatilities as the contract settlement date approaches. We propose a dynamic binary option model that captures all features of the empirical data and can potentially provide a tool with which one may extract true information events from a price time series. PMID:19155442

Reconstruction of dynamic structures of experimental setups based on measurable experimental data only

NASA Astrophysics Data System (ADS)

Chen, Tian-Yu; Chen, Yang; Yang, Hu-Jiang; Xiao, Jing-Hua; Hu, Gang

2018-03-01

Nowadays, massive amounts of data have been accumulated in various and wide fields, it has become today one of the central issues in interdisciplinary fields to analyze existing data and extract as much useful information as possible from data. It is often that the output data of systems are measurable while dynamic structures producing these data are hidden, and thus studies to reveal system structures by analyzing available data, i.e., reconstructions of systems become one of the most important tasks of information extractions. In the past, most of the works in this respect were based on theoretical analyses and numerical verifications. Direct analyses of experimental data are very rare. In physical science, most of the analyses of experimental setups were based on the first principles of physics laws, i.e., so-called top-down analyses. In this paper, we conducted an experiment of “Boer resonant instrument for forced vibration” (BRIFV) and inferred the dynamic structure of the experimental set purely from the analysis of the measurable experimental data, i.e., by applying the bottom-up strategy. Dynamics of the experimental set is strongly nonlinear and chaotic, and itʼs subjects to inevitable noises. We proposed to use high-order correlation computations to treat nonlinear dynamics; use two-time correlations to treat noise effects. By applying these approaches, we have successfully reconstructed the structure of the experimental setup, and the dynamic system reconstructed with the measured data reproduces good experimental results in a wide range of parameters.

Dynamic RSA: Examining parasympathetic regulatory dynamics via vector-autoregressive modeling of time-varying RSA and heart period.

PubMed

Fisher, Aaron J; Reeves, Jonathan W; Chi, Cyrus

2016-07-01

Expanding on recently published methods, the current study presents an approach to estimating the dynamic, regulatory effect of the parasympathetic nervous system on heart period on a moment-to-moment basis. We estimated second-to-second variation in respiratory sinus arrhythmia (RSA) in order to estimate the contemporaneous and time-lagged relationships among RSA, interbeat interval (IBI), and respiration rate via vector autoregression. Moreover, we modeled these relationships at lags of 1 s to 10 s, in order to evaluate the optimal latency for estimating dynamic RSA effects. The IBI (t) on RSA (t-n) regression parameter was extracted from individual models as an operationalization of the regulatory effect of RSA on IBI-referred to as dynamic RSA (dRSA). Dynamic RSA positively correlated with standard averages of heart rate and negatively correlated with standard averages of RSA. We propose that dRSA reflects the active downregulation of heart period by the parasympathetic nervous system and thus represents a novel metric that provides incremental validity in the measurement of autonomic cardiac control-specifically, a method by which parasympathetic regulatory effects can be measured in process. © 2016 Society for Psychophysiological Research.

Probing nanocrystalline grain dynamics in nanodevices

PubMed Central

Yeh, Sheng-Shiuan; Chang, Wen-Yao; Lin, Juhn-Jong

2017-01-01

Dynamical structural defects exist naturally in a wide variety of solids. They fluctuate temporally and hence can deteriorate the performance of many electronic devices. Thus far, the entities of these dynamic objects have been identified to be individual atoms. On the other hand, it is a long-standing question whether a nanocrystalline grain constituted of a large number of atoms can switch, as a whole, reversibly like a dynamical atomic defect (that is, a two-level system). This is an emergent issue considering the current development of nanodevices with ultralow electrical noise, qubits with long quantum coherence time, and nanoelectromechanical system sensors with ultrahigh resolution. We demonstrate experimental observations of dynamic nanocrystalline grains that repeatedly switch between two or more metastable coordinate states. We study temporal resistance fluctuations in thin ruthenium dioxide (RuO2) metal nanowires and extract microscopic parameters, including relaxation time scales, mobile grain sizes, and the bonding strengths of nanograin boundaries. These material parameters are not obtainable by other experimental approaches. When combined with previous in situ high-resolution transmission electron microscopy, our electrical method can be used to infer rich information about the structural dynamics of a wide variety of nanodevices and new two-dimensional materials. PMID:28691094

Machine Learning and Network Analysis of Molecular Dynamics Trajectories Reveal Two Chains of Red/Ox-specific Residue Interactions in Human Protein Disulfide Isomerase.

PubMed

Karamzadeh, Razieh; Karimi-Jafari, Mohammad Hossein; Sharifi-Zarchi, Ali; Chitsaz, Hamidreza; Salekdeh, Ghasem Hosseini; Moosavi-Movahedi, Ali Akbar

2017-06-16

The human protein disulfide isomerase (hPDI), is an essential four-domain multifunctional enzyme. As a result of disulfide shuffling in its terminal domains, hPDI exists in two oxidation states with different conformational preferences which are important for substrate binding and functional activities. Here, we address the redox-dependent conformational dynamics of hPDI through molecular dynamics (MD) simulations. Collective domain motions are identified by the principal component analysis of MD trajectories and redox-dependent opening-closing structure variations are highlighted on projected free energy landscapes. Then, important structural features that exhibit considerable differences in dynamics of redox states are extracted by statistical machine learning methods. Mapping the structural variations to time series of residue interaction networks also provides a holistic representation of the dynamical redox differences. With emphasizing on persistent long-lasting interactions, an approach is proposed that compiled these time series networks to a single dynamic residue interaction network (DRIN). Differential comparison of DRIN in oxidized and reduced states reveals chains of residue interactions that represent potential allosteric paths between catalytic and ligand binding sites of hPDI.

Fractal Folding and Medium Viscoelasticity Contribute Jointly to Chromosome Dynamics

NASA Astrophysics Data System (ADS)

Polovnikov, K. E.; Gherardi, M.; Cosentino-Lagomarsino, M.; Tamm, M. V.

2018-02-01

Chromosomes are key players of cell physiology, their dynamics provides valuable information about its physical organization. In both prokaryotes and eukaryotes, the short-time motion of chromosomal loci has been described with a Rouse model in a simple or viscoelastic medium. However, little emphasis has been put on the influence of the folded organization of chromosomes on the local dynamics. Clearly, stress propagation, and thus dynamics, must be affected by such organization, but a theory allowing us to extract such information from data, e.g., on two-point correlations, is lacking. Here, we describe a theoretical framework able to answer this general polymer dynamics question. We provide a scaling analysis of the stress-propagation time between two loci at a given arclength distance along the chromosomal coordinate. The results suggest a precise way to assess folding information from the dynamical coupling of chromosome segments. Additionally, we realize this framework in a specific model of a polymer whose long-range interactions are designed to make it fold in a fractal way and immersed in a medium characterized by subdiffusive fractional Langevin motion with a tunable scaling exponent. This allows us to derive explicit analytical expressions for the correlation functions.

Will a category cue attract you? Motor output reveals dynamic competition across person construal.

PubMed

Freeman, Jonathan B; Ambady, Nalini; Rule, Nicholas O; Johnson, Kerri L

2008-11-01

People use social categories to perceive others, extracting category cues to glean membership. Growing evidence for continuous dynamics in real-time cognition suggests, contrary to prevailing social psychological accounts, that person construal may involve dynamic competition between simultaneously active representations. To test this, the authors examined social categorization in real-time by streaming the x, y coordinates of hand movements as participants categorized typical and atypical faces by sex. Though judgments of atypical targets were largely accurate, online motor output exhibited a continuous spatial attraction toward the opposite sex category, indicating dynamic competition between multiple social category alternatives. The authors offer a dynamic continuity account of social categorization and provide converging evidence across categorizations of real male and female faces (containing a typical or an atypical sex-specifying cue) and categorizations of computer-generated male and female faces (with subtly morphed sex-typical or sex-atypical features). In 3 studies, online motor output revealed continuous dynamics underlying person construal, in which multiple simultaneously and partially active category representations gradually cascade into social categorical judgments. Such evidence is challenging for discrete stage-based accounts. (c) 2008 APA, all rights reserved

Multisensor-based real-time quality monitoring by means of feature extraction, selection and modeling for Al alloy in arc welding

NASA Astrophysics Data System (ADS)

Zhang, Zhifen; Chen, Huabin; Xu, Yanling; Zhong, Jiyong; Lv, Na; Chen, Shanben

2015-08-01

Multisensory data fusion-based online welding quality monitoring has gained increasing attention in intelligent welding process. This paper mainly focuses on the automatic detection of typical welding defect for Al alloy in gas tungsten arc welding (GTAW) by means of analzing arc spectrum, sound and voltage signal. Based on the developed algorithms in time and frequency domain, 41 feature parameters were successively extracted from these signals to characterize the welding process and seam quality. Then, the proposed feature selection approach, i.e., hybrid fisher-based filter and wrapper was successfully utilized to evaluate the sensitivity of each feature and reduce the feature dimensions. Finally, the optimal feature subset with 19 features was selected to obtain the highest accuracy, i.e., 94.72% using established classification model. This study provides a guideline for feature extraction, selection and dynamic modeling based on heterogeneous multisensory data to achieve a reliable online defect detection system in arc welding.

Optimization of process parameters for supercritical fluid extraction of cholesterol from whole milk powder using ethanol as co-solvent.

PubMed

Dey Paul, Indira; Jayakumar, Chitra; Niwas Mishra, Hari

2016-12-01

In spite of being highly nutritious, the consumption of milk is hindered because of its high cholesterol content, which is responsible for numerous cardiac diseases. Supercritical carbon dioxide using ethanol as co-solvent was employed to extract cholesterol from whole milk powder (WMP). This study was undertaken to optimize the process parameters of supercritical fluid extraction (SCFE), viz. extraction temperature, pressure and volume of ethanol. The cholesterol content of WMP was quantified using high-performance liquid chromatography. The impact of the extraction conditions on the fat content (FC), solubility index (SI) and lightness (L*) of the SCFE-treated WMP were also investigated. The process parameters were optimized using response surface methodology. About 46% reduction in cholesterol was achieved at the optimized conditions of 48 °C, 17 MPa and 31 mL co-solvent; flow rate of expanded CO 2 , static time and dynamic time of extraction were 6 L min -1 , 10 min and 80 min respectively. The treated WMP retained its FC, SI, and L* at moderate limits of 183.67 g kg -1 , 96.3% and 96.90, respectively. This study demonstrated the feasibility of ethanol-modified SCFE of cholesterol from WMP with negligible changes in its physicochemical properties. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Multiscale Behavior of Viscous Fluids Dynamics: Experimental Observations

NASA Astrophysics Data System (ADS)

Arciniega-Ceballos, Alejandra; Spina, Laura; Scheu, Bettina; Dingwell, Donald B.

2016-04-01

The dynamics of Newtonian fluids with viscosities of mafic to intermediate silicate melts (10-1000 Pa s) during slow decompression present multi-time scale processes. To observe these processes we have performed several experiments on silicon oil saturated with Argon gas for 72 hours, in a Plexiglas autoclave. The slow decompression, dropping from 10 MPa to ambient pressure, acting as the excitation mechanism, triggered several processes with their own distinct timescales. These processes generate complex non-stationary microseismic signals, which have been recorded with 7 high-dynamic piezoelectric sensors located along the conduit flanked by high-speed video recordings. The analysis in time and frequency of these time series and their correlation with the associated high-speed imaging enables the characterization of distinct phases and the extraction of the individual processes during the evolution of decompression of these viscous fluids. We have observed fluid-solid elastic interaction, degassing, fluid mass expansion and flow, bubble nucleation, growth, coalescence and collapse, foam building and vertical wagging. All these processes (in fine and coarse scales) are sequentially coupled in time, occur within specific pressure intervals, and exhibit a localized distribution along the conduit. Their coexistence and interactions constitute the stress field and driving forces that determine the dynamics of the conduit system. Our observations point to the great potential of this experimental approach in the understanding of volcanic conduit dynamics and volcanic seismicity.

Targeted Data Extraction of the MS/MS Spectra Generated by Data-independent Acquisition: A New Concept for Consistent and Accurate Proteome Analysis*

PubMed Central

Gillet, Ludovic C.; Navarro, Pedro; Tate, Stephen; Röst, Hannes; Selevsek, Nathalie; Reiter, Lukas; Bonner, Ron; Aebersold, Ruedi

2012-01-01

Most proteomic studies use liquid chromatography coupled to tandem mass spectrometry to identify and quantify the peptides generated by the proteolysis of a biological sample. However, with the current methods it remains challenging to rapidly, consistently, reproducibly, accurately, and sensitively detect and quantify large fractions of proteomes across multiple samples. Here we present a new strategy that systematically queries sample sets for the presence and quantity of essentially any protein of interest. It consists of using the information available in fragment ion spectral libraries to mine the complete fragment ion maps generated using a data-independent acquisition method. For this study, the data were acquired on a fast, high resolution quadrupole-quadrupole time-of-flight (TOF) instrument by repeatedly cycling through 32 consecutive 25-Da precursor isolation windows (swaths). This SWATH MS acquisition setup generates, in a single sample injection, time-resolved fragment ion spectra for all the analytes detectable within the 400–1200 m/z precursor range and the user-defined retention time window. We show that suitable combinations of fragment ions extracted from these data sets are sufficiently specific to confidently identify query peptides over a dynamic range of 4 orders of magnitude, even if the precursors of the queried peptides are not detectable in the survey scans. We also show that queried peptides are quantified with a consistency and accuracy comparable with that of selected reaction monitoring, the gold standard proteomic quantification method. Moreover, targeted data extraction enables ad libitum quantification refinement and dynamic extension of protein probing by iterative re-mining of the once-and-forever acquired data sets. This combination of unbiased, broad range precursor ion fragmentation and targeted data extraction alleviates most constraints of present proteomic methods and should be equally applicable to the comprehensive analysis of other classes of analytes, beyond proteomics. PMID:22261725

Solving of the coefficient inverse problems for a nonlinear singularly perturbed reaction-diffusion-advection equation with the final time data

NASA Astrophysics Data System (ADS)

Lukyanenko, D. V.; Shishlenin, M. A.; Volkov, V. T.

2018-01-01

We propose the numerical method for solving coefficient inverse problem for a nonlinear singularly perturbed reaction-diffusion-advection equation with the final time observation data based on the asymptotic analysis and the gradient method. Asymptotic analysis allows us to extract a priory information about interior layer (moving front), which appears in the direct problem, and boundary layers, which appear in the conjugate problem. We describe and implement the method of constructing a dynamically adapted mesh based on this a priory information. The dynamically adapted mesh significantly reduces the complexity of the numerical calculations and improve the numerical stability in comparison with the usual approaches. Numerical example shows the effectiveness of the proposed method.

Direct identification of predator-prey dynamics in gyrokinetic simulations

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

Kobayashi, Sumire, E-mail: sumire.kobayashi@lpp.polytechnique.fr; Gürcan, Özgür D; Diamond, Patrick H.

2015-09-15

The interaction between spontaneously formed zonal flows and small-scale turbulence in nonlinear gyrokinetic simulations is explored in a shearless closed field line geometry. It is found that when clear limit cycle oscillations prevail, the observed turbulent dynamics can be quantitatively captured by a simple Lotka-Volterra type predator-prey model. Fitting the time traces of full gyrokinetic simulations by such a reduced model allows extraction of the model coefficients. Scanning physical plasma parameters, such as collisionality and density gradient, it was observed that the effective growth rates of turbulence (i.e., the prey) remain roughly constant, in spite of the higher and varyingmore » level of primary mode linear growth rates. The effective growth rate that was extracted corresponds roughly to the zonal-flow-modified primary mode growth rate. It was also observed that the effective damping of zonal flows (i.e., the predator) in the parameter range, where clear predator-prey dynamics is observed, (i.e., near marginal stability) agrees with the collisional damping expected in these simulations. This implies that the Kelvin-Helmholtz-like instability may be negligible in this range. The results imply that when the tertiary instability plays a role, the dynamics becomes more complex than a simple Lotka-Volterra predator prey.« less

Supercritical fluid extraction of selected pharmaceuticals from water and serum.

PubMed

Simmons, B R; Stewart, J T

1997-01-24

Selected drugs from benzodiazepine, anabolic agent and non-steroidal anti-inflammatory drug (NSAID) therapeutic classes were extracted from water and serum using a supercritical CO2 mobile phase. The samples were extracted at a pump pressure of 329 MPa, an extraction chamber temperature of 45 degrees C, and a restrictor temperature of 60 degrees C. The static extraction time for all samples was 2.5 min and the dynamic extraction time ranged from 5 to 20 min. The analytes were collected in appropriate solvent traps and assayed by modified literature HPLC procedures. Analyte recoveries were calculated based on peak height measurements of extracted vs. unextracted analyte. The recovery of the benzodiazepines ranged from 80 to 98% in water and from 75 to 94% in serum. Anabolic drug recoveries from water and serum ranged from 67 to 100% and 70 to 100%, respectively. The NSAIDs were recovered from water in the 76 to 97% range and in the 76 to 100% range from serum. Accuracy, precision and endogenous peak interference, if any, were determined for blank and spiked serum extractions and compared with classical sample preparation techniques of liquid-liquid and solid-phase extraction reported in the literature. For the benzodiazepines, accuracy and precision for supercritical fluid extraction (SFE) ranged from 1.95 to 3.31 and 0.57 to 1.25%, respectively (n = 3). The SFE accuracy and precision data for the anabolic agents ranged from 4.03 to 7.84 and 0.66 to 2.78%, respectively (n = 3). The accuracy and precision data reported for the SFE of the NSAIDs ranged from 2.79 to 3.79 and 0.33 to 1.27%, respectively (n = 3). The precision of the SFE method from serum was shown to be comparable to the precision obtained with other classical preparation techniques.

Can SNOMED CT be squeezed without losing its shape?

PubMed

López-García, Pablo; Schulz, Stefan

2016-09-21

In biomedical applications where the size and complexity of SNOMED CT become problematic, using a smaller subset that can act as a reasonable substitute is usually preferred. In a special class of use cases-like ontology-based quality assurance, or when performing scaling experiments for real-time performance-it is essential that modules show a similar shape than SNOMED CT in terms of concept distribution per sub-hierarchy. Exactly how to extract such balanced modules remains unclear, as most previous work on ontology modularization has focused on other problems. In this study, we investigate to what extent extracting balanced modules that preserve the original shape of SNOMED CT is possible, by presenting and evaluating an iterative algorithm. We used a graph-traversal modularization approach based on an input signature. To conform to our definition of a balanced module, we implemented an iterative algorithm that carefully bootstraped and dynamically adjusted the signature at each step. We measured the error for each sub-hierarchy and defined convergence as a residual sum of squares <1. Using 2000 concepts as an initial signature, our algorithm converged after seven iterations and extracted a module 4.7 % the size of SNOMED CT. Seven sub-hierarhies were either over or under-represented within a range of 1-8 %. Our study shows that balanced modules from large terminologies can be extracted using ontology graph-traversal modularization techniques under certain conditions: that the process is repeated a number of times, the input signature is dynamically adjusted in each iteration, and a moderate under/over-representation of some hierarchies is tolerated. In the case of SNOMED CT, our results conclusively show that it can be squeezed to less than 5 % of its size without any sub-hierarchy losing its shape more than 8 %, which is likely sufficient in most use cases.

Experimental Observations of Multiscale Dynamics of Viscous Fluid Behavior: Implications in Volcanic Systems

NASA Astrophysics Data System (ADS)

Arciniega-Ceballos, A.; Spina, L.; Scheu, B.; Dingwell, D. B.

2015-12-01

We have investigated the dynamics of Newtonian fluids with viscosities (10-1000 Pa s; corresponding to mafic to intermediate silicate melts) during slow decompression, in a Plexiglas shock tube. As an analogue fluid we used silicon oil saturated with Argon gas for 72 hours. Slow decompression, dropping from 10 MPa to ambient pressure, acts as the excitation mechanism, initiating several processes with their own distinct timescales. The evolution of this multi-timescale phenomenon generates complex non-stationary microseismic signals, which have been recorded with 7 high-dynamic piezoelectric sensors located along the conduit. Correlation analysis of these time series with the associated high-speed imaging enables characterization of distinct phases of the dynamics of these viscous fluids and the extraction of the time and the frequency characteristics of the individual processes. We have identified fluid-solid elastic interaction, degassing, fluid mass expansion and flow, bubble nucleation, growth, coalescence and collapse, foam building and vertical wagging. All these processes (in fine and coarse scales) are sequentially coupled in time, occur within specific pressure intervals, and exhibit a localized distribution in space. Their coexistence and interactions constitute the stress field and driving forces that determine the dynamics of the system. Our observations point to the great potential of this experimental approach in the understanding of volcanic processes and volcanic seismicity.

Evaluation of a method for the simultaneous quantification of N-nitrosamines in water samples based on stir bar sorptive extraction combined with high-performance liquid chromatography and diode array detection.

PubMed

Talebpour, Zahra; Rostami, Simindokht; Rezadoost, Hassan

2015-05-01

A simple, sensitive, and reliable procedure based on stir bar sorptive extraction coupled with high-performance liquid chromatography was applied to simultaneously extract and determine three semipolar nitrosamines including N-nitrosodibutylamine, N-nitrosodiphenylamine, and N-nitrosodicyclohexylamine. To achieve the optimum conditions, the effective parameters on the extraction efficiency including desorption solvent and time, ionic strength of sample, extraction time, and sample volume were systematically investigated. The optimized extraction procedure was carried out by stir bars coated with polydimethylsiloxane. Under optimum extraction conditions, the performance of the proposed method was studied. The linear dynamic range was obtained in the range of 0.95-1000 ng/mL (r = 0.9995), 0.26-1000 ng/mL (r = 0.9988) and both 0.32-100 ng/mL (r = 0.9999) and 100-1000 ng/mL (r = 0.9998) with limits of detection of 0.28, 0.08, and 0.09 ng/mL for N-nitrosodibutylamine, N-nitrosodiphenylamine, and N-nitrosodicyclohexylamine, respectively. The average recoveries were obtained >81%, and the reproducibility of the proposed method presented as intra- and interday precision were also found with a relative standard deviation <6%. Finally, the proposed method was successfully applied to the determination of trace amounts of selected nitrosamines in various water and wastewater samples and the obtained results were confirmed using mass spectrometry. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Multiscale Analysis of Time Irreversibility Based on Phase-Space Reconstruction and Horizontal Visibility Graph Approach

NASA Astrophysics Data System (ADS)

Zhang, Yongping; Shang, Pengjian; Xiong, Hui; Xia, Jianan

Time irreversibility is an important property of nonequilibrium dynamic systems. A visibility graph approach was recently proposed, and this approach is generally effective to measure time irreversibility of time series. However, its result may be unreliable when dealing with high-dimensional systems. In this work, we consider the joint concept of time irreversibility and adopt the phase-space reconstruction technique to improve this visibility graph approach. Compared with the previous approach, the improved approach gives a more accurate estimate for the irreversibility of time series, and is more effective to distinguish irreversible and reversible stochastic processes. We also use this approach to extract the multiscale irreversibility to account for the multiple inherent dynamics of time series. Finally, we apply the approach to detect the multiscale irreversibility of financial time series, and succeed to distinguish the time of financial crisis and the plateau. In addition, Asian stock indexes away from other indexes are clearly visible in higher time scales. Simulations and real data support the effectiveness of the improved approach when detecting time irreversibility.

Incremental fuzzy C medoids clustering of time series data using dynamic time warping distance

PubMed Central

Chen, Jingli; Wu, Shuai; Liu, Zhizhong; Chao, Hao

2018-01-01

Clustering time series data is of great significance since it could extract meaningful statistics and other characteristics. Especially in biomedical engineering, outstanding clustering algorithms for time series may help improve the health level of people. Considering data scale and time shifts of time series, in this paper, we introduce two incremental fuzzy clustering algorithms based on a Dynamic Time Warping (DTW) distance. For recruiting Single-Pass and Online patterns, our algorithms could handle large-scale time series data by splitting it into a set of chunks which are processed sequentially. Besides, our algorithms select DTW to measure distance of pair-wise time series and encourage higher clustering accuracy because DTW could determine an optimal match between any two time series by stretching or compressing segments of temporal data. Our new algorithms are compared to some existing prominent incremental fuzzy clustering algorithms on 12 benchmark time series datasets. The experimental results show that the proposed approaches could yield high quality clusters and were better than all the competitors in terms of clustering accuracy. PMID:29795600

Incremental fuzzy C medoids clustering of time series data using dynamic time warping distance.

PubMed

Liu, Yongli; Chen, Jingli; Wu, Shuai; Liu, Zhizhong; Chao, Hao

2018-01-01

Clustering time series data is of great significance since it could extract meaningful statistics and other characteristics. Especially in biomedical engineering, outstanding clustering algorithms for time series may help improve the health level of people. Considering data scale and time shifts of time series, in this paper, we introduce two incremental fuzzy clustering algorithms based on a Dynamic Time Warping (DTW) distance. For recruiting Single-Pass and Online patterns, our algorithms could handle large-scale time series data by splitting it into a set of chunks which are processed sequentially. Besides, our algorithms select DTW to measure distance of pair-wise time series and encourage higher clustering accuracy because DTW could determine an optimal match between any two time series by stretching or compressing segments of temporal data. Our new algorithms are compared to some existing prominent incremental fuzzy clustering algorithms on 12 benchmark time series datasets. The experimental results show that the proposed approaches could yield high quality clusters and were better than all the competitors in terms of clustering accuracy.

Modelling and simulation of a moving interface problem: freeze drying of black tea extract

NASA Astrophysics Data System (ADS)

Aydin, Ebubekir Sıddık; Yucel, Ozgun; Sadikoglu, Hasan

2017-06-01

The moving interface separates the material that is subjected to the freeze drying process as dried and frozen. Therefore, the accurate modeling the moving interface reduces the process time and energy consumption by improving the heat and mass transfer predictions during the process. To describe the dynamic behavior of the drying stages of the freeze-drying, a case study of brewed black tea extract in storage trays including moving interface was modeled that the heat and mass transfer equations were solved using orthogonal collocation method based on Jacobian polynomial approximation. Transport parameters and physical properties describing the freeze drying of black tea extract were evaluated by fitting the experimental data using Levenberg-Marquardt algorithm. Experimental results showed good agreement with the theoretical predictions.

A comparison study on a sulfonated graphene-polyaniline nanocomposite coated fiber for analysis of nicotine in solid samples through the traditional and vacuum-assisted HS-SPME.

PubMed

Ghiasvand, Alireza; Koonani, Samira; Yazdankhah, Fatemeh; Farhadi, Saeid

2018-02-05

A simple, rapid, and reliable headspace solid-phase microextraction (HS-SPME) procedure, reinforced by applying vacuum in the extraction vial, was developed. It was applied for the extraction of nicotine in solid samples prior to determination by gas chromatography-flame ionization detection (GC-FID). First, the surface of a narrow stainless steel wire was made porous and adhesive by platinization to obtain a durable, higher surface area, and resistant fiber. Then, a thin film of sulfonated graphene/polyaniline (Sulf-G/PANI) nanocomposite was synthesized and simultaneously coated on the platinized fiber using the electrophoretic deposition (EPD) method. It was demonstrated that the extraction efficiency remarkably increased by applying the reduced-pressure condition in the extraction vial. To evaluate the conventional HS-SPME and vacuum-assisted HS-SPME (VA-HS-SPME) platforms, all experimental parameters affecting the extraction efficiency including desorption time and temperature, extraction time and temperature and moisture content of sample matrix were optimized. The highest extraction efficiency was obtained at 60°C, 10min (extraction temperature and time) and 280°C, 2min (desorption condition), for VA-HS-SPME strategy, while for conventional HS-SPME the extraction and desorption conditions found to be 100°C, 30min and 280°C, 2min, respectively. The Sulf-G/PANI coated fiber showed high thermal stability, good chemical/mechanical resistance, and long lifetime. For analysis of nicotine in solid samples using VA-HS-SPME-GC-FID, linear dynamic range (LDR) was 0.01-30μgg -1 (R 2 =0.996), the relative standard deviation (RSD%, n=6), for analyses of 1μgg -1 nicotine was calculated 3.4% and limit of detection (LOD) found to be 0.002μgg -1 . The VA-HS-SPME-GC-FID strategy was successfully carried out for quantitation of nicotine in hair and tobacco real samples. Copyright © 2017 Elsevier B.V. All rights reserved.

Tracking transcriptional activities with high-content epifluorescent imaging

NASA Astrophysics Data System (ADS)

Hua, Jianping; Sima, Chao; Cypert, Milana; Gooden, Gerald C.; Shack, Sonsoles; Alla, Lalitamba; Smith, Edward A.; Trent, Jeffrey M.; Dougherty, Edward R.; Bittner, Michael L.

2012-04-01

High-content cell imaging based on fluorescent protein reporters has recently been used to track the transcriptional activities of multiple genes under different external stimuli for extended periods. This technology enhances our ability to discover treatment-induced regulatory mechanisms, temporally order their onsets and recognize their relationships. To fully realize these possibilities and explore their potential in biological and pharmaceutical applications, we introduce a new data processing procedure to extract information about the dynamics of cell processes based on this technology. The proposed procedure contains two parts: (1) image processing, where the fluorescent images are processed to identify individual cells and allow their transcriptional activity levels to be quantified; and (2) data representation, where the extracted time course data are summarized and represented in a way that facilitates efficient evaluation. Experiments show that the proposed procedure achieves fast and robust image segmentation with sufficient accuracy. The extracted cellular dynamics are highly reproducible and sensitive enough to detect subtle activity differences and identify mechanisms responding to selected perturbations. This method should be able to help biologists identify the alterations of cellular mechanisms that allow drug candidates to change cell behavior and thereby improve the efficiency of drug discovery and treatment design.

A Tribute to J. C. Sprott

NASA Astrophysics Data System (ADS)

Nazarimehr, Fahimeh; Jafari, Sajad; Chen, Guanrong; Kapitaniak, Tomasz; Kuznetsov, Nikolay V.; Leonov, Gennady A.; Li, Chunbiao; Wei, Zhouchao

2017-12-01

In honor of his 75th birthday, we review the prominent works of Professor Julien Clinton Sprott in chaos and nonlinear dynamics. We categorize his works into three important groups. The first and most important group is identifying new dynamical systems with special properties. He has proposed different chaotic maps, flows, complex variable systems, nonautonomous systems, partial differential equations, fractional-order systems, delay differential systems, spatiotemporal systems, artificial neural networks, and chaotic electrical circuits. He has also studied dynamical properties of complex systems such as bifurcations and basins of attraction. He has done work on generating fractal art. He has examined models of real-world systems that exhibit chaos. The second group of his works comprise control and synchronization of chaos. Finally, the third group is extracting dynamical properties of systems using time-series analysis. This paper highlights the impact of Sprott’s work on the promotion of nonlinear dynamics.

Intelligent classifier for dynamic fault patterns based on hidden Markov model

NASA Astrophysics Data System (ADS)

Xu, Bo; Feng, Yuguang; Yu, Jinsong

2006-11-01

It's difficult to build precise mathematical models for complex engineering systems because of the complexity of the structure and dynamics characteristics. Intelligent fault diagnosis introduces artificial intelligence and works in a different way without building the analytical mathematical model of a diagnostic object, so it's a practical approach to solve diagnostic problems of complex systems. This paper presents an intelligent fault diagnosis method, an integrated fault-pattern classifier based on Hidden Markov Model (HMM). This classifier consists of dynamic time warping (DTW) algorithm, self-organizing feature mapping (SOFM) network and Hidden Markov Model. First, after dynamic observation vector in measuring space is processed by DTW, the error vector including the fault feature of being tested system is obtained. Then a SOFM network is used as a feature extractor and vector quantization processor. Finally, fault diagnosis is realized by fault patterns classifying with the Hidden Markov Model classifier. The importing of dynamic time warping solves the problem of feature extracting from dynamic process vectors of complex system such as aeroengine, and makes it come true to diagnose complex system by utilizing dynamic process information. Simulating experiments show that the diagnosis model is easy to extend, and the fault pattern classifier is efficient and is convenient to the detecting and diagnosing of new faults.

Quantification of Campylobacter spp. in pig feces by direct real-time PCR with an internal control of extraction and amplification.

PubMed

Leblanc-Maridor, Mily; Garénaux, Amélie; Beaudeau, François; Chidaine, Bérangère; Seegers, Henri; Denis, Martine; Belloc, Catherine

2011-04-01

The rapid and direct quantification of Campylobacter spp. in complex substrates like feces or environmental samples is crucial to facilitate epidemiological studies on Campylobacter in pig production systems. We developed a real-time PCR assay for detecting and quantifying Campylobacter spp. directly in pig feces with the use of an internal control. Campylobacter spp. and Yersinia ruckeri primers-probes sets were designed and checked for specificity with diverse Campylobacter, related organisms, and other bacterial pathogens before being used in field samples. The quantification of Campylobacter spp. by the real-time PCR then was realized on 531 fecal samples obtained from experimentally and naturally infected pigs; the numeration of Campylobacter on Karmali plate was done in parallel. Yersinia ruckeri, used as bacterial internal control, was added to the samples before DNA extraction to control DNA-extraction and PCR-amplification. The sensitivity of the PCR assay was 10 genome copies. The established Campylobacter real-time PCR assay showed a 7-log-wide linear dynamic range of quantification (R²=0.99) with a detection limit of 200 Colony Forming Units of Campylobacter per gram of feces. A high correlation was found between the results obtained by real-time PCR and those by culture at both qualitative and quantitative levels. Moreover, DNA extraction followed by real-time PCR reduced the time needed for analysis to a few hours (within a working day). In conclusion, the real-time PCR developed in this study provides new tools for further epidemiological surveys to investigate the carriage and excretion of Campylobacter by pigs. Copyright © 2011 Elsevier B.V. All rights reserved.

Extraction of ochratoxin A in red wine with dopamine-coated magnetic multi-walled carbon nanotubes.

PubMed

Wan, Hong; Zhang, Bo; Bai, Xiao-Lin; Zhao, Yan; Xiao, Meng-Wei; Liao, Xun

2017-10-01

A new, rapid, green, and cost-effective magnetic solid-phase extraction of ochratoxin A from red wine samples was developed using polydopamine-coated magnetic multi-walled carbon nanotubes as the absorbent. The polydopamine-coated magnetic multi-walled carbon nanotubes were fabricated with magnetic multi-walled carbon nanotubes and dopamine by an in situ oxidative self-polymerization approach. Transmission electron microscopy, dynamic light scattering, X-ray photoelectron spectroscopy and vibrating sample magnetometry were used to characterize the absorbents. Ochratoxin A was quantified with high-performance liquid chromatography coupled with fluorescence detection, with excitation and emission wavelengths of 338 and 455 nm, respectively. The conditions affecting the magnetic solid-phase extraction procedure, such as pH, extraction solution, extraction time, absorbent amount, desorption solution and desorption time were investigated to obtain the optimal extraction conditions. Under the optimized conditions, the extraction recovery was 91.8-104.5% for ochratoxin A. A linear calibration curve was obtained in the range of 0.1-2.0 ng/mL. The limit of detection was 0.07 ng/mL, and the limit of quantitation was 0.21 ng/mL. The recoveries of ochratoxin A for spiked red wine sample ranged from 95.65 to 100.65% with relative standard deviation less than 8%. The polydopamine-coated magnetic multi-walled carbon nanotubes showed a high affinity toward ochratoxin A, allowing selective extraction and quantification of ochratoxin A from complex sample matrixes. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

On continuous user authentication via typing behavior.

PubMed

Roth, Joseph; Liu, Xiaoming; Metaxas, Dimitris

2014-10-01

We hypothesize that an individual computer user has a unique and consistent habitual pattern of hand movements, independent of the text, while typing on a keyboard. As a result, this paper proposes a novel biometric modality named typing behavior (TB) for continuous user authentication. Given a webcam pointing toward a keyboard, we develop real-time computer vision algorithms to automatically extract hand movement patterns from the video stream. Unlike the typical continuous biometrics, such as keystroke dynamics (KD), TB provides a reliable authentication with a short delay, while avoiding explicit key-logging. We collect a video database where 63 unique subjects type static text and free text for multiple sessions. For one typing video, the hands are segmented in each frame and a unique descriptor is extracted based on the shape and position of hands, as well as their temporal dynamics in the video sequence. We propose a novel approach, named bag of multi-dimensional phrases, to match the cross-feature and cross-temporal pattern between a gallery sequence and probe sequence. The experimental results demonstrate a superior performance of TB when compared with KD, which, together with our ultrareal-time demo system, warrant further investigation of this novel vision application and biometric modality.

Local Time-Dependent Charging in a Perovskite Solar Cell.

PubMed

Bergmann, Victor W; Guo, Yunlong; Tanaka, Hideyuki; Hermes, Ilka M; Li, Dan; Klasen, Alexander; Bretschneider, Simon A; Nakamura, Eiichi; Berger, Rüdiger; Weber, Stefan A L

2016-08-03

Efficient charge extraction within solar cells explicitly depends on the optimization of the internal interfaces. Potential barriers, unbalanced charge extraction, and interfacial trap states can prevent cells from reaching high power conversion efficiencies. In the case of perovskite solar cells, slow processes happening on time scales of seconds cause hysteresis in the current-voltage characteristics. In this work, we localized and investigated these slow processes using frequency-modulation Kelvin probe force microscopy (FM-KPFM) on cross sections of planar methylammonium lead iodide (MAPI) perovskite solar cells. FM-KPFM can map the charge density distribution and its dynamics at internal interfaces. Upon illumination, space charge layers formed at the interfaces of the selective contacts with the MAPI layer within several seconds. We observed distinct differences in the charging dynamics at the interfaces of MAPI with adjacent layers. Our results indicate that more than one process is involved in hysteresis. This finding is in agreement with recent simulation studies claiming that a combination of ion migration and interfacial trap states causes the hysteresis in perovskite solar cells. Such differences in the charging rates at different interfaces cannot be separated by conventional device measurements.

Optimal control of energy extraction in LES of large wind farms

NASA Astrophysics Data System (ADS)

Meyers, Johan; Goit, Jay; Munters, Wim

2014-11-01

We investigate the use of optimal control combined with Large-Eddy Simulations (LES) of wind-farm boundary layer interaction for the increase of total energy extraction in very large ``infinite'' wind farms and in finite farms. We consider the individual wind turbines as flow actuators, whose energy extraction can be dynamically regulated in time so as to optimally influence the turbulent flow field, maximizing the wind farm power. For the simulation of wind-farm boundary layers we use large-eddy simulations in combination with an actuator-disk representation of wind turbines. Simulations are performed in our in-house pseudo-spectral code SP-Wind. For the optimal control study, we consider the dynamic control of turbine-thrust coefficients in the actuator-disk model. They represent the effect of turbine blades that can actively pitch in time, changing the lift- and drag coefficients of the turbine blades. In a first infinite wind-farm case, we find that farm power is increases by approximately 16% over one hour of operation. This comes at the cost of a deceleration of the outer layer of the boundary layer. A detailed analysis of energy balances is presented, and a comparison is made between infinite and finite farm cases, for which boundary layer entrainment plays an import role. The authors acknowledge support from the European Research Council (FP7-Ideas, Grant No. 306471). Simulations were performed on the computing infrastructure of the VSC Flemish Supercomputer Center, funded by the Hercules Foundation and the Flemish Govern.

Automatic sleep staging using empirical mode decomposition, discrete wavelet transform, time-domain, and nonlinear dynamics features of heart rate variability signals.

PubMed

Ebrahimi, Farideh; Setarehdan, Seyed-Kamaledin; Ayala-Moyeda, Jose; Nazeran, Homer

2013-10-01

The conventional method for sleep staging is to analyze polysomnograms (PSGs) recorded in a sleep lab. The electroencephalogram (EEG) is one of the most important signals in PSGs but recording and analysis of this signal presents a number of technical challenges, especially at home. Instead, electrocardiograms (ECGs) are much easier to record and may offer an attractive alternative for home sleep monitoring. The heart rate variability (HRV) signal proves suitable for automatic sleep staging. Thirty PSGs from the Sleep Heart Health Study (SHHS) database were used. Three feature sets were extracted from 5- and 0.5-min HRV segments: time-domain features, nonlinear-dynamics features and time-frequency features. The latter was achieved by using empirical mode decomposition (EMD) and discrete wavelet transform (DWT) methods. Normalized energies in important frequency bands of HRV signals were computed using time-frequency methods. ANOVA and t-test were used for statistical evaluations. Automatic sleep staging was based on HRV signal features. The ANOVA followed by a post hoc Bonferroni was used for individual feature assessment. Most features were beneficial for sleep staging. A t-test was used to compare the means of extracted features in 5- and 0.5-min HRV segments. The results showed that the extracted features means were statistically similar for a small number of features. A separability measure showed that time-frequency features, especially EMD features, had larger separation than others. There was not a sizable difference in separability of linear features between 5- and 0.5-min HRV segments but separability of nonlinear features, especially EMD features, decreased in 0.5-min HRV segments. HRV signal features were classified by linear discriminant (LD) and quadratic discriminant (QD) methods. Classification results based on features from 5-min segments surpassed those obtained from 0.5-min segments. The best result was obtained from features using 5-min HRV segments classified by the LD classifier. A combination of linear/nonlinear features from HRV signals is effective in automatic sleep staging. Moreover, time-frequency features are more informative than others. In addition, a separability measure and classification results showed that HRV signal features, especially nonlinear features, extracted from 5-min segments are more discriminative than those from 0.5-min segments in automatic sleep staging. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Interaction of the branes in the presence of the background fields: The dynamical, nonintersecting, perpendicular, wrapped-fractional configuration

NASA Astrophysics Data System (ADS)

Maghsoodi, Elham; Kamani, Davoud

2017-05-01

We shall obtain the interaction of the Dp1- and Dp2-branes in the toroidal-orbifold space-time Tn × ℝ1,d-n-5 × ℂ2/ℤ 2. The configuration of the branes is nonintersecting, perpendicular, moving-rotating, wrapped-fractional with background fields. For this, we calculate the bosonic boundary state corresponding to a dynamical fractional-wrapped Dp-brane in the presence of the Kalb-Ramond field, a U1 gauge potential and an open string tachyon field. The long-range behavior of the interaction amplitude will be extracted.

Variational Flooding Study of a SN2 Reaction.

PubMed

Piccini, GiovanniMaria; McCarty, James J; Valsson, Omar; Parrinello, Michele

2017-02-02

We have studied the reaction dynamics of a prototypical organic reaction using a variationally optimized truncated bias to accelerate transitions between educt and product reactant states. The asymmetric S N 2 nucleophilic substitution reaction of fluoromethane and chloromethane CH 3 F + Cl - ⇌ CH 3 Cl + F - is considered, and many independent biased molecular dynamics simulations have been performed at 600, 900, and 1200 K, collecting several hundred transitions at each temperature. The transition times and relative rate constants have been obtained for both reaction directions. The activation energies extracted from an Arrhenius plot compare well with standard static calculations.

Combining Experiments and Simulations of Extraction Kinetics and Thermodynamics in Advanced Separation Processes for Used Nuclear Fuel

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

Nilsson, Mikael

This 3-year project was a collaboration between University of California Irvine (UC Irvine), Pacific Northwest National Laboratory (PNNL), Idaho National Laboratory (INL), Argonne National Laboratory (ANL) and with an international collaborator at ForschungZentrum Jülich (FZJ). The project was led from UC Irvine under the direction of Profs. Mikael Nilsson and Hung Nguyen. The leads at PNNL, INL, ANL and FZJ were Dr. Liem Dang, Dr. Peter Zalupski, Dr. Nathaniel Hoyt and Dr. Giuseppe Modolo, respectively. Involved in this project at UC Irvine were three full time PhD graduate students, Tro Babikian, Ted Yoo, and Quynh Vo, and one MS student,more » Alba Font Bosch. The overall objective of this project was to study how the kinetics and thermodynamics of metal ion extraction can be described by molecular dynamic (MD) simulations and how the simulations can be validated by experimental data. Furthermore, the project includes the applied separation by testing the extraction systems in a single stage annular centrifugal contactor and coupling the experimental data with computational fluid dynamic (CFD) simulations. Specific objectives of the proposed research were: Study and establish a rigorous connection between MD simulations based on polarizable force fields and extraction thermodynamic and kinetic data. Compare and validate CFD simulations of extraction processes for An/Ln separation using different sizes (and types) of annular centrifugal contactors. Provide a theoretical/simulation and experimental base for scale-up of batch-wise extraction to continuous contactors. We approached objective 1 and 2 in parallel. For objective 1 we started by studying a well established extraction system with a relatively simple extraction mechanism, namely tributyl phosphate. What we found was that well optimized simulations can inform experiments and new information on TBP behavior was presented in this project, as well be discussed below. The second objective proved a larger challenge and most of the efforts were devoted to experimental studies.« less

Optimization of dynamic headspace extraction system for measurement of halogenated volatile organic compounds in liquid or viscous samples

NASA Astrophysics Data System (ADS)

Taniai, G.; Oda, H.; Kurihara, M.; Hashimoto, S.

2010-12-01

Halogenated volatile organic compounds (HVOCs) produced in the marine environment are thought to play a key role in atmospheric reactions, particularly those involved in the global radiation budget and the depression of tropospheric and stratospheric ozone. To evaluate HVOCs concentrations in the various natural samples, we developed an automated dynamic headspace extraction method for the determination of 15 HVOCs, such as chloromethane, bromomethane, bromoethane, iodomethane, iodoethane, bromochloromethane, 1-iodopropane, 2-iodopropane, dibromomethane, bromodichloromethane, chloroiodomethane, chlorodibromomethane, bromoiodomethane, tribromomethane, and diiodomethane. Dynamic headspace system (GERSTEL DHS) was used to purge the gas phase above samples and to trap HVOCs on the adsorbent column from the purge gas. We measured the HVOCs concentrations in the adsorbent column with gas chromatograph (Agilent 6890N)- mass spectrometer (Agilent 5975C). In dynamic headspace system, an glass tube containing Tenax TA or Tenax GR was used as adsorbent column for the collection of 15 HVOCs. The parameters for purge and trap extraction, such as purge flow rate (ml/min), purge volume (ml), incubation time (min), and agitator speed (rpm), were optimized. The detection limits of HVOCs in water samples were 1270 pM (chloromethane), 103 pM (bromomethane), 42.1 pM (iodomethane), and 1.4 to 10.2 pM (other HVOCs). The repeatability (relative standard deviation) for 15 HVOCs were < 9 % except chloromethane (16.2 %) and bromomethane (11.0 %). On the basis of the measurements for various samples, we concluded that this analytical method is useful for the determination of wide range of HVOCs with boiling points between - 24°C (chloromethane) and 181°C (diiodomethane) for the liquid or viscous samples.

Synaptic dynamics and neuronal network connectivity are reflected in the distribution of times in Up states.

PubMed

Dao Duc, Khanh; Parutto, Pierre; Chen, Xiaowei; Epsztein, Jérôme; Konnerth, Arthur; Holcman, David

2015-01-01

The dynamics of neuronal networks connected by synaptic dynamics can sustain long periods of depolarization that can last for hundreds of milliseconds such as Up states recorded during sleep or anesthesia. Yet the underlying mechanism driving these periods remain unclear. We show here within a mean-field model that the residence time of the neuronal membrane potential in cortical Up states does not follow a Poissonian law, but presents several peaks. Furthermore, the present modeling approach allows extracting some information about the neuronal network connectivity from the time distribution histogram. Based on a synaptic-depression model, we find that these peaks, that can be observed in histograms of patch-clamp recordings are not artifacts of electrophysiological measurements, but rather are an inherent property of the network dynamics. Analysis of the equations reveals a stable focus located close to the unstable limit cycle, delimiting a region that defines the Up state. The model further shows that the peaks observed in the Up state time distribution are due to winding around the focus before escaping from the basin of attraction. Finally, we use in vivo recordings of intracellular membrane potential and we recover from the peak distribution, some information about the network connectivity. We conclude that it is possible to recover the network connectivity from the distribution of times that the neuronal membrane voltage spends in Up states.

Racial variations in interfacial behavior of lipids extracted from worn soft contact lenses.

PubMed

Svitova, Tatyana F; Lin, Meng C

2013-12-01

To explore interfacial behaviors and effects of temperature and dilatation on dynamic properties of multilayered human tear lipids extracted from silicone hydrogel (SiH) lenses worn by asymptomatic Asian and white subjects. Interfacial properties of lipids extracted from Focus N&D lenses worn by 14 subjects continuously for 1 month were studied. The lipids were deposited on an air bubble immersed in a model tear electrolyte (MTE) solution to form 100 ± 20-nm-thick films. Surface pressure was recorded during slow expansion/contraction cycles to evaluate compressibility and hysteresis of lipid films. Films were also subjected to fast step-strain dilatations at temperatures of 22 to 45°C for their viscoelastic property assessment. Isocycles for Asian and white lipids were similar at low surface pressures but had distinctly different compressibility and hysteresis at dynamic pressures exceeding 30 mN/m. Rheological parameters of reconstituted lipids were also dissimilar between Asian and white. The elastic modulus E∞ for white lipids was 1.5 times higher than that for Asian lipids, whereas relaxation time (t) was on average 1.3 times higher for Asian. No significant changes were observed in rheological properties of both Asian and white lipids when temperature increased from 22.0 to 36.5°C. However, for white lipids, E∞ reduced considerably at temperatures higher than 42.0°C, whereas t remained unchanged. For Asian lipids, both E∞ and t started to decline as temperature increased to 38°C and higher. Higher elastic modulus of white lipids and elasticity threshold at certain deformations indicate stronger structure and intermolecular interactions as compared with more viscous Asian lipids. The differences in interfacial behaviors between Asian and white lipids may be associated with the differences in their chemical compositions.

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

Wang, Shaobu; Lu, Shuai; Zhou, Ning

In interconnected power systems, dynamic model reduction can be applied on generators outside the area of interest to mitigate the computational cost with transient stability studies. This paper presents an approach of deriving the reduced dynamic model of the external area based on dynamic response measurements, which comprises of three steps, dynamic-feature extraction, attribution and reconstruction (DEAR). In the DEAR approach, a feature extraction technique, such as singular value decomposition (SVD), is applied to the measured generator dynamics after a disturbance. Characteristic generators are then identified in the feature attribution step for matching the extracted dynamic features with the highestmore » similarity, forming a suboptimal ‘basis’ of system dynamics. In the reconstruction step, generator state variables such as rotor angles and voltage magnitudes are approximated with a linear combination of the characteristic generators, resulting in a quasi-nonlinear reduced model of the original external system. Network model is un-changed in the DEAR method. Tests on several IEEE standard systems show that the proposed method gets better reduction ratio and response errors than the traditional coherency aggregation methods.« less

Dynamic fiber Bragg gratings based health monitoring system of composite aerospace structures

NASA Astrophysics Data System (ADS)

Panopoulou, A.; Loutas, T.; Roulias, D.; Fransen, S.; Kostopoulos, V.

2011-09-01

The main purpose of the current work is to develop a new system for structural health monitoring of composite aerospace structures based on real-time dynamic measurements, in order to identify the structural state condition. Long-gauge Fibre Bragg Grating (FBG) optical sensors were used for monitoring the dynamic response of the composite structure. The algorithm that was developed for structural damage detection utilizes the collected dynamic response data, analyzes them in various ways and through an artificial neural network identifies the damage state and its location. Damage was simulated by slightly varying locally the mass of the structure (by adding a known mass) at different zones of the structure. Lumped masses in different locations upon the structure alter the eigen-frequencies in a way similar to actual damage. The structural dynamic behaviour has been numerically simulated and experimentally verified by means of modal testing on two different composite aerospace structures. Advanced digital signal processing techniques, e.g. the wavelet transform (WT), were used for the analysis of the dynamic response for feature extraction. WT's capability of separating the different frequency components in the time domain without loosing frequency information makes it a versatile tool for demanding signal processing applications. The use of WT is also suggested by the no-stationary nature of dynamic response signals and the opportunity of evaluating the temporal evolution of their frequency contents. Feature extraction is the first step of the procedure. The extracted features are effective indices of damage size and location. The classification step comprises of a feed-forward back propagation network, whose output determines the simulated damage location. Finally, dedicated training and validation activities were carried out by means of numerical simulations and experimental procedures. Experimental validation was performed initially on a flat stiffened panel, representing a section of a typical aeronautical structure, manufactured and tested in the lab and, as a second step, on a scaled up space oriented structure, which is a composite honeycomb plate, used as a deployment base for antenna arrays. An integrated FBG sensor network, based on the advantage of multiplexing, was mounted on both structures and different excitation positions and boundary conditions were used. The analysis of operational dynamic responses was employed to identify both the damage and its position. The system that was designed and tested initially on the thin composite panel, was successfully validated on the larger honeycomb structure. Numerical simulation of both structures was used as a support tool at all the steps of the work providing among others the location of the optical sensors used. The proposed work will be the base for the whole system qualification and validation on an antenna reflector in future work.

Batch process fault detection and identification based on discriminant global preserving kernel slow feature analysis.

PubMed

Zhang, Hanyuan; Tian, Xuemin; Deng, Xiaogang; Cao, Yuping

2018-05-16

As an attractive nonlinear dynamic data analysis tool, global preserving kernel slow feature analysis (GKSFA) has achieved great success in extracting the high nonlinearity and inherently time-varying dynamics of batch process. However, GKSFA is an unsupervised feature extraction method and lacks the ability to utilize batch process class label information, which may not offer the most effective means for dealing with batch process monitoring. To overcome this problem, we propose a novel batch process monitoring method based on the modified GKSFA, referred to as discriminant global preserving kernel slow feature analysis (DGKSFA), by closely integrating discriminant analysis and GKSFA. The proposed DGKSFA method can extract discriminant feature of batch process as well as preserve global and local geometrical structure information of observed data. For the purpose of fault detection, a monitoring statistic is constructed based on the distance between the optimal kernel feature vectors of test data and normal data. To tackle the challenging issue of nonlinear fault variable identification, a new nonlinear contribution plot method is also developed to help identifying the fault variable after a fault is detected, which is derived from the idea of variable pseudo-sample trajectory projection in DGKSFA nonlinear biplot. Simulation results conducted on a numerical nonlinear dynamic system and the benchmark fed-batch penicillin fermentation process demonstrate that the proposed process monitoring and fault diagnosis approach can effectively detect fault and distinguish fault variables from normal variables. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Controlling the influence of elastic eigenmodes on nanomagnet dynamics through pattern geometry

NASA Astrophysics Data System (ADS)

Berk, C.; Yahagi, Y.; Dhuey, S.; Cabrini, S.; Schmidt, H.

2017-03-01

The effect of the nanoscale array geometry on the interaction between optically generated surface acoustic waves (SAWs) and nanomagnet dynamics is investigated using Time-Resolved Magneto-Optical Kerr Effect Microscopy (TR-MOKE). It is demonstrated that altering the nanomagnet geometry from a periodic to a randomized aperiodic pattern effectively removes the magneto-elastic effect of SAWs on the magnetization dynamics. The efficiency of this method depends on the extent of any residual spatial correlations and is quantified by spatial Fourier analysis of the two structures. Randomization allows observation and extraction of intrinsic magnetic parameters such as spin wave frequencies and damping to be resolvable using all-optical methods, enabling the conclusion that the fabrication process does not affect the damping.

The number comb for a soil physical properties dynamic measurement

NASA Astrophysics Data System (ADS)

Olechko, K.; Patiño, P.; Tarquis, A. M.

2012-04-01

We propose the prime numbers distribution extracted from the soil digital multiscale images and some physical properties time series as the precise indicator of the spatial and temporal dynamics under soil management changes. With this new indicator the soil dynamics can be studied as a critical phenomenon where each phase transition is estimated and modeled by the graph partitioning induced phase transition. The critical point of prime numbers distribution was correlated with the beginning of Andosols, Vertisols and saline soils physical degradation under the unsustainable soil management in Michoacan, Guanajuato and Veracruz States of Mexico. The data banks corresponding to the long time periods (between 10 and 28 years) were statistically compared by RISK 5.0 software and our own algorithms. Our approach makes us able to distill free-form natural laws of soils physical properties dynamics directly from the experimental data. The Richter (1987) and Schmidt and Lipson (2009) original approaches were very useful to design the algorithms to identify Hamiltonians, Lagrangians and other laws of geometric and momentum conservation especially for erosion case.

Multi-channel dynamics in high harmonic generation of aligned CO2: ab initio analysis with time-dependent B-spline algebraic diagrammatic construction.

PubMed

Ruberti, M; Decleva, P; Averbukh, V

2018-03-28

Here we present a fully ab initio study of the high-order harmonic generation (HHG) spectrum of aligned CO 2 molecules. The calculations have been performed by using the molecular time-dependent (TD) B-spline algebraic diagrammatic construction (ADC) method. We quantitatively study how the sub-cycle laser-driven multi-channel dynamics, as reflected in the position of the dynamical minimum in the HHG spectrum, is affected by the full inclusion of both correlation-driven and laser-driven dipole interchannel couplings. We calculate channel-resolved spectral intensities as well as the phase differences between contributions of the different ionization-recombination channels to the total HHG spectrum. Our results show that electron correlation effectively controls the relative contributions of the different channels to the total HHG spectrum, leading to the opening of the new ones (1 2 Π u , 1 2 Σ), previously disregarded for the aligned molecular setup. We conclude that inclusion of many-electron effects into the theoretical interpretation of molecular HHG spectra is essential in order to correctly extract ultrafast electron dynamics using HHG spectroscopy.

Potential-based dynamical reweighting for Markov state models of protein dynamics.

PubMed

Weber, Jeffrey K; Pande, Vijay S

2015-06-09

As simulators attempt to replicate the dynamics of large cellular components in silico, problems related to sampling slow, glassy degrees of freedom in molecular systems will be amplified manyfold. It is tempting to augment simulation techniques with external biases to overcome such barriers with ease; biased simulations, however, offer little utility unless equilibrium properties of interest (both kinetic and thermodynamic) can be recovered from the data generated. In this Article, we present a general scheme that harnesses the power of Markov state models (MSMs) to extract equilibrium kinetic properties from molecular dynamics trajectories collected on biased potential energy surfaces. We first validate our reweighting protocol on a simple two-well potential, and we proceed to test our method on potential-biased simulations of the Trp-cage miniprotein. In both cases, we find that equilibrium populations, time scales, and dynamical processes are reliably reproduced as compared to gold standard, unbiased data sets. We go on to discuss the limitations of our dynamical reweighting approach, and we suggest auspicious target systems for further application.

Phenomenological analysis of medical time series with regular and stochastic components

NASA Astrophysics Data System (ADS)

Timashev, Serge F.; Polyakov, Yuriy S.

2007-06-01

Flicker-Noise Spectroscopy (FNS), a general approach to the extraction and parameterization of resonant and stochastic components contained in medical time series, is presented. The basic idea of FNS is to treat the correlation links present in sequences of different irregularities, such as spikes, "jumps", and discontinuities in derivatives of different orders, on all levels of the spatiotemporal hierarchy of the system under study as main information carriers. The tools to extract and analyze the information are power spectra and difference moments (structural functions), which complement the information of each other. The structural function stochastic component is formed exclusively by "jumps" of the dynamic variable while the power spectrum stochastic component is formed by both spikes and "jumps" on every level of the hierarchy. The information "passport" characteristics that are determined by fitting the derived expressions to the experimental variations for the stochastic components of power spectra and structural functions are interpreted as the correlation times and parameters that describe the rate of "memory loss" on these correlation time intervals for different irregularities. The number of the extracted parameters is determined by the requirements of the problem under study. Application of this approach to the analysis of tremor velocity signals for a Parkinsonian patient is discussed.

Density-based clustering: A 'landscape view' of multi-channel neural data for inference and dynamic complexity analysis.

PubMed

Baglietto, Gabriel; Gigante, Guido; Del Giudice, Paolo

2017-01-01

Two, partially interwoven, hot topics in the analysis and statistical modeling of neural data, are the development of efficient and informative representations of the time series derived from multiple neural recordings, and the extraction of information about the connectivity structure of the underlying neural network from the recorded neural activities. In the present paper we show that state-space clustering can provide an easy and effective option for reducing the dimensionality of multiple neural time series, that it can improve inference of synaptic couplings from neural activities, and that it can also allow the construction of a compact representation of the multi-dimensional dynamics, that easily lends itself to complexity measures. We apply a variant of the 'mean-shift' algorithm to perform state-space clustering, and validate it on an Hopfield network in the glassy phase, in which metastable states are largely uncorrelated from memories embedded in the synaptic matrix. In this context, we show that the neural states identified as clusters' centroids offer a parsimonious parametrization of the synaptic matrix, which allows a significant improvement in inferring the synaptic couplings from the neural activities. Moving to the more realistic case of a multi-modular spiking network, with spike-frequency adaptation inducing history-dependent effects, we propose a procedure inspired by Boltzmann learning, but extending its domain of application, to learn inter-module synaptic couplings so that the spiking network reproduces a prescribed pattern of spatial correlations; we then illustrate, in the spiking network, how clustering is effective in extracting relevant features of the network's state-space landscape. Finally, we show that the knowledge of the cluster structure allows casting the multi-dimensional neural dynamics in the form of a symbolic dynamics of transitions between clusters; as an illustration of the potential of such reduction, we define and analyze a measure of complexity of the neural time series.

Non-linear controls influence functions in an aircraft dynamics simulator

NASA Technical Reports Server (NTRS)

Guerreiro, Nelson M.; Hubbard, James E., Jr.; Motter, Mark A.

2006-01-01

In the development and testing of novel structural and controls concepts, such as morphing aircraft wings, appropriate models are needed for proper system characterization. In most instances, available system models do not provide the required additional degrees of freedom for morphing structures but may be modified to some extent to achieve a compatible system. The objective of this study is to apply wind tunnel data collected for an Unmanned Air Vehicle (UAV), that implements trailing edge morphing, to create a non-linear dynamics simulator, using well defined rigid body equations of motion, where the aircraft stability derivatives change with control deflection. An analysis of this wind tunnel data, using data extraction algorithms, was performed to determine the reference aerodynamic force and moment coefficients for the aircraft. Further, non-linear influence functions were obtained for each of the aircraft s control surfaces, including the sixteen trailing edge flap segments. These non-linear controls influence functions are applied to the aircraft dynamics to produce deflection-dependent aircraft stability derivatives in a non-linear dynamics simulator. Time domain analysis of the aircraft motion, trajectory, and state histories can be performed using these nonlinear dynamics and may be visualized using a 3-dimensional aircraft model. Linear system models can be extracted to facilitate frequency domain analysis of the system and for control law development. The results of this study are useful in similar projects where trailing edge morphing is employed and will be instrumental in the University of Maryland s continuing study of active wing load control.

Spacecraft angular velocity estimation algorithm for star tracker based on optical flow techniques

NASA Astrophysics Data System (ADS)

Tang, Yujie; Li, Jian; Wang, Gangyi

2018-02-01

An integrated navigation system often uses the traditional gyro and star tracker for high precision navigation with the shortcomings of large volume, heavy weight and high-cost. With the development of autonomous navigation for deep space and small spacecraft, star tracker has been gradually used for attitude calculation and angular velocity measurement directly. At the same time, with the dynamic imaging requirements of remote sensing satellites and other imaging satellites, how to measure the angular velocity in the dynamic situation to improve the accuracy of the star tracker is the hotspot of future research. We propose the approach to measure angular rate with a nongyro and improve the dynamic performance of the star tracker. First, the star extraction algorithm based on morphology is used to extract the star region, and the stars in the two images are matched according to the method of angular distance voting. The calculation of the displacement of the star image is measured by the improved optical flow method. Finally, the triaxial angular velocity of the star tracker is calculated by the star vector using the least squares method. The method has the advantages of fast matching speed, strong antinoise ability, and good dynamic performance. The triaxial angular velocity of star tracker can be obtained accurately with these methods. So, the star tracker can achieve better tracking performance and dynamic attitude positioning accuracy to lay a good foundation for the wide application of various satellites and complex space missions.

Automatic extraction of forward stroke volume using dynamic PET/CT: a dual-tracer and dual-scanner validation in patients with heart valve disease.

PubMed

Harms, Hendrik Johannes; Tolbod, Lars Poulsen; Hansson, Nils Henrik Stubkjær; Kero, Tanja; Orndahl, Lovisa Holm; Kim, Won Yong; Bjerner, Tomas; Bouchelouche, Kirsten; Wiggers, Henrik; Frøkiær, Jørgen; Sörensen, Jens

2015-12-01

The aim of this study was to develop and validate an automated method for extracting forward stroke volume (FSV) using indicator dilution theory directly from dynamic positron emission tomography (PET) studies for two different tracers and scanners. 35 subjects underwent a dynamic (11)C-acetate PET scan on a Siemens Biograph TruePoint-64 PET/CT (scanner I). In addition, 10 subjects underwent both dynamic (15)O-water PET and (11)C-acetate PET scans on a GE Discovery-ST PET/CT (scanner II). The left ventricular (LV)-aortic time-activity curve (TAC) was extracted automatically from PET data using cluster analysis. The first-pass peak was isolated by automatic extrapolation of the downslope of the TAC. FSV was calculated as the injected dose divided by the product of heart rate and the area under the curve of the first-pass peak. Gold standard FSV was measured using phase-contrast cardiovascular magnetic resonance (CMR). FSVPET correlated highly with FSVCMR (r = 0.87, slope = 0.90 for scanner I, r = 0.87, slope = 1.65, and r = 0.85, slope = 1.69 for scanner II for (15)O-water and (11)C-acetate, respectively) although a systematic bias was observed for both scanners (p < 0.001 for all). FSV based on (11)C-acetate and (15)O-water correlated highly (r = 0.99, slope = 1.03) with no significant difference between FSV estimates (p = 0.14). FSV can be obtained automatically using dynamic PET/CT and cluster analysis. Results are almost identical for (11)C-acetate and (15)O-water. A scanner-dependent bias was observed, and a scanner calibration factor is required for multi-scanner studies. Generalization of the method to other tracers and scanners requires further validation.

Ultrasound-assisted extraction and preliminary purification of proanthocyanidins and chlorogenic acid from almond (Prunus dulcis) skin.

PubMed

Ma, Xue; Zhou, Xin-Yu; Qiang, Qian-Qian; Zhang, Zhi-Qi

2014-07-01

An aqueous solution of polyethylene glycol (PEG) as a green solvent was employed for the first time to develop the ultrasound-assisted extraction of proanthocyanidins (PA) and chlorogenic acid (CA) from almond skin. The optimized extraction parameters were determined based on response surface methodology, and corresponded to an ultrasound power of 120 W, a liquid-to-solid ratio of 20:1 (mL/g), and a PEG concentration of 50% (v/v). Under these optimized conditions, the extraction yields of PAs and CA from almond skin were 32.68 ± 0.22 and 16.01 ± 0.19 mg/g, respectively. Compared with organic solvent extraction, PEG solution extraction produced higher yields. Different macroporous resins were compared for their performance in purifying PAs and CA from almond skin extract. Static adsorption/desorption experimental results demonstrated that AB-8 resin exhibits excellent purification performance at pH 4. Under the optimized dynamic adsorption/desorption conditions on the AB-8 column, the total recovery of purification for PAs and CA was 80.67%. The total content of PAs and CA in the preliminarily purified extract was 89.17% (with respective contents of 60.90 and 28.27%). © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A comparison of two types of neural network for weld quality prediction in small scale resistance spot welding

NASA Astrophysics Data System (ADS)

Wan, Xiaodong; Wang, Yuanxun; Zhao, Dawei; Huang, YongAn

2017-09-01

Our study aims at developing an effective quality monitoring system in small scale resistance spot welding of titanium alloy. The measured electrical signals were interpreted in combination with the nugget development. Features were extracted from the dynamic resistance and electrode voltage curve. A higher welding current generally indicated a lower overall dynamic resistance level. A larger electrode voltage peak and higher change rate of electrode voltage could be detected under a smaller electrode force or higher welding current condition. Variation of the extracted features and weld quality was found more sensitive to the change of welding current than electrode force. Different neural network model were proposed for weld quality prediction. The back propagation neural network was more proper in failure load estimation. The probabilistic neural network model was more appropriate to be applied in quality level classification. A real-time and on-line weld quality monitoring system may be developed by taking advantages of both methods.

Sensitive method for the quantitation of droloxifene in plasma and serum by high-performance liquid chromatography employing fluorimetric detection.

PubMed

Tess, D A; Cole, R O; Toler, S M

1995-12-15

A simple and highly sensitive reversed-phase fluorimetric HPLC method for the quantitation of droloxifene from rat, monkey, and human plasma as well as human serum is described. This assay employs solid-phase extraction and has a dynamic range of 25 to 10,000 pg/ml. Sample extraction (efficiencies > 86%) was accomplished using a benzenesulfonic acid (SCX) column with water and methanol rinses. Droloxifene and internal standard were eluted with 1 ml of 3.5% (v/v) ammonium hydroxide (30%) in methanol. Samples were quantitated using post-column UV-photochemical cyclization coupled with fluorimetric detection with excitation and emission wavelengths of 260 nm and 375 nm, respectively. Relative ease of sample extraction and short run times allow for the analysis of approximately 100 samples per day.

Time-dependent structural transformation analysis to high-level Petri net model with active state transition diagram.

PubMed

Li, Chen; Nagasaki, Masao; Saito, Ayumu; Miyano, Satoru

2010-04-01

With an accumulation of in silico data obtained by simulating large-scale biological networks, a new interest of research is emerging for elucidating how living organism functions over time in cells. Investigating the dynamic features of current computational models promises a deeper understanding of complex cellular processes. This leads us to develop a method that utilizes structural properties of the model over all simulation time steps. Further, user-friendly overviews of dynamic behaviors can be considered to provide a great help in understanding the variations of system mechanisms. We propose a novel method for constructing and analyzing a so-called active state transition diagram (ASTD) by using time-course simulation data of a high-level Petri net. Our method includes two new algorithms. The first algorithm extracts a series of subnets (called temporal subnets) reflecting biological components contributing to the dynamics, while retaining positive mathematical qualities. The second one creates an ASTD composed of unique temporal subnets. ASTD provides users with concise information allowing them to grasp and trace how a key regulatory subnet and/or a network changes with time. The applicability of our method is demonstrated by the analysis of the underlying model for circadian rhythms in Drosophila. Building ASTD is a useful means to convert a hybrid model dealing with discrete, continuous and more complicated events to finite time-dependent states. Based on ASTD, various analytical approaches can be applied to obtain new insights into not only systematic mechanisms but also dynamics.

Diagnosing and Reconstructing Real-World Hydroclimatic Dynamics from Time Sequenced Data: The Case of Saltwater Intrusion into Coastal Wetlands in Everglades National Park

NASA Astrophysics Data System (ADS)

Huffaker, R.; Munoz-Carpena, R.

2016-12-01

There are increasing calls to audit decision-support models used for environmental policy to ensure that they correspond with the reality facing policy makers. Modelers can establish correspondence by providing empirical evidence of real-world dynamic behavior that their models skillfully simulate. We present a pre-modeling diagnostic framework—based on nonlinear dynamic analysis—for detecting and reconstructing real-world environmental dynamics from observed time-sequenced data. Phenomenological (data-driven) modeling—based on machine learning regression techniques—extracts a set of ordinary differential equations governing empirically-diagnosed system dynamics from a single time series, or from multiple time series on causally-interacting variables. We apply the framework to investigate saltwater intrusion into coastal wetlands in Everglades National Park, Florida, USA. We test the following hypotheses posed in the literature linking regional hydrologic variables with global climatic teleconnections: (1) Sea level in Florida Bay drives well level and well salinity in the coastal Everglades; (2) Atlantic Multidecadal Oscillation (AMO) drives sea level, well level and well salinity; and (3) AMO and (El Niño Southern Oscillation) ENSO bi-causally interact. The thinking is that salt water intrusion links ocean-surface salinity with salinity of inland water sources, and sea level with inland water; that AMO and ENSO share a teleconnective relationship (perhaps through the atmosphere); and that AMO and ENSO both influence inland precipitation and thus well levels. Our results support these hypotheses, and we successfully construct a parsimonious phenomenological model that reproduces diagnosed nonlinear dynamics and system interactions. We propose that reconstructed data dynamics be used, along with other expert information, as a rigorous benchmark to guide specification and testing of hydrologic decision support models corresponding with real-world behavior.

The combined use of dynamic factor analysis and wavelet analysis to evaluate latent factors controlling complex groundwater level fluctuations in a riverside alluvial aquifer

NASA Astrophysics Data System (ADS)

Oh, Yun-Yeong; Yun, Seong-Taek; Yu, Soonyoung; Hamm, Se-Yeong

2017-12-01

To identify and quantitatively evaluate complex latent factors controlling groundwater level (GWL) fluctuations in a riverside alluvial aquifer influenced by barrage construction, we developed the combined use of dynamic factor analysis (DFA) and wavelet analysis (WA). Time series data of GWL, river water level and precipitation were collected for 3 years (July 2012 to June 2015) from an alluvial aquifer underneath an agricultural area of the Nakdong river basin, South Korea. Based on the wavelet coefficients of the final approximation, the GWL data was clustered into three groups (WCG1 to WCG3). Two dynamic factors (DFs) were then extracted using DFA for each group; thus, six major factors were extracted. Next, the time-frequency variability of the extracted DFs was examined using multiresolution cross-correlation analysis (MRCCA) with the following steps: 1) major driving forces and their scales in GWL fluctuations were identified by comparing maximum correlation coefficients (rmax) between DFs and the GWL time series and 2) the results were supplemented using the wavelet transformed coherence (WTC) analysis between DFs and the hydrological time series. Finally, relative contributions of six major DFs to the GWL fluctuations could be quantitatively assessed by calculating the effective dynamic efficiency (Def). The characteristics and relevant process of the identified six DFs are: 1) WCG1DF4,1 as an indicative of seasonal agricultural pumping (scales = 64-128 days; rmax = 0.68-0.89; Def ≤ 23.1%); 2) WCG1DF4,4 representing the cycle of regional groundwater recharge (scales = 64-128 days; rmax = 0.98-1.00; Def ≤ 11.1%); 3) WCG2DF4,1 indicating the complex interaction between the episodes of precipitation and direct runoff (scales = 2-8 days; rmax = 0.82-0.91; Def ≤ 35.3%) and seasonal GW-RW interaction (scales = 64-128 days; rmax = 0.76-0.91; Def ≤ 14.2%); 4) WCG2DF4,4 reflecting the complex effects of seasonal pervasive pumping and the local recharge cycle (scales = 64-128 days; rmax = 0.86-0.94; Def ≤ 16.4%); 5) WCG3DF4,2 as the result of temporal pumping (scales = 2-8 days; rmax = 0.98-0.99; Def ≤ 7.7%); and 6) WCG3DF4,4 indicating the local recharge cycle (scales = 64-128 days; rmax = 0.76-0.91; Def ≤ 34.2 %). This study shows that major driving forces controlling GWL time series data in a complex hydrological setting can be identified and quantitatively evaluated by the combined use of DFA and WA and applying MRCCA and WTC.

Application of alkyl polyglycoside surfactant in ultrasonic-assisted extraction followed by macroporous resin enrichment for the separation of vitexin-2″-O-rhamnoside and vitexin from Crataegus pinnatifida leaves.

PubMed

Han, Feng; Guo, Yupin; Gu, Huiyan; Li, Fenglan; Hu, Baozhong; Yang, Lei

2016-02-15

An alkyl polyglycoside (APG) surfactant was used in ultrasonic-assisted extraction to effectively extract vitexin-2″-O-rhamnoside (VOR) and vitexin (VIT) from Crataegus pinnatifida leaves. APG0810 was selected as the surfactant. The extraction process was optimized for ultrasonic power, the APG concentration, ultrasonic time, soaking time, and liquid-solid ratio. The proposed approach showed good recovery (99.80-102.50% for VOR and 98.83-103.19% for VIT) and reproducibility (relative standard deviation, n=5; 3.7% for VOR and 4.2% for VIT) for both components. The proposed sample preparation method is both simple and effective. The use of APG for extraction of key herbal ingredients shows great potential. Ten widely used commercial macroporous resins were evaluated in a screening study to identify a suitable resin for the separation and purification of VOR and VIT. After comparing static and dynamic adsorption and desorption processes, HPD100B was selected as the most suitable resin. After column adsorption and desorption on this resin, the target compounds VOR and VIT can be effectively separated from the APG0810 extraction solution. Recoveries of VOR and VIT were 89.27%±0.42% and 85.29%±0.36%, respectively. The purity of VOR increased from 35.0% to 58.3% and the purity of VIT increased from 12.5% to 19.9%. Copyright © 2016 Elsevier B.V. All rights reserved.

Effect of cosmetic matrices on the release and odour profiles of the supercritical CO2 extract of Origanum majorana L.

PubMed

Costa, P; Velasco, C V; Loureiro, J M; Rodrigues, A E

2016-08-01

In this study, the effect of different cosmetic matrices on the release profile and odour intensity of the fragrance O. majorana was investigated for the first time. The fragrance compounds of O. majorana were extracted by supercritical fluid extraction using carbon dioxide (SFE-CO2 ) at 40°C and two operating pressures (8.5 and 10 MPa), and their chemical profiles were assessed by gas chromatography with flame ionization detector coupled with mass spectrometry (GC-FID/MS). Lastly, the fragrance compounds were incorporated into three cosmetic matrices (glycerine, dipropylene glycol and skin lotion) to assess their release and odour profiles over time using dynamic headspace (DHS)/GC-FID/MS and Odour Value concept, respectively. The SFE-CO2 enabled recovering extracts with the pleasant scent of the living plant, and the increment of pressure induced an increase on the extraction yield. GC-FID/MS analyses revealed that oxygen-containing monoterpenes was the principal group of components identified in both SFE-CO2 extracts. The fragrance compounds were more retained in dipropylene glycol, and the major deviations from the original odour intensity (control) were observed in the presence of dipropylene glycol and skin lotion. The hydrophilic character of the cosmetic matrices strongly influenced the release of the fragrance compounds, thus affecting the odour profile of the studied mixtures. © 2015 Society of Cosmetic Scientists and the Société Française de Cosmétologie.

Optimized ultrasonic assisted extraction-dispersive liquid-liquid microextraction coupled with gas chromatography for determination of essential oil of Oliveria decumbens Vent.

PubMed

Sereshti, Hassan; Izadmanesh, Yahya; Samadi, Soheila

2011-07-22

Ultrasonic assisted extraction-dispersive liquid-liquid microextraction (UAE-DLLME) coupled with gas chromatography (GC) was applied for extraction and determination of essential oil constituents of the plant Oliveria decumbens Vent. Scanning electron microscopy (SEM) was used to see the effect of ultrasonic radiation on the extraction efficiency. By comparison with hydrodistillation, UAE-DLLME is fast, low cost, simple, efficient and consuming small amount of plant materials (∼1.0 g). The effects of various parameters such as temperature, ultrasonication time, volume of disperser and extraction solvents were investigated by a full factorial design to identify significant variables and their interactions. The results demonstrated that temperature and ultrasonication time had no considerable effect on the results. In the next step, a central composite design (CCD) was performed to obtain the optimum levels of significant parameters. The obtained optimal conditions were: 0.45 mL for disperser solvent (acetonitrile) and 94.84 μL for extraction solvent (chlorobenzene). The limits of detection (LODs), linear dynamic range and determination coefficients (R(2)) were 0.2-29 ng mL(-1), 1-2100 ng mL(-1) and 0.995-0.998, respectively. The main components of the essential oil were: thymol (47.06%), carvacrol (23.31%), gamma-terpinene (18.94%), p-cymene (8.71%), limonene (0.76%) and myristicin (0.63%). Copyright © 2011 Elsevier B.V. All rights reserved.

Sexual affordances, perceptual-motor invariance extraction and intentional nonlinear dynamics: sexually deviant and non-deviant patterns in male subjects.

PubMed

Renaud, Patrice; Goyette, Mathieu; Chartier, Sylvain; Zhornitski, Simon; Trottier, Dominique; Rouleau, Joanne-L; Proulx, Jean; Fedoroff, Paul; Bradford, John-P; Dassylva, Benoit; Bouchard, Stephane

2010-10-01

Sexual arousal and gaze behavior dynamics are used to characterize deviant sexual interests in male subjects. Pedophile patients and non-deviant subjects are immersed with virtual characters depicting relevant sexual features. Gaze behavior dynamics as indexed from correlation dimensions (D2) appears to be fractal in nature and significantly different from colored noise (surrogate data tests and recurrence plot analyses were performed). This perceptual-motor fractal dynamics parallels sexual arousal and differs from pedophiles to non-deviant subjects when critical sexual information is processed. Results are interpreted in terms of sexual affordance, perceptual invariance extraction and intentional nonlinear dynamics.

A synergic simulation-optimization approach for analyzing biomolecular dynamics in living organisms.

PubMed

Sadegh Zadeh, Kouroush

2011-01-01

A synergic duo simulation-optimization approach was developed and implemented to study protein-substrate dynamics and binding kinetics in living organisms. The forward problem is a system of several coupled nonlinear partial differential equations which, with a given set of kinetics and diffusion parameters, can provide not only the commonly used bleached area-averaged time series in fluorescence microscopy experiments but more informative full biomolecular/drug space-time series and can be successfully used to study dynamics of both Dirac and Gaussian fluorescence-labeled biomacromolecules in vivo. The incomplete Cholesky preconditioner was coupled with the finite difference discretization scheme and an adaptive time-stepping strategy to solve the forward problem. The proposed approach was validated with analytical as well as reference solutions and used to simulate dynamics of GFP-tagged glucocorticoid receptor (GFP-GR) in mouse cancer cell during a fluorescence recovery after photobleaching experiment. Model analysis indicates that the commonly practiced bleach spot-averaged time series is not an efficient approach to extract physiological information from the fluorescence microscopy protocols. It was recommended that experimental biophysicists should use full space-time series, resulting from experimental protocols, to study dynamics of biomacromolecules and drugs in living organisms. It was also concluded that in parameterization of biological mass transfer processes, setting the norm of the gradient of the penalty function at the solution to zero is not an efficient stopping rule to end the inverse algorithm. Theoreticians should use multi-criteria stopping rules to quantify model parameters by optimization. Copyright © 2010 Elsevier Ltd. All rights reserved.

Robust, non-invasive methods for metering groundwater well extraction in remote environments

NASA Astrophysics Data System (ADS)

Bulovic, Nevenka; Keir, Greg; McIntyre, Neil

2017-04-01

Quantifying the rate of extraction from groundwater wells can be essential for regional scale groundwater management and impact assessment. This is especially the case in regions heavily dependent on groundwater such as the semi-arid Surat and Bowen Basins in Queensland, Australia. Of the 30 000+ groundwater wells in this area, the majority of which are used for stock watering and domestic purposes, almost none have flow metering devices installed. As part of a research project to estimate regional groundwater extraction, we have undertaken a small scale flow metering program on a selected set of wells. Conventional in-line flow meters were unsuitable for our project, as both non-invasiveness and adaptability / suitability to a variety of discharge pipe characteristics was critical. We describe the use of two metering technologies not widely used in groundwater applications, non-invasive, clamp-on ultrasonic transit time flow meters and tipping bucket flow meters, as semi-permanent installations on discharge pipes of various artesian and sub-artesian groundwater wells. We present examples of detailed extraction rate time-series, which are of particular value in developing predictive models of water well extraction in data limited areas where water use dynamics and drivers are poorly understood. We conclude by discussing future project trajectories, which include expansion of the monitoring network through development of novel metering techniques and telemetry across large areas of poor connectivity.

An introduction to chaotic and random time series analysis

NASA Technical Reports Server (NTRS)

Scargle, Jeffrey D.

1989-01-01

The origin of chaotic behavior and the relation of chaos to randomness are explained. Two mathematical results are described: (1) a representation theorem guarantees the existence of a specific time-domain model for chaos and addresses the relation between chaotic, random, and strictly deterministic processes; (2) a theorem assures that information on the behavior of a physical system in its complete state space can be extracted from time-series data on a single observable. Focus is placed on an important connection between the dynamical state space and an observable time series. These two results lead to a practical deconvolution technique combining standard random process modeling methods with new embedded techniques.

Bioaerosol DNA Extraction Technique from Air Filters Collected from Marine and Freshwater Locations

NASA Astrophysics Data System (ADS)

Beckwith, M.; Crandall, S. G.; Barnes, A.; Paytan, A.

2015-12-01

Bioaerosols are composed of microorganisms suspended in air. Among these organisms include bacteria, fungi, virus, and protists. Microbes introduced into the atmosphere can drift, primarily by wind, into natural environments different from their point of origin. Although bioaerosols can impact atmospheric dynamics as well as the ecology and biogeochemistry of terrestrial systems, very little is known about the composition of bioaerosols collected from marine and freshwater environments. The first step to determine composition of airborne microbes is to successfully extract environmental DNA from air filters. We asked 1) can DNA be extracted from quartz (SiO2) air filters? and 2) how can we optimize the DNA yield for downstream metagenomic sequencing? Aerosol filters were collected and archived on a weekly basis from aquatic sites (USA, Bermuda, Israel) over the course of 10 years. We successfully extracted DNA from a subsample of ~ 20 filters. We modified a DNA extraction protocol (Qiagen) by adding a beadbeating step to mechanically shear cell walls in order to optimize our DNA product. We quantified our DNA yield using a spectrophotometer (Nanodrop 1000). Results indicate that DNA can indeed be extracted from quartz filters. The additional beadbeating step helped increase our yield - up to twice as much DNA product was obtained compared to when this step was omitted. Moreover, bioaerosol DNA content does vary across time. For instance, the DNA extracted from filters from Lake Tahoe, USA collected near the end of June decreased from 9.9 ng/μL in 2007 to 3.8 ng/μL in 2008. Further next-generation sequencing analysis of our extracted DNA will be performed to determine the composition of these microbes. We will also model the meteorological and chemical factors that are good predictors for microbial composition for our samples over time and space.

Trend Motif: A Graph Mining Approach for Analysis of Dynamic Complex Networks

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

Jin, R; McCallen, S; Almaas, E

2007-05-28

Complex networks have been used successfully in scientific disciplines ranging from sociology to microbiology to describe systems of interacting units. Until recently, studies of complex networks have mainly focused on their network topology. However, in many real world applications, the edges and vertices have associated attributes that are frequently represented as vertex or edge weights. Furthermore, these weights are often not static, instead changing with time and forming a time series. Hence, to fully understand the dynamics of the complex network, we have to consider both network topology and related time series data. In this work, we propose a motifmore » mining approach to identify trend motifs for such purposes. Simply stated, a trend motif describes a recurring subgraph where each of its vertices or edges displays similar dynamics over a userdefined period. Given this, each trend motif occurrence can help reveal significant events in a complex system; frequent trend motifs may aid in uncovering dynamic rules of change for the system, and the distribution of trend motifs may characterize the global dynamics of the system. Here, we have developed efficient mining algorithms to extract trend motifs. Our experimental validation using three disparate empirical datasets, ranging from the stock market, world trade, to a protein interaction network, has demonstrated the efficiency and effectiveness of our approach.« less

Enhancing the sensitivity of fluorescence correlation spectroscopy by using time-correlated single photon counting.

PubMed

Lamb, D C; Müller, B K; Bräuchle, C

2005-10-01

Fluorescence correlation spectroscopy (FCS) and fluorescence cross-correlation spectroscopy (FCCS) are methods that extract information about a sample from the influence of thermodynamic equilibrium fluctuations on the fluorescence intensity. This method allows dynamic information to be obtained from steady state equilibrium measurements and its popularity has dramatically increased in the last 10 years due to the development of high sensitivity detectors and its combination with confocal microscopy. Using time-correlated single-photon counting (TCSPC) detection and pulsed excitation, information over the duration of the excited state can be extracted and incorporated in the analysis. In this short review, we discuss new methodologies that have recently emerged which incorporated fluorescence lifetime information or TCSPC data in the FCS and FCCS analysis. Time-gated FCS discriminates between which photons are to be incorporated in the analysis dependent upon their arrival time after excitation. This allows for accurate FCS measurements in the presence of fluorescent background, determination of sample homogeneity, and the ability to distinguish between static and dynamic heterogeneities. A similar method, time-resolved FCS can be used to resolve the individual correlation functions from multiple fluorophores through the different fluorescence lifetimes. Pulsed interleaved excitation (PIE) encodes the excitation source into the TCSPC data. PIE can be used to perform dual-channel FCCS with a single detector and allows elimination of spectral cross-talk with dual-channel detection. For samples that undergo fluorescence resonance energy transfer (FRET), quantitative FCCS measurements can be performed in spite of the FRET and the static FRET efficiency can be determined.

Experimental resource pulses influence social-network dynamics and the potential for information flow in tool-using crows

PubMed Central

St Clair, James J. H.; Burns, Zackory T.; Bettaney, Elaine M.; Morrissey, Michael B.; Otis, Brian; Ryder, Thomas B.; Fleischer, Robert C.; James, Richard; Rutz, Christian

2015-01-01

Social-network dynamics have profound consequences for biological processes such as information flow, but are notoriously difficult to measure in the wild. We used novel transceiver technology to chart association patterns across 19 days in a wild population of the New Caledonian crow—a tool-using species that may socially learn, and culturally accumulate, tool-related information. To examine the causes and consequences of changing network topology, we manipulated the environmental availability of the crows' preferred tool-extracted prey, and simulated, in silico, the diffusion of information across field-recorded time-ordered networks. Here we show that network structure responds quickly to environmental change and that novel information can potentially spread rapidly within multi-family communities, especially when tool-use opportunities are plentiful. At the same time, we report surprisingly limited social contact between neighbouring crow communities. Such scale dependence in information-flow dynamics is likely to influence the evolution and maintenance of material cultures. PMID:26529116

A novel approach to assess temporal sensory perception of muscle foods: application of a time-intensity technique to diverse Iberian meat products.

PubMed

Lorido, Laura; Estévez, Mario; Ventanas, Sonia

2014-01-01

Although dynamic sensory techniques such as time-intensity (TI) have been applied to certain meat products, existing knowledge regarding the temporal sensory perception of muscle foods is still limited. The objective of the present study was to apply TI to the flavour and texture perception of three different Iberian meat products: liver pâté, dry-cured sausages ("salchichon") and dry-cured loin. Moreover, the advantages of using dynamic versus static sensory techniques were explored by subjecting the same products to a quantitative descriptive analysis (QDA). TI was a suitable technique to assess the impact of composition and structure of the three meat products on flavour and texture perception from a dynamic perspective. TI parameters extracted from the TI-curves and related to temporal perception enabled the detection of clear differences in sensory temporal perception between the meat products and provided additional insight on sensory perception compared to the conventional static sensory technique (QDA). © 2013.

Image segmentation and dynamic lineage analysis in single-cell fluorescence microscopy.

PubMed

Wang, Quanli; Niemi, Jarad; Tan, Chee-Meng; You, Lingchong; West, Mike

2010-01-01

An increasingly common component of studies in synthetic and systems biology is analysis of dynamics of gene expression at the single-cell level, a context that is heavily dependent on the use of time-lapse movies. Extracting quantitative data on the single-cell temporal dynamics from such movies remains a major challenge. Here, we describe novel methods for automating key steps in the analysis of single-cell, fluorescent images-segmentation and lineage reconstruction-to recognize and track individual cells over time. The automated analysis iteratively combines a set of extended morphological methods for segmentation, and uses a neighborhood-based scoring method for frame-to-frame lineage linking. Our studies with bacteria, budding yeast and human cells, demonstrate the portability and usability of these methods, whether using phase, bright field or fluorescent images. These examples also demonstrate the utility of our integrated approach in facilitating analyses of engineered and natural cellular networks in diverse settings. The automated methods are implemented in freely available, open-source software.

Exciton dynamics in a site-controlled quantum dot coupled to a photonic crystal cavity

NASA Astrophysics Data System (ADS)

Jarlov, C.; Lyasota, A.; Ferrier, L.; Gallo, P.; Dwir, B.; Rudra, A.; Kapon, E.

2015-11-01

Exciton and cavity mode (CM) dynamics in site-controlled pyramidal quantum dots (QDs), integrated with linear photonic crystal membrane cavities, are investigated for a range of temperatures and photo-excitation power levels. The absence of spurious multi-excitonic effects, normally observed in similar structures based on self-assembled QDs, permits the observation of effects intrinsic to two-level systems embedded in a solid state matrix and interacting with optical cavity modes. The coupled exciton and CM dynamics follow the same trend, indicating that the CM is fed only by the exciton transition. The Purcell reduction of the QD and CM decay times is reproduced well by a theoretical model that includes exciton linewidth broadening and temperature dependent non-radiative processes, from which we extract a Purcell factor of 17 ± 5. For excitation powers above QD saturation, we show the influence of quantum wire barrier states at short delay time, and demonstrate the absence of multiexcitonic background emission.

Microdialysis as a New Technique for Extracting Phenolic Compounds from Extra Virgin Olive Oil.

PubMed

Bazzu, Gianfranco; Molinu, Maria Giovanna; Dore, Antonio; Serra, Pier Andrea

2017-03-01

The amount and composition of the phenolic components play a major role in determining the quality of olive oil. The traditional liquid-liquid extraction (LLE) method requires a time-consuming sample preparation to obtain the "phenolic profile" of extra virgin olive oil (EVOO). This study aimed to develop a microdialysis extraction (MDE) as an alternative to the LLE method to evaluate the phenolic components of EVOO. To this purpose, a microdialysis device and dialysis procedure were developed. "Dynamic-oil" microdialysis was performed using an extracting solution (80:20 methanol/water) flow rate of 2 μL min -1 and a constant EVOO stream of 4 μL min -1 . The results indicated a strong positive correlation between MDE and the LLE method, providing a very similar phenolic profile obtained with traditional LLE. In conclusion, the MDE approach, easier and quicker in comparison to LLE, provided a reliable procedure to determine the phenolic components used as a marker of the quality and traceability of EVOO.

A Joint Time-Frequency and Matrix Decomposition Feature Extraction Methodology for Pathological Voice Classification

NASA Astrophysics Data System (ADS)

Ghoraani, Behnaz; Krishnan, Sridhar

2009-12-01

The number of people affected by speech problems is increasing as the modern world places increasing demands on the human voice via mobile telephones, voice recognition software, and interpersonal verbal communications. In this paper, we propose a novel methodology for automatic pattern classification of pathological voices. The main contribution of this paper is extraction of meaningful and unique features using Adaptive time-frequency distribution (TFD) and nonnegative matrix factorization (NMF). We construct Adaptive TFD as an effective signal analysis domain to dynamically track the nonstationarity in the speech and utilize NMF as a matrix decomposition (MD) technique to quantify the constructed TFD. The proposed method extracts meaningful and unique features from the joint TFD of the speech, and automatically identifies and measures the abnormality of the signal. Depending on the abnormality measure of each signal, we classify the signal into normal or pathological. The proposed method is applied on the Massachusetts Eye and Ear Infirmary (MEEI) voice disorders database which consists of 161 pathological and 51 normal speakers, and an overall classification accuracy of 98.6% was achieved.

Green synthesis of Copper nanoparticle using ionic liquid-based extraction from Polygonum minus and their applications.

PubMed

Ullah, Habib; Wilfred, Cecilia Devi; Shaharun, Maizatul Shima

2018-06-06

The present work reports the extraction of phenolic compounds from Polygonum minus using ionic liquid as extracting solvent. In this work, 1-Butyl-3-methylimidazolium hydrogen sulfate [BMIM][HSO 4 ] was used for the extraction of bioactive compounds. Accordingly, ionic liquids based microwave-assisted extraction treatment for separating of bioactive compounds from polygonum minus was first performed in the present study. The results obtained in this work have high extraction yield in comparison with conventional solvent. UV/Vis results showed that microwave synthesis was fast, well dispersed and nanosized copper nanoparticle (CuNPs) in comparison with conventional synthesis. CuNPs was characterized by X-Rays diffractometer (XRD), Fourier transform infrared (FTIR), dynamic light scattering (DLS), field emission scanning electron microscopy combined with energy dispersive x-rays (FESEM-EDX), and thermogravimetric analysis (TGA). All the instrumental analyses confirmed the particles were nanosized. Furthermore, the antibacterial activity of as-synthesized CuNPs showed effective inhibitory zone against three different bacteria. The photocatalytic degradation of copper nanoparticles was studied using methylene blue (MB) and methyl orange (MO) dyes under UV light and degraded 99.9% within short time 8 and 7 minutes.

Construction of Green Tide Monitoring System and Research on its Key Techniques

NASA Astrophysics Data System (ADS)

Xing, B.; Li, J.; Zhu, H.; Wei, P.; Zhao, Y.

2018-04-01

As a kind of marine natural disaster, Green Tide has been appearing every year along the Qingdao Coast, bringing great loss to this region, since the large-scale bloom in 2008. Therefore, it is of great value to obtain the real time dynamic information about green tide distribution. In this study, methods of optical remote sensing and microwave remote sensing are employed in Green Tide Monitoring Research. A specific remote sensing data processing flow and a green tide information extraction algorithm are designed, according to the optical and microwave data of different characteristics. In the aspect of green tide spatial distribution information extraction, an automatic extraction algorithm of green tide distribution boundaries is designed based on the principle of mathematical morphology dilation/erosion. And key issues in information extraction, including the division of green tide regions, the obtaining of basic distributions, the limitation of distribution boundary, and the elimination of islands, have been solved. The automatic generation of green tide distribution boundaries from the results of remote sensing information extraction is realized. Finally, a green tide monitoring system is built based on IDL/GIS secondary development in the integrated environment of RS and GIS, achieving the integration of RS monitoring and information extraction.

Growth of Listeria monocytogenes in pasteurized vanilla cream pudding as affected by storage temperature and the presence of cinnamon extract.

PubMed

Lianou, Alexandra; Moschonas, Galatios; Nychas, George-John E; Panagou, Efstathios Z

2018-04-01

The objective of the present study was the assessment and quantitative description of the growth behavior of Listeria monocytogenes as a function of temperature in vanilla cream pudding, formulated with or without cinnamon extract. Commercially prepared pasteurized vanilla cream pudding, formulated with (0.1% w/w) or without cinnamon extract, was inoculated with a five-strain mixture of L. monocytogenes (ca. 2logCFU/g) and stored aerobically at 4, 8, 12 and 16°C. At appropriate time intervals, L. monocytogenes populations were determined, and the primary model of Baranyi and Roberts was fitted to the derived microbiological data for the estimation of the pathogen's growth kinetic parameters. The effect of temperature on maximum specific growth rate (μ max ) was then modeled for each product type using a square-root-type model, and the developed models were validated using independent growth data generated during storage of inoculated vanilla cream samples under dynamic temperature conditions. Although the kinetic behavior of the pathogen was similar in cream with and without cinnamon extract during storage at higher temperatures, significant (P<0.05) differences were observed between the two product types at 4°C. With regard to secondary modelling, the estimated values of T min for cream with and without cinnamon extract were 0.39°C and -2.54°C, respectively, while the dynamic models exhibited satisfactory performance. Finally, as demonstrated by the findings of pulsed-field gel electrophoresis, both temperature and cinnamon extract affected the pathogen's strains dominating during storage. According to the collected data, cinnamon extract exhibits an important potential of enhancing the microbiological safety of vanilla cream pudding, provided that efficient temperature control is in place. The developed models should be useful in quantitative microbial risk assessment regarding the studied cream products. Copyright © 2017 Elsevier Ltd. All rights reserved.

Modelling of caesium dynamics in the negative ion sources at BATMAN and ELISE

NASA Astrophysics Data System (ADS)

Mimo, A.; Wimmer, C.; Wünderlich, D.; Fantz, U.

2017-08-01

The knowledge of Cs dynamics in negative hydrogen ion sources is a primary issue to achieve the ITER requirements for the Neutral Beam Injection (NBI) systems, i.e. one hour operation with an accelerated ion current of 40 A of D- and a ratio between negative ions and co-extracted electrons below one. Production of negative ions is mostly achieved by conversion of hydrogen/deuterium atoms on a converter surface, which is caesiated in order to reduce the work function and increase the conversion efficiency. The understanding of the Cs transport and redistribution mechanism inside the source is necessary for the achievement of high performances. Cs dynamics was therefore investigated by means of numerical simulations performed with the Monte Carlo transport code CsFlow3D. Simulations of the prototype source (1/8 of the ITER NBI source size) have shown that the plasma distribution inside the source has the major effect on Cs dynamics during the pulse: asymmetry of the plasma parameters leads to asymmetry in Cs distribution in front of the plasma grid. The simulated time traces and the general simulation results are in agreement with the experimental measurements. Simulations performed for the ELISE testbed (half of the ITER NBI source size) have shown an effect of the vacuum phase time on the amount and stability of Cs during the pulse. The sputtering of Cs due to back-streaming ions was reproduced by the simulations and it is in agreement with the experimental observation: this can become a critical issue during long pulses, especially in case of continuous extraction as foreseen for ITER. These results and the acquired knowledge of Cs dynamics will be useful to have a better management of Cs and thus to reduce its consumption, in the direction of the demonstration fusion power plant DEMO.

Determination of arsenic species in solid matrices utilizing supercritical fluid extraction coupled with gas chromatography after derivatization with thioglycolic acid n-butyl ester.

PubMed

Wang, Zhifeng; Cui, Zhaojie

2016-12-01

A method using derivatization and supercritical fluid extraction coupled with gas chromatography was developed for the analysis of dimethylarsinate, monomethylarsonate and inorganic arsenic simultaneously in solid matrices. Thioglycolic acid n-butyl ester was used as a novel derivatizing reagent. A systematic discussion was made to investigate the effects of pressure, temperature, flow rate of the supercritical CO 2 , extraction time, concentration of the modifier, and microemulsion on extraction efficiency. The application for real environmental samples was also studied. Results showed that thioglycolic acid n-butyl ester was an effective derivatizing reagent that could be applied for arsenic speciation. Using methanol as modifier of the supercritical CO 2 can raise the extraction efficiency, which can be further enhanced by adding a microemulsion that contains Triton X-405. The optimum extraction conditions were: 25 MPa, 90°C, static extraction for 10 min, dynamic extraction for 25 min with a flow rate of 2.0 mL/min of supercritical CO 2 modified by 5% v/v methanol and microemulsion. The detection limits of dimethylarsinate, monomethylarsonate, and inorganic arsenic in solid matrices were 0.12, 0.26, and 1.1 mg/kg, respectively. The optimized method was sensitive, convenient, and reliable for the extraction and analysis of different arsenic species in solid samples. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Integrated microwave processing system for the extraction of organophosphorus pesticides in fresh vegetables.

PubMed

Wu, Lijie; Song, Ying; Hu, Mingzhu; Xu, Xu; Zhang, Hanqi; Yu, Aimin; Ma, Qiang; Wang, Ziming

2015-03-01

A simple and efficient integrated microwave processing system (IMPS) was firstly assembled and validated for the extraction of organophosphorus pesticides in fresh vegetables. Two processes under microwave irradiation, dynamic microwave-assisted extraction (DMAE) and microwave-accelerated solvent elution (MASE), were integrated for simplifying the pretreatment of the sample. Extraction, separation, enrichment and elution were finished in a simple step. The organophosphorus pesticides were extracted from the fresh vegetables into hexane with DMAE, and then the extract was directly introduced into the enrichment column packed with active carbon fiber (ACF). Subsequently, the organophosphorus pesticides trapped on the ACF were eluted with ethyl acetate under microwave irradiation. No further filtration or cleanup was required before analysis of the eluate by gas chromatography-mass spectrometry. Some experimental parameters affecting extraction efficiency were investigated and optimized, such as microwave output power, kind and volume of extraction solvent, extraction time, amount of sorbent, elution microwave power, kind and volume of elution solvent, elution solvent flow rate. Under the optimized conditions, the recoveries were in the range of 71.5-105.2%, and the relative standard deviations were lower than 11.6%. The experiment results prove that the present method is a simple and effective sample preparation method for the determination of pesticides in solid samples. Copyright © 2014 Elsevier B.V. All rights reserved.

Development of green betaine-based deep eutectic solvent aqueous two-phase system for the extraction of protein.

PubMed

Li, Na; Wang, Yuzhi; Xu, Kaijia; Huang, Yanhua; Wen, Qian; Ding, Xueqin

2016-05-15

Six kinds of new type of green betaine-based deep eutectic solvents (DESs) have been synthesized. Deep eutectic solvent aqueous two-phase systems (DES-ATPS) were established and successfully applied in the extraction of protein. Betaine-urea (Be-U) was selected as the suitable extractant. Single factor experiments were carried out to determine the optimum conditions of the extraction process, such as the salt concentration, the mass of DES, the separation time, the amount of protein, the temperature and the pH value. The extraction efficiency could achieve to 99.82% under the optimum conditions. Mixed sample and practical sample analysis were discussed. The back extraction experiment was implemented and the back extraction efficiency could reach to 32.66%. The precision experiment, repeatability experiment and stability experiment were investigated. UV-vis, FT-IR and circular dichroism (CD) spectra confirmed that the conformation of protein was not changed during the process of extraction. The mechanisms of extraction were researched by dynamic light scattering (DLS), the measurement of the conductivity and transmission electron microscopy (TEM). DES-protein aggregates and embraces phenomenon play considerable roles in the separation process. All of these results indicated that betaine-based DES-ATPS may provide a potential substitute new method for the separation of proteins. Copyright © 2016 Elsevier B.V. All rights reserved.

Detecting and interpreting distortions in hierarchical organization of complex time series

NASA Astrophysics Data System (ADS)

DroŻdŻ, Stanisław; OświÈ©cimka, Paweł

2015-03-01

Hierarchical organization is a cornerstone of complexity and multifractality constitutes its central quantifying concept. For model uniform cascades the corresponding singularity spectra are symmetric while those extracted from empirical data are often asymmetric. Using selected time series representing such diverse phenomena as price changes and intertransaction times in financial markets, sentence length variability in narrative texts, Missouri River discharge, and sunspot number variability as examples, we show that the resulting singularity spectra appear strongly asymmetric, more often left sided but in some cases also right sided. We present a unified view on the origin of such effects and indicate that they may be crucially informative for identifying the composition of the time series. One particularly intriguing case of this latter kind of asymmetry is detected in the daily reported sunspot number variability. This signals that either the commonly used famous Wolf formula distorts the real dynamics in expressing the largest sunspot numbers or, if not, that their dynamics is governed by a somewhat different mechanism.

Oscillatory dynamics in the dorsal and ventral attention networks during the reorienting of attention.

PubMed

Proskovec, Amy L; Heinrichs-Graham, Elizabeth; Wiesman, Alex I; McDermott, Timothy J; Wilson, Tony W

2018-05-01

The ability to reorient attention within the visual field is central to daily functioning, and numerous fMRI studies have shown that the dorsal and ventral attention networks (DAN, VAN) are critical to such processes. However, despite the instantaneous nature of attentional shifts, the dynamics of oscillatory activity serving attentional reorientation remain poorly characterized. In this study, we utilized magnetoencephalography (MEG) and a Posner task to probe the dynamics of attentional reorienting in 29 healthy adults. MEG data were transformed into the time-frequency domain and significant oscillatory responses were imaged using a beamformer. Voxel time series were then extracted from peak voxels in the functional beamformer images. These time series were used to quantify the dynamics of attentional reorienting, and to compute dynamic functional connectivity. Our results indicated strong increases in theta and decreases in alpha and beta activity across many nodes in the DAN and VAN. Interestingly, theta responses were generally stronger during trials that required attentional reorienting relative to those that did not, while alpha and beta oscillations were more dynamic, with many regions exhibiting significantly stronger responses during non-reorienting trials initially, and the opposite pattern during later processing. Finally, stronger functional connectivity was found following target presentation (575-700 ms) between bilateral superior parietal lobules during attentional reorienting. In sum, these data show that visual attention is served by multiple cortical regions within the DAN and VAN, and that attentional reorienting processes are often associated with spectrally-specific oscillations that have largely distinct spatiotemporal dynamics. © 2018 Wiley Periodicals, Inc.

Delocalization and stretch-bend mixing of the HOH bend in liquid water

NASA Astrophysics Data System (ADS)

Carpenter, William B.; Fournier, Joseph A.; Biswas, Rajib; Voth, Gregory A.; Tokmakoff, Andrei

2017-08-01

Liquid water's rich sub-picosecond vibrational dynamics arise from the interplay of different high- and low-frequency modes evolving in a strong yet fluctuating hydrogen bond network. Recent studies of the OH stretching excitations of H2O indicate that they are delocalized over several molecules, raising questions about whether the bending vibrations are similarly delocalized. In this paper, we take advantage of an improved 50 fs time-resolution and broadband infrared (IR) spectroscopy to interrogate the 2D IR lineshape and spectral dynamics of the HOH bending vibration of liquid H2O. Indications of strong bend-stretch coupling are observed in early time 2D IR spectra through a broad excited state absorption that extends from 1500 cm-1 to beyond 1900 cm-1, which corresponds to transitions from the bend to the bend overtone and OH stretching band between 3150 and 3550 cm-1. Pump-probe measurements reveal a fast 180 fs vibrational relaxation time, which results in a hot-ground state spectrum that is the same as observed for water IR excitation at any other frequency. The fastest dynamical time scale is 80 fs for the polarization anisotropy decay, providing evidence for the delocalized or excitonic character of the bend. Normal mode analysis conducted on water clusters extracted from molecular dynamics simulations corroborate significant stretch-bend mixing and indicate delocalization of δHOH on 2-7 water molecules.

Dark-field-based observation of single-nanoparticle dynamics on a supported lipid bilayer for in situ analysis of interacting molecules and nanoparticles.

PubMed

Lee, Young Kwang; Kim, Sungi; Nam, Jwa-Min

2015-01-12

Observation of single plasmonic nanoparticles in reconstituted biological systems allows us to obtain snapshots of dynamic processes between molecules and nanoparticles with unprecedented spatiotemporal resolution and single-molecule/single-particle-level data acquisition. This Concept is intended to introduce nanoparticle-tethered supported lipid bilayer platforms that allow for the dynamic confinement of nanoparticles on a two-dimensional fluidic surface. The dark-field-based long-term, stable, real-time observation of freely diffusing plasmonic nanoparticles on a lipid bilayer enables one to extract a broad range of information about interparticle and molecular interactions throughout the entire reaction period. Herein, we highlight important developments in this context to provide ideas on how molecular interactions can be interpreted by monitoring dynamic behaviors and optical signals of laterally mobile nanoparticles. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Interevent time distributions of human multi-level activity in a virtual world

NASA Astrophysics Data System (ADS)

Mryglod, O.; Fuchs, B.; Szell, M.; Holovatch, Yu.; Thurner, S.

2015-02-01

Studying human behavior in virtual environments provides extraordinary opportunities for a quantitative analysis of social phenomena with levels of accuracy that approach those of the natural sciences. In this paper we use records of player activities in the massive multiplayer online game Pardus over 1238 consecutive days, and analyze dynamical features of sequences of actions of players. We build on previous work where temporal structures of human actions of the same type were quantified, and provide an empirical understanding of human actions of different types. This study of multi-level human activity can be seen as a dynamic counterpart of static multiplex network analysis. We show that the interevent time distributions of actions in the Pardus universe follow highly non-trivial distribution functions, from which we extract action-type specific characteristic 'decay constants'. We discuss characteristic features of interevent time distributions, including periodic patterns on different time scales, bursty dynamics, and various functional forms on different time scales. We comment on gender differences of players in emotional actions, and find that while males and females act similarly when performing some positive actions, females are slightly faster for negative actions. We also observe effects on the age of players: more experienced players are generally faster in making decisions about engaging in and terminating enmity and friendship, respectively.

Extracting the time scales of conformational dynamics from single-molecule single-photon fluorescence statistics.

PubMed

Shang, Jianyuan; Geva, Eitan

2007-04-26

The quenching rate of a fluorophore attached to a macromolecule can be rather sensitive to its conformational state. The decay of the corresponding fluorescence lifetime autocorrelation function can therefore provide unique information on the time scales of conformational dynamics. The conventional way of measuring the fluorescence lifetime autocorrelation function involves evaluating it from the distribution of delay times between photoexcitation and photon emission. However, the time resolution of this procedure is limited by the time window required for collecting enough photons in order to establish this distribution with sufficient signal-to-noise ratio. Yang and Xie have recently proposed an approach for improving the time resolution, which is based on the argument that the autocorrelation function of the delay time between photoexcitation and photon emission is proportional to the autocorrelation function of the square of the fluorescence lifetime [Yang, H.; Xie, X. S. J. Chem. Phys. 2002, 117, 10965]. In this paper, we show that the delay-time autocorrelation function is equal to the autocorrelation function of the square of the fluorescence lifetime divided by the autocorrelation function of the fluorescence lifetime. We examine the conditions under which the delay-time autocorrelation function is approximately proportional to the autocorrelation function of the square of the fluorescence lifetime. We also investigate the correlation between the decay of the delay-time autocorrelation function and the time scales of conformational dynamics. The results are demonstrated via applications to a two-state model and an off-lattice model of a polypeptide.

Effects of Neutron-Star Dynamic Tides on Gravitational Waveforms within the Effective-One-Body Approach

NASA Astrophysics Data System (ADS)

Hinderer, Tanja; Taracchini, Andrea; Foucart, Francois; Buonanno, Alessandra; Steinhoff, Jan; Duez, Matthew; Kidder, Lawrence E.; Pfeiffer, Harald P.; Scheel, Mark A.; Szilagyi, Bela; Hotokezaka, Kenta; Kyutoku, Koutarou; Shibata, Masaru; Carpenter, Cory W.

2016-05-01

Extracting the unique information on ultradense nuclear matter from the gravitational waves emitted by merging neutron-star binaries requires robust theoretical models of the signal. We develop a novel effective-one-body waveform model that includes, for the first time, dynamic (instead of only adiabatic) tides of the neutron star as well as the merger signal for neutron-star-black-hole binaries. We demonstrate the importance of the dynamic tides by comparing our model against new numerical-relativity simulations of nonspinning neutron-star-black-hole binaries spanning more than 24 gravitational-wave cycles, and to other existing numerical simulations for double neutron-star systems. Furthermore, we derive an effective description that makes explicit the dependence of matter effects on two key parameters: tidal deformability and fundamental oscillation frequency.

The Dynamics of Disorder-Order Transition in Hard Sphere Colloidal Dispersions

NASA Technical Reports Server (NTRS)

Chaikin, Paul M.; Zhu, Jixiang; Cheng, Zhengdong; Phan, See-Eng; Russel, William B.; Lant, Christian T.; Doherty, Michael P.; Meyer, William V.; Rogers, Richard; Cannell, D. S.;

A Multiscale Survival Process for Modeling Human Activity Patterns.

PubMed

Zhang, Tianyang; Cui, Peng; Song, Chaoming; Zhu, Wenwu; Yang, Shiqiang

2016-01-01

Human activity plays a central role in understanding large-scale social dynamics. It is well documented that individual activity pattern follows bursty dynamics characterized by heavy-tailed interevent time distributions. Here we study a large-scale online chatting dataset consisting of 5,549,570 users, finding that individual activity pattern varies with timescales whereas existing models only approximate empirical observations within a limited timescale. We propose a novel approach that models the intensity rate of an individual triggering an activity. We demonstrate that the model precisely captures corresponding human dynamics across multiple timescales over five orders of magnitudes. Our model also allows extracting the population heterogeneity of activity patterns, characterized by a set of individual-specific ingredients. Integrating our approach with social interactions leads to a wide range of implications.

Effects of Neutron-Star Dynamic Tides on Gravitational Waveforms within the Effective-One-Body Approach.

PubMed

Hinderer, Tanja; Taracchini, Andrea; Foucart, Francois; Buonanno, Alessandra; Steinhoff, Jan; Duez, Matthew; Kidder, Lawrence E; Pfeiffer, Harald P; Scheel, Mark A; Szilagyi, Bela; Hotokezaka, Kenta; Kyutoku, Koutarou; Shibata, Masaru; Carpenter, Cory W

2016-05-06

Extracting the unique information on ultradense nuclear matter from the gravitational waves emitted by merging neutron-star binaries requires robust theoretical models of the signal. We develop a novel effective-one-body waveform model that includes, for the first time, dynamic (instead of only adiabatic) tides of the neutron star as well as the merger signal for neutron-star-black-hole binaries. We demonstrate the importance of the dynamic tides by comparing our model against new numerical-relativity simulations of nonspinning neutron-star-black-hole binaries spanning more than 24 gravitational-wave cycles, and to other existing numerical simulations for double neutron-star systems. Furthermore, we derive an effective description that makes explicit the dependence of matter effects on two key parameters: tidal deformability and fundamental oscillation frequency.

An explicit asymptotic model for the surface wave in a viscoelastic half-space based on applying Rabotnov's fractional exponential integral operators

NASA Astrophysics Data System (ADS)

Wilde, M. V.; Sergeeva, N. V.

2018-05-01

An explicit asymptotic model extracting the contribution of a surface wave to the dynamic response of a viscoelastic half-space is derived. Fractional exponential Rabotnov's integral operators are used for describing of material properties. The model is derived by extracting the principal part of the poles corresponding to the surface waves after applying Laplace and Fourier transforms. The simplified equations for the originals are written by using power series expansions. Padè approximation is constructed to unite short-time and long-time models. The form of this approximation allows to formulate the explicit model using a fractional exponential Rabotnov's integral operator with parameters depending on the properties of surface wave. The applicability of derived models is studied by comparing with the exact solutions of a model problem. It is revealed that the model based on Padè approximation is highly effective for all the possible time domains.

Dynamic fractionation of trace metals in soil and sediment samples using rotating coiled column extraction and sequential injection microcolumn extraction: a comparative study.

PubMed

Rosende, Maria; Savonina, Elena Yu; Fedotov, Petr S; Miró, Manuel; Cerdà, Víctor; Wennrich, Rainer

2009-09-15

Dynamic fractionation has been recognized as an appealing alternative to conventional equilibrium-based sequential extraction procedures (SEPs) for partitioning of trace elements (TE) in environmental solid samples. This paper reports the first attempt for harmonization of flow-through dynamic fractionation using two novel methods, the so-called sequential injection microcolumn (SIMC) extraction and rotating coiled column (RCC) extraction. In SIMC extraction, a column packed with the solid sample is clustered in a sequential injection system, while in RCC, the particulate matter is retained under the action of centrifugal forces. In both methods, the leachants are continuously pumped through the solid substrates by the use of either peristaltic or syringe pumps. A five-step SEP was selected for partitioning of Cu, Pb and Zn in water soluble/exchangeable, acid-soluble, easily reducible, easily oxidizable and moderately reducible fractions from 0.2 to 0.5 g samples at an extractant flow rate of 1.0 mL min(-1) prior to leachate analysis by inductively coupled plasma-atomic emission spectrometry. Similarities and discrepancies between both dynamic approaches were ascertained by fractionation of TE in certified reference materials, namely, SRM 2711 Montana Soil and GBW 07311 sediment, and two real soil samples as well. Notwithstanding the different extraction conditions set by both methods, similar trends of metal distribution were in generally found. The most critical parameters for reliable assessment of mobilizable pools of TE in worse-case scenarios are the size-distribution of sample particles, the density of particles, the content of organic matter and the concentration of major elements. For reference materials and a soil rich in organic matter, the extraction in RCC results in slightly higher recoveries of environmentally relevant fractions of TE, whereas SIMC leaching is more effective for calcareous soils.

Single ion dynamics in molten sodium bromide

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

Alcaraz, O.; Trullas, J.; Demmel, F.

We present a study on the single ion dynamics in the molten alkali halide NaBr. Quasielastic neutron scattering was employed to extract the self-diffusion coefficient of the sodium ions at three temperatures. Molecular dynamics simulations using rigid and polarizable ion models have been performed in parallel to extract the sodium and bromide single dynamics and ionic conductivities. Two methods have been employed to derive the ion diffusion, calculating the mean squared displacements and the velocity autocorrelation functions, as well as analysing the increase of the line widths of the self-dynamic structure factors. The sodium diffusion coefficients show a remarkable goodmore » agreement between experiment and simulation utilising the polarisable potential.« less

On artifacts in single-molecule force spectroscopy

PubMed Central

Cossio, Pilar; Hummer, Gerhard; Szabo, Attila

2015-01-01

In typical force spectroscopy experiments, a small biomolecule is attached to a soft polymer linker that is pulled with a relatively large bead or cantilever. At constant force, the total extension stochastically changes between two (or more) values, indicating that the biomolecule undergoes transitions between two (or several) conformational states. In this paper, we consider the influence of the dynamics of the linker and mesoscopic pulling device on the force-dependent rate of the conformational transition extracted from the time dependence of the total extension, and the distribution of rupture forces in force-clamp and force-ramp experiments, respectively. For these different experiments, we derive analytic expressions for the observables that account for the mechanical response and dynamics of the pulling device and linker. Possible artifacts arise when the characteristic times of the pulling device and linker become comparable to, or slower than, the lifetimes of the metastable conformational states, and when the highly anharmonic regime of stretched linkers is probed at high forces. We also revisit the problem of relating force-clamp and force-ramp experiments, and identify a linker and loading rate-dependent correction to the rates extracted from the latter. The theory provides a framework for both the design and the quantitative analysis of force spectroscopy experiments by highlighting, and correcting for, factors that complicate their interpretation. PMID:26540730

Dynamic displacement measurement of large-scale structures based on the Lucas-Kanade template tracking algorithm

NASA Astrophysics Data System (ADS)

Guo, Jie; Zhu, Chang`an

2016-01-01

The development of optics and computer technologies enables the application of the vision-based technique that uses digital cameras to the displacement measurement of large-scale structures. Compared with traditional contact measurements, vision-based technique allows for remote measurement, has a non-intrusive characteristic, and does not necessitate mass introduction. In this study, a high-speed camera system is developed to complete the displacement measurement in real time. The system consists of a high-speed camera and a notebook computer. The high-speed camera can capture images at a speed of hundreds of frames per second. To process the captured images in computer, the Lucas-Kanade template tracking algorithm in the field of computer vision is introduced. Additionally, a modified inverse compositional algorithm is proposed to reduce the computing time of the original algorithm and improve the efficiency further. The modified algorithm can rapidly accomplish one displacement extraction within 1 ms without having to install any pre-designed target panel onto the structures in advance. The accuracy and the efficiency of the system in the remote measurement of dynamic displacement are demonstrated in the experiments on motion platform and sound barrier on suspension viaduct. Experimental results show that the proposed algorithm can extract accurate displacement signal and accomplish the vibration measurement of large-scale structures.

Experimental Determination of Dynamical Lee-Yang Zeros

NASA Astrophysics Data System (ADS)

Brandner, Kay; Maisi, Ville F.; Pekola, Jukka P.; Garrahan, Juan P.; Flindt, Christian

2017-05-01

Statistical physics provides the concepts and methods to explain the phase behavior of interacting many-body systems. Investigations of Lee-Yang zeros—complex singularities of the free energy in systems of finite size—have led to a unified understanding of equilibrium phase transitions. The ideas of Lee and Yang, however, are not restricted to equilibrium phenomena. Recently, Lee-Yang zeros have been used to characterize nonequilibrium processes such as dynamical phase transitions in quantum systems after a quench or dynamic order-disorder transitions in glasses. Here, we experimentally realize a scheme for determining Lee-Yang zeros in such nonequilibrium settings. We extract the dynamical Lee-Yang zeros of a stochastic process involving Andreev tunneling between a normal-state island and two superconducting leads from measurements of the dynamical activity along a trajectory. From the short-time behavior of the Lee-Yang zeros, we predict the large-deviation statistics of the activity which is typically difficult to measure. Our method paves the way for further experiments on the statistical mechanics of many-body systems out of equilibrium.

Dynamic x-ray imaging of laser-driven nanoplasmas

NASA Astrophysics Data System (ADS)

Fennel, Thomas

2016-05-01

A major promise of current x-ray science at free electron lasers is the realization of unprecedented imaging capabilities for resolving the structure and ultrafast dynamics of matter with nanometer spatial and femtosecond temporal resolution or even below via single-shot x-ray diffraction. Laser-driven atomic clusters and nanoparticles provide an ideal platform for developing and demonstrating the required technology to extract the ultrafast transient spatiotemporal dynamics from the diffraction images. In this talk, the perspectives and challenges of dynamic x-ray imaging will be discussed using complete self-consistent microscopic electromagnetic simulations of IR pump x-ray probe imaging for the example of clusters. The results of the microscopic particle-in-cell simulations (MicPIC) enable the simulation-assisted reconstruction of corresponding experimental data. This capability is demonstrated by converting recently measured LCLS data into a ultrahigh resolution movie of laser-induced plasma expansion. Finally, routes towards reaching attosecond time resolution in the visualization of complex dynamical processes in matter by x-ray diffraction will be discussed.

Principal component analysis of indocyanine green fluorescence dynamics for diagnosis of vascular diseases

NASA Astrophysics Data System (ADS)

Seo, Jihye; An, Yuri; Lee, Jungsul; Choi, Chulhee

2015-03-01

Indocyanine green (ICG), a near-infrared fluorophore, has been used in visualization of vascular structure and non-invasive diagnosis of vascular disease. Although many imaging techniques have been developed, there are still limitations in diagnosis of vascular diseases. We have recently developed a minimally invasive diagnostics system based on ICG fluorescence imaging for sensitive detection of vascular insufficiency. In this study, we used principal component analysis (PCA) to examine ICG spatiotemporal profile and to obtain pathophysiological information from ICG dynamics. Here we demonstrated that principal components of ICG dynamics in both feet showed significant differences between normal control and diabetic patients with vascula complications. We extracted the PCA time courses of the first three components and found distinct pattern in diabetic patient. We propose that PCA of ICG dynamics reveal better classification performance compared to fluorescence intensity analysis. We anticipate that specific feature of spatiotemporal ICG dynamics can be useful in diagnosis of various vascular diseases.

Comprehensive cosmographic analysis by Markov chain method

NASA Astrophysics Data System (ADS)

Capozziello, S.; Lazkoz, R.; Salzano, V.

2011-12-01

We study the possibility of extracting model independent information about the dynamics of the Universe by using cosmography. We intend to explore it systematically, to learn about its limitations and its real possibilities. Here we are sticking to the series expansion approach on which cosmography is based. We apply it to different data sets: Supernovae type Ia (SNeIa), Hubble parameter extracted from differential galaxy ages, gamma ray bursts, and the baryon acoustic oscillations data. We go beyond past results in the literature extending the series expansion up to the fourth order in the scale factor, which implies the analysis of the deceleration q0, the jerk j0, and the snap s0. We use the Markov chain Monte Carlo method (MCMC) to analyze the data statistically. We also try to relate direct results from cosmography to dark energy (DE) dynamical models parametrized by the Chevallier-Polarski-Linder model, extracting clues about the matter content and the dark energy parameters. The main results are: (a) even if relying on a mathematical approximate assumption such as the scale factor series expansion in terms of time, cosmography can be extremely useful in assessing dynamical properties of the Universe; (b) the deceleration parameter clearly confirms the present acceleration phase; (c) the MCMC method can help giving narrower constraints in parameter estimation, in particular for higher order cosmographic parameters (the jerk and the snap), with respect to the literature; and (d) both the estimation of the jerk and the DE parameters reflect the possibility of a deviation from the ΛCDM cosmological model.

High-efficiency headspace sampling of volatile organic compounds in explosives using capillary microextraction of volatiles (CMV) coupled to gas chromatography-mass spectrometry (GC-MS).

PubMed

Fan, Wen; Almirall, José

2014-03-01

A novel geometry configuration based on sorbent-coated glass microfibers packed within a glass capillary is used to sample volatile organic compounds, dynamically, in the headspace of an open system or in a partially open system to achieve quantitative extraction of the available volatiles of explosives with negligible breakthrough. Air is sampled through the newly developed sorbent-packed 2 cm long, 2 mm diameter capillary microextraction of volatiles (CMV) and subsequently introduced into a commercially available thermal desorption probe fitted directly into a GC injection port. A sorbent coating surface area of ∼5 × 10(-2) m(2) or 5,000 times greater than that of a single solid-phase microextraction (SPME) fiber allows for fast (30 s), flow-through sampling of relatively large volumes using sampling flow rates of ∼1.5 L/min. A direct comparison of the new CMV extraction to a static (equilibrium) SPME extraction of the same headspace sample yields a 30 times improvement in sensitivity for the CMV when sampling nitroglycerine (NG), 2,4-dinitrotoluene (2,4-DNT), and diphenylamine (DPA) in a mixture containing a total mass of 500 ng of each analyte, when spiked into a liter-volume container. Calibration curves were established for all compounds studied, and the recovery was determined to be ∼1 % or better after only 1 min of sampling time. Quantitative analysis is also possible using this extraction technique when the sampling temperature, flow rate, and time are kept constant between calibration curves and the sample.

Revealing the subfemtosecond dynamics of orbital angular momentum in nanoplasmonic vortices

NASA Astrophysics Data System (ADS)

Spektor, G.; Kilbane, D.; Mahro, A. K.; Frank, B.; Ristok, S.; Gal, L.; Kahl, P.; Podbiel, D.; Mathias, S.; Giessen, H.; Meyer zu Heringdorf, F.-J.; Orenstein, M.; Aeschlimann, M.

2017-03-01

The ability of light to carry and deliver orbital angular momentum (OAM) in the form of optical vortices has attracted much interest. The physical properties of light with a helical wavefront can be confined onto two-dimensional surfaces with subwavelength dimensions in the form of plasmonic vortices, opening avenues for thus far unknown light-matter interactions. Because of their extreme rotational velocity, the ultrafast dynamics of such vortices remained unexplored. Here we show the detailed spatiotemporal evolution of nanovortices using time-resolved two-photon photoemission electron microscopy. We observe both long- and short-range plasmonic vortices confined to deep subwavelength dimensions on the scale of 100 nanometers with nanometer spatial resolution and subfemtosecond time-step resolution. Finally, by measuring the angular velocity of the vortex, we directly extract the OAM magnitude of light.

Biosynthesis of silver nanoparticles using Ocimum sanctum (Tulsi) leaf extract and screening its antimicrobial activity

NASA Astrophysics Data System (ADS)

Singhal, Garima; Bhavesh, Riju; Kasariya, Kunal; Sharma, Ashish Ranjan; Singh, Rajendra Pal

2011-07-01

Development of green nanotechnology is generating interest of researchers toward ecofriendly biosynthesis of nanoparticles. In this study, biosynthesis of stable silver nanoparticles was done using Tulsi ( Ocimum sanctum) leaf extract. These biosynthesized nanoparticles were characterized with the help of UV-vis spectrophotometer, Atomic Absorption Spectroscopy (AAS), Dynamic light scattering (DLS), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and Transmission electron microscopy (TEM). Stability of bioreduced silver nanoparticles was analyzed using UV-vis absorption spectra, and their antimicrobial activity was screened against both gram-negative and gram-positive microorganisms. It was observed that O. sanctum leaf extract can reduce silver ions into silver nanoparticles within 8 min of reaction time. Thus, this method can be used for rapid and ecofriendly biosynthesis of stable silver nanoparticles of size range 4-30 nm possessing antimicrobial activity suggesting their possible application in medical industry.

Antibacterial, anticancer and antioxidant potential of silver nanoparticles engineered using Trigonella foenum-graecum seed extract.

PubMed

Goyal, Shivangi; Gupta, Nidhi; Kumar, Ajeet; Chatterjee, Sreemoyee; Nimesh, Surendra

2018-06-01

In this study, the authors report a simple and eco-friendly method for the synthesis of silver nanoparticles (AgNPs) using Trigonella foenum-graecum (TFG) seed extract. They explored several parameters dictating the biosynthesis of TFG-AgNPs such as reaction time, temperature, concentration of AgNO 3 , and TFG extract amount. Physicochemical characterisation of TFG-AgNPs was done on dynamic light scattering (DLS), field emission electron microscopy, energy dispersive X-ray spectroscopy, X-ray diffraction and Fourier transform infrared spectroscopy. The size determination studies using DLS revealed of TFG-AgNPs size between 95 and 110 nm. The antibacterial activity was studied against Escherichia coli, Proteus vulgaris, Pseudomonas aeruginosa and Staphylococcus aureus . The biosynthesised TFG-AgNPs showed remarkable anticancer efficacy against skin cancer cell line, A431 and also exhibited significant antioxidant efficacy.

System-size and beam energy dependence of the space-time extent of the pion emission source

NASA Astrophysics Data System (ADS)

Pak, Robert; Phenix Collaboration

2014-09-01

Two-pion interferometry measurements are used to extract the Gaussian source radii Rout ,Rside and Rlong , of the pion emission sources produced in d + Au, Cu +Cu and Au +Au collisions for several beam collision energies at PHENIX experiment. The extracted radii, which are compared to recent STAR and ALICE data, show characteristic scaling patterns as a function of the initial transverse geometric size of the collision system, and the transverse mass of the emitted pion pairs. These scaling patterns indicate a linear dependence of Rside on the initial transverse size, as well as a smaller freeze-out size for the d + Au system. Mathematical combinations of the extracted radii generally associated with the emission source duration and expansion rate exhibit non-monotonic behavior, suggesting a change in the expansion dynamics over this beam energy range.

Thermal machines beyond the weak coupling regime

NASA Astrophysics Data System (ADS)

Gallego, R.; Riera, A.; Eisert, J.

2014-12-01

How much work can be extracted from a heat bath using a thermal machine? The study of this question has a very long history in statistical physics in the weak-coupling limit, when applied to macroscopic systems. However, the assumption that thermal heat baths remain uncorrelated with associated physical systems is less reasonable on the nano-scale and in the quantum setting. In this work, we establish a framework of work extraction in the presence of quantum correlations. We show in a mathematically rigorous and quantitative fashion that quantum correlations and entanglement emerge as limitations to work extraction compared to what would be allowed by the second law of thermodynamics. At the heart of the approach are operations that capture the naturally non-equilibrium dynamics encountered when putting physical systems into contact with each other. We discuss various limits that relate to known results and put our work into the context of approaches to finite-time quantum thermodynamics.

Multiunit Activity-Based Real-Time Limb-State Estimation from Dorsal Root Ganglion Recordings

PubMed Central

Han, Sungmin; Chu, Jun-Uk; Kim, Hyungmin; Park, Jong Woong; Youn, Inchan

2017-01-01

Proprioceptive afferent activities could be useful for providing sensory feedback signals for closed-loop control during functional electrical stimulation (FES). However, most previous studies have used the single-unit activity of individual neurons to extract sensory information from proprioceptive afferents. This study proposes a new decoding method to estimate ankle and knee joint angles using multiunit activity data. Proprioceptive afferent signals were recorded from a dorsal root ganglion with a single-shank microelectrode during passive movements of the ankle and knee joints, and joint angles were measured as kinematic data. The mean absolute value (MAV) was extracted from the multiunit activity data, and a dynamically driven recurrent neural network (DDRNN) was used to estimate ankle and knee joint angles. The multiunit activity-based MAV feature was sufficiently informative to estimate limb states, and the DDRNN showed a better decoding performance than conventional linear estimators. In addition, processing time delay satisfied real-time constraints. These results demonstrated that the proposed method could be applicable for providing real-time sensory feedback signals in closed-loop FES systems. PMID:28276474

Temporal and spectral characteristics of dynamic functional connectivity between resting-state networks reveal information beyond static connectivity

PubMed Central

Yeh, Hsiang J.; Guindani, Michele; Vannucci, Marina; Haneef, Zulfi; Stern, John M.

2018-01-01

Estimation of functional connectivity (FC) has become an increasingly powerful tool for investigating healthy and abnormal brain function. Static connectivity, in particular, has played a large part in guiding conclusions from the majority of resting-state functional MRI studies. However, accumulating evidence points to the presence of temporal fluctuations in FC, leading to increasing interest in estimating FC as a dynamic quantity. One central issue that has arisen in this new view of connectivity is the dramatic increase in complexity caused by dynamic functional connectivity (dFC) estimation. To computationally handle this increased complexity, a limited set of dFC properties, primarily the mean and variance, have generally been considered. Additionally, it remains unclear how to integrate the increased information from dFC into pattern recognition techniques for subject-level prediction. In this study, we propose an approach to address these two issues based on a large number of previously unexplored temporal and spectral features of dynamic functional connectivity. A Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model is used to estimate time-varying patterns of functional connectivity between resting-state networks. Time-frequency analysis is then performed on dFC estimates, and a large number of previously unexplored temporal and spectral features drawn from signal processing literature are extracted for dFC estimates. We apply the investigated features to two neurologic populations of interest, healthy controls and patients with temporal lobe epilepsy, and show that the proposed approach leads to substantial increases in predictive performance compared to both traditional estimates of static connectivity as well as current approaches to dFC. Variable importance is assessed and shows that there are several quantities that can be extracted from dFC signal which are more informative than the traditional mean or variance of dFC. This work illuminates many previously unexplored facets of the dynamic properties of functional connectivity between resting-state networks, and provides a platform for dynamic functional connectivity analysis that facilitates its usage as an investigative measure for healthy as well as abnormal brain function. PMID:29320526

A procedure for damage detection and localization of framed buildings based on curvature variation

NASA Astrophysics Data System (ADS)

Ditommaso, Rocco; Carlo Ponzo, Felice; Auletta, Gianluca; Iacovino, Chiara; Mossucca, Antonello; Nigro, Domenico; Nigro, Antonella

2014-05-01

Structural Health Monitoring and Damage Detection are topics of current interest in civil, mechanical and aerospace engineering. Damage Detection approach based on dynamic monitoring of structural properties over time has received a considerable attention in recent scientific literature of the last years. The basic idea arises from the observation that spectral properties, described in terms of the so-called modal parameters (eigenfrequencies, mode shapes, and modal damping), are functions of the physical properties of the structure (mass, energy dissipation mechanisms and stiffness). Structural damage exhibits its main effects in terms of stiffness and damping variation. As a consequence, a permanent dynamic monitoring system makes it possible to detect and, if suitably concentrated on the structure, to localize structural and non-structural damage occurred on the structure during a strong earthquake. In the last years many researchers are working to set-up new methodologies for Non-destructive Damage Evaluation (NDE) based on the variation of the dynamic behaviour of structures under seismic loads. Pandey et al. (1991) highlighted on the possibility to use the structural mode shapes to extract useful information for structural damage localization. In this paper a new procedure for damage detection on framed structures based on changes in modal curvature is proposed. The proposed approach is based on the use of Stockwell Transform, a special kind of integral transformation that become a powerful tool for nonlinear signal analysis and then to analyse the nonlinear behaviour of a general structure. Using this kind of approach, it is possible to use a band-variable filter (Ditommaso et al., 2012) to extract from a signal recorded on a structure (excited by an earthquake) the response related to a single mode of vibration for which the related frequency changes over time (if the structure is being damaged). İn general, by acting simultaneously in both frequency and time domain, it is possible to use the band-variable filter to extract the dynamic characteristics of a system that evolves over time. Aim of this paper is to show, through practical examples, how it is possible to identify and to localize damage on a structure comparing mode shapes and the related curvature variations over time. It is possible to demonstrate that mode curvature variation is strongly related with the damage occurred on a structure. This paper resumes the main outcomes retrieved from many numerical non linear dynamic models of reinforced concrete framed structures characterized by different geometric configurations and designed for gravity loads only. The numerical campaign was conducted using both natural and artificial accelerograms compatible with the Italian code. The main results of experimental shaking table tests carried out on a steel framed model are also showed to confirm the effectiveness of the proposed procedure. REFERENCES Ditommaso R., Mucciarelli M., Ponzo F. C. (2012). Analysis of non-stationary structural systems by using a band-variable filter. Bulletin of Earthquake Engineering. Volume 10, Number 3, pp. 895-911. DOI: 10.1007/s10518-012-9338-y. Pandey AK, Biswas M, Samman MM (1991) "Damage detection from changes in curvature mode shapes", Journal of Sound and Vibration, Vol. 145: Issue 2, pp. 321-332.

Enhanced subject-specific resting-state network detection and extraction with fast fMRI.

PubMed

Akin, Burak; Lee, Hsu-Lei; Hennig, Jürgen; LeVan, Pierre

2017-02-01

Resting-state networks have become an important tool for the study of brain function. An ultra-fast imaging technique that allows to measure brain function, called Magnetic Resonance Encephalography (MREG), achieves an order of magnitude higher temporal resolution than standard echo-planar imaging (EPI). This new sequence helps to correct physiological artifacts and improves the sensitivity of the fMRI analysis. In this study, EPI is compared with MREG in terms of capability to extract resting-state networks. Healthy controls underwent two consecutive resting-state scans, one with EPI and the other with MREG. Subject-level independent component analyses (ICA) were performed separately for each of the two datasets. Using Stanford FIND atlas parcels as network templates, the presence of ICA maps corresponding to each network was quantified in each subject. The number of detected individual networks was significantly higher in the MREG data set than for EPI. Moreover, using short time segments of MREG data, such as 50 seconds, one can still detect and track consistent networks. Fast fMRI thus results in an increased capability to extract distinct functional regions at the individual subject level for the same scan times, and also allow the extraction of consistent networks within shorter time intervals than when using EPI, which is notably relevant for the analysis of dynamic functional connectivity fluctuations. Hum Brain Mapp 38:817-830, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Effects of stream turbine array configuration on tidal current energy extraction near an island

NASA Astrophysics Data System (ADS)

Chen, Yaling; Lin, Binliang; Lin, Jie; Wang, Shujie

2015-04-01

Enhanced tidal currents around islands appear to present the potential for power extraction. In this research, a three-dimensional numerical model is applied to investigate the naturally occurring tidal dynamics and the extractable energy from turbines close to Zhaitang Island, located off the east coast of China. In the model, the effect of tidal turbine is represented by a horizontal thrust and added to the momentum equations. To determine a better configuration of turbine array, a detailed work has been undertaken to investigate the combined influences of the topographic features and array arrangement on the performance of power generation. First, three single row arrays are examined with lateral spacing being 2, 3 and 4 times rotor diameters. Then, corresponding to each lateral spacing, three multi-row arrays in a staggered manner with longitudinal spacing being 5, 10 and 15 times rotor diameters are developed. It has been found that single row arrays with higher local blockage outperform arrays with lower blockage. While for multi-row arrays, the performance of inside turbine is significantly experienced the wake influence of upstream turbines, which can be weakened with an increment of turbine spacing. And a remarkable improvement of turbine performance is observed as the longitudinal spacing increases to 10 times rotor diameters. However, the change pattern of power extraction is mainly dependent on that of naturally kinetic energy when the turbine density is further decreasing in the given region.

Superstatistical fluctuations in time series: Applications to share-price dynamics and turbulence

NASA Astrophysics Data System (ADS)

van der Straeten, Erik; Beck, Christian

2009-09-01

We report a general technique to study a given experimental time series with superstatistics. Crucial for the applicability of the superstatistics concept is the existence of a parameter β that fluctuates on a large time scale as compared to the other time scales of the complex system under consideration. The proposed method extracts the main superstatistical parameters out of a given data set and examines the validity of the superstatistical model assumptions. We test the method thoroughly with surrogate data sets. Then the applicability of the superstatistical approach is illustrated using real experimental data. We study two examples, velocity time series measured in turbulent Taylor-Couette flows and time series of log returns of the closing prices of some stock market indices.

A Bayesian framework for extracting human gait using strong prior knowledge.

PubMed

Zhou, Ziheng; Prügel-Bennett, Adam; Damper, Robert I

2006-11-01

Extracting full-body motion of walking people from monocular video sequences in complex, real-world environments is an important and difficult problem, going beyond simple tracking, whose satisfactory solution demands an appropriate balance between use of prior knowledge and learning from data. We propose a consistent Bayesian framework for introducing strong prior knowledge into a system for extracting human gait. In this work, the strong prior is built from a simple articulated model having both time-invariant (static) and time-variant (dynamic) parameters. The model is easily modified to cater to situations such as walkers wearing clothing that obscures the limbs. The statistics of the parameters are learned from high-quality (indoor laboratory) data and the Bayesian framework then allows us to "bootstrap" to accurate gait extraction on the noisy images typical of cluttered, outdoor scenes. To achieve automatic fitting, we use a hidden Markov model to detect the phases of images in a walking cycle. We demonstrate our approach on silhouettes extracted from fronto-parallel ("sideways on") sequences of walkers under both high-quality indoor and noisy outdoor conditions. As well as high-quality data with synthetic noise and occlusions added, we also test walkers with rucksacks, skirts, and trench coats. Results are quantified in terms of chamfer distance and average pixel error between automatically extracted body points and corresponding hand-labeled points. No one part of the system is novel in itself, but the overall framework makes it feasible to extract gait from very much poorer quality image sequences than hitherto. This is confirmed by comparing person identification by gait using our method and a well-established baseline recognition algorithm.

Time-lapse seismic waveform modelling and attribute analysis using hydromechanical models for a deep reservoir undergoing depletion

NASA Astrophysics Data System (ADS)

He, Y.-X.; Angus, D. A.; Blanchard, T. D.; Wang, G.-L.; Yuan, S.-Y.; Garcia, A.

2016-04-01

Extraction of fluids from subsurface reservoirs induces changes in pore pressure, leading not only to geomechanical changes, but also perturbations in seismic velocities and hence observable seismic attributes. Time-lapse seismic analysis can be used to estimate changes in subsurface hydromechanical properties and thus act as a monitoring tool for geological reservoirs. The ability to observe and quantify changes in fluid, stress and strain using seismic techniques has important implications for monitoring risk not only for petroleum applications but also for geological storage of CO2 and nuclear waste scenarios. In this paper, we integrate hydromechanical simulation results with rock physics models and full-waveform seismic modelling to assess time-lapse seismic attribute resolution for dynamic reservoir characterization and hydromechanical model calibration. The time-lapse seismic simulations use a dynamic elastic reservoir model based on a North Sea deep reservoir undergoing large pressure changes. The time-lapse seismic traveltime shifts and time strains calculated from the modelled and processed synthetic data sets (i.e. pre-stack and post-stack data) are in a reasonable agreement with the true earth models, indicating the feasibility of using 1-D strain rock physics transform and time-lapse seismic processing methodology. Estimated vertical traveltime shifts for the overburden and the majority of the reservoir are within ±1 ms of the true earth model values, indicating that the time-lapse technique is sufficiently accurate for predicting overburden velocity changes and hence geomechanical effects. Characterization of deeper structure below the overburden becomes less accurate, where more advanced time-lapse seismic processing and migration is needed to handle the complex geometry and strong lateral induced velocity changes. Nevertheless, both migrated full-offset pre-stack and near-offset post-stack data image the general features of both the overburden and reservoir units. More importantly, the results from this study indicate that integrated seismic and hydromechanical modelling can help constrain time-lapse uncertainty and hence reduce risk due to fluid extraction and injection.

Time-dependent structural transformation analysis to high-level Petri net model with active state transition diagram

PubMed Central

2010-01-01

Background With an accumulation of in silico data obtained by simulating large-scale biological networks, a new interest of research is emerging for elucidating how living organism functions over time in cells. Investigating the dynamic features of current computational models promises a deeper understanding of complex cellular processes. This leads us to develop a method that utilizes structural properties of the model over all simulation time steps. Further, user-friendly overviews of dynamic behaviors can be considered to provide a great help in understanding the variations of system mechanisms. Results We propose a novel method for constructing and analyzing a so-called active state transition diagram (ASTD) by using time-course simulation data of a high-level Petri net. Our method includes two new algorithms. The first algorithm extracts a series of subnets (called temporal subnets) reflecting biological components contributing to the dynamics, while retaining positive mathematical qualities. The second one creates an ASTD composed of unique temporal subnets. ASTD provides users with concise information allowing them to grasp and trace how a key regulatory subnet and/or a network changes with time. The applicability of our method is demonstrated by the analysis of the underlying model for circadian rhythms in Drosophila. Conclusions Building ASTD is a useful means to convert a hybrid model dealing with discrete, continuous and more complicated events to finite time-dependent states. Based on ASTD, various analytical approaches can be applied to obtain new insights into not only systematic mechanisms but also dynamics. PMID:20356411

Phase-Space Detection of Cyber Events

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

Hernandez Jimenez, Jarilyn M; Ferber, Aaron E; Prowell, Stacy J

Energy Delivery Systems (EDS) are a network of processes that produce, transfer and distribute energy. EDS are increasingly dependent on networked computing assets, as are many Industrial Control Systems. Consequently, cyber-attacks pose a real and pertinent threat, as evidenced by Stuxnet, Shamoon and Dragonfly. Hence, there is a critical need for novel methods to detect, prevent, and mitigate effects of such attacks. To detect cyber-attacks in EDS, we developed a framework for gathering and analyzing timing data that involves establishing a baseline execution profile and then capturing the effect of perturbations in the state from injecting various malware. The datamore » analysis was based on nonlinear dynamics and graph theory to improve detection of anomalous events in cyber applications. The goal was the extraction of changing dynamics or anomalous activity in the underlying computer system. Takens' theorem in nonlinear dynamics allows reconstruction of topologically invariant, time-delay-embedding states from the computer data in a sufficiently high-dimensional space. The resultant dynamical states were nodes, and the state-to-state transitions were links in a mathematical graph. Alternatively, sequential tabulation of executing instructions provides the nodes with corresponding instruction-to-instruction links. Graph theorems guarantee graph-invariant measures to quantify the dynamical changes in the running applications. Results showed a successful detection of cyber events.« less

Topological Principles of Control in Dynamical Networks

NASA Astrophysics Data System (ADS)

Kim, Jason; Pasqualetti, Fabio; Bassett, Danielle

Networked biological systems, such as the brain, feature complex patterns of interactions. To predict and correct the dynamic behavior of such systems, it is imperative to understand how the underlying topological structure affects and limits the function of the system. Here, we use network control theory to extract topological features that favor or prevent network controllability, and to understand the network-wide effect of external stimuli on large-scale brain systems. Specifically, we treat each brain region as a dynamic entity with real-valued state, and model the time evolution of all interconnected regions using linear, time-invariant dynamics. We propose a simplified feed-forward scheme where the effect of upstream regions (drivers) on the connected downstream regions (non-drivers) is characterized in closed-form. Leveraging this characterization of the simplified model, we derive topological features that predict the controllability properties of non-simplified networks. We show analytically and numerically that these predictors are accurate across a large range of parameters. Among other contributions, our analysis shows that heterogeneity in the network weights facilitate controllability, and allows us to implement targeted interventions that profoundly improve controllability. By assuming an underlying dynamical mechanism, we are able to understand the complex topology of networked biological systems in a functionally meaningful way.

Monitoring and characterizing natural hazards with satellite InSAR imagery

USGS Publications Warehouse

Lu, Zhong; Zhang, Jixian; Zhang, Yonghong; Dzurisin, Daniel

2010-01-01

Interferometric synthetic aperture radar (InSAR) provides an all-weather imaging capability for measuring ground-surface deformation and inferring changes in land surface characteristics. InSAR enables scientists to monitor and characterize hazards posed by volcanic, seismic, and hydrogeologic processes, by landslides and wildfires, and by human activities such as mining and fluid extraction or injection. Measuring how a volcano’s surface deforms before, during, and after eruptions provides essential information about magma dynamics and a basis for mitigating volcanic hazards. Measuring spatial and temporal patterns of surface deformation in seismically active regions is extraordinarily useful for understanding rupture dynamics and estimating seismic risks. Measuring how landslides develop and activate is a prerequisite to minimizing associated hazards. Mapping surface subsidence or uplift related to extraction or injection of fluids during exploitation of groundwater aquifers or petroleum reservoirs provides fundamental data on aquifer or reservoir properties and improves our ability to mitigate undesired consequences. Monitoring dynamic water-level changes in wetlands improves hydrological modeling predictions and the assessment of future flood impacts. In addition, InSAR imagery can provide near-real-time estimates of fire scar extents and fire severity for wildfire management and control. All-weather satellite radar imagery is critical for studying various natural processes and is playing an increasingly important role in understanding and forecasting natural hazards.

Development of Carbon Nanotube-Polyamide Nanocomposite-based Stir Bar Sorptive Extraction Coupled to HPLC-UV Applying Response Surface Methodology for the Analysis of Bisphenol A in Aqueous Samples.

PubMed

Ayazi, Z; Matin, A A

2016-11-01

A novel nanocomposite based on reinforcing of multiwalled carbon nanotubes in polyamide (PA) was prepared by solvent exchange method as stir bar coating. The morphology and surface characteristic of PA and CNT/PA coated stir bars were investigated using scanning electron microscopy. The stir bar coated by CNT/PA nanocomposite was used as an extraction device for stir bar sorptive extraction of bisphenol A from aqueous samples followed by high performance liquid chromatography-UV detection. The effect of CNTs doping level and oxidation of CNTs on the extraction capability of the coating was investigated. Response surface methodology applying central composite design was used for modeling and optimization of important factors influencing the extraction and desorption processes including extraction time, salt and methanol content, desorption solvent, its volume and desorption time. Limit of detection and linear dynamic range of the method were 0.3 ng mL -1 and 1-10 ng mL -1 , respectively. The method precision (RSD%) with four replicate determinations was 4.9% for distilled water at the concentration level of 10 ng mL -1 The obtained RSD% for reproducibility of stir bars was 7.4%. The developed method was successfully applied to the bottled mineral water samples, while the relative recoveries (RR%) were obtained to be in the range of 92.0-101.9%. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Preconcentration of Trace Neonicotinoid Insecticide Residues Using Vortex-Assisted Dispersive Micro Solid-Phase Extraction with Montmorillonite as an Efficient Sorbent.

PubMed

Moyakao, Khwankaew; Santaladchaiyakit, Yanawath; Srijaranai, Supalax; Vichapong, Jitlada

2018-04-11

In this work, we investigated montmorillonite for adsorption of neonicotinoid insecticides in vortex-assisted dispersive micro-solid phase extraction (VA-d-μ-SPE). High-performance liquid chromatography with photodiode array detection was used for quantification and determination of neonicotinoid insecticide residues, including thiamethoxam, clothianidin, imidacloprid, acetamiprid, and thiacloprid. In this method, the solid sorbent was dispersed into the aqueous sample solution and vortex agitation was performed to accelerate the extraction process. Finally, the solution was filtered from the solid sorbent with a membrane filter. The parameters affecting the extraction efficiency of the proposed method were optimized, such as amount of sorbent, sample volume, salt addition, type and volume of extraction solvent, and vortex time. The adsorbing results show that montmorillonite could be reused at least 4 times and be used as an effective adsorbent for rapid extraction/preconcentration of neonicotinoid insecticide residues. Under optimum conditions, linear dynamic ranges were achieved between 0.5 and 1000 ng mL -1 with a correlation of determination ( R² ) greater than 0.99. Limit of detection (LOD) ranged from 0.005 to 0.065 ng mL -1 , while limit of quantification (LOQ) ranged from 0.008 to 0.263 ng mL -1 . The enrichment factor (EF) ranged from 8 to 176-fold. The results demonstrated that the proposed method not only provided a more simple and sensitive method, but also can be used as a powerful alternative method for the simultaneous determination of insecticide residues in natural surface water and fruit juice samples.

Data-driven Inference and Investigation of Thermosphere Dynamics and Variations

NASA Astrophysics Data System (ADS)

Mehta, P. M.; Linares, R.

2017-12-01

This paper presents a methodology for data-driven inference and investigation of thermosphere dynamics and variations. The approach uses data-driven modal analysis to extract the most energetic modes of variations for neutral thermospheric species using proper orthogonal decomposition, where the time-independent modes or basis represent the dynamics and the time-depedent coefficients or amplitudes represent the model parameters. The data-driven modal analysis approach combined with sparse, discrete observations is used to infer amplitues for the dynamic modes and to calibrate the energy content of the system. In this work, two different data-types, namely the number density measurements from TIMED/GUVI and the mass density measurements from CHAMP/GRACE are simultaneously ingested for an accurate and self-consistent specification of the thermosphere. The assimilation process is achieved with a non-linear least squares solver and allows estimation/tuning of the model parameters or amplitudes rather than the driver. In this work, we use the Naval Research Lab's MSIS model to derive the most energetic modes for six different species, He, O, N2, O2, H, and N. We examine the dominant drivers of variations for helium in MSIS and observe that seasonal latitudinal variation accounts for about 80% of the dynamic energy with a strong preference of helium for the winter hemisphere. We also observe enhanced helium presence near the poles at GRACE altitudes during periods of low solar activity (Feb 2007) as previously deduced. We will also examine the storm-time response of helium derived from observations. The results are expected to be useful in tuning/calibration of the physics-based models.

Imaging stress redistribution in a high-stress mining environment using induced microseismicity and seismic tomography

NASA Astrophysics Data System (ADS)

Baig, A. M.; Urbancic, T.; Bosman, K.; Smith-Boughner, L.; Viegas, G. F.

2016-12-01

Underground excavation of ore tends to concentrate stress in the pillars of the mines. As the mining progresses, the stress tends to concentrate in these pillars resulting in potentially critical stress conditions that lead to concerns over personnel safety and has implications with regards to efficient and effective extraction criteria. It therefore becomes critical for operations to manage this stress behaviour as the extraction activities progress. In this study, we examine seismicity recorded with a full three-dimensional array consisting of single- and three-component accelerometers and geophones around the extraction volumes; this data formed the basis for characterization of stress variations. Specifically, we present an integrated study of the seismological properties of a sill pillar during the blasting of a stope to characterize how the stress is evolving in the mine. Our results suggest that the seismicity itself reacts to the stress conditions of the mining and through investigation of the source parameters, reveals how these events are being activated. Through consideration of the both the source parameters and the inter-event times and distances, we arrive at a description of the deformation of the reservoir and are able to assess the role of stress during this process. Further resolution of the stress state in the mine is obtained through inversions of moment tensors on the highest-quality microseismic data, and a descriptive analysis of event clustering by space and time to resolve the dynamics of the stress orientations. To corroborate our inferences based on microseismicity, we use blasts recorded around the extraction volume to understand how stress is manifesting itself through P-wave velocity anomalies. We confirm the dynamics of the stress field that we observe from the microseismicity and show the destressing effect of blasting coupled with stress migration through to other parts of the sill pillar.

Using Wavelet Analysis To Assist in Identification of Significant Events in Molecular Dynamics Simulations.

PubMed

Heidari, Zahra; Roe, Daniel R; Galindo-Murillo, Rodrigo; Ghasemi, Jahan B; Cheatham, Thomas E

2016-07-25

Long time scale molecular dynamics (MD) simulations of biological systems are becoming increasingly commonplace due to the availability of both large-scale computational resources and significant advances in the underlying simulation methodologies. Therefore, it is useful to investigate and develop data mining and analysis techniques to quickly and efficiently extract the biologically relevant information from the incredible amount of generated data. Wavelet analysis (WA) is a technique that can quickly reveal significant motions during an MD simulation. Here, the application of WA on well-converged long time scale (tens of μs) simulations of a DNA helix is described. We show how WA combined with a simple clustering method can be used to identify both the physical and temporal locations of events with significant motion in MD trajectories. We also show that WA can not only distinguish and quantify the locations and time scales of significant motions, but by changing the maximum time scale of WA a more complete characterization of these motions can be obtained. This allows motions of different time scales to be identified or ignored as desired.

In Vitro Anti/Pro-oxidant Activities of R. ferruginea Extract and Its Effect on Glioma Cell Viability: Correlation with Phenolic Compound Content and Effects on Membrane Dynamics.

PubMed

Dos Santos, Desirée Magalhães; Rocha, Camila Valesca Jardim; da Silveira, Elita Ferreira; Marinho, Marcelo Augusto Germani; Rodrigues, Marisa Raquel; Silva, Nichole Osti; da Silva Ferreira, Ailton; de Moura, Neusa Fernandes; Darelli, Gabriel Jorge Sagrera; Braganhol, Elizandra; Horn, Ana Paula; de Lima, Vânia Rodrigues

2018-04-01

Rapanea ferruginea antioxidant and antitumoral properties were not explored before in literature. This study aimed to investigate these biological activities for the R. ferruginea leaf extract and correlate them with its phenolic content and influence in biological membrane dynamics. Thus, in this study, anti/pro-oxidative properties of R. ferruginea leaf extract by in vitro DPPH and TBARS assays, with respect to the free radical reducing potential and to its activity regarding membrane free radical-induced peroxidation, respectively. Furthermore, preliminary tests related to the extract effect on in vitro glioma cell viability were also performed. In parallel, the phenolic content was detected by HPLC-DAD and included syringic and trans-cinnamic acids, quercetrin, catechin, quercetin, and gallic acid. In an attempt to correlate the biological activity of R. ferruginea extract and its effect on membrane dynamics, the molecular interaction between the extract and a liposomal model with natural-sourced phospholipids was investigated. Location and changes in vibrational, rotational, and translational lipid motions, as well as in the phase state of liposomes, induced by R. ferruginea extract, were monitored by Fourier-transform infrared spectroscopy, nuclear magnetic resonance, differential scanning calorimetry, and UV-visible spectroscopy. In its free form, the extract showed promising in vitro antioxidant properties. Free-form extract (at 1000µ g/mL) exposure reduced glioma cell in vitro viability in 40%, as evidenced by MTT tests. Pro-oxidant behavior was observed when the extract was loaded into liposomes. A 70.8% cell viability reduction was achieved with 500 µg/mL of liposome-loaded extract. The compounds of R. ferruginea extract ordered liposome interface and disorder edits a polar region. Phenolic content, as well as membrane interaction and modulation may have an important role in the oxidative and antitumoral activities of the R. ferruginea leaf extract.

Untangling Trends and Drivers of Changing River Discharge Along Florida's Gulf Coast

NASA Astrophysics Data System (ADS)

Glodzik, K.; Kaplan, D. A.; Klarenberg, G.

2017-12-01

Along the relatively undeveloped Big Bend coastline of Florida, discharge in many rivers and springs is decreasing. The causes are unclear, though they likely include a combination of groundwater extraction for water supply, climate variability, and altered land use. Saltwater intrusion from altered freshwater influence and sea level rise is causing transformative ecosystem impacts along this flat coastline, including coastal forest die-off and oyster reef collapse. A key uncertainty for understanding river discharge change is predicting discharge from rainfall, since Florida's karstic bedrock stores large amounts of groundwater, which has a long residence time. This study uses Dynamic Factor Analysis (DFA), a multivariate data reduction technique for time series, to find common trends in flow and reveal hydrologic variables affecting flow in eight Big Bend rivers since 1965. The DFA uses annual river flows as response time series, and climate data (annual rainfall and evapotranspiration by watershed) and climatic indices (El Niño Southern Oscillation [ENSO] Index and North Atlantic Oscillation [NAO] Index) as candidate explanatory variables. Significant explanatory variables (one evapotranspiration and three rainfall time series) explained roughly 50% of discharge variation across rivers. Significant trends (representing unexplained variation) were shared among rivers, with geographical grouping of five northern rivers and three southern rivers, along with a strong downward trend affecting six out of eight systems. ENSO and NAO had no significant impact. Advancing knowledge of these dynamics is necessary for forecasting how altered rainfall and temperatures from climate change may impact flows. Improved forecasting is especially important given Florida's reliance on groundwater extraction to support its growing population.

Effects of cockpit lateral stick characteristics on handling qualities and pilot dynamics

NASA Technical Reports Server (NTRS)

Mitchell, David G.; Aponso, Bimal L.; Klyde, David H.

1992-01-01

This report presents the results of analysis of cockpit lateral control feel-system studies. Variations in feel-system natural frequency, damping, and command sensing reference (force and position) were investigated, in combination with variations in the aircraft response characteristics. The primary data for the report were obtained from a flight investigation conducted with a variable-stability airplane, with additional information taken from other flight experiments and ground-based simulations for both airplanes and helicopters . The study consisted of analysis of handling qualities ratings and extraction of open-loop, pilot-vehicle describing functions from sum-of-sines tracking data, including, for a limited subset of these data, the development of pilot models. The study confirms the findings of other investigators that the effects on pilot opinion of cockpit feel-system dynamics are not equivalent to a comparable level of added time delay, and until a more comprehensive set of criteria are developed, it is recommended that feel-system dynamics be considered a delay-inducing element in the aircraft response. The best correlation with time-delay requirements was found when the feel-system dynamics were included in the delay measurements, regardless of the command reference. This is a radical departure from past approaches.

Real-time fusion of endoscopic views with dynamic 3-D cardiac images: a phantom study.

PubMed

Szpala, Stanislaw; Wierzbicki, Marcin; Guiraudon, Gerard; Peters, Terry M

2005-09-01

Minimally invasive robotically assisted cardiac surgical systems currently do not routinely employ 3-D image guidance. However, preoperative magnetic resonance and computed tomography (CT) images have the potential to be used in this role, if appropriately registered with the patient anatomy and animated synchronously with the motion of the actual heart. This paper discusses the fusion of optical images of a beating heart phantom obtained from an optically tracked endoscope, with volumetric images of the phantom created from a dynamic CT dataset. High quality preoperative dynamic CT images are created by first extracting the motion parameters of the heart from the series of temporal frames, and then applying this information to animate a high-quality heart image acquired at end systole. Temporal synchronization of the endoscopic and CT model is achieved by selecting the appropriate CT image from the dynamic set, based on an electrocardiographic trigger signal. The spatial error between the optical and virtual images is 1.4 +/- 1.1 mm, while the time discrepancy is typically 50-100 ms. Index Terms-Image guidance, image warping, minimally invasive cardiac surgery, virtual endoscopy, virtual reality.

Extraction and Separation Modeling of Orion Test Vehicles with ADAMS Simulation

NASA Technical Reports Server (NTRS)

Fraire, Usbaldo, Jr.; Anderson, Keith; Cuthbert, Peter A.

2013-01-01

The Capsule Parachute Assembly System (CPAS) project has increased efforts to demonstrate the performance of fully integrated parachute systems at both higher dynamic pressures and in the presence of wake fields using a Parachute Compartment Drop Test Vehicle (PCDTV) and a Parachute Test Vehicle (PTV), respectively. Modeling the extraction and separation events has proven challenging and an understanding of the physics is required to reduce the risk of separation malfunctions. The need for extraction and separation modeling is critical to a successful CPAS test campaign. Current PTV-alone simulations, such as Decelerator System Simulation (DSS), require accurate initial conditions (ICs) drawn from a separation model. Automatic Dynamic Analysis of Mechanical Systems (ADAMS), a Commercial off the Shelf (COTS) tool, was employed to provide insight into the multi-body six degree of freedom (DOF) interaction between parachute test hardware and external and internal forces. Components of the model include a composite extraction parachute, primary vehicle (PTV or PCDTV), platform cradle, a release mechanism, aircraft ramp, and a programmer parachute with attach points. Independent aerodynamic forces were applied to the mated test vehicle/platform cradle and the separated test vehicle and platform cradle. The aero coefficients were determined from real time lookup tables which were functions of both angle of attack ( ) and sideslip ( ). The atmospheric properties were also determined from a real time lookup table characteristic of the Yuma Proving Grounds (YPG) atmosphere relative to the planned test month. Representative geometries were constructed in ADAMS with measured mass properties generated for each independent vehicle. Derived smart separation parameters were included in ADAMS as sensors with defined pitch and pitch rate criteria used to refine inputs to analogous avionics systems for optimal separation conditions. Key design variables were dispersed in a Monte Carlo analysis to provide the maximum expected range of the state variables at programmer deployment to be used as ICs in DSS. Extensive comparisons were made with Decelerator System Simulation Application (DSSA) to validate the mated portion of the ADAMS extraction trajectory. Results of the comparisons improved the fidelity of ADAMS with a ramp pitch profile update from DSSA. Post-test reconstructions resulted in improvements to extraction parachute drag area knock-down factors, extraction line modeling, and the inclusion of ball-to-socket attachments used as a release mechanism on the PTV. Modeling of two Extraction parachutes was based on United States Air Force (USAF) tow test data and integrated into ADAMS for nominal and Monte Carlo trajectory assessments. Video overlay of ADAMS animations and actual C-12 chase plane test videos supported analysis and observation efforts of extraction and separation events. The COTS ADAMS simulation has been integrated with NASA based simulations to provide complete end to end trajectories with a focus on the extraction, separation, and programmer deployment sequence. The flexibility of modifying ADAMS inputs has proven useful for sensitivity studies and extraction/separation modeling efforts. 1

Carrier thermalization dynamics in single zincblende and wurtzite InP Nanowires.

PubMed

Wang, Yuda; Jackson, Howard E; Smith, Leigh M; Burgess, Tim; Paiman, Suriati; Gao, Qiang; Tan, Hark Hoe; Jagadish, Chennupati

2014-12-10

Using transient Rayleigh scattering (TRS) measurements, we obtain photoexcited carrier thermalization dynamics for both zincblende (ZB) and wurtzite (WZ) InP single nanowires (NW) with picosecond resolution. A phenomenological fitting model based on direct band-to-band transition theory is developed to extract the electron-hole-plasma density and temperature as a function of time from TRS measurements of single nanowires, which have complex valence band structures. We find that the thermalization dynamics of hot carriers depends strongly on material (GaAs NW vs InP NW) and less strongly on crystal structure (ZB vs WZ). The thermalization dynamics of ZB and WZ InP NWs are similar. But a comparison of the thermalization dynamics in ZB and WZ InP NWs with ZB GaAs NWs reveals more than an order of magnitude slower relaxation for the InP NWs. We interpret these results as reflecting their distinctive phonon band structures that lead to different hot phonon effects. Knowledge of hot carrier thermalization dynamics is an essential component for effective incorporation of nanowire materials into electronic devices.

Experimental Determination of the Dynamic Hydraulic Transfer Function for the J-2X Oxidizer Turbopump. Part One; Methodology

NASA Technical Reports Server (NTRS)

Zoladz, Tom; Patel, Sandeep; Lee, Erik; Karon, Dave

2011-01-01

An advanced methodology for extracting the hydraulic dynamic pump transfer matrix (Yp) for a cavitating liquid rocket engine turbopump inducer+impeller has been developed. The transfer function is required for integrated vehicle pogo stability analysis as well as optimization of local inducer pumping stability. Laboratory pulsed subscale waterflow test of the J-2X oxygen turbo pump is introduced and our new extraction method applied to the data collected. From accurate measures of pump inlet and discharge perturbational mass flows and pressures, and one-dimensional flow models that represents complete waterflow loop physics, we are able to derive Yp and hence extract the characteristic pump parameters: compliance, pump gain, impedance, mass flow gain. Detailed modeling is necessary to accurately translate instrument plane measurements to the pump inlet and discharge and extract Yp. We present the MSFC Dynamic Lump Parameter Fluid Model Framework and describe critical dynamic component details. We report on fit minimization techniques, cost (fitness) function derivation, and resulting model fits to our experimental data are presented. Comparisons are made to alternate techniques for spatially translating measurement stations to actual pump inlet and discharge.

Connectionist Architectures for Time Series Prediction of Dynamical Systems

NASA Astrophysics Data System (ADS)

Weigend, Andreas Sebastian

We investigate the effectiveness of connectionist networks for predicting the future continuation of temporal sequences. The problem of overfitting, particularly serious for short records of noisy data, is addressed by the method of weight-elimination: a term penalizing network complexity is added to the usual cost function in back-propagation. We describe the dynamics of the procedure and clarify the meaning of the parameters involved. From a Bayesian perspective, the complexity term can be usefully interpreted as an assumption about prior distribution of the weights. We analyze three time series. On the benchmark sunspot series, the networks outperform traditional statistical approaches. We show that the network performance does not deteriorate when there are more input units than needed. In the second example, the notoriously noisy foreign exchange rates series, we pick one weekday and one currency (DM vs. US). Given exchange rate information up to and including a Monday, the task is to predict the rate for the following Tuesday. Weight-elimination manages to extract a significant part of the dynamics and makes the solution interpretable. In the third example, the networks predict the resource utilization of a chaotic computational ecosystem for hundreds of steps forward in time.

A time series analysis of multiple ambient pollutants to investigate the underlying air pollution dynamics and interactions.

PubMed

Yu, Hwa-Lung; Lin, Yuan-Chien; Kuo, Yi-Ming

2015-09-01

Understanding the temporal dynamics and interactions of particulate matter (PM) concentration and composition is important for air quality control. This paper applied a dynamic factor analysis method (DFA) to reveal the underlying mechanisms of nonstationary variations in twelve ambient concentrations of aerosols and gaseous pollutants, and the associations with meteorological factors. This approach can consider the uncertainties and temporal dependences of time series data. The common trends of the yearlong and three selected diurnal variations were obtained to characterize the dominant processes occurring in general and specific scenarios in Taipei during 2009 (i.e., during Asian dust storm (ADS) events, rainfall, and under normal conditions). The results revealed the two distinct yearlong NOx transformation processes, and demonstrated that traffic emissions and photochemical reactions both critically influence diurnal variation, depending upon meteorological conditions. During an ADS event, transboundary transport and distinct weather conditions both influenced the temporal pattern of identified common trends. This study shows the DFA method can effectively extract meaningful latent processes of time series data and provide insights of the dominant associations and interactions in the complex air pollution processes. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Wang, Dong; Tsui, Kwok-Leung

2017-05-01

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

Multiparametric dynamic contrast-enhanced ultrasound imaging of prostate cancer.

PubMed

Wildeboer, Rogier R; Postema, Arnoud W; Demi, Libertario; Kuenen, Maarten P J; Wijkstra, Hessel; Mischi, Massimo

2017-08-01

The aim of this study is to improve the accuracy of dynamic contrast-enhanced ultrasound (DCE-US) for prostate cancer (PCa) localization by means of a multiparametric approach. Thirteen different parameters related to either perfusion or dispersion were extracted pixel-by-pixel from 45 DCE-US recordings in 19 patients referred for radical prostatectomy. Multiparametric maps were retrospectively produced using a Gaussian mixture model algorithm. These were subsequently evaluated on their pixel-wise performance in classifying 43 benign and 42 malignant histopathologically confirmed regions of interest, using a prostate-based leave-one-out procedure. The combination of the spatiotemporal correlation (r), mean transit time (μ), curve skewness (κ), and peak time (PT) yielded an accuracy of 81% ± 11%, which was higher than the best performing single parameters: r (73%), μ (72%), and wash-in time (72%). The negative predictive value increased to 83% ± 16% from 70%, 69% and 67%, respectively. Pixel inclusion based on the confidence level boosted these measures to 90% with half of the pixels excluded, but without disregarding any prostate or region. Our results suggest multiparametric DCE-US analysis might be a useful diagnostic tool for PCa, possibly supporting future targeting of biopsies or therapy. Application in other types of cancer can also be foreseen. • DCE-US can be used to extract both perfusion and dispersion-related parameters. • Multiparametric DCE-US performs better in detecting PCa than single-parametric DCE-US. • Multiparametric DCE-US might become a useful tool for PCa localization.

Detecting brain dynamics during resting state: a tensor based evolutionary clustering approach

NASA Astrophysics Data System (ADS)

Al-sharoa, Esraa; Al-khassaweneh, Mahmood; Aviyente, Selin

2017-08-01

Human brain is a complex network with connections across different regions. Understanding the functional connectivity (FC) of the brain is important both during resting state and task; as disruptions in connectivity patterns are indicators of different psychopathological and neurological diseases. In this work, we study the resting state functional connectivity networks (FCNs) of the brain from fMRI BOLD signals. Recent studies have shown that FCNs are dynamic even during resting state and understanding the temporal dynamics of FCNs is important for differentiating between different conditions. Therefore, it is important to develop algorithms to track the dynamic formation and dissociation of FCNs of the brain during resting state. In this paper, we propose a two step tensor based community detection algorithm to identify and track the brain network community structure across time. First, we introduce an information-theoretic function to reduce the dynamic FCN and identify the time points that are similar topologically to combine them into a tensor. These time points will be used to identify the different FC states. Second, a tensor based spectral clustering approach is developed to identify the community structure of the constructed tensors. The proposed algorithm applies Tucker decomposition to the constructed tensors and extract the orthogonal factor matrices along the connectivity mode to determine the common subspace within each FC state. The detected community structure is summarized and described as FC states. The results illustrate the dynamic structure of resting state networks (RSNs), including the default mode network, somatomotor network, subcortical network and visual network.

Extracting motor synergies from random movements for low-dimensional task-space control of musculoskeletal robots.

PubMed

Fu, Kin Chung Denny; Dalla Libera, Fabio; Ishiguro, Hiroshi

2015-10-08

In the field of human motor control, the motor synergy hypothesis explains how humans simplify body control dimensionality by coordinating groups of muscles, called motor synergies, instead of controlling muscles independently. In most applications of motor synergies to low-dimensional control in robotics, motor synergies are extracted from given optimal control signals. In this paper, we address the problems of how to extract motor synergies without optimal data given, and how to apply motor synergies to achieve low-dimensional task-space tracking control of a human-like robotic arm actuated by redundant muscles, without prior knowledge of the robot. We propose to extract motor synergies from a subset of randomly generated reaching-like movement data. The essence is to first approximate the corresponding optimal control signals, using estimations of the robot's forward dynamics, and to extract the motor synergies subsequently. In order to avoid modeling difficulties, a learning-based control approach is adopted such that control is accomplished via estimations of the robot's inverse dynamics. We present a kernel-based regression formulation to estimate the forward and the inverse dynamics, and a sliding controller in order to cope with estimation error. Numerical evaluations show that the proposed method enables extraction of motor synergies for low-dimensional task-space control.

The life of a meander bend: Connecting shape and dynamics via analysis of a numerical model

NASA Astrophysics Data System (ADS)

Schwenk, Jon; Lanzoni, Stefano; Foufoula-Georgiou, Efi

2015-04-01

Analysis of bend-scale meandering river dynamics is a problem of theoretical and practical interest. This work introduces a method for extracting and analyzing the history of individual meander bends from inception until cutoff (called "atoms") by tracking backward through time the set of two cutoff nodes in numerical meander migration models. Application of this method to a simplified yet physically based model provides access to previously unavailable bend-scale meander dynamics over long times and at high temporal resolutions. We find that before cutoffs, the intrinsic model dynamics invariably simulate a prototypical cutoff atom shape we dub simple. Once perturbations from cutoffs occur, two other archetypal cutoff planform shapes emerge called long and round that are distinguished by a stretching along their long and perpendicular axes, respectively. Three measures of meander migration—growth rate, average migration rate, and centroid migration rate—are introduced to capture the dynamic lives of individual bends and reveal that similar cutoff atom geometries share similar dynamic histories. Specifically, through the lens of the three shape types, simples are seen to have the highest growth and average migration rates, followed by rounds, and finally longs. Using the maximum average migration rate as a metric describing an atom's dynamic past, we show a strong connection between it and two metrics of cutoff geometry. This result suggests both that early formative dynamics may be inferred from static cutoff planforms and that there exists a critical period early in a meander bend's life when its dynamic trajectory is most sensitive to cutoff perturbations. An example of how these results could be applied to Mississippi River oxbow lakes with unknown historic dynamics is shown. The results characterize the underlying model and provide a framework for comparisons against more complex models and observed dynamics.

Miniaturized hollow fibre assisted liquid-phase microextraction and gas chromatography for determination of trace concentration of sufentanil and alfentanil in biological samples.

PubMed

Fakhari, Ali Reza; Tabani, Hadi; Nojavan, Saeed

2013-07-01

A simple and highly sensitive method that involves miniaturized hollow fibre assisted liquid-phase microextraction with gas chromatography-flame ionization detector was developed for the determination of trace concentration of sufentanil and alfentanil in biological samples. These drugs were extracted from 5 ml of aqueous solution with pH 10.0 into an organic extracting solvent (1-octanol) impregnated in the pores and lumen of a hollow fibre. After extraction for a prescribed time, 2.0 µl of the extraction solvent was injected directly in to the GC injection port. Under the optimized conditions, (1-octanol as extracting solvent, stirring rate of 700 rpm, 15% (w/v) salt addition, pH 10.0 and 25 min sampling time at 50 °C) large enrichment factors of 535 and 420 were achieved for sufentanil and alfentanil, respectively. Dynamic linear ranges were in the range of 0.05 to 500 ng/ml for sufentanil and 0.1 to 500 ng/ml for alfentanil. Limits of detection 0.01 and 0.02 ng/ml were obtained for sufentanil and alfentanil, respectively. The percent relative intra-day and inter-day standard deviations were found to be less than 8.4% (n = 5). Finally, this method was successfully applied for the separation, preconcentration and determination of trace concentration of sufentanil and alfentanil in plasma and urine samples. Copyright © 2012 John Wiley & Sons, Ltd.

Thermal energy storage to minimize cost and improve efficiency of a polygeneration district energy system in a real-time electricity market

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

Powell, Kody M.; Kim, Jong Suk; Cole, Wesley J.

2016-10-01

District energy systems can produce low-cost utilities for large energy networks, but can also be a resource for the electric grid by their ability to ramp production or to store thermal energy by responding to real-time market signals. In this work, dynamic optimization exploits the flexibility of thermal energy storage by determining optimal times to store and extract excess energy. This concept is applied to a polygeneration distributed energy system with combined heat and power, district heating, district cooling, and chilled water thermal energy storage. The system is a university campus responsible for meeting the energy needs of tens ofmore » thousands of people. The objective for the dynamic optimization problem is to minimize cost over a 24-h period while meeting multiple loads in real time. The paper presents a novel algorithm to solve this dynamic optimization problem with energy storage by decomposing the problem into multiple static mixed-integer nonlinear programming (MINLP) problems. Another innovative feature of this work is the study of a large, complex energy network which includes the interrelations of a wide variety of energy technologies. Results indicate that a cost savings of 16.5% is realized when the system can participate in the wholesale electricity market.« less

Molecular Dynamics Simulation of Mahkota Dewa (Phaleria Macrocarpa) Extract in Subcritical Water Extraction Process

NASA Astrophysics Data System (ADS)

Hashim, N. A.; Mudalip, S. K. Abdul; Harun, N.; Che Man, R.; Sulaiman, S. Z.; Arshad, Z. I. M.; Shaarani, S. M.

2018-05-01

Mahkota Dewa (Phaleria Macrocarpa), a good source of saponin, flavanoid, polyphenol, alkaloid, and mangiferin has an extensive range of medicinal effects. The intermolecular interactions between solute and solvents such as hydrogen bonding considered as an important factor that affect the extraction of bioactive compounds. In this work, molecular dynamics simulation was performed to elucidate the hydrogen bonding exists between Mahkota Dewa extracts and water during subcritical extraction process. A bioactive compound in the Mahkota Dewa extract, namely mangiferin was selected as a model compound. The simulation was performed at 373 K and 4.0 MPa using COMPASS force field and Ewald summation method available in Material Studio 7.0 simulation package. The radial distribution functions (RDF) between mangiferin and water signify the presence of hydrogen bonding in the extraction process. The simulation of the binary mixture of mangiferin:water shows that strong hydrogen bonding was formed. It is suggested that, the intermolecular interaction between OH2O••HMR4(OH1) has been identified to be responsible for the mangiferin extraction process.

Optical sectioning in wide-field microscopy obtained by dynamic structured light illumination and detection based on a smart pixel detector array.

PubMed

Mitić, Jelena; Anhut, Tiemo; Meier, Matthias; Ducros, Mathieu; Serov, Alexander; Lasser, Theo

2003-05-01

Optical sectioning in wide-field microscopy is achieved by illumination of the object with a continuously moving single-spatial-frequency pattern and detecting the image with a smart pixel detector array. This detector performs an on-chip electronic signal processing that extracts the optically sectioned image. The optically sectioned image is directly observed in real time without any additional postprocessing.

Unsupervised classification of surface defects in wire rod production obtained by eddy current sensors.

PubMed

Saludes-Rodil, Sergio; Baeyens, Enrique; Rodríguez-Juan, Carlos P

2015-04-29

An unsupervised approach to classify surface defects in wire rod manufacturing is developed in this paper. The defects are extracted from an eddy current signal and classified using a clustering technique that uses the dynamic time warping distance as the dissimilarity measure. The new approach has been successfully tested using industrial data. It is shown that it outperforms other classification alternatives, such as the modified Fourier descriptors.

Update: Advancement of Contact Dynamics Modeling for Human Spaceflight Simulation Applications

NASA Technical Reports Server (NTRS)

Brain, Thomas A.; Kovel, Erik B.; MacLean, John R.; Quiocho, Leslie J.

2017-01-01

Pong is a new software tool developed at the NASA Johnson Space Center that advances interference-based geometric contact dynamics based on 3D graphics models. The Pong software consists of three parts: a set of scripts to extract geometric data from 3D graphics models, a contact dynamics engine that provides collision detection and force calculations based on the extracted geometric data, and a set of scripts for visualizing the dynamics response with the 3D graphics models. The contact dynamics engine can be linked with an external multibody dynamics engine to provide an integrated multibody contact dynamics simulation. This paper provides a detailed overview of Pong including the overall approach and modeling capabilities, which encompasses force generation from contact primitives and friction to computational performance. Two specific Pong-based examples of International Space Station applications are discussed, and the related verification and validation using this new tool are also addressed.

Musical structure analysis using similarity matrix and dynamic programming

NASA Astrophysics Data System (ADS)

Shiu, Yu; Jeong, Hong; Kuo, C.-C. Jay

2005-10-01

Automatic music segmentation and structure analysis from audio waveforms based on a three-level hierarchy is examined in this research, where the three-level hierarchy includes notes, measures and parts. The pitch class profile (PCP) feature is first extracted at the note level. Then, a similarity matrix is constructed at the measure level, where a dynamic time warping (DTW) technique is used to enhance the similarity computation by taking the temporal distortion of similar audio segments into account. By processing the similarity matrix, we can obtain a coarse-grain music segmentation result. Finally, dynamic programming is applied to the coarse-grain segments so that a song can be decomposed into several major parts such as intro, verse, chorus, bridge and outro. The performance of the proposed music structure analysis system is demonstrated for pop and rock music.

Gain in computational efficiency by vectorization in the dynamic simulation of multi-body systems

NASA Technical Reports Server (NTRS)

Amirouche, F. M. L.; Shareef, N. H.

1991-01-01

An improved technique for the identification and extraction of the exact quantities associated with the degrees of freedom at the element as well as the flexible body level is presented. It is implemented in the dynamic equations of motions based on the recursive formulation of Kane et al. (1987) and presented in a matrix form, integrating the concepts of strain energy, the finite-element approach, modal analysis, and reduction of equations. This technique eliminates the CPU intensive matrix multiplication operations in the code's hot spots for the dynamic simulation of the interconnected rigid and flexible bodies. A study of a simple robot with flexible links is presented by comparing the execution times on a scalar machine and a vector-processor with and without vector options. Performance figures demonstrating the substantial gains achieved by the technique are plotted.

Insights into the Cell Shape Dynamics of Migrating Dictyostelium discoideum

NASA Astrophysics Data System (ADS)

Driscoll, Meghan; Homan, Tess; McCann, Colin; Parent, Carole; Fourkas, John; Losert, Wolfgang

2010-03-01

Dynamic cell shape is a highly visible manifestation of the interaction between the internal biochemical state of a cell and its external environment. We analyzed the dynamic cell shape of migrating cells using the model system Dictyostelium discoideum. Applying a snake algorithm to experimental movies, we extracted cell boundaries in each frame and followed local boundary motion over long time intervals. Using a local motion measure that corresponds to protrusive/retractive activity, we found that protrusions are intermittent and zig-zag, whereas retractions are more sustained and straight. Correlations of this local motion measure reveal that protrusions appear more localized than retractions. Using a local shape measure, curvature, we also found that small peaks in boundary curvature tend to originate at the front of cells and propagate backwards. We will review the possible cytoskeletal origin of these mechanical waves.

Quantum Quench Dynamics

NASA Astrophysics Data System (ADS)

Mitra, Aditi

2018-03-01

Quench dynamics is an active area of study encompassing condensed matter physics and quantum information, with applications to cold-atomic gases and pump-probe spectroscopy of materials. Recent theoretical progress in studying quantum quenches is reviewed. Quenches in interacting one-dimensional systems as well as systems in higher spatial dimensions are covered. The appearance of nontrivial steady states following a quench in exactly solvable models is discussed, and the stability of these states to perturbations is described. Proper conserving approximations needed to capture the onset of thermalization at long times are outlined. The appearance of universal scaling for quenches near critical points and the role of the renormalization group in capturing the transient regime are reviewed. Finally, the effect of quenches near critical points on the dynamics of entanglement entropy and entanglement statistics is discussed. The extraction of critical exponents from the entanglement statistics is outlined.

Practical limits for reverse engineering of dynamical systems: a statistical analysis of sensitivity and parameter inferability in systems biology models.

PubMed

Erguler, Kamil; Stumpf, Michael P H

2011-05-01

The size and complexity of cellular systems make building predictive models an extremely difficult task. In principle dynamical time-course data can be used to elucidate the structure of the underlying molecular mechanisms, but a central and recurring problem is that many and very different models can be fitted to experimental data, especially when the latter are limited and subject to noise. Even given a model, estimating its parameters remains challenging in real-world systems. Here we present a comprehensive analysis of 180 systems biology models, which allows us to classify the parameters with respect to their contribution to the overall dynamical behaviour of the different systems. Our results reveal candidate elements of control in biochemical pathways that differentially contribute to dynamics. We introduce sensitivity profiles that concisely characterize parameter sensitivity and demonstrate how this can be connected to variability in data. Systematically linking data and model sloppiness allows us to extract features of dynamical systems that determine how well parameters can be estimated from time-course measurements, and associates the extent of data required for parameter inference with the model structure, and also with the global dynamical state of the system. The comprehensive analysis of so many systems biology models reaffirms the inability to estimate precisely most model or kinetic parameters as a generic feature of dynamical systems, and provides safe guidelines for performing better inferences and model predictions in the context of reverse engineering of mathematical models for biological systems.

Role of Equatorial Anomaly in Earthquake time precursive features: A few strong events over West Pacific zone

NASA Astrophysics Data System (ADS)

Devi, Minakshi; Patgiri, S.; Barbara, A. K.; Oyama, Koh-Ichiro; Ryu, K.; Depuev, V.; Depueva, A.

2018-03-01

The earthquake (EQ) time coupling processes between equator-low-mid latitude ionosphere are complex due to inherent dynamical status of each latitudinal zone and qualified geomagnetic roles working in the system. In an attempt to identify such process, the paper presents temporal and latitudinal variations of ionization density (foF2) covering 45°N to 35°S, during a number of earthquake events (M > 5.5). The approaches adopted for extraction of features by the earthquake induced preparatory processes are discussed in the paper through identification of parameters like the 'EQ time modification in density gradient' defined by δ = (foF2 max - foF2 min)/τmm, where τmm - time span (in days) between EQ modified density maximum and minimum, and the Earthquake time Equatorial Anomaly, i.e. EEA, one of the most significant phenomenon which develops even during night time irrespective of epicenter position. Based on the observations, the paper presents the seismic time coupling dynamics through anomaly like manifestations between equator, low and mid latitude ionosphere bringing in the global Total Electron Content (TEC) features as supporting indices.

Biomimetic measurement of allelochemical dynamics in the rhizosphere.

PubMed

Weidenhamer, Jeffrey D

2005-02-01

Polydimethylsiloxane (PDMS) materials were used to quantify levels of the photosynthesis inhibitor sorgoleone in the undisturbed rhizosphere of sorghum plants. The materials used included stir bars coated with PDMS (stir bar sorptive extraction), technical grade optical fiber coated with a thin film of PDMS (matrix-solid phase microextraction), and PDMS tubing. PDMS tubing retained the most sorgoleone. As analyzed by high performance liquid chromatography, amounts of sorgoleone retained on the PDMS materials increased with time. Other materials tested (polyurethane foam plugs, C18 and Tenax disks, and resin capsules) proved less suitable, as they were subject to sometimes extensive penetration by fine root hairs. These results demonstrate the potential for PDMS-based materials to monitor the release of allelochemicals in the undisturbed rhizosphere of allelopathic plants. Unlike extraction procedures that recover all available compounds present in the soil, PDMS functions in a manner more analogous to plant roots in sorbing compounds from soil solution or root exudates. Information on chemical dynamics in the rhizosphere is crucial for evaluating specific hypotheses of allelopathic effects, understanding allelopathic mechanisms, and assessing the importance of allelopathic processes in plant communities.

Carrier-density-dependent recombination dynamics of excitons and electron-hole plasma in m -plane InGaN/GaN quantum wells

NASA Astrophysics Data System (ADS)

Liu, W.; Butté, R.; Dussaigne, A.; Grandjean, N.; Deveaud, B.; Jacopin, G.

2016-11-01

We study the carrier-density-dependent recombination dynamics in m -plane InGaN/GaN multiple quantum wells in the presence of n -type background doping by time-resolved photoluminescence. Based on Fermi's golden rule and Saha's equation, we decompose the radiative recombination channel into an excitonic and an electron-hole pair contribution, and extract the injected carrier-density-dependent bimolecular recombination coefficients. Contrary to the standard electron-hole picture, our results confirm the strong influence of excitons even at room temperature. Indeed, at 300 K, excitons represent up to 63 ± 6% of the photoexcited carriers. In addition, following the Shockley-Read-Hall model, we extract the electron and hole capture rates by deep levels and demonstrate that the increase in the effective lifetime with injected carrier density is due to asymmetric capture rates in presence of an n -type background doping. Thanks to the proper determination of the density-dependent recombination coefficients up to high injection densities, our method provides a way to evaluate the importance of Auger recombination.

Fault detection method for railway wheel flat using an adaptive multiscale morphological filter

NASA Astrophysics Data System (ADS)

Li, Yifan; Zuo, Ming J.; Lin, Jianhui; Liu, Jianxin

2017-02-01

This study explores the capacity of the morphology analysis for railway wheel flat fault detection. A dynamic model of vehicle systems with 56 degrees of freedom was set up along with a wheel flat model to calculate the dynamic responses of axle box. The vehicle axle box vibration signal is complicated because it not only contains the information of wheel defect, but also includes track condition information. Thus, how to extract the influential features of wheels from strong background noise effectively is a typical key issue for railway wheel fault detection. In this paper, an algorithm for adaptive multiscale morphological filtering (AMMF) was proposed, and its effect was evaluated by a simulated signal. And then this algorithm was employed to study the axle box vibration caused by wheel flats, as well as the influence of track irregularity and vehicle running speed on diagnosis results. Finally, the effectiveness of the proposed method was verified by bench testing. Research results demonstrate that the AMMF extracts the influential characteristic of axle box vibration signals effectively and can diagnose wheel flat faults in real time.

OBSERVATIONAL DETECTION OF DRIFT VELOCITY BETWEEN IONIZED AND NEUTRAL SPECIES IN SOLAR PROMINENCES

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

Khomenko, Elena; Collados, Manuel; Díaz, Antonio J., E-mail: khomenko@iac.es, E-mail: mcv@iac.es, E-mail: aj.diaz@uib.es

2016-06-01

We report the detection of differences in the ion and neutral velocities in prominences using high-resolution spectral data obtained in 2012 September at the German Vacuum Tower Telescope (Observatorio del Teide, Tenerife). A time series of scans of a small portion of a solar prominence was obtained simultaneously with high cadence using the lines of two elements with different ionization states, namely, Ca ii 8542 Å and He i 10830 Å. The displacements, widths, and amplitudes of both lines were carefully compared to extract dynamical information about the plasma. Many dynamical features are detected, such as counterstreaming flows, jets, andmore » propagating waves. In all of the cases, we find a very strong correlation between the parameters extracted from the lines of both elements, confirming that both lines trace the same plasma. Nevertheless, we also find short-lived transients where this correlation is lost. These transients are associated with ion-neutral drift velocities of the order of several hundred m s{sup −1}. The patches of non-zero drift velocity show coherence in time–distance diagrams.« less

Dynamic analysis and pattern visualization of forest fires.

PubMed

Lopes, António M; Tenreiro Machado, J A

2014-01-01

This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns.

Dynamic Analysis and Pattern Visualization of Forest Fires

PubMed Central

Lopes, António M.; Tenreiro Machado, J. A.

2014-01-01

This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns. PMID:25137393

Deep liquid-chromatographic purification of uranium extract from technetium

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

Volk, V.; Dvoeglazov, K; Podrezova, L.

The recycling of uranium in the nuclear fuel cycle requires the removal of a number of radioactive and stable impurities like {sup 99}Tc from spent fuels. In order to improve the grade of uranium extract purification from technetium the method of liquid chromatography and the apparatus for its performance have been developed. Process of technetium extraction and concentrating in aqueous solution containing reducing agent has been studied on simulated solutions (U-Tc-HNO{sub 3}-30% TBP-isoparM). The dynamic tests of the method have been carried out on the laboratory unit. Solution of diformyl-hydrazine in nitric acid was used as a stationary phase. Silicamore » gel with specific surface of 186 m{sup 2}/g was used as a carrier of the stationary phase. It is shown that the volume of purified extract increases as the solution temperature increases, concentration of reducing agent increases and extract flow rate decreases. It is established that the technetium content in uranium by this method could achieve a value below 0.3 ppm. Some variants of overload and composition of the stationary phase containing the extracted technetium have been offered and tested. It is defined that the method provides reduction of processing medium-active wastes by more than 10 times during finish refining process. (authors)« less

Green synthesis of silver nanoparticles from aqueous Aegle marmelos leaf extract

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

Jagajjanani Rao, K.; Paria, Santanu, E-mail: santanuparia@yahoo.com

Graphical abstract: Silver nanoparticles capped with polyphenols present in Aegle marmelos leaf extract. Display Omitted Highlights: ► Silver nanoparticles are synthesized using Aegle marmelos leaf extract in aqueous media. ► Reduction reaction is fast and occurs at room temperature. ► The presence of polyphenols acts as in situ capping agent. -- Abstract: Synthesis of nanoparticles by green route is an emerging technique drawing more attention recently because of several advantages over the convention chemical routes. The present study reports one-pot synthesis and in situ stabilization of silver nanoparticles using Aegle marmelos leaf extract. Nanoparticles of almost uniform spherical size (∼60more » nm) were synthesized within ∼25 min reaction time at room temperature. The size of particles depends on the ratio of AgNO{sub 3} and leaf extract. The crystallinity, size, and shape of the nanoparticles were characterized by X-ray diffraction, dynamic light scattering, and scanning electron microscopy respectively. The size stability was attained by the capping effect of polyphenolic tannin compound, procatacheuate in the extract. The capped polyphenols can be removed from the particle surface by simple NaOH/methanol wash. The involvement of phenolic compounds in metal ion reduction and capping were supported by UV–visible spectroscopy, infrared spectroscopy, high performance liquid chromatography, and zeta potential measurements.« less

Feasibility of corona discharge ion mobility spectrometry for direct analysis of samples extracted by dispersive liquid-liquid microextraction.

PubMed

Jafari, Mohammad T; Riahi, Farhad

2014-05-23

The capability of corona discharge ionization ion mobility spectrometry (CD-IMS) for direct analysis of the samples extracted by dispersive liquid-liquid microextraction (DLLME) was investigated and evaluated, for the first time. To that end, an appropriate new injection port was designed and constructed, resulting in possibility of direct injection of the known sample volume, without tedious sample preparation steps (e.g. derivatization, solvent evaporation, and re-solving in another solvent…). Malathion as a test compound was extracted from different matrices by a rapid and convenient DLLME method. The positive ion mobility spectra of the extracted malathion were obtained after direct injection of carbon tetrachloride or methanol solutions. The analyte responses were compared and the statistical results revealed the feasibility of direct analysis of the extracted samples in carbon tetrachloride, resulting in a convenient methodology. The coupled method of DLLME-CD-IMS was exhaustively validated in terms of sensitivity, dynamic range, recovery, and enrichment factor. Finally, various real samples of apple, river and underground water were analyzed, all verifying the feasibility and success of the proposed method for the easy extraction of the analyte using DLLME separation before the direct analysis by CD-IMS. Copyright © 2014 Elsevier B.V. All rights reserved.

Dynamic Pore-scale Reservoir-condition Imaging of Reaction in Carbonates Using Synchrotron Fast Tomography

PubMed Central

Menke, Hannah P.; Andrew, Matthew G.; Vila-Comamala, Joan; Rau, Christoph; Blunt, Martin J.; Bijeljic, Branko

2017-01-01

Underground storage permanence is a major concern for carbon capture and storage. Pumping CO2 into carbonate reservoirs has the potential to dissolve geologic seals and allow CO2 to escape. However, the dissolution processes at reservoir conditions are poorly understood. Thus, time-resolved experiments are needed to observe and predict the nature and rate of dissolution at the pore scale. Synchrotron fast tomography is a method of taking high-resolution time-resolved images of complex pore structures much more quickly than traditional µ-CT. The Diamond Lightsource Pink Beam was used to dynamically image dissolution of limestone in the presence of CO2-saturated brine at reservoir conditions. 100 scans were taken at a 6.1 µm resolution over a period of 2 hours. The images were segmented and the porosity and permeability were measured using image analysis and network extraction. Porosity increased uniformly along the length of the sample; however, the rate of increase of both porosity and permeability slowed at later times. PMID:28287529

Dynamic Pore-scale Reservoir-condition Imaging of Reaction in Carbonates Using Synchrotron Fast Tomography.

PubMed

Menke, Hannah P; Andrew, Matthew G; Vila-Comamala, Joan; Rau, Christoph; Blunt, Martin J; Bijeljic, Branko

2017-02-21

Underground storage permanence is a major concern for carbon capture and storage. Pumping CO2 into carbonate reservoirs has the potential to dissolve geologic seals and allow CO2 to escape. However, the dissolution processes at reservoir conditions are poorly understood. Thus, time-resolved experiments are needed to observe and predict the nature and rate of dissolution at the pore scale. Synchrotron fast tomography is a method of taking high-resolution time-resolved images of complex pore structures much more quickly than traditional µ-CT. The Diamond Lightsource Pink Beam was used to dynamically image dissolution of limestone in the presence of CO2-saturated brine at reservoir conditions. 100 scans were taken at a 6.1 µm resolution over a period of 2 hours. The images were segmented and the porosity and permeability were measured using image analysis and network extraction. Porosity increased uniformly along the length of the sample; however, the rate of increase of both porosity and permeability slowed at later times.

CLUSTERING OF INTERICTAL SPIKES BY DYNAMIC TIME WARPING AND AFFINITY PROPAGATION

PubMed Central

Thomas, John; Jin, Jing; Dauwels, Justin; Cash, Sydney S.; Westover, M. Brandon

2018-01-01

Epilepsy is often associated with the presence of spikes in electroencephalograms (EEGs). The spike waveforms vary vastly among epilepsy patients, and also for the same patient across time. In order to develop semi-automated and automated methods for detecting spikes, it is crucial to obtain a better understanding of the various spike shapes. In this paper, we develop several approaches to extract exemplars of spikes. We generate spike exemplars by applying clustering algorithms to a database of spikes from 12 patients. As similarity measures for clustering, we consider the Euclidean distance and Dynamic Time Warping (DTW). We assess two clustering algorithms, namely, K-means clustering and affinity propagation. The clustering methods are compared based on the mean squared error, and the similarity measures are assessed based on the number of generated spike clusters. Affinity propagation with DTW is shown to be the best combination for clustering epileptic spikes, since it generates fewer spike templates and does not require to pre-specify the number of spike templates. PMID:29527130

n-SIFT: n-dimensional scale invariant feature transform.

PubMed

Cheung, Warren; Hamarneh, Ghassan

2009-09-01

We propose the n-dimensional scale invariant feature transform (n-SIFT) method for extracting and matching salient features from scalar images of arbitrary dimensionality, and compare this method's performance to other related features. The proposed features extend the concepts used for 2-D scalar images in the computer vision SIFT technique for extracting and matching distinctive scale invariant features. We apply the features to images of arbitrary dimensionality through the use of hyperspherical coordinates for gradients and multidimensional histograms to create the feature vectors. We analyze the performance of a fully automated multimodal medical image matching technique based on these features, and successfully apply the technique to determine accurate feature point correspondence between pairs of 3-D MRI images and dynamic 3D + time CT data.

Determination of the scalar polarizabilities of the proton using beam asymmetry $$\\Sigma_{3}$$ in Compton scattering

DOE PAGES

Sokhoyan, V.; Downie, E. J.; Mornacchi, E.; ...

2017-01-01

The scalar dipole polarizabilities, α E1 and β M1, are fundamental properties related to the internal dynamics of the nucleon. The currently accepted values of the proton polarizabilities were determined by fitting to unpolarized proton Compton scattering cross section data. The measurement of the beam asymmetry Σ 3 in a certain kinematical range provides an alternative approach to the extraction of the scalar polarizabilities. At the Mainz Microtron (MAMI) the beam asymmetry was measured for Compton scattering below pion photoproduction threshold for the first time. Finally, the results are compared with model calculations and the influence of the experimental datamore » on the extraction of the scalar polarizabilities is determined.« less

Operando Lithium Dynamics in the Li-Rich Layered Oxide Cathode Material via Neutron Diffraction

DOE PAGES

Liu, Haodong; An, Ke; Venkatachalam, Subramanian; ...

2016-04-06

Neutron diffraction under operando battery cycling is used to study the lithium and oxygen dynamics of high Li-rich Li(Li x/3Ni (3/8-3x/8)Co (1/4-x/4)Mn (3/8+7x/24)O 2 (x = 0.6, HLR) and low Li-rich Li(Li x/3Ni (1/3-x/3)Co (1/3-x/3)Mn(1/3+x/3)O 2 (x = 0.24, LLR) compounds that exhibit different degrees of oxygen activation at high voltage. The measured lattice parameter changes and oxygen position show largely contrasting changes for the two cathodes where the LLR exhibits larger movement of oxygen and lattice contractions in comparison to the HLR that maintains relatively constant lattice parameters and oxygen position during the high voltage plateau until the endmore » of charge. Density functional theory calculations show the presence of oxygen vacancy during the high voltage plateau; changes in the lattice parameters and oxygen position are consistent with experimental observations. Lithium migration kinetics for the Li-rich material is observed under operando conditions for the first time to reveal the rate of lithium extraction from the lithium layer, and transition metal layer is related to the different charge and discharge characteristics. At the beginning of charging, the lithium extraction predominately occurs within the lithium layer. The lithium extraction from the lithium layer slows down and extraction from the transition metal layer evolves at a faster rate once the high voltage plateau is reached.« less

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

Islam, Md. Shafiqul, E-mail: shafique@eng.ukm.my; Hannan, M.A., E-mail: hannan@eng.ukm.my; Basri, Hassan

Highlights: • Solid waste bin level detection using Dynamic Time Warping (DTW). • Gabor wavelet filter is used to extract the solid waste image features. • Multi-Layer Perceptron classifier network is used for bin image classification. • The classification performance evaluated by ROC curve analysis. - Abstract: The increasing requirement for Solid Waste Management (SWM) has become a significant challenge for municipal authorities. A number of integrated systems and methods have introduced to overcome this challenge. Many researchers have aimed to develop an ideal SWM system, including approaches involving software-based routing, Geographic Information Systems (GIS), Radio-frequency Identification (RFID), or sensormore » intelligent bins. Image processing solutions for the Solid Waste (SW) collection have also been developed; however, during capturing the bin image, it is challenging to position the camera for getting a bin area centralized image. As yet, there is no ideal system which can correctly estimate the amount of SW. This paper briefly discusses an efficient image processing solution to overcome these problems. Dynamic Time Warping (DTW) was used for detecting and cropping the bin area and Gabor wavelet (GW) was introduced for feature extraction of the waste bin image. Image features were used to train the classifier. A Multi-Layer Perceptron (MLP) classifier was used to classify the waste bin level and estimate the amount of waste inside the bin. The area under the Receiver Operating Characteristic (ROC) curves was used to statistically evaluate classifier performance. The results of this developed system are comparable to previous image processing based system. The system demonstration using DTW with GW for feature extraction and an MLP classifier led to promising results with respect to the accuracy of waste level estimation (98.50%). The application can be used to optimize the routing of waste collection based on the estimated bin level.« less

Racial Variations in Interfacial Behavior of Lipids Extracted from Worn Soft Contact Lenses

PubMed Central

Svitova, Tatyana F.; Lin, Meng C.

2014-01-01

Purpose To explore interfacial behaviors and effect of temperature and dilatation on dynamic properties of multilayered human tear lipids extracted from silicone hydrogel (SiH) lenses worn by asymptomatic Asian and Caucasian subjects. Methods Interfacial properties of lipids extracted from Focus® N&D lenses worn by 14 subjects continuously for 1 month were studied. The lipids were deposited on an air bubble immersed in a model tear electrolytes (MTE) solution to form 100 ± 20 nm-thick films. Surface pressure was recorded during slow expansion/contraction cycles to evaluate compressibility and hysteresis of lipid films. Films were also subjected to fast step-strain dilatations at temperatures 22°–45° C for their visco-elastic properties assessment. Results Iso-cycles for Asian and Caucasian lipids were similar at low surface pressures, but had distinctly different compressibility and hysteresis at dynamic pressures exceeding 30 mN/m. Rheological parameters of reconstituted lipids were also dissimilar between Asian and Caucasian. The elastic modulusE∞ for Caucasian lipids was 1.5 times higher than that for Asian lipids, whereas relaxation time (t) was on average 1.3 times higher for Asian. No significant changes were observed in rheological properties of both Asian and Caucasian lipids when temperature increased from 22.0° to 36.5° C. However, for Caucasian lipids, E∞ reduced considerably at temperatures above 42.0° C, while t remained unchanged. For Asian lipids, both E∞ and t started to decline as temperature increased to 38° C and higher. Conclusions Higher elastic modulus of Caucasian lipids and elasticity threshold at certain deformations indicate stronger structure and intermolecular interactions as compared with more viscous Asian lipids. The differences in interfacial behaviors between Asian and Caucasian lipids may be associated with the differences in their chemical compositions. PMID:24270592

Method to investigate temporal dynamics of ganglion and other retinal cells in the living human eye

NASA Astrophysics Data System (ADS)

Kurokawa, Kazuhiro; Liu, Zhuolin; Crowell, James; Zhang, Furu; Miller, Donald T.

2018-02-01

The inner retina is critical for visual processing, but much remains unknown about its neural circuitry and vulnerability to disease. A major bottleneck has been our inability to observe the structure and function of the cells composing these retinal layers in the living human eye. Here, we present a noninvasive method to observe both structural and functional information. Adaptive optics optical coherence tomography (AO-OCT) is used to resolve the inner retinal cells in all three dimensions and novel post processing algorithms are applied to extract structure and physiology down to the cellular level. AO-OCT captured the 3D mosaic of individual ganglion cell somas, retinal nerve fiber bundles of micron caliber, and microglial cells, all in exquisite detail. Time correlation analysis of the AO-OCT videos revealed notable temporal differences between the principal layers of the inner retina. The GC layer was more dynamic than the nerve fiber and inner plexiform layers. At the cellular level, we applied a customized correlation method to individual GCL somas, and found a mean time constant of activity of 0.57 s and spread of +/-0.1 s suggesting a range of physiological dynamics even in the same cell type. Extending our method to slower dynamics (from minutes to one year), time-lapse imaging and temporal speckle contrast revealed appendage and soma motion of resting microglial cells at the retinal surface.

Vibrational dynamics of adsorbed molecules under conditions of photodesorption: pump-probe SFG spectra of CO/Pt(111).

PubMed

Fournier, Frédéric; Zheng, Wanquan; Carrez, Serge; Dubost, Henri; Bourguignon, Bernard

2004-09-08

Interaction of CO adsorbed on Pt(111) with electrons and phonons is studied experimentally by means of a pump-probe experiment where CO is probed by IR + visible sum frequency generation under a pump laser intensity that allows photodesorption. Vibrational spectra of CO internal stretch are obtained as a function of pump-probe delay. A two-temperature and anharmonic coupling model is used to extract from the spectra the real time variations of CO peak frequency and dephasing time. The main conclusions are the following: (i) The CO stretch is perturbed by two low-frequency modes, assigned to frustrated rotation and frustrated translation. (ii) The frustrated rotation is directly coupled to electrons photoexcited in Pt(111) by the pump laser. (iii) There is no evidence of Pt-CO stretch excitation in the spectra. The implications for the photodesorption dynamics are discussed. Copyright 2004 American Institute of Physics

Vibrational dynamics of adsorbed molecules under conditions of photodesorption: Pump-probe SFG spectra of CO/Pt(111)

NASA Astrophysics Data System (ADS)

Fournier, Frédéric; Zheng, Wanquan; Carrez, Serge; Dubost, Henri; Bourguignon, Bernard

2004-09-01

Interaction of CO adsorbed on Pt(111) with electrons and phonons is studied experimentally by means of a pump-probe experiment where CO is probed by IR+visible sum frequency generation under a pump laser intensity that allows photodesorption. Vibrational spectra of CO internal stretch are obtained as a function of pump-probe delay. A two-temperature and anharmonic coupling model is used to extract from the spectra the real time variations of CO peak frequency and dephasing time. The main conclusions are the following: (i) The CO stretch is perturbed by two low-frequency modes, assigned to frustrated rotation and frustrated translation. (ii) The frustrated rotation is directly coupled to electrons photoexcited in Pt(111) by the pump laser. (iii) There is no evidence of Pt-CO stretch excitation in the spectra. The implications for the photodesorption dynamics are discussed.

Experimental study of non-stationary operation of a dual-wavelength passively mode-locked fibre ring laser

NASA Astrophysics Data System (ADS)

Ibarra Villalón, H. E.; Pottiez, O.; Bracamontes Rodriguez, Y. E.; Lauterio-Cruz, J. P.; Gomez Vieyra, A.

2018-06-01

In this paper, we report an experimental study of different dynamics taking place in a 20 m long passively mode-locked fibre ring laser in dual-wavelength operation, at 1531 nm and 1558 nm. For different polarization adjustments, self-starting mode locking is obtained, yielding different types of emission: bunches of solitons in quasi-stationary regime, a compact bunch of solitons coexisting with loose bunches of solitons, a noise-like pulse coexisting with bunches of solitons and a noise-like pulse displaying quasi-periodic fluctuations. In each regime, we extract information on the pulse dynamics from measurements of the temporal profile evolution using a 16 GHz real-time oscilloscope and, at the same time, we propose a phase-space diagram representation of the intensity versus the energy of the temporal profile of the pulses; the latter allows evidencing patterns that could not be identified using conventional measurement techniques.

Population shuffling between ground and high energy excited states

PubMed Central

Sabo, T Michael; Trent, John O; Lee, Donghan

2015-01-01

Stochastic processes powered by thermal energy lead to protein motions traversing time-scales from picoseconds to seconds. Fundamental to protein functionality is the utilization of these dynamics for tasks such as catalysis, folding, and allostery. A hierarchy of motion is hypothesized to connect and synergize fast and slow dynamics toward performing these essential activities. Population shuffling predicts a “top-down” temporal hierarchy, where slow time-scale conformational interconversion leads to a shuffling of the free energy landscape for fast time-scale events. Until now, population shuffling was only applied to interconverting ground states. Here, we extend the framework of population shuffling to be applicable for a system interconverting between low energy ground and high energy excited states, such as the SH3 domain mutants G48M and A39V/N53P/V55L from the Fyn tyrosine kinase, providing another tool for accessing the structural dynamics of high energy excited states. Our results indicate that the higher energy gauche− rotameric state for the leucine χ2 dihedral angle contributes significantly to the distribution of rotameric states in both the major and minor forms of the SH3 domain. These findings are corroborated with unrestrained molecular dynamics (MD) simulations on both the major and minor states of the SH3 domain demonstrating high correlations between experimental and back-calculated leucine χ2 rotameric populations. Taken together, we demonstrate how fast time-scale rotameric side-chain population distributions can be extracted from slow time-scale conformational exchange data further extending the scope and the applicability of the population shuffling model. PMID:26316263

Population shuffling between ground and high energy excited states.

PubMed

Sabo, T Michael; Trent, John O; Lee, Donghan

2015-11-01

Stochastic processes powered by thermal energy lead to protein motions traversing time-scales from picoseconds to seconds. Fundamental to protein functionality is the utilization of these dynamics for tasks such as catalysis, folding, and allostery. A hierarchy of motion is hypothesized to connect and synergize fast and slow dynamics toward performing these essential activities. Population shuffling predicts a "top-down" temporal hierarchy, where slow time-scale conformational interconversion leads to a shuffling of the free energy landscape for fast time-scale events. Until now, population shuffling was only applied to interconverting ground states. Here, we extend the framework of population shuffling to be applicable for a system interconverting between low energy ground and high energy excited states, such as the SH3 domain mutants G48M and A39V/N53P/V55L from the Fyn tyrosine kinase, providing another tool for accessing the structural dynamics of high energy excited states. Our results indicate that the higher energy gauche - rotameric state for the leucine χ2 dihedral angle contributes significantly to the distribution of rotameric states in both the major and minor forms of the SH3 domain. These findings are corroborated with unrestrained molecular dynamics (MD) simulations on both the major and minor states of the SH3 domain demonstrating high correlations between experimental and back-calculated leucine χ2 rotameric populations. Taken together, we demonstrate how fast time-scale rotameric side-chain population distributions can be extracted from slow time-scale conformational exchange data further extending the scope and the applicability of the population shuffling model. © 2015 The Protein Society.

Vortex-Assisted Dispersive Micro-Solid Phase Extraction Using CTAB-Modified Zeolite NaY Sorbent Coupled with HPLC for the Determination of Carbamate Insecticides.

PubMed

Salisaeng, Pawina; Arnnok, Prapha; Patdhanagul, Nopbhasinthu; Burakham, Rodjana

2016-03-16

A vortex-assisted dispersive micro-solid phase extraction (VA-D-μ-SPE) based on cetyltrimethylammonium bromide (CTAB)-modified zeolite NaY was developed for preconcentration of carbamate pesticides in fruits, vegetables, and natural surface water prior to analysis by high performance liquid chromatography with photodiode array detection. The small amounts of solid sorbent were dispersed in a sample solution, and extraction occurred by adsorption in a short time, which was accelerated by vortex agitation. Finally, the sorbents were filtered from the solution, and the analytes were subsequently desorbed using an appropriate solvent. Parameters affecting the VA-D-μ-SPE performance including sorbent amount, sample volume, desorption solvent ,and vortex time were optimized. Under the optimum condition, linear dynamic ranges were achieved between 0.004-24.000 mg kg(-1) (R(2) > 0.9946). The limits of detection (LODs) ranged from 0.004-4.000 mg kg(-1). The applicability of the developed procedure was successfully evaluated by the determination of the carbamate residues in fruits (dragon fruit, rambutan, and watermelon), vegetables (cabbage, cauliflower, and cucumber), and natural surface water.

Incoherent optical generalized Hough transform: pattern recognition and feature extraction applications

NASA Astrophysics Data System (ADS)

Fernández, Ariel; Ferrari, José A.

2017-05-01

Pattern recognition and feature extraction are image processing applications of great interest in defect inspection and robot vision among others. In comparison to purely digital methods, the attractiveness of optical processors for pattern recognition lies in their highly parallel operation and real-time processing capability. This work presents an optical implementation of the generalized Hough transform (GHT), a well-established technique for recognition of geometrical features in binary images. Detection of a geometric feature under the GHT is accomplished by mapping the original image to an accumulator space; the large computational requirements for this mapping make the optical implementation an attractive alternative to digital-only methods. We explore an optical setup where the transformation is obtained, and the size and orientation parameters can be controlled, allowing for dynamic scale and orientation-variant pattern recognition. A compact system for the above purposes results from the use of an electrically tunable lens for scale control and a pupil mask implemented on a high-contrast spatial light modulator for orientation/shape variation of the template. Real-time can also be achieved. In addition, by thresholding of the GHT and optically inverse transforming, the previously detected features of interest can be extracted.

Extracting Temporal and Spatial Distributions Information about Algal Glooms Based on Multitemporal Modis

NASA Astrophysics Data System (ADS)

Chunguang, L.; Qingjiu, T.

2012-07-01

Based on MODIS remote sensing data, method and technology to extraction the time and space distribution information of algae bloom is studied and established. The dynamic feature of time and space in Taihu Lake from 2009 to 2011 can be obtained by extracted method. Variation of cyanobacterial bloom in the Taihu Lake is analyzed and discussed. The algae bloom frequency index (AFI) and algae bloom sustainability index (ASI) is important criterion which can show the interannual and inter-monthly variation in the whole area or the subregion of Taihu Lake. Utilizing the AFI and ASI from 2009 to 2011, it found some phenomena that: the booming frequency decreased from the north and west to the East and South of Taihu Lake. The annual month algae bloom variation of AFI reflect the booming existing twin peaks in the high shock level and lag trend in general. In the subregion statistics, the IBD and ASI in 2011 show the abnormal condition in the border between the Gongshan Bay and Central Lake. The date is obvious earlier than that on the same subregion in previous years and that on others subregion in the same year.

A robust and efficient method for the extraction of plant extracellular surface lipids as applied to the analysis of silks and seedling leaves of maize

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

Loneman, Derek M.; Peddicord, Layton; Al-Rashid, Amani

Aerial plant organs possess a diverse array of extracellular surface lipids, including both non-polar and amphipathic constituents that collectively provide a primary line of defense against environmental stressors. Extracellular surface lipids on the stigmatic silks of maize are composed primarily of saturated and unsaturated linear hydrocarbons, as well as fatty acids, and aldehydes. To efficiently extract lipids of differing polarities from maize silks, five solvent systems (hexanes; hexanes:diethyl ether (95:5); hexanes:diethyl ether (90:10); chloroform:hexanes (1:1) and chloroform) were tested by immersing fresh silks in solvent for different extraction times. Surface lipid recovery and the relative composition of individual constituents weremore » impacted to varying degrees depending on solvent choice and duration of extraction. Analyses were performed using both silks and leaves to demonstrate the utility of the solvent- and time-optimized protocol in comparison to extraction with the commonly used chloroform solvent. Overall, the preferred solvent system was identified as hexanes:diethyl ether (90:10), based on its effectiveness in extracting surface hydrocarbons and fatty acids as well as its reduced propensity to extract presumed internal fatty acids. Metabolite profiling of wildtype and glossy1 seedlings, which are impaired in surface lipid biosynthesis, demonstrated the ability of the preferred solvent to extract extracellular surface lipids rich in amphipathic compounds (aldehydes and alcohols). In addition to the expected deficiencies in dotriacontanal and dotriacontan-1-ol for gl1 seedlings, an unexpected increase in fatty acid recovery was observed in gl1 seedlings extracted in chloroform, suggesting that chloro-form extracts lipids from internal tissues of gl1 seedlings. This highlights the importance of extraction method when evaluating mutants that have altered cuticular lipid compositions. Lastly, metabolite profiling of silks from maize inbreds B73 and Mo17, exposed to different environments and harvested at different ages, revealed differences in hydrocarbon and fatty acid composition, demonstrating the dynamic nature of surface lipid accumulation on silks.« less

A robust and efficient method for the extraction of plant extracellular surface lipids as applied to the analysis of silks and seedling leaves of maize

DOE PAGES

Loneman, Derek M.; Peddicord, Layton; Al-Rashid, Amani; ...

2017-07-11

Aerial plant organs possess a diverse array of extracellular surface lipids, including both non-polar and amphipathic constituents that collectively provide a primary line of defense against environmental stressors. Extracellular surface lipids on the stigmatic silks of maize are composed primarily of saturated and unsaturated linear hydrocarbons, as well as fatty acids, and aldehydes. To efficiently extract lipids of differing polarities from maize silks, five solvent systems (hexanes; hexanes:diethyl ether (95:5); hexanes:diethyl ether (90:10); chloroform:hexanes (1:1) and chloroform) were tested by immersing fresh silks in solvent for different extraction times. Surface lipid recovery and the relative composition of individual constituents weremore » impacted to varying degrees depending on solvent choice and duration of extraction. Analyses were performed using both silks and leaves to demonstrate the utility of the solvent- and time-optimized protocol in comparison to extraction with the commonly used chloroform solvent. Overall, the preferred solvent system was identified as hexanes:diethyl ether (90:10), based on its effectiveness in extracting surface hydrocarbons and fatty acids as well as its reduced propensity to extract presumed internal fatty acids. Metabolite profiling of wildtype and glossy1 seedlings, which are impaired in surface lipid biosynthesis, demonstrated the ability of the preferred solvent to extract extracellular surface lipids rich in amphipathic compounds (aldehydes and alcohols). In addition to the expected deficiencies in dotriacontanal and dotriacontan-1-ol for gl1 seedlings, an unexpected increase in fatty acid recovery was observed in gl1 seedlings extracted in chloroform, suggesting that chloro-form extracts lipids from internal tissues of gl1 seedlings. This highlights the importance of extraction method when evaluating mutants that have altered cuticular lipid compositions. Lastly, metabolite profiling of silks from maize inbreds B73 and Mo17, exposed to different environments and harvested at different ages, revealed differences in hydrocarbon and fatty acid composition, demonstrating the dynamic nature of surface lipid accumulation on silks.« less

Using Dynamic Multi-Task Non-Negative Matrix Factorization to Detect the Evolution of User Preferences in Collaborative Filtering

PubMed Central

Ju, Bin; Qian, Yuntao; Ye, Minchao; Ni, Rong; Zhu, Chenxi

2015-01-01

Predicting what items will be selected by a target user in the future is an important function for recommendation systems. Matrix factorization techniques have been shown to achieve good performance on temporal rating-type data, but little is known about temporal item selection data. In this paper, we developed a unified model that combines Multi-task Non-negative Matrix Factorization and Linear Dynamical Systems to capture the evolution of user preferences. Specifically, user and item features are projected into latent factor space by factoring co-occurrence matrices into a common basis item-factor matrix and multiple factor-user matrices. Moreover, we represented both within and between relationships of multiple factor-user matrices using a state transition matrix to capture the changes in user preferences over time. The experiments show that our proposed algorithm outperforms the other algorithms on two real datasets, which were extracted from Netflix movies and Last.fm music. Furthermore, our model provides a novel dynamic topic model for tracking the evolution of the behavior of a user over time. PMID:26270539

Using Dynamic Multi-Task Non-Negative Matrix Factorization to Detect the Evolution of User Preferences in Collaborative Filtering.

PubMed

Ju, Bin; Qian, Yuntao; Ye, Minchao; Ni, Rong; Zhu, Chenxi

2015-01-01

Predicting what items will be selected by a target user in the future is an important function for recommendation systems. Matrix factorization techniques have been shown to achieve good performance on temporal rating-type data, but little is known about temporal item selection data. In this paper, we developed a unified model that combines Multi-task Non-negative Matrix Factorization and Linear Dynamical Systems to capture the evolution of user preferences. Specifically, user and item features are projected into latent factor space by factoring co-occurrence matrices into a common basis item-factor matrix and multiple factor-user matrices. Moreover, we represented both within and between relationships of multiple factor-user matrices using a state transition matrix to capture the changes in user preferences over time. The experiments show that our proposed algorithm outperforms the other algorithms on two real datasets, which were extracted from Netflix movies and Last.fm music. Furthermore, our model provides a novel dynamic topic model for tracking the evolution of the behavior of a user over time.

A comparative analysis of alternative approaches for quantifying nonlinear dynamics in cardiovascular system.

PubMed

Chen, Yun; Yang, Hui

2013-01-01

Heart rate variability (HRV) analysis has emerged as an important research topic to evaluate autonomic cardiac function. However, traditional time and frequency-domain analysis characterizes and quantify only linear and stationary phenomena. In the present investigation, we made a comparative analysis of three alternative approaches (i.e., wavelet multifractal analysis, Lyapunov exponents and multiscale entropy analysis) for quantifying nonlinear dynamics in heart rate time series. Note that these extracted nonlinear features provide information about nonlinear scaling behaviors and the complexity of cardiac systems. To evaluate the performance, we used 24-hour HRV recordings from 54 healthy subjects and 29 heart failure patients, available in PhysioNet. Three nonlinear methods are evaluated not only individually but also in combination using three classification algorithms, i.e., linear discriminate analysis, quadratic discriminate analysis and k-nearest neighbors. Experimental results show that three nonlinear methods capture nonlinear dynamics from different perspectives and the combined feature set achieves the best performance, i.e., sensitivity 97.7% and specificity 91.5%. Collectively, nonlinear HRV features are shown to have the promise to identify the disorders in autonomic cardiovascular function.

Nuclear Fission: from more phenomenology and adjusted parameters to more fundamental theory and increased predictive power

NASA Astrophysics Data System (ADS)

Bulgac, Aurel; Jin, Shi; Magierski, Piotr; Roche, Kenneth; Schunck, Nicolas; Stetcu, Ionel

2017-11-01

Two major recent developments in theory and computational resources created the favorable conditions for achieving a microscopic description of fission dynamics in classically allowed regions of the collective potential energy surface, almost eighty years after its discovery in 1939 by Hahn and Strassmann [1]. The first major development was in theory, the extension of the Time-Dependent Density Functional Theory (TDDFT) [2-5] to superfluid fermion systems [6]. The second development was in computing, the emergence of powerful enough supercomputers capable of solving the complex systems of equations describing the time evolution in three dimensions without any restrictions of hundreds of strongly interacting nucleons. Thus the conditions have been created to renounce phenomenological models and incomplete microscopic treatments with uncontrollable approximations and/or assumptions in the description of the complex dynamics of fission. Even though the available nuclear energy density functionals (NEDFs) are phenomenological still, their accuracy is improving steadily and the prospects of being able to perform calculations of the nuclear fission dynamics and to predict many properties of the fission fragments, otherwise not possible to extract from experiments.

Angular Declination and the Dynamic Perception of Egocentric Distance

PubMed Central

Gajewski, Daniel A.; Philbeck, John W.; Wirtz, Philip W.; Chichka, David

2014-01-01

The extraction of the distance between an object and an observer is fast when angular declination is informative, as it is with targets placed on the ground. To what extent does angular declination drive performance when viewing time is limited? Participants judged target distances in a real-world environment with viewing durations ranging from 36–220 ms. An important role for angular declination was supported by experiments showing that the cue provides information about egocentric distance even on the very first glimpse, and that it supports a sensitive response to distance in the absence of other useful cues. Performance was better at 220 ms viewing durations than for briefer glimpses, suggesting that the perception of distance is dynamic even within the time frame of a typical eye fixation. Critically, performance in limited viewing trials was better when preceded by a 15 second preview of the room without a designated target. The results indicate that the perception of distance is powerfully shaped by memory from prior visual experience with the scene. A theoretical framework for the dynamic perception of distance is presented. PMID:24099588

The dynamics of information-driven coordination phenomena: A transfer entropy analysis

PubMed Central

Borge-Holthoefer, Javier; Perra, Nicola; Gonçalves, Bruno; González-Bailón, Sandra; Arenas, Alex; Moreno, Yamir; Vespignani, Alessandro

2016-01-01

Data from social media provide unprecedented opportunities to investigate the processes that govern the dynamics of collective social phenomena. We consider an information theoretical approach to define and measure the temporal and structural signatures typical of collective social events as they arise and gain prominence. We use the symbolic transfer entropy analysis of microblogging time series to extract directed networks of influence among geolocalized subunits in social systems. This methodology captures the emergence of system-level dynamics close to the onset of socially relevant collective phenomena. The framework is validated against a detailed empirical analysis of five case studies. In particular, we identify a change in the characteristic time scale of the information transfer that flags the onset of information-driven collective phenomena. Furthermore, our approach identifies an order-disorder transition in the directed network of influence between social subunits. In the absence of clear exogenous driving, social collective phenomena can be represented as endogenously driven structural transitions of the information transfer network. This study provides results that can help define models and predictive algorithms for the analysis of societal events based on open source data. PMID:27051875

The dynamics of information-driven coordination phenomena: A transfer entropy analysis.

PubMed

Borge-Holthoefer, Javier; Perra, Nicola; Gonçalves, Bruno; González-Bailón, Sandra; Arenas, Alex; Moreno, Yamir; Vespignani, Alessandro

2016-04-01

Data from social media provide unprecedented opportunities to investigate the processes that govern the dynamics of collective social phenomena. We consider an information theoretical approach to define and measure the temporal and structural signatures typical of collective social events as they arise and gain prominence. We use the symbolic transfer entropy analysis of microblogging time series to extract directed networks of influence among geolocalized subunits in social systems. This methodology captures the emergence of system-level dynamics close to the onset of socially relevant collective phenomena. The framework is validated against a detailed empirical analysis of five case studies. In particular, we identify a change in the characteristic time scale of the information transfer that flags the onset of information-driven collective phenomena. Furthermore, our approach identifies an order-disorder transition in the directed network of influence between social subunits. In the absence of clear exogenous driving, social collective phenomena can be represented as endogenously driven structural transitions of the information transfer network. This study provides results that can help define models and predictive algorithms for the analysis of societal events based on open source data.

Cosmology from group field theory formalism for quantum gravity.

PubMed

Gielen, Steffen; Oriti, Daniele; Sindoni, Lorenzo

2013-07-19

We identify a class of condensate states in the group field theory (GFT) formulation of quantum gravity that can be interpreted as macroscopic homogeneous spatial geometries. We then extract the dynamics of such condensate states directly from the fundamental quantum GFT dynamics, following the procedure used in ordinary quantum fluids. The effective dynamics is a nonlinear and nonlocal extension of quantum cosmology. We also show that any GFT model with a kinetic term of Laplacian type gives rise, in a semiclassical (WKB) approximation and in the isotropic case, to a modified Friedmann equation. This is the first concrete, general procedure for extracting an effective cosmological dynamics directly from a fundamental theory of quantum geometry.

Corrections of arterial input function for dynamic H215O PET to assess perfusion of pelvic tumours: arterial blood sampling versus image extraction

NASA Astrophysics Data System (ADS)

Lüdemann, L.; Sreenivasa, G.; Michel, R.; Rosner, C.; Plotkin, M.; Felix, R.; Wust, P.; Amthauer, H.

2006-06-01

Assessment of perfusion with 15O-labelled water (H215O) requires measurement of the arterial input function (AIF). The arterial time activity curve (TAC) measured using the peripheral sampling scheme requires corrections for delay and dispersion. In this study, parametrizations with and without arterial spillover correction for fitting of the tissue curve are evaluated. Additionally, a completely noninvasive method for generation of the AIF from a dynamic positron emission tomography (PET) acquisition is applied to assess perfusion of pelvic tumours. This method uses a volume of interest (VOI) to extract the TAC from the femoral artery. The VOI TAC is corrected for spillover using a separate tissue TAC and for recovery by determining the recovery coefficient on a coregistered CT data set. The techniques were applied in five patients with pelvic tumours who underwent a total of 11 examinations. Delay and dispersion correction of the blood TAC without arterial spillover correction yielded in seven examinations solutions inconsistent with physiology. Correction of arterial spillover increased the fitting accuracy and yielded consistent results in all patients. Generation of an AIF from PET image data was investigated as an alternative to arterial blood sampling and was shown to have an intrinsic potential to determine the AIF noninvasively and reproducibly. The AIF extracted from a VOI in a dynamic PET scan was similar in shape to the blood AIF but yielded significantly higher tissue perfusion values (mean of 104.0 ± 52.0%) and lower partition coefficients (-31.6 ± 24.2%). The perfusion values and partition coefficients determined with the VOI technique have to be corrected in order to compare the results with those of studies using a blood AIF.

Modelling of discrete TDS-spectrum of hydrogen desorption

NASA Astrophysics Data System (ADS)

Rodchenkova, Natalia I.; Zaika, Yury V.

2015-12-01

High concentration of hydrogen in metal leads to hydrogen embrittlement. One of the methods to evaluate the hydrogen content is the method of thermal desorption spectroscopy (TDS). As the sample is heated under vacuumization, atomic hydrogen diffuses inside the bulk and is desorbed from the surface in the molecular form. The extraction curve (measured by a mass-spectrometric analyzer) is recorded. In experiments with monotonous external heating it is observed that background hydrogen fluxes from the extractor walls and fluxes from the sample cannot be reliably distinguished. Thus, the extraction curve is doubtful. Therefore, in this case experimenters use discrete TDS-spectrum: the sample is removed from the analytical part of the device for the specified time interval, and external temperature is then increased stepwise. The paper is devoted to the mathematical modelling and simulation of experimental studies. In the corresponding boundary-value problem with nonlinear dynamic boundary conditions physical- chemical processes in the bulk and on the surface are taken into account: heating of the sample, diffusion in the bulk, hydrogen capture by defects, penetration from the bulk to the surface and desorption. The model aimed to analyze the dynamics of hydrogen concentrations without preliminary artificial sample saturation. Numerical modelling allows to choose the point on the extraction curve that corresponds to the initial quantity of the surface hydrogen, to estimate the values of the activation energies of diffusion, desorption, parameters of reversible capture and hydride phase decomposition.

A green deep eutectic solvent-based aqueous two-phase system for protein extracting.

PubMed

Xu, Kaijia; Wang, Yuzhi; Huang, Yanhua; Li, Na; Wen, Qian

2015-03-15

As a new type of green solvent, deep eutectic solvent (DES) has been applied for the extraction of proteins with an aqueous two-phase system (ATPS) in this work. Four kinds of choline chloride (ChCl)-based DESs were synthesized to extract bovine serum albumin (BSA), and ChCl-glycerol was selected as the suitable extraction solvent. Single factor experiments have been done to investigate the effects of the extraction process, including the amount of DES, the concentration of salt, the mass of protein, the shaking time, the temperature and PH value. Experimental results show 98.16% of the BSA could be extracted into the DES-rich phase in a single-step extraction under the optimized conditions. A high extraction efficiency of 94.36% was achieved, while the conditions were applied to the extraction of trypsin (Try). Precision, repeatability and stability experiments were studied and the relative standard deviations (RSD) of the extraction efficiency were 0.4246% (n=3), 1.6057% (n=3) and 1.6132% (n=3), respectively. Conformation of BSA was not changed during the extraction process according to the investigation of UV-vis spectra, FT-IR spectra and CD spectra of BSA. The conductivity, dynamic light scattering (DLS) and transmission electron microscopy (TEM) were used to explore the mechanism of the extraction. It turned out that the formation of DES-protein aggregates play a significant role in the separation process. All the results suggest that ChCl-based DES-ATPS are supposed to have the potential to provide new possibilities in the separation of proteins. Copyright © 2015 Elsevier B.V. All rights reserved.

Extraction and Analysis of Mega Cities’ Impervious Surface on Pixel-based and Object-oriented Support Vector Machine Classification Technology: A case of Bombay

NASA Astrophysics Data System (ADS)

Yu, S. S.; Sun, Z. C.; Sun, L.; Wu, M. F.

2017-02-01

The object of this paper is to study the impervious surface extraction method using remote sensing imagery and monitor the spatiotemporal changing patterns of mega cities. Megacity Bombay was selected as the interesting area. Firstly, the pixel-based and object-oriented support vector machine (SVM) classification methods were used to acquire the land use/land cover (LULC) products of Bombay in 2010. Consequently, the overall accuracy (OA) and overall Kappa (OK) of the pixel-based method were 94.97% and 0.96 with a running time of 78 minutes, the OA and OK of the object-oriented method were 93.72% and 0.94 with a running time of only 17s. Additionally, OA and OK of the object-oriented method after a post-classification were improved up to 95.8% and 0.94. Then, the dynamic impervious surfaces of Bombay in the period 1973-2015 were extracted and the urbanization pattern of Bombay was analysed. Results told that both the two SVM classification methods could accomplish the impervious surface extraction, but the object-oriented method should be a better choice. Urbanization of Bombay experienced a fast extending during the past 42 years, implying a dramatically urban sprawl of mega cities in the developing countries along the One Belt and One Road (OBOR).

Analysis of musical expression in audio signals

NASA Astrophysics Data System (ADS)

Dixon, Simon

2003-01-01

In western art music, composers communicate their work to performers via a standard notation which specificies the musical pitches and relative timings of notes. This notation may also include some higher level information such as variations in the dynamics, tempo and timing. Famous performers are characterised by their expressive interpretation, the ability to convey structural and emotive information within the given framework. The majority of work on audio content analysis focusses on retrieving score-level information; this paper reports on the extraction of parameters describing the performance, a task which requires a much higher degree of accuracy. Two systems are presented: BeatRoot, an off-line beat tracking system which finds the times of musical beats and tracks changes in tempo throughout a performance, and the Performance Worm, a system which provides a real-time visualisation of the two most important expressive dimensions, tempo and dynamics. Both of these systems are being used to process data for a large-scale study of musical expression in classical and romantic piano performance, which uses artificial intelligence (machine learning) techniques to discover fundamental patterns or principles governing expressive performance.

Extraction of Blebs in Human Embryonic Stem Cell Videos.

PubMed

Guan, Benjamin X; Bhanu, Bir; Talbot, Prue; Weng, Nikki Jo-Hao

2016-01-01

Blebbing is an important biological indicator in determining the health of human embryonic stem cells (hESC). Especially, areas of a bleb sequence in a video are often used to distinguish two cell blebbing behaviors in hESC: dynamic and apoptotic blebbings. This paper analyzes various segmentation methods for bleb extraction in hESC videos and introduces a bio-inspired score function to improve the performance in bleb extraction. Full bleb formation consists of bleb expansion and retraction. Blebs change their size and image properties dynamically in both processes and between frames. Therefore, adaptive parameters are needed for each segmentation method. A score function derived from the change of bleb area and orientation between consecutive frames is proposed which provides adaptive parameters for bleb extraction in videos. In comparison to manual analysis, the proposed method provides an automated fast and accurate approach for bleb sequence extraction.

Multiaperture ion beam extraction from gas-dynamic electron cyclotron resonance source of multicharged ions

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

Sidorov, A.; Dorf, M.; Zorin, V.

2008-02-15

Electron cyclotron resonance ion source with quasi-gas-dynamic regime of plasma confinement (ReGIS), constructed at the Institute of Applied Physics, Russia, provides opportunities for extracting intense and high-brightness multicharged ion beams. Despite the short plasma lifetime in a magnetic trap of a ReGIS, the degree of multiple ionization may be significantly enhanced by the increase in power and frequency of the applied microwave radiation. The present work is focused on studying the intense beam quality of this source by the pepper-pot method. A single beamlet emittance measured by the pepper-pot method was found to be {approx}70 {pi} mm mrad, and themore » total extracted beam current obtained at 14 kV extraction voltage was {approx}25 mA. The results of the numerical simulations of ion beam extraction are found to be in good agreement with experimental data.« less

Towards ultrafast dynamics with split-pulse X-ray photon correlation spectroscopy at free electron laser sources

DOE PAGES

Roseker, W.; Hruszkewycz, S. O.; Lehmkuhler, F.; ...

2018-04-27

One of the important challenges in condensed matter science is to understand ultrafast, atomic-scale fluctuations that dictate dynamic processes in equilibrium and non-equilibrium materials. Here, we report an important step towards reaching that goal by using a state-of-the-art perfect crystal based split-and-delay system, capable of splitting individual X-ray pulses and introducing femtosecond to nanosecond time delays. We show the results of an ultrafast hard X-ray photon correlation spectroscopy experiment at LCLS where split X-ray pulses were used to measure the dynamics of gold nanoparticles suspended in hexane. We show how reliable speckle contrast values can be extracted even from verymore » low intensity free electron laser (FEL) speckle patterns by applying maximum likelihood fitting, thus demonstrating the potential of a split-and-delay approach for dynamics measurements at FEL sources. This will enable the characterization of equilibrium and, importantly also reversible non-equilibrium processes in atomically disordered materials.« less

Application of system identification to analytic rotor modeling from simulated and wind tunnel dynamic test data, part 2

NASA Technical Reports Server (NTRS)

Hohenemser, K. H.; Banerjee, D.

1977-01-01

An introduction to aircraft state and parameter identification methods is presented. A simplified form of the maximum likelihood method is selected to extract analytical aeroelastic rotor models from simulated and dynamic wind tunnel test results for accelerated cyclic pitch stirring excitation. The dynamic inflow characteristics for forward flight conditions from the blade flapping responses without direct inflow measurements were examined. The rotor blades are essentially rigid for inplane bending and for torsion within the frequency range of study, but flexible in out-of-plane bending. Reverse flow effects are considered for high rotor advance ratios. Two inflow models are studied; the first is based on an equivalent blade Lock number, the second is based on a time delayed momentum inflow. In addition to the inflow parameters, basic rotor parameters like the blade natural frequency and the actual blade Lock number are identified together with measurement bias values. The effect of the theoretical dynamic inflow on the rotor eigenvalues is evaluated.

Towards ultrafast dynamics with split-pulse X-ray photon correlation spectroscopy at free electron laser sources

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

Roseker, W.; Hruszkewycz, S. O.; Lehmkuhler, F.

One of the important challenges in condensed matter science is to understand ultrafast, atomic-scale fluctuations that dictate dynamic processes in equilibrium and non-equilibrium materials. Here, we report an important step towards reaching that goal by using a state-of-the-art perfect crystal based split-and-delay system, capable of splitting individual X-ray pulses and introducing femtosecond to nanosecond time delays. We show the results of an ultrafast hard X-ray photon correlation spectroscopy experiment at LCLS where split X-ray pulses were used to measure the dynamics of gold nanoparticles suspended in hexane. We show how reliable speckle contrast values can be extracted even from verymore » low intensity free electron laser (FEL) speckle patterns by applying maximum likelihood fitting, thus demonstrating the potential of a split-and-delay approach for dynamics measurements at FEL sources. This will enable the characterization of equilibrium and, importantly also reversible non-equilibrium processes in atomically disordered materials.« less

Detecting many-body-localization lengths with cold atoms

NASA Astrophysics Data System (ADS)

Guo, Xuefei; Li, Xiaopeng

2018-03-01

Considering ultracold atoms in optical lattices, we propose experimental protocols to study many-body-localization (MBL) length and criticality in quench dynamics. Through numerical simulations with exact diagonalization, we show that in the MBL phase the perturbed density profile following a local quench remains exponentially localized in postquench dynamics. The size of this density profile after long-time-dynamics defines a localization length, which tends to diverge at the MBL-to-ergodic transition as we increase the system size. The determined localization transition point agrees with previous exact diagonalization calculations using other diagnostics. Our numerical results provide evidence for violation of the Harris-Chayes bound for the MBL criticality. The critical exponent ν can be extracted from our proposed dynamical procedure, which can then be used directly in experiments to determine whether the Harris-Chayes-bound holds for the MBL transition. These proposed protocols to detect localization criticality are justified by benchmarking to the well-established results for the noninteracting three-dimensional Anderson localization.

Facile Separation of 5-O-Galloylquinic Acid from Chinese Green Tea Extract using Mesoporous Zirconium Phosphate.

PubMed

Ma, Yilong; Shang, Yafang; Zhu, Danye; Wang, Caihong; Zhong, Zhifeng; Xu, Ziyang

2016-05-01

5-O-Galloylquinic acid from green tea and other plants is attracting increasing attention for its antioxidant and antileishmanial bioactivities. It is always isolated using a silica column, a Sephadex column and high-performance liquid chromatography (HPLC) methods, which are either laborious or instrument dependent. To develop a new method to easily separate 5-O-galloylquinic acid. Mesoporous zirconium phosphate (m-ZrP) was prepared to conveniently separate 5-O-galloylquinic acid from Chinese green tea extract, and the target compound was easily obtained by simple steps of adsorption, washing and desorption. The effects of the green tea extraction conditions, extract concentrations, and m-ZrP adsorption/desorption dynamics on the 5-O-galloylquinic acid separation were evaluated. 5-O-Galloylquinic acid that was separated from a 70% ethanol extract of green tea was of moderate HPLC purity (92%) and recovery (88%), and an increased non-specific binding of epigallocatechin gallate (EGCG) on m-ZrP was observed in the diluted tea extract. The times for maximal adsorption of 5-O-galloylquinic acid in 70% ethanol extract and maximal desorption of 5-O-galloylquinic acid in 0.4% phosphoric acid solution were confirmed as 7 h and 5 h, respectively. A facile method to separate 5-O-galloylquinic acid from Chinese green tea extract using m-ZrP was established. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

An Energy-Aware Trajectory Optimization Layer for sUAS

NASA Astrophysics Data System (ADS)

Silva, William A.

The focus of this work is the implementation of an energy-aware trajectory optimization algorithm that enables small unmanned aircraft systems (sUAS) to operate in unknown, dynamic severe weather environments. The software is designed as a component of an Energy-Aware Dynamic Data Driven Application System (EA-DDDAS) for sUAS. This work addresses the challenges of integrating and executing an online trajectory optimization algorithm during mission operations in the field. Using simplified aircraft kinematics, the energy-aware algorithm enables extraction of kinetic energy from measured winds to optimize thrust use and endurance during flight. The optimization layer, based upon a nonlinear program formulation, extracts energy by exploiting strong wind velocity gradients in the wind field, a process known as dynamic soaring. The trajectory optimization layer extends the energy-aware path planner developed by Wenceslao Shaw-Cortez te{Shaw-cortez2013} to include additional mission configurations, simulations with a 6-DOF model, and validation of the system with flight testing in June 2015 in Lubbock, Texas. The trajectory optimization layer interfaces with several components within the EA-DDDAS to provide an sUAS with optimal flight trajectories in real-time during severe weather. As a result, execution timing, data transfer, and scalability are considered in the design of the software. Severe weather also poses a measure of unpredictability to the system with respect to communication between systems and available data resources during mission operations. A heuristic mission tree with different cost functions and constraints is implemented to provide a level of adaptability to the optimization layer. Simulations and flight experiments are performed to assess the efficacy of the trajectory optimization layer. The results are used to assess the feasibility of flying dynamic soaring trajectories with existing controllers as well as to verify the interconnections between EA-DDDAS components. Results also demonstrate the usage of the trajectory optimization layer in conjunction with a lattice-based path planner as a method of guiding the optimization layer and stitching together subsequent trajectories.

A heuristic method for identifying chaos from frequency content.

PubMed

Wiebe, R; Virgin, L N

2012-03-01

The sign of the largest Lyapunov exponent is the fundamental indicator of chaos in a dynamical system. However, although the extraction of Lyapunov exponents can be accomplished with (necessarily noisy) the experimental data, this is still a relatively data-intensive and sensitive endeavor. This paper presents an alternative pragmatic approach to identifying chaos using response frequency characteristics and extending the concept of the spectrogram. The method is shown to work well on both experimental and simulated time series.

Detecting, anticipating, and predicting critical transitions in spatially extended systems.

PubMed

Kwasniok, Frank

2018-03-01

A data-driven linear framework for detecting, anticipating, and predicting incipient bifurcations in spatially extended systems based on principal oscillation pattern (POP) analysis is discussed. The dynamics are assumed to be governed by a system of linear stochastic differential equations which is estimated from the data. The principal modes of the system together with corresponding decay or growth rates and oscillation frequencies are extracted as the eigenvectors and eigenvalues of the system matrix. The method can be applied to stationary datasets to identify the least stable modes and assess the proximity to instability; it can also be applied to nonstationary datasets using a sliding window approach to track the changing eigenvalues and eigenvectors of the system. As a further step, a genuinely nonstationary POP analysis is introduced. Here, the system matrix of the linear stochastic model is time-dependent, allowing for extrapolation and prediction of instabilities beyond the learning data window. The methods are demonstrated and explored using the one-dimensional Swift-Hohenberg equation as an example, focusing on the dynamics of stochastic fluctuations around the homogeneous stable state prior to the first bifurcation. The POP-based techniques are able to extract and track the least stable eigenvalues and eigenvectors of the system; the nonstationary POP analysis successfully predicts the timing of the first instability and the unstable mode well beyond the learning data window.

Repurposing video recordings for structure motion estimations

NASA Astrophysics Data System (ADS)

Khaloo, Ali; Lattanzi, David

2016-04-01

Video monitoring of public spaces is becoming increasingly ubiquitous, particularly near essential structures and facilities. During any hazard event that dynamically excites a structure, such as an earthquake or hurricane, proximal video cameras may inadvertently capture the motion time-history of the structure during the event. If this dynamic time-history could be extracted from the repurposed video recording it would become a valuable forensic analysis tool for engineers performing post-disaster structural evaluations. The difficulty is that almost all potential video cameras are not installed to monitor structure motions, leading to camera perspective distortions and other associated challenges. This paper presents a method for extracting structure motions from videos using a combination of computer vision techniques. Images from a video recording are first reprojected into synthetic images that eliminate perspective distortion, using as-built knowledge of a structure for calibration. The motion of the camera itself during an event is also considered. Optical flow, a technique for tracking per-pixel motion, is then applied to these synthetic images to estimate the building motion. The developed method was validated using the experimental records of the NEESHub earthquake database. The results indicate that the technique is capable of estimating structural motions, particularly the frequency content of the response. Further work will evaluate variants and alternatives to the optical flow algorithm, as well as study the impact of video encoding artifacts on motion estimates.

Temporal dynamics underlying the modulation of social status on social attention.

PubMed

Dalmaso, Mario; Galfano, Giovanni; Coricelli, Carol; Castelli, Luigi

2014-01-01

Fixating someone suddenly moving the eyes is known to trigger a corresponding shift of attention in the observer. This phenomenon, known as gaze-cueing effect, can be modulated as a function of the social status of the individual depicted in the cueing face. Here, in two experiments, we investigated the temporal dynamics underlying this modulation. To this end, a gaze-cueing paradigm was implemented in which centrally-placed faces depicting high- and low-status individuals suddenly shifted the eyes towards a location either spatially congruent or incongruent with that occupied by a subsequent target stimulus. Social status was manipulated by presenting fictive Curriculum Vitae before the experimental phase. In Experiment 1, in which two temporal intervals (50 ms vs. 900 ms) occurred between the direct-gaze face and the averted-gaze face onsets, a stronger gaze-cueing effect in response to high-status faces than low-status faces was observed, irrespective of the time participants were allowed for extracting social information. In Experiment 2, in which two temporal intervals (200 ms vs. 1000 ms) occurred between the averted-gaze face and target onset, a stronger gaze cueing for high-status faces was observed at the shorter interval only. Taken together, these results suggest that information regarding social status is extracted from faces rapidly (Experiment 1), and that the tendency to selectively attend to the locations gazed by high-status individuals may decay with time (Experiment 2).

Detecting, anticipating, and predicting critical transitions in spatially extended systems

NASA Astrophysics Data System (ADS)

Kwasniok, Frank

2018-03-01

A data-driven linear framework for detecting, anticipating, and predicting incipient bifurcations in spatially extended systems based on principal oscillation pattern (POP) analysis is discussed. The dynamics are assumed to be governed by a system of linear stochastic differential equations which is estimated from the data. The principal modes of the system together with corresponding decay or growth rates and oscillation frequencies are extracted as the eigenvectors and eigenvalues of the system matrix. The method can be applied to stationary datasets to identify the least stable modes and assess the proximity to instability; it can also be applied to nonstationary datasets using a sliding window approach to track the changing eigenvalues and eigenvectors of the system. As a further step, a genuinely nonstationary POP analysis is introduced. Here, the system matrix of the linear stochastic model is time-dependent, allowing for extrapolation and prediction of instabilities beyond the learning data window. The methods are demonstrated and explored using the one-dimensional Swift-Hohenberg equation as an example, focusing on the dynamics of stochastic fluctuations around the homogeneous stable state prior to the first bifurcation. The POP-based techniques are able to extract and track the least stable eigenvalues and eigenvectors of the system; the nonstationary POP analysis successfully predicts the timing of the first instability and the unstable mode well beyond the learning data window.

Nonlinear Dynamics of River Runoff Elucidated by Horizontal Visibility Graphs

NASA Astrophysics Data System (ADS)

Lange, Holger; Rosso, Osvaldo A.

2017-04-01

We investigate a set of long-term river runoff time series at daily resolution from Brazil, monitored by the Agencia Nacional de Aguas. A total of 150 time series was obtained, with an average length of 65 years. Both long-term trends and human influence (water management, e.g. for power production) on the dynamical behaviour are analyzed. We use Horizontal Visibility Graphs (HVGs) to determine the individual temporal networks for the time series, and extract their degree and their distance (shortest path length) distributions. Statistical and information-theoretic properties of these distributions are calculated: robust estimators of skewness and kurtosis, the maximum degree occurring in the time series, the Shannon entropy, permutation complexity and Fisher Information. For the latter, we also compare the information measures obtained from the degree distributions to those using the original time series directly, to investigate the impact of graph construction on the dynamical properties as reflected in these measures. Focus is on one hand on universal properties of the HVG, common to all runoff series, and on site-specific aspects on the other. Results demonstrate that the assumption of power law behaviour for the degree distribtion does not generally hold, and that management has a significant impact on this distribution. We also show that a specific pretreatment of the time series conventional in hydrology, the elimination of seasonality by a separate z-transformation for each calendar day, is highly detrimental to the nonlinear behaviour. It changes long-term correlations and the overall dynamics towards more random behaviour. Analysis based on the transformed data easily leads to spurious results, and bear a high risk of misinterpretation.

Development of a new extraction technique and HPLC method for the analysis of non-psychoactive cannabinoids in fibre-type Cannabis sativa L. (hemp).

PubMed

Brighenti, Virginia; Pellati, Federica; Steinbach, Marleen; Maran, Davide; Benvenuti, Stefania

2017-09-05

The present work was aimed at the development and validation of a new, efficient and reliable technique for the analysis of the main non-psychoactive cannabinoids in fibre-type Cannabis sativa L. (hemp) inflorescences belonging to different varieties. This study was designed to identify samples with a high content of bioactive compounds, with a view to underscoring the importance of quality control in derived products as well. Different extraction methods, including dynamic maceration (DM), ultrasound-assisted extraction (UAE), microwave-assisted extraction (MAE) and supercritical-fluid extraction (SFE) were applied and compared in order to obtain a high yield of the target analytes from hemp. Dynamic maceration for 45min with ethanol (EtOH) at room temperature proved to be the most suitable technique for the extraction of cannabinoids in hemp samples. The analysis of the target analytes in hemp extracts was carried out by developing a new reversed-phase high-performance liquid chromatography (HPLC) method coupled with diode array (UV/DAD) and electrospray ionization-mass spectrometry (ESI-MS) detection, by using an ion trap mass analyser. An Ascentis Express C 18 column (150mm×3.0mm I.D., 2.7μm) was selected for the HPLC analysis, with a mobile phase composed of 0.1% formic acid in both water and acetonitrile, under gradient elution. The application of the fused-core technology allowed us to obtain a significant improvement of the HPLC performance compared with that of conventional particulate stationary phases, with a shorter analysis time and a remarkable reduction of solvent usage. The analytical method optimized in this study was fully validated to show compliance with international requirements. Furthermore, it was applied to the characterization of nine hemp samples and six hemp-based pharmaceutical products. As such, it was demonstrated to be a very useful tool for the analysis of cannabinoids in both the plant material and its derivatives for pharmaceutical and nutraceutical applications. Copyright © 2017 Elsevier B.V. All rights reserved.

Subpicosecond surface dynamics in genomic DNA from in vitro-grown plant species: a SERS assessment.

PubMed

Muntean, Cristina M; Bratu, Ioan; Leopold, Nicolae; Morari, Cristian; Buimaga-Iarinca, Luiza; Purcaru, Monica A P

2015-09-07

In this work the surface-enhanced Raman total half band widths of seven genomic DNAs from leaves of chrysanthemum (Dendranthema grandiflora Ramat.), common sundew (Drosera rotundifolia L.), edelweiss (Leontopodium alpinum Cass), Epilobium hirsutum L., Hypericum richeri ssp. transsilvanicum (Čelak) Ciocârlan, rose (Rosa x hybrida L.) and redwood (Sequoia sempervirens D. Don. Endl.) have been measured. We have shown that surface-enhanced Raman spectroscopy (SERS) can be used to study the fast subpicosecond dynamics of DNA in the proximity of a metallic surface. The dependencies of the total half band widths and the global relaxation times, on the DNA molecular subgroup structure and on the type of genomic DNA, are reported. In our study, the full widths at half-maximum (FWHMs) for the SERS bands of genomic DNAs from different leaf tissues are typically in the wavenumber range from 15 to 55 cm(-1). Besides, it can be observed that molecular relaxation processes studied in this work have a global relaxation time smaller than 0.71 ps and larger than 0.19 ps. A comparison between different ranges of FT-Raman and SERS band parameters, respectively, corresponding to DNA extracted from leaf tissues is given. It is shown that the interaction between DNA and a metallic surface has the potential to lead to a shortening of the global relaxation times, as compared with molecular dynamics in solution. We have found that the surface dynamics of molecular subgroups in plant DNA is, in some cases, about two times faster than the solution dynamics of nucleic acids. This can be rationalized in a qualitative manner by invoking the complex landscape of the interaction energy between the molecule and the silver surface.

Effect of molecular shape on rotation under severe confinement

DOE PAGES

Dhiman, Indu; Bhowmik, Debsindhu; Shrestha, Utsab R.; ...

2018-01-31

Orientational structure and dynamics of molecules is known to be affected by confinement in space comparable in size to the molecule itself. ZSM-5 with porous channels of ≈0.55 nm is such a porous medium, which offers a strict spatial confinement on low molecular weight hydrocarbons. An important factor that determines these properties is the shape of the confined molecules. In this work, we employed molecular dynamics simulation to study the orientational structure and dynamics of four molecules that differ in shape but have similar kinetic diameters and moments of inertia, confined in ZSM-5. The effect of molecular shape on themore » orientational structure and dynamics of propane, acetonitrile, acetaldehyde and acetone in ZSM-5 is studied by means of probing the differences in the orientational distribution of molecules in the ZSM-5 channels, and extracting time scales of the decay of correlation functions related to rotational motion. Orientational correlation functions of all the four molecules exhibit two regimes of rotational motion. While the short time regime represents free rotation of the molecules before they collide with the pore walls, the long time orientational jumps driven by inter-channel migrations give rise to a very slow varying second regime. Of the molecules studied, orientational structure and dynamics of propane is found to be least affected by confinement under ZSM-5, whereas charge and shape asymmetry of other molecules makes their interchannel migration-driven rotation slow. The time scales involved in the rotational motion for the molecules studied are compared with similar studies reported in literature. Lastly, this study reveals the important role that molecular shape plays in the behavior of confined molecules.« less

Effect of molecular shape on rotation under severe confinement

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

Dhiman, Indu; Bhowmik, Debsindhu; Shrestha, Utsab R.

Orientational structure and dynamics of molecules is known to be affected by confinement in space comparable in size to the molecule itself. ZSM-5 with porous channels of ≈0.55 nm is such a porous medium, which offers a strict spatial confinement on low molecular weight hydrocarbons. An important factor that determines these properties is the shape of the confined molecules. In this work, we employed molecular dynamics simulation to study the orientational structure and dynamics of four molecules that differ in shape but have similar kinetic diameters and moments of inertia, confined in ZSM-5. The effect of molecular shape on themore » orientational structure and dynamics of propane, acetonitrile, acetaldehyde and acetone in ZSM-5 is studied by means of probing the differences in the orientational distribution of molecules in the ZSM-5 channels, and extracting time scales of the decay of correlation functions related to rotational motion. Orientational correlation functions of all the four molecules exhibit two regimes of rotational motion. While the short time regime represents free rotation of the molecules before they collide with the pore walls, the long time orientational jumps driven by inter-channel migrations give rise to a very slow varying second regime. Of the molecules studied, orientational structure and dynamics of propane is found to be least affected by confinement under ZSM-5, whereas charge and shape asymmetry of other molecules makes their interchannel migration-driven rotation slow. The time scales involved in the rotational motion for the molecules studied are compared with similar studies reported in literature. Lastly, this study reveals the important role that molecular shape plays in the behavior of confined molecules.« less

Event-Based Computation of Motion Flow on a Neuromorphic Analog Neural Platform

PubMed Central

Giulioni, Massimiliano; Lagorce, Xavier; Galluppi, Francesco; Benosman, Ryad B.

2016-01-01

Estimating the speed and direction of moving objects is a crucial component of agents behaving in a dynamic world. Biological organisms perform this task by means of the neural connections originating from their retinal ganglion cells. In artificial systems the optic flow is usually extracted by comparing activity of two or more frames captured with a vision sensor. Designing artificial motion flow detectors which are as fast, robust, and efficient as the ones found in biological systems is however a challenging task. Inspired by the architecture proposed by Barlow and Levick in 1965 to explain the spiking activity of the direction-selective ganglion cells in the rabbit's retina, we introduce an architecture for robust optical flow extraction with an analog neuromorphic multi-chip system. The task is performed by a feed-forward network of analog integrate-and-fire neurons whose inputs are provided by contrast-sensitive photoreceptors. Computation is supported by the precise time of spike emission, and the extraction of the optical flow is based on time lag in the activation of nearby retinal neurons. Mimicking ganglion cells our neuromorphic detectors encode the amplitude and the direction of the apparent visual motion in their output spiking pattern. Hereby we describe the architectural aspects, discuss its latency, scalability, and robustness properties and demonstrate that a network of mismatched delicate analog elements can reliably extract the optical flow from a simple visual scene. This work shows how precise time of spike emission used as a computational basis, biological inspiration, and neuromorphic systems can be used together for solving specific tasks. PMID:26909015

Event-Based Computation of Motion Flow on a Neuromorphic Analog Neural Platform.

PubMed

Giulioni, Massimiliano; Lagorce, Xavier; Galluppi, Francesco; Benosman, Ryad B

2016-01-01

Estimating the speed and direction of moving objects is a crucial component of agents behaving in a dynamic world. Biological organisms perform this task by means of the neural connections originating from their retinal ganglion cells. In artificial systems the optic flow is usually extracted by comparing activity of two or more frames captured with a vision sensor. Designing artificial motion flow detectors which are as fast, robust, and efficient as the ones found in biological systems is however a challenging task. Inspired by the architecture proposed by Barlow and Levick in 1965 to explain the spiking activity of the direction-selective ganglion cells in the rabbit's retina, we introduce an architecture for robust optical flow extraction with an analog neuromorphic multi-chip system. The task is performed by a feed-forward network of analog integrate-and-fire neurons whose inputs are provided by contrast-sensitive photoreceptors. Computation is supported by the precise time of spike emission, and the extraction of the optical flow is based on time lag in the activation of nearby retinal neurons. Mimicking ganglion cells our neuromorphic detectors encode the amplitude and the direction of the apparent visual motion in their output spiking pattern. Hereby we describe the architectural aspects, discuss its latency, scalability, and robustness properties and demonstrate that a network of mismatched delicate analog elements can reliably extract the optical flow from a simple visual scene. This work shows how precise time of spike emission used as a computational basis, biological inspiration, and neuromorphic systems can be used together for solving specific tasks.

Efficient screening method for determination of polycyclic aromatic hydrocarbons (PAHs) in airborne particles. Application in real samples of Santiago-Chile metropolitan urban area

NASA Astrophysics Data System (ADS)

Romero, Rodrigo; Sienra, Rosario; Richter, Pablo

A rapid analytical approach for determination of polycyclic aromatic hydrocarbons (PAHs) present in real samples of particulate matter (PM10 filters) was investigated, based on the use of water under sub critical conditions, and the subsequent determination by GC-MS (SIM). The method avoids the use of large volumes of organic solvents as dichloromethane, toluene or other unhealthy liquid organic mixtures which are normally used in time-consuming conventional sample preparation methods. By using leaching times <1 h, the method allows determination of PAHs in the range of ng/m 3 (detection limits between 0.05 and 0.2 ng/m 3 for 1458 m 3 of sampled air) with a precision expressed as RSD between 5.6% and 11.2%. The main idea behind this approach is to raise the temperature and pressure of water inside a miniaturized laboratory-made extraction unit and to decrease its dielectric constant from 80 to nearly 20. This effect allows an increase in the solubility of low polarity hydrocarbons such as PAHs. In this way, an extraction step of a few minutes can be sufficient for a quantitative extraction of airborne particles collected in high volume PM10 samplers. Parameters such as: extraction flow, static or dynamic extraction times and water volume were optimized by using a standard reference material. Technical details are given and a comparison using real samples is made between the conventional Soxhlet extraction method and the proposed approach. The proposed approach can be used as a quantitative method to characterize low molecular PAHs and simultaneously as a screening method for high molecular weight PAHs, because the recoveries are not quantitative for molecular weights over 202. In the specific case of the Santiago metropolitan area, due to the frequent occurrence of particulate matter during high pollution episodes, this approach was applied as an efficient short-time screening method for urban PAHs. Application of this screening method is recommended especially during the winter, when periods of clear detriment of the atmospheric and meteorological conditions occur in the area.

Extracting ligands from receptors by reversed targeted molecular dynamics.

PubMed

Wolf, Romain M

2015-11-01

Short targeted MD trajectories are used to expel ligands from binding sites. The expulsion is governed by a linear increase of the target RMSD value, growing from zero to an arbitrary chosen final RMSD that forces the ligand to a selected distance outside of the receptor. The RMSD lag (i.e., the difference between the imposed and the actual RMSD) can be used to follow barriers encountered by the ligand during its way out of the receptor. The force constant used for the targeted MD can transform the RMSD lag into a strain energy. Integration of the (time-dependent) strain energy over time yields a value with the dimensions of "action" (i.e, energy multiplied by time) and can serve as a measure for the overall effort required to extract the ligand from its binding site. Possibilities to compare (numerically and graphically) the randomly detected exit pathways are discussed. As an example, the method is tested on the exit of bisphenol A from the human estrogen-related receptor [Formula: see text] and of GW0072 from the peroxysome proliferator activated receptor.

Modelling dynamics in protein crystal structures by ensemble refinement

PubMed Central

Burnley, B Tom; Afonine, Pavel V; Adams, Paul D; Gros, Piet

2012-01-01

Single-structure models derived from X-ray data do not adequately account for the inherent, functionally important dynamics of protein molecules. We generated ensembles of structures by time-averaged refinement, where local molecular vibrations were sampled by molecular-dynamics (MD) simulation whilst global disorder was partitioned into an underlying overall translation–libration–screw (TLS) model. Modeling of 20 protein datasets at 1.1–3.1 Å resolution reduced cross-validated Rfree values by 0.3–4.9%, indicating that ensemble models fit the X-ray data better than single structures. The ensembles revealed that, while most proteins display a well-ordered core, some proteins exhibit a ‘molten core’ likely supporting functionally important dynamics in ligand binding, enzyme activity and protomer assembly. Order–disorder changes in HIV protease indicate a mechanism of entropy compensation for ordering the catalytic residues upon ligand binding by disordering specific core residues. Thus, ensemble refinement extracts dynamical details from the X-ray data that allow a more comprehensive understanding of structure–dynamics–function relationships. DOI: http://dx.doi.org/10.7554/eLife.00311.001 PMID:23251785

Dynamic Gesture Recognition with a Terahertz Radar Based on Range Profile Sequences and Doppler Signatures

PubMed Central

Pi, Yiming

2017-01-01

The frequency of terahertz radar ranges from 0.1 THz to 10 THz, which is higher than that of microwaves. Multi-modal signals, including high-resolution range profile (HRRP) and Doppler signatures, can be acquired by the terahertz radar system. These two kinds of information are commonly used in automatic target recognition; however, dynamic gesture recognition is rarely discussed in the terahertz regime. In this paper, a dynamic gesture recognition system using a terahertz radar is proposed, based on multi-modal signals. The HRRP sequences and Doppler signatures were first achieved from the radar echoes. Considering the electromagnetic scattering characteristics, a feature extraction model is designed using location parameter estimation of scattering centers. Dynamic Time Warping (DTW) extended to multi-modal signals is used to accomplish the classifications. Ten types of gesture signals, collected from a terahertz radar, are applied to validate the analysis and the recognition system. The results of the experiment indicate that the recognition rate reaches more than 91%. This research verifies the potential applications of dynamic gesture recognition using a terahertz radar. PMID:29267249

Single neuron computation: from dynamical system to feature detector.

PubMed

Hong, Sungho; Agüera y Arcas, Blaise; Fairhall, Adrienne L

2007-12-01

White noise methods are a powerful tool for characterizing the computation performed by neural systems. These methods allow one to identify the feature or features that a neural system extracts from a complex input and to determine how these features are combined to drive the system's spiking response. These methods have also been applied to characterize the input-output relations of single neurons driven by synaptic inputs, simulated by direct current injection. To interpret the results of white noise analysis of single neurons, we would like to understand how the obtained feature space of a single neuron maps onto the biophysical properties of the membrane, in particular, the dynamics of ion channels. Here, through analysis of a simple dynamical model neuron, we draw explicit connections between the output of a white noise analysis and the underlying dynamical system. We find that under certain assumptions, the form of the relevant features is well defined by the parameters of the dynamical system. Further, we show that under some conditions, the feature space is spanned by the spike-triggered average and its successive order time derivatives.

Dynamic Gesture Recognition with a Terahertz Radar Based on Range Profile Sequences and Doppler Signatures.

PubMed

Zhou, Zhi; Cao, Zongjie; Pi, Yiming

2017-12-21

The frequency of terahertz radar ranges from 0.1 THz to 10 THz, which is higher than that of microwaves. Multi-modal signals, including high-resolution range profile (HRRP) and Doppler signatures, can be acquired by the terahertz radar system. These two kinds of information are commonly used in automatic target recognition; however, dynamic gesture recognition is rarely discussed in the terahertz regime. In this paper, a dynamic gesture recognition system using a terahertz radar is proposed, based on multi-modal signals. The HRRP sequences and Doppler signatures were first achieved from the radar echoes. Considering the electromagnetic scattering characteristics, a feature extraction model is designed using location parameter estimation of scattering centers. Dynamic Time Warping (DTW) extended to multi-modal signals is used to accomplish the classifications. Ten types of gesture signals, collected from a terahertz radar, are applied to validate the analysis and the recognition system. The results of the experiment indicate that the recognition rate reaches more than 91%. This research verifies the potential applications of dynamic gesture recognition using a terahertz radar.

Dynamic of Air Invasion in an Immersed Granular Layer

NASA Astrophysics Data System (ADS)

Varas, G.; Ramos, G.; Géminard, J. C.; Vidal, V.

2014-12-01

Displacement processes (typically, grains displaced by a fluid) are the driving mechanism which control the dynamics of many geological processes (e.g. oil extraction, air sparging, piercement structures). They also play an important role in a wide range of industrial applications, from ground water hydrology and soil mechanics to agricultural engineering. The interaction between one or more moving fluids (e.g. rising gas immersed in a granular medium) and grains control the dynamics of these phenomena. Due to their economic and ecological importance, it is essential to understand the variety and potentiality of these phenomena. When an ascending air passes trough an immersed granular bed its fluidized producing the grains to start to move. When this process is repeated, its created a fluidized zone that evolves over time. Here, we investigate the morphology and dynamics of the region invaded by air as a function of a dimensionless parameter χ which accounts for the relative effects of the gravity and the capillarity. We propose new experimental observations on the air invasion regimes and on the morphology of the fluidized zone, in particular its growth dynamics.

Extraction-Separation Performance and Dynamic Modeling of Orion Test Vehicles with Adams Simulation: 3rd Edition

NASA Technical Reports Server (NTRS)

Varela, Jose G.; Reddy, Satish; Moeller, Enrique; Anderson, Keith

2017-01-01

NASA's Orion Capsule Parachute Assembly System (CPAS) Project is now in the qualification phase of testing, and the Adams simulation has continued to evolve to model the complex dynamics experienced during the test article extraction and separation phases of flight. The ability to initiate tests near the upper altitude limit of the Orion parachute deployment envelope requires extractions from the aircraft at 35,000 ft-MSL. Engineering development phase testing of the Parachute Test Vehicle (PTV) carried by the Carriage Platform Separation System (CPSS) at altitude resulted in test support equipment hardware failures due to increased energy caused by higher true airspeeds. As a result, hardware modifications became a necessity requiring ground static testing of the textile components to be conducted and a new ground dynamic test of the extraction system to be devised. Force-displacement curves from static tests were incorporated into the Adams simulations, allowing prediction of loads, velocities and margins encountered during both flight and ground dynamic tests. The Adams simulation was then further refined by fine tuning the damping terms to match the peak loads recorded in the ground dynamic tests. The failure observed in flight testing was successfully replicated in ground testing and true safety margins of the textile components were revealed. A multi-loop energy modulator was then incorporated into the system level Adams simulation model and the effect on improving test margins be properly evaluated leading to high confidence ground verification testing of the final design solution.

Chemical dynamics between wells across a time-dependent barrier: Self-similarity in the Lagrangian descriptor and reactive basins.

PubMed

Junginger, Andrej; Duvenbeck, Lennart; Feldmaier, Matthias; Main, Jörg; Wunner, Günter; Hernandez, Rigoberto

2017-08-14

In chemical or physical reaction dynamics, it is essential to distinguish precisely between reactants and products for all times. This task is especially demanding in time-dependent or driven systems because therein the dividing surface (DS) between these states often exhibits a nontrivial time-dependence. The so-called transition state (TS) trajectory has been seen to define a DS which is free of recrossings in a large number of one-dimensional reactions across time-dependent barriers and thus, allows one to determine exact reaction rates. A fundamental challenge to applying this method is the construction of the TS trajectory itself. The minimization of Lagrangian descriptors (LDs) provides a general and powerful scheme to obtain that trajectory even when perturbation theory fails. Both approaches encounter possible breakdowns when the overall potential is bounded, admitting the possibility of returns to the barrier long after the trajectories have reached the product or reactant wells. Such global dynamics cannot be captured by perturbation theory. Meanwhile, in the LD-DS approach, it leads to the emergence of additional local minima which make it difficult to extract the optimal branch associated with the desired TS trajectory. In this work, we illustrate this behavior for a time-dependent double-well potential revealing a self-similar structure of the LD, and we demonstrate how the reflections and side-minima can be addressed by an appropriate modification of the LD associated with the direct rate across the barrier.

Membrane cholesterol removal changes mechanical properties of cells and induces secretion of a specific pool of lysosomes.

PubMed

Hissa, Barbara; Pontes, Bruno; Roma, Paula Magda S; Alves, Ana Paula; Rocha, Carolina D; Valverde, Thalita M; Aguiar, Pedro Henrique N; Almeida, Fernando P; Guimarães, Allan J; Guatimosim, Cristina; Silva, Aristóbolo M; Fernandes, Maria C; Andrews, Norma W; Viana, Nathan B; Mesquita, Oscar N; Agero, Ubirajara; Andrade, Luciana O

2013-01-01

In a previous study we had shown that membrane cholesterol removal induced unregulated lysosomal exocytosis events leading to the depletion of lysosomes located at cell periphery. However, the mechanism by which cholesterol triggered these exocytic events had not been uncovered. In this study we investigated the importance of cholesterol in controlling mechanical properties of cells and its connection with lysosomal exocytosis. Tether extraction with optical tweezers and defocusing microscopy were used to assess cell dynamics in mouse fibroblasts. These assays showed that bending modulus and surface tension increased when cholesterol was extracted from fibroblasts plasma membrane upon incubation with MβCD, and that the membrane-cytoskeleton relaxation time increased at the beginning of MβCD treatment and decreased at the end. We also showed for the first time that the amplitude of membrane-cytoskeleton fluctuation decreased during cholesterol sequestration, showing that these cells become stiffer. These changes in membrane dynamics involved not only rearrangement of the actin cytoskeleton, but also de novo actin polymerization and stress fiber formation through Rho activation. We found that these mechanical changes observed after cholesterol sequestration were involved in triggering lysosomal exocytosis. Exocytosis occurred even in the absence of the lysosomal calcium sensor synaptotagmin VII, and was associated with actin polymerization induced by MβCD. Notably, exocytosis triggered by cholesterol removal led to the secretion of a unique population of lysosomes, different from the pool mobilized by actin depolymerizing drugs such as Latrunculin-A. These data support the existence of at least two different pools of lysosomes with different exocytosis dynamics, one of which is directly mobilized for plasma membrane fusion after cholesterol removal.

Membrane Cholesterol Removal Changes Mechanical Properties of Cells and Induces Secretion of a Specific Pool of Lysosomes

PubMed Central

Roma, Paula Magda S.; Alves, Ana Paula; Rocha, Carolina D.; Valverde, Thalita M.; Aguiar, Pedro Henrique N.; Almeida, Fernando P.; Guimarães, Allan J.; Guatimosim, Cristina; Silva, Aristóbolo M.; Fernandes, Maria C.; Andrews, Norma W.; Viana, Nathan B.; Mesquita, Oscar N.; Agero, Ubirajara; Andrade, Luciana O.

2013-01-01

In a previous study we had shown that membrane cholesterol removal induced unregulated lysosomal exocytosis events leading to the depletion of lysosomes located at cell periphery. However, the mechanism by which cholesterol triggered these exocytic events had not been uncovered. In this study we investigated the importance of cholesterol in controlling mechanical properties of cells and its connection with lysosomal exocytosis. Tether extraction with optical tweezers and defocusing microscopy were used to assess cell dynamics in mouse fibroblasts. These assays showed that bending modulus and surface tension increased when cholesterol was extracted from fibroblasts plasma membrane upon incubation with MβCD, and that the membrane-cytoskeleton relaxation time increased at the beginning of MβCD treatment and decreased at the end. We also showed for the first time that the amplitude of membrane-cytoskeleton fluctuation decreased during cholesterol sequestration, showing that these cells become stiffer. These changes in membrane dynamics involved not only rearrangement of the actin cytoskeleton, but also de novo actin polymerization and stress fiber formation through Rho activation. We found that these mechanical changes observed after cholesterol sequestration were involved in triggering lysosomal exocytosis. Exocytosis occurred even in the absence of the lysosomal calcium sensor synaptotagmin VII, and was associated with actin polymerization induced by MβCD. Notably, exocytosis triggered by cholesterol removal led to the secretion of a unique population of lysosomes, different from the pool mobilized by actin depolymerizing drugs such as Latrunculin-A. These data support the existence of at least two different pools of lysosomes with different exocytosis dynamics, one of which is directly mobilized for plasma membrane fusion after cholesterol removal. PMID:24376622

Poster — Thur Eve — 03: Application of the non-negative matrix factorization technique to [{sup 11}C]-DTBZ dynamic PET data for the early detection of Parkinson's disease

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

Lee, Dong-Chang; Jans, Hans; McEwan, Sandy

2014-08-15

In this work, a class of non-negative matrix factorization (NMF) technique known as alternating non-negative least squares, combined with the projected gradient method, is used to analyze twenty-five [{sup 11}C]-DTBZ dynamic PET/CT brain data. For each subject, a two-factor model is assumed and two factors representing the striatum (factor 1) and the non-striatum (factor 2) tissues are extracted using the proposed NMF technique and commercially available factor analysis software “Pixies”. The extracted factor 1 and 2 curves represent the binding site of the radiotracer and describe the uptake and clearance of the radiotracer by soft tissues in the brain, respectively.more » The proposed NMF technique uses prior information about the dynamic data to obtain sample time-activity curves representing the striatum and the non-striatum tissues. These curves are then used for “warm” starting the optimization. Factor solutions from the two methods are compared graphically and quantitatively. In healthy subjects, radiotracer uptake by factors 1 and 2 are approximately 35–40% and 60–65%, respectively. The solutions are also used to develop a factor-based metric for the detection of early, untreated Parkinson's disease. The metric stratifies healthy subjects from suspected Parkinson's patients (based on the graphical method). The analysis shows that both techniques produce comparable results with similar computational time. The “semi-automatic” approach used by the NMF technique allows clinicians to manually set a starting condition for “warm” starting the optimization in order to facilitate control and efficient interaction with the data.« less

Pinning time statistics for vortex lines in disordered environments.

PubMed

Dobramysl, Ulrich; Pleimling, Michel; Täuber, Uwe C

2014-12-01

We study the pinning dynamics of magnetic flux (vortex) lines in a disordered type-II superconductor. Using numerical simulations of a directed elastic line model, we extract the pinning time distributions of vortex line segments. We compare different model implementations for the disorder in the surrounding medium: discrete, localized pinning potential wells that are either attractive and repulsive or purely attractive, and whose strengths are drawn from a Gaussian distribution; as well as continuous Gaussian random potential landscapes. We find that both schemes yield power-law distributions in the pinned phase as predicted by extreme-event statistics, yet they differ significantly in their effective scaling exponents and their short-time behavior.

Quantification of Tumor Vascular Permeability and Blood Volume by Positron Emission Tomography

PubMed Central

Chen, Haojun; Tong, Xiao; Lang, Lixin; Jacobson, Orit; Yung, Bryant C.; Yang, Xiangyu; Bai, Ruiliang; Kiesewetter, Dale O.; Ma, Ying; Wu, Hua; Niu, Gang; Chen, Xiaoyuan

2017-01-01

Purpose: Evans Blue (EB) is an azo dye that binds quantitatively with serum albumin. With an albumin binding, NOTA conjugated truncated Evan's blue (NEB) dye derived PET tracer, we aimed to establish a strategy for evaluating vascular permeability in malignant tumors via non-invasive PET. Experimental design: Sixty-minute dynamic PET using [18F]FAl-NEB was performed in three xenograft tumor models including INS-1 rat insulinoma, UM-SCC-22B human head and neck carcinoma and U-87 MG human glioblastoma. Tumor vascular permeability was quantified by the difference of the slopes between tumor and blood time-activity curve (TACs, expressed as Ps). The method was further substantiated by EB extraction and colorimetric assay and correlates with that calculated from dynamic contrast enhanced magnetic resonance imaging (DCE-MRI). The changes in tumor vasculature at different time points were assessed with NEB PET in U-87 MG and UM-SCC-22B tumor models after treatment with bevacizumab or doxorubicin. Result: The Ps values calculated from tumor and blood TACs from multiple time-point static images are consistent with those from dynamic images. Moreover, the Ps showed a positive and significant correlation with extracted EB concentration and KPS-MRI generated from DCE-MRI, which further confirmed the soundness of this methodology. The antiangiogenic effect of bevacizumab could be revealed by NEB PET in U-87 MG tumors as early as 8 hrs after therapy, demonstrated by a substantial decrease of Ps. On the contrary, there was no significant change of Ps in bevacizumab treated UM-SCC-22B tumors, compared with control group. However, the significant changes of Pswere overestimated in doxorubicin treated UM-SCC-22B tumors. Conclusions: We successfully developed a relatively convenient and novel strategy to evaluate vascular permeability and blood volume using NEB PET. This method will be advantageous in evaluating vascular permeability, promoting drug delivery, and monitoring tumor response to therapeutics that affect tumor angiogenesis. PMID:28744320

Unraveling DNA dynamics using atomic force microscopy.

PubMed

Suzuki, Yuki; Yoshikawa, Yuko; Yoshimura, Shige H; Yoshikawa, Kenichi; Takeyasu, Kunio

2011-01-01

The elucidation of structure-function relationships of biological samples has become important issue in post-genomic researches. In order to unveil the molecular mechanisms controlling gene regulations, it is essential to understand the interplay between fundamental DNA properties and the dynamics of the entire molecule. The wide range of applicability of atomic force microscopy (AFM) has allowed us to extract physicochemical properties of DNA and DNA-protein complexes, as well as to determine their topographical information. Here, we review how AFM techniques have been utilized to study DNA and DNA-protein complexes and what types of analyses have accelerated the understanding of the DNA dynamics. We begin by illustrating the application of AFM to investigate the fundamental feature of DNA molecules; topological transition of DNA, length dependent properties of DNA molecules, flexibility of double-stranded DNA, and capability of the formation of non-Watson-Crick base pairing. These properties of DNA are critical for the DNA folding and enzymatic reactions. The technical advancement in the time-resolution of AFM and sample preparation methods enabled visual analysis of DNA-protein interactions at sub-second time region. DNA tension-dependent enzymatic reaction and DNA looping dynamics by restriction enzymes were examined at a nanoscale in physiological environments. Contribution of physical properties of DNA to dynamics of nucleosomes and transition of the higher-order structure of reconstituted chromatin are also reviewed. Copyright © 2011 John Wiley & Sons, Inc.

A stochastic-field description of finite-size spiking neural networks

PubMed Central

Longtin, André

2017-01-01

Neural network dynamics are governed by the interaction of spiking neurons. Stochastic aspects of single-neuron dynamics propagate up to the network level and shape the dynamical and informational properties of the population. Mean-field models of population activity disregard the finite-size stochastic fluctuations of network dynamics and thus offer a deterministic description of the system. Here, we derive a stochastic partial differential equation (SPDE) describing the temporal evolution of the finite-size refractory density, which represents the proportion of neurons in a given refractory state at any given time. The population activity—the density of active neurons per unit time—is easily extracted from this refractory density. The SPDE includes finite-size effects through a two-dimensional Gaussian white noise that acts both in time and along the refractory dimension. For an infinite number of neurons the standard mean-field theory is recovered. A discretization of the SPDE along its characteristic curves allows direct simulations of the activity of large but finite spiking networks; this constitutes the main advantage of our approach. Linearizing the SPDE with respect to the deterministic asynchronous state allows the theoretical investigation of finite-size activity fluctuations. In particular, analytical expressions for the power spectrum and autocorrelation of activity fluctuations are obtained. Moreover, our approach can be adapted to incorporate multiple interacting populations and quasi-renewal single-neuron dynamics. PMID:28787447

Orientational Dynamics of a Functionalized Alkyl Planar Monolayer Probed by Polarization-Selective Angle-Resolved Infrared Pump-Probe Spectroscopy.

PubMed

Nishida, Jun; Yan, Chang; Fayer, Michael D

2016-10-12

Polarization-selective angle-resolved infrared pump-probe spectroscopy was developed and used to study the orientational dynamics of a planar alkylsiloxane monolayer functionalized with a rhenium metal carbonyl headgroup on an SiO 2 surface. The technique, together with a time-averaged infrared linear dichroism measurement, characterized picosecond orientational relaxation of the headgroup occurring at the monolayer-air interface by employing several sets of incident angles of the infrared pulses relative to the sample surface. By application of this method and using a recently developed theory, it was possible to extract both the out-of-plane and "mainly"-in-plane orientational correlation functions in a model-independent manner. The observed correlation functions were compared with theoretically derived correlation functions based on several dynamical models. The out-of-plane correlation function reveals the highly restricted out-of-plane motions of the head groups and also suggests that the angular distribution of the transition dipole moments is bimodal. The mainly-in-plane correlation function, for the sample studied here with the strongly restricted out-of-plane motions, essentially arises from the purely in-plane dynamics. In contrast to the out-of-plane dynamics, significant in-plane motions occurring over various time scales were observed including an inertial motion, a restricted wobbling motion of ∼3 ps, and complete randomization occurring in ∼25 ps.

Direct thermal desorption in the analysis of cheese volatiles by gas chromatography and gas chromatography-mass spectrometry: comparison with simultaneous distillation-extraction and dynamic headspace.

PubMed

Valero, E; Sanz, J; Martínez-Castro, I

2001-06-01

Direct thermal desorption (DTD) has been used as a technique for extracting volatile components of cheese as a preliminary step to their gas chromatographic (GC) analysis. In this study, it is applied to different cheese varieties: Camembert, blue, Chaumes, and La Serena. Volatiles are also extracted using other techniques such as simultaneous distillation-extraction and dynamic headspace. Separation and identification of the cheese components are carried out by GC-mass spectrometry. Approximately 100 compounds are detected in the examined cheeses. The described results show that DTD is fast, simple, and easy to automate; requires only a small amount of sample (approximately 50 mg); and affords quantitative information about the main groups of compounds present in cheeses.

Leveraging Ensemble Dynamical Properties to Prioritize Exoplanet Follow-Up Observations

NASA Astrophysics Data System (ADS)

Ballard, Sarah

2017-01-01

The number of transiting exoplanets now exceeds several thousand, enabling ensemble studies of the dynamical properties of exoplanetary systems. We require a mixture model of dynamical conditions (whether frozen in from formation or sculpted by planet-planet interactions) to recover Kepler's yield of transiting planets. Around M dwarfs, which will be predominate sites of exoplanet follow-up atmospheric study in the next decade, even a modest orbital eccentricity can sterilize a planet. I will describe efforts to link cheap observables, such as number of transiting planets and presence of transit timing variations, to eccentricity and mutual inclination in exoplanet systems. The addition of a second transiting planet, for example, halves the expected orbital eccentricity. For the vast majority of TESS targets, the light curve alone will furnish the sum total of data about the exoplanet. Extracting information about orbital properties from these light curves will help prioritize precious follow-up resources.

Inferring Biological Structures from Super-Resolution Single Molecule Images Using Generative Models

PubMed Central

Maji, Suvrajit; Bruchez, Marcel P.

2012-01-01

Localization-based super resolution imaging is presently limited by sampling requirements for dynamic measurements of biological structures. Generating an image requires serial acquisition of individual molecular positions at sufficient density to define a biological structure, increasing the acquisition time. Efficient analysis of biological structures from sparse localization data could substantially improve the dynamic imaging capabilities of these methods. Using a feature extraction technique called the Hough Transform simple biological structures are identified from both simulated and real localization data. We demonstrate that these generative models can efficiently infer biological structures in the data from far fewer localizations than are required for complete spatial sampling. Analysis at partial data densities revealed efficient recovery of clathrin vesicle size distributions and microtubule orientation angles with as little as 10% of the localization data. This approach significantly increases the temporal resolution for dynamic imaging and provides quantitatively useful biological information. PMID:22629348

Consistent response of vegetation dynamics to recent climate change in tropical mountain regions.

PubMed

Krishnaswamy, Jagdish; John, Robert; Joseph, Shijo

2014-01-01

Global climate change has emerged as a major driver of ecosystem change. Here, we present evidence for globally consistent responses in vegetation dynamics to recent climate change in the world's mountain ecosystems located in the pan-tropical belt (30°N-30°S). We analyzed decadal-scale trends and seasonal cycles of vegetation greenness using monthly time series of satellite greenness (Normalized Difference Vegetation Index) and climate data for the period 1982-2006 for 47 mountain protected areas in five biodiversity hotspots. The time series of annual maximum NDVI for each of five continental regions shows mild greening trends followed by reversal to stronger browning trends around the mid-1990s. During the same period we found increasing trends in temperature but only marginal change in precipitation. The amplitude of the annual greenness cycle increased with time, and was strongly associated with the observed increase in temperature amplitude. We applied dynamic models with time-dependent regression parameters to study the time evolution of NDVI-climate relationships. We found that the relationship between vegetation greenness and temperature weakened over time or was negative. Such loss of positive temperature sensitivity has been documented in other regions as a response to temperature-induced moisture stress. We also used dynamic models to extract the trends in vegetation greenness that remain after accounting for the effects of temperature and precipitation. We found residual browning and greening trends in all regions, which indicate that factors other than temperature and precipitation also influence vegetation dynamics. Browning rates became progressively weaker with increase in elevation as indicated by quantile regression models. Tropical mountain vegetation is considered sensitive to climatic changes, so these consistent vegetation responses across widespread regions indicate persistent global-scale effects of climate warming and associated moisture stresses. © 2013 John Wiley & Sons Ltd.

Fitted Hanbury-Brown Twiss radii versus space-time variances in flow-dominated models

NASA Astrophysics Data System (ADS)

Frodermann, Evan; Heinz, Ulrich; Lisa, Michael Annan

2006-04-01

The inability of otherwise successful dynamical models to reproduce the Hanbury-Brown Twiss (HBT) radii extracted from two-particle correlations measured at the Relativistic Heavy Ion Collider (RHIC) is known as the RHIC HBT Puzzle. Most comparisons between models and experiment exploit the fact that for Gaussian sources the HBT radii agree with certain combinations of the space-time widths of the source that can be directly computed from the emission function without having to evaluate, at significant expense, the two-particle correlation function. We here study the validity of this approach for realistic emission function models, some of which exhibit significant deviations from simple Gaussian behavior. By Fourier transforming the emission function, we compute the two-particle correlation function, and fit it with a Gaussian to partially mimic the procedure used for measured correlation functions. We describe a novel algorithm to perform this Gaussian fit analytically. We find that for realistic hydrodynamic models the HBT radii extracted from this procedure agree better with the data than the values previously extracted from the space-time widths of the emission function. Although serious discrepancies between the calculated and the measured HBT radii remain, we show that a more apples-to-apples comparison of models with data can play an important role in any eventually successful theoretical description of RHIC HBT data.

Nondestructive nanostraw intracellular sampling for longitudinal cell monitoring

PubMed Central

Cao, Yuhong; Chen, Haodong; Birey, Fikri; Leal-Ortiz, Sergio A.; Han, Crystal M.; Santiago, Juan G.; Paşca, Sergiu P.; Wu, Joseph C.; Melosh, Nicholas A.

2017-01-01

Here, we report a method for time-resolved, longitudinal extraction and quantitative measurement of intracellular proteins and mRNA from a variety of cell types. Cytosolic contents were repeatedly sampled from the same cell or population of cells for more than 5 d through a cell-culture substrate, incorporating hollow 150-nm-diameter nanostraws (NS) within a defined sampling region. Once extracted, the cellular contents were analyzed with conventional methods, including fluorescence, enzymatic assays (ELISA), and quantitative real-time PCR. This process was nondestructive with >95% cell viability after sampling, enabling long-term analysis. It is important to note that the measured quantities from the cell extract were found to constitute a statistically significant representation of the actual contents within the cells. Of 48 mRNA sequences analyzed from a population of cardiomyocytes derived from human induced pluripotent stem cells (hiPSC-CMs), 41 were accurately quantified. The NS platform samples from a select subpopulation of cells within a larger culture, allowing native cell-to-cell contact and communication even during vigorous activity such as cardiomyocyte beating. This platform was applied both to cell lines and to primary cells, including CHO cells, hiPSC-CMs, and human astrocytes derived in 3D cortical spheroids. By tracking the same cell or group of cells over time, this method offers an avenue to understand dynamic cell behavior, including processes such as induced pluripotency and differentiation. PMID:28223521

Fitted Hanbury-Brown-Twiss radii versus space-time variances in flow-dominated models

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

Frodermann, Evan; Heinz, Ulrich; Lisa, Michael Annan

2006-04-15

The inability of otherwise successful dynamical models to reproduce the Hanbury-Brown-Twiss (HBT) radii extracted from two-particle correlations measured at the Relativistic Heavy Ion Collider (RHIC) is known as the RHIC HBT Puzzle. Most comparisons between models and experiment exploit the fact that for Gaussian sources the HBT radii agree with certain combinations of the space-time widths of the source that can be directly computed from the emission function without having to evaluate, at significant expense, the two-particle correlation function. We here study the validity of this approach for realistic emission function models, some of which exhibit significant deviations from simplemore » Gaussian behavior. By Fourier transforming the emission function, we compute the two-particle correlation function, and fit it with a Gaussian to partially mimic the procedure used for measured correlation functions. We describe a novel algorithm to perform this Gaussian fit analytically. We find that for realistic hydrodynamic models the HBT radii extracted from this procedure agree better with the data than the values previously extracted from the space-time widths of the emission function. Although serious discrepancies between the calculated and the measured HBT radii remain, we show that a more apples-to-apples comparison of models with data can play an important role in any eventually successful theoretical description of RHIC HBT data.« less

Non-rigid Reconstruction of Casting Process with Temperature Feature

NASA Astrophysics Data System (ADS)

Lin, Jinhua; Wang, Yanjie; Li, Xin; Wang, Ying; Wang, Lu

2017-09-01

Off-line reconstruction of rigid scene has made a great progress in the past decade. However, the on-line reconstruction of non-rigid scene is still a very challenging task. The casting process is a non-rigid reconstruction problem, it is a high-dynamic molding process lacking of geometric features. In order to reconstruct the casting process robustly, an on-line fusion strategy is proposed for dynamic reconstruction of casting process. Firstly, the geometric and flowing feature of casting are parameterized in manner of TSDF (truncated signed distance field) which is a volumetric block, parameterized casting guarantees real-time tracking and optimal deformation of casting process. Secondly, data structure of the volume grid is extended to have temperature value, the temperature interpolation function is build to generate the temperature of each voxel. This data structure allows for dynamic tracking of temperature of casting during deformation stages. Then, the sparse RGB features is extracted from casting scene to search correspondence between geometric representation and depth constraint. The extracted color data guarantees robust tracking of flowing motion of casting. Finally, the optimal deformation of the target space is transformed into a nonlinear regular variational optimization problem. This optimization step achieves smooth and optimal deformation of casting process. The experimental results show that the proposed method can reconstruct the casting process robustly and reduce drift in the process of non-rigid reconstruction of casting.

Role of Confinement on Adsorption and Dynamics of Ethane and an Ethane–CO 2 Mixture in Mesoporous CPG Silica

DOE PAGES

Patankar, Sumant; Gautam, Siddharth; Rother, Gernot; ...

2016-02-10

It was found that ethane is confined to mineral and organic pores in certain shale formations. Effects of confinement on structural and dynamic properties of ethane in mesoporous controlled pore glass (CPG) were studied by gravimetric adsorption and quasi-elastic neutron scattering (QENS) measurements. The obtained isotherms and scattering data complement each other by quantifying the relative strength of the solid–fluid interactions and the transport properties of the fluid under confinement, respectively. We used a magnetic suspension balance to measure the adsorption isotherms at two temperatures and over a range of pressures corresponding to a bulk density range of 0.01–0.35 g/cmmore » 3. Key confinement effects were highlighted through differences between isotherms for the two pore sizes. A comparison was made with previously published isotherms for CO 2 on the same CPG materials. Behavior of ethane in the smaller pore size was probed further using quasi-elastic neutron scattering. By extracting the self-diffusivity and residence time, we were able to study the effect of pressure and transition from gaseous to supercritical densities on the dynamics of confined ethane. Moreover, a temperature variation QENS study was also completed with pure ethane and a CO 2–ethane mixture. Activation energies extracted from the Arrhenius plots show the effects of CO 2 addition on ethane mobility.« less

Zero valent Fe-reduced graphene oxide quantum dots as a novel magnetic dispersive solid phase microextraction sorbent for extraction of organophosphorus pesticides in real water and fruit juice samples prior to analysis by gas chromatography-mass spectrometry.

PubMed

Akbarzade, Samaneh; Chamsaz, Mahmoud; Rounaghi, Gholam Hossein; Ghorbani, Mahdi

2018-01-01

A selective and sensitive magnetic dispersive solid-phase microextraction (MDSPME) coupled with gas chromatography-mass spectrometry was developed for extraction and determination of organophosphorus pesticides (Sevin, Fenitrothion, Malathion, Parathion, and Diazinon) in fruit juice and real water samples. Zero valent Fe-reduced graphene oxide quantum dots (rGOQDs@ Fe) as a new and effective sorbent were prepared and applied for extraction of organophosphorus pesticides using MDSPME method. In order to study the performance of this new sorbent, the ability of rGOQDs@ Fe was compared with graphene oxide and magnetic graphene oxide nanocomposite by recovery experiments of the organophosphorus pesticides. Several affecting parameters in the microextraction procedure, including pH of donor phase, donor phase volume, stirring rate, extraction time, and desorption conditions such as the type and volume of solvents and desorption time were thoroughly investigated and optimized. Under the optimal conditions, the method showed a wide linear dynamic range with R-square between 0.9959 and 0.9991. The limit of detections, the intraday and interday relative standard deviations (n = 5) were less than 0.07 ngmL -1 , 4.7, and 8.6%, respectively. The method was successfully applied for extraction and determination of organophosphorus pesticides in real water samples (well, river and tap water) and fruit juice samples (apple and grape juice). The obtained relative recoveries were in the range of 82.9%-113.2% with RSD percentages of less than 5.8% for all the real samples.

Optimized ultrasound-assisted emulsification microextraction for simultaneous trace multielement determination of heavy metals in real water samples by ICP-OES.

PubMed

Sereshti, Hassan; Heravi, Yeganeh Entezari; Samadi, Soheila

2012-08-15

Ultrasonic-assisted emulsification microextraction (USAEME) combined with inductively coupled plasma-optical emission spectrometry (ICP-OES) was used for preconcentration and determination of aluminum, bismuth, cadmium, cobalt, copper, iron, gallium, indium, nickel, lead, thallium and zinc in real water samples. Ammonium pyrrolidine dithiocarbamate (APDC) and carbon tetrachloride (CCl(4)) were used as the chelating agent and extraction solvent, respectively. The effective parameters (factors) of the extraction process such as volume of extraction solvent, pH, sonication time, and concentration of chelating agent were optimized by a small central composite design (CCD). The optimum conditions were found to be 98 μL for extraction solvent, 1476 mg L(-1) for chelating agent, 3.8 for pH and 9 min for sonication time. Under the optimal conditions, the limits of detection (LODs) for Al, Bi, Cd, Co, Cu, Fe, Ga, In, Ni, Pb, Tl and Zn were 0.13, 0.48, 0.19, 0.28, 0.29, 0.27, 0.27, 0.38, 0.44, 0.47, 0.52 and 0.17 μg L(-1), respectively. The linear dynamic range (LDR) was 1-1000 μ gL(-1) with determination coefficients of 0.991-0.998. Relative standard deviations (RSDs, C=200 μg L(-1), n=6) were between 1.87%-5.65%. The proposed method was successfully applied to the extraction and determination of heavy metals in real water samples and the satisfactory relative recoveries (90.3%-105.5%) were obtained. Copyright © 2012 Elsevier B.V. All rights reserved.

Quantification of cardiorespiratory interactions based on joint symbolic dynamics.

PubMed

Kabir, Muammar M; Saint, David A; Nalivaiko, Eugene; Abbott, Derek; Voss, Andreas; Baumert, Mathias

2011-10-01

Cardiac and respiratory rhythms are highly nonlinear and nonstationary. As a result traditional time-domain techniques are often inadequate to characterize their complex dynamics. In this article, we introduce a novel technique to investigate the interactions between R-R intervals and respiratory phases based on their joint symbolic dynamics. To evaluate the technique, electrocardiograms (ECG) and respiratory signals were recorded in 13 healthy subjects in different body postures during spontaneous and controlled breathing. Herein, the R-R time series were extracted from ECG and respiratory phases were obtained from abdomen impedance belts using the Hilbert transform. Both time series were transformed into ternary symbol vectors based on the changes between two successive R-R intervals or respiratory phases. Subsequently, words of different symbol lengths were formed and the correspondence between the two series of words was determined to quantify the interaction between cardiac and respiratory cycles. To validate our results, respiratory sinus arrhythmia (RSA) was further studied using the phase-averaged characterization of the RSA pattern. The percentage of similarity of the sequence of symbols, between the respective words of the two series determined by joint symbolic dynamics, was significantly reduced in the upright position compared to the supine position (26.4 ± 4.7 vs. 20.5 ± 5.4%, p < 0.01). Similarly, RSA was also reduced during upright posture, but the difference was less significant (0.11 ± 0.02 vs. 0.08 ± 0.01 s, p < 0.05). In conclusion, joint symbolic dynamics provides a new efficient technique for the analysis of cardiorespiratory interaction that is highly sensitive to the effects of orthostatic challenge.

Dynamics of a poly(ethylene oxide) tracer in a poly(methyl methacrylate) matrix: remarkable decoupling of local and global motions.

PubMed

Haley, Jeffrey C; Lodge, Timothy P

2005-06-15

The tracer diffusion coefficient of unentangled poly(ethylene oxide) (PEO, M=1000 gmol) in a matrix of poly(methyl methacrylate) (PMMA, M=10 000 gmol) has been measured over a temperature range from 125 to 220 degrees C with forced Rayleigh scattering. The dynamic viscosities of blends of two different high molecular weight PEO tracers (M=440 000 and 900 000 gmol) in the same PMMA matrix were also measured at temperatures ranging from 160 to 220 degrees C; failure of time-temperature superposition was observed for these systems. The monomeric friction factors for the PEO tracers were extracted from the diffusion coefficients and the rheological relaxation times using the Rouse model. The friction factors determined by diffusion and rheology were in good agreement, even though the molecular weights of the tracers differed by about three orders of magnitude. The PEO monomeric friction factors were compared with literature data for PEO segmental relaxation times measured directly with NMR. The monomeric friction factors of the PEO tracer in the PMMA matrix were found to be from two to six orders of magnitude greater than anticipated based on direct measurements of segmental dynamics. Additionally, the PEO tracer terminal dynamics are a much stronger function of temperature than the corresponding PEO segmental dynamics. These results indicate that the fastest PEO Rouse mode, inferred from diffusion and rheology, is completely separated from the bond reorientation of PEO detected by NMR. This result is unlike other blend systems in which global and local motions have been compared.

Extracting relevant information for cancer diagnosis from dynamic full field OCT through image processing and learning

NASA Astrophysics Data System (ADS)

Apelian, Clément; Gastaud, Clément; Boccara, A. Claude

2017-02-01

For a large number of cancer surgeries, the lack of reliable intraoperative diagnosis leads to reoperations or bad outcomes for the patients. To deliver better diagnosis, we developed Dynamic Full Field OCT (D-FFOCT) as a complement to FFOCT. FFOCT already presents interesting results for cancer diagnosis e.g. Mohs surgery and reaching 96% accuracy on prostate cancer. D-FFOCT accesses the dynamic processes of metabolism and gives new tools to diagnose the state of a tissue at the cellular level to complement FFOCT contrast. We developed a processing framework that intends to maximize the information provided by the FFOCT technology as well as D-FFOCT and synthetize this as a meaningful image. We use different time processing to generate metrics (standard deviation of time signals, decorrelation times and more) and spatial processing to sort out structures and the corresponding imaging modality, which is the most appropriate. Sorting was achieved through quadratic discriminant analysis in a N-dimension parametric space corresponding to our metrics. Combining the best imaging modalities for each structure leads to a rich morphology image. This image displaying the morphology is then colored to represent the dynamic behavior of these structures (slow or fast) and to be quickly analyzed by doctors. Therefore, we achieved a micron resolved image, rich of both FFOCT ability of imaging fixed and highly backscattering structures as well as D-FFOCT ability of imaging low level scattering cellular level details. We believe that this morphological contrast close to histology and the dynamic behavior contrast will push forward the limits of intraoperative diagnosis further on.

Gene regulatory network identification from the yeast cell cycle based on a neuro-fuzzy system.

PubMed

Wang, B H; Lim, J W; Lim, J S

2016-08-30

Many studies exist for reconstructing gene regulatory networks (GRNs). In this paper, we propose a method based on an advanced neuro-fuzzy system, for gene regulatory network reconstruction from microarray time-series data. This approach uses a neural network with a weighted fuzzy function to model the relationships between genes. Fuzzy rules, which determine the regulators of genes, are very simplified through this method. Additionally, a regulator selection procedure is proposed, which extracts the exact dynamic relationship between genes, using the information obtained from the weighted fuzzy function. Time-series related features are extracted from the original data to employ the characteristics of temporal data that are useful for accurate GRN reconstruction. The microarray dataset of the yeast cell cycle was used for our study. We measured the mean squared prediction error for the efficiency of the proposed approach and evaluated the accuracy in terms of precision, sensitivity, and F-score. The proposed method outperformed the other existing approaches.

Motion generation of robotic surgical tasks: learning from expert demonstrations.

PubMed

Reiley, Carol E; Plaku, Erion; Hager, Gregory D

2010-01-01

Robotic surgical assistants offer the possibility of automating portions of a task that are time consuming and tedious in order to reduce the cognitive workload of a surgeon. This paper proposes using programming by demonstration to build generative models and generate smooth trajectories that capture the underlying structure of the motion data recorded from expert demonstrations. Specifically, motion data from Intuitive Surgical's da Vinci Surgical System of a panel of expert surgeons performing three surgical tasks are recorded. The trials are decomposed into subtasks or surgemes, which are then temporally aligned through dynamic time warping. Next, a Gaussian Mixture Model (GMM) encodes the experts' underlying motion structure. Gaussian Mixture Regression (GMR) is then used to extract a smooth reference trajectory to reproduce a trajectory of the task. The approach is evaluated through an automated skill assessment measurement. Results suggest that this paper presents a means to (i) extract important features of the task, (ii) create a metric to evaluate robot imitative performance (iii) generate smoother trajectories for reproduction of three common medical tasks.

Determination of the Earth's Plasmapause Location from the CE-3 EUVC Images

NASA Technical Reports Server (NTRS)

He, Fei; Zhang, Xiao-Xin; Chen, Bo; Fok, Mei-Ching; Nakano, Shinya

2016-01-01

The Moon-based Extreme Ultraviolet Camera (EUVC) aboard China's Chang'e-3 (CE-3) mission has successfully imaged the entire Earth's plasmasphere for the first time from the side views on lunar surface. An EUVC image on 21 April 2014 is used in this study to demonstrate the characteristics and configurations of the Moon-based EUV imaging and to illustrate the determination algorithm of the plasmapause locations on the magnetic equator. The plasmapause locations determined from all the available EUVC images with the Minimum L Algorithm are quantitatively compared with those extracted from insitu observations (Defense Meteorological Satellite Program, Time History of Events and Macroscale Interactions during Substorms, and Radiation Belt Storm Probes). Excellent agreement between the determined plasmapauses seen by EUVC and the extracted ones from other satellites indicates the reliability of the Moon-based EUVC images as well as the determination algorithm. This preliminary study provides an important basis for future investigation of the dynamics of the plasmasphere with the Moon-based EUVC imaging.

Repetitive Regeneration of Media #1 in a Dynamic Column Extraction using Brine #1

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

Gary Garland

This data is from a regeneration study from a dynamic column extraction experiment where we ran a solution of REE's through a column of media #1 then stripped the REE's off the media using 2M HNO3 solution. We then re-equilibrated the media and repeated the process of running a REE solution through the column and stripping the REE's off the media and comparing the two runs.

Microalgae fractionation using steam explosion, dynamic and tangential cross-flow membrane filtration.

PubMed

Lorente, E; Hapońska, M; Clavero, E; Torras, C; Salvadó, J

2017-08-01

In this study, the microalga Nannochloropsis gaditana was subjected to acid catalysed steam explosion treatment and the resulting exploded material was subsequently fractionated to separate the different fractions (lipids, sugars and solids). Conventional and vibrational membrane setups were used with several polymeric commercial membranes. Two different routes were followed: 1) filtration+lipid solvent extraction and 2) lipid solvent extraction+filtration. Route 1 revealed to be much better since the used membrane for filtration was able to permeate the sugar aqueous phase and retained the fraction containing lipids; after this, an extraction required a much lower amount of solvent and a better recovering yield. Filtration allowed complete lipid rejection. Dynamic filtration improved permeability compared to the tangential cross-flow filtration. Best membrane performance was achieved using a 5000Da membrane with the dynamic system, obtaining a permeability of 6L/h/m 2 /bar. Copyright © 2017 Elsevier Ltd. All rights reserved.

Solid Phase Extraction of Inorganic Mercury Using 5-Phenylazo-8-hydroxyquinoline and Determination by Cold Vapor Atomic Fluorescence Spectroscopy in Natural Water Samples

PubMed Central

Daye, Mirna; Halwani, Jalal; Hamzeh, Mariam

2013-01-01

8-Hydroxyquinoline (8-HQ) was chosen as a powerful ligand for Hg solid phase extraction. Among several chelating resins based on 8-HQ, 5-phenylazo-8-hydroxyquinoline (5Ph8HQ) is used for mercury extraction in which the adsorption dynamics were fully studied. It has been shown that Hg(II) is totally absorbed by 5Ph8HQ within the first 30 minutes of contact time with t 1/2 5 minutes, following Langmuir adsorption model. At pH 4, the affinity of mercury is unchallenged by other metals except, for Cu(II), which have shown higher Kd value. With these latter characteristics, 5Ph8HQ was examined for the preconcentration of trace levels of Hg(II). The developed method showed quantitative recoveries of Hg(II) with LOD = 0.21 pg mL−1 and RSD = 3–6% using cold vapor atomic fluorescence spectroscopy (CV-AFS) with a preconcentration factor greater than 250. PMID:24459417

A.I.-based real-time support for high performance aircraft operations

NASA Technical Reports Server (NTRS)

Vidal, J. J.

1985-01-01

Artificial intelligence (AI) based software and hardware concepts are applied to the handling system malfunctions during flight tests. A representation of malfunction procedure logic using Boolean normal forms are presented. The representation facilitates the automation of malfunction procedures and provides easy testing for the embedded rules. It also forms a potential basis for a parallel implementation in logic hardware. The extraction of logic control rules, from dynamic simulation and their adaptive revision after partial failure are examined. It uses a simplified 2-dimensional aircraft model with a controller that adaptively extracts control rules for directional thrust that satisfies a navigational goal without exceeding pre-established position and velocity limits. Failure recovery (rule adjusting) is examined after partial actuator failure. While this experiment was performed with primitive aircraft and mission models, it illustrates an important paradigm and provided complexity extrapolations for the proposed extraction of expertise from simulation, as discussed. The use of relaxation and inexact reasoning in expert systems was also investigated.

Determination of semicarbazide in fish by molecularly imprinted stir bar sorptive extraction coupled with high performance liquid chromatography.

PubMed

Tang, Tang; Wei, Fangdi; Wang, Xu; Ma, Yujie; Song, Yueyue; Ma, Yunsu; Song, Quan; Xu, Guanhong; Cen, Yao; Hu, Qin

2018-02-15

A novel molecularly imprinted stir bar (MI-SB) for sorptive extraction of semicarbazide (SEM) was prepared in present paper. The coating of the stir bar was characterized by scanning electron microscopy, Fourier-transform infrared spectroscopy, dynamic adsorption and static adsorption tests. The saturated adsorption of MI-SB was about 4 times over that of non-imprinted stir bar (NI-SB). The selectivity of MI-SB for SEM was much better than NI-SB. A method to determine SEM was established by coupling MI-SB sorptive extraction with HPLC-UV. The liner range was 1-100ng/mL for SEM with a correlation coefficient of 0.9985. The limit of detection was about 0.59ng/mL, which was below the minimum required performance limit of SEM in meat products regulated by European Union. The method was applied to the determination of SEM in fish samples with satisfactory results. Copyright © 2018 Elsevier B.V. All rights reserved.

Antimicrobial kinetics of Alstonia scholaris bark extract-mediated AgNPs

NASA Astrophysics Data System (ADS)

Supraja, N.; Prasad, T. N. V. K. V.; David, E.; Giridhara Krishna, T.

2016-06-01

Nanobiotechnology is considered as one of the important branches of nanotechnology, and research on synthesis of nanoscale materials, silver in particular, using plant and plant parts has been progressing rapidly. Herein, we used bark extract of Alstonia scholaris one of the most important medicinal plants to synthesize silver nanoparticles (AgNPs) which exhibited excellent antimicrobial properties against biofilm formed in drinking water PVC pipes. The biosynthesis of silver nanoparticles was done by treating 90 mL of 1 mM AgNO3 aqueous solution with 10 mL of 5 % bark extract. As-prepared silver nanoparticles were characterized using the biophysical techniques such as UV-Vis spectroscopy, Fourier transform infrared spectroscopy, X-ray diffraction, thermogravimetric analysis, transmission electron microscopy, and dynamic light scattering for the measurement of hydrodynamic diameter and zeta potential. The kinetics of the antimicrobial activity against PVC biofilm of prepared silver nanoparticles were done using comparative solution suspension time-killing assessments and which are evidenced in Epi-fluorescent microscopic observations.

Dynamic information processing states revealed through neurocognitive models of object semantics

PubMed Central

Clarke, Alex

2015-01-01

Recognising objects relies on highly dynamic, interactive brain networks to process multiple aspects of object information. To fully understand how different forms of information about objects are represented and processed in the brain requires a neurocognitive account of visual object recognition that combines a detailed cognitive model of semantic knowledge with a neurobiological model of visual object processing. Here we ask how specific cognitive factors are instantiated in our mental processes and how they dynamically evolve over time. We suggest that coarse semantic information, based on generic shared semantic knowledge, is rapidly extracted from visual inputs and is sufficient to drive rapid category decisions. Subsequent recurrent neural activity between the anterior temporal lobe and posterior fusiform supports the formation of object-specific semantic representations – a conjunctive process primarily driven by the perirhinal cortex. These object-specific representations require the integration of shared and distinguishing object properties and support the unique recognition of objects. We conclude that a valuable way of understanding the cognitive activity of the brain is though testing the relationship between specific cognitive measures and dynamic neural activity. This kind of approach allows us to move towards uncovering the information processing states of the brain and how they evolve over time. PMID:25745632

Algorithm for Stabilizing a POD-Based Dynamical System

NASA Technical Reports Server (NTRS)

Kalb, Virginia L.

2010-01-01

This algorithm provides a new way to improve the accuracy and asymptotic behavior of a low-dimensional system based on the proper orthogonal decomposition (POD). Given a data set representing the evolution of a system of partial differential equations (PDEs), such as the Navier-Stokes equations for incompressible flow, one may obtain a low-dimensional model in the form of ordinary differential equations (ODEs) that should model the dynamics of the flow. Temporal sampling of the direct numerical simulation of the PDEs produces a spatial time series. The POD extracts the temporal and spatial eigenfunctions of this data set. Truncated to retain only the most energetic modes followed by Galerkin projection of these modes onto the PDEs obtains a dynamical system of ordinary differential equations for the time-dependent behavior of the flow. In practice, the steps leading to this system of ODEs entail numerically computing first-order derivatives of the mean data field and the eigenfunctions, and the computation of many inner products. This is far from a perfect process, and often results in the lack of long-term stability of the system and incorrect asymptotic behavior of the model. This algorithm describes a new stabilization method that utilizes the temporal eigenfunctions to derive correction terms for the coefficients of the dynamical system to significantly reduce these errors.

Beta Oscillatory Dynamics in the Prefrontal and Superior Temporal Cortices Predict Spatial Working Memory Performance.

PubMed

Proskovec, Amy L; Wiesman, Alex I; Heinrichs-Graham, Elizabeth; Wilson, Tony W

2018-05-31

The oscillatory dynamics serving spatial working memory (SWM), and how such dynamics relate to performance, are poorly understood. To address these topics, the present study recruited 22 healthy adults to perform a SWM task during magnetoencephalography (MEG). The resulting MEG data were transformed into the time-frequency domain, and significant oscillatory responses were imaged using a beamformer. Voxel time series data were extracted from the cluster peaks to quantify the dynamics, while whole-brain partial correlation maps were computed to identify regions where oscillatory strength varied with accuracy on the SWM task. The results indicated transient theta oscillations in spatially distinct subregions of the prefrontal cortices at the onset of encoding and maintenance, which may underlie selection of goal-relevant information. Additionally, strong and persistent decreases in alpha and beta oscillations were observed throughout encoding and maintenance in parietal, temporal, and occipital regions, which could serve sustained attention and maintenance processes during SWM performance. The neuro-behavioral correlations revealed that beta activity within left dorsolateral prefrontal control regions and bilateral superior temporal integration regions was negatively correlated with SWM accuracy. Notably, this is the first study to employ a whole-brain approach to significantly link neural oscillations to behavioral performance in the context of SWM.

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.

Nonlinear Dynamics, Poor Data, and What to Make of Them?

NASA Astrophysics Data System (ADS)

Ghil, M.; Zaliapin, I. V.

2005-12-01

The analysis of univariate or multivariate time series provides crucial information to describe, understand, and predict variability in the geosciences. The discovery and implementation of a number of novel methods for extracting useful information from time series has recently revitalized this classical field of study. Considerable progress has also been made in interpreting the information so obtained in terms of dynamical systems theory. In this talk we will describe the connections between time series analysis and nonlinear dynamics, discuss signal-to-noise enhancement, and present some of the novel methods for spectral analysis. These fall into two broad categories: (i) methods that try to ferret out regularities of the time series; and (ii) methods aimed at describing the characteristics of irregular processes. The former include singular-spectrum analysis (SSA), the multi-taper method (MTM), and the maximum-entropy method (MEM). The various steps, as well as the advantages and disadvantages of these methods, will be illustrated by their application to several important climatic time series, such as the Southern Oscillation Index (SOI), paleoclimatic time series, and instrumental temperature time series. The SOI index captures major features of interannual climate variability and is used extensively in its prediction. The other time series cover interdecadal and millennial time scales. The second category includes the calculation of fractional dimension, leading Lyapunov exponents, and Hurst exponents. More recently, multi-trend analysis (MTA), binary-decomposition analysis (BDA), and related methods have attempted to describe the structure of time series that include both regular and irregular components. Within the time available, I will try to give a feeling for how these methods work, and how well.

Controlling transient chaos in deterministic flows with applications to electrical power systems and ecology

NASA Astrophysics Data System (ADS)

Dhamala, Mukeshwar; Lai, Ying-Cheng

1999-02-01

Transient chaos is a common phenomenon in nonlinear dynamics of many physical, biological, and engineering systems. In applications it is often desirable to maintain sustained chaos even in parameter regimes of transient chaos. We address how to sustain transient chaos in deterministic flows. We utilize a simple and practical method, based on extracting the fundamental dynamics from time series, to maintain chaos. The method can result in control of trajectories from almost all initial conditions in the original basin of the chaotic attractor from which transient chaos is created. We apply our method to three problems: (1) voltage collapse in electrical power systems, (2) species preservation in ecology, and (3) elimination of undesirable bursting behavior in a chemical reaction system.

Photogrammetry and Videogrammetry Methods Development for Solar Sail Structures. Masters Thesis awarded by George Washington Univ.

NASA Technical Reports Server (NTRS)

Pappa, Richard S. (Technical Monitor); Black, Jonathan T.

2003-01-01

This report discusses the development and application of metrology methods called photogrammetry and videogrammetry that make accurate measurements from photographs. These methods have been adapted for the static and dynamic characterization of gossamer structures, as four specific solar sail applications demonstrate. The applications prove that high-resolution, full-field, non-contact static measurements of solar sails using dot projection photogrammetry are possible as well as full-field, non-contact, dynamic characterization using dot projection videogrammetry. The accuracy of the measurement of the resonant frequencies and operating deflection shapes that were extracted surpassed expectations. While other non-contact measurement methods exist, they are not full-field and require significantly more time to take data.

Tracking and Motion Analysis of Crack Propagations in Crystals for Molecular Dynamics

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

Tsap, L V; Duchaineau, M; Goldgof, D B

2001-05-14

This paper presents a quantitative analysis for a discovery in molecular dynamics. Recent simulations have shown that velocities of crack propagations in crystals under certain conditions can become supersonic, which is contrary to classical physics. In this research, they present a framework for tracking and motion analysis of crack propagations in crystals. It includes line segment extraction based on Canny edge maps, feature selection based on physical properties, and subsequent tracking of primary and secondary wavefronts. This tracking is completely automated; it runs in real time on three 834-image sequences using forty 250 MHZ processors. Results supporting physical observations aremore » presented in terms of both feature tracking and velocity analysis.« less

The study on the parallel processing based time series correlation analysis of RBC membrane flickering in quantitative phase imaging

NASA Astrophysics Data System (ADS)

Lee, Minsuk; Won, Youngjae; Park, Byungjun; Lee, Seungrag

2017-02-01

Not only static characteristics but also dynamic characteristics of the red blood cell (RBC) contains useful information for the blood diagnosis. Quantitative phase imaging (QPI) can capture sample images with subnanometer scale depth resolution and millisecond scale temporal resolution. Various researches have been used QPI for the RBC diagnosis, and recently many researches has been developed to decrease the process time of RBC information extraction using QPI by the parallel computing algorithm, however previous studies are interested in the static parameters such as morphology of the cells or simple dynamic parameters such as root mean square (RMS) of the membrane fluctuations. Previously, we presented a practical blood test method using the time series correlation analysis of RBC membrane flickering with QPI. However, this method has shown that there is a limit to the clinical application because of the long computation time. In this study, we present an accelerated time series correlation analysis of RBC membrane flickering using the parallel computing algorithm. This method showed consistent fractal scaling exponent results of the surrounding medium and the normal RBC with our previous research.

Sequential reconstruction of driving-forces from nonlinear nonstationary dynamics

NASA Astrophysics Data System (ADS)

Güntürkün, Ulaş

2010-07-01

This paper describes a functional analysis-based method for the estimation of driving-forces from nonlinear dynamic systems. The driving-forces account for the perturbation inputs induced by the external environment or the secular variations in the internal variables of the system. The proposed algorithm is applicable to the problems for which there is too little or no prior knowledge to build a rigorous mathematical model of the unknown dynamics. We derive the estimator conditioned on the differentiability of the unknown system’s mapping, and smoothness of the driving-force. The proposed algorithm is an adaptive sequential realization of the blind prediction error method, where the basic idea is to predict the observables, and retrieve the driving-force from the prediction error. Our realization of this idea is embodied by predicting the observables one-step into the future using a bank of echo state networks (ESN) in an online fashion, and then extracting the raw estimates from the prediction error and smoothing these estimates in two adaptive filtering stages. The adaptive nature of the algorithm enables to retrieve both slowly and rapidly varying driving-forces accurately, which are illustrated by simulations. Logistic and Moran-Ricker maps are studied in controlled experiments, exemplifying chaotic state and stochastic measurement models. The algorithm is also applied to the estimation of a driving-force from another nonlinear dynamic system that is stochastic in both state and measurement equations. The results are judged by the posterior Cramer-Rao lower bounds. The method is finally put into test on a real-world application; extracting sun’s magnetic flux from the sunspot time series.

A Method for Extracting the Free Energy Surface and Conformational Dynamics of Fast-Folding Proteins from Single Molecule Photon Trajectories

PubMed Central

2015-01-01

Single molecule fluorescence spectroscopy holds the promise of providing direct measurements of protein folding free energy landscapes and conformational motions. However, fulfilling this promise has been prevented by technical limitations, most notably, the difficulty in analyzing the small packets of photons per millisecond that are typically recorded from individual biomolecules. Such limitation impairs the ability to accurately determine conformational distributions and resolve sub-millisecond processes. Here we develop an analytical procedure for extracting the conformational distribution and dynamics of fast-folding proteins directly from time-stamped photon arrival trajectories produced by single molecule FRET experiments. Our procedure combines the maximum likelihood analysis originally developed by Gopich and Szabo with a statistical mechanical model that describes protein folding as diffusion on a one-dimensional free energy surface. Using stochastic kinetic simulations, we thoroughly tested the performance of the method in identifying diverse fast-folding scenarios, ranging from two-state to one-state downhill folding, as a function of relevant experimental variables such as photon count rate, amount of input data, and background noise. The tests demonstrate that the analysis can accurately retrieve the original one-dimensional free energy surface and microsecond folding dynamics in spite of the sub-megahertz photon count rates and significant background noise levels of current single molecule fluorescence experiments. Therefore, our approach provides a powerful tool for the quantitative analysis of single molecule FRET experiments of fast protein folding that is also potentially extensible to the analysis of any other biomolecular process governed by sub-millisecond conformational dynamics. PMID:25988351

A Method for Extracting the Free Energy Surface and Conformational Dynamics of Fast-Folding Proteins from Single Molecule Photon Trajectories.

PubMed

Ramanathan, Ravishankar; Muñoz, Victor

2015-06-25

Single molecule fluorescence spectroscopy holds the promise of providing direct measurements of protein folding free energy landscapes and conformational motions. However, fulfilling this promise has been prevented by technical limitations, most notably, the difficulty in analyzing the small packets of photons per millisecond that are typically recorded from individual biomolecules. Such limitation impairs the ability to accurately determine conformational distributions and resolve sub-millisecond processes. Here we develop an analytical procedure for extracting the conformational distribution and dynamics of fast-folding proteins directly from time-stamped photon arrival trajectories produced by single molecule FRET experiments. Our procedure combines the maximum likelihood analysis originally developed by Gopich and Szabo with a statistical mechanical model that describes protein folding as diffusion on a one-dimensional free energy surface. Using stochastic kinetic simulations, we thoroughly tested the performance of the method in identifying diverse fast-folding scenarios, ranging from two-state to one-state downhill folding, as a function of relevant experimental variables such as photon count rate, amount of input data, and background noise. The tests demonstrate that the analysis can accurately retrieve the original one-dimensional free energy surface and microsecond folding dynamics in spite of the sub-megahertz photon count rates and significant background noise levels of current single molecule fluorescence experiments. Therefore, our approach provides a powerful tool for the quantitative analysis of single molecule FRET experiments of fast protein folding that is also potentially extensible to the analysis of any other biomolecular process governed by sub-millisecond conformational dynamics.

Directed Hidden-Code Extractor for Environment-Sensitive Malwares

NASA Astrophysics Data System (ADS)

Jia, Chunfu; Wang, Zhi; Lu, Kai; Liu, Xinhai; Liu, Xin

Malware writers often use packing technique to hide malicious payload. A number of dynamic unpacking tools are.designed in order to identify and extract the hidden code in the packed malware. However, such unpacking methods.are all based on a highly controlled environment that is vulnerable to various anti-unpacking techniques. If execution.environment is suspicious, malwares may stay inactive for a long time or stop execution immediately to evade.detection. In this paper, we proposed a novel approach that automatically reasons about the environment requirements.imposed by malware, then directs a unpacking tool to change the controlled environment to extract the hide code at.the new environment. The experimental results show that our approach significantly increases the resilience of the.traditional unpacking tools to environment-sensitive malware.

Acceleration of hepatobiliary dynamics in liver transplant donors.

PubMed

Aktaş, A; Koyuncu, A; Yalçin, H

2004-01-01

This study compared hepatobiliary scintigraphy findings in livers before and after liver graft donation to examine whether there is a change in hepatobiliary dynamics. Nine donors underwent hepatobiliary scintigraphy with intravenous injection of Tc-99m mebrofenin 1 day before and during the first week after left liver lobectomy. Five donors also underwent additional scintigraphy more than 1 year postsurgery. Images were acquired every second for the first minute, and then every minute for the next 40 minutes. Hepatic arterial perfusion index and portal perfusion index(PPI) were calculated from the images acquired during the first minute. For the function phase the computed parameters included: hepatic extraction efficiency, (HEE), time to appearance of activity in the intrahepatic biliary channels, and in the intestine, time to half maximal activity, and activity retained in the liver parenchyma at 40 minutes. Time to appearance of intrahepatic biliary channels and of intestinal activity was shorter among scintigraphies obtained within 1 week postsurgery compared to the preoperative values. Early after the operation HEE increased and PPI decreased significantly. Visual inspection of the scintigraphy scan obtained in all donors, within the first week postsurgery revealed hypertrophy of the right liver lobe. None of the patients showed progression of right lobe activity to the left side, even among scans obtained more than 1 year after donation. Reduced time to activity in the biliary channels and intestine and increased HEE suggest acceleration of hepatobiliary dynamics.

Observations & modeling of solar-wind/magnetospheric interactions

NASA Astrophysics Data System (ADS)

Hoilijoki, Sanni; Von Alfthan, Sebastian; Pfau-Kempf, Yann; Palmroth, Minna; Ganse, Urs

2016-07-01

The majority of the global magnetospheric dynamics is driven by magnetic reconnection, indicating the need to understand and predict reconnection processes and their global consequences. So far, global magnetospheric dynamics has been simulated using mainly magnetohydrodynamic (MHD) models, which are approximate but fast enough to be executed in real time or near-real time. Due to their fast computation times, MHD models are currently the only possible frameworks for space weather predictions. However, in MHD models reconnection is not treated kinetically. In this presentation we will compare the results from global kinetic (hybrid-Vlasov) and global MHD simulations. Both simulations are compared with in-situ measurements. We will show that the kinetic processes at the bow shock, in the magnetosheath and at the magnetopause affect global dynamics even during steady solar wind conditions. Foreshock processes cause an asymmetry in the magnetosheath plasma, indicating that the plasma entering the magnetosphere is not symmetrical on different sides of the magnetosphere. Behind the bow shock in the magnetosheath kinetic wave modes appear. Some of these waves propagate to the magnetopause and have an effect on the magnetopause reconnection. Therefore we find that kinetic phenomena have a significant role in the interaction between the solar wind and the magnetosphere. While kinetic models cannot be executed in real time currently, they could be used to extract heuristics to be added in the faster MHD models.

Automated reverse engineering of nonlinear dynamical systems

PubMed Central

Bongard, Josh; Lipson, Hod

2007-01-01

Complex nonlinear dynamics arise in many fields of science and engineering, but uncovering the underlying differential equations directly from observations poses a challenging task. The ability to symbolically model complex networked systems is key to understanding them, an open problem in many disciplines. Here we introduce for the first time a method that can automatically generate symbolic equations for a nonlinear coupled dynamical system directly from time series data. This method is applicable to any system that can be described using sets of ordinary nonlinear differential equations, and assumes that the (possibly noisy) time series of all variables are observable. Previous automated symbolic modeling approaches of coupled physical systems produced linear models or required a nonlinear model to be provided manually. The advance presented here is made possible by allowing the method to model each (possibly coupled) variable separately, intelligently perturbing and destabilizing the system to extract its less observable characteristics, and automatically simplifying the equations during modeling. We demonstrate this method on four simulated and two real systems spanning mechanics, ecology, and systems biology. Unlike numerical models, symbolic models have explanatory value, suggesting that automated “reverse engineering” approaches for model-free symbolic nonlinear system identification may play an increasing role in our ability to understand progressively more complex systems in the future. PMID:17553966