Wavelet extractor: A Bayesian well-tie and wavelet extraction program

NASA Astrophysics Data System (ADS)

Gunning, James; Glinsky, Michael E.

2006-06-01

We introduce a new open-source toolkit for the well-tie or wavelet extraction problem of estimating seismic wavelets from seismic data, time-to-depth information, and well-log suites. The wavelet extraction model is formulated as a Bayesian inverse problem, and the software will simultaneously estimate wavelet coefficients, other parameters associated with uncertainty in the time-to-depth mapping, positioning errors in the seismic imaging, and useful amplitude-variation-with-offset (AVO) related parameters in multi-stack extractions. It is capable of multi-well, multi-stack extractions, and uses continuous seismic data-cube interpolation to cope with the problem of arbitrary well paths. Velocity constraints in the form of checkshot data, interpreted markers, and sonic logs are integrated in a natural way. The Bayesian formulation allows computation of full posterior uncertainties of the model parameters, and the important problem of the uncertain wavelet span is addressed uses a multi-model posterior developed from Bayesian model selection theory. The wavelet extraction tool is distributed as part of the Delivery seismic inversion toolkit. A simple log and seismic viewing tool is included in the distribution. The code is written in Java, and thus platform independent, but the Seismic Unix (SU) data model makes the inversion particularly suited to Unix/Linux environments. It is a natural companion piece of software to Delivery, having the capacity to produce maximum likelihood wavelet and noise estimates, but will also be of significant utility to practitioners wanting to produce wavelet estimates for other inversion codes or purposes. The generation of full parameter uncertainties is a crucial function for workers wishing to investigate questions of wavelet stability before proceeding to more advanced inversion studies.

A Study of Al-Mn Transition Edge Sensor Engineering for Stability

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

George, E. M.; et al.

2013-11-10

The stability of Al-Mn transition edge sensor (TES) bolometers is studied as we vary the engineered TES transition, heat capacity, and/or coupling between the heat capacity and TES. We present thermal structure measurements of each of the 39 designs tested. The data is accurately fit by a two-body bolometer model, which allows us to extract the basic TES parameters that affect device stability. We conclude that parameters affecting device stability can be engineered for optimal device operation, and present the model parameters extracted for the different TES designs.

Optimization of microwave-assisted extraction of total extract, stevioside and rebaudioside-A from Stevia rebaudiana (Bertoni) leaves, using response surface methodology (RSM) and artificial neural network (ANN) modelling.

PubMed

Ameer, Kashif; Bae, Seong-Woo; Jo, Yunhee; Lee, Hyun-Gyu; Ameer, Asif; Kwon, Joong-Ho

2017-08-15

Stevia rebaudiana (Bertoni) consists of stevioside and rebaudioside-A (Reb-A). We compared response surface methodology (RSM) and artificial neural network (ANN) modelling for their estimation and predictive capabilities in building effective models with maximum responses. A 5-level 3-factor central composite design was used to optimize microwave-assisted extraction (MAE) to obtain maximum yield of target responses as a function of extraction time (X 1 : 1-5min), ethanol concentration, (X 2 : 0-100%) and microwave power (X 3 : 40-200W). Maximum values of the three output parameters: 7.67% total extract yield, 19.58mg/g stevioside yield, and 15.3mg/g Reb-A yield, were obtained under optimum extraction conditions of 4min X 1 , 75% X 2 , and 160W X 3 . The ANN model demonstrated higher efficiency than did the RSM model. Hence, RSM can demonstrate interaction effects of inherent MAE parameters on target responses, whereas ANN can reliably model the MAE process with better predictive and estimation capabilities. Copyright © 2017. Published by Elsevier Ltd.

User's Guide for the Agricultural Non-Point Source (AGNPS) Pollution Model Data Generator

USGS Publications Warehouse

Finn, Michael P.; Scheidt, Douglas J.; Jaromack, Gregory M.

2003-01-01

BACKGROUND Throughout this user guide, we refer to datasets that we used in conjunction with developing of this software for supporting cartographic research and producing the datasets to conduct research. However, this software can be used with these datasets or with more 'generic' versions of data of the appropriate type. For example, throughout the guide, we refer to national land cover data (NLCD) and digital elevation model (DEM) data from the U.S. Geological Survey (USGS) at a 30-m resolution, but any digital terrain model or land cover data at any appropriate resolution will produce results. Another key point to keep in mind is to use a consistent data resolution for all the datasets per model run. The U.S. Department of Agriculture (USDA) developed the Agricultural Nonpoint Source (AGNPS) pollution model of watershed hydrology in response to the complex problem of managing nonpoint sources of pollution. AGNPS simulates the behavior of runoff, sediment, and nutrient transport from watersheds that have agriculture as their prime use. The model operates on a cell basis and is a distributed parameter, event-based model. The model requires 22 input parameters. Output parameters are grouped primarily by hydrology, sediment, and chemical output (Young and others, 1995.) Elevation, land cover, and soil are the base data from which to extract the 22 input parameters required by the AGNPS. For automatic parameter extraction, follow the general process described in this guide of extraction from the geospatial data through the AGNPS Data Generator to generate input parameters required by the pollution model (Finn and others, 2002.)

Electromembrane extraction of zwitterionic compounds as acid or base: comparison of extraction behavior at acidic and basic pHs.

PubMed

Nojavan, Saeed; Pourahadi, Ahmad; Hosseiny Davarani, Saied Saeed; Morteza-Najarian, Amin; Beigzadeh Abbassi, Mojtaba

2012-10-01

This study has performed on electromembrane extraction (EME) of some zwitterionic compounds based on their acidic and basic properties. High performance liquid chromatography (HPLC) equipped with UV detection was used for determination of model compounds. Cetirizine (CTZ) and mesalazine (MS) were chosen as model compounds, and each of them was extracted from acidic (as a cation) and basic (as an anion) sample solutions, separately. 1-Octanol and 2-nitrophenyl octylether (NPOE) were used as the common supported liquid membrane (SLM) solvents. EME parameters, such as extraction time, extraction voltage and pH of donor and acceptor solutions were studied in details for cationic and anionic forms of each model compound and obtained results for two ionic forms (cationic and anionic) of each compound were compared together. Results showed that zwitterionic compounds could be extracted in both cationic and anionic forms. Moreover, it was found that the extraction of anionic form of each model compound could be done in low voltages when 1-octanol was used as the SLM solvent. Results showed that charge type was not highly effective on the extraction efficiency of model compounds whereas the position of charge within the molecule was the key parameter. In optimized conditions, enrichment factors (EF) of 27-60 that corresponded to recoveries ranging from 39 to 86% were achieved. Copyright © 2012 Elsevier B.V. All rights reserved.

A square-force cohesion model and its extraction from bulk measurements

NASA Astrophysics Data System (ADS)

Liu, Peiyuan; Lamarche, Casey; Kellogg, Kevin; Hrenya, Christine

2017-11-01

Cohesive particles remain poorly understood, with order of magnitude differences exhibited for prior, physical predictions of agglomerate size. A major obstacle lies in the absence of robust models of particle-particle cohesion, thereby precluding accurate prediction of the behavior of cohesive particles. Rigorous cohesion models commonly contain parameters related to surface roughness, to which cohesion shows extreme sensitivity. However, both roughness measurement and its distillation into these model parameters are challenging. Accordingly, we propose a ``square-force'' model, where cohesive force remains constant until a cut-off separation. Via DEM simulations, we demonstrate validity of the square-force model as surrogate of more rigorous models, when its two parameters are selected to match the two key quantities governing dense and dilute granular flows, namely maximum cohesive force and critical cohesive energy, respectively. Perhaps more importantly, we establish a method to extract the parameters in the square-force model via defluidization, due to its ability to isolate the effects of the two parameters. Thus, instead of relying on complicated scans of individual grains, determination of particle-particle cohesion from simple bulk measurements becomes feasible. Dow Corning Corporation.

Development of an electrical model for integrated magnetic inductors

NASA Astrophysics Data System (ADS)

Bechir, M. B.; Yaya, D. D.; Youssouf, M. K.; Soultan, M.; Capraro, S.; Siblini, A.; Chatelon, J. P.; Rousseau, J. J.

2014-07-01

Nowadays, the current trend consists in the development of new technologies with the aim of reducing volume, weight as well as production cost. With the aim of decreasing occupied component area, it will be interesting to use magnetic materials to confine the fields. Therefore, our works concern the modelling and the characterization of magnetic planar inductors. The proposed model is detailed for inductors fabricated with one magnetic layer. The model can take into account, the capacitance between turns and the capacitance between the last turn and the ground plane, the magnetic permeability, the skin and proximity effects of the conductors according to the frequency. The structure of optimization developed to extract the parameters of the model will be presented. Results of extracted parameters are compared with the simulation parameters. A good correlation is observed on Y11 and Y12 parameters on all the broad band frequency.

Simulation-based Extraction of Key Material Parameters from Atomic Force Microscopy

NASA Astrophysics Data System (ADS)

Alsafi, Huseen; Peninngton, Gray

Models for the atomic force microscopy (AFM) tip and sample interaction contain numerous material parameters that are often poorly known. This is especially true when dealing with novel material systems or when imaging samples that are exposed to complicated interactions with the local environment. In this work we use Monte Carlo methods to extract sample material parameters from the experimental AFM analysis of a test sample. The parameterized theoretical model that we use is based on the Virtual Environment for Dynamic AFM (VEDA) [1]. The extracted material parameters are then compared with the accepted values for our test sample. Using this procedure, we suggest a method that can be used to successfully determine unknown material properties in novel and complicated material systems. We acknowledge Fisher Endowment Grant support from the Jess and Mildred Fisher College of Science and Mathematics,Towson University.

Application of Modified Particle Swarm Optimization Method for Parameter Extraction of 2-D TEC Mapping

NASA Astrophysics Data System (ADS)

Toker, C.; Gokdag, Y. E.; Arikan, F.; Arikan, O.

2012-04-01

Ionosphere is a very important part of Space Weather. Modeling and monitoring of ionospheric variability is a major part of satellite communication, navigation and positioning systems. Total Electron Content (TEC), which is defined as the line integral of the electron density along a ray path, is one of the parameters to investigate the ionospheric variability. Dual-frequency GPS receivers, with their world wide availability and efficiency in TEC estimation, have become a major source of global and regional TEC modeling. When Global Ionospheric Maps (GIM) of International GPS Service (IGS) centers (http://iono.jpl.nasa.gov/gim.html) are investigated, it can be observed that regional ionosphere along the midlatitude regions can be modeled as a constant, linear or a quadratic surface. Globally, especially around the magnetic equator, the TEC surfaces resemble twisted and dispersed single centered or double centered Gaussian functions. Particle Swarm Optimization (PSO) proved itself as a fast converging and an effective optimization tool in various diverse fields. Yet, in order to apply this optimization technique into TEC modeling, the method has to be modified for higher efficiency and accuracy in extraction of geophysical parameters such as model parameters of TEC surfaces. In this study, a modified PSO (mPSO) method is applied to regional and global synthetic TEC surfaces. The synthetic surfaces that represent the trend and small scale variability of various ionospheric states are necessary to compare the performance of mPSO over number of iterations, accuracy in parameter estimation and overall surface reconstruction. The Cramer-Rao bounds for each surface type and model are also investigated and performance of mPSO are tested with respect to these bounds. For global models, the sample points that are used in optimization are obtained using IGS receiver network. For regional TEC models, regional networks such as Turkish National Permanent GPS Network (TNPGN-Active) receiver sites are used. The regional TEC models are grouped into constant (one parameter), linear (two parameters), and quadratic (six parameters) surfaces which are functions of latitude and longitude. Global models require seven parameters for single centered Gaussian and 13 parameters for double centered Gaussian function. The error criterion is the normalized percentage error for both the surface and the parameters. It is observed that mPSO is very successful in parameter extraction of various regional and global models. The normalized reconstruction error varies from 10-4 for constant surfaces to 10-3 for quadratic surfaces in regional models, sampled with regional networks. Even for the cases of a severe geomagnetic storm that affects measurements globally, with IGS network, the reconstruction error is on the order of 10-1 even though individual parameters have higher normalized errors. The modified PSO technique proved itself to be a useful tool for parameter extraction of more complicated TEC models. This study is supported by TUBITAK EEEAG under Grant No: 109E055.

Rate-equation modelling and ensemble approach to extraction of parameters for viral infection-induced cell apoptosis and necrosis

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

Domanskyi, Sergii; Schilling, Joshua E.; Privman, Vladimir, E-mail: privman@clarkson.edu

We develop a theoretical approach that uses physiochemical kinetics modelling to describe cell population dynamics upon progression of viral infection in cell culture, which results in cell apoptosis (programmed cell death) and necrosis (direct cell death). Several model parameters necessary for computer simulation were determined by reviewing and analyzing available published experimental data. By comparing experimental data to computer modelling results, we identify the parameters that are the most sensitive to the measured system properties and allow for the best data fitting. Our model allows extraction of parameters from experimental data and also has predictive power. Using the model wemore » describe interesting time-dependent quantities that were not directly measured in the experiment and identify correlations among the fitted parameter values. Numerical simulation of viral infection progression is done by a rate-equation approach resulting in a system of “stiff” equations, which are solved by using a novel variant of the stochastic ensemble modelling approach. The latter was originally developed for coupled chemical reactions.« less

Parameter extraction using global particle swarm optimization approach and the influence of polymer processing temperature on the solar cell parameters

NASA Astrophysics Data System (ADS)

Kumar, S.; Singh, A.; Dhar, A.

2017-08-01

The accurate estimation of the photovoltaic parameters is fundamental to gain an insight of the physical processes occurring inside a photovoltaic device and thereby to optimize its design, fabrication processes, and quality. A simulative approach of accurately determining the device parameters is crucial for cell array and module simulation when applied in practical on-field applications. In this work, we have developed a global particle swarm optimization (GPSO) approach to estimate the different solar cell parameters viz., ideality factor (η), short circuit current (Isc), open circuit voltage (Voc), shunt resistant (Rsh), and series resistance (Rs) with wide a search range of over ±100 % for each model parameter. After validating the accurateness and global search power of the proposed approach with synthetic and noisy data, we applied the technique to the extract the PV parameters of ZnO/PCDTBT based hybrid solar cells (HSCs) prepared under different annealing conditions. Further, we examine the variation of extracted model parameters to unveil the physical processes occurring when different annealing temperatures are employed during the device fabrication and establish the role of improved charge transport in polymer films from independent FET measurements. The evolution of surface morphology, optical absorption, and chemical compositional behaviour of PCDTBT co-polymer films as a function of processing temperature has also been captured in the study and correlated with the findings from the PV parameters extracted using GPSO approach.

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.

Modeling of layered anisotropic composite material based on effective medium theory

NASA Astrophysics Data System (ADS)

Bao, Yang; Song, Jiming

2018-04-01

In this paper, we present an efficient method to simulate multilayered anisotropic composite material with effective medium theory. Effective permittivity, permeability and orientation angle for a layered anisotropic composite medium are extracted with this equivalent model. We also derive analytical expressions for effective parameters and orientation angle with low frequency (LF) limit, which will be shown in detail. Numerical results are shown in comparing extracted effective parameters and orientation angle with analytical results from low frequency limit. Good agreements are achieved to demonstrate the accuracy of our efficient model.

Models for estimating photosynthesis parameters from in situ production profiles

NASA Astrophysics Data System (ADS)

Kovač, Žarko; Platt, Trevor; Sathyendranath, Shubha; Antunović, Suzana

2017-12-01

The rate of carbon assimilation in phytoplankton primary production models is mathematically prescribed with photosynthesis irradiance functions, which convert a light flux (energy) into a material flux (carbon). Information on this rate is contained in photosynthesis parameters: the initial slope and the assimilation number. The exactness of parameter values is crucial for precise calculation of primary production. Here we use a model of the daily production profile based on a suite of photosynthesis irradiance functions and extract photosynthesis parameters from in situ measured daily production profiles at the Hawaii Ocean Time-series station Aloha. For each function we recover parameter values, establish parameter distributions and quantify model skill. We observe that the choice of the photosynthesis irradiance function to estimate the photosynthesis parameters affects the magnitudes of parameter values as recovered from in situ profiles. We also tackle the problem of parameter exchange amongst the models and the effect it has on model performance. All models displayed little or no bias prior to parameter exchange, but significant bias following parameter exchange. The best model performance resulted from using optimal parameter values. Model formulation was extended further by accounting for spectral effects and deriving a spectral analytical solution for the daily production profile. The daily production profile was also formulated with time dependent growing biomass governed by a growth equation. The work on parameter recovery was further extended by exploring how to extract photosynthesis parameters from information on watercolumn production. It was demonstrated how to estimate parameter values based on a linearization of the full analytical solution for normalized watercolumn production and from the solution itself, without linearization. The paper complements previous works on photosynthesis irradiance models by analysing the skill and consistency of photosynthesis irradiance functions and parameters for modeling in situ production profiles. In light of the results obtained in this work we argue that the choice of the primary production model should reflect the available data and these models should be data driven regarding parameter estimation.

A risk-based approach to management of leachables utilizing statistical analysis of extractables.

PubMed

Stults, Cheryl L M; Mikl, Jaromir; Whelehan, Oliver; Morrical, Bradley; Duffield, William; Nagao, Lee M

2015-04-01

To incorporate quality by design concepts into the management of leachables, an emphasis is often put on understanding the extractable profile for the materials of construction for manufacturing disposables, container-closure, or delivery systems. Component manufacturing processes may also impact the extractable profile. An approach was developed to (1) identify critical components that may be sources of leachables, (2) enable an understanding of manufacturing process factors that affect extractable profiles, (3) determine if quantitative models can be developed that predict the effect of those key factors, and (4) evaluate the practical impact of the key factors on the product. A risk evaluation for an inhalation product identified injection molding as a key process. Designed experiments were performed to evaluate the impact of molding process parameters on the extractable profile from an ABS inhaler component. Statistical analysis of the resulting GC chromatographic profiles identified processing factors that were correlated with peak levels in the extractable profiles. The combination of statistically significant molding process parameters was different for different types of extractable compounds. ANOVA models were used to obtain optimal process settings and predict extractable levels for a selected number of compounds. The proposed paradigm may be applied to evaluate the impact of material composition and processing parameters on extractable profiles and utilized to manage product leachables early in the development process and throughout the product lifecycle.

On statistical analysis of factors affecting anthocyanin extraction from Ixora siamensis

NASA Astrophysics Data System (ADS)

Mat Nor, N. A.; Arof, A. K.

2016-10-01

This study focused on designing an experimental model in order to evaluate the influence of operative extraction parameters employed for anthocyanin extraction from Ixora siamensis on CIE color measurements (a*, b* and color saturation). Extractions were conducted at temperatures of 30, 55 and 80°C, soaking time of 60, 120 and 180 min using acidified methanol solvent with different trifluoroacetic acid (TFA) contents of 0.5, 1.75 and 3% (v/v). The statistical evaluation was performed by running analysis of variance (ANOVA) and regression calculation to investigate the significance of the generated model. Results show that the generated regression models adequately explain the data variation and significantly represented the actual relationship between the independent variables and the responses. Analysis of variance (ANOVA) showed high coefficient determination values (R2) of 0.9687 for a*, 0.9621 for b* and 0.9758 for color saturation, thus ensuring a satisfactory fit of the developed models with the experimental data. Interaction between TFA content and extraction temperature exhibited to the highest significant influence on CIE color parameter.

Multifractal Characterization of Geologic Noise for Improved UXO Detection and Discrimination

DTIC Science & Technology

2008-03-01

12 Recovery of the Universal Multifractal Parameters ...dipole-model to each magnetic anomaly and compares the extracted model parameters with a library of UXO items. They found that remnant magnetization...the survey parameters , and the geologic environment. In this pilot study we have focused on the multifractal representation of natural variations

Viability of using seismic data to predict hydrogeological parameters

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

Mela, K.

1997-10-01

Design of modem contaminant mitigation and fluid extraction projects make use of solutions from stochastic hydrogeologic models. These models rely heavily on the hydraulic parameters of hydraulic conductivity and the correlation length of hydraulic conductivity. Reliable values of these parameters must be acquired to successfully predict flow of fluids through the aquifer of interest. An inexpensive method of acquiring these parameters by use of seismic reflection surveying would be beneficial. Relationships between seismic velocity and porosity together with empirical observations relating porosity to permeability may lead to a method of extracting the correlation length of hydraulic conductivity from shallow highmore » resolution seismic data making the use of inexpensive high density data sets commonplace for these studies.« less

Study of optimal extraction conditions for achieving high yield and antioxidant activity of tomato seed oil.

PubMed

Shao, Dongyan; Atungulu, Griffiths G; Pan, Zhongli; Yue, Tianli; Zhang, Ang; Li, Xuan

2012-08-01

Value of tomato seed has not been fully recognized. The objectives of this research were to establish suitable processing conditions for extracting oil from tomato seed by using solvent, determine the impact of processing conditions on yield and antioxidant activity of extracted oil, and elucidate kinetics of the oil extraction process. Four processing parameters, including time, temperature, solvent-to-solid ratio and particle size were studied. A second order model was established to describe the oil extraction process. Based on the results, increasing temperature, solvent-to-solid ratio, and extraction time increased oil yield. In contrast, larger particle size reduced the oil yield. The recommended oil extraction conditions were 8 min of extraction time at temperature of 25 °C, solvent-to-solids ratio of 5/1 (v/w) and particle size of 0.38 mm, which gave oil yield of 20.32% with recovery rate of 78.56%. The DPPH scavenging activity of extracted oil was not significantly affected by the extraction parameters. The inhibitory concentration (IC(50) ) of tomato seed oil was 8.67 mg/mL which was notably low compared to most vegetable oils. A 2nd order model successfully described the kinetics of tomato oil extraction process and parameters of extraction kinetics including initial extraction rate (h), equilibrium concentration of oil (C(s) ), and the extraction rate constant (k) could be precisely predicted with R(2) of at least 0.957. The study revealed that tomato seed which is typically treated as a low value byproduct of tomato processing has great potential in producing oil with high antioxidant capability. The impact of processing conditions including time, temperature, solvent-to-solid ratio and particle size on yield, and antioxidant activity of extracted tomato seed oil are reported. Optimal conditions and models which describe the extraction process are recommended. The information is vital for determining the extraction processing conditions for industrial production of high quality tomato seed oil. Journal of Food Science © 2012 Institute of Food Technologists® No claim to original US government works.

A first approach to the distortion analysis of nonlinear analog circuits utilizing X-parameters

NASA Astrophysics Data System (ADS)

Weber, H.; Widemann, C.; Mathis, W.

2013-07-01

In this contribution a first approach to the distortion analysis of nonlinear 2-port-networks with X-parameters1 is presented. The X-parameters introduced by Verspecht and Root (2006) offer the possibility to describe nonlinear microwave 2-port-networks under large signal conditions. On the basis of X-parameter measurements with a nonlinear network analyzer (NVNA) behavioral models can be extracted for the networks. These models can be used to consider the nonlinear behavior during the design process of microwave circuits. The idea of the present work is to extract the behavioral models in order to describe the influence of interfering signals on the output behavior of the nonlinear circuits. Hereby, a simulator is used instead of a NVNA to extract the X-parameters. Assuming that the interfering signals are relatively small compared to the nominal input signal, the output signal can be described as a superposition of the effects of each input signal. In order to determine the functional correlation between the scattering variables, a polynomial dependency is assumed. The required datasets for the approximation of the describing functions are simulated by a directional coupler model in Cadence Design Framework. The polynomial coefficients are obtained by a least-square method. The resulting describing functions can be used to predict the system's behavior under certain conditions as well as the effects of the interfering signal on the output signal. 1 X-parameter is a registered trademark of Agilent Technologies, Inc.

Statistical modeling of ecosystem respiration using eddy covariance data: Maximum likelihood parameter estimation, and Monte Carlo simulation of model and parameter uncertainty, applied to three simple models

Treesearch

Andrew D. Richardson; David Y. Hollinger; David Y. Hollinger

2005-01-01

Whether the goal is to fill gaps in the flux record, or to extract physiological parameters from eddy covariance data, researchers are frequently interested in fitting simple models of ecosystem physiology to measured data. Presently, there is no consensus on the best models to use, or the ideal optimization criteria. We demonstrate that, given our estimates of the...

Application of genetic algorithm in modeling on-wafer inductors for up to 110 Ghz

NASA Astrophysics Data System (ADS)

Liu, Nianhong; Fu, Jun; Liu, Hui; Cui, Wenpu; Liu, Zhihong; Liu, Linlin; Zhou, Wei; Wang, Quan; Guo, Ao

2018-05-01

In this work, the genetic algorithm has been introducted into parameter extraction for on-wafer inductors for up to 110 GHz millimeter-wave operations, and nine independent parameters of the equivalent circuit model are optimized together. With the genetic algorithm, the model with the optimized parameters gives a better fitting accuracy than the preliminary parameters without optimization. Especially, the fitting accuracy of the Q value achieves a significant improvement after the optimization.

Multi-criteria optimization for ultrasonic-assisted extraction of antioxidants from Pericarpium Citri Reticulatae using response surface methodology, an activity-based approach.

PubMed

Zeng, Shanshan; Wang, Lu; Zhang, Lei; Qu, Haibin; Gong, Xingchu

2013-06-01

An activity-based approach to optimize the ultrasonic-assisted extraction of antioxidants from Pericarpium Citri Reticulatae (Chenpi in Chinese) was developed. Response surface optimization based on a quantitative composition-activity relationship model showed the relationships among product chemical composition, antioxidant activity of extract, and parameters of extraction process. Three parameters of ultrasonic-assisted extraction, including the ethanol/water ratio, Chenpi amount, and alkaline amount, were investigated to give optimum extraction conditions for antioxidants of Chenpi: ethanol/water 70:30 v/v, Chenpi amount of 10 g, and alkaline amount of 28 mg. The experimental antioxidant yield under the optimum conditions was found to be 196.5 mg/g Chenpi, and the antioxidant activity was 2023.8 μmol Trolox equivalents/g of the Chenpi powder. The results agreed well with the second-order polynomial regression model. This presented approach promised great application potentials in both food and pharmaceutical industries. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A compact model and direct parameters extraction techniques For amorphous gallium-indium-zinc-oxide thin film transistors

NASA Astrophysics Data System (ADS)

Moldovan, Oana; Castro-Carranza, Alejandra; Cerdeira, Antonio; Estrada, Magali; Barquinha, Pedro; Martins, Rodrigo; Fortunato, Elvira; Miljakovic, Slobodan; Iñiguez, Benjamin

2016-12-01

An advanced compact and analytical drain current model for the amorphous gallium indium zinc oxide (GIZO) thin film transistors (TFTs) is proposed. Its output saturation behavior is improved by introducing a new asymptotic function. All model parameters were extracted using an adapted version of the Universal Method and Extraction Procedure (UMEM) applied for the first time for GIZO devices in a simple and direct form. We demonstrate the correct behavior of the model for negative VDS, a necessity for a complete compact model. In this way we prove the symmetry of source and drain electrodes and extend the range of applications to both signs of VDS. The model, in Verilog-A code, is implemented in Electronic Design Automation (EDA) tools, such as Smart Spice, and compared with measurements of TFTs. It describes accurately the experimental characteristics in the whole range of GIZO TFTs operation, making the model suitable for the design of circuits using these types of devices.

A novel multiple batch extraction test to assess contaminant mobilization from porous waste materials

NASA Astrophysics Data System (ADS)

Iden, S. C.; Durner, W.; Delay, M.; Frimmel, F. H.

2009-04-01

Contaminated porous materials, like soils, dredged sediments or waste materials must be tested before they can be used as filling materials in order to minimize the risk of groundwater pollution. We applied a multiple batch extraction test at varying liquid-to-solid (L/S) ratios to a demolition waste material and a municipal waste incineration product and investigated the release of chloride, sulphate, sodium, copper, chromium and dissolved organic carbon from both waste materials. The liquid phase test concentrations were used to estimate parameters of a relatively simple mass balance model accounting for equilibrium partitioning. The model parameters were estimated within a Bayesian framework by applying an efficient MCMC sampler and the uncertainties of the model parameters and model predictions were quantified. We tested isotherms of the linear, Freundlich and Langmuir type and selected the optimal isotherm model by use of the Deviance Information Criterion (DIC). Both the excellent fit to the experimental data and a comparison between the model-predicted and independently measured concentrations at the L/S ratios of 0.25 and 0.5 L/kg demonstrate the applicability of the model for almost all studied substances and both waste materials. We conclude that batch extraction tests at varying L/S ratios provide, at moderate experimental cost, a powerful complement to established test designs like column leaching or single batch extraction tests. The method constitutes an important tool in risk assessments, because concentrations at soil water contents representative for the field situation can be predicted from easier-to-obtain test concentrations at larger L/S ratios. This helps to circumvent the experimental difficulties of the soil saturation extract and eliminates the need to apply statistical approaches to predict such representative concentrations which have been shown to suffer dramatically from poor correlations.

Intensification of extraction of curcumin from Curcuma amada using ultrasound assisted approach: Effect of different operating parameters.

PubMed

Shirsath, S R; Sable, S S; Gaikwad, S G; Sonawane, S H; Saini, D R; Gogate, P R

2017-09-01

Curcumin, a dietary phytochemical, has been extracted from rhizomes of Curcuma amada using ultrasound assisted extraction (UAE) and the results compared with the conventional extraction approach to establish the process intensification benefits. The effect of operating parameters such as type of solvent, extraction time, extraction temperature, solid to solvent ratio, particle size and ultrasonic power on the extraction yield have been investigated in details for the approach UAE. The maximum extraction yield as 72% was obtained in 1h under optimized conditions of 35°C temperature, solid to solvent ratio of 1:25, particle size of 0.09mm, ultrasonic power of 250W and ultrasound frequency of 22kHz with ethanol as the solvent. The obtained yield was significantly higher as compared to the batch extraction where only about 62% yield was achieved in 8h of treatment. Peleg's model was used to describe the kinetics of UAE and the model showed a good agreement with the experimental results. Overall, ultrasound has been established to be a green process for extraction of curcumin with benefits of reduction in time as compared to batch extraction and the operating temperature as compared to Soxhlet extraction. Copyright © 2017. Published by Elsevier B.V.

Classifying Physical Morphology of Cocoa Beans Digital Images using Multiclass Ensemble Least-Squares Support Vector Machine

NASA Astrophysics Data System (ADS)

Lawi, Armin; Adhitya, Yudhi

2018-03-01

The objective of this research is to determine the quality of cocoa beans through morphology of their digital images. Samples of cocoa beans were scattered on a bright white paper under a controlled lighting condition. A compact digital camera was used to capture the images. The images were then processed to extract their morphological parameters. Classification process begins with an analysis of cocoa beans image based on morphological feature extraction. Parameters for extraction of morphological or physical feature parameters, i.e., Area, Perimeter, Major Axis Length, Minor Axis Length, Aspect Ratio, Circularity, Roundness, Ferret Diameter. The cocoa beans are classified into 4 groups, i.e.: Normal Beans, Broken Beans, Fractured Beans, and Skin Damaged Beans. The model of classification used in this paper is the Multiclass Ensemble Least-Squares Support Vector Machine (MELS-SVM), a proposed improvement model of SVM using ensemble method in which the separate hyperplanes are obtained by least square approach and the multiclass procedure uses One-Against- All method. The result of our proposed model showed that the classification with morphological feature input parameters were accurately as 99.705% for the four classes, respectively.

Bio-inspired optimization algorithms for optical parameter extraction of dielectric materials: A comparative study

NASA Astrophysics Data System (ADS)

Ghulam Saber, Md; Arif Shahriar, Kh; Ahmed, Ashik; Hasan Sagor, Rakibul

2016-10-01

Particle swarm optimization (PSO) and invasive weed optimization (IWO) algorithms are used for extracting the modeling parameters of materials useful for optics and photonics research community. These two bio-inspired algorithms are used here for the first time in this particular field to the best of our knowledge. The algorithms are used for modeling graphene oxide and the performances of the two are compared. Two objective functions are used for different boundary values. Root mean square (RMS) deviation is determined and compared.

[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.

Optimization of Bioactive Ingredient Extraction from Chinese Herbal Medicine Glycyrrhiza glabra: A Comparative Study of Three Optimization Models

PubMed Central

Li, Xiaohong; Zhang, Yuyan

2018-01-01

The ultraviolet spectrophotometric method is often used for determining the content of glycyrrhizic acid from Chinese herbal medicine Glycyrrhiza glabra. Based on the traditional single variable approach, four extraction parameters of ammonia concentration, ethanol concentration, circumfluence time, and liquid-solid ratio are adopted as the independent extraction variables. In the present work, central composite design of four factors and five levels is applied to design the extraction experiments. Subsequently, the prediction models of response surface methodology, artificial neural networks, and genetic algorithm-artificial neural networks are developed to analyze the obtained experimental data, while the genetic algorithm is utilized to find the optimal extraction parameters for the above well-established models. It is found that the optimization of extraction technology is presented as ammonia concentration 0.595%, ethanol concentration 58.45%, return time 2.5 h, and liquid-solid ratio 11.065 : 1. Under these conditions, the model predictive value is 381.24 mg, the experimental average value is 376.46 mg, and the expectation discrepancy is 4.78 mg. For the first time, a comparative study of these three approaches is conducted for the evaluation and optimization of the effects of the extraction independent variables. Furthermore, it is demonstrated that the combinational method of genetic algorithm and artificial neural networks provides a more reliable and more accurate strategy for design and optimization of glycyrrhizic acid extraction from Glycyrrhiza glabra. PMID:29887907

Optimization of Bioactive Ingredient Extraction from Chinese Herbal Medicine Glycyrrhiza glabra: A Comparative Study of Three Optimization Models.

PubMed

Yu, Li; Jin, Weifeng; Li, Xiaohong; Zhang, Yuyan

2018-01-01

The ultraviolet spectrophotometric method is often used for determining the content of glycyrrhizic acid from Chinese herbal medicine Glycyrrhiza glabra . Based on the traditional single variable approach, four extraction parameters of ammonia concentration, ethanol concentration, circumfluence time, and liquid-solid ratio are adopted as the independent extraction variables. In the present work, central composite design of four factors and five levels is applied to design the extraction experiments. Subsequently, the prediction models of response surface methodology, artificial neural networks, and genetic algorithm-artificial neural networks are developed to analyze the obtained experimental data, while the genetic algorithm is utilized to find the optimal extraction parameters for the above well-established models. It is found that the optimization of extraction technology is presented as ammonia concentration 0.595%, ethanol concentration 58.45%, return time 2.5 h, and liquid-solid ratio 11.065 : 1. Under these conditions, the model predictive value is 381.24 mg, the experimental average value is 376.46 mg, and the expectation discrepancy is 4.78 mg. For the first time, a comparative study of these three approaches is conducted for the evaluation and optimization of the effects of the extraction independent variables. Furthermore, it is demonstrated that the combinational method of genetic algorithm and artificial neural networks provides a more reliable and more accurate strategy for design and optimization of glycyrrhizic acid extraction from Glycyrrhiza glabra .

Novel mathematic models for quantitative transitivity of quality-markers in extraction process of the Buyanghuanwu decoction.

PubMed

Zhang, Yu-Tian; Xiao, Mei-Feng; Deng, Kai-Wen; Yang, Yan-Tao; Zhou, Yi-Qun; Zhou, Jin; He, Fu-Yuan; Liu, Wen-Long

2018-06-01

Nowadays, to research and formulate an efficiency extraction system for Chinese herbal medicine, scientists have always been facing a great challenge for quality management, so that the transitivity of Q-markers in quantitative analysis of TCM was proposed by Prof. Liu recently. In order to improve the quality of extraction from raw medicinal materials for clinical preparations, a series of integrated mathematic models for transitivity of Q-markers in quantitative analysis of TCM were established. Buyanghuanwu decoction (BYHWD) was a commonly TCMs prescription, which was used to prevent and treat the ischemic heart and brain diseases. In this paper, we selected BYHWD as an extraction experimental subject to study the quantitative transitivity of TCM. Based on theory of Fick's Rule and Noyes-Whitney equation, novel kinetic models were established for extraction of active components. Meanwhile, fitting out kinetic equations of extracted models and then calculating the inherent parameters in material piece and Q-marker quantitative transfer coefficients, which were considered as indexes to evaluate transitivity of Q-markers in quantitative analysis of the extraction process of BYHWD. HPLC was applied to screen and analyze the potential Q-markers in the extraction process. Fick's Rule and Noyes-Whitney equation were adopted for mathematically modeling extraction process. Kinetic parameters were fitted and calculated by the Statistical Program for Social Sciences 20.0 software. The transferable efficiency was described and evaluated by potential Q-markers transfer trajectory via transitivity availability AUC, extraction ratio P, and decomposition ratio D respectively. The Q-marker was identified with AUC, P, D. Astragaloside IV, laetrile, paeoniflorin, and ferulic acid were studied as potential Q-markers from BYHWD. The relative technologic parameters were presented by mathematic models, which could adequately illustrate the inherent properties of raw materials preparation and affection of Q-markers transitivity in equilibrium processing. AUC, P, D for potential Q-markers of AST-IV, laetrile, paeoniflorin, and FA were obtained, with the results of 289.9 mAu s, 46.24%, 22.35%; 1730 mAu s, 84.48%, 1.963%; 5600 mAu s, 70.22%, 0.4752%; 7810 mAu s, 24.29%, 4.235%, respectively. The results showed that the suitable Q-markers were laetrile and paeoniflorin in our study, which exhibited acceptable traceability and transitivity in the extraction process of TCMs. Therefore, these novel mathematic models might be developed as a new standard to control TCMs quality process from raw medicinal materials to product manufacturing. Copyright © 2018 Elsevier GmbH. All rights reserved.

Capturing Revolute Motion and Revolute Joint Parameters with Optical Tracking

NASA Astrophysics Data System (ADS)

Antonya, C.

2017-12-01

Optical tracking of users and various technical systems are becoming more and more popular. It consists of analysing sequence of recorded images using video capturing devices and image processing algorithms. The returned data contains mainly point-clouds, coordinates of markers or coordinates of point of interest. These data can be used for retrieving information related to the geometry of the objects, but also to extract parameters for the analytical model of the system useful in a variety of computer aided engineering simulations. The parameter identification of joints deals with extraction of physical parameters (mainly geometric parameters) for the purpose of constructing accurate kinematic and dynamic models. The input data are the time-series of the marker’s position. The least square method was used for fitting the data into different geometrical shapes (ellipse, circle, plane) and for obtaining the position and orientation of revolute joins.

Optimization of extraction of linarin from Flos chrysanthemi indici by response surface methodology and artificial neural network.

PubMed

Pan, Hongye; Zhang, Qing; Cui, Keke; Chen, Guoquan; Liu, Xuesong; Wang, Longhu

2017-05-01

The extraction of linarin from Flos chrysanthemi indici by ethanol was investigated. Two modeling techniques, response surface methodology and artificial neural network, were adopted to optimize the process parameters, such as, ethanol concentration, extraction period, extraction frequency, and solvent to material ratio. We showed that both methods provided good predictions, but artificial neural network provided a better and more accurate result. The optimum process parameters include, ethanol concentration of 74%, extraction period of 2 h, extraction three times, solvent to material ratio of 12 mL/g. The experiment yield of linarin was 90.5% that deviated less than 1.6% from that obtained by predicted result. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Modeling stress–strain state of rock mass under mining of complex-shape extraction pillar

NASA Astrophysics Data System (ADS)

Fryanov, VN; Pavlova, LD

2018-03-01

Based on the results of numerical modeling of stresses and strains in rock mass, geomechanical parameters of development workings adjacent to coal face operation area are provided for multi-entry preparation and extraction of flat seams with production faces of variable length. The negative effects on the geomechanical situation during the transition from the longwall to shortwall mining in a fully mechanized extraction face are found.

A fast and efficient method for device level layout analysis

NASA Astrophysics Data System (ADS)

Dong, YaoQi; Zou, Elaine; Pang, Jenny; Huang, Lucas; Yang, Legender; Zhang, Chunlei; Du, Chunshan; Hu, Xinyi; Wan, Qijian

2017-03-01

There is an increasing demand for device level layout analysis, especially as technology advances. The analysis is to study standard cells by extracting and classifying critical dimension parameters. There are couples of parameters to extract, like channel width, length, gate to active distance, and active to adjacent active distance, etc. for 14nm technology, there are some other parameters that are cared about. On the one hand, these parameters are very important for studying standard cell structures and spice model development with the goal of improving standard cell manufacturing yield and optimizing circuit performance; on the other hand, a full chip device statistics analysis can provide useful information to diagnose the yield issue. Device analysis is essential for standard cell customization and enhancements and manufacturability failure diagnosis. Traditional parasitic parameters extraction tool like Calibre xRC is powerful but it is not sufficient for this device level layout analysis application as engineers would like to review, classify and filter out the data more easily. This paper presents a fast and efficient method based on Calibre equation-based DRC (eqDRC). Equation-based DRC extends the traditional DRC technology to provide a flexible programmable modeling engine which allows the end user to define grouped multi-dimensional feature measurements using flexible mathematical expressions. This paper demonstrates how such an engine and its programming language can be used to implement critical device parameter extraction. The device parameters are extracted and stored in a DFM database which can be processed by Calibre YieldServer. YieldServer is data processing software that lets engineers query, manipulate, modify, and create data in a DFM database. These parameters, known as properties in eqDRC language, can be annotated back to the layout for easily review. Calibre DesignRev can create a HTML formatted report of the results displayed in Calibre RVE which makes it easy to share results among groups. This method has been proven and used in SMIC PDE team and SPICE team.

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.

[Extraction Optimization of Rhizome of Curcuma longa by Response Surface Methodology and Support Vector Regression].

PubMed

Zhou, Pei-pei; Shan, Jin-feng; Jiang, Jian-lan

2015-12-01

To optimize the optimal microwave-assisted extraction method of curcuminoids from Curcuma longa. On the base of single factor experiment, the ethanol concentration, the ratio of liquid to solid and the microwave time were selected for further optimization. Support Vector Regression (SVR) and Central Composite Design-Response Surface Methodology (CCD) algorithm were utilized to design and establish models respectively, while Particle Swarm Optimization (PSO) was introduced to optimize the parameters of SVR models and to search optimal points of models. The evaluation indicator, the sum of curcumin, demethoxycurcumin and bisdemethoxycurcumin by HPLC, were used. The optimal parameters of microwave-assisted extraction were as follows: ethanol concentration of 69%, ratio of liquid to solid of 21 : 1, microwave time of 55 s. On those conditions, the sum of three curcuminoids was 28.97 mg/g (per gram of rhizomes powder). Both the CCD model and the SVR model were credible, for they have predicted the similar process condition and the deviation of yield were less than 1.2%.

Reactive decontamination of absorbing thin film polymer coatings: model development and parameter determination

NASA Astrophysics Data System (ADS)

Varady, Mark; Mantooth, Brent; Pearl, Thomas; Willis, Matthew

2014-03-01

A continuum model of reactive decontamination in absorbing polymeric thin film substrates exposed to the chemical warfare agent O-ethyl S-[2-(diisopropylamino)ethyl] methylphosphonothioate (known as VX) was developed to assess the performance of various decontaminants. Experiments were performed in conjunction with an inverse analysis method to obtain the necessary model parameters. The experiments involved contaminating a substrate with a fixed VX exposure, applying a decontaminant, followed by a time-resolved, liquid phase extraction of the absorbing substrate to measure the residual contaminant by chromatography. Decontamination model parameters were uniquely determined using the Levenberg-Marquardt nonlinear least squares fitting technique to best fit the experimental time evolution of extracted mass. The model was implemented numerically in both a 2D axisymmetric finite element program and a 1D finite difference code, and it was found that the more computationally efficient 1D implementation was sufficiently accurate. The resulting decontamination model provides an accurate quantification of contaminant concentration profile in the material, which is necessary to assess exposure hazards.

Extracting TSK-type Neuro-Fuzzy model using the Hunting search algorithm

NASA Astrophysics Data System (ADS)

Bouzaida, Sana; Sakly, Anis; M'Sahli, Faouzi

2014-01-01

This paper proposes a Takagi-Sugeno-Kang (TSK) type Neuro-Fuzzy model tuned by a novel metaheuristic optimization algorithm called Hunting Search (HuS). The HuS algorithm is derived based on a model of group hunting of animals such as lions, wolves, and dolphins when looking for a prey. In this study, the structure and parameters of the fuzzy model are encoded into a particle. Thus, the optimal structure and parameters are achieved simultaneously. The proposed method was demonstrated through modeling and control problems, and the results have been compared with other optimization techniques. The comparisons indicate that the proposed method represents a powerful search approach and an effective optimization technique as it can extract the accurate TSK fuzzy model with an appropriate number of rules.

Reactive extraction of lactic acid with trioctylamine/methylene chloride/n-hexane

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

Han, D.H.; Hong, W.H.

The trioctylamine (TOA)/methylene chloride (MC)/n-hexane system was used as the extraction agent for the extraction of lactic acid. Curves of equilibrium and hydration were obtained at various temperatures and concentrations of TOA. A modified mass action model was proposed to interpret the equilibrium and the hydration curves. The reaction mechanism and the corresponding parameters which best represent the equilibrium data were estimated, and the concentration of water in the organic phase was predicted by inserting the parameters into the simple mathematical equation of the modified model. The concentration of MC and the change of temperature were important factors for themore » extraction and the stripping process. The stripping was performed by a simple distillation which was a combination of temperature-swing regeneration and diluent-swing regeneration. The type of inactive diluent has no influence on the stripping. The stripping efficiencies were about 70%.« less

[Establishment of the mathematic model of total quantum statistical moment standard similarity for application to medical theoretical research].

PubMed

He, Fu-yuan; Deng, Kai-wen; Huang, Sheng; Liu, Wen-long; Shi, Ji-lian

2013-09-01

The paper aims to elucidate and establish a new mathematic model: the total quantum statistical moment standard similarity (TQSMSS) on the base of the original total quantum statistical moment model and to illustrate the application of the model to medical theoretical research. The model was established combined with the statistical moment principle and the normal distribution probability density function properties, then validated and illustrated by the pharmacokinetics of three ingredients in Buyanghuanwu decoction and of three data analytical method for them, and by analysis of chromatographic fingerprint for various extracts with different solubility parameter solvents dissolving the Buyanghanwu-decoction extract. The established model consists of four mainly parameters: (1) total quantum statistical moment similarity as ST, an overlapped area by two normal distribution probability density curves in conversion of the two TQSM parameters; (2) total variability as DT, a confidence limit of standard normal accumulation probability which is equal to the absolute difference value between the two normal accumulation probabilities within integration of their curve nodical; (3) total variable probability as 1-Ss, standard normal distribution probability within interval of D(T); (4) total variable probability (1-beta)alpha and (5) stable confident probability beta(1-alpha): the correct probability to make positive and negative conclusions under confident coefficient alpha. With the model, we had analyzed the TQSMS similarities of pharmacokinetics of three ingredients in Buyanghuanwu decoction and of three data analytical methods for them were at range of 0.3852-0.9875 that illuminated different pharmacokinetic behaviors of each other; and the TQSMS similarities (ST) of chromatographic fingerprint for various extracts with different solubility parameter solvents dissolving Buyanghuanwu-decoction-extract were at range of 0.6842-0.999 2 that showed different constituents with various solvent extracts. The TQSMSS can characterize the sample similarity, by which we can quantitate the correct probability with the test of power under to make positive and negative conclusions no matter the samples come from same population under confident coefficient a or not, by which we can realize an analysis at both macroscopic and microcosmic levels, as an important similar analytical method for medical theoretical research.

Maximum likelihood: Extracting unbiased information from complex networks

NASA Astrophysics Data System (ADS)

Garlaschelli, Diego; Loffredo, Maria I.

2008-07-01

The choice of free parameters in network models is subjective, since it depends on what topological properties are being monitored. However, we show that the maximum likelihood (ML) principle indicates a unique, statistically rigorous parameter choice, associated with a well-defined topological feature. We then find that, if the ML condition is incompatible with the built-in parameter choice, network models turn out to be intrinsically ill defined or biased. To overcome this problem, we construct a class of safely unbiased models. We also propose an extension of these results that leads to the fascinating possibility to extract, only from topological data, the “hidden variables” underlying network organization, making them “no longer hidden.” We test our method on World Trade Web data, where we recover the empirical gross domestic product using only topological information.

Multivariate analysis and extraction of parameters in resistive RAMs using the Quantum Point Contact model

NASA Astrophysics Data System (ADS)

Roldán, J. B.; Miranda, E.; González-Cordero, G.; García-Fernández, P.; Romero-Zaliz, R.; González-Rodelas, P.; Aguilera, A. M.; González, M. B.; Jiménez-Molinos, F.

2018-01-01

A multivariate analysis of the parameters that characterize the reset process in Resistive Random Access Memory (RRAM) has been performed. The different correlations obtained can help to shed light on the current components that contribute in the Low Resistance State (LRS) of the technology considered. In addition, a screening method for the Quantum Point Contact (QPC) current component is presented. For this purpose, the second derivative of the current has been obtained using a novel numerical method which allows determining the QPC model parameters. Once the procedure is completed, a whole Resistive Switching (RS) series of thousands of curves is studied by means of a genetic algorithm. The extracted QPC parameter distributions are characterized in depth to get information about the filamentary pathways associated with LRS in the low voltage conduction regime.

Solid phase extraction of copper(II) by fixed bed procedure on cation exchange complexing resins.

PubMed

Pesavento, Maria; Sturini, Michela; D'Agostino, Girolamo; Biesuz, Raffaela

2010-02-19

The efficiency of the metal ion recovery by solid phase extraction (SPE) in complexing resins columns is predicted by a simple model based on two parameters reflecting the sorption equilibria and kinetics of the metal ion on the considered resin. The parameter related to the adsorption equilibria was evaluated by the Gibbs-Donnan model, and that related to the kinetics by assuming that the ion exchange is the adsorption rate determining step. The predicted parameters make it possible to evaluate the breakthrough volume of the considered metal ion, Cu(II), from different kinds of complexing resins, and at different conditions, such as acidity and ionic composition. Copyright 2009. Published by Elsevier B.V.

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.

Extraction of Antioxidant Phenolic Compounds from Brewer’s Spent Grain: Optimization and Kinetics Modeling

PubMed Central

Sologubik, Carlos A.; Fernández, María B.; Manrique, Guillermo D.

2018-01-01

The kinetics of polyphenol extraction from brewer’s spent grain (BSG), using a batch system, ultrasound assistance, and microwave assistance and the evolution of antioxidant capacity of these extracts over time, were studied. The main parameters of extraction employed in the batch system were evaluated, and, by applying response surface analysis, the following optimal conditions were obtained: Liquid/solid ratio of 30:1 mL/g at 80 °C, using 72% (v/v) ethanol:water as the solvent system. Under these optimized conditions, ultrasound assistance demonstrated the highest extraction rate and equilibrium yield, as well as shortest extraction times, followed by microwave assistance. Among the mathematical models used, Patricelli’s model proved the most suitable for describing the extraction kinetics for each method tested, and is therefore able to predict the response values and estimate the extraction rates and potential maximum yields in each case. PMID:29570683

Modeling of the Kinetics of Supercritical Fluid Extraction of Lipids from Microalgae with Emphasis on Extract Desorption

PubMed Central

Sovová, Helena; Nobre, Beatriz P.; Palavra, António

2016-01-01

Microalgae contain valuable biologically active lipophilic substances such as omega-3 fatty acids and carotenoids. In contrast to the recovery of vegetable oils from seeds, where the extraction with supercritical CO2 is used as a mild and selective method, economically viable application of this method on similarly soluble oils from microalgae requires, in most cases, much higher pressure. This paper presents and verifies hypothesis that this difference is caused by high adsorption capacity of microalgae. Under the pressures usually applied in supercritical fluid extraction from plants, microalgae bind a large fraction of the extracted oil, while under extremely high CO2 pressures their adsorption capacity diminishes and the extraction rate depends on oil solubility in supercritical CO2. A mathematical model for the extraction from microalgae was derived and applied to literature data on the extraction kinetics in order to determine model parameters. PMID:28773546

Extracting falsifiable predictions from sloppy models.

PubMed

Gutenkunst, Ryan N; Casey, Fergal P; Waterfall, Joshua J; Myers, Christopher R; Sethna, James P

2007-12-01

Successful predictions are among the most compelling validations of any model. Extracting falsifiable predictions from nonlinear multiparameter models is complicated by the fact that such models are commonly sloppy, possessing sensitivities to different parameter combinations that range over many decades. Here we discuss how sloppiness affects the sorts of data that best constrain model predictions, makes linear uncertainty approximations dangerous, and introduces computational difficulties in Monte-Carlo uncertainty analysis. We also present a useful test problem and suggest refinements to the standards by which models are communicated.

Using a GIS to link digital spatial data and the precipitation-runoff modeling system, Gunnison River Basin, Colorado

USGS Publications Warehouse

Battaglin, William A.; Kuhn, Gerhard; Parker, Randolph S.

1993-01-01

The U.S. Geological Survey Precipitation-Runoff Modeling System, a modular, distributed-parameter, watershed-modeling system, is being applied to 20 smaller watersheds within the Gunnison River basin. The model is used to derive a daily water balance for subareas in a watershed, ultimately producing simulated streamflows that can be input into routing and accounting models used to assess downstream water availability under current conditions, and to assess the sensitivity of water resources in the basin to alterations in climate. A geographic information system (GIS) is used to automate a method for extracting physically based hydrologic response unit (HRU) distributed parameter values from digital data sources, and for the placement of those estimates into GIS spatial datalayers. The HRU parameters extracted are: area, mean elevation, average land-surface slope, predominant aspect, predominant land-cover type, predominant soil type, average total soil water-holding capacity, and average water-holding capacity of the root zone.

Robust determination of surface relaxivity from nuclear magnetic resonance DT2 measurements

NASA Astrophysics Data System (ADS)

Luo, Zhi-Xiang; Paulsen, Jeffrey; Song, Yi-Qiao

2015-10-01

Nuclear magnetic resonance (NMR) is a powerful tool to probe into geological materials such as hydrocarbon reservoir rocks and groundwater aquifers. It is unique in its ability to obtain in situ the fluid type and the pore size distributions (PSD). The T1 and T2 relaxation times are closely related to the pore geometry through the parameter called surface relaxivity. This parameter is critical for converting the relaxation time distribution into the PSD and so is key to accurately predicting permeability. The conventional way to determine the surface relaxivity ρ2 had required independent laboratory measurements of the pore size. Recently Zielinski et al. proposed a restricted diffusion model to extract the surface relaxivity from the NMR diffusion-T2 relaxation (DT2) measurement. Although this method significantly improved the ability to directly extract surface relaxivity from a pure NMR measurement, there are inconsistencies with their model and it relies on a number of preset parameters. Here we propose an improved signal model to incorporate a scalable LT and extend their method to extract the surface relaxivity based on analyzing multiple DT2 maps with varied diffusion observation time. With multiple diffusion observation times, the apparent diffusion coefficient correctly describes the restricted diffusion behavior in samples with wide PSDs, and the new method does not require predetermined parameters, such as the bulk diffusion coefficient and tortuosity. Laboratory experiments on glass beads packs with the beads diameter ranging from 50 μm to 500 μm are used to validate the new method. The extracted diffusion parameters are consistent with their known values and the determined surface relaxivity ρ2 agrees with the expected value within ±7%. This method is further successfully applied on a Berea sandstone core and yields surface relaxivity ρ2 consistent with the literature.

Electromembrane extraction through a virtually rotating supported liquid membrane.

PubMed

Hosseiny Davarani, Saied Saeed; Moazami, Hamid Reza; Memarian, Elham; Nojavan, Saeed

2016-01-01

Electromembrane extraction (EME) of model analytes was carried out using a virtually rotating supported liquid membrane (SLM). The virtual (nonmechanical) rotating of the SLM was achieved using a novel electrode assembly including a central electrode immersed inside the lumen of the SLM and five counter electrodes surrounding the SLM. A particular electronic circuit was designed to distribute the potential among five counter electrodes in a rotating pattern. The effect of the experimental parameters on the recovery of the extraction was investigated for verapamil (VPL), trimipramine (TRP), and clomipramine (CLP) as the model analytes and 2-ethyl hexanol as the SLM solvent. The results showed that the recovery of the extraction is a function of the angular velocity of the virtual rotation. The best results were obtained at an angular velocity of 1.83 RadS(-1) (or a rotation frequency of 0.29 Hz).The optimization of the parameters gave higher recoveries up to 50% greater than those of a conventional EME method. The rotating also allowed the extraction to be carried out at shorter time (15 min) and lower voltage (200 V) with respect to the conventional extraction. The model analytes were successfully extracted from wastewater and human urine samples with recoveries ranging from 38 to 85%. The RSD of the determinations was in the range of 12.6 to 14.8%. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Baccharis dracunculifolia methanol extract enhances glucose-stimulated insulin secretion in pancreatic islets of monosodium glutamate induced-obesity model rats.

PubMed

Hocayen, Palloma de A S; Grassiolli, Sabrina; Leite, Nayara C; Pochapski, Márcia T; Pereira, Ricardo A; da Silva, Luiz A; Snack, Andre L; Michel, R Garcia; Kagimura, Francini Y; da Cunha, Mário A A; Malfatti, Carlos R M

2016-07-01

Obesity is the main risk factor for type 2 diabetes mellitus. Secondary metabolites with biological activities and pharmacological potential have been identified in species of the Baccharis genus that are specifically distributed in the Americas. This study evaluated the effects of methanol extracts from Baccharis dracunculifolia DC. Asteraceae on metabolic parameters, satiety, and growth in monosodium glutamate (MSG) induced-obesity model rats. MSG was administered to 32 newborn rats (4 mg/g of body weight) once daily for 5 consecutive days. Four experimental groups (control, control + extract, MSG, and MSG + extract) were treated for 30 consecutive days with 400 mg/kg of B. dracunculifolia extract by gavage. Biochemical parameters, antioxidant activity, total extract phenolic content (methanolic, ethanolic, and acetone extractions), and pancreatic islets were evaluated. High levels of phenolic compounds were identified in B. dracunculifolia extracts (methanol: 46.2 ± 0.4 mg GAE/L; acetate: 70.5 ± 0.5 mg GAE/L; and ethanol: 30.3 ± 0.21 mg GAE/L); high antioxidant activity was detected in B. dracunculifolia ethanol and methanol extracts. The concentration of serum insulin increased 30% in obese animals treated with extract solutions (1.4-2.0 µU/mL, p < 0.05). Insulin secretion in pancreatic islets was 8.3 mM glucose (58%, p < 0.05) and 16.7 mM (99.5%, p < 0.05) in rats in the MSG + extract and MSG groups, respectively. Treatment with B. dracunculifolia extracts protected pancreatic islets and prevented the irreversible cellular damage observed in animals in obesity and diabetes models.

SU-E-J-252: A Motion Algorithm to Extract Physical and Motion Parameters of a Mobile Target in Cone-Beam Computed Tomographic Imaging Retrospective to Image Reconstruction

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

Ali, I; Ahmad, S; Alsbou, N

Purpose: A motion algorithm was developed to extract actual length, CT-numbers and motion amplitude of a mobile target imaged with cone-beam-CT (CBCT) retrospective to image-reconstruction. Methods: The motion model considered a mobile target moving with a sinusoidal motion and employed three measurable parameters: apparent length, CT number level and gradient of a mobile target obtained from CBCT images to extract information about the actual length and CT number value of the stationary target and motion amplitude. The algorithm was verified experimentally with a mobile phantom setup that has three targets with different sizes manufactured from homogenous tissue-equivalent gel material embeddedmore » into a thorax phantom. The phantom moved sinusoidal in one-direction using eight amplitudes (0–20mm) and a frequency of 15-cycles-per-minute. The model required imaging parameters such as slice thickness, imaging time. Results: This motion algorithm extracted three unknown parameters: length of the target, CT-number-level, motion amplitude for a mobile target retrospective to CBCT image reconstruction. The algorithm relates three unknown parameters to measurable apparent length, CT-number-level and gradient for well-defined mobile targets obtained from CBCT images. The motion model agreed with measured apparent lengths which were dependent on actual length of the target and motion amplitude. The cumulative CT-number for a mobile target was dependent on CT-number-level of the stationary target and motion amplitude. The gradient of the CT-distribution of mobile target is dependent on the stationary CT-number-level, actual target length along the direction of motion, and motion amplitude. Motion frequency and phase did not affect the elongation and CT-number distributions of mobile targets when imaging time included several motion cycles. Conclusion: The motion algorithm developed in this study has potential applications in diagnostic CT imaging and radiotherapy to extract actual length, size and CT-numbers distorted by motion in CBCT imaging. The model provides further information about motion of the target.« less

Poroviscoelastic cartilage properties in the mouse from indentation.

PubMed

Chiravarambath, Sidharth; Simha, Narendra K; Namani, Ravi; Lewis, Jack L

2009-01-01

A method for fitting parameters in a poroviscoelastic (PVE) model of articular cartilage in the mouse is presented. Indentation is performed using two different sized indenters and then these data are fitted using a PVE finite element program and parameter extraction algorithm. Data from a smaller indenter, a 15 mum diameter flat-ended 60 deg cone, is first used to fit the viscoelastic (VE) parameters, on the basis that for this tip size the gel diffusion time (approximate time constant of the poroelastic (PE) response) is of the order of 0.1 s, so that the PE response is negligible. These parameters are then used to fit the data from a second 170 mum diameter flat-ended 60 deg cone for the PE parameters, using the VE parameters extracted from the data from the 15 mum tip. Data from tests on five different mouse tibial plateaus are presented and fitted. Parameter variation studies for the larger indenter show that for this case the VE and PE time responses overlap in time, necessitating the use of both models.

Modeling axisymmetric flow and transport

USGS Publications Warehouse

Langevin, C.D.

2008-01-01

Unmodified versions of common computer programs such as MODFLOW, MT3DMS, and SEAWAT that use Cartesian geometry can accurately simulate axially symmetric ground water flow and solute transport. Axisymmetric flow and transport are simulated by adjusting several input parameters to account for the increase in flow area with radial distance from the injection or extraction well. Logarithmic weighting of interblock transmissivity, a standard option in MODFLOW, can be used for axisymmetric models to represent the linear change in hydraulic conductance within a single finite-difference cell. Results from three test problems (ground water extraction, an aquifer push-pull test, and upconing of saline water into an extraction well) show good agreement with analytical solutions or with results from other numerical models designed specifically to simulate the axisymmetric geometry. Axisymmetric models are not commonly used but can offer an efficient alternative to full three-dimensional models, provided the assumption of axial symmetry can be justified. For the upconing problem, the axisymmetric model was more than 1000 times faster than an equivalent three-dimensional model. Computational gains with the axisymmetric models may be useful for quickly determining appropriate levels of grid resolution for three-dimensional models and for estimating aquifer parameters from field tests.

Antidiabetic activity of flower buds of Michelia champaca Linn

PubMed Central

Jarald, E. Edwin; Joshi, S.B.; Jain, D.C.

2008-01-01

Objective: To identify the antihyperglycemic activity of various extracts, petroleum ether (60-80°), chloroform, acetone, ethanol, aqueous and crude aqueous, of the flower buds of Michelia champaca, and to identify the antidiabetic activity of active antihyperglycemic extract. Materials and Methods: Plant extracts were tested for antihyperglycemic activity in glucose overloaded hyperglycemic rats. The effective antihyperglycemic extract was tested for its hypoglycemic activity at two-dose levels, 200 and 400 mg/kg respectively. To confirm its utility in the higher model, the effective extract of M. champaca was subjected to antidiabetic study in alloxan induced diabetic model at two dose levels, 200 and 400 mg/kg respectively. The biochemical parameters, glucose, urea, creatinine, serum cholesterol, serum triglyceride, high density lipoprotein, low density lipoprotein, hemoglobin and glycosylated hemoglobin were also assessed in the experimental animals. Results: The ethanolic extract of M. champaca exhibited significant antihyperglycemic activity but did not produce hypoglycemia in fasted normal rats. Apart from this extract, the crude aqueous and petroleum ether extracts were found active only at the end of the first hour. Treatment of diabetic rats with ethanolic extract of this plant restored the elevated biochemical parameters significantly (P<0.05) (P<0.01) and the activity was found dose dependent. Conclusion: This study supports the traditional claim and the ethanolic extract of this plant could be added in traditional preparations for the ailment of various diabetes-associated complications. PMID:21279181

Gastroprotective activity of the ethanol extract from the inner bark of Caesalpinia pyramidalis in rats.

PubMed

Ribeiro, Ana Roseli S; Diniz, Polyana B F; Estevam, Charles S; Pinheiro, Malone S; Albuquerque-Júnior, Ricardo L C; Thomazzi, Sara M

2013-05-20

Caesalpinia pyramidalis Tul. (Fabaceae), known as "catingueira", has been used in folk medicine in the treatment of various disorders such as gastritis, heartburn, indigestion, and stomach ache. However, the gastroprotective properties of this species have not yet been studied. The ethanol extract of Caesalpinia pyramidalis inner bark was used in rats via oral route, at the doses of 30, 100, and 300 mg/kg. The antiulcer assays were performed using the ethanol- and nonsteroidal anti-inflammatory drug-induced ulcer models. Gastric secretion parameters (volume, pH, and total acidity) were also evaluated by the pylorus ligated model, and the mucus in the gastric content was determined. The anti-Helicobacter pylori activity of the ethanol extract of Caesalpinia pyramidalis was performed using the agar-well diffusion and broth microdilution methods. The ethanol extract (30, 100, and 300 mg/kg) produced dose dependent inhibition (P<0.01) on the ulcer lesion index, the total lesion area, and the percentage of lesion area in the ethanol-induced ulcer model. The ethanol extract (30, 100, and 300 mg/kg) also reduced (P<0.001) the ulcer index in the indomethacin-induced ulcer model. In the model ligature pylorus, the treatment with Caesalpinia pyramidalis ethanol extract failed to significantly change the gastric secretion parameters. However, after treatment with the ethanol extract of Caesalpinia pyramidalis (30, 100, and 300 mg/kg), there was a significant increase (P<0.05) in mucus production. The ethanol extract showed anti-Helicobacter pylori activity, with inhibition halos of 12.0 ± 1.7 mm at 10,000 μg/mL. The minimum inhibitory concentration (MIC) and minimal bactericidal concentration (MBC) values of the ethanol extract were of 625 and 10,000 μg/mL, respectively. Collectively, the present results suggest that the ethanol extract of Caesalpinia pyramidalis displays gastroprotective actions, supporting the folkloric usage of the plant to treat various gastrointestinal disturbances. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

A neural joint model for entity and relation extraction from biomedical text.

PubMed

Li, Fei; Zhang, Meishan; Fu, Guohong; Ji, Donghong

2017-03-31

Extracting biomedical entities and their relations from text has important applications on biomedical research. Previous work primarily utilized feature-based pipeline models to process this task. Many efforts need to be made on feature engineering when feature-based models are employed. Moreover, pipeline models may suffer error propagation and are not able to utilize the interactions between subtasks. Therefore, we propose a neural joint model to extract biomedical entities as well as their relations simultaneously, and it can alleviate the problems above. Our model was evaluated on two tasks, i.e., the task of extracting adverse drug events between drug and disease entities, and the task of extracting resident relations between bacteria and location entities. Compared with the state-of-the-art systems in these tasks, our model improved the F1 scores of the first task by 5.1% in entity recognition and 8.0% in relation extraction, and that of the second task by 9.2% in relation extraction. The proposed model achieves competitive performances with less work on feature engineering. We demonstrate that the model based on neural networks is effective for biomedical entity and relation extraction. In addition, parameter sharing is an alternative method for neural models to jointly process this task. Our work can facilitate the research on biomedical text mining.

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.

Sensitivity analysis of coupled processes and parameters on the performance of enhanced geothermal systems.

PubMed

Pandey, S N; Vishal, Vikram

2017-12-06

3-D modeling of coupled thermo-hydro-mechanical (THM) processes in enhanced geothermal systems using the control volume finite element code was done. In a first, a comparative analysis on the effects of coupled processes, operational parameters and reservoir parameters on heat extraction was conducted. We found that significant temperature drop and fluid overpressure occurred inside the reservoirs/fracture that affected the transport behavior of the fracture. The spatio-temporal variations of fracture aperture greatly impacted the thermal drawdown and consequently the net energy output. The results showed that maximum aperture evolution occurred near the injection zone instead of the production zone. Opening of the fracture reduced the injection pressure required to circulate a fixed mass of water. The thermal breakthrough and heat extraction strongly depend on the injection mass flow rate, well distances, reservoir permeability and geothermal gradients. High permeability caused higher water loss, leading to reduced heat extraction. From the results of TH vs THM process simulations, we conclude that appropriate coupling is vital and can impact the estimates of net heat extraction. This study can help in identifying the critical operational parameters, and process optimization for enhanced energy extraction from a geothermal system.

Variability aware compact model characterization for statistical circuit design optimization

NASA Astrophysics Data System (ADS)

Qiao, Ying; Qian, Kun; Spanos, Costas J.

2012-03-01

Variability modeling at the compact transistor model level can enable statistically optimized designs in view of limitations imposed by the fabrication technology. In this work we propose an efficient variabilityaware compact model characterization methodology based on the linear propagation of variance. Hierarchical spatial variability patterns of selected compact model parameters are directly calculated from transistor array test structures. This methodology has been implemented and tested using transistor I-V measurements and the EKV-EPFL compact model. Calculation results compare well to full-wafer direct model parameter extractions. Further studies are done on the proper selection of both compact model parameters and electrical measurement metrics used in the method.

Celestial Object Imaging Model and Parameter Optimization for an Optical Navigation Sensor Based on the Well Capacity Adjusting Scheme.

PubMed

Wang, Hao; Jiang, Jie; Zhang, Guangjun

2017-04-21

The simultaneous extraction of optical navigation measurements from a target celestial body and star images is essential for autonomous optical navigation. Generally, a single optical navigation sensor cannot simultaneously image the target celestial body and stars well-exposed because their irradiance difference is generally large. Multi-sensor integration or complex image processing algorithms are commonly utilized to solve the said problem. This study analyzes and demonstrates the feasibility of simultaneously imaging the target celestial body and stars well-exposed within a single exposure through a single field of view (FOV) optical navigation sensor using the well capacity adjusting (WCA) scheme. First, the irradiance characteristics of the celestial body are analyzed. Then, the celestial body edge model and star spot imaging model are established when the WCA scheme is applied. Furthermore, the effect of exposure parameters on the accuracy of star centroiding and edge extraction is analyzed using the proposed model. Optimal exposure parameters are also derived by conducting Monte Carlo simulation to obtain the best performance of the navigation sensor. Finally, laboratorial and night sky experiments are performed to validate the correctness of the proposed model and optimal exposure parameters.

Celestial Object Imaging Model and Parameter Optimization for an Optical Navigation Sensor Based on the Well Capacity Adjusting Scheme

PubMed Central

Wang, Hao; Jiang, Jie; Zhang, Guangjun

2017-01-01

The simultaneous extraction of optical navigation measurements from a target celestial body and star images is essential for autonomous optical navigation. Generally, a single optical navigation sensor cannot simultaneously image the target celestial body and stars well-exposed because their irradiance difference is generally large. Multi-sensor integration or complex image processing algorithms are commonly utilized to solve the said problem. This study analyzes and demonstrates the feasibility of simultaneously imaging the target celestial body and stars well-exposed within a single exposure through a single field of view (FOV) optical navigation sensor using the well capacity adjusting (WCA) scheme. First, the irradiance characteristics of the celestial body are analyzed. Then, the celestial body edge model and star spot imaging model are established when the WCA scheme is applied. Furthermore, the effect of exposure parameters on the accuracy of star centroiding and edge extraction is analyzed using the proposed model. Optimal exposure parameters are also derived by conducting Monte Carlo simulation to obtain the best performance of the navigation sensor. Finally, laboratorial and night sky experiments are performed to validate the correctness of the proposed model and optimal exposure parameters. PMID:28430132

Effects of process parameters on peanut skins extract and CO2 diffusivity by supercritical fluid extraction

NASA Astrophysics Data System (ADS)

Putra, N. R.; Yian, L. N.; Nasir, H. M.; Idham, Z. Binti; Yunus, M. A. C.

2018-03-01

Peanut skins (Arachis hypogea) are an agricultural waste product which has received much attention because they contain high nutritional values and can be potentially utilized in difference industries. At present, only a few studies have been conducted to study the effects of parameters on the peanut skins oil extraction. Therefore, this study aimed to determine the best extraction condition in order to obtain the highest extract yield using supercritical carbon dioxide (SC-CO2) with co-solvent Ethanol as compared to Soxhlet extraction method. Diffusivity of carbon dioxide in supercritical fluid extraction was determined using Crank model. The mean particle size used in this study was 425 µm. The supercritical carbon dioxide was performed at temperature (40 – 70 °C), flow rate of co-solvent ethanol (0 - 7.5% Vethanol/Vtotal), and extraction pressure (10 – 30 MPa) were used in this studies. The results showed that the percentage of oil yields and effective diffusivity increase as the pressure, rate of co-solvent, and temperature increased.

Synthesis of streamflow recession curves in dry environments

NASA Astrophysics Data System (ADS)

Arciniega, Saul; Breña-Naranjo, Agustín; Pedrozo-Acuña, Adrían

2015-04-01

The elucidation and predictability of hydrological systems can largely benefit by extracting observed patterns in processes, data and models. Such type of research framework in hydrology, also known as synthesis has gained significant attention over the last decade. For instance, hydrological synthesis implies that the identification of patterns in catchment behavior can enhance the extrapolation of hydrological signatures over large spatial and temporal scales. Hydrological signatures during dry periods such as streamflow recession curves (SRC) are of special interest in regions coping with water scarcity. Indeed, the study of SRCs from observed hydrographs allows to extract information about the storage-discharge relationship of a specific catchment and some of their groundwater hydraulic properties. This work aims at performing a synthesis work of SRCs in semi-arid & arid environments across Northern Mexico. Our dataset consisted in observed daily SRCs in 63 catchments with minima human interferences. Three streamflow recession extraction methods (Vogel, Brutsaert and Aksoy-Wittenberg) along with four recession models (Maillet, Boussinesq, Coutagne y Wittenberg) and three parameter estimation techniques (regressions, lower envelope y data binning) were used to determine the combination among different possible methods, processes and models that better describes SRCs in our study sites. Our results show that the extraction method proposed by Aksoy-Wittenberg along with Coutagne's nonlinear recession model provides a better approximation of SRCs across Northern Mexico, whereas regression was found to be the most adequate parameter estimation method. This study suggests that hydrological synthesis turned out to be an useful framework to identify similar patterns and model parameters during dry periods across Mexico's water-limited environments.

Temperature responses of individual soil organic matter components

NASA Astrophysics Data System (ADS)

Feng, Xiaojuan; Simpson, Myrna J.

2008-09-01

Temperature responses of soil organic matter (SOM) remain unclear partly due to its chemical and compositional heterogeneity. In this study, the decomposition of SOM from two grassland soils was investigated in a 1-year laboratory incubation at six different temperatures. SOM was separated into solvent extractable compounds, suberin- and cutin-derived compounds, and lignin-derived monomers by solvent extraction, base hydrolysis, and CuO oxidation, respectively. These SOM components have distinct chemical structures and stabilities and their decomposition patterns over the course of the experiment were fitted with a two-pool exponential decay model. The stability of SOM components was also assessed using geochemical parameters and kinetic parameters derived from model fitting. Compared with the solvent extractable compounds, a low percentage of lignin monomers partitioned into the labile SOM pool. Suberin- and cutin-derived compounds were poorly fitted by the decay model, and their recalcitrance was shown by the geochemical degradation parameter (ω - C16/∑C16), which was observed to stabilize during the incubation. The temperature sensitivity of decomposition, expressed as Q10, was derived from the relationship between temperature and SOM decay rates. SOM components exhibited varying temperature responses and the decomposition of lignin monomers exhibited higher Q10 values than the decomposition of solvent extractable compounds. Our study shows that Q10 values derived from soil respiration measurements may not be reliable indicators of temperature responses of individual SOM components.

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

Mudholkar, Mihir; Ahmed, Shamin; Ericson, Milton Nance

A compact model for SiC Power MOSFETs is presented. The model features a physical description of the channel current and internal capacitances and has been validated for dc, CV, and switching characteristics with measured data from a 1200-V, 20-A SiC power MOSFET in a temperature range of 25 degrees C to 225 degrees C. The peculiar variation of on-state resistance with temperature for SiC power MOSFETs has also been demonstrated through measurements and accounted for in the developed model. In order to improve the user experience with the model, a new datasheet driven parameter extraction strategy has been presented whichmore » requires only data available in device datasheets, to enable quick parameter extraction for off-the-shelf devices. Excellent agreement is shown between measurement and simulation using the presented model over the entire temperature range.« less

Quantifying properties of hot and dense QCD matter through systematic model-to-data comparison

DOE PAGES

Bernhard, Jonah E.; Marcy, Peter W.; Coleman-Smith, Christopher E.; ...

2015-05-22

We systematically compare an event-by-event heavy-ion collision model to data from the CERN Large Hadron Collider. Using a general Bayesian method, we probe multiple model parameters including fundamental quark-gluon plasma properties such as the specific shear viscosity η/s, calibrate the model to optimally reproduce experimental data, and extract quantitative constraints for all parameters simultaneously. Furthermore, the method is universal and easily extensible to other data and collision models.

Green ultrasound-assisted extraction of carotenoids from pomegranate wastes using vegetable oils.

PubMed

Goula, Athanasia M; Ververi, Maria; Adamopoulou, Anna; Kaderides, Kyriakos

2017-01-01

The objective of this work was to develop a new process for pomegranate peels application in food industries based on ultrasound-assisted extraction of carotenoids using different vegetable oils as solvents. In this way, an oil enriched with antioxidants is produced. Sunflower oil and soy oil were used as alternative solvents and the effects of various parameters on extraction yield were studied. Extraction temperature, solid/oil ratio, amplitude level, and extraction time were the factors investigated with respect to extraction yield. Comparative studies between ultrasound-assisted and conventional solvent extraction were carried out in terms of processing procedure and total carotenoids content. The efficient extraction period for achieving maximum yield of pomegranate peel carotenoids was about 30min. The optimum operating conditions were found to be: extraction temperature, 51.5°C; peels/solvent ratio, 0.10; amplitude level, 58.8%; solvent, sunflower oil. A second-order kinetic model was successfully developed for describing the mechanism of ultrasound extraction under different processing parameters. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

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).

Parameter extraction with neural networks

NASA Astrophysics Data System (ADS)

Cazzanti, Luca; Khan, Mumit; Cerrina, Franco

1998-06-01

In semiconductor processing, the modeling of the process is becoming more and more important. While the ultimate goal is that of developing a set of tools for designing a complete process (Technology CAD), it is also necessary to have modules to simulate the various technologies and, in particular, to optimize specific steps. This need is particularly acute in lithography, where the continuous decrease in CD forces the technologies to operate near their limits. In the development of a 'model' for a physical process, we face several levels of challenges. First, it is necessary to develop a 'physical model,' i.e. a rational description of the process itself on the basis of know physical laws. Second, we need an 'algorithmic model' to represent in a virtual environment the behavior of the 'physical model.' After a 'complete' model has been developed and verified, it becomes possible to do performance analysis. In many cases the input parameters are poorly known or not accessible directly to experiment. It would be extremely useful to obtain the values of these 'hidden' parameters from experimental results by comparing model to data. This is particularly severe, because the complexity and costs associated with semiconductor processing make a simple 'trial-and-error' approach infeasible and cost- inefficient. Even when computer models of the process already exists, obtaining data through simulations may be time consuming. Neural networks (NN) are powerful computational tools to predict the behavior of a system from an existing data set. They are able to adaptively 'learn' input/output mappings and to act as universal function approximators. In this paper we use artificial neural networks to build a mapping from the input parameters of the process to output parameters which are indicative of the performance of the process. Once the NN has been 'trained,' it is also possible to observe the process 'in reverse,' and to extract the values of the inputs which yield outputs with desired characteristics. Using this method, we can extract optimum values for the parameters and determine the process latitude very quickly.

SU-E-J-150: Four-Dimensional Cone-Beam CT Algorithm by Extraction of Physical and Motion Parameter of Mobile Targets Retrospective to Image Reconstruction with Motion Modeling

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

Ali, I; Ahmad, S; Alsbou, N

Purpose: To develop 4D-cone-beam CT (CBCT) algorithm by motion modeling that extracts actual length, CT numbers level and motion amplitude of a mobile target retrospective to image reconstruction by motion modeling. Methods: The algorithm used three measurable parameters: apparent length and blurred CT number distribution of a mobile target obtained from CBCT images to determine actual length, CT-number value of the stationary target, and motion amplitude. The predictions of this algorithm were tested with mobile targets that with different well-known sizes made from tissue-equivalent gel which was inserted into a thorax phantom. The phantom moved sinusoidally in one-direction to simulatemore » respiratory motion using eight amplitudes ranging 0–20mm. Results: Using this 4D-CBCT algorithm, three unknown parameters were extracted that include: length of the target, CT number level, speed or motion amplitude for the mobile targets retrospective to image reconstruction. The motion algorithms solved for the three unknown parameters using measurable apparent length, CT number level and gradient for a well-defined mobile target obtained from CBCT images. The motion model agreed with measured apparent lengths which were dependent on the actual target length and motion amplitude. The gradient of the CT number distribution of the mobile target is dependent on the stationary CT number level, actual target length and motion amplitude. Motion frequency and phase did not affect the elongation and CT number distribution of the mobile target and could not be determined. Conclusion: A 4D-CBCT motion algorithm was developed to extract three parameters that include actual length, CT number level and motion amplitude or speed of mobile targets directly from reconstructed CBCT images without prior knowledge of the stationary target parameters. This algorithm provides alternative to 4D-CBCT without requirement to motion tracking and sorting of the images into different breathing phases which has potential applications in diagnostic CT imaging and radiotherapy.« less

Biochemical Evaluation of the Hypoglycemic Effects of Extract and Fraction of Cassia fistula Linn. in Alloxan-induced Diabetic Rats

PubMed Central

Jarald, E. E.; Joshi, S. B.; Jain, D. C.; Edwin, S.

2013-01-01

Various extracts of flowers of Cassia fistula Linn (Leguminosae) such as petroleum ether (60-80°), chloroform, acetone, ethanol, aqueous, and crude aqueous extracts and two fractions of ethanol extract were tested for antihyperglycemic activity in glucose-overloaded hyperglycemic rats. The effective antihyperglycemic extracts and fraction were tested for their hypoglycemic activity at two dose levels, 200 and 400 mg/kg, respectively. To confirm their utility in higher models, the effective extracts and fraction of C. fistula were subjected to antidiabetic study in an alloxan-induced diabetic model at two dose levels, 200 and 400 mg/kg, respectively. Biochemical parameters like glucose, urea, creatinine, serum cholesterol, serum triglyceride, high-density lipoprotein, low-density lipoprotein, hemoglobin, and glycosylated hemoglobin were also assessed in experimental animals. The petroleum ether and ethanol extracts of C. fistula and the water-soluble fraction of ethanol extract were found to exhibit significant antihyperglycemic activity. The extracts, at the given doses, did not produce hypoglycemia in fasted normal rats, and the fraction exhibited weak hypoglycemic effect after 2 h of the treatment. Treatment of diabetic rats with ethanol extract and water-soluble fraction of this plant restored the elevated biochemical parameters significantly (P<0.05) to the normal level. No activity was found in the petroleum ether extract of the plant. Comparatively, the water-soluble fraction of ethanol extract was found to be more effective than the ethanol extract, and the activity was comparable with that of the standard, glibenclamide (5 mg/kg). PMID:24302797

Mathematical modelling for extraction of oil from Dracocephalum kotschyi seeds in supercritical carbon dioxide.

PubMed

Sodeifian, Gholamhossein; Sajadian, Seyed Ali; Honarvar, Bizhan

2018-04-01

Extraction of oil from Dracocephalum kotschyi Boiss seeds using supercritical carbon dioxide was designed using central composite design to evaluate the effect of various operating parameters including pressure, temperature, particle size and extraction time on the oil yield. Maximum extraction yield predicted from response surface method was 71.53% under the process conditions with pressure of 220 bar, temperature of 35 °C, particle diameter of 0.61 mm and extraction time of 130 min. Furthermore, broken and intact cells model was utilised to consider mass transfer kinetics of extracted natural materials. The results revealed that the model had a good agreement with the experimental data. The oil samples obtained via supercritical and solvent extraction methods were analysed by gas chromatography. The most abundant acid was linolenic acid. The results analysis showed that there was no significant difference between the fatty acid contents of the oils obtained by the supercritical and solvent extraction techniques.

Extraction kinetic modelling of total polyphenols and total anthocyanins from saffron floral bio-residues: Comparison of extraction methods.

PubMed

Da Porto, Carla; Natolino, Andrea

2018-08-30

Analysis of the extraction kinetic modelling for natural compounds is essential for industrial application. The second order rate model was applied to estimate the extraction kinetics of conventional solid-liquid extraction (CSLE), ultrasound-assisted extraction (UAE) and microwave-assisted extraction (MAE) of total polyphenols (TPC) from saffron floral bio-residues at different solid-to-liquid ratios (R S/L )(1:10, 1:20, 1:30, 1:50 g ml -1 ), ethanol 59% as solvent and 66 °C temperature. The optimum solid-to-liquid ratios for TPC kinetics were 1:20 for CLSE, 1:30 for UAE and 1:50 for MAE. The kinetics of total anthocyanins (TA) and antioxidant activity (AA) were investigated for the optimum R S/L for each method. The results showed a good prediction of the model for extraction kinetics in all experiments (R 2  > 0.99; NRMS 0.65-3.35%). The kinetic parameters were calculated and discussed. UAE, compared with the other methods, had the greater efficiency for TPC, TA and AA. Copyright © 2018 Elsevier Ltd. All rights reserved.

Kinetics of ultrasound-assisted extraction of antioxidant polyphenols from food by-products: Extraction and energy consumption optimization.

PubMed

Pradal, Delphine; Vauchel, Peggy; Decossin, Stéphane; Dhulster, Pascal; Dimitrov, Krasimir

2016-09-01

Ultrasound-assisted extraction (UAE) of antioxidant polyphenols from chicory grounds was studied in order to propose a suitable valorization of this food industry by-product. The main parameters influencing the extraction process were identified. A new mathematical model for multi-criteria optimization of UAE was proposed. This kinetic model permitted the following and the prediction of the yield of extracted polyphenols, the antioxidant activity of the obtained extracts and the energy consumption during the extraction process in wide ranges of temperature (20-60°C), ethanol content in the solvent (0-60% (vol.) in ethanol-water mixtures) and ultrasound power (0-100W). After experimental validation of the model, several simulations at different technological restrictions were performed to illustrate the potentiality of the model to find the optimal conditions for obtaining a given yield within minimal process duration or with minimal energy consumption. The advantage of ultrasound assistance was clearly demonstrated both for the reduction of extraction duration and for the reduction of energy consumption. Copyright © 2016 Elsevier B.V. All rights reserved.

Comparative Sensitivity Analysis of Muscle Activation Dynamics

PubMed Central

Günther, Michael; Götz, Thomas

2015-01-01

We mathematically compared two models of mammalian striated muscle activation dynamics proposed by Hatze and Zajac. Both models are representative for a broad variety of biomechanical models formulated as ordinary differential equations (ODEs). These models incorporate parameters that directly represent known physiological properties. Other parameters have been introduced to reproduce empirical observations. We used sensitivity analysis to investigate the influence of model parameters on the ODE solutions. In addition, we expanded an existing approach to treating initial conditions as parameters and to calculating second-order sensitivities. Furthermore, we used a global sensitivity analysis approach to include finite ranges of parameter values. Hence, a theoretician striving for model reduction could use the method for identifying particularly low sensitivities to detect superfluous parameters. An experimenter could use it for identifying particularly high sensitivities to improve parameter estimation. Hatze's nonlinear model incorporates some parameters to which activation dynamics is clearly more sensitive than to any parameter in Zajac's linear model. Other than Zajac's model, Hatze's model can, however, reproduce measured shifts in optimal muscle length with varied muscle activity. Accordingly we extracted a specific parameter set for Hatze's model that combines best with a particular muscle force-length relation. PMID:26417379

Retrieval of cloud cover parameters from multispectral satellite images

NASA Technical Reports Server (NTRS)

Arking, A.; Childs, J. D.

1985-01-01

A technique is described for extracting cloud cover parameters from multispectral satellite radiometric measurements. Utilizing three channels from the AVHRR (Advanced Very High Resolution Radiometer) on NOAA polar orbiting satellites, it is shown that one can retrieve four parameters for each pixel: cloud fraction within the FOV, optical thickness, cloud-top temperature and a microphysical model parameter. The last parameter is an index representing the properties of the cloud particle and is determined primarily by the radiance at 3.7 microns. The other three parameters are extracted from the visible and 11 micron infrared radiances, utilizing the information contained in the two-dimensional scatter plot of the measured radiances. The solution is essentially one in which the distributions of optical thickness and cloud-top temperature are maximally clustered for each region, with cloud fraction for each pixel adjusted to achieve maximal clustering.

Extraction channel design based on an equivalent lumped parameter method for a SCC-250 MeV superconducting cyclotron

NASA Astrophysics Data System (ADS)

Zhang, Lige; Fan, Kuanjun; Hu, Shengwei; Li, Xiaofei; Mei, Zhiyuan; Zeng, Zhijie; Chen, Wei; Qin, Bin; Rao, Yinong

2018-07-01

A SCC-250 MeV cyclotron, producing a 250 MeV proton beam, is under development in Huazhong University of Science and Technology (HUST) for proton therapy. The magnetic flux density, as a function of radius, decreases rapidly in the beam extraction region, which increases the radial beam size continuously along the extraction orbit. In this paper, an extraction channel inside the SCC-250 MeV is designed to control the beam size using passive magnetic channels. An equivalent lumped parameter method is used to establish the model of the extraction channel in the complex fringe magnetic field of the main magnet. Then, the extraction channel is designed using the lattice design software MADX. The beam envelopes are verified using particle tracing method. The maximum radial size of 6.8 mm and axial size of 4.3 mm meet the requirements of the extraction from the SCC-250 MeV.

3D numerical simulations of negative hydrogen ion extraction using realistic plasma parameters, geometry of the extraction aperture and full 3D magnetic field map

NASA Astrophysics Data System (ADS)

Mochalskyy, S.; Wünderlich, D.; Ruf, B.; Franzen, P.; Fantz, U.; Minea, T.

2014-02-01

Decreasing the co-extracted electron current while simultaneously keeping negative ion (NI) current sufficiently high is a crucial issue on the development plasma source system for ITER Neutral Beam Injector. To support finding the best extraction conditions the 3D Particle-in-Cell Monte Carlo Collision electrostatic code ONIX (Orsay Negative Ion eXtraction) has been developed. Close collaboration with experiments and other numerical models allows performing realistic simulations with relevant input parameters: plasma properties, geometry of the extraction aperture, full 3D magnetic field map, etc. For the first time ONIX has been benchmarked with commercial positive ions tracing code KOBRA3D. A very good agreement in terms of the meniscus position and depth has been found. Simulation of NI extraction with different e/NI ratio in bulk plasma shows high relevance of the direct negative ion extraction from the surface produced NI in order to obtain extracted NI current as in the experimental results from BATMAN testbed.

Predicting loop–helix tertiary structural contacts in RNA pseudoknots

PubMed Central

Cao, Song; Giedroc, David P.; Chen, Shi-Jie

2010-01-01

Tertiary interactions between loops and helical stems play critical roles in the biological function of many RNA pseudoknots. However, quantitative predictions for RNA tertiary interactions remain elusive. Here we report a statistical mechanical model for the prediction of noncanonical loop–stem base-pairing interactions in RNA pseudoknots. Central to the model is the evaluation of the conformational entropy for the pseudoknotted folds with defined loop–stem tertiary structural contacts. We develop an RNA virtual bond-based conformational model (Vfold model), which permits a rigorous computation of the conformational entropy for a given fold that contains loop–stem tertiary contacts. With the entropy parameters predicted from the Vfold model and the energy parameters for the tertiary contacts as inserted parameters, we can then predict the RNA folding thermodynamics, from which we can extract the tertiary contact thermodynamic parameters from theory–experimental comparisons. These comparisons reveal a contact enthalpy (ΔH) of −14 kcal/mol and a contact entropy (ΔS) of −38 cal/mol/K for a protonated C+•(G–C) base triple at pH 7.0, and (ΔH = −7 kcal/mol, ΔS = −19 cal/mol/K) for an unprotonated base triple. Tests of the model for a series of pseudoknots show good theory–experiment agreement. Based on the extracted energy parameters for the tertiary structural contacts, the model enables predictions for the structure, stability, and folding pathways for RNA pseudoknots with known or postulated loop–stem tertiary contacts from the nucleotide sequence alone. PMID:20100813

Encapsulation of brewing yeast in alginate/chitosan matrix: lab-scale optimization of lager beer fermentation.

PubMed

Naydenova, Vessela; Badova, Mariyana; Vassilev, Stoyan; Iliev, Vasil; Kaneva, Maria; Kostov, Georgi

2014-03-04

Two mathematical models were developed for studying the effect of main fermentation temperature ( T MF ), immobilized cell mass ( M IC ) and original wort extract (OE) on beer fermentation with alginate-chitosan microcapsules with a liquid core. During the experiments, the investigated parameters were varied in order to find the optimal conditions for beer fermentation with immobilized cells. The basic beer characteristics, i.e. extract, ethanol, biomass concentration, pH and colour, as well as the concentration of aldehydes and vicinal diketones, were measured. The results suggested that the process parameters represented a powerful tool in controlling the fermentation time. Subsequently, the optimized process parameters were used to produce beer in laboratory batch fermentation. The system productivity was also investigated and the data were used for the development of another mathematical model.

Encapsulation of brewing yeast in alginate/chitosan matrix: lab-scale optimization of lager beer fermentation

PubMed Central

Naydenova, Vessela; Badova, Mariyana; Vassilev, Stoyan; Iliev, Vasil; Kaneva, Maria; Kostov, Georgi

2014-01-01

Two mathematical models were developed for studying the effect of main fermentation temperature (T MF), immobilized cell mass (M IC) and original wort extract (OE) on beer fermentation with alginate-chitosan microcapsules with a liquid core. During the experiments, the investigated parameters were varied in order to find the optimal conditions for beer fermentation with immobilized cells. The basic beer characteristics, i.e. extract, ethanol, biomass concentration, pH and colour, as well as the concentration of aldehydes and vicinal diketones, were measured. The results suggested that the process parameters represented a powerful tool in controlling the fermentation time. Subsequently, the optimized process parameters were used to produce beer in laboratory batch fermentation. The system productivity was also investigated and the data were used for the development of another mathematical model. PMID:26019512

Automatic tissue characterization from ultrasound imagery

NASA Astrophysics Data System (ADS)

Kadah, Yasser M.; Farag, Aly A.; Youssef, Abou-Bakr M.; Badawi, Ahmed M.

1993-08-01

In this work, feature extraction algorithms are proposed to extract the tissue characterization parameters from liver images. Then the resulting parameter set is further processed to obtain the minimum number of parameters representing the most discriminating pattern space for classification. This preprocessing step was applied to over 120 pathology-investigated cases to obtain the learning data for designing the classifier. The extracted features are divided into independent training and test sets and are used to construct both statistical and neural classifiers. The optimal criteria for these classifiers are set to have minimum error, ease of implementation and learning, and the flexibility for future modifications. Various algorithms for implementing various classification techniques are presented and tested on the data. The best performance was obtained using a single layer tensor model functional link network. Also, the voting k-nearest neighbor classifier provided comparably good diagnostic rates.

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.

Analysis of geologic terrain models for determination of optimum SAR sensor configuration and optimum information extraction for exploration of global non-renewable resources. Pilot study: Arkansas Remote Sensing Laboratory, part 1, part 2, and part 3

NASA Technical Reports Server (NTRS)

Kaupp, V. H.; Macdonald, H. C.; Waite, W. P.; Stiles, J. A.; Frost, F. S.; Shanmugam, K. S.; Smith, S. A.; Narayanan, V.; Holtzman, J. C. (Principal Investigator)

1982-01-01

Computer-generated radar simulations and mathematical geologic terrain models were used to establish the optimum radar sensor operating parameters for geologic research. An initial set of mathematical geologic terrain models was created for three basic landforms and families of simulated radar images were prepared from these models for numerous interacting sensor, platform, and terrain variables. The tradeoffs between the various sensor parameters and the quantity and quality of the extractable geologic data were investigated as well as the development of automated techniques of digital SAR image analysis. Initial work on a texture analysis of SEASAT SAR imagery is reported. Computer-generated radar simulations are shown for combinations of two geologic models and three SAR angles of incidence.

Surface characteristics modeling and performance evaluation of urban building materials using LiDAR data.

PubMed

Li, Xiaolu; Liang, Yu

2015-05-20

Analysis of light detection and ranging (LiDAR) intensity data to extract surface features is of great interest in remote sensing research. One potential application of LiDAR intensity data is target classification. A new bidirectional reflectance distribution function (BRDF) model is derived for target characterization of rough and smooth surfaces. Based on the geometry of our coaxial full-waveform LiDAR system, the integration method is improved through coordinate transformation to establish the relationship between the BRDF model and intensity data of LiDAR. A series of experiments using typical urban building materials are implemented to validate the proposed BRDF model and integration method. The fitting results show that three parameters extracted from the proposed BRDF model can distinguish the urban building materials from perspectives of roughness, specular reflectance, and diffuse reflectance. A comprehensive analysis of these parameters will help characterize surface features in a physically rigorous manner.

Optimization of microwave-assisted extraction of polyphenols from Myrtus communis L. leaves.

PubMed

Dahmoune, Farid; Nayak, Balunkeswar; Moussi, Kamal; Remini, Hocine; Madani, Khodir

2015-01-01

Phytochemicals, such as phenolic compounds, are of great interest due to their health-benefitting antioxidant properties and possible protection against inflammation, cardiovascular diseases and certain types of cancer. Maximum retention of these phytochemicals during extraction requires optimised process parameter conditions. A microwave-assisted extraction (MAE) method was investigated for extraction of total phenolics from Myrtus communis leaves. The total phenolic capacity (TPC) of leaf extracts at optimised MAE conditions was compared with ultrasound-assisted extraction (UAE) and conventional solvent extraction (CSE). The influence of extraction parameters including ethanol concentration, microwave power, irradiation time and solvent-to-solid ratio on the extraction of TPC was modeled by using a second-order regression equation. The optimal MAE conditions were 42% ethanol concentration, 500 W microwave power, 62 s irradiation time and 32 mL/g solvent to material ratio. Ethanol concentration and liquid-to-solid ratio were the significant parameters for the extraction process (p<0.01). Under the MAE optimised conditions, the recovery of TPC was 162.49 ± 16.95 mg gallic acidequivalent/gdry weight(DW), approximating the predicted content (166.13 mg GAE/g DW). When bioactive phytochemicals extracted from Myrtus leaves using MAE compared with UAE and CSE, it was also observed that tannins (32.65 ± 0.01 mg/g), total flavonoids (5.02 ± 0.05 mg QE/g) and antioxidant activities (38.20 ± 1.08 μg GAE/mL) in MAE extracts were higher than the other two extracts. These findings further illustrate that extraction of bioactive phytochemicals from plant materials using MAE method consumes less extraction solvent and saves time. Copyright © 2014 Elsevier Ltd. All rights reserved.

Optimization of extraction parameters of pentacyclic triterpenoids from Swertia chirata stem using response surface methodology.

PubMed

Pandey, Devendra Kumar; Kaur, Prabhjot

2018-03-01

In the present investigation, pentacyclic triterpenoids were extracted from different parts of Swertia chirata by solid-liquid reflux extraction methods. The total pentacyclic triterpenoids (UA, OA, and BA) in extracted samples were determined by HPTLC method. Preliminary studies showed that stem part contains the maximum pentacyclic triterpenoid and was chosen for further studies. Response surface methodology (RSM) has been employed successfully by solid-liquid reflux extraction methods for the optimization of different extraction variables viz., temperature ( X 1 35-70 °C), extraction time ( X 2 30-60 min), solvent composition ( X 3 20-80%), solvent-to-solid ratio ( X 4 30-60 mlg -1 ), and particle size ( X 5 3-6 mm) on maximum recovery of triterpenoid from stem parts of Swertia chirata . A Plackett-Burman design has been used initially to screen out the three extraction factors viz., particle size, temperature, and solvent composition on yield of triterpenoid. Moreover, central composite design (CCD) was implemented to optimize the significant extraction parameters for maximum triterpenoid yield. Three extraction parameters viz., mean particle size (3 mm), temperature (65 °C), and methanol-ethyl acetate solvent composition (45%) can be considered as significant for the better yield of triterpenoid A second-order polynomial model satisfactorily fitted the experimental data with the R 2 values of 0.98 for the triterpenoid yield ( p  < 0.001), implying good agreement between the experimental triterpenoid yield (3.71%) to the predicted value (3.79%).

Two-structured solid particle model for predicting and analyzing supercritical extraction performance.

PubMed

Samadi, Sara; Vaziri, Behrooz Mahmoodzadeh

2017-07-14

Solid extraction process, using the supercritical fluid, is a modern science and technology, which has come in vogue regarding its considerable advantages. In the present article, a new and comprehensive model is presented for predicting the performance and separation yield of the supercritical extraction process. The base of process modeling is partial differential mass balances. In the proposed model, the solid particles are considered twofold: (a) particles with intact structure, (b) particles with destructed structure. A distinct mass transfer coefficient has been used for extraction of each part of solid particles to express different extraction regimes and to evaluate the process accurately (internal mass transfer coefficient was used for the intact-structure particles and external mass transfer coefficient was employed for the destructed-structure particles). In order to evaluate and validate the proposed model, the obtained results from simulations were compared with two series of available experimental data for extraction of chamomile extract with supercritical carbon dioxide, which had an excellent agreement. This is indicative of high potentiality of the model in predicting the extraction process, precisely. In the following, the effect of major parameters on supercritical extraction process, like pressure, temperature, supercritical fluid flow rate, and the size of solid particles was evaluated. The model can be used as a superb starting point for scientific and experimental applications. Copyright © 2017 Elsevier B.V. All rights reserved.

Extraction Optimization for Obtaining Artemisia capillaris Extract with High Anti-Inflammatory Activity in RAW 264.7 Macrophage Cells

PubMed Central

Jang, Mi; Jeong, Seung-Weon; Kim, Bum-Keun; Kim, Jong-Chan

2015-01-01

Plant extracts have been used as herbal medicines to treat a wide variety of human diseases. We used response surface methodology (RSM) to optimize the Artemisia capillaris Thunb. extraction parameters (extraction temperature, extraction time, and ethanol concentration) for obtaining an extract with high anti-inflammatory activity at the cellular level. The optimum ranges for the extraction parameters were predicted by superimposing 4-dimensional response surface plots of the lipopolysaccharide- (LPS-) induced PGE2 and NO production and by cytotoxicity of A. capillaris Thunb. extracts. The ranges of extraction conditions used for determining the optimal conditions were extraction temperatures of 57–65°C, ethanol concentrations of 45–57%, and extraction times of 5.5–6.8 h. On the basis of the results, a model with a central composite design was considered to be accurate and reliable for predicting the anti-inflammation activity of extracts at the cellular level. These approaches can provide a logical starting point for developing novel anti-inflammatory substances from natural products and will be helpful for the full utilization of A. capillaris Thunb. The crude extract obtained can be used in some A. capillaris Thunb.-related health care products. PMID:26075271

The ultrasonic-enhanced factor of mass-transfer coefficient in the supercritical carbon dioxide extraction

NASA Astrophysics Data System (ADS)

Luo, Benyi; Lu, Yigang

2008-10-01

Based on several hypotheses about the process of supercritical carbon dioxide extraction, the onflow around the solute granule is figured out by the Navier-Stocks equation. In combination with the Higbie’s solute infiltration model, the link between the mass-transfer coefficient and the velocity of flow is found. The mass-transfer coefficient with the ultrasonical effect is compared with that without the ultrasonical effect, and then a new parameter named the ultrasonic-enhanced factor of mass-transfer coefficient is brought forward, which describes the mathematical model of the supercritical carbon dioxide extraction process enhanced by ultrasonic. The model gives out the relationships among the ultrasonical power, the ultrasonical frequency, the radius of solute granule and the ultrasonic-enhanced factor of mass-transfer coefficient. The results calculated by this model fit well with the experimental data, including the extraction of Coix Lacryma-jobi Seed Oil (CLSO) and Coix Lacryma-jobi Seed Ester (CLSE) from coix seeds and the extraction of Eicosapentaenoic Acid (EPA) and Docosahexaenoic Acid (DHA) from the alga by means of the ultrasonic-enhanced supercritical carbon dioxide extraction (USFE) and the supercritical carbon dioxide extraction (SFE) respectively. This proves the rationality of the ultrasonic-enhanced factor model. The model provides a theoretical basis for the application of ultrasonic-enhanced supercritical fluid extraction technique.

Method for Face-Emotion Retrieval Using A Cartoon Emotional Expression Approach

NASA Astrophysics Data System (ADS)

Kostov, Vlaho; Yanagisawa, Hideyoshi; Johansson, Martin; Fukuda, Shuichi

A simple method for extracting emotion from a human face, as a form of non-verbal communication, was developed to cope with and optimize mobile communication in a globalized and diversified society. A cartoon face based model was developed and used to evaluate emotional content of real faces. After a pilot survey, basic rules were defined and student subjects were asked to express emotion using the cartoon face. Their face samples were then analyzed using principal component analysis and the Mahalanobis distance method. Feature parameters considered as having relations with emotions were extracted and new cartoon faces (based on these parameters) were generated. The subjects evaluated emotion of these cartoon faces again and we confirmed these parameters were suitable. To confirm how these parameters could be applied to real faces, we asked subjects to express the same emotions which were then captured electronically. Simple image processing techniques were also developed to extract these features from real faces and we then compared them with the cartoon face parameters. It is demonstrated via the cartoon face that we are able to express the emotions from very small amounts of information. As a result, real and cartoon faces correspond to each other. It is also shown that emotion could be extracted from still and dynamic real face images using these cartoon-based features.

QSAR modeling of flotation collectors using principal components extracted from topological indices.

PubMed

Natarajan, R; Nirdosh, Inderjit; Basak, Subhash C; Mills, Denise R

2002-01-01

Several topological indices were calculated for substituted-cupferrons that were tested as collectors for the froth flotation of uranium. The principal component analysis (PCA) was used for data reduction. Seven principal components (PC) were found to account for 98.6% of the variance among the computed indices. The principal components thus extracted were used in stepwise regression analyses to construct regression models for the prediction of separation efficiencies (Es) of the collectors. A two-parameter model with a correlation coefficient of 0.889 and a three-parameter model with a correlation coefficient of 0.913 were formed. PCs were found to be better than partition coefficient to form regression equations, and inclusion of an electronic parameter such as Hammett sigma or quantum mechanically derived electronic charges on the chelating atoms did not improve the correlation coefficient significantly. The method was extended to model the separation efficiencies of mercaptobenzothiazoles (MBT) and aminothiophenols (ATP) used in the flotation of lead and zinc ores, respectively. Five principal components were found to explain 99% of the data variability in each series. A three-parameter equation with correlation coefficient of 0.985 and a two-parameter equation with correlation coefficient of 0.926 were obtained for MBT and ATP, respectively. The amenability of separation efficiencies of chelating collectors to QSAR modeling using PCs based on topological indices might lead to the selection of collectors for synthesis and testing from a virtual database.

Survey of simulation methods for modeling pulsed sieve-plate extraction columns

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

Burkhart, L.

1979-03-01

The report first considers briefly the use of liquid-liquid extraction in nuclear fuel reprocessing and then describes the operation of the pulse column. Currently available simulation models of the column are reviewed, and followed by an analysis of the information presently available from which the necessary parameters can be obtained for use in a model of the column. Finally, overall conclusions are given regarding the information needed to develop an accurate model of the column for materials accountability in fuel reprocessing plants. 156 references.

Numerical framework for the modeling of electrokinetic flows

NASA Astrophysics Data System (ADS)

Deshpande, Manish; Ghaddar, Chahid; Gilbert, John R.; St. John, Pamela M.; Woudenberg, Timothy M.; Connell, Charles R.; Molho, Joshua; Herr, Amy; Mungal, Godfrey; Kenny, Thomas W.

1998-09-01

This paper presents a numerical framework for design-based analyses of electrokinetic flow in interconnects. Electrokinetic effects, which can be broadly divided into electrophoresis and electroosmosis, are of importance in providing a transport mechanism in microfluidic devices for both pumping and separation. Models for the electrokinetic effects can be derived and coupled to the fluid dynamic equations through appropriate source terms. In the design of practical microdevices, however, accurate coupling of the electrokinetic effects requires the knowledge of several material and physical parameters, such as the diffusivity and the mobility of the solute in the solvent. Additionally wall-based effects such as chemical binding sites might exist that affect the flow patterns. In this paper, we address some of these issues by describing a synergistic numerical/experimental process to extract the parameters required. Experiments were conducted to provide the numerical simulations with a mechanism to extract these parameters based on quantitative comparisons with each other. These parameters were then applied in predicting further experiments to validate the process. As part of this research, we have created NetFlow, a tool for micro-fluid analyses. The tool can be validated and applied in existing technologies by first creating test structures to extract representations of the physical phenomena in the device, and then applying them in the design analyses to predict correct behavior.

Automatic facial animation parameters extraction in MPEG-4 visual communication

NASA Astrophysics Data System (ADS)

Yang, Chenggen; Gong, Wanwei; Yu, Lu

2002-01-01

Facial Animation Parameters (FAPs) are defined in MPEG-4 to animate a facial object. The algorithm proposed in this paper to extract these FAPs is applied to very low bit-rate video communication, in which the scene is composed of a head-and-shoulder object with complex background. This paper addresses the algorithm to automatically extract all FAPs needed to animate a generic facial model, estimate the 3D motion of head by points. The proposed algorithm extracts human facial region by color segmentation and intra-frame and inter-frame edge detection. Facial structure and edge distribution of facial feature such as vertical and horizontal gradient histograms are used to locate the facial feature region. Parabola and circle deformable templates are employed to fit facial feature and extract a part of FAPs. A special data structure is proposed to describe deformable templates to reduce time consumption for computing energy functions. Another part of FAPs, 3D rigid head motion vectors, are estimated by corresponding-points method. A 3D head wire-frame model provides facial semantic information for selection of proper corresponding points, which helps to increase accuracy of 3D rigid object motion estimation.

Ion thruster performance model

NASA Technical Reports Server (NTRS)

Brophy, J. R.

1984-01-01

A model of ion thruster performance is developed for high flux density, cusped magnetic field thruster designs. This model is formulated in terms of the average energy required to produce an ion in the discharge chamber plasma and the fraction of these ions that are extracted to form the beam. The direct loss of high energy (primary) electrons from the plasma to the anode is shown to have a major effect on thruster performance. The model provides simple algebraic equations enabling one to calculate the beam ion energy cost, the average discharge chamber plasma ion energy cost, the primary electron density, the primary-to-Maxwellian electron density ratio and the Maxwellian electron temperature. Experiments indicate that the model correctly predicts the variation in plasma ion energy cost for changes in propellant gas (Ar, Kr and Xe), grid transparency to neutral atoms, beam extraction area, discharge voltage, and discharge chamber wall temperature. The model and experiments indicate that thruster performance may be described in terms of only four thruster configuration dependent parameters and two operating parameters. The model also suggests that improved performance should be exhibited by thruster designs which extract a large fraction of the ions produced in the discharge chamber, which have good primary electron and neutral atom containment and which operate at high propellant flow rates.

Accurate diode behavioral model with reverse recovery

NASA Astrophysics Data System (ADS)

Banáš, Stanislav; Divín, Jan; Dobeš, Josef; Paňko, Václav

2018-01-01

This paper deals with the comprehensive behavioral model of p-n junction diode containing reverse recovery effect, applicable to all standard SPICE simulators supporting Verilog-A language. The model has been successfully used in several production designs, which require its full complexity, robustness and set of tuning parameters comparable with standard compact SPICE diode model. The model is like standard compact model scalable with area and temperature and can be used as a stand-alone diode or as a part of more complex device macro-model, e.g. LDMOS, JFET, bipolar transistor. The paper briefly presents the state of the art followed by the chapter describing the model development and achieved solutions. During precise model verification some of them were found non-robust or poorly converging and replaced by more robust solutions, demonstrated in the paper. The measurement results of different technologies and different devices compared with a simulation using the new behavioral model are presented as the model validation. The comparison of model validation in time and frequency domains demonstrates that the implemented reverse recovery effect with correctly extracted parameters improves the model simulation results not only in switching from ON to OFF state, which is often published, but also its impedance/admittance frequency dependency in GHz range. Finally the model parameter extraction and the comparison with SPICE compact models containing reverse recovery effect is presented.

Using Simplistic Shape/Surface Models to Predict Brightness in Estimation Filters

NASA Astrophysics Data System (ADS)

Wetterer, C.; Sheppard, D.; Hunt, B.

The prerequisite for using brightness (radiometric flux intensity) measurements in an estimation filter is to have a measurement function that accurately predicts a space objects brightness for variations in the parameters of interest. These parameters include changes in attitude and articulations of particular components (e.g. solar panel east-west offsets to direct sun-tracking). Typically, shape models and bidirectional reflectance distribution functions are combined to provide this forward light curve modeling capability. To achieve precise orbit predictions with the inclusion of shape/surface dependent forces such as radiation pressure, relatively complex and sophisticated modeling is required. Unfortunately, increasing the complexity of the models makes it difficult to estimate all those parameters simultaneously because changes in light curve features can now be explained by variations in a number of different properties. The classic example of this is the connection between the albedo and the area of a surface. If, however, the desire is to extract information about a single and specific parameter or feature from the light curve, a simple shape/surface model could be used. This paper details an example of this where a complex model is used to create simulated light curves, and then a simple model is used in an estimation filter to extract out a particular feature of interest. In order for this to be successful, however, the simple model must be first constructed using training data where the feature of interest is known or at least known to be constant.

Feature extraction inspired by V1 in visual cortex

NASA Astrophysics Data System (ADS)

Lv, Chao; Xu, Yuelei; Zhang, Xulei; Ma, Shiping; Li, Shuai; Xin, Peng; Zhu, Mingning; Ma, Hongqiang

2018-04-01

Target feature extraction plays an important role in pattern recognition. It is the most complicated activity in the brain mechanism of biological vision. Inspired by high properties of primary visual cortex (V1) in extracting dynamic and static features, a visual perception model was raised. Firstly, 28 spatial-temporal filters with different orientations, half-squaring operation and divisive normalization were adopted to obtain the responses of V1 simple cells; then, an adjustable parameter was added to the output weight so that the response of complex cells was got. Experimental results indicate that the proposed V1 model can perceive motion information well. Besides, it has a good edge detection capability. The model inspired by V1 has good performance in feature extraction and effectively combines brain-inspired intelligence with computer vision.

Derivation of the spin-glass order parameter from stochastic thermodynamics

NASA Astrophysics Data System (ADS)

Crisanti, A.; Picco, M.; Ritort, F.

2018-05-01

A fluctuation relation is derived to extract the order parameter function q (x ) in weakly ergodic systems. The relation is based on measuring and classifying entropy production fluctuations according to the value of the overlap q between configurations. For a fixed value of q , entropy production fluctuations are Gaussian distributed allowing us to derive the quasi-FDT so characteristic of aging systems. The theory is validated by extracting the q (x ) in various types of glassy models. It might be generally applicable to other nonequilibrium systems and experimental small systems.

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

Reactive extraction at liquid-liquid systems

NASA Astrophysics Data System (ADS)

Wieszczycka, Karolina

2018-01-01

The chapter summarizes the state of knowledge about a metal transport in two-phase system. The first part of this review focuses on the distribution law and main factors determination in classical solvent extraction (solubility and polarity of the solute, as well as inter- and intramolecules interaction. Next part of the chapter is devoted to the reactive solvent extraction and the molecular modeling requiring knowledge on type of extractants, complexation mechanisms, metals ions speciation and oxidation during complexes forming, and other parameters that enable to understand the extraction process. Also the kinetic data that is needed for proper modeling, simulation and design of processes needed for critical separations are discussed. Extraction at liquid-solid system using solvent impregnated resins is partially identical as in the case of the corresponding solvent extraction, therefore this subject was also presented in all aspects of separation process (equilibrium, mechanism, kinetics).

Joint models for longitudinal and time-to-event data: a review of reporting quality with a view to meta-analysis.

PubMed

Sudell, Maria; Kolamunnage-Dona, Ruwanthi; Tudur-Smith, Catrin

2016-12-05

Joint models for longitudinal and time-to-event data are commonly used to simultaneously analyse correlated data in single study cases. Synthesis of evidence from multiple studies using meta-analysis is a natural next step but its feasibility depends heavily on the standard of reporting of joint models in the medical literature. During this review we aim to assess the current standard of reporting of joint models applied in the literature, and to determine whether current reporting standards would allow or hinder future aggregate data meta-analyses of model results. We undertook a literature review of non-methodological studies that involved joint modelling of longitudinal and time-to-event medical data. Study characteristics were extracted and an assessment of whether separate meta-analyses for longitudinal, time-to-event and association parameters were possible was made. The 65 studies identified used a wide range of joint modelling methods in a selection of software. Identified studies concerned a variety of disease areas. The majority of studies reported adequate information to conduct a meta-analysis (67.7% for longitudinal parameter aggregate data meta-analysis, 69.2% for time-to-event parameter aggregate data meta-analysis, 76.9% for association parameter aggregate data meta-analysis). In some cases model structure was difficult to ascertain from the published reports. Whilst extraction of sufficient information to permit meta-analyses was possible in a majority of cases, the standard of reporting of joint models should be maintained and improved. Recommendations for future practice include clear statement of model structure, of values of estimated parameters, of software used and of statistical methods applied.

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

Fernandes, P. A.; Lynch, K. A.

Here, we define the observational parameter regime necessary for observing low-altitude ionospheric origins of high-latitude ion upflow/outflow. We present measurement challenges and identify a new analysis technique which mitigates these impediments. To probe the initiation of auroral ion upflow, it is necessary to examine the thermal ion population at 200-350 km, where typical thermal energies are tenths of eV. Interpretation of the thermal ion distribution function measurement requires removal of payload sheath and ram effects. We use a 3-D Maxwellian model to quantify how observed ionospheric parameters such as density, temperature, and flows affect in situ measurements of the thermalmore » ion distribution function. We define the viable acceptance window of a typical top-hat electrostatic analyzer in this regime and show that the instrument's energy resolution prohibits it from directly observing the shape of the particle spectra. To extract detailed information about measured particle population, we define two intermediate parameters from the measured distribution function, then use a Maxwellian model to replicate possible measured parameters for comparison to the data. Liouville's theorem and the thin-sheath approximation allow us to couple the measured and modeled intermediate parameters such that measurements inside the sheath provide information about plasma outside the sheath. We apply this technique to sounding rocket data to show that careful windowing of the data and Maxwellian models allows for extraction of the best choice of geophysical parameters. More widespread use of this analysis technique will help our community expand its observational database of the seed regions of ionospheric outflows.« less

Mars Colony in situ resource utilization: An integrated architecture and economics model

NASA Astrophysics Data System (ADS)

Shishko, Robert; Fradet, René; Do, Sydney; Saydam, Serkan; Tapia-Cortez, Carlos; Dempster, Andrew G.; Coulton, Jeff

2017-09-01

This paper reports on our effort to develop an ensemble of specialized models to explore the commercial potential of mining water/ice on Mars in support of a Mars Colony. This ensemble starts with a formal systems architecting framework to describe a Mars Colony and capture its artifacts' parameters and technical attributes. The resulting database is then linked to a variety of ;downstream; analytic models. In particular, we integrated an extraction process (i.e., ;mining;) model, a simulation of the colony's environmental control and life support infrastructure known as HabNet, and a risk-based economics model. The mining model focuses on the technologies associated with in situ resource extraction, processing, storage and handling, and delivery. This model computes the production rate as a function of the systems' technical parameters and the local Mars environment. HabNet simulates the fundamental sustainability relationships associated with establishing and maintaining the colony's population. The economics model brings together market information, investment and operating costs, along with measures of market uncertainty and Monte Carlo techniques, with the objective of determining the profitability of commercial water/ice in situ mining operations. All told, over 50 market and technical parameters can be varied in order to address ;what-if; questions, including colony location.

Probing Quark-Gluon-Plasma properties with a Bayesian model-to-data comparison

NASA Astrophysics Data System (ADS)

Cai, Tianji; Bernhard, Jonah; Ke, Weiyao; Bass, Steffen; Duke QCD Group Team

2016-09-01

Experiments at RHIC and LHC study a special state of matter called the Quark Gluon Plasma (QGP), where quarks and gluons roam freely, by colliding relativistic heavy-ions. Given the transitory nature of the QGP, its properties can only be explored by comparing computational models of its formation and evolution to experimental data. The models fall, roughly speaking, under two categories-those solely using relativistic viscous hydrodynamics (pure hydro model) and those that in addition couple to a microscopic Boltzmann transport for the later evolution of the hadronic decay products (hybrid model). Each of these models has multiple parameters that encode the physical properties we want to probe and that need to be calibrated to experimental data, a task which is computationally expensive, but necessary for the knowledge extraction and determination of the models' quality. Our group has developed an analysis technique based on Bayesian Statistics to perform the model calibration and to extract probability distributions for each model parameter. Following the previous work that applies the technique to the hybrid model, we now perform a similar analysis on a pure-hydro model and display the posterior distributions for the same set of model parameters. We also develop a set of criteria to assess the quality of the two models with respect to their ability to describe current experimental data. Funded by Duke University Goldman Sachs Research Fellowship.

Regression analysis and transfer function in estimating the parameters of central pulse waves from brachial pulse wave.

PubMed

Chai Rui; Li Si-Man; Xu Li-Sheng; Yao Yang; Hao Li-Ling

2017-07-01

This study mainly analyzed the parameters such as ascending branch slope (A_slope), dicrotic notch height (Hn), diastolic area (Ad) and systolic area (As) diastolic blood pressure (DBP), systolic blood pressure (SBP), pulse pressure (PP), subendocardial viability ratio (SEVR), waveform parameter (k), stroke volume (SV), cardiac output (CO) and peripheral resistance (RS) of central pulse wave invasively and non-invasively measured. These parameters extracted from the central pulse wave invasively measured were compared with the parameters measured from the brachial pulse waves by a regression model and a transfer function model. The accuracy of the parameters which were estimated by the regression model and the transfer function model was compared too. Our findings showed that in addition to the k value, the above parameters of the central pulse wave and the brachial pulse wave invasively measured had positive correlation. Both the regression model parameters including A_slope, DBP, SEVR and the transfer function model parameters had good consistency with the parameters invasively measured, and they had the same effect of consistency. The regression equations of the three parameters were expressed by Y'=a+bx. The SBP, PP, SV, CO of central pulse wave could be calculated through the regression model, but their accuracies were worse than that of transfer function model.

Spectral Analysis and Experimental Modeling of Ice Accretion Roughness

NASA Technical Reports Server (NTRS)

Orr, D. J.; Breuer, K. S.; Torres, B. E.; Hansman, R. J., Jr.

1996-01-01

A self-consistent scheme for relating wind tunnel ice accretion roughness to the resulting enhancement of heat transfer is described. First, a spectral technique of quantitative analysis of early ice roughness images is reviewed. The image processing scheme uses a spectral estimation technique (SET) which extracts physically descriptive parameters by comparing scan lines from the experimentally-obtained accretion images to a prescribed test function. Analysis using this technique for both streamwise and spanwise directions of data from the NASA Lewis Icing Research Tunnel (IRT) are presented. An experimental technique is then presented for constructing physical roughness models suitable for wind tunnel testing that match the SET parameters extracted from the IRT images. The icing castings and modeled roughness are tested for enhancement of boundary layer heat transfer using infrared techniques in a "dry" wind tunnel.

Comparison of contact conditions obtained by direct simulation with statistical analysis for normally distributed isotropic surfaces

NASA Astrophysics Data System (ADS)

Uchidate, M.

2018-09-01

In this study, with the aim of establishing a systematic knowledge on the impact of summit extraction methods and stochastic model selection in rough contact analysis, the contact area ratio (A r /A a ) obtained by statistical contact models with different summit extraction methods was compared with a direct simulation using the boundary element method (BEM). Fifty areal topography datasets with different autocorrelation functions in terms of the power index and correlation length were used for investigation. The non-causal 2D auto-regressive model which can generate datasets with specified parameters was employed in this research. Three summit extraction methods, Nayak’s theory, 8-point analysis and watershed segmentation, were examined. With regard to the stochastic model, Bhushan’s model and BGT (Bush-Gibson-Thomas) model were applied. The values of A r /A a from the stochastic models tended to be smaller than BEM. The discrepancy between the Bhushan’s model with the 8-point analysis and BEM was slightly smaller than Nayak’s theory. The results with the watershed segmentation was similar to those with the 8-point analysis. The impact of the Wolf pruning on the discrepancy between the stochastic analysis and BEM was not very clear. In case of the BGT model which employs surface gradients, good quantitative agreement against BEM was obtained when the Nayak’s bandwidth parameter was large.

Impact of one-layer assumption on diffuse reflectance spectroscopy of skin

NASA Astrophysics Data System (ADS)

Hennessy, Ricky; Markey, Mia K.; Tunnell, James W.

2015-02-01

Diffuse reflectance spectroscopy (DRS) can be used to noninvasively measure skin properties. To extract skin properties from DRS spectra, you need a model that relates the reflectance to the tissue properties. Most models are based on the assumption that skin is homogenous. In reality, skin is composed of multiple layers, and the homogeneity assumption can lead to errors. In this study, we analyze the errors caused by the homogeneity assumption. This is accomplished by creating realistic skin spectra using a computational model, then extracting properties from those spectra using a one-layer model. The extracted parameters are then compared to the parameters used to create the modeled spectra. We used a wavelength range of 400 to 750 nm and a source detector separation of 250 μm. Our results show that use of a one-layer skin model causes underestimation of hemoglobin concentration [Hb] and melanin concentration [mel]. Additionally, the magnitude of the error is dependent on epidermal thickness. The one-layer assumption also causes [Hb] and [mel] to be correlated. Oxygen saturation is overestimated when it is below 50% and underestimated when it is above 50%. We also found that the vessel radius factor used to account for pigment packaging is correlated with epidermal thickness.

UFCN: a fully convolutional neural network for road extraction in RGB imagery acquired by remote sensing from an unmanned aerial vehicle

NASA Astrophysics Data System (ADS)

Kestur, Ramesh; Farooq, Shariq; Abdal, Rameen; Mehraj, Emad; Narasipura, Omkar; Mudigere, Meenavathi

2018-01-01

Road extraction in imagery acquired by low altitude remote sensing (LARS) carried out using an unmanned aerial vehicle (UAV) is presented. LARS is carried out using a fixed wing UAV with a high spatial resolution vision spectrum (RGB) camera as the payload. Deep learning techniques, particularly fully convolutional network (FCN), are adopted to extract roads by dense semantic segmentation. The proposed model, UFCN (U-shaped FCN) is an FCN architecture, which is comprised of a stack of convolutions followed by corresponding stack of mirrored deconvolutions with the usage of skip connections in between for preserving the local information. The limited dataset (76 images and their ground truths) is subjected to real-time data augmentation during training phase to increase the size effectively. Classification performance is evaluated using precision, recall, accuracy, F1 score, and brier score parameters. The performance is compared with support vector machine (SVM) classifier, a one-dimensional convolutional neural network (1D-CNN) model, and a standard two-dimensional CNN (2D-CNN). The UFCN model outperforms the SVM, 1D-CNN, and 2D-CNN models across all the performance parameters. Further, the prediction time of the proposed UFCN model is comparable with SVM, 1D-CNN, and 2D-CNN models.

Validation of Slosh Model Parameters and Anti-Slosh Baffle Designs of Propellant Tanks by Using Lateral Slosh Testing

NASA Technical Reports Server (NTRS)

Perez, Jose G.; Parks, Russel, A.; Lazor, Daniel R.

2012-01-01

The slosh dynamics of propellant tanks can be represented by an equivalent mass-pendulum-dashpot mechanical model. The parameters of this equivalent model, identified as slosh mechanical model parameters, are slosh frequency, slosh mass, and pendulum hinge point location. They can be obtained by both analysis and testing for discrete fill levels. Anti-slosh baffles are usually needed in propellant tanks to control the movement of the fluid inside the tank. Lateral slosh testing, involving both random excitation testing and free-decay testing, are performed to validate the slosh mechanical model parameters and the damping added to the fluid by the anti-slosh baffles. Traditional modal analysis procedures were used to extract the parameters from the experimental data. Test setup of sub-scale tanks will be described. A comparison between experimental results and analysis will be presented.

Validation of Slosh Model Parameters and Anti-Slosh Baffle Designs of Propellant Tanks by Using Lateral Slosh Testing

NASA Technical Reports Server (NTRS)

Perez, Jose G.; Parks, Russel A.; Lazor, Daniel R.

2012-01-01

The slosh dynamics of propellant tanks can be represented by an equivalent pendulum-mass mechanical model. The parameters of this equivalent model, identified as slosh model parameters, are slosh mass, slosh mass center of gravity, slosh frequency, and smooth-wall damping. They can be obtained by both analysis and testing for discrete fill heights. Anti-slosh baffles are usually needed in propellant tanks to control the movement of the fluid inside the tank. Lateral slosh testing, involving both random testing and free-decay testing, are performed to validate the slosh model parameters and the damping added to the fluid by the anti-slosh baffles. Traditional modal analysis procedures are used to extract the parameters from the experimental data. Test setup of sub-scale test articles of cylindrical and spherical shapes will be described. A comparison between experimental results and analysis will be presented.

Self-consistent modeling of electron cyclotron resonance ion sources

NASA Astrophysics Data System (ADS)

Girard, A.; Hitz, D.; Melin, G.; Serebrennikov, K.; Lécot, C.

2004-05-01

In order to predict the performances of electron cyclotron resonance ion source (ECRIS), it is necessary to perfectly model the different parts of these sources: (i) magnetic configuration; (ii) plasma characteristics; (iii) extraction system. The magnetic configuration is easily calculated via commercial codes; different codes also simulate the ion extraction, either in two dimension, or even in three dimension (to take into account the shape of the plasma at the extraction influenced by the hexapole). However the characteristics of the plasma are not always mastered. This article describes the self-consistent modeling of ECRIS: we have developed a code which takes into account the most important construction parameters: the size of the plasma (length, diameter), the mirror ratio and axial magnetic profile, whether a biased probe is installed or not. These input parameters are used to feed a self-consistent code, which calculates the characteristics of the plasma: electron density and energy, charge state distribution, plasma potential. The code is briefly described, and some of its most interesting results are presented. Comparisons are made between the calculations and the results obtained experimentally.

Anticonvulsant activity of Aloe vera leaf extract in acute and chronic models of epilepsy in mice.

PubMed

Rathor, Naveen; Arora, Tarun; Manocha, Sachin; Patil, Amol N; Mediratta, Pramod K; Sharma, Krishna K

2014-03-01

The effect of Aloe vera in epilepsy has not yet been explored. This study was done to explore the effect of aqueous extract of Aloe vera leaf powder on three acute and one chronic model of epilepsy. In acute study, aqueous extract of Aloe vera leaf (extract) powder was administered in doses 100, 200 and 400 mg/kg p.o. Dose of 400 mg/kg of Aloe vera leaf extract was chosen for chronic administration. Oxidative stress parameters viz. malondialdehyde (MDA) and reduced glutathione (GSH) were also estimated in brain of kindled animals. In acute study, Aloe vera leaf (extract) powder in a dose-dependent manner significantly decreased duration of tonic hind limb extension in maximal electroshock seizure model, increased seizure threshold current in increasing current electroshock seizure model, and increased latency to onset and decreased duration of clonic convulsion in pentylenetetrazole (PTZ) model as compared with control group. In chronic study, Aloe vera leaf (extract) powder prevented progression of kindling in PTZ-kindled mice. Aloe vera leaf (extract) powder 400 mg/kg p.o. also reduced brain levels of MDA and increased GSH levels as compared to the PTZ-kindled non-treated group. The results of study showed that Aloe vera leaf (extract) powder possessed significant anticonvulsant and anti-oxidant activity. © 2013 Royal Pharmaceutical Society.

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.

A portable foot-parameter-extracting system

NASA Astrophysics Data System (ADS)

Zhang, MingKai; Liang, Jin; Li, Wenpan; Liu, Shifan

2016-03-01

In order to solve the problem of automatic foot measurement in garment customization, a new automatic footparameter- extracting system based on stereo vision, photogrammetry and heterodyne multiple frequency phase shift technology is proposed and implemented. The key technologies applied in the system are studied, including calibration of projector, alignment of point clouds, and foot measurement. Firstly, a new projector calibration algorithm based on plane model has been put forward to get the initial calibration parameters and a feature point detection scheme of calibration board image is developed. Then, an almost perfect match of two clouds is achieved by performing a first alignment using the Sampled Consensus - Initial Alignment algorithm (SAC-IA) and refining the alignment using the Iterative Closest Point algorithm (ICP). Finally, the approaches used for foot-parameterextracting and the system scheme are presented in detail. Experimental results show that the RMS error of the calibration result is 0.03 pixel and the foot parameter extracting experiment shows the feasibility of the extracting algorithm. Compared with the traditional measurement method, the system can be more portable, accurate and robust.

Linearly Supporting Feature Extraction for Automated Estimation of Stellar Atmospheric Parameters

NASA Astrophysics Data System (ADS)

Li, Xiangru; Lu, Yu; Comte, Georges; Luo, Ali; Zhao, Yongheng; Wang, Yongjun

2015-05-01

We describe a scheme to extract linearly supporting (LSU) features from stellar spectra to automatically estimate the atmospheric parameters {{T}{\\tt{eff} }}, log g, and [Fe/H]. “Linearly supporting” means that the atmospheric parameters can be accurately estimated from the extracted features through a linear model. The successive steps of the process are as follow: first, decompose the spectrum using a wavelet packet (WP) and represent it by the derived decomposition coefficients; second, detect representative spectral features from the decomposition coefficients using the proposed method Least Absolute Shrinkage and Selection Operator (LARS)bs; third, estimate the atmospheric parameters {{T}{\\tt{eff} }}, log g, and [Fe/H] from the detected features using a linear regression method. One prominent characteristic of this scheme is its ability to evaluate quantitatively the contribution of each detected feature to the atmospheric parameter estimate and also to trace back the physical significance of that feature. This work also shows that the usefulness of a component depends on both the wavelength and frequency. The proposed scheme has been evaluated on both real spectra from the Sloan Digital Sky Survey (SDSS)/SEGUE and synthetic spectra calculated from Kurucz's NEWODF models. On real spectra, we extracted 23 features to estimate {{T}{\\tt{eff} }}, 62 features for log g, and 68 features for [Fe/H]. Test consistencies between our estimates and those provided by the Spectroscopic Parameter Pipeline of SDSS show that the mean absolute errors (MAEs) are 0.0062 dex for log {{T}{\\tt{eff} }} (83 K for {{T}{\\tt{eff} }}), 0.2345 dex for log g, and 0.1564 dex for [Fe/H]. For the synthetic spectra, the MAE test accuracies are 0.0022 dex for log {{T}{\\tt{eff} }} (32 K for {{T}{\\tt{eff} }}), 0.0337 dex for log g, and 0.0268 dex for [Fe/H].

Inactivation disinfection property of Moringa Oleifera seed extract: optimization and kinetic studies

NASA Astrophysics Data System (ADS)

Idris, M. A.; Jami, M. S.; Hammed, A. M.

2017-05-01

This paper presents the statistical optimization study of disinfection inactivation parameters of defatted Moringa oleifera seed extract on Pseudomonas aeruginosa bacterial cells. Three level factorial design was used to estimate the optimum range and the kinetics of the inactivation process was also carried. The inactivation process involved comparing different disinfection models of Chicks-Watson, Collins-Selleck and Homs models. The results from analysis of variance (ANOVA) of the statistical optimization process revealed that only contact time was significant. The optimum disinfection range of the seed extract was 125 mg/L, 30 minutes and 120rpm agitation. At the optimum dose, the inactivation kinetics followed the Collin-Selleck model with coefficient of determination (R2) of 0.6320. This study is the first of its kind in determining the inactivation kinetics of pseudomonas aeruginosa using the defatted seed extract.

A novel compact model for on-chip stacked transformers in RF-CMOS technology

NASA Astrophysics Data System (ADS)

Jun, Liu; Jincai, Wen; Qian, Zhao; Lingling, Sun

2013-08-01

A novel compact model for on-chip stacked transformers is presented. The proposed model topology gives a clear distinction to the eddy current, resistive and capacitive losses of the primary and secondary coils in the substrate. A method to analytically determine the non-ideal parasitics between the primary coil and substrate is provided. The model is further verified by the excellent match between the measured and simulated S -parameters on the extracted parameters for a 1 : 1 stacked transformer manufactured in a commercial RF-CMOS technology.

Theoretical models for supercritical fluid extraction.

PubMed

Huang, Zhen; Shi, Xiao-Han; Jiang, Wei-Juan

2012-08-10

For the proper design of supercritical fluid extraction processes, it is essential to have a sound knowledge of the mass transfer mechanism of the extraction process and the appropriate mathematical representation. In this paper, the advances and applications of kinetic models for describing supercritical fluid extraction from various solid matrices have been presented. The theoretical models overviewed here include the hot ball diffusion, broken and intact cell, shrinking core and some relatively simple models. Mathematical representations of these models have been in detail interpreted as well as their assumptions, parameter identifications and application examples. Extraction process of the analyte solute from the solid matrix by means of supercritical fluid includes the dissolution of the analyte from the solid, the analyte diffusion in the matrix and its transport to the bulk supercritical fluid. Mechanisms involved in a mass transfer model are discussed in terms of external mass transfer resistance, internal mass transfer resistance, solute-solid interactions and axial dispersion. The correlations of the external mass transfer coefficient and axial dispersion coefficient with certain dimensionless numbers are also discussed. Among these models, the broken and intact cell model seems to be the most relevant mathematical model as it is able to provide realistic description of the plant material structure for better understanding the mass-transfer kinetics and thus it has been widely employed for modeling supercritical fluid extraction of natural matters. Copyright © 2012 Elsevier B.V. All rights reserved.

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

Extracting surface diffusion coefficients from batch adsorption measurement data: application of the classic Langmuir kinetics model.

PubMed

Chu, Khim Hoong

2017-11-09

Surface diffusion coefficients may be estimated by fitting solutions of a diffusion model to batch kinetic data. For non-linear systems, a numerical solution of the diffusion model's governing equations is generally required. We report here the application of the classic Langmuir kinetics model to extract surface diffusion coefficients from batch kinetic data. The use of the Langmuir kinetics model in lieu of the conventional surface diffusion model allows derivation of an analytical expression. The parameter estimation procedure requires determining the Langmuir rate coefficient from which the pertinent surface diffusion coefficient is calculated. Surface diffusion coefficients within the 10 -9 to 10 -6  cm 2 /s range obtained by fitting the Langmuir kinetics model to experimental kinetic data taken from the literature are found to be consistent with the corresponding values obtained from the traditional surface diffusion model. The virtue of this simplified parameter estimation method is that it reduces the computational complexity as the analytical expression involves only an algebraic equation in closed form which is easily evaluated by spreadsheet computation.

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.

Wound healing activity of Sida cordifolia Linn. in rats.

PubMed

Pawar, Rajesh S; Chaurasiya, Pradeep K; Rajak, Harish; Singour, Pradeep K; Toppo, Fedelic Ashish; Jain, Ankit

2013-01-01

The present study provides a scientific evaluation for the wound healing potential of ethanolic (EtOH) extract of Sida cordifolia Linn. (SCL) plant. Excision, incision and burn wounds were inflicted upon three groups of six rats each. Group I was assigned as control (ointment base). Group II was treated with 10% EtOH extract ointment. Group III was treated with standard silver sulfadiazine (0.01%) cream. The parameters observed were percentage of wound contraction, epithelialization period, hydroxyproline content, tensile strength including histopathological studies. It was noted that the effect produced by the ethanolic extract of SCL ointment showed significant (P < 0.01) healing in all wound models when compared with the control group. All parameters such as wound contraction, epithelialization period, hydroxyproline content, tensile strength and histopathological studies showed significant (P < 0.01) changes when compared with the control. The ethanolic extract ointment of SCL effectively stimulates wound contraction; increases tensile strength of excision, incision and burn wounds.

Differential Geometry Applied To Least-Square Error Surface Approximations

NASA Astrophysics Data System (ADS)

Bolle, Ruud M.; Sabbah, Daniel

1987-08-01

This paper focuses on extraction of the parameters of individual surfaces from noisy depth maps. The basis for this are least-square error polynomial approximations to the range data and the curvature properties that can be computed from these approximations. The curvature properties are derived using the invariants of the Weingarten Map evaluated at the origin of local coordinate systems centered at the range points. The Weingarten Map is a well-known concept in differential geometry; a brief treatment of the differential geometry pertinent to surface curvature is given. We use the curvature properties for extracting certain surface parameters from the curvature properties of the approximations. Then we show that curvature properties alone are not enough to obtain all the parameters of the surfaces; higher order properties (information about change of curvature) are needed to obtain full parametric descriptions. This surface parameter estimation problem arises in the design of a vision system to recognize 3D objects whose surfaces are composed of planar patches and patches of quadrics of revolution. (Quadrics of revolution are quadrics that are surfaces of revolution.) A significant portion of man-made objects can be modeled using these surfaces. The actual process of recognition and parameter extraction is framed as a set of stacked parameter space transforms. The transforms are "stacked" in the sense that any one transform computes only a partial geometric description that forms the input to the next transform. Those who are interested in the organization and control of the recognition and parameter recognition process are referred to [Sabbah86], this paper briefly touches upon the organization, but concentrates mainly on geometrical aspects of the parameter extraction.

A modified temporal criterion to meta-optimize the extended Kalman filter for land cover classification of remotely sensed time series

NASA Astrophysics Data System (ADS)

Salmon, B. P.; Kleynhans, W.; Olivier, J. C.; van den Bergh, F.; Wessels, K. J.

2018-05-01

Humans are transforming land cover at an ever-increasing rate. Accurate geographical maps on land cover, especially rural and urban settlements are essential to planning sustainable development. Time series extracted from MODerate resolution Imaging Spectroradiometer (MODIS) land surface reflectance products have been used to differentiate land cover classes by analyzing the seasonal patterns in reflectance values. The proper fitting of a parametric model to these time series usually requires several adjustments to the regression method. To reduce the workload, a global setting of parameters is done to the regression method for a geographical area. In this work we have modified a meta-optimization approach to setting a regression method to extract the parameters on a per time series basis. The standard deviation of the model parameters and magnitude of residuals are used as scoring function. We successfully fitted a triply modulated model to the seasonal patterns of our study area using a non-linear extended Kalman filter (EKF). The approach uses temporal information which significantly reduces the processing time and storage requirements to process each time series. It also derives reliability metrics for each time series individually. The features extracted using the proposed method are classified with a support vector machine and the performance of the method is compared to the original approach on our ground truth data.

Description of the National Hydrologic Model for use with the Precipitation-Runoff Modeling System (PRMS)

USGS Publications Warehouse

Regan, R. Steven; Markstrom, Steven L.; Hay, Lauren E.; Viger, Roland J.; Norton, Parker A.; Driscoll, Jessica M.; LaFontaine, Jacob H.

2018-01-08

This report documents several components of the U.S. Geological Survey National Hydrologic Model of the conterminous United States for use with the Precipitation-Runoff Modeling System (PRMS). It provides descriptions of the (1) National Hydrologic Model, (2) Geospatial Fabric for National Hydrologic Modeling, (3) PRMS hydrologic simulation code, (4) parameters and estimation methods used to compute spatially and temporally distributed default values as required by PRMS, (5) National Hydrologic Model Parameter Database, and (6) model extraction tool named Bandit. The National Hydrologic Model Parameter Database contains values for all PRMS parameters used in the National Hydrologic Model. The methods and national datasets used to estimate all the PRMS parameters are described. Some parameter values are derived from characteristics of topography, land cover, soils, geology, and hydrography using traditional Geographic Information System methods. Other parameters are set to long-established default values and computation of initial values. Additionally, methods (statistical, sensitivity, calibration, and algebraic) were developed to compute parameter values on the basis of a variety of nationally-consistent datasets. Values in the National Hydrologic Model Parameter Database can periodically be updated on the basis of new parameter estimation methods and as additional national datasets become available. A companion ScienceBase resource provides a set of static parameter values as well as images of spatially-distributed parameters associated with PRMS states and fluxes for each Hydrologic Response Unit across the conterminuous United States.

Ionic liquid-salt aqueous two-phase extraction based on salting-out coupled with high-performance liquid chromatography for the determination of sulfonamides in water and food.

PubMed

Han, Juan; Wang, Yun; Liu, Yan; Li, Yanfang; Lu, Yang; Yan, Yongsheng; Ni, Liang

2013-02-01

Ionic liquid-salt aqueous two-phase extraction coupled with high-performance liquid chromatography with ultraviolet detection was developed for the determination of sulfonamides in water and food samples. In the procedure, the analytes were extracted from the aqueous samples into the ionic liquid top phase in one step. Three sulfonamides, sulfamerazine, sulfamethoxazole, and sulfamethizole were selected here as model compounds for developing and evaluating the method. The effects of various experimental parameters in extraction step were studied using two optimization methods, one variable at a time and Box-Behnken design. The results showed that the amount of sulfonamides did not have effect on the extraction efficiency. Therefore, a three-level Box-Behnken experimental design with three factors, which combined the response surface modeling, was used to optimize sulfonamides extraction. Under the most favorable extraction parameters, the detection limits (S/N = 3) and quantification limits (S/N = 10) of the proposed method for the target compounds were achieved within the range of 0.15-0.3 ng/mL and 0.5-1.0 ng/mL from spiked samples, respectively, which are lower than or comparable with other reported approaches applied to the determination of the same compounds. Finally, the proposed method was successfully applied to the determination of sulfonamide compounds in different water and food samples and satisfactory recoveries of spiked target compounds in real samples were obtained.

Immunomodulatory activity of methanolic extracts of fruits and bark of Ficus glomerata Roxb. in mice and on human neutrophils.

PubMed

Heroor, Sanjeev; Beknal, Arun Kumar; Mahurkar, Nitin

2013-01-01

To evaluate the immunomodulatory activity of methanolic extracts of fruit and bark of Ficus glomerata Roxb. on cyclophosphamide-induced myelosuppression in mice and the phagocytic effect on human neutrophils. Methanolic extracts of fruits and bark of Ficus glomerata Roxb. at two dose levels of 250 and 500 mg/kg p.o. were administered for 13 days to albino mice and cyclophosphamide (30 mg/kg i.p.) was administered on 11th, 12th, and 13th days, 1 hour after the administration of the respective treatment. On 14th day blood was collected and the hematological parameters were evaluated. The two extracts in the concentration range 100, 50, 25, 12 and 6.25 μg were also tested for phagocytic effect on human neutrophils using the in vitro models-nitroblue tetrazolium (NBT) dye test, phagocytosis of Candida albicans, and chemotaxis assay. Methanolic extracts of fruit and bark of Ficus glomerata Roxb. showed significant counteracting effect (P < 0.01) to cyclophosphamide-induced reduction in total WBC, differential leucocyte count, platelet counts, RBC counts, and hemoglobin levels. The extracts of the plant in the concentration range 100, 50, 25, 12, and 6.25 μg also showed significant (P < 0.01) phagocytic effect on human neutrophils in the parameters studied. Methanolic extracts of fruits and bark of Ficus glomerata Roxb. exhibited immunomodulatory property in both in vivo and in vitro models.

Optimization of Reflux Conditions for Total Flavonoid and Total Phenolic Extraction and Enhanced Antioxidant Capacity in Pandan (Pandanus amaryllifolius Roxb.) Using Response Surface Methodology

PubMed Central

Ghasemzadeh, Ali; Jaafar, Hawa Z. E.

2014-01-01

Response surface methodology was applied to optimization of the conditions for reflux extraction of Pandan (Pandanus amaryllifolius Roxb.) in order to achieve a high content of total flavonoids (TF), total phenolics (TP), and high antioxidant capacity (AC) in the extracts. Central composite experimental design with three factors and three levels was employed to consider the effects of the operation parameters, including the methanol concentration (MC, 40%–80%), extraction temperature (ET, 40–70°C), and liquid-to-solid ratio (LS ratio, 20–40 mL/g) on the properties of the extracts. Response surface plots showed that increasing these operation parameters induced the responses significantly. The TF content and AC could be maximized when the extraction conditions (MC, ET, and LS ratio) were 78.8%, 69.5°C, and 32.4 mL/g, respectively, whereas the TP content was optimal when these variables were 75.1%, 70°C, and 31.8 mL/g, respectively. Under these optimum conditions, the experimental TF and TP content and AC were 1.78, 6.601 mg/g DW, and 87.38%, respectively. The optimized model was validated by a comparison of the predicted and experimental values. The experimental values were found to be in agreement with the predicted values, indicating the suitability of the model for optimizing the conditions for the reflux extraction of Pandan. PMID:25147852

Fault Detection of Bearing Systems through EEMD and Optimization Algorithm

PubMed Central

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

2017-01-01

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

Assessing the environmental availability of sulfamethoxazole and its acetylated metabolite in agricultural soils amended with compost and manure: an experimental and modeling study

NASA Astrophysics Data System (ADS)

Goulas, Anaïs; Sertillange, Nicolas; Garnier, Patricia; Dumény, Valérie; Bergheaud, Valérie; Benoit, Pierre; Haudin, Claire-Sophie

2017-04-01

The recycling of sludge compost and farmyard manure in agriculture can lead to the introduction of sulfonamide antibiotics and their acetylated metabolites into soils. The quality and the biodegradability of the exogenous organic matter (EOM) containing antibiotic residues is determinant for their environmental availability and fate in soils (Goulas et al., 2016). This study combined experimental and modeling approaches in order to: 1) assess the fraction of sulfamethoxazole (SMX) and N-acetyl-sulfamethoxazole (AcSMX) available in EOM-amended soils by using soft extractions (CaCl2, EDTA or cyclodextrin solutions) during a 28-day incubation; and 2) better understand the dynamics of sulfonamide residues in amended soils in connection with their availability and the mineralization of EOM organic matter thanks to the COP-Soil model (Geng et al. 2015). This model proposes several options to couple the biotransformation of organic pollutants (OP) with the decomposition of EOM in soil. The microbial degradation can be simulated by co-metabolism and specific-metabolism. The model also accounts for the formation of non-extractable residues (NER) via both physicochemical and microbial routes. The available fraction in both soil/EOM mixtures decreased from 56-96% and 31-63% initial 14C-activity for AcSMX and SMX, respectively, to reach 7-33% after 28 days. This high decrease in the first seven days was mainly due to the formation of NER that were more abundant in soil/manure mixtures than in the soil/compost ones. The three aqueous solutions differently extracted the available 14C-residues according to the incubation time, the EOM and the molecule. The mineralized fractions for both 14C-molecules were only 2-3% with a little more mineralization in the soil/manure mixtures than in the soil/compost. By using the COP-Soil model, the dynamics of EOM and OP were well described using parameter values specific to the organic matter mineralization, and this for the three soft extractants used. Others parameter values were common to both EOM and both sulfonamide compounds when coupling the dynamics of OP to EOM with the assumption of co-metabolism. The set of parameter values describing the pollutant fate strongly differed according to the soft extractant, confirming different mechanisms of extraction. Globally, the best OP simulations were obtained for the CaCl2-based extraction. Keywords Sulfonamides; environmental availability; recycling; organic matter; modeling References Goulas A. Haudin C.-S., Bergheaud V., Dumény V., Fehri S., Bourdat-Deschamps M, Nelieu S., Benoit P. 2016. A new extraction method to assess the environmental availability of ciprofloxacin in agricultural soil amended with exogenous organic matters. Chemosphere, 165, 460-469. Geng C., Haudin C.-S., Zhang Y., Lashermes G., Houot S., Garnier P.. 2015. Modelling the release of organic contaminants during compost decomposition in soil. Chemosphere, 119: 423-431.

VizieR Online Data Catalog: Fundamental parameters of Kepler stars (Silva Aguirre+, 2015)

NASA Astrophysics Data System (ADS)

Silva Aguirre, V.; Davies, G. R.; Basu, S.; Christensen-Dalsgaard, J.; Creevey, O.; Metcalfe, T. S.; Bedding, T. R.; Casagrande, L.; Handberg, R.; Lund, M. N.; Nissen, P. E.; Chaplin, W. J.; Huber, D.; Serenelli, A. M.; Stello, D.; van Eylen, V.; Campante, T. L.; Elsworth, Y.; Gilliland, R. L.; Hekker, S.; Karoff, C.; Kawaler, S. D.; Kjeldsen, H.; Lundkvist, M. S.

2016-02-01

Our sample has been extracted from the 77 exoplanet host stars presented in Huber et al. (2013, Cat. J/ApJ/767/127). We have made use of the full time-base of observations from the Kepler satellite to uniformly determine precise fundamental stellar parameters, including ages, for a sample of exoplanet host stars where high-quality asteroseismic data were available. We devised a Bayesian procedure flexible in its input and applied it to different grids of models to study systematics from input physics and extract statistically robust properties for all stars. (4 data files).

Experimental validation of a numerical 3-D finite model applied to wind turbines design under vibration constraints: TREVISE platform

NASA Astrophysics Data System (ADS)

Sellami, Takwa; Jelassi, Sana; Darcherif, Abdel Moumen; Berriri, Hanen; Mimouni, Med Faouzi

2018-04-01

With the advancement of wind turbines towards complex structures, the requirement of trusty structural models has become more apparent. Hence, the vibration characteristics of the wind turbine components, like the blades and the tower, have to be extracted under vibration constraints. Although extracting the modal properties of blades is a simple task, calculating precise modal data for the whole wind turbine coupled to its tower/foundation is still a perplexing task. In this framework, this paper focuses on the investigation of the structural modeling approach of modern commercial micro-turbines. Thus, the structural model a complex designed wind turbine, which is Rutland 504, is established based on both experimental and numerical methods. A three-dimensional (3-D) numerical model of the structure was set up based on the finite volume method (FVM) using the academic finite element analysis software ANSYS. To validate the created model, experimental vibration tests were carried out using the vibration test system of TREVISE platform at ECAM-EPMI. The tests were based on the experimental modal analysis (EMA) technique, which is one of the most efficient techniques for identifying structures parameters. Indeed, the poles and residues of the frequency response functions (FRF), between input and output spectra, were calculated to extract the mode shapes and the natural frequencies of the structure. Based on the obtained modal parameters, the numerical designed model was up-dated.

Dynamical compensation and structural identifiability of biological models: Analysis, implications, and reconciliation.

PubMed

Villaverde, Alejandro F; Banga, Julio R

2017-11-01

The concept of dynamical compensation has been recently introduced to describe the ability of a biological system to keep its output dynamics unchanged in the face of varying parameters. However, the original definition of dynamical compensation amounts to lack of structural identifiability. This is relevant if model parameters need to be estimated, as is often the case in biological modelling. Care should we taken when using an unidentifiable model to extract biological insight: the estimated values of structurally unidentifiable parameters are meaningless, and model predictions about unmeasured state variables can be wrong. Taking this into account, we explore alternative definitions of dynamical compensation that do not necessarily imply structural unidentifiability. Accordingly, we show different ways in which a model can be made identifiable while exhibiting dynamical compensation. Our analyses enable the use of the new concept of dynamical compensation in the context of parameter identification, and reconcile it with the desirable property of structural identifiability.

Analysis and Modeling of Echolocation Signals Emitted by Mediterranean Bottlenose Dolphins

NASA Astrophysics Data System (ADS)

Greco, Maria; Gini, Fulvio

2006-12-01

We analyzed the echolocation sounds emitted by Mediterranean bottlenose dolphins. We extracted the click trains by visual inspection of the data files recorded along the coast of the Tuscany with the collaboration of the CETUS Research Center. We modeled the extracted sonar clicks as Gaussian or exponential multicomponent signals, we estimated the characteristic parameters and compared the data with the reconstructed signals based on the estimates. Results about the estimation and the data fitting are largely shown in the paper.

Towards an integrative computational model for simulating tumor growth and response to radiation therapy

NASA Astrophysics Data System (ADS)

Marrero, Carlos Sosa; Aubert, Vivien; Ciferri, Nicolas; Hernández, Alfredo; de Crevoisier, Renaud; Acosta, Oscar

2017-11-01

Understanding the response to irradiation in cancer radiotherapy (RT) may help devising new strategies with improved tumor local control. Computational models may allow to unravel the underlying radiosensitive mechanisms intervening in the dose-response relationship. By using extensive simulations a wide range of parameters may be evaluated providing insights on tumor response thus generating useful data to plan modified treatments. We propose in this paper a computational model of tumor growth and radiation response which allows to simulate a whole RT protocol. Proliferation of tumor cells, cell life-cycle, oxygen diffusion, radiosensitivity, RT response and resorption of killed cells were implemented in a multiscale framework. The model was developed in C++, using the Multi-formalism Modeling and Simulation Library (M2SL). Radiosensitivity parameters extracted from literature enabled us to simulate in a regular grid (voxel-wise) a prostate cell tissue. Histopathological specimens with different aggressiveness levels extracted from patients after prostatectomy were used to initialize in silico simulations. Results on tumor growth exhibit a good agreement with data from in vitro studies. Moreover, standard fractionation of 2 Gy/fraction, with a total dose of 80 Gy as a real RT treatment was applied with varying radiosensitivity and oxygen diffusion parameters. As expected, the high influence of these parameters was observed by measuring the percentage of survival tumor cell after RT. This work paves the way to further models allowing to simulate increased doses in modified hypofractionated schemes and to develop new patient-specific combined therapies.

Removal of sodium lauryl sulphate by coagulation/flocculation with Moringa oleifera seed extract.

PubMed

Beltrán-Heredia, J; Sánchez-Martín, J

2009-05-30

Among other natural flocculant/coagulant agents, Moringa oleifera seed extract ability to remove an anionic surfactant has been evaluated and it has been found to be very interesting. Sodium lauryl sulphate was removed from aqueous solutions up to 80% through coagulation/flocculation process. pH and temperature were found to be not very important factors in removal efficiency. Freundlich (F), Frumkin-Fowler-Guggenheim (FFG) and Gu-Zhu (GZ) models were used to adjust experimental data in a solid-liquid adsorption hypothesis. Last one resulted to be the most accurate one. Several data fit parameters were determined, as Freundlich order, which was found to be 1.66, Flory-Huggins interaction parameter from FFG model, which was found to be 4.87; and limiting Moringa surfactant adsorption capacity from GZ model, which was found to be 2.13 x 10(-3)mol/g.

Optimization and adsorption kinetic studies of aqueous manganese ion removal using chitin extracted from shells of edible Philippine crabs

NASA Astrophysics Data System (ADS)

Quimque, Mark Tristan J.; Jimenez, Marvin C.; Acas, Meg Ina S.; Indoc, Danrelle Keth L.; Gomez, Enjelyn C.; Tabuñag, Jenny Syl D.

2017-01-01

Manganese is a common contaminant in drinking water along with other metal pollutants. This paper investigates the use of chitin, extracted from crab shells obtained as restaurant throwaway, as an adsorbent in removing manganese ions from aqueous medium. In particular, this aims to optimize the adsorption parameters and look into the kinetics of the process. The adsorption experiments done in this study employed the batch equilibration method. In the optimization, the following parameters were considered: pH and concentration of Mn (II) sorbate solution, particle size and dosage of adsorbent chitin, and adsorbent-adsorbate contact time. At the optimal condition, the order of the adsorption reaction was estimated using kinetic models which describes the process best. It was found out that the adsorption of aqueous Mn (II) ions onto chitin obeys the pseudo-second order model. This model assumes that the adsorption occurred via chemisorption

Electrostatic analyzer measurements of ionospheric thermal ion populations

DOE PAGES

Fernandes, P. A.; Lynch, K. A.

2016-07-09

Here, we define the observational parameter regime necessary for observing low-altitude ionospheric origins of high-latitude ion upflow/outflow. We present measurement challenges and identify a new analysis technique which mitigates these impediments. To probe the initiation of auroral ion upflow, it is necessary to examine the thermal ion population at 200-350 km, where typical thermal energies are tenths of eV. Interpretation of the thermal ion distribution function measurement requires removal of payload sheath and ram effects. We use a 3-D Maxwellian model to quantify how observed ionospheric parameters such as density, temperature, and flows affect in situ measurements of the thermalmore » ion distribution function. We define the viable acceptance window of a typical top-hat electrostatic analyzer in this regime and show that the instrument's energy resolution prohibits it from directly observing the shape of the particle spectra. To extract detailed information about measured particle population, we define two intermediate parameters from the measured distribution function, then use a Maxwellian model to replicate possible measured parameters for comparison to the data. Liouville's theorem and the thin-sheath approximation allow us to couple the measured and modeled intermediate parameters such that measurements inside the sheath provide information about plasma outside the sheath. We apply this technique to sounding rocket data to show that careful windowing of the data and Maxwellian models allows for extraction of the best choice of geophysical parameters. More widespread use of this analysis technique will help our community expand its observational database of the seed regions of ionospheric outflows.« less

HYDRORECESSION: A toolbox for streamflow recession analysis

NASA Astrophysics Data System (ADS)

Arciniega, S.

2015-12-01

Streamflow recession curves are hydrological signatures allowing to study the relationship between groundwater storage and baseflow and/or low flows at the catchment scale. Recent studies have showed that streamflow recession analysis can be quite sensitive to the combination of different models, extraction techniques and parameter estimation methods. In order to better characterize streamflow recession curves, new methodologies combining multiple approaches have been recommended. The HYDRORECESSION toolbox, presented here, is a Matlab graphical user interface developed to analyse streamflow recession time series with the support of different tools allowing to parameterize linear and nonlinear storage-outflow relationships through four of the most useful recession models (Maillet, Boussinesq, Coutagne and Wittenberg). The toolbox includes four parameter-fitting techniques (linear regression, lower envelope, data binning and mean squared error) and three different methods to extract hydrograph recessions segments (Vogel, Brutsaert and Aksoy). In addition, the toolbox has a module that separates the baseflow component from the observed hydrograph using the inverse reservoir algorithm. Potential applications provided by HYDRORECESSION include model parameter analysis, hydrological regionalization and classification, baseflow index estimates, catchment-scale recharge and low-flows modelling, among others. HYDRORECESSION is freely available for non-commercial and academic purposes.

Hippocampal effective synchronization values are not pre-seizure indicator without considering the state of the onset channels

PubMed Central

Shayegh, Farzaneh; Sadri, Saeed; Amirfattahi, Rassoul; Ansari-Asl, Karim; Bellanger, Jean-Jacques; Senhadji, Lotfi

2014-01-01

In this paper, a model-based approach is presented to quantify the effective synchrony between hippocampal areas from depth-EEG signals. This approach is based on the parameter identification procedure of a realistic Multi-Source/Multi-Channel (MSMC) hippocampal model that simulates the function of different areas of hippocampus. In the model it is supposed that the observed signals recorded using intracranial electrodes are generated by some hidden neuronal sources, according to some parameters. An algorithm is proposed to extract the intrinsic (solely relative to one hippocampal area) and extrinsic (coupling coefficients between two areas) model parameters, simultaneously, by a Maximum Likelihood (ML) method. Coupling coefficients are considered as the measure of effective synchronization. This work can be considered as an application of Dynamic Causal Modeling (DCM) that enables us to understand effective synchronization changes during transition from inter-ictal to pre -ictal state. The algorithm is first validated by using some synthetic datasets. Then by extracting the coupling coefficients of real depth-EEG signals by the proposed approach, it is observed that the coupling values show no significant difference between ictal, pre-ictal and inter-ictal states, i.e., either the increase or decrease of coupling coefficients has been observed in all states. However, taking the value of intrinsic parameters into account, pre-seizure state can be distinguished from inter-ictal state. It is claimed that seizures start to appear when there are seizure-related physiological parameters on the onset channel, and its coupling coefficient toward other channels increases simultaneously. As a result of considering both intrinsic and extrinsic parameters as the feature vector, inter-ictal, pre-ictal and ictal activities are discriminated from each other with an accuracy of 91.33% accuracy. PMID:25061815

An automatic scaling method for obtaining the trace and parameters from oblique ionogram based on hybrid genetic algorithm

NASA Astrophysics Data System (ADS)

Song, Huan; Hu, Yaogai; Jiang, Chunhua; Zhou, Chen; Zhao, Zhengyu; Zou, Xianjian

2016-12-01

Scaling oblique ionogram plays an important role in obtaining ionospheric structure at the midpoint of oblique sounding path. The paper proposed an automatic scaling method to extract the trace and parameters of oblique ionogram based on hybrid genetic algorithm (HGA). The extracted 10 parameters come from F2 layer and Es layer, such as maximum observation frequency, critical frequency, and virtual height. The method adopts quasi-parabolic (QP) model to describe F2 layer's electron density profile that is used to synthesize trace. And it utilizes secant theorem, Martyn's equivalent path theorem, image processing technology, and echoes' characteristics to determine seven parameters' best fit values, and three parameter's initial values in QP model to set up their searching spaces which are the needed input data of HGA. Then HGA searches the three parameters' best fit values from their searching spaces based on the fitness between the synthesized trace and the real trace. In order to verify the performance of the method, 240 oblique ionograms are scaled and their results are compared with manual scaling results and the inversion results of the corresponding vertical ionograms. The comparison results show that the scaling results are accurate or at least adequate 60-90% of the time.

Modelling space-based integral-field spectrographs and their application to Type Ia supernova cosmology

NASA Astrophysics Data System (ADS)

Shukla, Hemant; Bonissent, Alain

2017-04-01

We present the parameterized simulation of an integral-field unit (IFU) slicer spectrograph and its applications in spectroscopic studies, namely, for probing dark energy with type Ia supernovae. The simulation suite is called the fast-slicer IFU simulator (FISim). The data flow of FISim realistically models the optics of the IFU along with the propagation effects, including cosmological, zodiacal, instrumentation and detector effects. FISim simulates the spectrum extraction by computing the error matrix on the extracted spectrum. The applications for Type Ia supernova spectroscopy are used to establish the efficacy of the simulator in exploring the wider parametric space, in order to optimize the science and mission requirements. The input spectral models utilize the observables such as the optical depth and velocity of the Si II absorption feature in the supernova spectrum as the measured parameters for various studies. Using FISim, we introduce a mechanism for preserving the complete state of a system, called the partial p/partial f matrix, which allows for compression, reconstruction and spectrum extraction, we introduce a novel and efficient method for spectrum extraction, called super-optimal spectrum extraction, and we conduct various studies such as the optimal point spread function, optimal resolution, parameter estimation, etc. We demonstrate that for space-based telescopes, the optimal resolution lies in the region near R ˜ 117 for read noise of 1 e- and 7 e- using a 400 km s-1 error threshold on the Si II velocity.

[Optimization for supercritical CO2 extraction with response surface methodology of Prunus armeniaca oil].

PubMed

Chen, Fei-Fei; Wu, Yan; Ge, Fa-Huan

2012-03-01

To optimize the extraction conditions of Prunus armeniaca oil by Supercritical CO2 extraction and identify its components by GC-MS. Optimized of SFE-CO extraction by response surface methodology and used GC-MS to analysis Prunus armeniaca oil compounds. Established the model of an equation for the extraction rate of Prunus armeniaca oil by supercritical CO2 extraction, and the optimal parameters for the supercritical CO2 extraction determined by the equation were: the extraction pressure was 27 MPa, temperature was 39 degrees C, the extraction rate of Prunus armeniaca oil was 44.5%. 16 main compounds of Prunus armeniaca oil extracted by supercritical CO2 were identified by GC-MS, unsaturated fatty acids were 92.6%. This process is simple, and can be used for the extraction of Prunus armeniaca oil.

Determining fundamental properties of matter created in ultrarelativistic heavy-ion collisions

NASA Astrophysics Data System (ADS)

Novak, J.; Novak, K.; Pratt, S.; Vredevoogd, J.; Coleman-Smith, C. E.; Wolpert, R. L.

2014-03-01

Posterior distributions for physical parameters describing relativistic heavy-ion collisions, such as the viscosity of the quark-gluon plasma, are extracted through a comparison of hydrodynamic-based transport models to experimental results from 100AGeV+100AGeV Au +Au collisions at the Relativistic Heavy Ion Collider. By simultaneously varying six parameters and by evaluating several classes of observables, we are able to explore the complex intertwined dependencies of observables on model parameters. The methods provide a full multidimensional posterior distribution for the model output, including a range of acceptable values for each parameter, and reveal correlations between them. The breadth of observables and the number of parameters considered here go beyond previous studies in this field. The statistical tools, which are based upon Gaussian process emulators, are tested in detail and should be extendable to larger data sets and a higher number of parameters.

Estimation of trabecular bone parameters in children from multisequence MRI using texture-based regression

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

Lekadir, Karim, E-mail: karim.lekadir@upf.edu; Hoogendoorn, Corné; Armitage, Paul

Purpose: This paper presents a statistical approach for the prediction of trabecular bone parameters from low-resolution multisequence magnetic resonance imaging (MRI) in children, thus addressing the limitations of high-resolution modalities such as HR-pQCT, including the significant exposure of young patients to radiation and the limited applicability of such modalities to peripheral bones in vivo. Methods: A statistical predictive model is constructed from a database of MRI and HR-pQCT datasets, to relate the low-resolution MRI appearance in the cancellous bone to the trabecular parameters extracted from the high-resolution images. The description of the MRI appearance is achieved between subjects by usingmore » a collection of feature descriptors, which describe the texture properties inside the cancellous bone, and which are invariant to the geometry and size of the trabecular areas. The predictive model is built by fitting to the training data a nonlinear partial least square regression between the input MRI features and the output trabecular parameters. Results: Detailed validation based on a sample of 96 datasets shows correlations >0.7 between the trabecular parameters predicted from low-resolution multisequence MRI based on the proposed statistical model and the values extracted from high-resolution HRp-QCT. Conclusions: The obtained results indicate the promise of the proposed predictive technique for the estimation of trabecular parameters in children from multisequence MRI, thus reducing the need for high-resolution radiation-based scans for a fragile population that is under development and growth.« less

Extracting Damping Ratio from Dynamic Data and Numerical Solutions

NASA Technical Reports Server (NTRS)

Casiano, M. J.

2016-01-01

There are many ways to extract damping parameters from data or models. This Technical Memorandum provides a quick reference for some of the more common approaches used in dynamics analysis. Described are six methods of extracting damping from data: the half-power method, logarithmic decrement (decay rate) method, an autocorrelation/power spectral density fitting method, a frequency response fitting method, a random decrement fitting method, and a newly developed half-quadratic gain method. Additionally, state-space models and finite element method modeling tools, such as COMSOL Multiphysics (COMSOL), provide a theoretical damping via complex frequency. Each method has its advantages which are briefly noted. There are also likely many other advanced techniques in extracting damping within the operational modal analysis discipline, where an input excitation is unknown; however, these approaches discussed here are objective, direct, and can be implemented in a consistent manner.

Description of jambolan (Syzygium cumini (L.)) anthocyanin extraction kinetics at different stirring frequencies of the medium using diffusion models

NASA Astrophysics Data System (ADS)

da Silva, Wilton Pereira; Nunes, Jarderlany Sousa; Gomes, Josivanda Palmeira; de Araújo, Auryclennedy Calou; e Silva, Cleide M. D. P. S.

2018-05-01

Anthocyanin extraction kinetics was described for jambolan fruits. The spherical granules obtained were dried at 40 °C and the average radius of the sphere equivalent to the granules was determined. Solid-solvent ratio was fixed at 1:20 and temperature at 35 °C. A mixture of ethyl alcohol and hydrochloric acid (85:15) was used as solvent. Experiments were conducted with the following stirring frequencies: 0, 50, 100 and 150 rpm. Two diffusion models were used to describe the extraction process. The first one used an analytical solution, with boundary condition of the first kind. The second one used a numerical solution, with boundary condition of the third kind. The second model was the most adequate, and its results were used to determine empirical equations relating the process parameters with the stirring frequency, allowing to simulate new extraction kinetics.

Bias-dependent hybrid PKI empirical-neural model of microwave FETs

NASA Astrophysics Data System (ADS)

Marinković, Zlatica; Pronić-Rančić, Olivera; Marković, Vera

2011-10-01

Empirical models of microwave transistors based on an equivalent circuit are valid for only one bias point. Bias-dependent analysis requires repeated extractions of the model parameters for each bias point. In order to make model bias-dependent, a new hybrid empirical-neural model of microwave field-effect transistors is proposed in this article. The model is a combination of an equivalent circuit model including noise developed for one bias point and two prior knowledge input artificial neural networks (PKI ANNs) aimed at introducing bias dependency of scattering (S) and noise parameters, respectively. The prior knowledge of the proposed ANNs involves the values of the S- and noise parameters obtained by the empirical model. The proposed hybrid model is valid in the whole range of bias conditions. Moreover, the proposed model provides better accuracy than the empirical model, which is illustrated by an appropriate modelling example of a pseudomorphic high-electron mobility transistor device.

Microcrystalline silicon thin-film transistors for large area electronic applications

NASA Astrophysics Data System (ADS)

Chan, Kah-Yoong; Bunte, Eerke; Knipp, Dietmar; Stiebig, Helmut

2007-11-01

Thin-film transistors (TFTs) based on microcrystalline silicon (µc-Si:H) exhibit high charge carrier mobilities exceeding 35 cm2 V-1 s-1. The devices are fabricated by plasma-enhanced chemical vapor deposition at substrate temperatures below 200 °C. The fabrication process of the µc-Si:H TFTs is similar to the low temperature fabrication of amorphous silicon TFTs. The electrical characteristics of the µc-Si:H-based transistors will be presented. As the device charge carrier mobility of short channel TFTs is limited by the contacts, the influence of the drain and source contacts on the device parameters including the device charge carrier mobility and the device threshold voltage will be discussed. The experimental data will be described by a modified standard transistor model which accounts for the contact effects. Furthermore, the transmission line method was used to extract the device parameters including the contact resistance. The modified standard transistor model and the transmission line method will be compared in terms of the extracted device parameters and contact resistances.

Method for extracting relevant electrical parameters from graphene field-effect transistors using a physical model

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

Boscá, A., E-mail: alberto.bosca@upm.es; Dpto. de Ingeniería Electrónica, E.T.S.I. de Telecomunicación, Universidad Politécnica de Madrid, Madrid 28040; Pedrós, J.

2015-01-28

Due to its intrinsic high mobility, graphene has proved to be a suitable material for high-speed electronics, where graphene field-effect transistor (GFET) has shown excellent properties. In this work, we present a method for extracting relevant electrical parameters from GFET devices using a simple electrical characterization and a model fitting. With experimental data from the device output characteristics, the method allows to calculate parameters such as the mobility, the contact resistance, and the fixed charge. Differentiated electron and hole mobilities and direct connection with intrinsic material properties are some of the key aspects of this method. Moreover, the method outputmore » values can be correlated with several issues during key fabrication steps such as the graphene growth and transfer, the lithographic steps, or the metalization processes, providing a flexible tool for quality control in GFET fabrication, as well as a valuable feedback for improving the material-growth process.« less

Centrifugal compressor fault diagnosis based on qualitative simulation and thermal parameters

NASA Astrophysics Data System (ADS)

Lu, Yunsong; Wang, Fuli; Jia, Mingxing; Qi, Yuanchen

2016-12-01

This paper concerns fault diagnosis of centrifugal compressor based on thermal parameters. An improved qualitative simulation (QSIM) based fault diagnosis method is proposed to diagnose the faults of centrifugal compressor in a gas-steam combined-cycle power plant (CCPP). The qualitative models under normal and two faulty conditions have been built through the analysis of the principle of centrifugal compressor. To solve the problem of qualitative description of the observations of system variables, a qualitative trend extraction algorithm is applied to extract the trends of the observations. For qualitative states matching, a sliding window based matching strategy which consists of variables operating ranges constraints and qualitative constraints is proposed. The matching results are used to determine which QSIM model is more consistent with the running state of system. The correct diagnosis of two typical faults: seal leakage and valve stuck in the centrifugal compressor has validated the targeted performance of the proposed method, showing the advantages of fault roots containing in thermal parameters.

An analytical-numerical approach for parameter determination of a five-parameter single-diode model of photovoltaic cells and modules

NASA Astrophysics Data System (ADS)

Hejri, Mohammad; Mokhtari, Hossein; Azizian, Mohammad Reza; Söder, Lennart

2016-04-01

Parameter extraction of the five-parameter single-diode model of solar cells and modules from experimental data is a challenging problem. These parameters are evaluated from a set of nonlinear equations that cannot be solved analytically. On the other hand, a numerical solution of such equations needs a suitable initial guess to converge to a solution. This paper presents a new set of approximate analytical solutions for the parameters of a five-parameter single-diode model of photovoltaic (PV) cells and modules. The proposed solutions provide a good initial point which guarantees numerical analysis convergence. The proposed technique needs only a few data from the PV current-voltage characteristics, i.e. open circuit voltage Voc, short circuit current Isc and maximum power point current and voltage Im; Vm making it a fast and low cost parameter determination technique. The accuracy of the presented theoretical I-V curves is verified by experimental data.

Modeling of extraction process of crude polysaccharides from Basil seeds (Ocimum basilicum l.) as affected by process variables.

PubMed

Salehi, Fakhreddin; Kashaninejad, Mahdi; Tadayyon, Ali; Arabameri, Fatemeh

2015-08-01

Basil seed (Ocimum basilicum L.) has practical amounts of gum with good functional properties. In this work, extraction of gum from Basil seed was studied. Effect of pH, temperature and water/seed ratio on the kinetic and thermodynamic parameters; entropy, enthalpy and free energy of extraction were investigated. The maximum gum yield was 17.95 % at 50 °C for pH=7 and water/seed ratio 30:1. In this study, the experimental data were fitted to a mathematical model of mass transfer and equations constants were obtained. The kinetic of Basil seed gum extraction was found to be a first order mass transfer model. Statistical results indicated that the model used in this study will be able to predict the gum extraction from Basil seed adequately. It also found that ΔH and ΔS were positive and ΔG was negative indicating that the extraction process was spontaneous, irreversible and endothermic. The ΔH, ΔS and ΔG values were 0.26-7.87 kJ/mol, 8.12-33.2 J/mol K and 1.62-4.42 kJ/mol, respectively.

Green tea polyphenol extract attenuates lung injury in experimental model of carrageenan-induced pleurisy in mice

PubMed Central

Di Paola, Rosanna; Mazzon, Emanuela; Muià, Carmelo; Genovese, Tiziana; Menegazzi, Marta; Zaffini, Raffaela; Suzuki, Hisanory; Cuzzocrea, Salvatore

2005-01-01

Here we investigate the effects of the green tea extract in an animal model of acute inflammation, carrageenan-induced pleurisy. We report here that green tea extract (given at 25 mg/kg i.p. bolus 1 h prior to carrageenan), exerts potent anti-inflammatory effects in an animal model of acute inflammation in vivo. Injection of carrageenan (2%) into the pleural cavity of mice elicited an acute inflammatory response characterized by fluid accumulation in the pleural cavity that contained many neutrophils (PMNs), an infiltration of PMNs in lung tissues and increased production of nitrite/nitrate, tumour necrosis factor alpha. All parameters of inflammation were attenuated by green tea extract treatment. Furthermore, carrageenan induced an up-regulation of the adhesion molecule ICAM-1, as well as nitrotyrosine and poly (ADP-ribose) synthetase (PARS) formation, as determined by immunohistochemical analysis of lung tissues. Staining for the ICAM-1, nitrotyrosine, and PARS was reduced by green tea extract. Our results clearly demonstrate that treatment with green tea extract exerts a protective effect and offers a novel therapeutic approach for the management of lung injury. PMID:15987519

Black-hole kicks from numerical-relativity surrogate models

NASA Astrophysics Data System (ADS)

Gerosa, Davide; Hébert, François; Stein, Leo C.

2018-05-01

Binary black holes radiate linear momentum in gravitational waves as they merge. Recoils imparted to the black-hole remnant can reach thousands of km /s , thus ejecting black holes from their host galaxies. We exploit recent advances in gravitational waveform modeling to quickly and reliably extract recoils imparted to generic, precessing, black-hole binaries. Our procedure uses a numerical-relativity surrogate model to obtain the gravitational waveform given a set of binary parameters; then, from this waveform we directly integrate the gravitational-wave linear momentum flux. This entirely bypasses the need for fitting formulas which are typically used to model black-hole recoils in astrophysical contexts. We provide a thorough exploration of the black-hole kick phenomenology in the parameter space, summarizing and extending previous numerical results on the topic. Our extraction procedure is made publicly available as a module for the Python programming language named surrkick. Kick evaluations take ˜0.1 s on a standard off-the-shelf machine, thus making our code ideal to be ported to large-scale astrophysical studies.

A new model for simulating microbial cyanide production and optimizing the medium parameters for recovering precious metals from waste printed circuit boards.

PubMed

Yuan, Zhihui; Ruan, Jujun; Li, Yaying; Qiu, Rongliang

2018-04-10

Bioleaching is a green recycling technology for recovering precious metals from waste printed circuit boards (WPCBs). However, this technology requires increasing cyanide production to obtain desirable recovery efficiency. Luria-Bertani medium (LB medium, containing tryptone 10 g/L, yeast extract 5 g/L, NaCl 10 g/L) was commonly used in bioleaching of precious metal. In this study, results showed that LB medium did not produce highest yield of cyanide. Under optimal culture conditions (25 °C, pH 7.5), the maximum cyanide yield of the optimized medium (containing tryptone 6 g/L and yeast extract 5 g/L) was 1.5 times as high as that of LB medium. In addition, kinetics and relationship of cell growth and cyanide production was studied. Data of cell growth fitted logistics model well. Allometric model was demonstrated effective in describing relationship between cell growth and cyanide production. By inserting logistics equation into allometric equation, we got a novel hybrid equation containing five parameters. Kinetic data for cyanide production were well fitted to the new model. Model parameters reflected both cell growth and cyanide production process. Copyright © 2018 Elsevier B.V. All rights reserved.

Algebraic method for parameter identification of circuit models for batteries under non-zero initial condition

NASA Astrophysics Data System (ADS)

Devarakonda, Lalitha; Hu, Tingshu

2014-12-01

This paper presents an algebraic method for parameter identification of Thevenin's equivalent circuit models for batteries under non-zero initial condition. In traditional methods, it was assumed that all capacitor voltages have zero initial conditions at the beginning of each charging/discharging test. This would require a long rest time between two tests, leading to very lengthy tests for a charging/discharging cycle. In this paper, we propose an algebraic method which can extract the circuit parameters together with initial conditions. This would theoretically reduce the rest time to 0 and substantially accelerate the testing cycles.

Parameter as a Switch Between Dynamical States of a Network in Population Decoding.

PubMed

Yu, Jiali; Mao, Hua; Yi, Zhang

2017-04-01

Population coding is a method to represent stimuli using the collective activities of a number of neurons. Nevertheless, it is difficult to extract information from these population codes with the noise inherent in neuronal responses. Moreover, it is a challenge to identify the right parameter of the decoding model, which plays a key role for convergence. To address the problem, a population decoding model is proposed for parameter selection. Our method successfully identified the key conditions for a nonzero continuous attractor. Both the theoretical analysis and the application studies demonstrate the correctness and effectiveness of this strategy.

Extracting Tree Height from Repeat-Pass PolInSAR Data : Experiments with JPL and ESA Airborne Systems

NASA Technical Reports Server (NTRS)

Lavalle, Marco; Ahmed, Razi; Neumann, Maxim; Hensley, Scott

2013-01-01

In this paper we present our latest developments and experiments with the random-motion-over-ground (RMoG) model used to extract canopy height and other important forest parameters from repeat-pass polarimetricinterferometric SAR (Pol-InSAR) data. More specifically, we summarize the key features of the RMoG model in contrast with the random-volume-over-ground (RVoG) model, describe in detail a possible inversion scheme for the RMoG model and illustrate the results of the RMoG inversion using airborne data collected by the Jet Propulsion Laboratory (JPL) and the European Space Agency (ESA).

Modeling As(III) oxidation and removal with iron electrocoagulation in groundwater.

PubMed

Li, Lei; van Genuchten, Case M; Addy, Susan E A; Yao, Juanjuan; Gao, Naiyun; Gadgil, Ashok J

2012-11-06

Understanding the chemical kinetics of arsenic during electrocoagulation (EC) treatment is essential for a deeper understanding of arsenic removal using EC under a variety of operating conditions and solution compositions. We describe a highly constrained, simple chemical dynamic model of As(III) oxidation and As(III,V), Si, and P sorption for the EC system using model parameters extracted from some of our experimental results and previous studies. Our model predictions agree well with both data extracted from previous studies and our observed experimental data over a broad range of operating conditions (charge dosage rate) and solution chemistry (pH, co-occurring ions) without free model parameters. Our model provides insights into why higher pH and lower charge dosage rate (Coulombs/L/min) facilitate As(III) removal by EC and sheds light on the debate in the recent published literature regarding the mechanism of As(III) oxidation during EC. Our model also provides practically useful estimates of the minimum amount of iron required to remove 500 μg/L As(III) to <50 μg/L. Parameters measured in this work include the ratio of rate constants for Fe(II) and As(III) reactions with Fe(IV) in synthetic groundwater (k(1)/k(2) = 1.07) and the apparent rate constant of Fe(II) oxidation with dissolved oxygen at pH 7 (k(app) = 10(0.22) M(-1)s(-1)).

Evaluation of bacterial run and tumble motility parameters through trajectory analysis

NASA Astrophysics Data System (ADS)

Liang, Xiaomeng; Lu, Nanxi; Chang, Lin-Ching; Nguyen, Thanh H.; Massoudieh, Arash

2018-04-01

In this paper, a method for extraction of the behavior parameters of bacterial migration based on the run and tumble conceptual model is described. The methodology is applied to the microscopic images representing the motile movement of flagellated Azotobacter vinelandii. The bacterial cells are considered to change direction during both runs and tumbles as is evident from the movement trajectories. An unsupervised cluster analysis was performed to fractionate each bacterial trajectory into run and tumble segments, and then the distribution of parameters for each mode were extracted by fitting mathematical distributions best representing the data. A Gaussian copula was used to model the autocorrelation in swimming velocity. For both run and tumble modes, Gamma distribution was found to fit the marginal velocity best, and Logistic distribution was found to represent better the deviation angle than other distributions considered. For the transition rate distribution, log-logistic distribution and log-normal distribution, respectively, was found to do a better job than the traditionally agreed exponential distribution. A model was then developed to mimic the motility behavior of bacteria at the presence of flow. The model was applied to evaluate its ability to describe observed patterns of bacterial deposition on surfaces in a micro-model experiment with an approach velocity of 200 μm/s. It was found that the model can qualitatively reproduce the attachment results of the micro-model setting.

Temperature Responses of Soil Organic Matter Components With Varying Recalcitrance

NASA Astrophysics Data System (ADS)

Simpson, M. J.; Feng, X.

2007-12-01

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

Response surface optimization of extraction protocols to obtain phenolic rich antioxidant from sea buckthorn and their potential application into model meat system.

PubMed

Wagh, Rajesh V; Chatli, Manish K

2017-05-01

In the present study, processing parameters for the extraction of phenolic rich sea buckthorn seed (SBTE) extract were optimised using response surface method and subjected for in vitro efficacy viz. total phenolic, ABTS, DPPH and SASA activity. The optimised model depicted MeOH as a solvent at 60% concentration level with a reaction time of 20 min and extracting temperature of 55 °C for the highest yield and total phenolic content. The efficacy of different concentration of obtained SBT was evaluated in raw ground pork as a model meat system on the basis of various physico-chemical, microbiological, sensory quality characteristics. Addition of 0.3% SBTE significantly reduced the lipid peroxidation (PV, TBARS and FFA) and improved instrumental colour ( L* , a*, b* ) attributes of raw ground pork during refrigerated storage of 9 days. Results concluded that SBTE at 0.3% level can successfully improve the oxidative stability, microbial, sensory quality attributes in the meat model system.

Enhancement of multimodality texture-based prediction models via optimization of PET and MR image acquisition protocols: a proof of concept

NASA Astrophysics Data System (ADS)

Vallières, Martin; Laberge, Sébastien; Diamant, André; El Naqa, Issam

2017-11-01

Texture-based radiomic models constructed from medical images have the potential to support cancer treatment management via personalized assessment of tumour aggressiveness. While the identification of stable texture features under varying imaging settings is crucial for the translation of radiomics analysis into routine clinical practice, we hypothesize in this work that a complementary optimization of image acquisition parameters prior to texture feature extraction could enhance the predictive performance of texture-based radiomic models. As a proof of concept, we evaluated the possibility of enhancing a model constructed for the early prediction of lung metastases in soft-tissue sarcomas by optimizing PET and MR image acquisition protocols via computerized simulations of image acquisitions with varying parameters. Simulated PET images from 30 STS patients were acquired by varying the extent of axial data combined per slice (‘span’). Simulated T 1-weighted and T 2-weighted MR images were acquired by varying the repetition time and echo time in a spin-echo pulse sequence, respectively. We analyzed the impact of the variations of PET and MR image acquisition parameters on individual textures, and we investigated how these variations could enhance the global response and the predictive properties of a texture-based model. Our results suggest that it is feasible to identify an optimal set of image acquisition parameters to improve prediction performance. The model constructed with textures extracted from simulated images acquired with a standard clinical set of acquisition parameters reached an average AUC of 0.84 +/- 0.01 in bootstrap testing experiments. In comparison, the model performance significantly increased using an optimal set of image acquisition parameters (p = 0.04 ), with an average AUC of 0.89 +/- 0.01 . Ultimately, specific acquisition protocols optimized to generate superior radiomics measurements for a given clinical problem could be developed and standardized via dedicated computer simulations and thereafter validated using clinical scanners.

Equilibrium and kinetic modelling of Cd(II) biosorption by algae Gelidium and agar extraction algal waste.

PubMed

Vilar, Vítor J P; Botelho, Cidália M S; Boaventura, Rui A R

2006-01-01

In this study an industrial algal waste from agar extraction has been used as an inexpensive and effective biosorbent for cadmium (II) removal from aqueous solutions. This biosorbent was compared with the algae Gelidium itself, which is the raw material for agar extraction. Equilibrium data follow both Langmuir and Redlich-Peterson models. The parameters of Langmuir equilibrium model are q(max)=18.0 mgg(-1), b=0.19 mgl(-1) and q(max)=9.7 mgg(-1), b=0.16 mgl(-1), respectively for Gelidium and the algal waste. Kinetic experiments were conducted at initial Cd(II) concentrations in the range 6-91 mgl(-1). Data were fitted to pseudo-first- and second-order Lagergren models. For an initial Cd(II) concentration of 91 mgl(-1) the parameters of the pseudo-first-order Lagergren model are k(1,ads)=0.17 and 0.87 min(-1); q(eq)=16.3 and 8.7 mgg(-1), respectively, for Gelidium and algal waste. Kinetic constants vary with the initial metal concentration. The adsorptive behaviour of biosorbent particles was modelled using a batch reactor mass transfer kinetic model. The model successfully predicts Cd(II) concentration profiles and provides significant insights on the biosorbents performance. The homogeneous diffusivity, D(h), is in the range 0.5-2.2 x10(-8) and 2.1-10.4 x10(-8)cm(2)s(-1), respectively, for Gelidium and algal waste.

Modulating Wnt Signaling Pathway to Enhance Allograft Integration in Orthopedic Trauma Treatment

DTIC Science & Technology

2013-10-01

presented below. Quantitative output provides an extensive set of data but we have chosen to present the most relevant parameters that are reflected in...multiple parameters .  Most samples have been mechanically tested and data extracted for multiple parameters .  Histological evaluation of subset of...Sumner, D. R. Saline Irrigation Does Not Affect Bone Formation or Fixation Strength of Hydroxyapatite /Tricalcium Phosphate-Coated Implants in a Rat Model

Semiparametric modeling: Correcting low-dimensional model error in parametric models

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

Berry, Tyrus, E-mail: thb11@psu.edu; Harlim, John, E-mail: jharlim@psu.edu; Department of Meteorology, the Pennsylvania State University, 503 Walker Building, University Park, PA 16802-5013

2016-03-01

In this paper, a semiparametric modeling approach is introduced as a paradigm for addressing model error arising from unresolved physical phenomena. Our approach compensates for model error by learning an auxiliary dynamical model for the unknown parameters. Practically, the proposed approach consists of the following steps. Given a physics-based model and a noisy data set of historical observations, a Bayesian filtering algorithm is used to extract a time-series of the parameter values. Subsequently, the diffusion forecast algorithm is applied to the retrieved time-series in order to construct the auxiliary model for the time evolving parameters. The semiparametric forecasting algorithm consistsmore » of integrating the existing physics-based model with an ensemble of parameters sampled from the probability density function of the diffusion forecast. To specify initial conditions for the diffusion forecast, a Bayesian semiparametric filtering method that extends the Kalman-based filtering framework is introduced. In difficult test examples, which introduce chaotically and stochastically evolving hidden parameters into the Lorenz-96 model, we show that our approach can effectively compensate for model error, with forecasting skill comparable to that of the perfect model.« less

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.

Probing the standard model and beyond with CP violation and particle cosmology

NASA Astrophysics Data System (ADS)

Savastio, Michael Paul

We discuss topics related to CP violation and particle cosmology. First, we present some developments in improving the extraction of the CP violating parameter gamma from the decay B+/- → DK+/- followed by the subsequent decay D → KS pi +pi--. The mixing of the final state kaon is an additional CP violating effect which should be taken into account in the extraction of gamma, and we discuss how this should be done. We also discuss the optimization of phase space binning needed to extract gamma from these decays in a model independent way. Next, we discuss some cosmological constraints on R-parity violating, Minimally Flavor Violating (MFV) Supersymmetry (SUSY). Finally, we show that oribtally excited dark matter cannot persist over cosmic timescales for various model independent reasons.

Box-Behnken factorial design to obtain a phenolic-rich extract from the aerial parts of Chelidonium majus L.

PubMed

Grosso, Clara; Ferreres, Federico; Gil-Izquierdo, Angel; Valentão, Patrícia; Sampaio, Maria; Lima, Júlio; Andrade, Paula B

2014-12-01

A Box-Behnken design (BBD) was developed to study the influence of four parameters (X1: % methanol; X2: extraction time; X3: extraction temperature; X4: solid/solvent ratio) on two responses, namely extraction yield and phenolics content of the aerial parts of Chelidonium majus L. The model presented a good fit to the experimental results for the extraction yield, being significantly influenced by X1 and X4. On the other hand a parameter reduction was necessary to run the model for phenolics content, showing that only X1 and X2 had great influence on the response. Two best extraction conditions were defined: X1=76.8% MeOH, X2=150.0 min, X3=60.0°C and X4=1:100 and X1=69.2%, X2=150 min, X3=42.5°C and X4=1:100. Moreover, the HPLC-DAD-ESI/MS(n) analysis conducted with the center point sample revealed the presence of 15 alkaloids and 15 phenolic compounds, from which the 9 flavonoids and 3 hydroxycinnamic acids are described for the first time. Only phenolic compounds were quantified by a validated HPLC-DAD method, the pair quercetin-3-O-rutinoside+quercetin-3-O-glucoside dominating all the 29 extracts. This study is of great importance for future works that seek to apply the phenolic profile to the quality control of C. majus samples. Copyright © 2014 Elsevier B.V. All rights reserved.

The relative pose estimation of aircraft based on contour model

NASA Astrophysics Data System (ADS)

Fu, Tai; Sun, Xiangyi

2017-02-01

This paper proposes a relative pose estimation approach based on object contour model. The first step is to obtain a two-dimensional (2D) projection of three-dimensional (3D)-model-based target, which will be divided into 40 forms by clustering and LDA analysis. Then we proceed by extracting the target contour in each image and computing their Pseudo-Zernike Moments (PZM), thus a model library is constructed in an offline mode. Next, we spot a projection contour that resembles the target silhouette most in the present image from the model library with reference of PZM; then similarity transformation parameters are generated as the shape context is applied to match the silhouette sampling location, from which the identification parameters of target can be further derived. Identification parameters are converted to relative pose parameters, in the premise that these values are the initial result calculated via iterative refinement algorithm, as the relative pose parameter is in the neighborhood of actual ones. At last, Distance Image Iterative Least Squares (DI-ILS) is employed to acquire the ultimate relative pose parameters.

Investigation of physical parameters in stellar flares observed by GINGA

NASA Technical Reports Server (NTRS)

Stern, Robert A.

1994-01-01

This program involves analysis and interpretation of results from GINGA Large Area Counter (LAC) observations from a group of large stellar x-ray flares. All LAC data are re-extracted using the standard Hayashida method of LAC background subtraction and analyzed using various models available with the XSPEC spectral fitting program. Temperature-emission measure histories are available for a total of 5 flares observed by GINGA. These will be used to compare physical parameters of these flares with solar and stellar flare models.

Investigation of physical parameters in stellar flares observed by GINGA

NASA Technical Reports Server (NTRS)

Stern, Robert A.

1994-01-01

This program involves analysis and interpretation of results from GINGA Large Area Counter (LAC) observations from a group of large stellar X-ray flares. All LAC data are re-extracted using the standard Hayashida method of LAC background subtraction and analyzed using various models available with the XSPEC spectral fitting program.Temperature-emission measure histories are available for a total of 5 flares observed by GINGA. These will be used to compare physical parameters of these flares with solar and stellar flare models.

Parallel optimization of signal detection in active magnetospheric signal injection experiments

NASA Astrophysics Data System (ADS)

Gowanlock, Michael; Li, Justin D.; Rude, Cody M.; Pankratius, Victor

2018-05-01

Signal detection and extraction requires substantial manual parameter tuning at different stages in the processing pipeline. Time-series data depends on domain-specific signal properties, necessitating unique parameter selection for a given problem. The large potential search space makes this parameter selection process time-consuming and subject to variability. We introduce a technique to search and prune such parameter search spaces in parallel and select parameters for time series filters using breadth- and depth-first search strategies to increase the likelihood of detecting signals of interest in the field of magnetospheric physics. We focus on studying geomagnetic activity in the extremely and very low frequency ranges (ELF/VLF) using ELF/VLF transmissions from Siple Station, Antarctica, received at Québec, Canada. Our technique successfully detects amplified transmissions and achieves substantial speedup performance gains as compared to an exhaustive parameter search. We present examples where our algorithmic approach reduces the search from hundreds of seconds down to less than 1 s, with a ranked signal detection in the top 99th percentile, thus making it valuable for real-time monitoring. We also present empirical performance models quantifying the trade-off between the quality of signal recovered and the algorithm response time required for signal extraction. In the future, improved signal extraction in scenarios like the Siple experiment will enable better real-time diagnostics of conditions of the Earth's magnetosphere for monitoring space weather activity.

Substitution of carcinogenic solvent dichloromethane for the extraction of volatile compounds in a fat-free model food system.

PubMed

Cayot, Nathalie; Lafarge, Céline; Bou-Maroun, Elias; Cayot, Philippe

2016-07-22

Dichloromethane is known as a very efficient solvent, but, as other halogenated solvents, is recognized as a hazardous product (CMR substance). The objective of the present work is to propose substitution solvent for the extraction of volatile compounds. The most important physico-chemical parameters in the choice of an appropriate extraction solvent of volatile compounds are reviewed. Various solvents are selected on this basis and on their hazard characteristics. The selected solvents, safer than dichloromethane, are compared using the extraction efficiency of volatile compounds from a model food product able to interact with volatile compounds. Volatile compounds with different hydrophobicity are used. High extraction yields were positively correlated with high boiling points and high Log Kow values of volatile compounds. Mixtures of solvents such as azeotrope propan-2-one/cyclopentane, azeotrope ethyl acetate/ethanol, and mixture ethyl acetate/ethanol (3:1, v/v) gave higher extraction yields than those obtained with dichloromethane. Copyright © 2016 Elsevier B.V. All rights reserved.

Ethanolic extract of Clerodendrum violaceum Gürke leaves enhances kidney function in mouse model of malaria.

PubMed

Zailani, Ahmed H; Balogun, Elizabeth A; Adebayo, Joseph O

2009-05-01

Evaluation of the effects of daily oral administration of ethanolic extract of C. violaceum leaves (13 mg/kg body weight) for 5 days on some kidney function indices of uninfected and Plasmodium berghei-infected mice was done on days 3, 8 and 14 post-infection. The indices studied include serum urea and creatinine concentrations with the specific activities of alkaline phosphatase, aspartate aminotransferase and alanine aminotransferase in the kidney. Treatment of P. berghei-infected mice with ethanolic extract of C. violaceum leaves (13 mg/kg body weight) for 5 days was able to ameliorate significantly the alterations in the various parameters observed in infected untreated mice, comparing favourably with chloroquine treatment in most cases. Administration of extract to uninfected mice had no significant effect on both serum and kidney parameters compared to the uninfected control. The results suggest that the ethanolic extract of C. violaceum leaves does not adversely affect kidney function at the dose used in traditional medicine for the treatment of malaria but rather enhances it.

The Impact of Parametric Uncertainties on Biogeochemistry in the E3SM Land Model

NASA Astrophysics Data System (ADS)

Ricciuto, Daniel; Sargsyan, Khachik; Thornton, Peter

2018-02-01

We conduct a global sensitivity analysis (GSA) of the Energy Exascale Earth System Model (E3SM), land model (ELM) to calculate the sensitivity of five key carbon cycle outputs to 68 model parameters. This GSA is conducted by first constructing a Polynomial Chaos (PC) surrogate via new Weighted Iterative Bayesian Compressive Sensing (WIBCS) algorithm for adaptive basis growth leading to a sparse, high-dimensional PC surrogate with 3,000 model evaluations. The PC surrogate allows efficient extraction of GSA information leading to further dimensionality reduction. The GSA is performed at 96 FLUXNET sites covering multiple plant functional types (PFTs) and climate conditions. About 20 of the model parameters are identified as sensitive with the rest being relatively insensitive across all outputs and PFTs. These sensitivities are dependent on PFT, and are relatively consistent among sites within the same PFT. The five model outputs have a majority of their highly sensitive parameters in common. A common subset of sensitive parameters is also shared among PFTs, but some parameters are specific to certain types (e.g., deciduous phenology). The relative importance of these parameters shifts significantly among PFTs and with climatic variables such as mean annual temperature.

Maca polysaccharides: Extraction optimization, structural features and anti-fatigue activities.

PubMed

Li, Yujuan; Xin, Yizhou; Xu, Fangxue; Zheng, Mengmeng; Xi, Xiaozhi; Cui, Xiaowei; Cao, Hui; Guo, Hong; Han, Chunchao

2018-08-01

The maca polysaccharides optimal extraction conditions were obtained by using response surface methodology (RSM) method and the anti-fatigue activity of maca polysaccharides (MCP) was explored. The maca polysaccharides extract yield of RSM could reach 9.97 mg/g by using the model predicts, and the total sugar and protein purity were 61.00% and 4.46% with the further isolation process, respectively. And the monosaccharide compositions obtained by gas chromatograph (GC) were composed of rhamnose (rha), glucose (glc), galactose (gal) with the ratio of 2.34:10.21:1.00. Furthermore, the anti-fatigue activity was evaluated by the swimming parameter, biochemistry parameters (liver glycogen (LG), blood urea nitrogen (BUN), and lactic acid (LD)), the result indicated that the low-dose maca polysaccharides group had the significant anti-fatigue activity. Copyright © 2018 Elsevier B.V. All rights reserved.

Optimization of an innovative approach involving mechanical activation and acid digestion for the extraction of lithium from lepidolite

NASA Astrophysics Data System (ADS)

Vieceli, Nathália; Nogueira, Carlos A.; Pereira, Manuel F. C.; Durão, Fernando O.; Guimarães, Carlos; Margarido, Fernanda

2018-01-01

The recovery of lithium from hard rock minerals has received increased attention given the high demand for this element. Therefore, this study optimized an innovative process, which does not require a high-temperature calcination step, for lithium extraction from lepidolite. Mechanical activation and acid digestion were suggested as crucial process parameters, and experimental design and response-surface methodology were applied to model and optimize the proposed lithium extraction process. The promoting effect of amorphization and the formation of lithium sulfate hydrate on lithium extraction yield were assessed. Several factor combinations led to extraction yields that exceeded 90%, indicating that the proposed process is an effective approach for lithium recovery.

Continuum Model for Decontamination of Chemical Warfare Agent from a Rubbery Polymer using the Maxwell-Stefan Formulation

NASA Astrophysics Data System (ADS)

Varady, Mark; Bringuier, Stefan; Pearl, Thomas; Stevenson, Shawn; Mantooth, Brent

Decontamination of polymers exposed to chemical warfare agents (CWA) often proceeds by application of a liquid solution. Absorption of some decontaminant components proceed concurrently with extraction of the CWA, resulting in multicomponent diffusion in the polymer. In this work, the Maxwell-Stefan equations were used with the Flory-Huggins model of species activity to mathematically describe the transport of two species within a polymer. This model was used to predict the extraction of the nerve agent O-ethyl S-[2(diisopropylamino)ethyl] methylphosphonothioate (VX) from a silicone elastomer into both water and methanol. Comparisons with experimental results show good agreement with minimal fitting of model parameters from pure component uptake data. Reaction of the extracted VX with sodium hydroxide in the liquid-phase was also modeled and used to predict the overall rate of destruction of VX. Although the reaction proceeds more slowly in the methanol-based solution compared to the aqueous solution, the extraction rate is faster due to increasing VX mobility as methanol absorbs into the silicone, resulting in an overall faster rate of VX destruction.

A combined model of heat and mass transfer for the in situ extraction of volatile water from lunar regolith

NASA Astrophysics Data System (ADS)

Reiss, P.

2018-05-01

Chemical analysis of lunar soil samples often involves thermal processing to extract their volatile constituents, such as loosely adsorbed water. For the characterization of volatiles and their bonding mechanisms it is important to determine their desorption temperature. However, due to the low thermal diffusivity of lunar regolith, it might be difficult to reach a uniform heat distribution in a sample that is larger than only a few particles. Furthermore, the mass transport through such a sample is restricted, which might lead to a significant delay between actual desorption and measurable outgassing of volatiles from the sample. The entire volatiles extraction process depends on the dynamically changing heat and mass transfer within the sample, and is influenced by physical parameters such as porosity, tortuosity, gas density, temperature and pressure. To correctly interpret measurements of the extracted volatiles, it is important to understand the interaction between heat transfer, sorption, and gas transfer through the sample. The present paper discusses the molecular kinetics and mechanisms that are involved in the thermal extraction process and presents a combined parametrical computation model to simulate this process. The influence of water content on the gas diffusivity and thermal diffusivity is discussed and the issue of possible resorption of desorbed molecules within the sample is addressed. Based on the multi-physical computation model, a case study for the ProSPA instrument for in situ analysis of lunar volatiles is presented, which predicts relevant dynamic process parameters, such as gas pressure and process duration.

Impact of Extraction Parameters on the Recovery of Lipolytic Activity from Fermented Babassu Cake

PubMed Central

Silva, Jaqueline N.; Godoy, Mateus G.; Gutarra, Melissa L. E.; Freire, Denise M. G.

2014-01-01

Enzyme extraction from solid matrix is as important step in solid-state fermentation to obtain soluble enzymes for further immobilization and application in biocatalysis. A method for the recovery of a pool of lipases from Penicillium simplicissimum produced by solid-state fermentation was developed. For lipase recovery different extraction solution was used and phosphate buffer containing Tween 80 and NaCl showed the best results, yielding lipase activity of 85.7 U/g and 65.7 U/g, respectively. The parameters with great impacts on enzyme extraction detected by the Plackett-Burman analysis were studied by Central Composite Rotatable experimental designs where a quadratic model was built showing maximum predicted lipase activity (160 U/g) at 25°C, Tween 80 0.5% (w/v), pH 8.0 and extraction solution 7 mL/g, maintaining constant buffer molarity of 0.1 M and 200 rpm. After the optimization process a 2.5 fold increase in lipase activity in the crude extract was obtained, comparing the intial value (64 U/g) with the experimental design (160 U/g), thus improving the overall productivity of the process. PMID:25090644

Aqueous extraction kinetics of soluble solids, phenolics and flavonoids from sage (Salvia fruticosa Miller) leaves.

PubMed

Torun, Mehmet; Dincer, Cuneyt; Topuz, Ayhan; Sahin-Nadeem, Hilal; Ozdemir, Feramuz

2015-05-01

In the present study, aqueous extraction kinetics of total soluble solids (TSS), total phenolic content (TPC) and total flavonoid content (TFC) from Salvia fruticosa leaves were investigated throughout 150 min. of extraction period against temperature (60-80 °C), particle size (2-8 mm) and loading percentage (1-4 %). The extract yielded 25 g/100 g TSS which contained 30 g/100 g TPC and 25 g/100 g TFC. The extraction data in time course fit with reversible first order kinetic model. All tested variables showed significant effect on the estimated kinetic parameters except equilibrium concentration. Increasing the extraction temperature resulted high extraction rate constants and equilibrium concentrations of the tested variables notably above 70 °C. By using the Arrhenius relationship, activation energy of the TSS, TPC and TFC were determined as 46.11 ± 5.61, 36.80 ± 3.12 and 33.52 ± 2.23 kj/mol, respectively. By decreasing the particle size, the extraction rate constants and diffusion coefficients exponentially increased whereas equilibrium concentrations did not change significantly. The equilibrium concentrations of the tested parameters showed linear behavior with increasing the loading percentage of the sage, however; the change in extraction rates did not show linear behavior due to submerging effect of 4 % loading.

Target Classification of Canonical Scatterers Using Classical Estimation and Dictionary Based Techniques

DTIC Science & Technology

2012-03-22

shapes tested , when the objective parameter set was confined to a dictionary’s de - fined parameter space. These physical characteristics included...8 2.3 Hypothesis Testing and Detection Theory . . . . . . . . . . . . . . . 8 2.4 3-D SAR Scattering Models...basis pursuit de -noising (BPDN) algorithm is chosen to perform extraction due to inherent efficiency and error tolerance. Multiple shape dictionaries

Improving Measurement of Forest Structural Parameters by Co-Registering of High Resolution Aerial Imagery and Low Density LiDAR Data

PubMed Central

Huang, Huabing; Gong, Peng; Cheng, Xiao; Clinton, Nick; Li, Zengyuan

2009-01-01

Forest structural parameters, such as tree height and crown width, are indispensable for evaluating forest biomass or forest volume. LiDAR is a revolutionary technology for measurement of forest structural parameters, however, the accuracy of crown width extraction is not satisfactory when using a low density LiDAR, especially in high canopy cover forest. We used high resolution aerial imagery with a low density LiDAR system to overcome this shortcoming. A morphological filtering was used to generate a DEM (Digital Elevation Model) and a CHM (Canopy Height Model) from LiDAR data. The LiDAR camera image is matched to the aerial image with an automated keypoints search algorithm. As a result, a high registration accuracy of 0.5 pixels was obtained. A local maximum filter, watershed segmentation, and object-oriented image segmentation are used to obtain tree height and crown width. Results indicate that the camera data collected by the integrated LiDAR system plays an important role in registration with aerial imagery. The synthesis with aerial imagery increases the accuracy of forest structural parameter extraction when compared to only using the low density LiDAR data. PMID:22573971

Wound healing activity of Sida cordifolia Linn. in rats

PubMed Central

Pawar, Rajesh S.; Chaurasiya, Pradeep K.; Rajak, Harish; Singour, Pradeep K.; Toppo, Fedelic Ashish; Jain, Ankit

2013-01-01

Introduction: The present study provides a scientific evaluation for the wound healing potential of ethanolic (EtOH) extract of Sida cordifolia Linn. (SCL) plant. Materials and Methods: Excision, incision and burn wounds were inflicted upon three groups of six rats each. Group I was assigned as control (ointment base). Group II was treated with 10% EtOH extract ointment. Group III was treated with standard silver sulfadiazine (0.01%) cream. The parameters observed were percentage of wound contraction, epithelialization period, hydroxyproline content, tensile strength including histopathological studies. Result: It was noted that the effect produced by the ethanolic extract of SCL ointment showed significant (P < 0.01) healing in all wound models when compared with the control group. All parameters such as wound contraction, epithelialization period, hydroxyproline content, tensile strength and histopathological studies showed significant (P < 0.01) changes when compared with the control. Conclusion: The ethanolic extract ointment of SCL effectively stimulates wound contraction; increases tensile strength of excision, incision and burn wounds. PMID:24130382

Long-Term Oral Administration of Capsicum baccatum Extracts Does Not Alter Behavioral, Hematological, and Metabolic Parameters in CF1 Mice

PubMed Central

Zimmer, Aline Rigon; Leonardi, Bianca; Kalinine, Eduardo; de Souza, Diogo Onofre; Portela, Luis Valmor; Gosmann, Grace

2012-01-01

Our group showed that crude ethanol (CE) and butanol (BUT) extracts of Capsicum baccatum presented anti-inflammatory and antioxidant properties. Furthermore, the flavonoid and total phenolic contents were positively correlated with both of these properties observed for C. baccatum extracts. The present study demonstrated that 60 days of oral administration of CE and BUT (200 mg/kg) in mice did not cause significant differences in the following parameters evaluated: hematological profile, body weight and relative weight of visceral organs, systemic lipid profile, glucose homeostasis (GTT), kidney and hepatic biochemical markers, and spontaneous locomotion and anxiety-like behavior. Altogether, these results indicate for the first time that the long-term oral administration of C. baccatum extracts does not affect specific aspects of CF1 mice physiology, suggesting their safety, building up the venue to test their efficacy in animal models underlying persistent activation of oxidative and inflammatory pathways. PMID:23320023

Freeze-out conditions in proton-proton collisions at the highest energies available at the BNL Relativistic Heavy Ion Collider and the CERN Large Hadron Collider

NASA Astrophysics Data System (ADS)

Das, Sabita; Mishra, Debadeepti; Chatterjee, Sandeep; Mohanty, Bedangadas

2017-01-01

The freeze-out conditions in proton-proton collisions at √{sNN}=200 , 900, and 7000 GeV have been extracted by fits to the mean hadron yields at midrapidity within the framework of the statistical model of an ideal gas of hadrons and resonances in the grand canonical ensemble. The variation of the extracted freeze-out thermal parameters and the goodness of the fits with √{sN N} are discussed. We find the extracted temperature and baryon chemical potential of the freeze-out surface to be similar in p +p and heavy-ion collisions. On the other hand, the thermal behavior of the strange hadrons is qualitatively different in p +p as compared to A +A collisions. We find an additional parameter accounting for nonequilibrium strangeness production is essential for describing the p +p data. This is in contrast to A +A where the nonequilibrium framework could be successfully replaced by a sequential and complete equilibrium model with an early freeze-out of the strange hadrons.

A motion algorithm to extract physical and motion parameters of mobile targets from cone-beam computed tomographic images.

PubMed

Alsbou, Nesreen; Ahmad, Salahuddin; Ali, Imad

2016-05-17

A motion algorithm has been developed to extract length, CT number level and motion amplitude of a mobile target from cone-beam CT (CBCT) images. The algorithm uses three measurable parameters: Apparent length and blurred CT number distribution of a mobile target obtained from CBCT images to determine length, CT-number value of the stationary target, and motion amplitude. The predictions of this algorithm are tested with mobile targets having different well-known sizes that are made from tissue-equivalent gel which is inserted into a thorax phantom. The phantom moves sinusoidally in one-direction to simulate respiratory motion using eight amplitudes ranging 0-20 mm. Using this motion algorithm, three unknown parameters are extracted that include: Length of the target, CT number level, speed or motion amplitude for the mobile targets from CBCT images. The motion algorithm solves for the three unknown parameters using measured length, CT number level and gradient for a well-defined mobile target obtained from CBCT images. The motion model agrees with the measured lengths which are dependent on the target length and motion amplitude. The gradient of the CT number distribution of the mobile target is dependent on the stationary CT number level, the target length and motion amplitude. Motion frequency and phase do not affect the elongation and CT number distribution of the mobile target and could not be determined. A motion algorithm has been developed to extract three parameters that include length, CT number level and motion amplitude or speed of mobile targets directly from reconstructed CBCT images without prior knowledge of the stationary target parameters. This algorithm provides alternative to 4D-CBCT without requirement of motion tracking and sorting of the images into different breathing phases. The motion model developed here works well for tumors that have simple shapes, high contrast relative to surrounding tissues and move nearly in regular motion pattern that can be approximated with a simple sinusoidal function. This algorithm has potential applications in diagnostic CT imaging and radiotherapy in terms of motion management.

Charge relaxation and dynamics in organic semiconductors

NASA Astrophysics Data System (ADS)

Kwok, H. L.

2006-08-01

Charge relaxation in dispersive materials is often described in terms of the stretched exponential function (Kohlrausch law). The process can be explained using a "hopping" model which in principle, also applies to charge transport such as current conduction. This work analyzed reported transient photoconductivity data on functionalized pentacene single crystals using a geometric hopping model developed by B. Sturman et al and extracted values (or range of values) on the materials parameters relevant to charge relaxation as well as charge transport. Using the correlated disorder model (CDM), we estimated values of the carrier mobility for the pentacene samples. From these results, we observed the following: i) the transport site density appeared to be of the same order of magnitude as the carrier density; ii) it was possible to extract lower bound values on the materials parameters linked to the transport process; and iii) by matching the simulated charge decay to the transient photoconductivity data, we were able to refine estimates on the materials parameters. The data also allowed us to simulate the stretched exponential decay. Our observations suggested that the stretching index and the carrier mobility were related. Physically, such interdependence would allow one to demarcate between localized molecular interactions and distant coulomb interactions.

In vivo toxicity and antitumor activity of essential oils extract from agarwood (Aquilaria crassna).

PubMed

Dahham, Saad Sabbar; Hassan, Loiy E Ahmed; Ahamed, Mohamed B Khadeer; Majid, Aman Shah Abdul; Majid, Amin Malik Shah Abdul; Zulkepli, Nik Noriman

2016-07-22

Aquilaria crassna has been used in traditional Asian medicine to treat vomiting, rheumatism, asthma, and cough. Furthermore, earlier studies from our laboratory have revealed that the essential oil extract from agarwood inhibited colorectal carcinoma cells. Despite of the wide range of ethno-pharmacological uses of agarwood, its toxicity has not been previously evaluated through systematic toxicological studies. Therefore, the potential safety of essential oil extract and its in vivo anti-tumor activity had been investigated. In the acute toxicity study, Swiss female mice were given a single dose of the essential oil extract at 2000 mg/kg/day orally and screened for two weeks after administration. Meanwhile, in the sub-chronic study, two different doses of the extract were administered for 28 days. Mortality, clinical signs, body weight changes, hematological and biochemical parameters, gross findings, organ weights, and histological parameters were monitored during the study. Other than that, in vivo anti-tumor study was assessed by using subcutaneous tumors model established in nude mice. The acute toxicity study showed that the LD50 of the extract was greater than 2000 mg/kg. In the repeated dose for 28-day oral toxicity study, the administration of 100 mg/kg and 500 mg/kg of essential oil per body weight revealed insignificant difference in food and water intakes, bodyweight change, hematological and biochemical parameters, relative organ weights, gross findings or histopathology compared to the control group. Nevertheless, the essential oil extract, when supplemented to nude mice, caused significant growth inhibition of the subcutaneous tumor of HCT 116 colorectal carcinoma cells. Collectively, the data obtained indicated that essential oil extract from agarwood might be a safe material, and this essential oil is suggested as a potential anti-colon cancer candidate.

Mapping model behaviour using Self-Organizing Maps

NASA Astrophysics Data System (ADS)

Herbst, M.; Gupta, H. V.; Casper, M. C.

2009-03-01

Hydrological model evaluation and identification essentially involves extracting and processing information from model time series. However, the type of information extracted by statistical measures has only very limited meaning because it does not relate to the hydrological context of the data. To overcome this inadequacy we exploit the diagnostic evaluation concept of Signature Indices, in which model performance is measured using theoretically relevant characteristics of system behaviour. In our study, a Self-Organizing Map (SOM) is used to process the Signatures extracted from Monte-Carlo simulations generated by the distributed conceptual watershed model NASIM. The SOM creates a hydrologically interpretable mapping of overall model behaviour, which immediately reveals deficits and trade-offs in the ability of the model to represent the different functional behaviours of the watershed. Further, it facilitates interpretation of the hydrological functions of the model parameters and provides preliminary information regarding their sensitivities. Most notably, we use this mapping to identify the set of model realizations (among the Monte-Carlo data) that most closely approximate the observed discharge time series in terms of the hydrologically relevant characteristics, and to confine the parameter space accordingly. Our results suggest that Signature Index based SOMs could potentially serve as tools for decision makers inasmuch as model realizations with specific Signature properties can be selected according to the purpose of the model application. Moreover, given that the approach helps to represent and analyze multi-dimensional distributions, it could be used to form the basis of an optimization framework that uses SOMs to characterize the model performance response surface. As such it provides a powerful and useful way to conduct model identification and model uncertainty analyses.

Mapping model behaviour using Self-Organizing Maps

NASA Astrophysics Data System (ADS)

Herbst, M.; Gupta, H. V.; Casper, M. C.

2008-12-01

Hydrological model evaluation and identification essentially depends on the extraction of information from model time series and its processing. However, the type of information extracted by statistical measures has only very limited meaning because it does not relate to the hydrological context of the data. To overcome this inadequacy we exploit the diagnostic evaluation concept of Signature Indices, in which model performance is measured using theoretically relevant characteristics of system behaviour. In our study, a Self-Organizing Map (SOM) is used to process the Signatures extracted from Monte-Carlo simulations generated by a distributed conceptual watershed model. The SOM creates a hydrologically interpretable mapping of overall model behaviour, which immediately reveals deficits and trade-offs in the ability of the model to represent the different functional behaviours of the watershed. Further, it facilitates interpretation of the hydrological functions of the model parameters and provides preliminary information regarding their sensitivities. Most notably, we use this mapping to identify the set of model realizations (among the Monte-Carlo data) that most closely approximate the observed discharge time series in terms of the hydrologically relevant characteristics, and to confine the parameter space accordingly. Our results suggest that Signature Index based SOMs could potentially serve as tools for decision makers inasmuch as model realizations with specific Signature properties can be selected according to the purpose of the model application. Moreover, given that the approach helps to represent and analyze multi-dimensional distributions, it could be used to form the basis of an optimization framework that uses SOMs to characterize the model performance response surface. As such it provides a powerful and useful way to conduct model identification and model uncertainty analyses.

Toward a Model-Based Predictive Controller Design in Brain–Computer Interfaces

PubMed Central

Kamrunnahar, M.; Dias, N. S.; Schiff, S. J.

2013-01-01

A first step in designing a robust and optimal model-based predictive controller (MPC) for brain–computer interface (BCI) applications is presented in this article. An MPC has the potential to achieve improved BCI performance compared to the performance achieved by current ad hoc, nonmodel-based filter applications. The parameters in designing the controller were extracted as model-based features from motor imagery task-related human scalp electroencephalography. Although the parameters can be generated from any model-linear or non-linear, we here adopted a simple autoregressive model that has well-established applications in BCI task discriminations. It was shown that the parameters generated for the controller design can as well be used for motor imagery task discriminations with performance (with 8–23% task discrimination errors) comparable to the discrimination performance of the commonly used features such as frequency specific band powers and the AR model parameters directly used. An optimal MPC has significant implications for high performance BCI applications. PMID:21267657

Toward a model-based predictive controller design in brain-computer interfaces.

PubMed

Kamrunnahar, M; Dias, N S; Schiff, S J

2011-05-01

A first step in designing a robust and optimal model-based predictive controller (MPC) for brain-computer interface (BCI) applications is presented in this article. An MPC has the potential to achieve improved BCI performance compared to the performance achieved by current ad hoc, nonmodel-based filter applications. The parameters in designing the controller were extracted as model-based features from motor imagery task-related human scalp electroencephalography. Although the parameters can be generated from any model-linear or non-linear, we here adopted a simple autoregressive model that has well-established applications in BCI task discriminations. It was shown that the parameters generated for the controller design can as well be used for motor imagery task discriminations with performance (with 8-23% task discrimination errors) comparable to the discrimination performance of the commonly used features such as frequency specific band powers and the AR model parameters directly used. An optimal MPC has significant implications for high performance BCI applications.

Dynamical compensation and structural identifiability of biological models: Analysis, implications, and reconciliation

PubMed Central

2017-01-01

The concept of dynamical compensation has been recently introduced to describe the ability of a biological system to keep its output dynamics unchanged in the face of varying parameters. However, the original definition of dynamical compensation amounts to lack of structural identifiability. This is relevant if model parameters need to be estimated, as is often the case in biological modelling. Care should we taken when using an unidentifiable model to extract biological insight: the estimated values of structurally unidentifiable parameters are meaningless, and model predictions about unmeasured state variables can be wrong. Taking this into account, we explore alternative definitions of dynamical compensation that do not necessarily imply structural unidentifiability. Accordingly, we show different ways in which a model can be made identifiable while exhibiting dynamical compensation. Our analyses enable the use of the new concept of dynamical compensation in the context of parameter identification, and reconcile it with the desirable property of structural identifiability. PMID:29186132

Utilizing High-Performance Computing to Investigate Parameter Sensitivity of an Inversion Model for Vadose Zone Flow and Transport

NASA Astrophysics Data System (ADS)

Fang, Z.; Ward, A. L.; Fang, Y.; Yabusaki, S.

2011-12-01

High-resolution geologic models have proven effective in improving the accuracy of subsurface flow and transport predictions. However, many of the parameters in subsurface flow and transport models cannot be determined directly at the scale of interest and must be estimated through inverse modeling. A major challenge, particularly in vadose zone flow and transport, is the inversion of the highly-nonlinear, high-dimensional problem as current methods are not readily scalable for large-scale, multi-process models. In this paper we describe the implementation of a fully automated approach for addressing complex parameter optimization and sensitivity issues on massively parallel multi- and many-core systems. The approach is based on the integration of PNNL's extreme scale Subsurface Transport Over Multiple Phases (eSTOMP) simulator, which uses the Global Array toolkit, with the Beowulf-Cluster inspired parallel nonlinear parameter estimation software, BeoPEST in the MPI mode. In the eSTOMP/BeoPEST implementation, a pre-processor generates all of the PEST input files based on the eSTOMP input file. Simulation results for comparison with observations are extracted automatically at each time step eliminating the need for post-process data extractions. The inversion framework was tested with three different experimental data sets: one-dimensional water flow at Hanford Grass Site; irrigation and infiltration experiment at the Andelfingen Site; and a three-dimensional injection experiment at Hanford's Sisson and Lu Site. Good agreements are achieved in all three applications between observations and simulations in both parameter estimates and water dynamics reproduction. Results show that eSTOMP/BeoPEST approach is highly scalable and can be run efficiently with hundreds or thousands of processors. BeoPEST is fault tolerant and new nodes can be dynamically added and removed. A major advantage of this approach is the ability to use high-resolution geologic models to preserve the spatial structure in the inverse model, which leads to better parameter estimates and improved predictions when using the inverse-conditioned realizations of parameter fields.

Optimization of microwave-assisted extraction of protopine and allocryptopine from stems of Macleaya cordata (Willd) R. Br. using response surface methodology.

PubMed

Zhong, Ming; Huang, Ke-Long; Zeng, Jian-Guo; Li, Shuang; She, Jin-Ming; Li, Guiyin; Zhang, Li

2010-07-01

The purpose of the research was to investigate the multiple response optimizations for the extraction of protopine and allocryptopine from the stems of Macleaya cordata (Willd) R. Br. by using microwave-assisted extraction (MAE). A three-level, three-factor Box-Behnken design of response surface methodology was used to develop response model, and desirability function was employed to optimize the effects of main extraction parameters. Three variables, ethanol concentration (20-80%, v/v), extraction temperature (30-70 degrees C) and solvent/solid ratio (10:1 to 30:1, mL/g), were investigated in this study. The results showed that the optimum parameters of MAE were ethanol concentration of 45.2 % (v/v), extraction temperature of 54.7 degrees C and solvent/solid ratio of 20.4:1 (mL/g). Under these conditions, the extraction yields of protopine and allocryptopine were 89.4 and 102.0%, respectively, and the extracta sicca yield was 12.5%. The combination use of response surface methodology, Box-Behnken design and the appropriate desirability function could provide an insight into a lab-scale MAE process, and help to develop procedures for commercial production of active ingredients from medical plants.

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.

Coregistration refinement of hyperspectral images and DSM: An object-based approach using spectral information

NASA Astrophysics Data System (ADS)

Avbelj, Janja; Iwaszczuk, Dorota; Müller, Rupert; Reinartz, Peter; Stilla, Uwe

2015-02-01

For image fusion in remote sensing applications the georeferencing accuracy using position, attitude, and camera calibration measurements can be insufficient. Thus, image processing techniques should be employed for precise coregistration of images. In this article a method for multimodal object-based image coregistration refinement between hyperspectral images (HSI) and digital surface models (DSM) is presented. The method is divided in three parts: object outline detection in HSI and DSM, matching, and determination of transformation parameters. The novelty of our proposed coregistration refinement method is the use of material properties and height information of urban objects from HSI and DSM, respectively. We refer to urban objects as objects which are typical in urban environments and focus on buildings by describing them with 2D outlines. Furthermore, the geometric accuracy of these detected building outlines is taken into account in the matching step and for the determination of transformation parameters. Hence, a stochastic model is introduced to compute optimal transformation parameters. The feasibility of the method is shown by testing it on two aerial HSI of different spatial and spectral resolution, and two DSM of different spatial resolution. The evaluation is carried out by comparing the accuracies of the transformations parameters to the reference parameters, determined by considering object outlines at much higher resolution, and also by computing the correctness and the quality rate of the extracted outlines before and after coregistration refinement. Results indicate that using outlines of objects instead of only line segments is advantageous for coregistration of HSI and DSM. The extraction of building outlines in comparison to the line cue extraction provides a larger amount of assigned lines between the images and is more robust to outliers, i.e. false matches.

Automatic Determination of the Conic Coronal Mass Ejection Model Parameters

NASA Technical Reports Server (NTRS)

Pulkkinen, A.; Oates, T.; Taktakishvili, A.

2009-01-01

Characterization of the three-dimensional structure of solar transients using incomplete plane of sky data is a difficult problem whose solutions have potential for societal benefit in terms of space weather applications. In this paper transients are characterized in three dimensions by means of conic coronal mass ejection (CME) approximation. A novel method for the automatic determination of cone model parameters from observed halo CMEs is introduced. The method uses both standard image processing techniques to extract the CME mass from white-light coronagraph images and a novel inversion routine providing the final cone parameters. A bootstrap technique is used to provide model parameter distributions. When combined with heliospheric modeling, the cone model parameter distributions will provide direct means for ensemble predictions of transient propagation in the heliosphere. An initial validation of the automatic method is carried by comparison to manually determined cone model parameters. It is shown using 14 halo CME events that there is reasonable agreement, especially between the heliocentric locations of the cones derived with the two methods. It is argued that both the heliocentric locations and the opening half-angles of the automatically determined cones may be more realistic than those obtained from the manual analysis

A hybrid system identification methodology for wireless structural health monitoring systems based on dynamic substructuring

NASA Astrophysics Data System (ADS)

Dragos, Kosmas; Smarsly, Kay

2016-04-01

System identification has been employed in numerous structural health monitoring (SHM) applications. Traditional system identification methods usually rely on centralized processing of structural response data to extract information on structural parameters. However, in wireless SHM systems the centralized processing of structural response data introduces a significant communication bottleneck. Exploiting the merits of decentralization and on-board processing power of wireless SHM systems, many system identification methods have been successfully implemented in wireless sensor networks. While several system identification approaches for wireless SHM systems have been proposed, little attention has been paid to obtaining information on the physical parameters (e.g. stiffness, damping) of the monitored structure. This paper presents a hybrid system identification methodology suitable for wireless sensor networks based on the principles of component mode synthesis (dynamic substructuring). A numerical model of the monitored structure is embedded into the wireless sensor nodes in a distributed manner, i.e. the entire model is segmented into sub-models, each embedded into one sensor node corresponding to the substructure the sensor node is assigned to. The parameters of each sub-model are estimated by extracting local mode shapes and by applying the equations of the Craig-Bampton method on dynamic substructuring. The proposed methodology is validated in a laboratory test conducted on a four-story frame structure to demonstrate the ability of the methodology to yield accurate estimates of stiffness parameters. Finally, the test results are discussed and an outlook on future research directions is provided.

Mathematical modeling of phase change electrodes and application to a novel titanium extraction process

NASA Astrophysics Data System (ADS)

Kar, Pritish

Titanium and its alloys have excellent engineering properties but their applications are limited because they are expensive and a good percentage of this cost results from the extraction process. The national agencies of many countries around the world have invested a lot of resources to develop a more cost-effective titanium extraction process. A result of one such research efforts is the Fray-Farthing-Chen (FFC) process in which pellets of titanium dioxide are made the cathode in an electrochemical cell with a graphite anode and an electrolyte of molten CaCl2 at 900°C. After electro-deoxidation, the pellets are reduced to titanium with oxygen in solid solution. From this short description, this one step process provides distinct advantages over the current process of extracting titanium known as the Kroll process that takes several days to complete. For investigation of the FFC process theoretically, a coupled electrochemical and diffusion based model was set-up to simulate the linear sweep voltammograms that was developed by collaborators working on lab-scale experiments on the FCC process. Using this model, a parameter called "deltadc" (that is the product of diffusion coefficients of oxygen in the phases, Ti3O5 and Ti2O3 and the stoichiometric range of these phases) was determined. The results suggest a reaction of first-order in the concentration of oxygen in the solid phase. For modeling the reaction of an individual sintered pellet of TiO 2 as it undergoes electro-deoxidation in a molten salt bath of CaCl 2, a similarity of this process with the operation of a lithium ion battery was exploited. Using the model, a number of parameters of physical importance, namely thickness of the sintered pellets, porosity of the pellets and the radius of the particles making up the pellets and the optimum values for the these parameters were proposed based on the simulation data. It is also shown that if the reduction is started with a pellet of partially reduced titanium dioxide (such as by reducing with hydrogen), one can avoid titanate formation. The work described in this dissertation will hopefully help in the development of a more cost-effective titanium extraction process.

Extracting sensitive spectrum bands of rapeseed using multiscale multifractal detrended fluctuation analysis

NASA Astrophysics Data System (ADS)

Jiang, Shan; Wang, Fang; Shen, Luming; Liao, Guiping; Wang, Lin

2017-03-01

Spectrum technology has been widely used in crop non-destructive testing diagnosis for crop information acquisition. Since spectrum covers a wide range of bands, it is of critical importance to extract the sensitive bands. In this paper, we propose a methodology to extract the sensitive spectrum bands of rapeseed using multiscale multifractal detrended fluctuation analysis. Our obtained sensitive bands are relatively robust in the range of 534 nm-574 nm. Further, by using the multifractal parameter (Hurst exponent) of the extracted sensitive bands, we propose a prediction model to forecast the Soil and plant analyzer development values ((SPAD), often used as a parameter to indicate the chlorophyll content) and an identification model to distinguish the different planting patterns. Three vegetation indices (VIs) based on previous work are used for comparison. Three evaluation indicators, namely, the root mean square error, the correlation coefficient, and the relative error employed in the SPAD values prediction model all demonstrate that our Hurst exponent has the best performance. Four rapeseed compound planting factors, namely, seeding method, planting density, fertilizer type, and weed control method are considered in the identification model. The Youden indices calculated by the random decision forest method and the K-nearest neighbor method show that our Hurst exponent is superior to other three Vis, and their combination for the factor of seeding method. In addition, there is no significant difference among the five features for other three planting factors. This interesting finding suggests that the transplanting and the direct seeding would make a big difference in the growth of rapeseed.

[The release of biologically active compounds from peat peloids].

PubMed

Babaskin, D V

2011-01-01

This work had the objective to study kinetics of the release of flavonoides from peat peloid compositions containing extracts of medicinal herbs in model systems.The key parameters of the process are defined. The rate of liberation of flavonoides is shown to depend on their initial concentration in the compositions being used. The influence of the flavonoide composition of the tested extracts and dimethylsulfoxide on the release of biologically active compounds contained in the starting material in the model environment is estimated. The possibility of the layer-by-layer deposition of the compositions and peat peloids in order to increase the efficacy of flavonoide release from the starting composition and to ensure more rational utilization of the extracts of medicinal plants is demonstrated.

[Optimization for supercritical CO2 extraction with response surface methodology and component analysis of Sapindus mukorossi oil].

PubMed

Wu, Yan; Xiao, Xin-yu; Ge, Fa-huan

2012-02-01

To study the extraction conditions of Sapindus mukorossi oil by Supercritical CO2 Extraction and identify its components. Optimized SFE-CO2 Extraction by response surface methodology and used GC-MS to analysie Sapindus mukorossi oil compounds. Established the model of an equation for the extraction rate of Sapindus mukorossi oil by Supercritical CO2 Extraction, and the optimal parameters for the Supercritical CO2 Extraction determined by the equation were: the extraction pressure was 30 MPa, temperature was 40 degrees C; The separation I pressure was 14 MPa, temperature was 45 degrees C; The separation II pressure was 6 MPa, temperature was 40 degrees C; The extraction time was 60 min and the extraction rate of Sapindus mukorossi oil of 17.58%. 22 main compounds of Sapindus mukorossi oil extracted by supercritical CO2 were identified by GC-MS, unsaturated fatty acids were 86.59%. This process is reliable, safe and with simple operation, and can be used for the extraction of Sapindus mukorossi oil.

Evaluation of Myrtus communis Linn. berries (common myrtle) in experimental ulcer models in rats.

PubMed

Sumbul, Sabiha; Ahmad, Mohd Aftab; Asif, Mohd; Saud, Ibne; Akhtar, Mohd

2010-11-01

The present study was conducted to investigate the protective effect of the dried berries of Myrtus communis L. in gastric ulcer against ethanol, indomethacin and pyloric ligation induced models in Wistar rats. Two doses of aqueous extracts of M. communis (AE( 1) and AE(2)) at the dose 105 and 175 mg/kg, respectively, and methanolic extracts (ME(1) and ME(2)) at the dose of 93 and 154 mg/kg, respectively, were administered orally to animals prior to the exposure of ulcerogens. The parameters taken to assess anti-ulcer activity were ulcer index, gastric juice volume, gastric pH, total acidity, gastric wall mucus and histopathological studies. Oral administration of AE(1) and AE(2) significantly reduced the ulcer index in all models of ulcers. Low dose of aqueous extract and high dose of methanolic extract of M. communis exhibited more significant effect in comparison to omeprazole (standard drug) in ethanol-induced ulcer model. Both the doses of aqueous and methanolic extracts also reduced the gastric juice volume, total acidity and increased the gastric pH and gastric wall mucus content in all the models of ulcers used in the present study. Histopathological examinations of gastric tissues of rats treated with the aqueous and methanolic extracts in indomethacin-induced ulcer exhibited significant ulcer-protective effect at both the dose levels.

Scale-invariant feature extraction of neural network and renormalization group flow

NASA Astrophysics Data System (ADS)

Iso, Satoshi; Shiba, Shotaro; Yokoo, Sumito

2018-05-01

Theoretical understanding of how a deep neural network (DNN) extracts features from input images is still unclear, but it is widely believed that the extraction is performed hierarchically through a process of coarse graining. It reminds us of the basic renormalization group (RG) concept in statistical physics. In order to explore possible relations between DNN and RG, we use the restricted Boltzmann machine (RBM) applied to an Ising model and construct a flow of model parameters (in particular, temperature) generated by the RBM. We show that the unsupervised RBM trained by spin configurations at various temperatures from T =0 to T =6 generates a flow along which the temperature approaches the critical value Tc=2.2 7 . This behavior is the opposite of the typical RG flow of the Ising model. By analyzing various properties of the weight matrices of the trained RBM, we discuss why it flows towards Tc and how the RBM learns to extract features of spin configurations.

Automatic Parametrization of Somatosensory Evoked Potentials With Chirp Modeling.

PubMed

Vayrynen, Eero; Noponen, Kai; Vipin, Ashwati; Thow, X Y; Al-Nashash, Hasan; Kortelainen, Jukka; All, Angelo

2016-09-01

In this paper, an approach using polynomial phase chirp signals to model somatosensory evoked potentials (SEPs) is proposed. SEP waveforms are assumed as impulses undergoing group velocity dispersion while propagating along a multipath neural connection. Mathematical analysis of pulse dispersion resulting in chirp signals is performed. An automatic parameterization of SEPs is proposed using chirp models. A Particle Swarm Optimization algorithm is used to optimize the model parameters. Features describing the latencies and amplitudes of SEPs are automatically derived. A rat model is then used to evaluate the automatic parameterization of SEPs in two experimental cases, i.e., anesthesia level and spinal cord injury (SCI). Experimental results show that chirp-based model parameters and the derived SEP features are significant in describing both anesthesia level and SCI changes. The proposed automatic optimization based approach for extracting chirp parameters offers potential for detailed SEP analysis in future studies. The method implementation in Matlab technical computing language is provided online.

3D space positioning and image feature extraction for workpiece

NASA Astrophysics Data System (ADS)

Ye, Bing; Hu, Yi

2008-03-01

An optical system of 3D parameters measurement for specific area of a workpiece has been presented and discussed in this paper. A number of the CCD image sensors are employed to construct the 3D coordinate system for the measured area. The CCD image sensor of the monitoring target is used to lock the measured workpiece when it enters the field of view. The other sensors, which are placed symmetrically beam scanners, measure the appearance of the workpiece and the characteristic parameters. The paper established target image segmentation and the image feature extraction algorithm to lock the target, based on the geometric similarity of objective characteristics, rapid locking the goal can be realized. When line laser beam scan the tested workpiece, a number of images are extracted equal time interval and the overlapping images are processed to complete image reconstruction, and achieve the 3D image information. From the 3D coordinate reconstruction model, the 3D characteristic parameters of the tested workpiece are gained. The experimental results are provided in the paper.

Influence of material uncertainties on the RLC parameters of wound inductors modeled using the finite element method

NASA Astrophysics Data System (ADS)

Lossa, Geoffrey; Deblecker, Olivier; Grève, Zacharie De

2018-05-01

In this work, we highlight the influence of the material uncertainties (magnetic permeability, electric conductivity of a Mn-Zn ferrite core, and electric permittivity of wire insulation) on the RLC parameters of a wound inductor extracted from the finite element method. To that end, the finite element method is embedded in a Monte Carlo simulation. We show that considering mentioned different material properties as real random variables, leads to significant variations in the distributions of the RLC parameters.

Ricci-Gauss-Bonnet holographic dark energy

NASA Astrophysics Data System (ADS)

Saridakis, Emmanuel N.

2018-03-01

We present a model of holographic dark energy in which the infrared cutoff is determined by both the Ricci and the Gauss-Bonnet invariants. Such a construction has the significant advantage that the infrared cutoff, and consequently the holographic dark energy density, does not depend on the future or the past evolution of the universe, but only on its current features, and moreover it is determined by invariants, whose role is fundamental in gravitational theories. We extract analytical solutions for the behavior of the dark energy density and equation-of-state parameters as functions of the redshift. These reveal the usual thermal history of the universe, with the sequence of radiation, matter and dark energy epochs, resulting in the future to a complete dark energy domination. The corresponding dark energy equation-of-state parameter can lie in the quintessence or phantom regime, or experience the phantom-divide crossing during the cosmological evolution, and its asymptotic value can be quintessencelike, phantomlike, or be exactly equal to the cosmological-constant value. Finally, we extract the constraints on the model parameters that arise from big bang nucleosynthesis.

Method and apparatus for autonomous, in-receiver prediction of GNSS ephemerides

NASA Technical Reports Server (NTRS)

Bar-Sever, Yoaz E. (Inventor); Bertiger, William I. (Inventor)

2012-01-01

Methods and apparatus for autonomous in-receiver prediction of orbit and clock states of Global Navigation Satellite Systems (GNSS) are described. Only the GNSS broadcast message is used, without need for periodic externally-communicated information. Earth orientation information is extracted from the GNSS broadcast ephemeris. With the accurate estimation of the Earth orientation parameters it is possible to propagate the best-fit GNSS orbits forward in time in an inertial reference frame. Using the estimated Earth orientation parameters, the predicted orbits are then transformed into Earth-Centered-Earth-Fixed (ECEF) coordinates to be used to assist the GNSS receiver in the acquisition of the signals. GNSS satellite clock states are also extracted from the broadcast ephemeris and a parameterized model of clock behavior is fit to that data. The estimated modeled clocks are then propagated forward in time to enable, together with the predicted orbits, quicker GNSS signal acquisition.

Static terrestrial laser scanning of juvenile understory trees for field phenotyping

NASA Astrophysics Data System (ADS)

Wang, Huanhuan; Lin, Yi

2014-11-01

This study was to attempt the cutting-edge 3D remote sensing technique of static terrestrial laser scanning (TLS) for parametric 3D reconstruction of juvenile understory trees. The data for test was collected with a Leica HDS6100 TLS system in a single-scan way. The geometrical structures of juvenile understory trees are extracted by model fitting. Cones are used to model trunks and branches. Principal component analysis (PCA) is adopted to calculate their major axes. Coordinate transformation and orthogonal projection are used to estimate the parameters of the cones. Then, AutoCAD is utilized to simulate the morphological characteristics of the understory trees, and to add secondary branches and leaves in a random way. Comparison of the reference values and the estimated values gives the regression equation and shows that the proposed algorithm of extracting parameters is credible. The results have basically verified the applicability of TLS for field phenotyping of juvenile understory trees.

Angle-domain common-image gathers from anisotropic Gaussian beam migration and its application to anisotropy-induced imaging errors analysis

NASA Astrophysics Data System (ADS)

Han, Jianguang; Wang, Yun; Yu, Changqing; Chen, Peng

2017-02-01

An approach for extracting angle-domain common-image gathers (ADCIGs) from anisotropic Gaussian beam prestack depth migration (GB-PSDM) is presented in this paper. The propagation angle is calculated in the process of migration using the real-value traveltime information of Gaussian beam. Based on the above, we further investigate the effects of anisotropy on GB-PSDM, where the corresponding ADCIGs are extracted to assess the quality of migration images. The test results of the VTI syncline model and the TTI thrust sheet model show that anisotropic parameters ɛ, δ, and tilt angle 𝜃, have a great influence on the accuracy of the migrated image in anisotropic media, and ignoring any one of them will cause obvious imaging errors. The anisotropic GB-PSDM with the true anisotropic parameters can obtain more accurate seismic images of subsurface structures in anisotropic media.

Rapid and effective decontamination of chlorophenol-contaminated soil by sorption into commercial polymers: concept demonstration and process modeling.

PubMed

Tomei, M Concetta; Mosca Angelucci, Domenica; Ademollo, Nicoletta; Daugulis, Andrew J

2015-03-01

Solid phase extraction performed with commercial polymer beads to treat soil contaminated by chlorophenols (4-chlorophenol, 2,4-dichlorophenol and pentachlorophenol) as single compounds and in a mixture has been investigated in this study. Soil-water-polymer partition tests were conducted to determine the relative affinities of single compounds in soil-water and polymer-water pairs. Subsequent soil extraction tests were performed with Hytrel 8206, the polymer showing the highest affinity for the tested chlorophenols. Factors that were examined were polymer type, moisture content, and contamination level. Increased moisture content (up to 100%) improved the extraction efficiency for all three compounds. Extraction tests at this upper level of moisture content showed removal efficiencies ≥70% for all the compounds and their ternary mixture, for 24 h of contact time, which is in contrast to the weeks and months, normally required for conventional ex situ remediation processes. A dynamic model characterizing the rate and extent of decontamination was also formulated, calibrated and validated with the experimental data. The proposed model, based on the simplified approach of "lumped parameters" for the mass transfer coefficients, provided very good predictions of the experimental data for the absorptive removal of contaminants from soil at different individual solute levels. Parameters evaluated from calibration by fitting of single compound data, have been successfully applied to predict mixture data, with differences between experimental and predicted data in all cases being ≤3%. Copyright © 2014 Elsevier Ltd. All rights reserved.

Development of a Landforms Model for Puerto Rico and its Application for Land Cover Change Analysis

Treesearch

Sebastian Martinuzzi; William A. Gould; Olga M. Ramos Gonzalez; Brook E. Edwards

2007-01-01

Comprehensive analysis of land morphology is essential to supporting a wide range environmental studies. We developed a landforms model that identifies eleven landform units for Puerto Rico based on parameters of land position and slope. The model is capable of extracting operational information in a simple way and is adaptable to different environments and objectives...

Transient Method for Determining Indoor Chemical Concentrations Based on SPME: Model Development and Calibration.

PubMed

Cao, Jianping; Xiong, Jianyin; Wang, Lixin; Xu, Ying; Zhang, Yinping

2016-09-06

Solid-phase microextraction (SPME) is regarded as a nonexhaustive sampling technique with a smaller extraction volume and a shorter extraction time than traditional sampling techniques and is hence widely used. The SPME sampling process is affected by the convection or diffusion effect along the coating surface, but this factor has seldom been studied. This paper derives an analytical model to characterize SPME sampling for semivolatile organic compounds (SVOCs) as well as for volatile organic compounds (VOCs) by considering the surface mass transfer process. Using this model, the chemical concentrations in a sample matrix can be conveniently calculated. In addition, the model can be used to determine the characteristic parameters (partition coefficient and diffusion coefficient) for typical SPME chemical samplings (SPME calibration). Experiments using SPME samplings of two typical SVOCs, dibutyl phthalate (DBP) in sealed chamber and di(2-ethylhexyl) phthalate (DEHP) in ventilated chamber, were performed to measure the two characteristic parameters. The experimental results demonstrated the effectiveness of the model and calibration method. Experimental data from the literature (VOCs sampled by SPME) were used to further validate the model. This study should prove useful for relatively rapid quantification of concentrations of different chemicals in various circumstances with SPME.

Using bioimpedance spectroscopy parameters as real-time feedback during tDCS.

PubMed

Nejadgholi, Isar; Caytak, Herschel; Bolic, Miodrag

2016-08-01

An exploratory analysis is carried out to investigate the feasibility of using BioImpedance Spectroscopy (BIS) parameters, measured on scalp, as real-time feedback during Transcranial Direct Current Stimulation (tDCS). TDCS is shown to be a potential treatment for neurological disorders. However, this technique is not considered as a reliable clinical treatment, due to the lack of a measurable indicator of treatment efficacy. Although the voltage that is applied on the head is very simple to measure during a tDCS session, changes of voltage are difficult to interpret in terms of variables that affect clinical outcome. BIS parameters are considered as potential feedback parameters, because: 1) they are shown to be associated with the DC voltage applied on the head, 2) they are interpretable in terms of conductive and capacitive properties of head tissues, 3) physical interpretation of BIS measurements makes them prone to be adjusted by clinically controllable variables, 4) BIS parameters are measurable in a cost-effective and safe way and do not interfere with DC stimulation. This research indicates that a quadratic regression model can predict the DC voltage between anode and cathode based on parameters extracted from BIS measurements. These parameters are extracted by fitting the measured BIS spectra to an equivalent electrical circuit model. The effect of clinical tDCS variables on BIS parameters needs to be investigated in future works. This work suggests that BIS is a potential method to be used for monitoring a tDCS session in order to adjust, tailor, or personalize tDCS treatment protocols.

Compositional and textural information from the dual inversion of visible, near and thermal infrared remotely sensed data

NASA Technical Reports Server (NTRS)

Brackett, Robert A.; Arvidson, Raymond E.

1993-01-01

A technique is presented that allows extraction of compositional and textural information from visible, near and thermal infrared remotely sensed data. Using a library of both emissivity and reflectance spectra, endmember abundances and endmember thermal inertias are extracted from AVIRIS (Airborne Visible and Infrared Imaging Spectrometer) and TIMS (Thermal Infrared Mapping Spectrometer) data over Lunar Crater Volcanic Field, Nevada, using a dual inversion. The inversion technique is motivated by upcoming Mars Observer data and the need for separation of composition and texture parameters from sub pixel mixtures of bedrock and dust. The model employed offers the opportunity to extract compositional and textural information for a variety of endmembers within a given pixel. Geologic inferences concerning grain size, abundance, and source of endmembers can be made directly from the inverted data. These parameters are of direct relevance to Mars exploration, both for Mars Observer and for follow-on missions.

Improved model reduction and tuning of fractional-order PI(λ)D(μ) controllers for analytical rule extraction with genetic programming.

PubMed

Das, Saptarshi; Pan, Indranil; Das, Shantanu; Gupta, Amitava

2012-03-01

Genetic algorithm (GA) has been used in this study for a new approach of suboptimal model reduction in the Nyquist plane and optimal time domain tuning of proportional-integral-derivative (PID) and fractional-order (FO) PI(λ)D(μ) controllers. Simulation studies show that the new Nyquist-based model reduction technique outperforms the conventional H(2)-norm-based reduced parameter modeling technique. With the tuned controller parameters and reduced-order model parameter dataset, optimum tuning rules have been developed with a test-bench of higher-order processes via genetic programming (GP). The GP performs a symbolic regression on the reduced process parameters to evolve a tuning rule which provides the best analytical expression to map the data. The tuning rules are developed for a minimum time domain integral performance index described by a weighted sum of error index and controller effort. From the reported Pareto optimal front of the GP-based optimal rule extraction technique, a trade-off can be made between the complexity of the tuning formulae and the control performance. The efficacy of the single-gene and multi-gene GP-based tuning rules has been compared with the original GA-based control performance for the PID and PI(λ)D(μ) controllers, handling four different classes of representative higher-order processes. These rules are very useful for process control engineers, as they inherit the power of the GA-based tuning methodology, but can be easily calculated without the requirement for running the computationally intensive GA every time. Three-dimensional plots of the required variation in PID/fractional-order PID (FOPID) controller parameters with reduced process parameters have been shown as a guideline for the operator. Parametric robustness of the reported GP-based tuning rules has also been shown with credible simulation examples. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

Antidiabetic activity of aqueous extract and non polysaccharide fraction of Cynodon dactylon Pers.

PubMed

Jarald, E E; Joshi, S B; Jain, D C

2008-09-01

Petroleum ether (60 degrees-80 degrees C), chloroform, acetone, ethanol, aqueous and crude hot water extracts of the whole plant of C. dactylon and the two fractions of aqueous extract were tested for antihyperglycaemic activity in glucose overloaded hyperglycemic rats and in alloxan induced diabetic model at two-dose levels, 200 and 400 mg/kg (po) respectively. The aqueous extract of C. dactylon and the non polysaccharide fraction of aqueous extract were found to exhibit significant antihyperglycaemic activity and only the non polysaccharide fraction was found to produce hypoglycemia in fasted normal rats. Treatment of diabetic rats with aqueous extract and non polysaccharide fraction of the plant decreased the elevated biochemical parameters, glucose, urea, creatinine, serum cholesterol, serum triglyceride, high density lipoprotein, low density lipoprotein, haemoglobin and glycosylated haemoglobin significantly. Comparatively, the non polysaccharide fraction of aqueous extract was found to be more effective than the aqueous extract.

Determination of the ultrasound power effects on flavonoid compounds from Psidium guajava L. using ANFIS

NASA Astrophysics Data System (ADS)

Ratu Ayu, Humairoh; Suryono, Suryono; Endro Suseno, Jatmiko; Kurniawati, Ratna

2018-05-01

The Adaptive Neural Fuzzy Inference System (ANFIS) model was used to predict and optimize the content of flavonoid compounds in guava leaves (Psidium Guajava L.). The extraction process was carried out by using ultrasound assisted extraction (UAE) with the variable parameters: temperature ranging from 25°C to 35°C, ultrasonic frequency (30 - 40 kHz) and extraction time (20 - 40 minutes). ANFIS learning procedure began by providing the input variable data set (temperature, frequency and time) and the output of the flavonoid compounds from the experiments that had been done. Subtractive clustering methods was used in the manufacture of FIS (fuzzy inference system) structures by varying the range of influence parameters to generate the ANFIS system. The ANFIS trainingsconducted wereaimed at minimum error value. The results showed that the best ANFIS models used a subtractive clustering method, in which the ranges of influence 0.1 were 0.70 x 10-4 for training RMSE, 8.11 for testing RMSE, 2.7 % MAPE, and 7.72 MAE. The optimum condition was obtained at a temperature of 35°C and frequency of 40 kHz, for 30 minutes. This result proves that the ANFIS model can be used to predict the content of flavonoid compounds in guava leaves.

Thermodynamic modeling of transcription: sensitivity analysis differentiates biological mechanism from mathematical model-induced effects.

PubMed

Dresch, Jacqueline M; Liu, Xiaozhou; Arnosti, David N; Ay, Ahmet

2010-10-24

Quantitative models of gene expression generate parameter values that can shed light on biological features such as transcription factor activity, cooperativity, and local effects of repressors. An important element in such investigations is sensitivity analysis, which determines how strongly a model's output reacts to variations in parameter values. Parameters of low sensitivity may not be accurately estimated, leading to unwarranted conclusions. Low sensitivity may reflect the nature of the biological data, or it may be a result of the model structure. Here, we focus on the analysis of thermodynamic models, which have been used extensively to analyze gene transcription. Extracted parameter values have been interpreted biologically, but until now little attention has been given to parameter sensitivity in this context. We apply local and global sensitivity analyses to two recent transcriptional models to determine the sensitivity of individual parameters. We show that in one case, values for repressor efficiencies are very sensitive, while values for protein cooperativities are not, and provide insights on why these differential sensitivities stem from both biological effects and the structure of the applied models. In a second case, we demonstrate that parameters that were thought to prove the system's dependence on activator-activator cooperativity are relatively insensitive. We show that there are numerous parameter sets that do not satisfy the relationships proferred as the optimal solutions, indicating that structural differences between the two types of transcriptional enhancers analyzed may not be as simple as altered activator cooperativity. Our results emphasize the need for sensitivity analysis to examine model construction and forms of biological data used for modeling transcriptional processes, in order to determine the significance of estimated parameter values for thermodynamic models. Knowledge of parameter sensitivities can provide the necessary context to determine how modeling results should be interpreted in biological systems.

Comparison of ONIX simulation results with experimental data from the BATMAN testbed for the study of negative ion extraction

NASA Astrophysics Data System (ADS)

Mochalskyy, Serhiy; Fantz, Ursel; Wünderlich, Dirk; Minea, Tiberiu

2016-10-01

The development of negative ion (NI) sources for the ITER neutral beam injector is strongly accompanied by modelling activities. The ONIX (Orsay Negative Ion eXtraction) code simulates the formation and extraction of negative hydrogen ions and co-extracted electrons produced in caesiated sources. In this paper the 3D geometry of the BATMAN extraction system, and the source characteristics such as the extraction and bias potential, and the 3D magnetic field were integrated in the model. Calculations were performed using plasma parameters experimentally obtained on BATMAN. The comparison of the ONIX calculated extracted NI density with the experimental results suggests that predictive calculations of the extraction of NIs are possible. The results show that for an ideal status of the Cs conditioning the extracted hydrogen NI current density could reach ~30 mA cm-2 at 10 kV and ~20 mA cm-2 at 5 kV extraction potential, with an electron/NI current density ratio of about 1, as measured in the experiments under the same plasma and source conditions. The dependency of the extracted NI current on the NI density in the bulk plasma region from both the modeling and the experiment was investigated. The separate distributions composing the NI beam originating from the plasma bulk region and the PG surface are presented for different NI plasma volume densities and NI emission rates from the plasma grid (PG) wall, respectively. The extracted current from the NIs produced at the Cs covered PG surface, initially moving towards the bulk plasma and then being bent towards the extraction surfaces, is lower compared to the extracted NI current from directly extracted surface produced ions.

Automatic pole-like object modeling via 3D part-based analysis of point cloud

NASA Astrophysics Data System (ADS)

He, Liu; Yang, Haoxiang; Huang, Yuchun

2016-10-01

Pole-like objects, including trees, lampposts and traffic signs, are indispensable part of urban infrastructure. With the advance of vehicle-based laser scanning (VLS), massive point cloud of roadside urban areas becomes applied in 3D digital city modeling. Based on the property that different pole-like objects have various canopy parts and similar trunk parts, this paper proposed the 3D part-based shape analysis to robustly extract, identify and model the pole-like objects. The proposed method includes: 3D clustering and recognition of trunks, voxel growing and part-based 3D modeling. After preprocessing, the trunk center is identified as the point that has local density peak and the largest minimum inter-cluster distance. Starting from the trunk centers, the remaining points are iteratively clustered to the same centers of their nearest point with higher density. To eliminate the noisy points, cluster border is refined by trimming boundary outliers. Then, candidate trunks are extracted based on the clustering results in three orthogonal planes by shape analysis. Voxel growing obtains the completed pole-like objects regardless of overlaying. Finally, entire trunk, branch and crown part are analyzed to obtain seven feature parameters. These parameters are utilized to model three parts respectively and get signal part-assembled 3D model. The proposed method is tested using the VLS-based point cloud of Wuhan University, China. The point cloud includes many kinds of trees, lampposts and other pole-like posters under different occlusions and overlaying. Experimental results show that the proposed method can extract the exact attributes and model the roadside pole-like objects efficiently.

Power maximization of a point absorber wave energy converter using improved model predictive control

NASA Astrophysics Data System (ADS)

Milani, Farideh; Moghaddam, Reihaneh Kardehi

2017-08-01

This paper considers controlling and maximizing the absorbed power of wave energy converters for irregular waves. With respect to physical constraints of the system, a model predictive control is applied. Irregular waves' behavior is predicted by Kalman filter method. Owing to the great influence of controller parameters on the absorbed power, these parameters are optimized by imperialist competitive algorithm. The results illustrate the method's efficiency in maximizing the extracted power in the presence of unknown excitation force which should be predicted by Kalman filter.

Alternative Bio-Based Solvents for Extraction of Fat and Oils: Solubility Prediction, Global Yield, Extraction Kinetics, Chemical Composition and Cost of Manufacturing

PubMed Central

Sicaire, Anne-Gaëlle; Vian, Maryline; Fine, Frédéric; Joffre, Florent; Carré, Patrick; Tostain, Sylvain; Chemat, Farid

2015-01-01

The present study was designed to evaluate the performance of alternative bio-based solvents, more especially 2-methyltetrahydrofuran, obtained from crop’s byproducts for the substitution of petroleum solvents such as hexane in the extraction of fat and oils for food (edible oil) and non-food (bio fuel) applications. First a solvent selection as well as an evaluation of the performance was made with Hansen Solubility Parameters and the COnductor-like Screening MOdel for Realistic Solvation (COSMO-RS) simulations. Experiments were performed on rapeseed oil extraction at laboratory and pilot plant scale for the determination of lipid yields, extraction kinetics, diffusion modeling, and complete lipid composition in term of fatty acids and micronutrients (sterols, tocopherols and tocotrienols). Finally, economic and energetic evaluations of the process were conducted to estimate the cost of manufacturing using 2-methyltetrahydrofuran (MeTHF) as alternative solvent compared to hexane as petroleum solvent. PMID:25884332

Helichrysum plicatum DC. subsp. plicatum extract as a preventive agent in experimentally induced urolithiasis model.

PubMed

Bayir, Yasin; Halici, Zekai; Keles, Mevlut Sait; Colak, Suat; Cakir, Ahmet; Kaya, Yusuf; Akçay, Fatih

2011-11-18

Since ancient times, various herbal preparations have been used in treatment of urolithiasis, which is basically formation of calcium oxalate stones in kidney. The aim of our study is to assess the effects of Helichrysum plicatum DC. subsp. plicatum (HP) as a preventive agent in experimentally induced urolithiasis model in rats. The efficacy of 125, 250, and 500 mg/kg HP extract was studied in 1% ethylene glycol and 1% ammonium chloride-induced urolithiasis for 21 days in rats. The weight difference and the levels of calcium, magnesium, phosphorus, urea nitrogen, creatinine and uric acid in both serum and 24h-urine were measured. The calcium oxalate (CaOx) and pH were defined in urine. Histo-pathological analyses in kidneys were also performed. The rats' weights were higher in HP groups than urolithiasis group. Urolithiasis caused a significant increase in both serum and urine biochemical parameters compared to healthy rats. HP extract decreased levels of these parameters. Urine CaOx level was high in urolithiasis rats, whereas it was decreased by HP extract. Histopathological examinations revealed extensive intratubular crystal depositions and degenerative tubular structures in urolithiasis group, but not in HP treatment groups. More studies will be necessary to elucidate the antiurolithiatic activity of HP. Nonetheless, having a beneficial effect in preventing and eliminating CaOx deposition into kidneys, HP extract may be a potential drug for urolithiasis treatment. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Preparation of molecularly imprinted solid-phase microextraction fiber for the selective removal and extraction of the antiviral drug abacavir in environmental and biological matrices.

PubMed

Terzopoulou, Zoi; Papageorgiou, Myrsini; Kyzas, George Z; Bikiaris, Dimitrios N; Lambropoulou, Dimitra A

2016-03-24

In the present study, a molecularly imprinted solid-phase microextraction fiber (MIP-SPMEf) was synthesized and applied for the selective removal and extraction of the antiviral drug, abacavir (ABA). Morphology and structure characterization of fibers were performed by scanning electron microscopy and Fourier transform infrared spectra, respectively. The effects on the adsorption behavior of the process parameters were studied and the equilibrium data were fitted by the Langmuir, Freundlich and Langmuir-Freundlich models. The maximum adsorption capability (Qmax) was determined by Langmuir- Freundlich model and was 149 mg/g for MIP-SPMEf. In the next step, SPME methodology followed by liquid desorption and liquid chromatography with mass spectrometry (LC/MS) has been developed and evaluated for the determination of the target compound in environmental and biological matrices (surface waters, wastewaters and urine). Parameters that could influence SPME efficiency were investigated. Then, optimization of stirring speed, extraction time and salt content was carried out by using a central composite design (CCD) and response surface methodology (RSM). A quadratic model between dependent and independent variables was built. Under the optimum conditions (extraction time 40 min, stirring rate 650 rpm and salt content 0.3% NaCl w/v) the validated method presented a high sensitivity and selectivity with LODs and LOQs in the range of 10.1-13.6 and 33.3-43.9 ng/L, respectively. The developed method was successfully applied to the analysis of ABA in real samples. The percentage extraction efficiency ranged from 88 to 99% revealing good accuracy and absence of matrix effects. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

Sorption testing and generalized composite surface complexation models for determining uranium sorption parameters at a proposed in-situ recovery site

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

Johnson, Raymond H.; Truax, Ryan A.; Lankford, David A.

Solid-phase iron concentrations and generalized composite surface complexation models were used to evaluate procedures in determining uranium sorption on oxidized aquifer material at a proposed U in situ recovery (ISR) site. At the proposed Dewey Burdock ISR site in South Dakota, USA, oxidized aquifer material occurs downgradient of the U ore zones. Solid-phase Fe concentrations did not explain our batch sorption test results,though total extracted Fe appeared to be positively correlated with overall measured U sorption. Batch sorption test results were used to develop generalized composite surface complexation models that incorporated the full genericsorption potential of each sample, without detailedmore » mineralogiccharacterization. The resultant models provide U sorption parameters (site densities and equilibrium constants) for reactive transport modeling. The generalized composite surface complexation sorption models were calibrated to batch sorption data from three oxidized core samples using inverse modeling, and gave larger sorption parameters than just U sorption on the measured solidphase Fe. These larger sorption parameters can significantly influence reactive transport modeling, potentially increasing U attenuation. Because of the limited number of calibration points, inverse modeling required the reduction of estimated parameters by fixing two parameters. The best-fit models used fixed values for equilibrium constants, with the sorption site densities being estimated by the inversion process. While these inverse routines did provide best-fit sorption parameters, local minima and correlated parameters might require further evaluation. Despite our limited number of proxy samples, the procedures presented provide a valuable methodology to consider for sites where metal sorption parameters are required. Furthermore, these sorption parameters can be used in reactive transport modeling to assess downgradient metal attenuation, especially when no other calibration data are available, such as at proposed U ISR sites.« less

Sorption testing and generalized composite surface complexation models for determining uranium sorption parameters at a proposed in-situ recovery site

DOE PAGES

Johnson, Raymond H.; Truax, Ryan A.; Lankford, David A.; ...

2016-02-03

Solid-phase iron concentrations and generalized composite surface complexation models were used to evaluate procedures in determining uranium sorption on oxidized aquifer material at a proposed U in situ recovery (ISR) site. At the proposed Dewey Burdock ISR site in South Dakota, USA, oxidized aquifer material occurs downgradient of the U ore zones. Solid-phase Fe concentrations did not explain our batch sorption test results,though total extracted Fe appeared to be positively correlated with overall measured U sorption. Batch sorption test results were used to develop generalized composite surface complexation models that incorporated the full genericsorption potential of each sample, without detailedmore » mineralogiccharacterization. The resultant models provide U sorption parameters (site densities and equilibrium constants) for reactive transport modeling. The generalized composite surface complexation sorption models were calibrated to batch sorption data from three oxidized core samples using inverse modeling, and gave larger sorption parameters than just U sorption on the measured solidphase Fe. These larger sorption parameters can significantly influence reactive transport modeling, potentially increasing U attenuation. Because of the limited number of calibration points, inverse modeling required the reduction of estimated parameters by fixing two parameters. The best-fit models used fixed values for equilibrium constants, with the sorption site densities being estimated by the inversion process. While these inverse routines did provide best-fit sorption parameters, local minima and correlated parameters might require further evaluation. Despite our limited number of proxy samples, the procedures presented provide a valuable methodology to consider for sites where metal sorption parameters are required. Furthermore, these sorption parameters can be used in reactive transport modeling to assess downgradient metal attenuation, especially when no other calibration data are available, such as at proposed U ISR sites.« less

The Impact of Parametric Uncertainties on Biogeochemistry in the E3SM Land Model

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

Ricciuto, Daniel; Sargsyan, Khachik; Thornton, Peter

We conduct a global sensitivity analysis (GSA) of the Energy Exascale Earth System Model (E3SM), land model (ELM) to calculate the sensitivity of five key carbon cycle outputs to 68 model parameters. This GSA is conducted by first constructing a Polynomial Chaos (PC) surrogate via new Weighted Iterative Bayesian Compressive Sensing (WIBCS) algorithm for adaptive basis growth leading to a sparse, high-dimensional PC surrogate with 3,000 model evaluations. The PC surrogate allows efficient extraction of GSA information leading to further dimensionality reduction. The GSA is performed at 96 FLUXNET sites covering multiple plant functional types (PFTs) and climate conditions. Aboutmore » 20 of the model parameters are identified as sensitive with the rest being relatively insensitive across all outputs and PFTs. These sensitivities are dependent on PFT, and are relatively consistent among sites within the same PFT. The five model outputs have a majority of their highly sensitive parameters in common. A common subset of sensitive parameters is also shared among PFTs, but some parameters are specific to certain types (e.g., deciduous phenology). In conclusion, the relative importance of these parameters shifts significantly among PFTs and with climatic variables such as mean annual temperature.« less

The Impact of Parametric Uncertainties on Biogeochemistry in the E3SM Land Model

DOE PAGES

Ricciuto, Daniel; Sargsyan, Khachik; Thornton, Peter

2018-02-27

We conduct a global sensitivity analysis (GSA) of the Energy Exascale Earth System Model (E3SM), land model (ELM) to calculate the sensitivity of five key carbon cycle outputs to 68 model parameters. This GSA is conducted by first constructing a Polynomial Chaos (PC) surrogate via new Weighted Iterative Bayesian Compressive Sensing (WIBCS) algorithm for adaptive basis growth leading to a sparse, high-dimensional PC surrogate with 3,000 model evaluations. The PC surrogate allows efficient extraction of GSA information leading to further dimensionality reduction. The GSA is performed at 96 FLUXNET sites covering multiple plant functional types (PFTs) and climate conditions. Aboutmore » 20 of the model parameters are identified as sensitive with the rest being relatively insensitive across all outputs and PFTs. These sensitivities are dependent on PFT, and are relatively consistent among sites within the same PFT. The five model outputs have a majority of their highly sensitive parameters in common. A common subset of sensitive parameters is also shared among PFTs, but some parameters are specific to certain types (e.g., deciduous phenology). In conclusion, the relative importance of these parameters shifts significantly among PFTs and with climatic variables such as mean annual temperature.« less

Evaluation of Planetary Boundary Layer Scheme Sensitivities for the Purpose of Parameter Estimation

EPA Science Inventory

Meteorological model errors caused by imperfect parameterizations generally cannot be overcome simply by optimizing initial and boundary conditions. However, advanced data assimilation methods are capable of extracting significant information about parameterization behavior from ...

Modelling of influential parameters on a continuous evaporation process by Doehlert shells

PubMed Central

Porte, Catherine; Havet, Jean-Louis; Daguet, David

2003-01-01

The modelling of the parameters that influence the continuous evaporation of an alcoholic extract was considered using Doehlert matrices. The work was performed with a wiped falling film evaporator that allowed us to study the influence of the pressure, temperature, feed flow and dry matter of the feed solution on the dry matter contents of the resulting concentrate, and the productivity of the process. The Doehlert shells were used to model the influential parameters. The pattern obtained from the experimental results was checked allowing for some dysfunction in the unit. The evaporator was modified and a new model applied; the experimental results were then in agreement with the equations. The model was finally determined and successfully checked in order to obtain an 8% dry matter concentrate with the best productivity; the results fit in with the industrial constraints of subsequent processes. PMID:18924887

Involvement of NFκB in the antirheumatic potential of Chenopodium album L., aerial parts extracts.

PubMed

Arora, Sumit K; Itankar, Prakash R; Verma, Prashant R; Bharne, Ashish P; Kokare, Dadasaheb M

2014-08-08

Chenopodium album L. (C. album) is commonly known as Bathua in Hindi (Family: Chenopodiaceae). Traditionally, the plant is used as a laxative, diuretic, sedative and the infusion of the plant is used for the treatment of rheumatism. However, no scientific validation is available on the antirheumatic potential of the plant. In the present investigation, role of NF kappa B (NFκB) in the antiarthritic potential of extracts of aerial parts of Chenopodium album was explored and evaluated. The defatted aerial parts of Chenopodium album were successively extracted with ethylacetate, acetone, methanol and 50% methanol to study their antioxidant capacity followed by antiarthritic potential using Complete Freund׳s adjuvant (CFA) induced arthritis model in rats. The polyphenol, flavonoid and flavanone contents of different extracts were quantified and correlated with their antioxidant capacity, antiarthritic activity and NFκB inhibition potential. The experimental data indicated that the acetone extract of Chenopodium album (ACCA) has shown significant reduction in rat paw edema (80.13%) at dose level of 200 mg/kg per oral in 21 days of this study. On 22nd day, hematological and biochemical parameters were estimated and it was observed that the altered hematological parameters (Hb, RBC, WBC and ESR), biochemical parameters (Serum creatinine, total proteins and acute phase proteins) and loss in body weight in the arthritic rats were significantly brought back to near normal level by the ACCA extract. ACCA extract significantly decreased the NFκB expression in paraventricular nucleus of hypothalamus and this effect is comparable with standard indomethacine in CFA treated rats. The polyphenolic and flavonoid content of different extracts were in the range of 14.56±0.21-42.00±0.2 mg (gallic acid equivalent/g extract) and 2.20±0.003-7.33±0.5 mg (rutin equivalent/g extract) respectively. The antiarthritic activity possessed by ACCA extract can be correlated directly to its antioxidant potential, high flavonoidal content achieved by successive extraction and its capacity to inhibit the NFκB protein, as proven by immunohistochemistry study. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Variability-aware compact modeling and statistical circuit validation on SRAM test array

NASA Astrophysics Data System (ADS)

Qiao, Ying; Spanos, Costas J.

2016-03-01

Variability modeling at the compact transistor model level can enable statistically optimized designs in view of limitations imposed by the fabrication technology. In this work we propose a variability-aware compact model characterization methodology based on stepwise parameter selection. Transistor I-V measurements are obtained from bit transistor accessible SRAM test array fabricated using a collaborating foundry's 28nm FDSOI technology. Our in-house customized Monte Carlo simulation bench can incorporate these statistical compact models; and simulation results on SRAM writability performance are very close to measurements in distribution estimation. Our proposed statistical compact model parameter extraction methodology also has the potential of predicting non-Gaussian behavior in statistical circuit performances through mixtures of Gaussian distributions.

The application of remote sensing to the development and formulation of hydrologic planning models

NASA Technical Reports Server (NTRS)

Fowler, T. R.; Castruccio, P. A.; Loats, H. L., Jr.

1977-01-01

The development of a remote sensing model and its efficiency in determining parameters of hydrologic models are reviewed. Procedures for extracting hydrologic data from LANDSAT imagery, and the visual analysis of composite imagery are presented. A hydrologic planning model is developed and applied to determine seasonal variations in watershed conditions. The transfer of this technology to a user community and contract arrangements are discussed.

Band head spin assignment of superdeformed bands in 133Pr using two-parameter formulae

NASA Astrophysics Data System (ADS)

Sharma, Honey; Mittal, H. M.

2018-03-01

The two-parameter formulae viz. the power index formula, the nuclear softness formula and the VMI model are adopted to accredit the band head spin (I0) of four superdeformed rotational bands in 133Pr. The technique of least square fitting is used to accredit the band head spin for four superdeformed rotational bands in 133Pr. The root mean deviation among the computed transition energies and well-known experimental transition energies are attained by extracting the model parameters from the two-parameter formulae. The determined transition energies are in excellent agreement with the experimental transition energies, whenever exact spins are accredited. The power index formula coincides well with the experimental data and provides minimum root mean deviation. So, the power index formula is more efficient tool than the nuclear softness formula and the VMI model. The deviation of dynamic moment of inertia J(2) against the rotational frequency is also examined.

Information Extraction of High Resolution Remote Sensing Images Based on the Calculation of Optimal Segmentation Parameters

PubMed Central

Zhu, Hongchun; Cai, Lijie; Liu, Haiying; Huang, Wei

2016-01-01

Multi-scale image segmentation and the selection of optimal segmentation parameters are the key processes in the object-oriented information extraction of high-resolution remote sensing images. The accuracy of remote sensing special subject information depends on this extraction. On the basis of WorldView-2 high-resolution data, the optimal segmentation parameters methodof object-oriented image segmentation and high-resolution image information extraction, the following processes were conducted in this study. Firstly, the best combination of the bands and weights was determined for the information extraction of high-resolution remote sensing image. An improved weighted mean-variance method was proposed andused to calculatethe optimal segmentation scale. Thereafter, the best shape factor parameter and compact factor parameters were computed with the use of the control variables and the combination of the heterogeneity and homogeneity indexes. Different types of image segmentation parameters were obtained according to the surface features. The high-resolution remote sensing images were multi-scale segmented with the optimal segmentation parameters. Ahierarchical network structure was established by setting the information extraction rules to achieve object-oriented information extraction. This study presents an effective and practical method that can explain expert input judgment by reproducible quantitative measurements. Furthermore the results of this procedure may be incorporated into a classification scheme. PMID:27362762

Information Extraction of High Resolution Remote Sensing Images Based on the Calculation of Optimal Segmentation Parameters.

PubMed

Zhu, Hongchun; Cai, Lijie; Liu, Haiying; Huang, Wei

2016-01-01

Multi-scale image segmentation and the selection of optimal segmentation parameters are the key processes in the object-oriented information extraction of high-resolution remote sensing images. The accuracy of remote sensing special subject information depends on this extraction. On the basis of WorldView-2 high-resolution data, the optimal segmentation parameters methodof object-oriented image segmentation and high-resolution image information extraction, the following processes were conducted in this study. Firstly, the best combination of the bands and weights was determined for the information extraction of high-resolution remote sensing image. An improved weighted mean-variance method was proposed andused to calculatethe optimal segmentation scale. Thereafter, the best shape factor parameter and compact factor parameters were computed with the use of the control variables and the combination of the heterogeneity and homogeneity indexes. Different types of image segmentation parameters were obtained according to the surface features. The high-resolution remote sensing images were multi-scale segmented with the optimal segmentation parameters. Ahierarchical network structure was established by setting the information extraction rules to achieve object-oriented information extraction. This study presents an effective and practical method that can explain expert input judgment by reproducible quantitative measurements. Furthermore the results of this procedure may be incorporated into a classification scheme.

Reaction Wheel Disturbance Model Extraction Software - RWDMES

NASA Technical Reports Server (NTRS)

Blaurock, Carl

2009-01-01

The RWDMES is a tool for modeling the disturbances imparted on spacecraft by spinning reaction wheels. Reaction wheels are usually the largest disturbance source on a precision pointing spacecraft, and can be the dominating source of pointing error. Accurate knowledge of the disturbance environment is critical to accurate prediction of the pointing performance. In the past, it has been difficult to extract an accurate wheel disturbance model since the forcing mechanisms are difficult to model physically, and the forcing amplitudes are filtered by the dynamics of the reaction wheel. RWDMES captures the wheel-induced disturbances using a hybrid physical/empirical model that is extracted directly from measured forcing data. The empirical models capture the tonal forces that occur at harmonics of the spin rate, and the broadband forces that arise from random effects. The empirical forcing functions are filtered by a physical model of the wheel structure that includes spin-rate-dependent moments (gyroscopic terms). The resulting hybrid model creates a highly accurate prediction of wheel-induced forces. It accounts for variation in disturbance frequency, as well as the shifts in structural amplification by the whirl modes, as the spin rate changes. This software provides a point-and-click environment for producing accurate models with minimal user effort. Where conventional approaches may take weeks to produce a model of variable quality, RWDMES can create a demonstrably high accuracy model in two hours. The software consists of a graphical user interface (GUI) that enables the user to specify all analysis parameters, to evaluate analysis results and to iteratively refine the model. Underlying algorithms automatically extract disturbance harmonics, initialize and tune harmonic models, and initialize and tune broadband noise models. The component steps are described in the RWDMES user s guide and include: converting time domain data to waterfall PSDs (power spectral densities); converting PSDs to order analysis data; extracting harmonics; initializing and simultaneously tuning a harmonic model and a wheel structural model; initializing and tuning a broadband model; and verifying the harmonic/broadband/structural model against the measurement data. Functional operation is through a MATLAB GUI that loads test data, performs the various analyses, plots evaluation data for assessment and refinement of analysis parameters, and exports the data to documentation or downstream analysis code. The harmonic models are defined as specified functions of frequency, typically speed-squared. The reaction wheel structural model is realized as mass, damping, and stiffness matrices (typically from a finite element analysis package) with the addition of a gyroscopic forcing matrix. The broadband noise model is realized as a set of speed-dependent filters. The tuning of the combined model is performed using nonlinear least squares techniques. RWDMES is implemented as a MATLAB toolbox comprising the Fit Manager for performing the model extraction, Data Manager for managing input data and output models, the Gyro Manager for modifying wheel structural models, and the Harmonic Editor for evaluating and tuning harmonic models. This software was validated using data from Goodrich E wheels, and from GSFC Lunar Reconnaissance Orbiter (LRO) wheels. The validation testing proved that RWDMES has the capability to extract accurate disturbance models from flight reaction wheels with minimal user effort.

Constitutive parameter de-embedding using inhomogeneously-filled rectangular waveguides with longitudinal section modes

NASA Technical Reports Server (NTRS)

Park, A.; Dominek, A. K.

1990-01-01

Constitutive parameter extraction from S parameter data using a rectangular waveguide whose cross section is partially filled with a material sample as opposed to being completely filled was examined. One reason for studying a partially filled geometry is to analyze the effect of air gaps between the sample and fixture for the extraction of constitutive parameters. Air gaps can occur in high temperature parameter measurements when the sample was prepared at room temperature. Single port and two port measurement approaches to parameter extraction are also discussed.

Characterization, parameter estimation, and aircraft response statistics of atmospheric turbulence

NASA Technical Reports Server (NTRS)

Mark, W. D.

1981-01-01

A nonGaussian three component model of atmospheric turbulence is postulated that accounts for readily observable features of turbulence velocity records, their autocorrelation functions, and their spectra. Methods for computing probability density functions and mean exceedance rates of a generic aircraft response variable are developed using nonGaussian turbulence characterizations readily extracted from velocity recordings. A maximum likelihood method is developed for optimal estimation of the integral scale and intensity of records possessing von Karman transverse of longitudinal spectra. Formulas for the variances of such parameter estimates are developed. The maximum likelihood and least-square approaches are combined to yield a method for estimating the autocorrelation function parameters of a two component model for turbulence.

Monte Carlo modelling of Schottky diode for rectenna simulation

NASA Astrophysics Data System (ADS)

Bernuchon, E.; Aniel, F.; Zerounian, N.; Grimault-Jacquin, A. S.

2017-09-01

Before designing a detector circuit, the electrical parameters extraction of the Schottky diode is a critical step. This article is based on a Monte-Carlo (MC) solver of the Boltzmann Transport Equation (BTE) including different transport mechanisms at the metal-semiconductor contact such as image force effect or tunneling. The weight of tunneling and thermionic current is quantified according to different degrees of tunneling modelling. The I-V characteristic highlights the dependence of the ideality factor and the current saturation with bias. Harmonic Balance (HB) simulation on a rectifier circuit within Advanced Design System (ADS) software shows that considering non-linear ideality factor and saturation current for the electrical model of the Schottky diode does not seem essential. Indeed, bias independent values extracted in forward regime on I-V curve are sufficient. However, the non-linear series resistance extracted from a small signal analysis (SSA) strongly influences the conversion efficiency at low input powers.

Geothermal reservoir simulation of hot sedimentary aquifer system using FEFLOW®

NASA Astrophysics Data System (ADS)

Nur Hidayat, Hardi; Gala Permana, Maximillian

2017-12-01

The study presents the simulation of hot sedimentary aquifer for geothermal utilization. Hot sedimentary aquifer (HSA) is a conduction-dominated hydrothermal play type utilizing deep aquifer, which is heated by near normal heat flow. One of the examples of HSA is Bavarian Molasse Basin in South Germany. This system typically uses doublet wells: an injection and production well. The simulation was run for 3650 days of simulation time. The technical feasibility and performance are analysed in regards to the extracted energy from this concept. Several parameters are compared to determine the model performance. Parameters such as reservoir characteristics, temperature information and well information are defined. Several assumptions are also defined to simplify the simulation process. The main results of the simulation are heat period budget or total extracted heat energy, and heat rate budget or heat production rate. Qualitative approaches for sensitivity analysis are conducted by using five parameters in which assigned lower and higher value scenarios.

SEE rate estimation based on diffusion approximation of charge collection

NASA Astrophysics Data System (ADS)

Sogoyan, Armen V.; Chumakov, Alexander I.; Smolin, Anatoly A.

2018-03-01

The integral rectangular parallelepiped (IRPP) method remains the main approach to single event rate (SER) prediction for aerospace systems, despite the growing number of issues impairing method's validity when applied to scaled technology nodes. One of such issues is uncertainty in parameters extraction in the IRPP method, which can lead to a spread of several orders of magnitude in the subsequently calculated SER. The paper presents an alternative approach to SER estimation based on diffusion approximation of the charge collection by an IC element and geometrical interpretation of SEE cross-section. In contrast to the IRPP method, the proposed model includes only two parameters which are uniquely determined from the experimental data for normal incidence irradiation at an ion accelerator. This approach eliminates the necessity of arbitrary decisions during parameter extraction and, thus, greatly simplifies calculation procedure and increases the robustness of the forecast.

Measurement system for 3-D foot coordinates and parameters

NASA Astrophysics Data System (ADS)

Liu, Guozhong; Li, Yunhui; Wang, Boxiong; Shi, Hui; Luo, Xiuzhi

2008-12-01

The 3-D foot-shape measurement system based on laser-line-scanning principle and the model of the measurement system were presented. Errors caused by nonlinearity of CCD cameras and caused by installation can be eliminated by using the global calibration method for CCD cameras, which based on nonlinear coordinate mapping function and the optimized method. A local foot coordinate system is defined with the Pternion and the Acropodion extracted from the boundaries of foot projections. The characteristic points can thus be located and foot parameters be extracted automatically by the local foot coordinate system and the related sections. Foot measurements for about 200 participants were conducted and the measurement results for male and female participants were presented. 3-D foot coordinates and parameters measurement makes it possible to realize custom-made shoe-making and shows great prosperity in shoe design, foot orthopaedic treatment, shoe size standardization, and establishment of a feet database for consumers.

Parameter extraction of coupling-of-modes equations including coupling between two surface acoustic waves on SiO2/Cu/LiNbO3 structures

NASA Astrophysics Data System (ADS)

Huang, Yulin; Bao, Jingfu; Li, Xinyi; Zhang, Benfeng; Omori, Tatsuya; Hashimoto, Ken-ya

2018-07-01

This paper describes extraction of parameters of an extended coupling-of-modes (COM) model including coupling between Rayleigh and shear-horizontal (SH) surface acoustic waves (SAW) on the SiO2-overlay/Cu-grating/LiNbO3-substrate structure. First, dispersion characteristics of two SAWs are calculated by the finite element method (FEM), and are fitted with those given by the extended COM. Then variation of COM parameters is expressed in polynomials in terms of the SiO2 and Cu thicknesses and the rotation angle Θ of LiNbO3. Then it is shown how the optimal Θ giving the SH SAW suppression changes with the thicknesses. The result agrees well with that obtained directly by FEM. It is also shown the optimal Θ changes abruptly at certain Cu thickness, and is due to decoupling between two SAW modes.

surrkick: Black-hole kicks from numerical-relativity surrogate models

NASA Astrophysics Data System (ADS)

Gerosa, Davide; Hébert, François; Stein, Leo C.

2018-04-01

surrkick quickly and reliably extract recoils imparted to generic, precessing, black hole binaries. It uses a numerical-relativity surrogate model to obtain the gravitational waveform given a set of binary parameters, and from this waveform directly integrates the gravitational-wave linear momentum flux. This entirely bypasses the need of fitting formulae which are typically used to model black-hole recoils in astrophysical contexts.

Time-reversal imaging for classification of submerged elastic targets via Gibbs sampling and the Relevance Vector Machine.

PubMed

Dasgupta, Nilanjan; Carin, Lawrence

2005-04-01

Time-reversal imaging (TRI) is analogous to matched-field processing, although TRI is typically very wideband and is appropriate for subsequent target classification (in addition to localization). Time-reversal techniques, as applied to acoustic target classification, are highly sensitive to channel mismatch. Hence, it is crucial to estimate the channel parameters before time-reversal imaging is performed. The channel-parameter statistics are estimated here by applying a geoacoustic inversion technique based on Gibbs sampling. The maximum a posteriori (MAP) estimate of the channel parameters are then used to perform time-reversal imaging. Time-reversal implementation requires a fast forward model, implemented here by a normal-mode framework. In addition to imaging, extraction of features from the time-reversed images is explored, with these applied to subsequent target classification. The classification of time-reversed signatures is performed by the relevance vector machine (RVM). The efficacy of the technique is analyzed on simulated in-channel data generated by a free-field finite element method (FEM) code, in conjunction with a channel propagation model, wherein the final classification performance is demonstrated to be relatively insensitive to the associated channel parameters. The underlying theory of Gibbs sampling and TRI are presented along with the feature extraction and target classification via the RVM.

Parameters Identification for Photovoltaic Module Based on an Improved Artificial Fish Swarm Algorithm

PubMed Central

Wang, Hong-Hua

2014-01-01

A precise mathematical model plays a pivotal role in the simulation, evaluation, and optimization of photovoltaic (PV) power systems. Different from the traditional linear model, the model of PV module has the features of nonlinearity and multiparameters. Since conventional methods are incapable of identifying the parameters of PV module, an excellent optimization algorithm is required. Artificial fish swarm algorithm (AFSA), originally inspired by the simulation of collective behavior of real fish swarms, is proposed to fast and accurately extract the parameters of PV module. In addition to the regular operation, a mutation operator (MO) is designed to enhance the searching performance of the algorithm. The feasibility of the proposed method is demonstrated by various parameters of PV module under different environmental conditions, and the testing results are compared with other studied methods in terms of final solutions and computational time. The simulation results show that the proposed method is capable of obtaining higher parameters identification precision. PMID:25243233

Voice Quality Modelling for Expressive Speech Synthesis

PubMed Central

Socoró, Joan Claudi

2014-01-01

This paper presents the perceptual experiments that were carried out in order to validate the methodology of transforming expressive speech styles using voice quality (VoQ) parameters modelling, along with the well-known prosody (F 0, duration, and energy), from a neutral style into a number of expressive ones. The main goal was to validate the usefulness of VoQ in the enhancement of expressive synthetic speech in terms of speech quality and style identification. A harmonic plus noise model (HNM) was used to modify VoQ and prosodic parameters that were extracted from an expressive speech corpus. Perception test results indicated the improvement of obtained expressive speech styles using VoQ modelling along with prosodic characteristics. PMID:24587738

A Model for the Estimation of Hepatic Insulin Extraction After a Meal.

PubMed

Piccinini, Francesca; Dalla Man, Chiara; Vella, Adrian; Cobelli, Claudio

2016-09-01

Quantitative assessment of hepatic insulin extraction (HE) after an oral glucose challenge, e.g., a meal, is important to understand the regulation of carbohydrate metabolism. The aim of the current study is to develop a model of system for estimating HE. Nine different models, of increasing complexity, were tested on data of 204 normal subjects, who underwent a mixed meal tolerance test, with frequent measurement of plasma glucose, insulin, and C-peptide concentrations. All these models included a two-compartment model of C-peptide kinetics, an insulin secretion model, a compartmental model of insulin kinetics (with number of compartments ranging from one to three), and different HE descriptions, depending on plasma glucose and insulin. Model performances were compared on the basis of data fit, precision of parameter estimates, and parsimony criteria. The three-compartment model of insulin kinetics, coupled with HE depending on glucose concentration, showed the best fit and a good ability to precisely estimate the parameters. In addition, the model calculates basal and total indices of HE ( HE b and HE tot , respectively), and provides an index of HE sensitivity to glucose ( S G HE ). A new physiologically based HE model has been developed, which allows an improved quantitative description of glucose regulation. The use of the new model provides an in-depth description of insulin kinetics, thus enabling a better understanding of a given subject's metabolic state.

Radiator Enhanced Geothermal System - A Revolutionary Method for Extracting Geothermal Energy

NASA Astrophysics Data System (ADS)

Karimi, S.; Marsh, B. D.; Hilpert, M.

2017-12-01

A new method of extracting geothermal energy, the Radiator Enhanced Geothermal System (RAD-EGS) has been developed. RAD-EGS attempts to mimic natural hydrothermal systems by 1) generating a vertical vane of artificially produced high porosity/permeability material deep in a hot sedimentary aquifer, 2) injecting water at surface temperatures to the bottom of the vane, where the rock is the hottest, 3) extracting super-heated water at the top of the vane. The novel RAD-EGS differs greatly from the currently available Enhanced Geothermal Systems in vane orientation, determined in the governing local crustal stress field by Shmax and Sl (meaning it is vertical), and in the vane location in a hot sedimentary aquifer, which naturally increases the longevity of the system. In this study, we explore several parameters regimes affecting the water temperature in the extraction well, keeping in mind that the minimum temperature of the extracted water has to be 150 °C in order for a geothermal system to be commercially viable. We used the COMSOL finite element package to simulate coupled heat and fluid transfer within the RAD-EGS model. The following geologic layers from top to bottom are accounted for in the model: i) confining upper layer, ii) hot sedimentary aquifer, and iii) underlying basement rock. The vane is placed vertically within the sedimentary aquifer. An injection well and an extraction well are also included in the simulation. We tested the model for a wide range of various parameters including background heat flux, thickness of geologic layers, geometric properties of the vane, diameter and location of the wells, fluid flow within the wells, regional hydraulic gradient, and permeability and porosity of the layers. The results show that among the aforementioned parameters, background heat flux and the depth of vane emplacement are highly significant in determining the level of commercial viability of the geothermal system. These results indicate that for the terrains with relatively high background heat flux or for vanes located in relatively deep layers, the RAD-EGS can produce economic geothermal energy for more than 40 years. Moreover, these simulations show that the geothermal vane design with the injection well at the bottom and production well at the top of the vane greatly contributes to the longevity of the system.

Double β-decay nuclear matrix elements for the A=48 and A=58 systems

NASA Astrophysics Data System (ADS)

Skouras, L. D.; Vergados, J. D.

1983-11-01

The nuclear matrix elements entering the double β decays of the 48Ca-48Ti and 58Ni-58Fe systems have been calculated using a realistic two nucleon interaction and realistic shell model spaces. Effective transition operators corresponding to a variety of gauge theory models have been considered. The stability of such matrix elements against variations of the nuclear parameters is examined. Appropriate lepton violating parameters are extracted from the A=48 data and predictions are made for the lifetimes of the positron decays of the A=58 system. RADIOACTIVITY Double β decay. Gauge theories. Lepton nonconservation. Neutrino mass. Shell model calculations.

Nitric Acid and Water Extraction by T2EHDGA in n -Dodecane

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

Campbell, Emily L.; Holfeltz, Vanessa E.; Hall, Gabriel B.

Liquid-liquid distribution behavior of nitric acid (HNO3) and water by a diglycolamide ligand, N,N,N',N'-tetra-2-ethylhexyldiglycolamide (T2EHDGA) into n-dodecane diluent was investigated. Spectroscopic FTIR and NMR characterization of the organic extraction solutions indicate T2EHDGA carbonyl coordinates HNO3 and progressively aggregates at high acid conditions. Water extraction increases in the presence of HNO3. The experimentally observed distribution of HNO3 was modeled using the computer program, SXLSQI. The results indicated that the formation of two organic phase species—HNO3·T2EHDGA and (HNO3)2·T2EHDGA—satisfactory describes the acid transport behavior. Temperature dependent solvent extraction studies allowed for determination of thermodynamic extraction constants and ΔH and ΔS parameters for themore » corresponding extractive processes.« less

Intelligent person identification system using stereo camera-based height and stride estimation

NASA Astrophysics Data System (ADS)

Ko, Jung-Hwan; Jang, Jae-Hun; Kim, Eun-Soo

2005-05-01

In this paper, a stereo camera-based intelligent person identification system is suggested. In the proposed method, face area of the moving target person is extracted from the left image of the input steros image pair by using a threshold value of YCbCr color model and by carrying out correlation between the face area segmented from this threshold value of YCbCr color model and the right input image, the location coordinates of the target face can be acquired, and then these values are used to control the pan/tilt system through the modified PID-based recursive controller. Also, by using the geometric parameters between the target face and the stereo camera system, the vertical distance between the target and stereo camera system can be calculated through a triangulation method. Using this calculated vertical distance and the angles of the pan and tilt, the target's real position data in the world space can be acquired and from them its height and stride values can be finally extracted. Some experiments with video images for 16 moving persons show that a person could be identified with these extracted height and stride parameters.

Model-based analysis of fatigued human knee extensors : Effects of isometrically induced fatigue on Hill-type model parameters and ballistic contractions.

PubMed

Penasso, Harald; Thaller, Sigrid

2018-05-05

This study investigated the effect of isometrically induced fatigue on Hill-type muscle model parameters and related task-dependent effects. Parameter identification methods were used to extract fatigue-related parameter trends from isometric and ballistic dynamic maximum voluntary knee extensions. Nine subjects, who completed ten fatiguing sets, each consisting of nine 3 s isometric maximum voluntary contractions with 3 s rest plus two ballistic contractions with different loads, were analyzed. Only at the isometric task, the identified optimized model parameter values of muscle activation rate and maximum force generating capacity of the contractile element decreased from [Formula: see text] to [Formula: see text] Hz and from [Formula: see text] to [Formula: see text] N, respectively. For all tasks, the maximum efficiency of the contractile element, mathematically related to the curvature of the force-velocity relation, increased from [Formula: see text] to [Formula: see text]. The model parameter maximum contraction velocity decreased from [Formula: see text] to [Formula: see text] m/s and the stiffness of the serial elastic element from [Formula: see text] to [Formula: see text] N/mm. Thus, models of fatigue should consider fatigue dependencies in active as well as in passive elements, and muscle activation dynamics should account for the task dependency of fatigue.

Evaluation of different digital elevation models for analyzing drainage morphometric parameters in a mountainous terrain: a case study of the Supin-Upper Tons Basin, Indian Himalayas.

PubMed

Das, Sayantan; Patel, Priyank Pravin; Sengupta, Somasis

2016-01-01

With myriad geospatial datasets now available for terrain information extraction and particularly streamline demarcation, there arises questions regarding the scale, accuracy and sensitivity of the initial dataset from which these aspects are derived, as they influence all other parameters computed subsequently. In this study, digital elevation models (DEM) derived from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER V2), Shuttle Radar Topography Mission (SRTM V4, C-Band, 3 arc-second), Cartosat -1 (CartoDEM 1.0) and topographical maps (R.F. 1:250,000 and 1:50,000), have been used to individually extract and analyze the relief, surface, size, shape and texture properties of a mountainous drainage basin. Nestled inside a mountainous setting, the basin is a semi-elongated one with high relief ratio (>90), steep slopes (25°-30°) and high drainage density (>3.5 km/sq km), as computed from the different DEMs. The basin terrain and stream network is extracted from each DEM, whose morphometric attributes are compared with the surveyed stream networks present in the topographical maps, with resampling of finer DEM datasets to coarser resolutions, to reduce scale-implications during the delineation process. Ground truth verifications for altitudinal accuracy have also been done by a GPS survey. DEMs derived from the 1:50,000 topographical map and ASTER GDEM V2 data are found to be more accurate and consistent in terms of absolute accuracy, than the other generated or available DEM data products, on basis of the morphometric parameters extracted from each. They also exhibit a certain degree of proximity to the surveyed topographical map.

Nonlinear integral equations for the sausage model

NASA Astrophysics Data System (ADS)

Ahn, Changrim; Balog, Janos; Ravanini, Francesco

2017-08-01

The sausage model, first proposed by Fateev, Onofri, and Zamolodchikov, is a deformation of the O(3) sigma model preserving integrability. The target space is deformed from the sphere to ‘sausage’ shape by a deformation parameter ν. This model is defined by a factorizable S-matrix which is obtained by deforming that of the O(3) sigma model by a parameter λ. Clues for the deformed sigma model are provided by various UV and IR information through the thermodynamic Bethe ansatz (TBA) analysis based on the S-matrix. Application of TBA to the sausage model is, however, limited to the case of 1/λ integer where the coupled integral equations can be truncated to a finite number. In this paper, we propose a finite set of nonlinear integral equations (NLIEs), which are applicable to generic value of λ. Our derivation is based on T-Q relations extracted from the truncated TBA equations. For a consistency check, we compute next-leading order corrections of the vacuum energy and extract the S-matrix information in the IR limit. We also solved the NLIE both analytically and numerically in the UV limit to get the effective central charge and compared with that of the zero-mode dynamics to obtain exact relation between ν and λ. Dedicated to the memory of Petr Petrovich Kulish.

Analysis of dark energy models in DGP braneworld

NASA Astrophysics Data System (ADS)

Jawad, Abdul

2015-12-01

In this paper, we reconsider the accelerated expansion phenomenon in the DGP braneworld scenario which leads to an accelerated universe without cosmological constant or other form of dark energy for the positive branch (ɛ= +1) which is not more attractive model. Thus, we assume the DGP braneworld scenario with (ɛ= -1) and also interacting Hubble and event horizons pilgrim dark energy models. We extract various cosmological parameters in this scenario and displayed our results with respect to redshift parameter. It is found that the ranges of Hubble parameter are coincided with observational results. The equation of state parameter lies within the suggested ranges of different observational schemes. The squared speed of sound shows stability for all present models in DGP braneworld scenario. The ω_{\\vartheta}-ω'_{\\vartheta} planes lie in the range (ω_{\\vartheta}=-1.13^{+0.24}_{-0.25},ω'_{\\vartheta}<1.32) which has been obtained through different observational schemes. It is remarked that our results of various cosmological parameters shows consistency with different observational data like Planck, WP, BAO, H0 and SNLS.

Optimization of β-cyclodextrin-based flavonol extraction from apple pomace using response surface methodology.

PubMed

Parmar, Indu; Sharma, Sowmya; Rupasinghe, H P Vasantha

2015-04-01

The present study investigated five cyclodextrins (CDs) for the extraction of flavonols from apple pomace powder and optimized β-CD based extraction of total flavonols using response surface methodology. A 2(3) central composite design with β-CD concentration (0-5 g 100 mL(-1)), extraction temperature (20-72 °C), extraction time (6-48 h) and second-order quadratic model for the total flavonol yield (mg 100 g(-1) DM) was selected to generate the response surface curves. The optimal conditions obtained were: β-CD concentration, 2.8 g 100 mL(-1); extraction temperature, 45 °C and extraction time, 25.6 h that predicted the extraction of 166.6 mg total flavonols 100 g(-1) DM. The predicted amount was comparable to the experimental amount of 151.5 mg total flavonols 100 g(-1) DM obtained from optimal β-CD based parameters, thereby giving a low absolute error and adequacy of fitted model. In addition, the results from optimized extraction conditions showed values similar to those obtained through previously established solvent based sonication assisted flavonol extraction procedure. To the best of our knowledge, this is the first study to optimize aqueous β-CD based flavonol extraction which presents an environmentally safe method for value-addition to under-utilized bio resources.

Extended behavioural modelling of FET and lattice-mismatched HEMT devices

NASA Astrophysics Data System (ADS)

Khawam, Yahya; Albasha, Lutfi

2017-07-01

This study presents an improved large signal model that can be used for high electron mobility transistors (HEMTs) and field effect transistors using measurement-based behavioural modelling techniques. The steps for accurate large and small signal modelling for transistor are also discussed. The proposed DC model is based on the Fager model since it compensates between the number of model's parameters and accuracy. The objective is to increase the accuracy of the drain-source current model with respect to any change in gate or drain voltages. Also, the objective is to extend the improved DC model to account for soft breakdown and kink effect found in some variants of HEMT devices. A hybrid Newton's-Genetic algorithm is used in order to determine the unknown parameters in the developed model. In addition to accurate modelling of a transistor's DC characteristics, the complete large signal model is modelled using multi-bias s-parameter measurements. The way that the complete model is performed is by using a hybrid multi-objective optimisation technique (Non-dominated Sorting Genetic Algorithm II) and local minimum search (multivariable Newton's method) for parasitic elements extraction. Finally, the results of DC modelling and multi-bias s-parameters modelling are presented, and three-device modelling recommendations are discussed.

Evaluation of Fenugreek (Trigonella foenum-graceum L.), Effects Seeds Extract on Insulin Resistance in Women with Polycystic Ovarian Syndrome

PubMed Central

Hassanzadeh Bashtian, Maryam; Emami, Seyed Ahmad; Mousavifar, Nezhat; Esmaily, Habib Allah; Mahmoudi, Mahmoud; Mohammad Poor, Amir Hooshang

2013-01-01

PCOS (Polycystic Ovarian Syndrome) is associated with insulin resistance, obesity and disorders of lipid metabolism as well as infertility. Fenugreek seeds extract is successfully used in lowering blood glucose. Metformin has also the same effect but in a different way. The aim of this study was the assessment of fenugreek effects on insulin resistance in women with PCOS. This was a prospective randomized, double-blind, placebo-controlled trial. The study was conducted at the Montaserieh Hospital in Mashhad University of Medical Sciences, Mashhad, Khorasan Razavi Province, Iran. The patient population included 58 oligo-anovulatory PCOS women with typical ovaries. Women were randomly allocated to receive hydroalcoholic extract of fenugreek seeds in capsules with metformin (n = 30) or placebo capsules with metformin (n = 28) and were assessed before and every 4 weeks within a treatment period of 8 weeks. Menstrual disturbance and metabolic parameters (markers of insulin resistance and hormonal parameters) were measured. Insulin resistance based on HOMA-IR (homeostasis model assessment for insulin resistance) model was not significantly different between two groups. Ultrasound scans were performed before and at the end of 8 weeks treatment with significant decrease in PAO (polycystic appearing ovaries) in group 1 (p = 0/01). Adjuvant therapy to the fenugreek seeds extract (with metformin) in PCOS women improved the sonographic results and menstrual cyclicity. PMID:24250624

Inferring the photometric and size evolution of galaxies from image simulations. I. Method

NASA Astrophysics Data System (ADS)

Carassou, Sébastien; de Lapparent, Valérie; Bertin, Emmanuel; Le Borgne, Damien

2017-09-01

Context. Current constraints on models of galaxy evolution rely on morphometric catalogs extracted from multi-band photometric surveys. However, these catalogs are altered by selection effects that are difficult to model, that correlate in non trivial ways, and that can lead to contradictory predictions if not taken into account carefully. Aims: To address this issue, we have developed a new approach combining parametric Bayesian indirect likelihood (pBIL) techniques and empirical modeling with realistic image simulations that reproduce a large fraction of these selection effects. This allows us to perform a direct comparison between observed and simulated images and to infer robust constraints on model parameters. Methods: We use a semi-empirical forward model to generate a distribution of mock galaxies from a set of physical parameters. These galaxies are passed through an image simulator reproducing the instrumental characteristics of any survey and are then extracted in the same way as the observed data. The discrepancy between the simulated and observed data is quantified, and minimized with a custom sampling process based on adaptive Markov chain Monte Carlo methods. Results: Using synthetic data matching most of the properties of a Canada-France-Hawaii Telescope Legacy Survey Deep field, we demonstrate the robustness and internal consistency of our approach by inferring the parameters governing the size and luminosity functions and their evolutions for different realistic populations of galaxies. We also compare the results of our approach with those obtained from the classical spectral energy distribution fitting and photometric redshift approach. Conclusions: Our pipeline infers efficiently the luminosity and size distribution and evolution parameters with a very limited number of observables (three photometric bands). When compared to SED fitting based on the same set of observables, our method yields results that are more accurate and free from systematic biases.

Comparison of four kinds of extraction techniques and kinetics of microwave-assisted extraction of vanillin from Vanilla planifolia Andrews.

PubMed

Dong, Zhizhe; Gu, Fenglin; Xu, Fei; Wang, Qinghuang

2014-04-15

Vanillin yield, microscopic structure, antioxidant activity and overall odour of vanilla extracts obtained by different treatments were investigated. MAE showed the strongest extraction power, shortest time and highest antioxidant activity. Maceration gave higher vanillin yields than UAE and PAE, similar antioxidant activity with UAE, but longer times than UAE and PAE. Overall odour intensity of different vanilla extracts obtained by UAE, PAE and MAE were similar, while higher than maceration extracts. Then, powered vanilla bean with a sample/solvent ratio of 4 g/100 mL was selected as the optimum condition for MAE. Next, compared with other three equations, two-site kinetic equation with lowest RMSD and highest R²(adj) was shown to be more suitable in describing the kinetics of vanillin extraction. By fitting the parameters C(eq), k₁, k₂, and f, a kinetics model was constructed to describe vanillin extraction in terms of irradiation power, ethanol concentration, and extraction time. Copyright © 2013 Elsevier Ltd. All rights reserved.

A Real-time Breakdown Prediction Method for Urban Expressway On-ramp Bottlenecks

NASA Astrophysics Data System (ADS)

Ye, Yingjun; Qin, Guoyang; Sun, Jian; Liu, Qiyuan

2018-01-01

Breakdown occurrence on expressway is considered to relate with various factors. Therefore, to investigate the association between breakdowns and these factors, a Bayesian network (BN) model is adopted in this paper. Based on the breakdown events identified at 10 urban expressways on-ramp in Shanghai, China, 23 parameters before breakdowns are extracted, including dynamic environment conditions aggregated with 5-minutes and static geometry features. Different time periods data are used to predict breakdown. Results indicate that the models using 5-10 min data prior to breakdown performs the best prediction, with the prediction accuracies higher than 73%. Moreover, one unified model for all bottlenecks is also built and shows reasonably good prediction performance with the classification accuracy of breakdowns about 75%, at best. Additionally, to simplify the model parameter input, the random forests (RF) model is adopted to identify the key variables. Modeling with the selected 7 parameters, the refined BN model can predict breakdown with adequate accuracy.

Plantago maxima leaves extract inhibits adipogenic action of a high-fat diet in female Wistar rats.

PubMed

Tinkov, Alexey A; Nemereshina, Olga N; Popova, Elizaveta V; Polyakova, Valentina S; Gritsenko, Viktor A; Nikonorov, Alexandr A

2014-04-01

The primary objective of this study is to investigate the content of biologically active compounds producing an antioxidant effect in Plantago maxima and their influence on main mechanisms of dietary obesity development. Biologically active compounds in P. maxima were tested using paper chromatography. In in vivo experiment, high-fat-fed Wistar rats obtained P. maxima water extract for 3 months. Morphometric parameters, weight gain, serum adipokines, and cytokines, as well as oxidative stress biomarkers in rats’ tissues were evaluated. Gut microflora was also examined. Plantago maxima leaves used in the experiment contained significant amount of flavonoids, iridoids, phenol carboxylic acids, and tannins and ascorbic acid. Our in vivo experiment data demonstrate that P. maxima water extract prevents excessive adiposity in a diet-induced model. P. maxima consumption reduced serum leptin (twofold), macrophage chemoattractant protein-1 (sevenfold), tumornecrosis factor-α (25%), and interleukine-6 (26%) levels. P. maxima water extract decreased adipose tissue oxidative stress biomarkers in rats fed a high-fat diet. In addition, increased bacterial growth in the diet-induced obesity model was reversed by the P. maxima extract treatment. Plantago maxima water extract possessed antiadipogenic, antidiabetic, antiinflammatory, antioxidant activity, and normalized gut microflora in a rat model of diet-induced excessive adiposity due to a high content of biologically active compounds.

Optimization of the trienzyme extraction for the microbiological assay of folate in vegetables.

PubMed

Chen, Liwen; Eitenmiller, Ronald R

2007-05-16

Response surface methodology was applied to optimize the trienzyme digestion for the extraction of folate from vegetables. Trienzyme extraction is a combined enzymatic digestion by protease, alpha-amylase, and conjugase (gamma-glutamyl hydrolase) to liberate the carbohydrate and protein-bound folates from food matrices for total folate analysis. It is the extraction method used in AOAC Official Method 2004.05 for assay of total folate in cereal grain products. Certified reference material (CRM) 485 mixed vegetables was used to represent the matrix of vegetables. Regression and ridge analysis were performed by statistical analysis software. The predicted second-order polynomial model was adequate (R2 = 0.947), without significant lack of fit (p > 0.1). Both protease and alpha-amylase have significant effects on the extraction. Ridge analysis gave an optimum trienzyme digestion time: Pronase, 1.5 h; alpha-amylase, 1.5 h; and conjugase, 3 h. The experimental value for CRM 485 under this optimum digestion was close to the predicted value from the model, confirming the validity and adequacy of the model. The optimized trienzyme digestion condition was applied to five vegetables and yielded higher folate levels than the trienzyme digestion parameters employed in AOAC Official Method 2004.05.

Physics-based forecasting of induced seismicity at Groningen gas field, the Netherlands

NASA Astrophysics Data System (ADS)

Dempsey, David; Suckale, Jenny

2017-08-01

Earthquakes induced by natural gas extraction from the Groningen reservoir, the Netherlands, put local communities at risk. Responsible operation of a reservoir whose gas reserves are of strategic importance to the country requires understanding of the link between extraction and earthquakes. We synthesize observations and a model for Groningen seismicity to produce forecasts for felt seismicity (M > 2.5) in the period February 2017 to 2024. Our model accounts for poroelastic earthquake triggering and rupture on the 325 largest reservoir faults, using an ensemble approach to model unknown heterogeneity and replicate earthquake statistics. We calculate probability distributions for key model parameters using a Bayesian method that incorporates the earthquake observations with a nonhomogeneous Poisson process. Our analysis indicates that the Groningen reservoir was not critically stressed prior to the start of production. Epistemic uncertainty and aleatoric uncertainty are incorporated into forecasts for three different future extraction scenarios. The largest expected earthquake was similar for all scenarios, with a 5% likelihood of exceeding M 4.0.

Recent advances in continuum plasticity: phenomenological modeling and experimentation using X-ray diffraction

NASA Astrophysics Data System (ADS)

Edmiston, John Kearney

This work explores the field of continuum plasticity from two fronts. On the theory side, we establish a complete specification of a phenomenological theory of plasticity for single crystals. The model serves as an alternative to the popular crystal plasticity formulation. Such a model has been previously proposed in the literature; the new contribution made here is the constitutive framework and resulting simulations. We calibrate the model to available data and use a simple numerical method to explore resulting predictions in plane strain boundary value problems. Results show promise for further investigation of the plasticity model. Conveniently, this theory comes with a corresponding experimental tool in X-ray diffraction. Recent advances in hardware technology at synchrotron sources have led to an increased use of the technique for studies of plasticity in the bulk of materials. The method has been successful in qualitative observations of material behavior, but its use in quantitative studies seeking to extract material properties is open for investigation. Therefore in the second component of the thesis several contributions are made to synchrotron X-ray diffraction experiments, in terms of method development as well as the quantitative reporting of constitutive parameters. In the area of method development, analytical tools are developed to determine the available precision of this type of experiment—a crucial aspect to determine if the method is to be used for quantitative studies. We also extract kinematic information relating to intragranular inhomogeneity which is not accessible with traditional methods of data analysis. In the area of constitutive parameter identification, we use the method to extract parameters corresponding to the proposed formulation of plasticity for a titanium alloy (HCP) which is continuously sampled by X-ray diffraction during uniaxial extension. These results and the lessons learned from the efforts constitute early reporting of the quantitative profitability of undertaking such a line of experimentation for the study of plastic deformation processes.

Hyperspectral imaging technique for determination of pork freshness attributes

NASA Astrophysics Data System (ADS)

Li, Yongyu; Zhang, Leilei; Peng, Yankun; Tang, Xiuying; Chao, Kuanglin; Dhakal, Sagar

2011-06-01

Freshness of pork is an important quality attribute, which can vary greatly in storage and logistics. The specific objectives of this research were to develop a hyperspectral imaging system to predict pork freshness based on quality attributes such as total volatile basic-nitrogen (TVB-N), pH value and color parameters (L*,a*,b*). Pork samples were packed in seal plastic bags and then stored at 4°C. Every 12 hours. Hyperspectral scattering images were collected from the pork surface at the range of 400 nm to 1100 nm. Two different methods were performed to extract scattering feature spectra from the hyperspectral scattering images. First, the spectral scattering profiles at individual wavelengths were fitted accurately by a three-parameter Lorentzian distribution (LD) function; second, reflectance spectra were extracted from the scattering images. Partial Least Square Regression (PLSR) method was used to establish prediction models to predict pork freshness. The results showed that the PLSR models based on reflectance spectra was better than combinations of LD "parameter spectra" in prediction of TVB-N with a correlation coefficient (r) = 0.90, a standard error of prediction (SEP) = 7.80 mg/100g. Moreover, a prediction model for pork freshness was established by using a combination of TVB-N, pH and color parameters. It could give a good prediction results with r = 0.91 for pork freshness. The research demonstrated that hyperspectral scattering technique is a valid tool for real-time and nondestructive detection of pork freshness.

Optimization of ultrasound assisted extraction of bioactive components from brown seaweed Ascophyllum nodosum using response surface methodology.

PubMed

Kadam, Shekhar U; Tiwari, Brijesh K; Smyth, Thomas J; O'Donnell, Colm P

2015-03-01

The objective of this study was to investigate the effect of key extraction parameters of extraction time (5-25 min), acid concentration (0-0.06 M HCl) and ultrasound amplitude (22.8-114 μm) on yields of bioactive compounds (total phenolics, fucose and uronic acid) from Ascophyllumnodosum. Response surface methodology was employed to optimize the extraction variables for bioactive compounds' yield. A second order polynomial model was fitted well to the extraction experimental data with (R(2)>0.79). Extraction yields of 143.12 mgGAE/gdb, 87.06 mg/gdb and 128.54 mg/gdb were obtained for total phenolics, fucose and uronic acid respectively at optimized extraction conditions of extraction time (25 min), acid concentration (0.03 M HCl) and ultrasonic amplitude (114 μm). Mass spectroscopy analysis of extracts show that ultrasound enhances the extraction of high molecular weight phenolic compounds from A. nodosum. This study demonstrates that ultrasound assisted extraction (UAE) can be employed to enhance extraction of bioactive compounds from seaweed. Copyright © 2014 Elsevier B.V. All rights reserved.

The anti-allergic activity of Cymbopogon citratus is mediated via inhibition of nuclear factor kappa B (Nf-Κb) activation.

PubMed

Santos Serafim Machado, Marta; Ferreira Silva, Hugo Bernardino; Rios, Raimon; Pires de Oliveira, Anaque; Vilany Queiroz Carneiro, Noma; Santos Costa, Ryan; Santos Alves, William; Meneses Souza, Fabio-Luis; da Silva Velozo, Eudes; Alves de Souza, Silvana; Sarmento Silva, Tania Maria; Silva, Maria Lenise; Pontes-de-Carvalho, Lain Carlos; Alcântara-Neves, Neuza Maria; Figueiredo, Camila Alexandrina

2015-06-06

The prevalence of allergic diseases such as asthma has significantly increased worldwide, making it a public health concern. There is an urgent need for new anti-inflammatory agents with selective pharmacology and lower toxicity. Plant extracts have been used for centuries in traditional medicine to alleviate inflammatory diseases. In this work, we evaluated the anti-allergic activity of Cymbopogon citratus (Cy), a medicinal herb used by folk medicine to treat asthma. We used a murine model of respiratory allergy to the mite Blomia tropicalis (Bt) and evaluated certain parameters known to be altered in this model. A/J mice were sensitized (100 μg/animal s.c.) and challenged (10 μg/animal i.n.) with Bt mite extract and treated with 60, 120 or 180 mg/kg of Cy standardized hexane extract. The parameters evaluated included: cellular infiltrate in bronchoalveolar lavage (BAL); eosinophil peroxidase activity (EPO); histopathological examination of the lung; serum levels of specific IgE, IgG1 and IgG2a; Th2 cytokine concentrations in BAL and expression of NF-κB. Our results showed that oral administration of a Cy hexane extract (especially 180 mg/Kg) reduced the numbers of leukocytes/eosinophils in BAL; the eosinophil peroxidase activity in BAL; the infiltration of leukocytes in lung tissue; the production of mucus in the respiratory tract; the level of IL-4 in BAL and the nuclear expression of NF-κB. The results presented demonstrate the potential of the Cy hexane extract to modulate allergic asthma; this extract may be an alternative future approach to treat this pathology.

Object-oriented classification of drumlins from digital elevation models

NASA Astrophysics Data System (ADS)

Saha, Kakoli

Drumlins are common elements of glaciated landscapes which are easily identified by their distinct morphometric characteristics including shape, length/width ratio, elongation ratio, and uniform direction. To date, most researchers have mapped drumlins by tracing contours on maps, or through on-screen digitization directly on top of hillshaded digital elevation models (DEMs). This paper seeks to utilize the unique morphometric characteristics of drumlins and investigates automated extraction of the landforms as objects from DEMs by Definiens Developer software (V.7), using the 30 m United States Geological Survey National Elevation Dataset DEM as input. The Chautauqua drumlin field in Pennsylvania and upstate New York, USA was chosen as a study area. As the study area is huge (approximately covers 2500 sq.km. of area), small test areas were selected for initial testing of the method. Individual polygons representing the drumlins were extracted from the elevation data set by automated recognition, using Definiens' Multiresolution Segmentation tool, followed by rule-based classification. Subsequently parameters such as length, width and length-width ratio, perimeter and area were measured automatically. To test the accuracy of the method, a second base map was produced by manual on-screen digitization of drumlins from topographic maps and the same morphometric parameters were extracted from the mapped landforms using Definiens Developer. Statistical comparison showed a high agreement between the two methods confirming that object-oriented classification for extraction of drumlins can be used for mapping these landforms. The proposed method represents an attempt to solve the problem by providing a generalized rule-set for mass extraction of drumlins. To check that the automated extraction process was next applied to a larger area. Results showed that the proposed method is as successful for the bigger area as it was for the smaller test areas.

Physiological basis for noninvasive skin cancer diagnosis using diffuse reflectance spectroscopy

NASA Astrophysics Data System (ADS)

Zhang, Yao; Markey, Mia K.; Tunnell, James W.

2017-02-01

Diffuse reflectance spectroscopy offers a noninvasive, fast, and low-cost alternative to visual screening and biopsy for skin cancer diagnosis. We have previously acquired reflectance spectra from 137 lesions in 76 patients and determined the capability of spectral diagnosis using principal component analysis (PCA). However, it is not well elucidated why spectral analysis enables tissue classification. To provide the physiological basis, we used the Monte Carlo look-up table (MCLUT) model to extract physiological parameters from those clinical data. The MCLUT model results in the following physiological parameters: oxygen saturation, hemoglobin concentration, melanin concentration, vessel radius, and scattering parameters. Physiological parameters show that cancerous skin tissue has lower scattering and larger vessel radii, compared to normal tissue. These results demonstrate the potential of diffuse reflectance spectroscopy for detection of early precancerous changes in tissue. In the future, a diagnostic algorithm that combines these physiological parameters could be enable non-invasive diagnosis of skin cancer.

Full extraction methods to retrieve effective refractive index and parameters of a bianisotropic metamaterial based on material dispersion models

NASA Astrophysics Data System (ADS)

Hsieh, Feng-Ju; Wang, Wei-Chih

2012-09-01

This paper discusses two improved methods in retrieving effective refractive indices, impedances, and material properties, such as permittivity (ɛ) and permeability (μ), of metamaterials. The first method modified from Kong's retrieval method allows effective constitutive parameters over all frequencies including the anti-resonant band, where imaginary parts of ɛ or μ are negative, to be solved. The second method is based on genetic algorithms and optimization of properly defined goal functions to retrieve parameters of the Drude and Lorentz dispersion models. Equations of effective refractive index and impedance at any reference planes are derived. Split ring resonator-rod based metamaterials operating in terahertz frequencies are designed and investigated with proposed methods. Retrieved material properties and parameters are used to regenerate S-parameters and compared with simulation results generated by cst microwave studio software.

A structured analysis of uncertainty surrounding modeled impacts of groundwater-extraction rules

NASA Astrophysics Data System (ADS)

Guillaume, Joseph H. A.; Qureshi, M. Ejaz; Jakeman, Anthony J.

2012-08-01

Integrating economic and groundwater models for groundwater-management can help improve understanding of trade-offs involved between conflicting socioeconomic and biophysical objectives. However, there is significant uncertainty in most strategic decision-making situations, including in the models constructed to represent them. If not addressed, this uncertainty may be used to challenge the legitimacy of the models and decisions made using them. In this context, a preliminary uncertainty analysis was conducted of a dynamic coupled economic-groundwater model aimed at assessing groundwater extraction rules. The analysis demonstrates how a variety of uncertainties in such a model can be addressed. A number of methods are used including propagation of scenarios and bounds on parameters, multiple models, block bootstrap time-series sampling and robust linear regression for model calibration. These methods are described within the context of a theoretical uncertainty management framework, using a set of fundamental uncertainty management tasks and an uncertainty typology.

Oil shale extraction using super-critical extraction

NASA Technical Reports Server (NTRS)

Compton, L. E. (Inventor)

1983-01-01

Significant improvement in oil shale extraction under supercritical conditions is provided by extracting the shale at a temperature below 400 C, such as from about 250 C to about 350 C, with a solvent having a Hildebrand solubility parameter within 1 to 2 Hb of the solubility parameter for oil shale bitumen.

Post-audits of Three Groundwater Models for Evaluating Plume Containment

NASA Astrophysics Data System (ADS)

Andersen, P. F.

2003-12-01

Groundwater extraction systems were designed using numerical models at three sites within a U.S. Army Ammunition Plant in Tennessee. Each site, and hence model, has unique qualities such as boundary conditions, extensiveness of the contaminant plume, and quantity and quality of hydrogeologic data. Performance of each of these extraction systems has been evaluated throughout their operation, providing an opportunity to perform post-audits on the accuracy of the groundwater models that were used in their design. Areas of comparison between the models and the observed response in the natural systems include hydraulic head, drawdown, horizontal and vertical gradients, and extent of capture zones. The results of the post-audits show the importance of using all available data in the construction and calibration of the models, the importance of having sufficient data, and the critical nature of an accurate conceptual model. The post-audits also show that although it may be possible to assess the accuracy of the model predictions, it is often not possible to explain the reasons for discrepancies between predicted and observed results. From a practical perspective, parameter uncertainty is important to account for in the development of the models and subsequent design of the extraction systems.

Technical Parameters Modeling of a Gas Probe Foaming Using an Active Experimental Type Research

NASA Astrophysics Data System (ADS)

Tîtu, A. M.; Sandu, A. V.; Pop, A. B.; Ceocea, C.; Tîtu, S.

2018-06-01

The present paper deals with a current and complex topic, namely - a technical problem solving regarding the modeling and then optimization of some technical parameters related to the natural gas extraction process. The study subject is to optimize the gas probe sputtering using experimental research methods and data processing by regular probe intervention with different sputtering agents. This procedure makes that the hydrostatic pressure to be reduced by the foam formation from the water deposit and the scrubbing agent which can be removed from the surface by the produced gas flow. The probe production data was analyzed and the so-called candidate for the research itself emerged. This is an extremely complex study and it was carried out on the field works, finding that due to the severe gas field depletion the wells flow decreases and the start of their loading with deposit water, was registered. It was required the regular wells foaming, to optimize the daily production flow and the disposal of the wellbore accumulated water. In order to analyze the process of natural gas production, the factorial experiment and other methods were used. The reason of this choice is that the method can offer very good research results with a small number of experimental data. Finally, through this study the extraction process problems were identified by analyzing and optimizing the technical parameters, which led to a quality improvement of the extraction process.

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

Crouzet, N.; McCullough, P. R.; Long, D.

Spectroscopy during planetary transits is a powerful tool to probe exoplanet atmospheres. We present the near-infrared transit spectroscopy of XO-2b obtained with Hubble Space Telescope NICMOS. Uniquely for NICMOS transit spectroscopy, a companion star of similar properties to XO-2 is present in the field of view. We derive improved star and planet parameters through a photometric white-light analysis. We show a clear correlation of the spectrum noise with instrumental parameters, in particular the angle of the spectral trace on the detector. An MCMC method using a decorrelation from instrumental parameters is used to extract the planetary spectrum. Spectra derived independentlymore » from each of the three visits have an rms of 430, 510, and 1000 ppm, respectively. The same analysis is performed on the companion star after numerical injection of a transit with a depth constant at all wavelengths. The extracted spectra exhibit residuals of similar amplitude as for XO-2, which represent the level of remaining NICMOS systematics. This shows that extracting planetary spectra is at the limit of NICMOS's capability. We derive a spectrum for the planet XO-2b using the companion star as a reference. The derived spectrum can be represented by a theoretical model including atmospheric water vapor or by a flat spectrum model. We derive a 3{sigma} upper limit of 1570 ppm on the presence of water vapor absorption in the atmosphere of XO-2b. In the Appendix, we perform a similar analysis for the gas giant planet XO-1b.« less

Accuracy of embedded fragment calculation for evaluating electron interactions in mixed valence magnetic systems: study of 2e-reduced lindqvist polyoxometalates.

PubMed

Suaud, Nicolas; López, Xavier; Ben Amor, Nadia; Bandeira, Nuno A G; de Graaf, Coen; Poblet, Josep M

2015-02-10

Accurate quantum chemical calculations on real-world magnetic systems are challenging, the inclusion of electron correlation being the bottleneck of such task. One method proposed to overcome this difficulty is the embedded fragment approach. It tackles a chemical problem by dividing it into small fragments, which are treated in a highly accurate way, surrounded by an embedding included at an approximate level. For the vast family of medium-to-large sized polyoxometalates, two-electron-reduced systems are habitual and their magnetic properties are interesting. In this paper, we aim at assessing the quality of embedded fragment calculations by checking their ability to reproduce the electronic spectra of a complete system, here the mixed-metal series [MoxW6-xO19](4-) (x = 0-6). The microscopic parameters extracted from fragment calculations (electron hopping, intersite electrostatic repulsion, local orbital energy, etc.) have been used to reproduce the spectra through model Hamiltonian calculations. These energies are compared to the results of the highly accurate ab initio difference dedicated configuration interaction (DDCI) method on the complete system. In general, the model Hamiltonian calculations using parameters extracted from embedded fragments nearly exactly reproduce the DDCI spectra. This is quite an important result since it can be generalized to any inorganic magnetic system. Finally, the occurrence of singlet or triplet ground states in the series of molecules studied is rationalized upon the interplay of the parameters extracted.

Luminance, Colour, Viewpoint and Border Enhanced Disparity Energy Model

PubMed Central

Martins, Jaime A.; Rodrigues, João M. F.; du Buf, Hans

2015-01-01

The visual cortex is able to extract disparity information through the use of binocular cells. This process is reflected by the Disparity Energy Model, which describes the role and functioning of simple and complex binocular neuron populations, and how they are able to extract disparity. This model uses explicit cell parameters to mathematically determine preferred cell disparities, like spatial frequencies, orientations, binocular phases and receptive field positions. However, the brain cannot access such explicit cell parameters; it must rely on cell responses. In this article, we implemented a trained binocular neuronal population, which encodes disparity information implicitly. This allows the population to learn how to decode disparities, in a similar way to how our visual system could have developed this ability during evolution. At the same time, responses of monocular simple and complex cells can also encode line and edge information, which is useful for refining disparities at object borders. The brain should then be able, starting from a low-level disparity draft, to integrate all information, including colour and viewpoint perspective, in order to propagate better estimates to higher cortical areas. PMID:26107954

Automated method for the systematic interpretation of resonance peaks in spectrum data

DOEpatents

Damiano, B.; Wood, R.T.

1997-04-22

A method is described for spectral signature interpretation. The method includes the creation of a mathematical model of a system or process. A neural network training set is then developed based upon the mathematical model. The neural network training set is developed by using the mathematical model to generate measurable phenomena of the system or process based upon model input parameter that correspond to the physical condition of the system or process. The neural network training set is then used to adjust internal parameters of a neural network. The physical condition of an actual system or process represented by the mathematical model is then monitored by extracting spectral features from measured spectra of the actual process or system. The spectral features are then input into said neural network to determine the physical condition of the system or process represented by the mathematical model. More specifically, the neural network correlates the spectral features (i.e. measurable phenomena) of the actual process or system with the corresponding model input parameters. The model input parameters relate to specific components of the system or process, and, consequently, correspond to the physical condition of the process or system. 1 fig.

Complex Impedance of Fast Optical Transition Edge Sensors up to 30 MHz

NASA Astrophysics Data System (ADS)

Hattori, K.; Kobayashi, R.; Numata, T.; Inoue, S.; Fukuda, D.

2018-03-01

Optical transition edge sensors (TESs) are characterized by a very fast response, of the order of μs, which is 10^3 times faster than TESs for X-ray and gamma-ray. To extract important parameters associated with the optical TES, complex impedances at high frequencies (> 1 MHz) need to be measured, where the parasitic impedance in the circuit and reflections of electrical signals due to discontinuities in the characteristic impedance of the readout circuits become significant. This prevents the measurements of the current sensitivity β , which can be extracted from the complex impedance. In usual setups, it is hard to build a circuit model taking into account the parasitic impedances and reflections. In this study, we present an alternative method to estimate a transfer function without investigating the details of the entire circuit. Based on this method, the complex impedance up to 30 MHz was measured. The parameters were extracted from the impedance and were compared with other measurements. Using these parameters, we calculated the theoretical limit on an energy resolution and compared it with the measured energy resolution. In this paper, the reasons for the deviation of the measured value from theoretically predicted values will be discussed.

Extraction of Modal Parameters from Spacecraft Flight Data

NASA Technical Reports Server (NTRS)

James, George H.; Cao, Timothy T.; Fogt, Vincent A.; Wilson, Robert L.; Bartkowicz, Theodore J.

2010-01-01

The modeled response of spacecraft systems must be validated using flight data as ground tests cannot adequately represent the flight. Tools from the field of operational modal analysis would typically be brought to bear on such structures. However, spacecraft systems have several complicated issues: 1. High amplitudes of loads; 2. Compressive loads on the vehicle in flight; 3. Lack of generous time-synchronized flight data; 4. Changing properties during the flight; and 5. Major vehicle changes due to staging. A particularly vexing parameter to extract is modal damping. Damping estimation has become a more critical issue as new mass-driven vehicle designs seek to use the highest damping value possible. The paper will focus on recent efforts to utilize spacecraft flight data to extract system parameters, with a special interest on modal damping. This work utilizes the analysis of correlation functions derived from a sliding window technique applied to the time record. Four different case studies are reported in the sequence that drove the authors understanding. The insights derived from these four exercises are preliminary conclusions for the general state-of-the-art, but may be of specific utility to similar problems approached with similar tools.

SiC-VJFETs power switching devices: an improved model and parameter optimization technique

NASA Astrophysics Data System (ADS)

Ben Salah, T.; Lahbib, Y.; Morel, H.

2009-12-01

Silicon carbide junction field effect transistor (SiC-JFETs) is a mature power switch newly applied in several industrial applications. SiC-JFETs are often simulated by Spice model in order to predict their electrical behaviour. Although such a model provides sufficient accuracy for some applications, this paper shows that it presents serious shortcomings in terms of the neglect of the body diode model, among many others in circuit model topology. Simulation correction is then mandatory and a new model should be proposed. Moreover, this paper gives an enhanced model based on experimental dc and ac data. New devices are added to the conventional circuit model giving accurate static and dynamic behaviour, an effect not accounted in the Spice model. The improved model is implemented into VHDL-AMS language and steady-state dynamic and transient responses are simulated for many SiC-VJFETs samples. Very simple and reliable optimization algorithm based on the optimization of a cost function is proposed to extract the JFET model parameters. The obtained parameters are verified by comparing errors between simulations results and experimental data.

Quaternion-Based Texture Analysis of Multiband Satellite Images: Application to the Estimation of Aboveground Biomass in the East Region of Cameroon.

PubMed

Djiongo Kenfack, Cedrigue Boris; Monga, Olivier; Mpong, Serge Moto; Ndoundam, René

2018-03-01

Within the last decade, several approaches using quaternion numbers to handle and model multiband images in a holistic manner were introduced. The quaternion Fourier transform can be efficiently used to model texture in multidimensional data such as color images. For practical application, multispectral satellite data appear as a primary source for measuring past trends and monitoring changes in forest carbon stocks. In this work, we propose a texture-color descriptor based on the quaternion Fourier transform to extract relevant information from multiband satellite images. We propose a new multiband image texture model extraction, called FOTO++, in order to address biomass estimation issues. The first stage consists in removing noise from the multispectral data while preserving the edges of canopies. Afterward, color texture descriptors are extracted thanks to a discrete form of the quaternion Fourier transform, and finally the support vector regression method is used to deduce biomass estimation from texture indices. Our texture features are modeled using a vector composed with the radial spectrum coming from the amplitude of the quaternion Fourier transform. We conduct several experiments in order to study the sensitivity of our model to acquisition parameters. We also assess its performance both on synthetic images and on real multispectral images of Cameroonian forest. The results show that our model is more robust to acquisition parameters than the classical Fourier Texture Ordination model (FOTO). Our scheme is also more accurate for aboveground biomass estimation. We stress that a similar methodology could be implemented using quaternion wavelets. These results highlight the potential of the quaternion-based approach to study multispectral satellite images.

Mechanism and analyses for extracting photosynthetic electrons using exogenous quinones - what makes a good extraction pathway?

PubMed

Longatte, G; Rappaport, F; Wollman, F-A; Guille-Collignon, M; Lemaître, F

2016-08-04

Plants or algae take many benefits from oxygenic photosynthesis by converting solar energy into chemical energy through the synthesis of carbohydrates from carbon dioxide and water. However, the overall yield of this process is rather low (about 4% of the total energy available from sunlight is converted into chemical energy). This is the principal reason why recently many studies have been devoted to extraction of photosynthetic electrons in order to produce a sustainable electric current. Practically, the electron transfer occurs between the photosynthetic organism and an electrode and can be assisted by an exogenous mediator, mainly a quinone. In this regard, we recently reported on a method involving fluorescence measurements to estimate the ability of different quinones to extract photosynthetic electrons from a mutant of Chlamydomonas reinhardtii. In the present work, we used the same kind of methodology to establish a zone diagram for predicting the most suitable experimental conditions to extract photoelectrons from intact algae (quinone concentration and light intensity) as a function of the purpose of the study. This will provide further insights into the extraction mechanism of photosynthetic electrons using exogenous quinones. Indeed fluorescence measurements allowed us to model the capacity of photosynthetic algae to donate electrons to an exogenous quinone by considering a numerical parameter called "open center ratio" which is related to the Photosystem II acceptor redox state. Then, using it as a proxy for investigating the extraction of photosynthetic electrons by means of an exogenous quinone, 2,6-DCBQ, we suggested an extraction mechanism that was globally found consistent with the experimentally extracted parameters.

A new technology for determining transport parameters in porous media

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

Conca, J.L.; Wright, J.

The UFA Method can directly and rapidly measure transport parameters for any porous medium over a wide range of water contents and conditions. UFA results for subsurface sediments at a mixed-waste disposal site at the Hanford Site in Washington State provided the data necessary for detailed hydrostratigraphic mapping, subsurface flux and recharge distributions, and subsurface chemical mapping. Seven hundred unsaturated conductivity measurements along with pristine pore water extractions were obtained in only six months using the UFA. These data are used to provide realistic information to conceptual models, predictive models and restoration strategies.

Thermal oil recovery method using self-contained windelectric sets

NASA Astrophysics Data System (ADS)

Belsky, A. A.; Korolyov, I. A.

2018-05-01

The paper reviews challenges associated with questions of efficiency of thermal methods of impact on productive oil strata. The concept of using electrothermal complexes with WEG power supply for the indicated purposes was proposed and justified, their operating principles, main advantages and disadvantages, as well as a schematechnical solution for the implementation of the intensification of oil extraction, were considered. A mathematical model for finding the operating characteristics of WEG is presented and its main energy parameters are determined. The adequacy of the mathematical model is confirmed by laboratory simulation stand tests with nominal parameters.

Personalized mitral valve closure computation and uncertainty analysis from 3D echocardiography.

PubMed

Grbic, Sasa; Easley, Thomas F; Mansi, Tommaso; Bloodworth, Charles H; Pierce, Eric L; Voigt, Ingmar; Neumann, Dominik; Krebs, Julian; Yuh, David D; Jensen, Morten O; Comaniciu, Dorin; Yoganathan, Ajit P

2017-01-01

Intervention planning is essential for successful Mitral Valve (MV) repair procedures. Finite-element models (FEM) of the MV could be used to achieve this goal, but the translation to the clinical domain is challenging. Many input parameters for the FEM models, such as tissue properties, are not known. In addition, only simplified MV geometry models can be extracted from non-invasive modalities such as echocardiography imaging, lacking major anatomical details such as the complex chordae topology. A traditional approach for FEM computation is to use a simplified model (also known as parachute model) of the chordae topology, which connects the papillary muscle tips to the free-edges and select basal points. Building on the existing parachute model a new and comprehensive MV model was developed that utilizes a novel chordae representation capable of approximating regional connectivity. In addition, a fully automated personalization approach was developed for the chordae rest length, removing the need for tedious manual parameter selection. Based on the MV model extracted during mid-diastole (open MV) the MV geometric configuration at peak systole (closed MV) was computed according to the FEM model. In this work the focus was placed on validating MV closure computation. The method is evaluated on ten in vitro ovine cases, where in addition to echocardiography imaging, high-resolution μCT imaging is available for accurate validation. Copyright © 2016 Elsevier B.V. All rights reserved.

The Use of an Acellular Oxygen Carrier in a Human Liver Model of Normothermic Machine Perfusion.

PubMed

Laing, Richard W; Bhogal, Ricky H; Wallace, Lorraine; Boteon, Yuri; Neil, Desley A H; Smith, Amanda; Stephenson, Barney T F; Schlegel, Andrea; Hübscher, Stefan G; Mirza, Darius F; Afford, Simon C; Mergental, Hynek

2017-11-01

Normothermic machine perfusion of the liver (NMP-L) is a novel technique that preserves liver grafts under near-physiological conditions while maintaining their normal metabolic activity. This process requires an adequate oxygen supply, typically delivered by packed red blood cells (RBC). We present the first experience using an acellular hemoglobin-based oxygen carrier (HBOC) Hemopure in a human model of NMP-L. Five discarded high-risk human livers were perfused with HBOC-based perfusion fluid and matched to 5 RBC-perfused livers. Perfusion parameters, oxygen extraction, metabolic activity, and histological features were compared during 6 hours of NMP-L. The cytotoxicity of Hemopure was also tested on human hepatic primary cell line cultures using an in vitro model of ischemia reperfusion injury. The vascular flow parameters and the perfusate lactate clearance were similar in both groups. The HBOC-perfused livers extracted more oxygen than those perfused with RBCs (O2 extraction ratio 13.75 vs 9.43 % ×10 per gram of tissue, P = 0.001). In vitro exposure to Hemopure did not alter intracellular levels of reactive oxygen species, and there was no increase in apoptosis or necrosis observed in any of the tested cell lines. Histological findings were comparable between groups. There was no evidence of histological damage caused by Hemopure. Hemopure can be used as an alternative oxygen carrier to packed red cells in NMP-L perfusion fluid.

Overview of refinement procedures within REFMAC5: utilizing data from different sources.

PubMed

Kovalevskiy, Oleg; Nicholls, Robert A; Long, Fei; Carlon, Azzurra; Murshudov, Garib N

2018-03-01

Refinement is a process that involves bringing into agreement the structural model, available prior knowledge and experimental data. To achieve this, the refinement procedure optimizes a posterior conditional probability distribution of model parameters, including atomic coordinates, atomic displacement parameters (B factors), scale factors, parameters of the solvent model and twin fractions in the case of twinned crystals, given observed data such as observed amplitudes or intensities of structure factors. A library of chemical restraints is typically used to ensure consistency between the model and the prior knowledge of stereochemistry. If the observation-to-parameter ratio is small, for example when diffraction data only extend to low resolution, the Bayesian framework implemented in REFMAC5 uses external restraints to inject additional information extracted from structures of homologous proteins, prior knowledge about secondary-structure formation and even data obtained using different experimental methods, for example NMR. The refinement procedure also generates the `best' weighted electron-density maps, which are useful for further model (re)building. Here, the refinement of macromolecular structures using REFMAC5 and related tools distributed as part of the CCP4 suite is discussed.

Measuring tongue shapes and positions with ultrasound imaging: a validation experiment using an articulatory model.

PubMed

Ménard, Lucie; Aubin, Jérôme; Thibeault, Mélanie; Richard, Gabrielle

2012-01-01

The goal of this paper is to assess the validity of various metrics developed to characterize tongue shapes and positions collected through ultrasound imaging in experimental setups where the probe is not constrained relative to the subject's head. Midsagittal contours were generated using an articulatory-acoustic model of the vocal tract. Sections of the tongue were extracted to simulate ultrasound imaging. Various transformations were applied to the tongue contours in order to simulate ultrasound probe displacements: vertical displacement, horizontal displacement, and rotation. The proposed data analysis method reshapes tongue contours into triangles and then extracts measures of angles, x and y coordinates of the highest point of the tongue, curvature degree, and curvature position. Parameters related to the absolute tongue position (tongue height and front/back position) are more sensitive to horizontal and vertical displacements of the probe, whereas parameters related to tongue curvature are less sensitive to such displacements. Because of their robustness to probe displacements, parameters related to tongue shape (especially curvature) are particularly well suited to cases where the transducer is not constrained relative to the head (studies with clinical populations or children). Copyright © 2011 S. Karger AG, Basel.

Impact of observational incompleteness on the structural properties of protein interaction networks

NASA Astrophysics Data System (ADS)

Kuhnt, Mathias; Glauche, Ingmar; Greiner, Martin

2007-01-01

The observed structure of protein interaction networks is corrupted by many false positive/negative links. This observational incompleteness is abstracted as random link removal and a specific, experimentally motivated (spoke) link rearrangement. Their impact on the structural properties of gene-duplication-and-mutation network models is studied. For the degree distribution a curve collapse is found, showing no sensitive dependence on the link removal/rearrangement strengths and disallowing a quantitative extraction of model parameters. The spoke link rearrangement process moves other structural observables, like degree correlations, cluster coefficient and motif frequencies, closer to their counterparts extracted from the yeast data. This underlines the importance to take a precise modeling of the observational incompleteness into account when network structure models are to be quantitatively compared to data.

Online model checking approach based parameter estimation to a neuronal fate decision simulation model in Caenorhabditis elegans with hybrid functional Petri net with extension.

PubMed

Li, Chen; Nagasaki, Masao; Koh, Chuan Hock; Miyano, Satoru

2011-05-01

Mathematical modeling and simulation studies are playing an increasingly important role in helping researchers elucidate how living organisms function in cells. In systems biology, researchers typically tune many parameters manually to achieve simulation results that are consistent with biological knowledge. This severely limits the size and complexity of simulation models built. In order to break this limitation, we propose a computational framework to automatically estimate kinetic parameters for a given network structure. We utilized an online (on-the-fly) model checking technique (which saves resources compared to the offline approach), with a quantitative modeling and simulation architecture named hybrid functional Petri net with extension (HFPNe). We demonstrate the applicability of this framework by the analysis of the underlying model for the neuronal cell fate decision model (ASE fate model) in Caenorhabditis elegans. First, we built a quantitative ASE fate model containing 3327 components emulating nine genetic conditions. Then, using our developed efficient online model checker, MIRACH 1.0, together with parameter estimation, we ran 20-million simulation runs, and were able to locate 57 parameter sets for 23 parameters in the model that are consistent with 45 biological rules extracted from published biological articles without much manual intervention. To evaluate the robustness of these 57 parameter sets, we run another 20 million simulation runs using different magnitudes of noise. Our simulation results concluded that among these models, one model is the most reasonable and robust simulation model owing to the high stability against these stochastic noises. Our simulation results provide interesting biological findings which could be used for future wet-lab experiments.

Image Segmentation, Registration, Compression, and Matching

NASA Technical Reports Server (NTRS)

Yadegar, Jacob; Wei, Hai; Yadegar, Joseph; Ray, Nilanjan; Zabuawala, Sakina

2011-01-01

A novel computational framework was developed of a 2D affine invariant matching exploiting a parameter space. Named as affine invariant parameter space (AIPS), the technique can be applied to many image-processing and computer-vision problems, including image registration, template matching, and object tracking from image sequence. The AIPS is formed by the parameters in an affine combination of a set of feature points in the image plane. In cases where the entire image can be assumed to have undergone a single affine transformation, the new AIPS match metric and matching framework becomes very effective (compared with the state-of-the-art methods at the time of this reporting). No knowledge about scaling or any other transformation parameters need to be known a priori to apply the AIPS framework. An automated suite of software tools has been created to provide accurate image segmentation (for data cleaning) and high-quality 2D image and 3D surface registration (for fusing multi-resolution terrain, image, and map data). These tools are capable of supporting existing GIS toolkits already in the marketplace, and will also be usable in a stand-alone fashion. The toolkit applies novel algorithmic approaches for image segmentation, feature extraction, and registration of 2D imagery and 3D surface data, which supports first-pass, batched, fully automatic feature extraction (for segmentation), and registration. A hierarchical and adaptive approach is taken for achieving automatic feature extraction, segmentation, and registration. Surface registration is the process of aligning two (or more) data sets to a common coordinate system, during which the transformation between their different coordinate systems is determined. Also developed here are a novel, volumetric surface modeling and compression technique that provide both quality-guaranteed mesh surface approximations and compaction of the model sizes by efficiently coding the geometry and connectivity/topology components of the generated models. The highly efficient triangular mesh compression compacts the connectivity information at the rate of 1.5-4 bits per vertex (on average for triangle meshes), while reducing the 3D geometry by 40-50 percent. Finally, taking into consideration the characteristics of 3D terrain data, and using the innovative, regularized binary decomposition mesh modeling, a multistage, pattern-drive modeling, and compression technique has been developed to provide an effective framework for compressing digital elevation model (DEM) surfaces, high-resolution aerial imagery, and other types of NASA data.

New approaches in agent-based modeling of complex financial systems

NASA Astrophysics Data System (ADS)

Chen, Ting-Ting; Zheng, Bo; Li, Yan; Jiang, Xiong-Fei

2017-12-01

Agent-based modeling is a powerful simulation technique to understand the collective behavior and microscopic interaction in complex financial systems. Recently, the concept for determining the key parameters of agent-based models from empirical data instead of setting them artificially was suggested. We first review several agent-based models and the new approaches to determine the key model parameters from historical market data. Based on the agents' behaviors with heterogeneous personal preferences and interactions, these models are successful in explaining the microscopic origination of the temporal and spatial correlations of financial markets. We then present a novel paradigm combining big-data analysis with agent-based modeling. Specifically, from internet query and stock market data, we extract the information driving forces and develop an agent-based model to simulate the dynamic behaviors of complex financial systems.

Linear degrees of freedom in speech production: analysis of cineradio- and labio-film data and articulatory-acoustic modeling.

PubMed

Beautemps, D; Badin, P; Bailly, G

2001-05-01

The following contribution addresses several issues concerning speech degrees of freedom in French oral vowels, stop, and fricative consonants based on an analysis of tongue and lip shapes extracted from cineradio- and labio-films. The midsagittal tongue shapes have been submitted to a linear decomposition where some of the loading factors were selected such as jaw and larynx position while four other components were derived from principal component analysis (PCA). For the lips, in addition to the more traditional protrusion and opening components, a supplementary component was extracted to explain the upward movement of both the upper and lower lips in [v] production. A linear articulatory model was developed; the six tongue degrees of freedom were used as the articulatory control parameters of the midsagittal tongue contours and explained 96% of the tongue data variance. These control parameters were also used to specify the frontal lip width dimension derived from the labio-film front views. Finally, this model was complemented by a conversion model going from the midsagittal to the area function, based on a fitting of the midsagittal distances and the formant frequencies for both vowels and consonants.

Antioxidant potential of banana: Study using simulated gastrointestinal model and conventional extraction.

PubMed

Bhatt, Anjali; Patel, Vinayak

2015-07-01

Most reports on fruit antioxidant capacities are based on extraction of antioxidants using polar solvents. In banana, little is known about the fate of bioactive compounds during the digestion process, particularly in the food matrix under the gastric and intestinal conditions. In the present study, an in vitro gastrointestinal digestion method was used to simulate physiological conditions of the stomach and small intestine to evaluate the actual antioxidant capacity of banana. The simulated gastrointestinal extracts showed significantly higher antioxidant properties. The total phenol content of the physiological enzymatic extract was higher by almost 150% than the methanolic extract. Similarly, the flavonoid and flavonol contents were higher in the physiological enzymatic extract by 330.6 and 141.7%, respectively as compared to methanolic extract. These differences were also noticed in the antioxidant capacity measurement parameters. From the results, it can be concluded that the conventional extracts underrate the antioxidant value of banana and that they may have much higher health significance, as an antioxidant in particular.

[Study on the extraction technology and hypoglycemic activity of lectin from Trichosanthes kirilowi].

PubMed

Li, Qiong; Ye, Xiao-Li; Zeng, Hong; Chen, Xin; Li, Xue-Gang

2012-03-01

To extract lectins from Trichosanthes kirilowi and study their hypoglycemic activity. The optimal extraction process included the following parameters were conformed by optimization analysis,lectins extracted from Trichosanthes kirilowi was achieved by ammonium sulfate precipitation; The agglutinate activity was determined by using the agglutination test with 5% human blood cells. Human hepatocarcinoma cell HepG2 and the alloxan-induced diabetic mice model were used to assess hypoglycemic activity of Lectin in Trichosanthes kirilowi. The agglutination indexes of lectins extraction buffer were 32; The cell and mice tests indicated that the lectins exhibited hypoglycemic activity in the 70% saturation. The optimum extraction technology is as follows: extraction with PBS, the material-water ratio is 1:30, the extraction time is 24 h, while the concentration of sodium chloride is 0 mol/L and pH is 7.2. Precipitate lectins by ammonium sulfate in the 70% saturation, centrifugal speed is 10 000 tracted from Trichosanthes kirilowi exposes proper hypoglycemic activity.

Water soluble polysaccharides from Spirulina platensis: extraction and in vitro anti-cancer activity.

PubMed

Kurd, Forouzan; Samavati, Vahid

2015-03-01

Polysaccharides from Spirulina platensis algae (SP) were extracted by ultrasound-assisted extraction procedure. The optimal conditions for ultrasonic extraction of SP were determined by response surface methodology. The four parameters were, extraction time (X1), extraction temperature (X2), ultrasonic power (X3) and the ratio of water to raw material (X4), respectively. The experimental data obtained were fitted to a second-order polynomial equation. The optimum conditions were extraction time of 25 min, extraction temperature 85°C, ultrasonic power 90 W and ratio of water to raw material 20 mL/g. Under these optimal conditions, the experimental yield was 13.583±0.51%, well matched with the predicted models with the coefficients of determination (R2) of 0.9971. Then, we demonstrated that SP polysaccharides had strong scavenging activities in vitro on DPPH and hydroxyl radicals. Overall, SP may have potential applications in the medical and food industries. Copyright © 2015 Elsevier B.V. All rights reserved.

Orientation Modeling for Amateur Cameras by Matching Image Line Features and Building Vector Data

NASA Astrophysics Data System (ADS)

Hung, C. H.; Chang, W. C.; Chen, L. C.

2016-06-01

With the popularity of geospatial applications, database updating is getting important due to the environmental changes over time. Imagery provides a lower cost and efficient way to update the database. Three dimensional objects can be measured by space intersection using conjugate image points and orientation parameters of cameras. However, precise orientation parameters of light amateur cameras are not always available due to their costliness and heaviness of precision GPS and IMU. To automatize data updating, the correspondence of object vector data and image may be built to improve the accuracy of direct georeferencing. This study contains four major parts, (1) back-projection of object vector data, (2) extraction of image feature lines, (3) object-image feature line matching, and (4) line-based orientation modeling. In order to construct the correspondence of features between an image and a building model, the building vector features were back-projected onto the image using the initial camera orientation from GPS and IMU. Image line features were extracted from the imagery. Afterwards, the matching procedure was done by assessing the similarity between the extracted image features and the back-projected ones. Then, the fourth part utilized line features in orientation modeling. The line-based orientation modeling was performed by the integration of line parametric equations into collinearity condition equations. The experiment data included images with 0.06 m resolution acquired by Canon EOS Mark 5D II camera on a Microdrones MD4-1000 UAV. Experimental results indicate that 2.1 pixel accuracy may be reached, which is equivalent to 0.12 m in the object space.

Memory-enhancing activities of the aqueous extract of Albizia adianthifolia leaves in the 6-hydroxydopamine-lesion rodent model of Parkinson’s disease

PubMed Central

2014-01-01

Background Albizia adianthifolia (Schumach.) W. Wright (Fabaceae) is a traditional herb largely used in the African traditional medicine as analgesic, purgative, anti-inflammatory, antioxidant, antimicrobial and memory-enhancer drug. This study was undertaken in order to evaluate the possible cognitive-enhancing and antioxidative effects of the aqueous extract of A. adianthifolia leaves in the 6-hydroxydopamine-lesion rodent model of Parkinson’s disease. Methods The effect of the aqueous extract of A. adianthifolia leaves (150 and 300 mg/kg, orally, daily, for 21 days) on spatial memory performance was assessed using Y-maze and radial arm-maze tasks, as animal models of spatial memory. Pergolide - induced rotational behavior test was employed to validate unilateral damage to dopamine nigrostriatal neurons. Also, in vitro antioxidant activity was assessed through the estimation of total flavonoid and total phenolic contents along with determination of free radical scavenging activity. Statistical analyses were performed using two-way analysis of variance (ANOVA). Significant differences were determined by Tukey’s post hoc test. F values for which p < 0.05 were regarded as statistically significant. Pearson’s correlation coefficient and regression analysis were used in order to evaluate the association between behavioral parameters and net rotations in rotational behavior test. Results The 6-OHDA-treated rats exhibited the following: decrease of spontaneous alternations percentage within Y-maze task and increase of working memory errors and reference memory errors within radial arm maze task. Administration of the aqueous extract of A. adianthifolia leaves significantly improved these parameters, suggesting positive effects on spatial memory formation. Also, the aqueous extract of A. adianthifolia leaves showed potent in vitro antioxidant activity. Furthermore, in vivo evaluation, the aqueous extract of A. adianthifolia leaves attenuated the contralateral rotational asymmetry observed by pergolide challenge in 6-OHDA-treated rats. Conclusions Taken together, our results suggest that the aqueous extract of A. adianthifolia leaves possesses antioxidant potential and might provide an opportunity for management neurological abnormalities in Parkinson’s disease conditions. PMID:24884469

Reconstruction scenario in modified Horava-Lifshitz F( R) gravity with well-known scale factors

NASA Astrophysics Data System (ADS)

Jawad, Abdul; Rani, Shamaila

2015-05-01

In this paper, we analyze the behavior of pilgrim dark energy with G-O cutoff scale in modified Horava-Lifshitz F( R) gravity through correspondence scenario. We consider three well-known scale factors in which one scale factor describes the unification of matter dominated and accelerated phases and others are intermediate and bouncing forms. We obtain the models for these scale factors and obtain increasing behavior with the passage of time. We also extract equation of state parameter corresponding to these models. We observe that this parameter shows transition from phantom towards quintessence by crossing the phantom divide line in all cases. We also give comparison of our results of equation of state parameter with observational constraints.

Estimating kinetic mechanisms with prior knowledge I: Linear parameter constraints.

PubMed

Salari, Autoosa; Navarro, Marco A; Milescu, Mirela; Milescu, Lorin S

2018-02-05

To understand how ion channels and other proteins function at the molecular and cellular levels, one must decrypt their kinetic mechanisms. Sophisticated algorithms have been developed that can be used to extract kinetic parameters from a variety of experimental data types. However, formulating models that not only explain new data, but are also consistent with existing knowledge, remains a challenge. Here, we present a two-part study describing a mathematical and computational formalism that can be used to enforce prior knowledge into the model using constraints. In this first part, we focus on constraints that enforce explicit linear relationships involving rate constants or other model parameters. We develop a simple, linear algebra-based transformation that can be applied to enforce many types of model properties and assumptions, such as microscopic reversibility, allosteric gating, and equality and inequality parameter relationships. This transformation converts the set of linearly interdependent model parameters into a reduced set of independent parameters, which can be passed to an automated search engine for model optimization. In the companion article, we introduce a complementary method that can be used to enforce arbitrary parameter relationships and any constraints that quantify the behavior of the model under certain conditions. The procedures described in this study can, in principle, be coupled to any of the existing methods for solving molecular kinetics for ion channels or other proteins. These concepts can be used not only to enforce existing knowledge but also to formulate and test new hypotheses. © 2018 Salari et al.

Automated method for the systematic interpretation of resonance peaks in spectrum data

DOEpatents

Damiano, Brian; Wood, Richard T.

1997-01-01

A method for spectral signature interpretation. The method includes the creation of a mathematical model of a system or process. A neural network training set is then developed based upon the mathematical model. The neural network training set is developed by using the mathematical model to generate measurable phenomena of the system or process based upon model input parameter that correspond to the physical condition of the system or process. The neural network training set is then used to adjust internal parameters of a neural network. The physical condition of an actual system or process represented by the mathematical model is then monitored by extracting spectral features from measured spectra of the actual process or system. The spectral features are then input into said neural network to determine the physical condition of the system or process represented by the mathematical. More specifically, the neural network correlates the spectral features (i.e. measurable phenomena) of the actual process or system with the corresponding model input parameters. The model input parameters relate to specific components of the system or process, and, consequently, correspond to the physical condition of the process or system.

Numerical research of a 2D axial symmetry hybrid model for the radio-frequency ion thruster

NASA Astrophysics Data System (ADS)

Chenchen, WU; Xinfeng, SUN; Zuo, GU; Yanhui, JIA

2018-04-01

Since the high efficiency discharge is critical to the radio-frequency ion thruster (RIT), a 2D axial symmetry hybrid model has been developed to study the plasma evolution of RIT. The fluid method and the drift energy correction of the electron energy distribution function (EEDF) are applied to the analysis of the RIT discharge. In the meantime, the PIC-MCC method is used to investigate the ion beam current extraction character for the plasma plume region. The beam current simulation results, with the hybrid model, agree well with the experimental results, and the error is lower than 11%, which shows the validity of the model. The further study shows there is an optimal ratio for the radio-frequency (RF) power and the beam current extraction power under the fixed RIT configuration. And the beam extraction efficiency will decrease when the discharge efficiency beyond a certain threshold (about 87 W). As the input parameters of the hybrid model are all the design values, it can be directly used to the optimum design for other kinds of RITs and radio-frequency ion sources.

Optimizing the recovery of copper from electroplating rinse bath solution by hollow fiber membrane.

PubMed

Oskay, Kürşad Oğuz; Kul, Mehmet

2015-01-01

This study aimed to recover and remove copper from industrial model wastewater solution by non-dispersive solvent extraction (NDSX). Two mathematical models were developed to simulate the performance of an integrated extraction-stripping process, based on the use of hollow fiber contactors using the response surface method. The models allow one to predict the time dependent efficiencies of the two phases involved in individual extraction or stripping processes. The optimal recovery efficiency parameters were determined as 227 g/L of H2SO4 concentration, 1.22 feed/strip ratio, 450 mL/min flow rate (115.9 cm/min. flow velocity) and 15 volume % LIX 84-I concentration in 270 min by central composite design (CCD). At these optimum conditions, the experimental value of recovery efficiency was 95.88%, which was in close agreement with the 97.75% efficiency value predicted by the model. At the end of the process, almost all the copper in the model wastewater solution was removed and recovered as CuSO4.5H2O salt, which can be reused in the copper electroplating industry.

Constraining f(T) teleparallel gravity by big bang nucleosynthesis: f(T) cosmology and BBN.

PubMed

Capozziello, S; Lambiase, G; Saridakis, E N

2017-01-01

We use Big Bang Nucleosynthesis (BBN) observational data on the primordial abundance of light elements to constrain f ( T ) gravity. The three most studied viable f ( T ) models, namely the power law, the exponential and the square-root exponential are considered, and the BBN bounds are adopted in order to extract constraints on their free parameters. For the power-law model, we find that the constraints are in agreement with those obtained using late-time cosmological data. For the exponential and the square-root exponential models, we show that for reliable regions of parameters space they always satisfy the BBN bounds. We conclude that viable f ( T ) models can successfully satisfy the BBN constraints.

Process-Structure Linkages Using a Data Science Approach: Application to Simulated Additive Manufacturing Data

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

Popova, Evdokia; Rodgers, Theron M.; Gong, Xinyi

A novel data science workflow is developed and demonstrated to extract process-structure linkages (i.e., reduced-order model) for microstructure evolution problems when the final microstructure depends on (simulation or experimental) processing parameters. Our workflow consists of four main steps: data pre-processing, microstructure quantification, dimensionality reduction, and extraction/validation of process-structure linkages. These methods that can be employed within each step vary based on the type and amount of available data. In this paper, this data-driven workflow is applied to a set of synthetic additive manufacturing microstructures obtained using the Potts-kinetic Monte Carlo (kMC) approach. Additive manufacturing techniques inherently produce complex microstructures thatmore » can vary significantly with processing conditions. Using the developed workflow, a low-dimensional data-driven model was established to correlate process parameters with the predicted final microstructure. In addition, the modular workflows developed and presented in this work facilitate easy dissemination and curation by the broader community.« less

Renewable fluid dynamic energy derived from aquatic animal locomotion.

PubMed

Dabiri, John O

2007-09-01

Aquatic animals swimming in isolation and in groups are known to extract energy from the vortices in environmental flows, significantly reducing muscle activity required for locomotion. A model for the vortex dynamics associated with this phenomenon is developed, showing that the energy extraction mechanism can be described by simple criteria governing the kinematics of the vortices relative to the body in the flow. In this way, we need not make direct appeal to the fluid dynamics, which can be more difficult to evaluate than the kinematics. Examples of these principles as exhibited in swimming fish and existing energy conversion devices are described. A benefit of the developed framework is that the potentially infinite-dimensional parameter space of the fluid-structure interaction is reduced to a maximum of eight combinations of three parameters. The model may potentially aid in the design and evaluation of unsteady aero- and hydrodynamic energy conversion systems that surpass the Betz efficiency limit of steady fluid dynamic energy conversion systems.

Process-Structure Linkages Using a Data Science Approach: Application to Simulated Additive Manufacturing Data

DOE PAGES

Popova, Evdokia; Rodgers, Theron M.; Gong, Xinyi; ...

2017-03-13

A novel data science workflow is developed and demonstrated to extract process-structure linkages (i.e., reduced-order model) for microstructure evolution problems when the final microstructure depends on (simulation or experimental) processing parameters. Our workflow consists of four main steps: data pre-processing, microstructure quantification, dimensionality reduction, and extraction/validation of process-structure linkages. These methods that can be employed within each step vary based on the type and amount of available data. In this paper, this data-driven workflow is applied to a set of synthetic additive manufacturing microstructures obtained using the Potts-kinetic Monte Carlo (kMC) approach. Additive manufacturing techniques inherently produce complex microstructures thatmore » can vary significantly with processing conditions. Using the developed workflow, a low-dimensional data-driven model was established to correlate process parameters with the predicted final microstructure. In addition, the modular workflows developed and presented in this work facilitate easy dissemination and curation by the broader community.« less

Natural Language Processing Techniques for Extracting and Categorizing Finding Measurements in Narrative Radiology Reports.

PubMed

Sevenster, M; Buurman, J; Liu, P; Peters, J F; Chang, P J

2015-01-01

Accumulating quantitative outcome parameters may contribute to constructing a healthcare organization in which outcomes of clinical procedures are reproducible and predictable. In imaging studies, measurements are the principal category of quantitative para meters. The purpose of this work is to develop and evaluate two natural language processing engines that extract finding and organ measurements from narrative radiology reports and to categorize extracted measurements by their "temporality". The measurement extraction engine is developed as a set of regular expressions. The engine was evaluated against a manually created ground truth. Automated categorization of measurement temporality is defined as a machine learning problem. A ground truth was manually developed based on a corpus of radiology reports. A maximum entropy model was created using features that characterize the measurement itself and its narrative context. The model was evaluated in a ten-fold cross validation protocol. The measurement extraction engine has precision 0.994 and recall 0.991. Accuracy of the measurement classification engine is 0.960. The work contributes to machine understanding of radiology reports and may find application in software applications that process medical data.

The Extract of Lycium depressum Stocks Enhances Wound Healing in Streptozotocin-Induced Diabetic Rats.

PubMed

Naji, Siamak; Zarei, Leila; Pourjabali, Masoumeh; Mohammadi, Rahim

2017-06-01

In diabetes, impaired wound healing and other tissue abnormalities are considered major concerns. The aim of the present study was to assess the wound-healing activity of methanolic extracts of the extract of Lycium depressum leaves. A total of 60 healthy male Wistar diabetic rats weighing approximately 160 to 180 g and 7 weeks of age were randomized into 10 groups for incision and excision wound models: sham surgery group (SHAM), including creation of wounds and no treatment; base formulation group (FG) with creation of wounds and application of base formulation ointment; treatment group 1 (TG1) with 1 g of powder extract of the plant material in ointment; treatment group 2 (TG2) with 2 g; and treatment group 4 (TG3) with 4 g of powder extract of the plant material in ointment. A wound was induced by an excision- and incision-based wound model in male rats. The mature green leaves of L depressum were collected and authenticated. Extractions of dried leaves were carried out. For wound-healing activity, the extracts were applied topically in the form of ointment and compared with control groups. The healing of the wound was assessed based on excision, incision, hydroxyproline estimation, and biomechanical and biochemical studies. The extract of L depressum leaves enhanced wound contraction, decreased epithelialization time, increased hydroxyproline content, and improved mechanical indices and histological characteristics in treatment groups compared with SHAM and FG ( P < .05). These findings permit the conclusion the extract of L depressum benefits parameters of wound healing in a diabetes induced model.

A Poisson nonnegative matrix factorization method with parameter subspace clustering constraint for endmember extraction in hyperspectral imagery

NASA Astrophysics Data System (ADS)

Sun, Weiwei; Ma, Jun; Yang, Gang; Du, Bo; Zhang, Liangpei

2017-06-01

A new Bayesian method named Poisson Nonnegative Matrix Factorization with Parameter Subspace Clustering Constraint (PNMF-PSCC) has been presented to extract endmembers from Hyperspectral Imagery (HSI). First, the method integrates the liner spectral mixture model with the Bayesian framework and it formulates endmember extraction into a Bayesian inference problem. Second, the Parameter Subspace Clustering Constraint (PSCC) is incorporated into the statistical program to consider the clustering of all pixels in the parameter subspace. The PSCC could enlarge differences among ground objects and helps finding endmembers with smaller spectrum divergences. Meanwhile, the PNMF-PSCC method utilizes the Poisson distribution as the prior knowledge of spectral signals to better explain the quantum nature of light in imaging spectrometer. Third, the optimization problem of PNMF-PSCC is formulated into maximizing the joint density via the Maximum A Posterior (MAP) estimator. The program is finally solved by iteratively optimizing two sub-problems via the Alternating Direction Method of Multipliers (ADMM) framework and the FURTHESTSUM initialization scheme. Five state-of-the art methods are implemented to make comparisons with the performance of PNMF-PSCC on both the synthetic and real HSI datasets. Experimental results show that the PNMF-PSCC outperforms all the five methods in Spectral Angle Distance (SAD) and Root-Mean-Square-Error (RMSE), and especially it could identify good endmembers for ground objects with smaller spectrum divergences.

Application of latent variable model in Rosenberg self-esteem scale.

PubMed

Leung, Shing-On; Wu, Hui-Ping

2013-01-01

Latent Variable Models (LVM) are applied to Rosenberg Self-Esteem Scale (RSES). Parameter estimations automatically give negative signs hence no recoding is necessary for negatively scored items. Bad items can be located through parameter estimate, item characteristic curves and other measures. Two factors are extracted with one on self-esteem and the other on the degree to take moderate views, with the later not often being covered in previous studies. A goodness-of-fit measure based on two-way margins is used but more works are needed. Results show that scaling provided by models with more formal statistical ground correlated highly with conventional method, which may provide justification for usual practice.

Combining the modified Skyrme-like model and the local density approximation to determine the symmetry energy of nuclear matter

NASA Astrophysics Data System (ADS)

Liu, Jian; Ren, Zhongzhou; Xu, Chang

2018-07-01

Combining the modified Skyrme-like model and the local density approximation model, the slope parameter L of symmetry energy is extracted from the properties of finite nuclei with an improved iterative method. The calculations of the iterative method are performed within the framework of the spherical symmetry. By choosing 200 neutron rich nuclei on 25 isotopic chains as candidates, the slope parameter is constrained to be 50 MeV < L < 62 MeV. The validity of this method is examined by the properties of finite nuclei. Results show that reasonable descriptions on the properties of finite nuclei and nuclear matter can be obtained together.

Physics-based statistical model and simulation method of RF propagation in urban environments

DOEpatents

Pao, Hsueh-Yuan; Dvorak, Steven L.

2010-09-14

A physics-based statistical model and simulation/modeling method and system of electromagnetic wave propagation (wireless communication) in urban environments. In particular, the model is a computationally efficient close-formed parametric model of RF propagation in an urban environment which is extracted from a physics-based statistical wireless channel simulation method and system. The simulation divides the complex urban environment into a network of interconnected urban canyon waveguides which can be analyzed individually; calculates spectral coefficients of modal fields in the waveguides excited by the propagation using a database of statistical impedance boundary conditions which incorporates the complexity of building walls in the propagation model; determines statistical parameters of the calculated modal fields; and determines a parametric propagation model based on the statistical parameters of the calculated modal fields from which predictions of communications capability may be made.

Physically based model for extracting dual permeability parameters using non-Newtonian fluids

NASA Astrophysics Data System (ADS)

Abou Najm, M. R.; Basset, C.; Stewart, R. D.; Hauswirth, S.

2017-12-01

Dual permeability models are effective for the assessment of flow and transport in structured soils with two dominant structures. The major challenge to those models remains in the ability to determine appropriate and unique parameters through affordable, simple, and non-destructive methods. This study investigates the use of water and a non-Newtonian fluid in saturated flow experiments to derive physically-based parameters required for improved flow predictions using dual permeability models. We assess the ability of these two fluids to accurately estimate the representative pore sizes in dual-domain soils, by determining the effective pore sizes of macropores and micropores. We developed two sub-models that solve for the effective macropore size assuming either cylindrical (e.g., biological pores) or planar (e.g., shrinkage cracks and fissures) pore geometries, with the micropores assumed to be represented by a single effective radius. Furthermore, the model solves for the percent contribution to flow (wi) corresponding to the representative macro and micro pores. A user-friendly solver was developed to numerically solve the system of equations, given that relevant non-Newtonian viscosity models lack forms conducive to analytical integration. The proposed dual-permeability model is a unique attempt to derive physically based parameters capable of measuring dual hydraulic conductivities, and therefore may be useful in reducing parameter uncertainty and improving hydrologic model predictions.

JMOSFET: A MOSFET parameter extractor with geometry-dependent terms

NASA Technical Reports Server (NTRS)

Buehler, M. G.; Moore, B. T.

1985-01-01

The parameters from metal-oxide-silicon field-effect transistors (MOSFETs) that are included on the Combined Release and Radiation Effects Satellite (CRRES) test chips need to be extracted to have a simple but comprehensive method that can be used in wafer acceptance, and to have a method that is sufficiently accurate that it can be used in integrated circuits. A set of MOSFET parameter extraction procedures that are directly linked to the MOSFET model equations and that facilitate the use of simple, direct curve-fitting techniques are developed. In addition, the major physical effects that affect MOSFET operation in the linear and saturation regions of operation for devices fabricated in 1.2 to 3.0 mm CMOS technology are included. The fitting procedures were designed to establish single values for such parameters as threshold voltage and transconductance and to provide for slope matching between the linear and saturation regions of the MOSFET output current-voltage curves. Four different sizes of transistors that cover a rectangular-shaped region of the channel length-width plane are analyzed.

Evaluation of wound healing and anti-inflammatory activity of the rhizomes of Rumex abyssinicus J. (Polygonaceae) in mice.

PubMed

Mulisa, Eshetu; Asres, Kaleab; Engidawork, Ephrem

2015-09-30

Rumex abyssinicus Jacq (Polygonaceae) is widely used in Ethiopia for treatment of wound and other diseases. Although reports are available in the literature on some of the claimed activities, nothing has so far been reported about the wound healing activity of R. abyssinicus. Thus, this work was initiated to investigate the wound healing and anti-inflammatory activities of 80% methanol extract of the rhizomes of R. abyssinicus in mice. Following extraction of the rhizomes of the plant with 80% methanol, the extract was formulated as ointment (5% & 10% w/w) with simple ointment base B.P. The ointment was then evaluated for wound healing activity using excision and incision wound models. Parameters, including wound contraction, epithelization time and hydroxyproline content were determined using the excision model, whereas tensile strength was measured from the incision model. In parallel, anti-inflammatory activity of the rhizome was evaluated with carrageenan induced hind paw edema model by dissolving the 80% methanol extract in 1% carboxyl methyl cellulose and administering orally in various doses (250, 500 and 750 mg/kg). Wound treated with 5% and 10% (w/w) hydroalcoholic extract ointment exhibited significant wound healing activity in both models, as evidenced by increased wound contraction, shorter epithelization time, higher tissue breaking strength and increased hydroxyproline content. The hydroalcoholic extract also produced dose-related significant reduction (p < 0.05-0.001) of inflammation. The results of this study demonstrated that the hydroalcoholic extract of the rhizomes of R. abyssinicus facilitated wound healing at least in part via its anti-inflammatory activity, supporting its traditional claim as a wound healing agent.

Anti-inflammatory and antiallergic activity in vivo of lipophilic Isatis tinctoria extracts and tryptanthrin.

PubMed

Recio, María-Carmen; Cerdá-Nicolás, Miguel; Potterat, Olivier; Hamburger, Matthias; Ríos, José-Luis

2006-05-01

The effects of a supercritical CO2 (SFE) extract, a dichloromethane (DCM) extract from Isatis tinctoria leaf and the alkaloidal constituent tryptanthrin were studied in acute and subchronic experimental models of inflammation. The SFE and DCM extracts showed anti-inflammatory activity in the carrageenan-induced acute mouse paw oedema (ED50 values of 78 mg/kg and 165 mg/kg P. O., respectively) and in the acute tetradecanoylphorbol acetate (TPA)-induced mouse ear oedema in oral (62% and 32% oedema reduction at 100 and 125 mg/kg, respectively) and topical application (37% and 33% reduction of oedema at 0.5 mg/ear). In contrast, tryptanthrin showed no significant anti-inflammatory effect. The DCM extract inhibited oedema formation and neutrophil infiltration in subchronic inflammation in mice induced by repeated application of TPA. The extract showed activity after oral and topical administration by reducing the various parameters of the inflammatory response. The DCM extract (1 mg/ear) inhibited the delayed-type hypersensitivity (DTH) reaction induced by application of dinitrofluorobenzene (DNFB) after topical application. The response during the induction phase (24 h) was decreased by 48%, and the inflammatory phase (48 to 96 h) was reduced by 53 to 56%. The extract had no effect in this model when administered orally. The DCM extract (200 mg/kg P. O.) inhibited the acetic acid-induced writhing by 49%.

Performance enhancement for audio-visual speaker identification using dynamic facial muscle model.

PubMed

Asadpour, Vahid; Towhidkhah, Farzad; Homayounpour, Mohammad Mehdi

2006-10-01

Science of human identification using physiological characteristics or biometry has been of great concern in security systems. However, robust multimodal identification systems based on audio-visual information has not been thoroughly investigated yet. Therefore, the aim of this work to propose a model-based feature extraction method which employs physiological characteristics of facial muscles producing lip movements. This approach adopts the intrinsic properties of muscles such as viscosity, elasticity, and mass which are extracted from the dynamic lip model. These parameters are exclusively dependent on the neuro-muscular properties of speaker; consequently, imitation of valid speakers could be reduced to a large extent. These parameters are applied to a hidden Markov model (HMM) audio-visual identification system. In this work, a combination of audio and video features has been employed by adopting a multistream pseudo-synchronized HMM training method. Noise robust audio features such as Mel-frequency cepstral coefficients (MFCC), spectral subtraction (SS), and relative spectra perceptual linear prediction (J-RASTA-PLP) have been used to evaluate the performance of the multimodal system once efficient audio feature extraction methods have been utilized. The superior performance of the proposed system is demonstrated on a large multispeaker database of continuously spoken digits, along with a sentence that is phonetically rich. To evaluate the robustness of algorithms, some experiments were performed on genetically identical twins. Furthermore, changes in speaker voice were simulated with drug inhalation tests. In 3 dB signal to noise ratio (SNR), the dynamic muscle model improved the identification rate of the audio-visual system from 91 to 98%. Results on identical twins revealed that there was an apparent improvement on the performance for the dynamic muscle model-based system, in which the identification rate of the audio-visual system was enhanced from 87 to 96%.

Population Coding of Visual Space: Modeling

PubMed Central

Lehky, Sidney R.; Sereno, Anne B.

2011-01-01

We examine how the representation of space is affected by receptive field (RF) characteristics of the encoding population. Spatial responses were defined by overlapping Gaussian RFs. These responses were analyzed using multidimensional scaling to extract the representation of global space implicit in population activity. Spatial representations were based purely on firing rates, which were not labeled with RF characteristics (tuning curve peak location, for example), differentiating this approach from many other population coding models. Because responses were unlabeled, this model represents space using intrinsic coding, extracting relative positions amongst stimuli, rather than extrinsic coding where known RF characteristics provide a reference frame for extracting absolute positions. Two parameters were particularly important: RF diameter and RF dispersion, where dispersion indicates how broadly RF centers are spread out from the fovea. For large RFs, the model was able to form metrically accurate representations of physical space on low-dimensional manifolds embedded within the high-dimensional neural population response space, suggesting that in some cases the neural representation of space may be dimensionally isomorphic with 3D physical space. Smaller RF sizes degraded and distorted the spatial representation, with the smallest RF sizes (present in early visual areas) being unable to recover even a topologically consistent rendition of space on low-dimensional manifolds. Finally, although positional invariance of stimulus responses has long been associated with large RFs in object recognition models, we found RF dispersion rather than RF diameter to be the critical parameter. In fact, at a population level, the modeling suggests that higher ventral stream areas with highly restricted RF dispersion would be unable to achieve positionally-invariant representations beyond this narrow region around fixation. PMID:21344012

FracFit: A Robust Parameter Estimation Tool for Anomalous Transport Problems

NASA Astrophysics Data System (ADS)

Kelly, J. F.; Bolster, D.; Meerschaert, M. M.; Drummond, J. D.; Packman, A. I.

2016-12-01

Anomalous transport cannot be adequately described with classical Fickian advection-dispersion equations (ADE). Rather, fractional calculus models may be used, which capture non-Fickian behavior (e.g. skewness and power-law tails). FracFit is a robust parameter estimation tool based on space- and time-fractional models used to model anomalous transport. Currently, four fractional models are supported: 1) space fractional advection-dispersion equation (sFADE), 2) time-fractional dispersion equation with drift (TFDE), 3) fractional mobile-immobile equation (FMIE), and 4) tempered fractional mobile-immobile equation (TFMIE); additional models may be added in the future. Model solutions using pulse initial conditions and continuous injections are evaluated using stable distribution PDFs and CDFs or subordination integrals. Parameter estimates are extracted from measured breakthrough curves (BTCs) using a weighted nonlinear least squares (WNLS) algorithm. Optimal weights for BTCs for pulse initial conditions and continuous injections are presented, facilitating the estimation of power-law tails. Two sample applications are analyzed: 1) continuous injection laboratory experiments using natural organic matter and 2) pulse injection BTCs in the Selke river. Model parameters are compared across models and goodness-of-fit metrics are presented, assisting model evaluation. The sFADE and time-fractional models are compared using space-time duality (Baeumer et. al., 2009), which links the two paradigms.

Effect of ultrasonic treatment on the polyphenol content and antioxidant capacity of extract from defatted hemp, flax and canola seed cakes.

PubMed

Teh, Sue-Siang; Birch, Edward John

2014-01-01

The effectiveness of ultrasonic extraction of phenolics and flavonoids from defatted hemp, flax and canola seed cakes was compared to the conventional extraction method. Ultrasonic treatment at room temperature showed increased polyphenol extraction yield and antioxidant capacity by two-fold over the conventional extraction method. Different combinations of ultrasonic treatment parameters consisting of solvent volume (25, 50, 75 and 100 mL), extraction time (20, 30 and 40 min) and temperature (40, 50, 60 and 70 °C) were selected for polyphenol extractions from the seed cakes. The chosen parameters had a significant effect (p<0.05) on the polyphenol extraction yield and subsequent antioxidant capacity from the seed cakes. Application of heat during ultrasonic extraction yielded higher polyphenol content in extracts compared to the non-heated extraction. From an orthogonal design test, the best combination of parameters was 50 mL of solvent volume, 20 min of extraction time and 70 °C of ultrasonic temperature. Copyright © 2013. Published by Elsevier B.V.

Measuring the reduced scattering coefficient and γ with SFR spectroscopy: studying the phase function dependence (Conference Presentation)

NASA Astrophysics Data System (ADS)

Post, Anouk L.; Zhang, Xu; Bosschaart, Nienke; Van Leeuwen, Ton G.; Sterenborg, Henricus J. C. M.; Faber, Dirk J.

2016-03-01

Both Optical Coherence Tomography (OCT) and Single Fiber Reflectance Spectroscopy (SFR) are used to determine various optical properties of tissue. We developed a method combining these two techniques to measure the scattering anisotropy (g1) and γ (=1-g2/1-g1), related to the 1st and 2nd order moments of the phase function. The phase function is intimately associated with the cellular organization and ultrastructure of tissue, physical parameters that may change during disease onset and progression. Quantification of these parameters may therefore allow for improved non-invasive, in vivo discrimination between healthy and diseased tissue. With SFR the reduced scattering coefficient and γ can be extracted from the reflectance spectrum (Kanick et al., Biomedical Optics Express 2(6), 2011). With OCT the scattering coefficient can be extracted from the signal as a function of depth (Faber et al., Optics Express 12(19), 2004). Consequently, by combining SFR and OCT measurements at the same wavelengths, the scattering anisotropy (g) can be resolved using µs'= µs*(1-g). We performed measurements on a suspension of silica spheres as a proof of principle. The SFR model for the reflectance as a function of the reduced scattering coefficient and γ is based on semi-empirical modelling. These models feature Monte-Carlo (MC) based model constants. The validity of these constants - and thus the accuracy of the estimated parameters - depends on the phase function employed in the MC simulations. Since the phase function is not known when measuring in tissue, we will investigate the influence of assuming an incorrect phase function on the accuracy of the derived parameters.

Simultaneous parameter optimization of x-ray and neutron reflectivity data using genetic algorithms

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

Singh, Surendra, E-mail: surendra@barc.gov.in; Basu, Saibal

2016-05-23

X-ray and neutron reflectivity are two non destructive techniques which provide a wealth of information on thickness, structure and interracial properties in nanometer length scale. Combination of X-ray and neutron reflectivity is well suited for obtaining physical parameters of nanostructured thin films and superlattices. Neutrons provide a different contrast between the elements than X-rays and are also sensitive to the magnetization depth profile in thin films and superlattices. The real space information is extracted by fitting a model for the structure of the thin film sample in reflectometry experiments. We have applied a Genetic Algorithms technique to extract depth dependentmore » structure and magnetic in thin film and multilayer systems by simultaneously fitting X-ray and neutron reflectivity data.« less

Anthropogenic seismicity rates and operational parameters at the Salton Sea Geothermal Field.

PubMed

Brodsky, Emily E; Lajoie, Lia J

2013-08-02

Geothermal power is a growing energy source; however, efforts to increase production are tempered by concern over induced earthquakes. Although increased seismicity commonly accompanies geothermal production, induced earthquake rate cannot currently be forecast on the basis of fluid injection volumes or any other operational parameters. We show that at the Salton Sea Geothermal Field, the total volume of fluid extracted or injected tracks the long-term evolution of seismicity. After correcting for the aftershock rate, the net fluid volume (extracted-injected) provides the best correlation with seismicity in recent years. We model the background earthquake rate with a linear combination of injection and net production rates that allows us to track the secular development of the field as the number of earthquakes per fluid volume injected decreases over time.

Wound-healing potential of the root extract of Albizzia lebbeck.

PubMed

Joshi, Apurva; Sengar, Nidhi; Prasad, Satyendra K; Goel, Raj Kumar; Singh, Akanksha; Hemalatha, Siva

2013-06-01

The present investigation is an attempt to scientifically validate the traditional use of the roots of the plant Albizzia lebbeck in Ayurvedic system of medicine for curing wounds. The study included phytochemical standardization of the ethanol root extract of A. lebbeck, which was further subjected to oral acute toxicity study. Wound-healing activity of the ethanol root extract was evaluated using incision and excision wound models. Biochemical parameters such as hydroxyproline, hexuronic acid, hexosamine, and antioxidant enzymes like superoxide dismutase, reduced glutathione and free radical parameters including lipid peroxidation and nitric oxide were evaluated on the 10th post-wounding day following dead space method. For confirmation of activity, histopathology of the wounds and granulation tissues from excision and dead space wound model were performed. The study also included assessment of antibacterial activity of ethanol root extract against strains implicated in wound infection. The ethanol root extract was found to be highly rich in flavonoids, saponins, phenols, and tannins, while the amount of rutin was found to be 4.66 % w/w. It significantly increased the wound breaking strength showing a ceiling effect at 500 mg/kg p. o. The ethanol root extract at 500 mg/kg p. o. depicted an optimum wound contraction on the 18th day, while complete wound contraction was observed at the 22nd post wound day. It also demonstrated a significant increase in dry tissue weight, total protein, hydroxyproline, hexosamine, hexuronic acid, superoxide dismutase, and reduced glutathione levels, whereas a decrease in the levels of lipid peroxidation and nitric oxide was also observed with a potential antibacterial activity. Histopathological studies revealed a normal epithelization and fibrosis which was evidenced through an increase in collagen density. Thus, the study scientifically validated the wound-healing activity of the ethanol root extract along with a potential antibacterial property which may be attributed to the enhanced collagen synthesis and a potential antioxidant activity. Georg Thieme Verlag KG Stuttgart · New York.

Modeling and optimization of lime-based stabilization in high alkaline arsenic-bearing sludges with a central composite design.

PubMed

Lei, Jie; Peng, Bing; Min, Xiaobo; Liang, Yanjie; You, Yang; Chai, Liyuan

2017-04-16

This study focuses on the modeling and optimization of lime-based stabilization in high alkaline arsenic-bearing sludges (HAABS) and describes the relationship between the arsenic leachate concentration (ALC) and stabilization parameters to develop a prediction model for obtaining the optimal process parameters and conditions. A central composite design (CCD) along with response surface methodology (RSM) was conducted to model and investigate the stabilization process with three independent variables: the Ca/As mole ratio, reaction time and liquid/solid ratio, along with their interactions. The obvious characteristic changes of the HAABS before and after stabilization were verified by X-ray diffraction (XRD), scanning electron microscopy (SEM), particle size distribution (PSD) and the community bureau of reference (BCR) sequential extraction procedure. A prediction model Y (ALC) with a statistically significant P-value <0.01 and high correlation coefficient R 2 = 93.22% was obtained. The optimal parameters were successfully predicted by the model for the minimum ALC of 0.312 mg/L, which was validated with the experimental result (0.306 mg/L). The XRD, SEM and PSD results indicated that crystal calcium arsenate Ca 5 (AsO 4 ) 3 OH and Ca 4 (OH) 2 (AsO 4 ) 2 ·4H 2 O formation played an important role in minimizing the ALC. The BCR sequential extraction results demonstrated that the treated HAABS were stable in a weak acidic environment for a short time but posed a potential environmental risk after a long time. The results clearly confirm that the proposed three-factor CCD is an effective approach for modeling the stabilization of HAABS. However, further solidification technology is suggested for use after lime-based stabilization treatment of arsenic-bearing sludges.

On the interpretation of weight vectors of linear models in multivariate neuroimaging.

PubMed

Haufe, Stefan; Meinecke, Frank; Görgen, Kai; Dähne, Sven; Haynes, John-Dylan; Blankertz, Benjamin; Bießmann, Felix

2014-02-15

The increase in spatiotemporal resolution of neuroimaging devices is accompanied by a trend towards more powerful multivariate analysis methods. Often it is desired to interpret the outcome of these methods with respect to the cognitive processes under study. Here we discuss which methods allow for such interpretations, and provide guidelines for choosing an appropriate analysis for a given experimental goal: For a surgeon who needs to decide where to remove brain tissue it is most important to determine the origin of cognitive functions and associated neural processes. In contrast, when communicating with paralyzed or comatose patients via brain-computer interfaces, it is most important to accurately extract the neural processes specific to a certain mental state. These equally important but complementary objectives require different analysis methods. Determining the origin of neural processes in time or space from the parameters of a data-driven model requires what we call a forward model of the data; such a model explains how the measured data was generated from the neural sources. Examples are general linear models (GLMs). Methods for the extraction of neural information from data can be considered as backward models, as they attempt to reverse the data generating process. Examples are multivariate classifiers. Here we demonstrate that the parameters of forward models are neurophysiologically interpretable in the sense that significant nonzero weights are only observed at channels the activity of which is related to the brain process under study. In contrast, the interpretation of backward model parameters can lead to wrong conclusions regarding the spatial or temporal origin of the neural signals of interest, since significant nonzero weights may also be observed at channels the activity of which is statistically independent of the brain process under study. As a remedy for the linear case, we propose a procedure for transforming backward models into forward models. This procedure enables the neurophysiological interpretation of the parameters of linear backward models. We hope that this work raises awareness for an often encountered problem and provides a theoretical basis for conducting better interpretable multivariate neuroimaging analyses. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

The Threshold Bias Model: A Mathematical Model for the Nomothetic Approach of Suicide

PubMed Central

Folly, Walter Sydney Dutra

2011-01-01

Background Comparative and predictive analyses of suicide data from different countries are difficult to perform due to varying approaches and the lack of comparative parameters. Methodology/Principal Findings A simple model (the Threshold Bias Model) was tested for comparative and predictive analyses of suicide rates by age. The model comprises of a six parameter distribution that was applied to the USA suicide rates by age for the years 2001 and 2002. Posteriorly, linear extrapolations are performed of the parameter values previously obtained for these years in order to estimate the values corresponding to the year 2003. The calculated distributions agreed reasonably well with the aggregate data. The model was also used to determine the age above which suicide rates become statistically observable in USA, Brazil and Sri Lanka. Conclusions/Significance The Threshold Bias Model has considerable potential applications in demographic studies of suicide. Moreover, since the model can be used to predict the evolution of suicide rates based on information extracted from past data, it will be of great interest to suicidologists and other researchers in the field of mental health. PMID:21909431

The threshold bias model: a mathematical model for the nomothetic approach of suicide.

PubMed

Folly, Walter Sydney Dutra

2011-01-01

Comparative and predictive analyses of suicide data from different countries are difficult to perform due to varying approaches and the lack of comparative parameters. A simple model (the Threshold Bias Model) was tested for comparative and predictive analyses of suicide rates by age. The model comprises of a six parameter distribution that was applied to the USA suicide rates by age for the years 2001 and 2002. Posteriorly, linear extrapolations are performed of the parameter values previously obtained for these years in order to estimate the values corresponding to the year 2003. The calculated distributions agreed reasonably well with the aggregate data. The model was also used to determine the age above which suicide rates become statistically observable in USA, Brazil and Sri Lanka. The Threshold Bias Model has considerable potential applications in demographic studies of suicide. Moreover, since the model can be used to predict the evolution of suicide rates based on information extracted from past data, it will be of great interest to suicidologists and other researchers in the field of mental health.

Mathematical estimation of melt depth in conduction mode of laser spot remelting process

NASA Astrophysics Data System (ADS)

Hadi, Iraj

2012-12-01

A one-dimensional mathematical model based on the front tracking method was developed to predict the melt depth as a function of internal and external parameters of laser spot remelting process in conduction mode. Power density, pulse duration, and thermophysical properties of material including thermal diffusivity, melting point, latent heat, and absorption coefficient have been taken into account in the model of this article. By comparing the theoretical results and experimental welding data of commercial pure nickel and titanium plates, the validity of the developed model was examined. Comparison shows a reasonably good agreement between the theory and experiment. For the sake of simplicity, a graphical technique was presented to obtain the melt depth of various materials at any arbitrary amount of power density and pulse duration. In the graphical technique, two dimensionless constants including the Stefan number (Ste) and an introduced constant named laser power factor (LPF) are used. Indeed, all of the internal and external parameters have been gathered in LPF. The effect of power density and pulse duration on the variation of melt depth for different materials such as aluminum, copper, and stainless steel were investigated. Additionally, appropriate expressions were extracted to describe the minimum power density and time to reach melting point in terms of process parameters. A simple expression is also extracted to estimate the thickness of mushy zone for alloys.

Angular motion estimation using dynamic models in a gyro-free inertial measurement unit.

PubMed

Edwan, Ezzaldeen; Knedlik, Stefan; Loffeld, Otmar

2012-01-01

In this paper, we summarize the results of using dynamic models borrowed from tracking theory in describing the time evolution of the state vector to have an estimate of the angular motion in a gyro-free inertial measurement unit (GF-IMU). The GF-IMU is a special type inertial measurement unit (IMU) that uses only a set of accelerometers in inferring the angular motion. Using distributed accelerometers, we get an angular information vector (AIV) composed of angular acceleration and quadratic angular velocity terms. We use a Kalman filter approach to estimate the angular velocity vector since it is not expressed explicitly within the AIV. The bias parameters inherent in the accelerometers measurements' produce a biased AIV and hence the AIV bias parameters are estimated within an augmented state vector. Using dynamic models, the appended bias parameters of the AIV become observable and hence we can have unbiased angular motion estimate. Moreover, a good model is required to extract the maximum amount of information from the observation. Observability analysis is done to determine the conditions for having an observable state space model. For higher grades of accelerometers and under relatively higher sampling frequency, the error of accelerometer measurements is dominated by the noise error. Consequently, simulations are conducted on two models, one has bias parameters appended in the state space model and the other is a reduced model without bias parameters.

Angular Motion Estimation Using Dynamic Models in a Gyro-Free Inertial Measurement Unit

PubMed Central

Edwan, Ezzaldeen; Knedlik, Stefan; Loffeld, Otmar

2012-01-01

In this paper, we summarize the results of using dynamic models borrowed from tracking theory in describing the time evolution of the state vector to have an estimate of the angular motion in a gyro-free inertial measurement unit (GF-IMU). The GF-IMU is a special type inertial measurement unit (IMU) that uses only a set of accelerometers in inferring the angular motion. Using distributed accelerometers, we get an angular information vector (AIV) composed of angular acceleration and quadratic angular velocity terms. We use a Kalman filter approach to estimate the angular velocity vector since it is not expressed explicitly within the AIV. The bias parameters inherent in the accelerometers measurements' produce a biased AIV and hence the AIV bias parameters are estimated within an augmented state vector. Using dynamic models, the appended bias parameters of the AIV become observable and hence we can have unbiased angular motion estimate. Moreover, a good model is required to extract the maximum amount of information from the observation. Observability analysis is done to determine the conditions for having an observable state space model. For higher grades of accelerometers and under relatively higher sampling frequency, the error of accelerometer measurements is dominated by the noise error. Consequently, simulations are conducted on two models, one has bias parameters appended in the state space model and the other is a reduced model without bias parameters. PMID:22778586

[Studying on purification technology of Resina Draconis phenol extracts based on design space method].

PubMed

Zhang, Jian; Zhang, Xin; Bi, Yu-An; Xu, Gui-Hong; Huang, Wen-Zhe; Wang, Zhen-Zhong; Xiao, Wei

2017-09-01

The "design space" method was used to optimize the purification process of Resina Draconis phenol extracts by using the concept of "quality derived from design" (QbD). The content and transfer rate of laurin B and 7,4'-dihydroxyflavone and yield of extract were selected as the critical quality attributes (CQA). Plackett-Burman design showed that the critical process parameters (CPP) were concentration of alkali, the amount of alkali and the temperature of alkali dissolution. Then the Box-Behnken design was used to establish the mathematical model between CQA and CPP. The variance analysis results showed that the P values of the five models were less than 0.05 and the mismatch values were all greater than 0.05, indicating that the model could well describe the relationship between CQA and CPP. Finally, the control limits of the above 5 indicators (content and transfer rate of laurine B and 7,4'-dihydroxyflavone, as well as the extract yield) were set, and then the probability-based design space was calculated by Monte Carlo simulation and verified. The results of the design space validation showed that the optimized purification method can ensure the stability of the Resina Draconis phenol extracts refining process, which would help to improve the quality uniformity between batches of phenol extracts and provide data support for production automation control. Copyright© by the Chinese Pharmaceutical Association.

Effects of ginseng extract on various haematological parameters during aerobic exercise in the rat.

PubMed

Ferrando, A; Vila, L; Voces, J A; Cabral, A C; Alvarez, A I; Prieto, J G

1999-04-01

The effects of the Ginseng extract on various biochemical and haematological parameters in male Wistar rats subjected to a treadmill exercise protocol were studied for 12 weeks. The results showed increases in the haematological parameters, these increases being greatest for the animals treated with the extract during the third month of the study. The exercise also led to increases in these parameters, while the combination of both exercise and extract produced smaller increases. This study shows a clear physiological response due to the ginseng extract administration that reproduces many of the effects obtained after long-term exercise. The combination of exercise and treatments seems to support the theory that there is no clear synergic effect when the advantages associated with the ingestion of ginseng are compared with the performance of exercise.

Ultrasound-assisted enzymatic extraction and antioxidant activity of polysaccharides from pumpkin (Cucurbita moschata).

PubMed

Wu, Hao; Zhu, Junxiang; Diao, Wenchao; Wang, Chengrong

2014-11-26

An efficient ultrasound-assisted enzymatic extraction (UAEE) of Cucurbita moschata polysaccharides (CMCP) was established and the CMCP antioxidant activities were studied. The UAEE operating parameters (extraction temperature, ultrasonic power, pH, and liquid-to-material ratio) were optimized using the central composite design (CCD) and the mass transfer kinetic study in UAEE procedure was used to select the optimal extraction time. Enzymolysis and ultrasonication that were simultaneously conducted was selected as the UAEE synergistic model and the optimum extraction conditions with a maximum polysaccharide yield of 4.33 ± 0.15% were as follows: extraction temperature, 51.5 °C; ultrasonic power, 440 W; pH, 5.0; liquid-to-material ratio, 5.70:1 mL/g; and extraction time, 20 min. Evaluation of the antioxidant activity in vitro suggested that CMCP has good potential as a natural antioxidant used in the food or medicine industry because of their high reducing power and positive radical scavenging activity for DPPH radical. Copyright © 2014 Elsevier Ltd. All rights reserved.

Application of the L-curve in geophysical inverse problems: methodologies for the extraction of the optimal parameter

NASA Astrophysics Data System (ADS)

Bassrei, A.; Terra, F. A.; Santos, E. T.

2007-12-01

Inverse problems in Applied Geophysics are usually ill-posed. One way to reduce such deficiency is through derivative matrices, which are a particular case of a more general family that receive the name regularization. The regularization by derivative matrices has an input parameter called regularization parameter, which choice is already a problem. It was suggested in the 1970's a heuristic approach later called L-curve, with the purpose to provide the optimum regularization parameter. The L-curve is a parametric curve, where each point is associated to a λ parameter. In the horizontal axis one represents the error between the observed data and the calculated one and in the vertical axis one represents the product between the regularization matrix and the estimated model. The ideal point is the L-curve knee, where there is a balance between the quantities represented in the Cartesian axes. The L-curve has been applied to a variety of inverse problems, also in Geophysics. However, the visualization of the knee is not always an easy task, in special when the L-curve does not the L shape. In this work three methodologies are employed for the search and obtainment of the optimal regularization parameter from the L curve. The first criterion is the utilization of Hansen's tool box which extracts λ automatically. The second criterion consists in to extract visually the optimal parameter. By third criterion one understands the construction of the first derivative of the L-curve, and the posterior automatic extraction of the inflexion point. The utilization of the L-curve with the three above criteria were applied and validated in traveltime tomography and 2-D gravity inversion. After many simulations with synthetic data, noise- free as well as data corrupted with noise, with the regularization orders 0, 1, and 2, we verified that the three criteria are valid and provide satisfactory results. The third criterion presented the best performance, specially in cases where the L-curve has an irregular shape.

Optimization of subcritical water extraction parameters of antioxidant polyphenols from sea buckthorn (Hippophaë rhamnoides L.) seed residue.

PubMed

Gong, Ying; Zhang, Xiaofei; He, Li; Yan, Qiuli; Yuan, Fang; Gao, Yanxiang

2015-03-01

Polyphenols was extracted with subcritical water from the sea buckthorn seed residue (after oil recovery), and the extraction parameters were optimized using response surface methodology (RSM). The independent processing variables were extraction temperature, extraction time and the ratio of water to solid. The optimal extraction parameters for the extracts with highest ABTS radical scavenging activity were 120 °C, 36 min and the water to solid ratio of 20, and the maximize antioxidant capacity value was 32.42 mmol Trolox equivalent (TE)/100 g. Under the optimal conditions, the yield of total phenolics, total flavonoids and proanthocyanidins was 36.62 mg gallic acid equivalents (GAE)/g, 19.98 mg rutin equivalent (RE)/g and 10.76 mg catechin equivalents (CE)/g, respectively.

Evaluation of the wound-healing activity of Hibiscus rosa sinensis L (Malvaceae) in Wistar albino rats.

PubMed

Bhaskar, Anusha; Nithya, V

2012-01-01

To investigate the wound-healing potency of the ethanolic extract of the flowers of Hibiscus rosa sinensis. The wound-healing activity of H. rosa sinensis (5 and 10% w/w) on Wistar albino rats was studied using three different models viz., excision, incision and dead space wound. The parameters studied were breaking strength in incision model, granulation tissue dry weight, breaking strength and collagen content in dead space wound model, percentage of wound contraction and period of epithelization in excision wound model. The granulation tissue formed on days 4, 8, 12, and 16 (post-wound) was used to estimate total collagen, hexosamine, protein, DNA and uronic acid. Data were analyzed by Analysis of Variance (ANOVA) test. P<0.05 was considered statistically significant. The extract increased cellular proliferation and collagen synthesis at the wound site, as evidenced by increase in DNA, total protein and total collagen content of granulation tissues. The extract-treated wounds were found to heal much faster as indicated by improved rates of epithelialization and wound contraction. The extract of H. rosa sinensis significantly (P<0.001) increased the wound-breaking strength in the incision wound model compared to controls. The extract-treated wounds were found to epithelialize faster, and the rate of wound contraction was significantly (P<0.001) increased as compared to control wounds. Wet and dry granulation tissue weights in a dead space wound model increased significantly (P<0.001). There was a significant increase in wound closure rate, tensile strength, dry granuloma weight, wet granuloma weight and decrease in epithelization period in H. rosa sinensis-treated group as compared to control and standard drug-treated groups. The ethanolic extract of H. rosa sinensis had greater wound-healing activity than the nitrofurazone ointment.

The Hull Method for Selecting the Number of Common Factors

ERIC Educational Resources Information Center

Lorenzo-Seva, Urbano; Timmerman, Marieke E.; Kiers, Henk A. L.

2011-01-01

A common problem in exploratory factor analysis is how many factors need to be extracted from a particular data set. We propose a new method for selecting the number of major common factors: the Hull method, which aims to find a model with an optimal balance between model fit and number of parameters. We examine the performance of the method in an…

[Development of an analyzing system for soil parameters based on NIR spectroscopy].

PubMed

Zheng, Li-Hua; Li, Min-Zan; Sun, Hong

2009-10-01

A rapid estimation system for soil parameters based on spectral analysis was developed by using object-oriented (OO) technology. A class of SOIL was designed. The instance of the SOIL class is the object of the soil samples with the particular type, specific physical properties and spectral characteristics. Through extracting the effective information from the modeling spectral data of soil object, a map model was established between the soil parameters and its spectral data, while it was possible to save the mapping model parameters in the database of the model. When forecasting the content of any soil parameter, the corresponding prediction model of this parameter can be selected with the same soil type and the similar soil physical properties of objects. And after the object of target soil samples was carried into the prediction model and processed by the system, the accurate forecasting content of the target soil samples could be obtained. The system includes modules such as file operations, spectra pretreatment, sample analysis, calibrating and validating, and samples content forecasting. The system was designed to run out of equipment. The parameters and spectral data files (*.xls) of the known soil samples can be input into the system. Due to various data pretreatment being selected according to the concrete conditions, the results of predicting content will appear in the terminal and the forecasting model can be stored in the model database. The system reads the predicting models and their parameters are saved in the model database from the module interface, and then the data of the tested samples are transferred into the selected model. Finally the content of soil parameters can be predicted by the developed system. The system was programmed with Visual C++6.0 and Matlab 7.0. And the Access XP was used to create and manage the model database.

Extracting a mix parameter from 2D radiography of variable density flow

NASA Astrophysics Data System (ADS)

Kurien, Susan; Doss, Forrest; Livescu, Daniel

2017-11-01

A methodology is presented for extracting quantities related to the statistical description of the mixing state from the 2D radiographic image of a flow. X-ray attenuation through a target flow is given by the Beer-Lambert law which exponentially damps the incident beam intensity by a factor proportional to the density, opacity and thickness of the target. By making reasonable assumptions for the mean density, opacity and effective thickness of the target flow, we estimate the contribution of density fluctuations to the attenuation. The fluctuations thus inferred may be used to form the correlation of density and specific-volume, averaged across the thickness of the flow in the direction of the beam. This correlation function, denoted by b in RANS modeling, quantifies turbulent mixing in variable density flows. The scheme is tested using DNS data computed for variable-density buoyancy-driven mixing. We quantify the deficits in the extracted value of b due to target thickness, Atwood number, and modeled noise in the incident beam. This analysis corroborates the proposed scheme to infer the mix parameter from thin targets at moderate to low Atwood numbers. The scheme is then applied to an image of counter-shear flow obtained from experiments at the National Ignition Facility. US Department of Energy.

Withania somnifera Extract Protects Model Neurons from In Vitro Traumatic Injury

PubMed Central

Saykally, Jessica N.; Hatic, Haris; Keeley, Kristen L.; Jain, Subhash C.; Ravindranath, Vijayalakshmi

2017-01-01

Withania somnifera has been used in traditional medicine for a variety of neural disorders. Recently, chronic neurodegenerative conditions have been shown to benefit from treatment with this extract. To evaluate the action of this extract on traumatically injured neurons, the efficacy of W. somnifera root extract as a neuroprotective agent was examined in cultured model neurons exposed to an in vitro injury system designed to mimic mild traumatic brain injury (TBI). Neuronal health was evaluated by staining with annexin V (an early, apoptotic feature) and monitoring released lactate dehydrogenase activity (a terminal cell loss parameter). Potential mechanisms underlying the observed neuroprotection were examined. Additionally, morphological changes were monitored following injury and treatment. Although no differences were found in the expression of the antioxidant transcription factor nuclear factor erythroid 2-like 2 (Nrf2) or other Nrf2-related downstream components, significant changes were seen in apoptotic signaling. Treatment with the extract resulted in an increased length of neurites projecting from the neuronal cell body after injury. W. somnifera extract treatment also resulted in reduced cell death in the model neuron TBI system. The cell death factor Bax was involved (its expression was reduced 2-fold by the treatment) and injury-induced reduction in neurite lengths and numbers was reversed by the treatment. This all indicates that W. somnifera root extract was neuroprotective and could have therapeutic potential to target factors involved in secondary injury and long-term sequelae of mild TBI. PMID:28933215

Withania somnifera Extract Protects Model Neurons from In Vitro Traumatic Injury.

PubMed

Saykally, Jessica N; Hatic, Haris; Keeley, Kristen L; Jain, Subhash C; Ravindranath, Vijayalakshmi; Citron, Bruce A

2017-07-01

Withania somnifera has been used in traditional medicine for a variety of neural disorders. Recently, chronic neurodegenerative conditions have been shown to benefit from treatment with this extract. To evaluate the action of this extract on traumatically injured neurons, the efficacy of W. somnifera root extract as a neuroprotective agent was examined in cultured model neurons exposed to an in vitro injury system designed to mimic mild traumatic brain injury (TBI). Neuronal health was evaluated by staining with annexin V (an early, apoptotic feature) and monitoring released lactate dehydrogenase activity (a terminal cell loss parameter). Potential mechanisms underlying the observed neuroprotection were examined. Additionally, morphological changes were monitored following injury and treatment. Although no differences were found in the expression of the antioxidant transcription factor nuclear factor erythroid 2-like 2 (Nrf2) or other Nrf2-related downstream components, significant changes were seen in apoptotic signaling. Treatment with the extract resulted in an increased length of neurites projecting from the neuronal cell body after injury. W. somnifera extract treatment also resulted in reduced cell death in the model neuron TBI system. The cell death factor Bax was involved (its expression was reduced 2-fold by the treatment) and injury-induced reduction in neurite lengths and numbers was reversed by the treatment. This all indicates that W. somnifera root extract was neuroprotective and could have therapeutic potential to target factors involved in secondary injury and long-term sequelae of mild TBI.

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.

[Study on new extraction technology of astragaloside IV].

PubMed

Sun, Haiyan; Guan, Su; Huang, Min

2005-08-01

To explore the possibility and the optimal extraction technology of astragaloside IV by SFE-CO2. According the content of astragaloside IV, the optimum extraction technology parameters such as extraction temperature, pressure, extraction time, velocity of fluid and co-solvent were investigated and the result was compared with that of water extraction. The optimum technical parameters were as follows: Extracting pressure 40 Mpa, temperature 45 degrees C, extracting time 2h, co-solvent was 95% ethanol and its dosage was 4ml/g, the ratio of CO2 fluid was 10 kg/kg x h. Extraction technology of astragaloside IV by SFE-CO2 is reliable, stable.

Estimation of Thalamocortical and Intracortical Network Models from Joint Thalamic Single-Electrode and Cortical Laminar-Electrode Recordings in the Rat Barrel System

PubMed Central

Blomquist, Patrick; Devor, Anna; Indahl, Ulf G.; Ulbert, Istvan; Einevoll, Gaute T.; Dale, Anders M.

2009-01-01

A new method is presented for extraction of population firing-rate models for both thalamocortical and intracortical signal transfer based on stimulus-evoked data from simultaneous thalamic single-electrode and cortical recordings using linear (laminar) multielectrodes in the rat barrel system. Time-dependent population firing rates for granular (layer 4), supragranular (layer 2/3), and infragranular (layer 5) populations in a barrel column and the thalamic population in the homologous barreloid are extracted from the high-frequency portion (multi-unit activity; MUA) of the recorded extracellular signals. These extracted firing rates are in turn used to identify population firing-rate models formulated as integral equations with exponentially decaying coupling kernels, allowing for straightforward transformation to the more common firing-rate formulation in terms of differential equations. Optimal model structures and model parameters are identified by minimizing the deviation between model firing rates and the experimentally extracted population firing rates. For the thalamocortical transfer, the experimental data favor a model with fast feedforward excitation from thalamus to the layer-4 laminar population combined with a slower inhibitory process due to feedforward and/or recurrent connections and mixed linear-parabolic activation functions. The extracted firing rates of the various cortical laminar populations are found to exhibit strong temporal correlations for the present experimental paradigm, and simple feedforward population firing-rate models combined with linear or mixed linear-parabolic activation function are found to provide excellent fits to the data. The identified thalamocortical and intracortical network models are thus found to be qualitatively very different. While the thalamocortical circuit is optimally stimulated by rapid changes in the thalamic firing rate, the intracortical circuits are low-pass and respond most strongly to slowly varying inputs from the cortical layer-4 population. PMID:19325875

Use of a Latent Topic Model for Characteristic Extraction from Health Checkup Questionnaire Data.

PubMed

Hatakeyama, Y; Miyano, I; Kataoka, H; Nakajima, N; Watabe, T; Yasuda, N; Okuhara, Y

2015-01-01

When patients complete questionnaires during health checkups, many of their responses are subjective, making topic extraction difficult. Therefore, the purpose of this study was to develop a model capable of extracting appropriate topics from subjective data in questionnaires conducted during health checkups. We employed a latent topic model to group the lifestyle habits of the study participants and represented their responses to items on health checkup questionnaires as a probability model. For the probability model, we used latent Dirichlet allocation to extract 30 topics from the questionnaires. According to the model parameters, a total of 4381 study participants were then divided into groups based on these topics. Results from laboratory tests, including blood glucose level, triglycerides, and estimated glomerular filtration rate, were compared between each group, and these results were then compared with those obtained by hierarchical clustering. If a significant (p < 0.05) difference was observed in any of the laboratory measurements between groups, it was considered to indicate a questionnaire response pattern corresponding to the value of the test result. A comparison between the latent topic model and hierarchical clustering grouping revealed that, in the latent topic model method, a small group of participants who reported having subjective signs of urinary disorder were allocated to a single group. The latent topic model is useful for extracting characteristics from a small number of groups from questionnaires with a large number of items. These results show that, in addition to chief complaints and history of past illness, questionnaire data obtained during medical checkups can serve as useful judgment criteria for assessing the conditions of patients.

Accuracy Assessment of Crown Delineation Methods for the Individual Trees Using LIDAR Data

NASA Astrophysics Data System (ADS)

Chang, K. T.; Lin, C.; Lin, Y. C.; Liu, J. K.

2016-06-01

Forest canopy density and height are used as variables in a number of environmental applications, including the estimation of biomass, forest extent and condition, and biodiversity. The airborne Light Detection and Ranging (LiDAR) is very useful to estimate forest canopy parameters according to the generated canopy height models (CHMs). The purpose of this work is to introduce an algorithm to delineate crown parameters, e.g. tree height and crown radii based on the generated rasterized CHMs. And accuracy assessment for the extraction of volumetric parameters of a single tree is also performed via manual measurement using corresponding aerial photo pairs. A LiDAR dataset of a golf course acquired by Leica ALS70-HP is used in this study. Two algorithms, i.e. a traditional one with the subtraction of a digital elevation model (DEM) from a digital surface model (DSM), and a pit-free approach are conducted to generate the CHMs firstly. Then two algorithms, a multilevel morphological active-contour (MMAC) and a variable window filter (VWF), are implemented and used in this study for individual tree delineation. Finally, experimental results of two automatic estimation methods for individual trees can be evaluated with manually measured stand-level parameters, i.e. tree height and crown diameter. The resulting CHM generated by a simple subtraction is full of empty pixels (called "pits") that will give vital impact on subsequent analysis for individual tree delineation. The experimental results indicated that if more individual trees can be extracted, tree crown shape will became more completely in the CHM data after the pit-free process.

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.

Evaluation of wound healing activity of root of Mimosa pudica.

PubMed

Kokane, Dnyaneshwar D; More, Rahul Y; Kale, Mandar B; Nehete, Minakshi N; Mehendale, Prachi C; Gadgoli, Chhaya H

2009-07-15

Mimosa pudica, commonly known as touch-me-not, is used in folklore medicine in arresting bleeding and in skin diseases. There was no scientific evidence justifying the use of Mimosa pudica, therefore the present study was aimed at evaluation of wound healing activity of the plant. In the present study the roots of Mimosa pudica were studied for wound healing activity by incorporating the methanolic and the total aqueous extract in simple ointment base B.P. in concentration of 0.5% (w/w), 1% (w/w) and 2% (w/w). Wound healing activity was studied in three types of model in rats viz. excision, incision and estimation of biochemical parameter. In case of the excision wound model wound contraction and period of epithelization was studied while in incision wound model was evaluated by determining tensile strength and hydroxyproline content in the scab. Treatment of wound with ointment containing 2% (w/w) the methanolic and 2% (w/w) the total aqueous extract exhibited significant (P<0.001) wound healing activity. The methanolic and total aqueous extracts were analyzed for total phenols content equivalent to Gallic acid. The content of total phenols was 11% (w/w) and 17% (w/w) in methanolic and total aqueous extract respectively. The methanolic extract exhibited good wound healing activity probably due to phenols constituents.

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.

Model, analysis, and evaluation of the effects of analog VLSI arithmetic on linear subspace-based image recognition.

PubMed

Carvajal, Gonzalo; Figueroa, Miguel

2014-07-01

Typical image recognition systems operate in two stages: feature extraction to reduce the dimensionality of the input space, and classification based on the extracted features. Analog Very Large Scale Integration (VLSI) is an attractive technology to achieve compact and low-power implementations of these computationally intensive tasks for portable embedded devices. However, device mismatch limits the resolution of the circuits fabricated with this technology. Traditional layout techniques to reduce the mismatch aim to increase the resolution at the transistor level, without considering the intended application. Relating mismatch parameters to specific effects in the application level would allow designers to apply focalized mismatch compensation techniques according to predefined performance/cost tradeoffs. This paper models, analyzes, and evaluates the effects of mismatched analog arithmetic in both feature extraction and classification circuits. For the feature extraction, we propose analog adaptive linear combiners with on-chip learning for both Least Mean Square (LMS) and Generalized Hebbian Algorithm (GHA). Using mathematical abstractions of analog circuits, we identify mismatch parameters that are naturally compensated during the learning process, and propose cost-effective guidelines to reduce the effect of the rest. For the classification, we derive analog models for the circuits necessary to implement Nearest Neighbor (NN) approach and Radial Basis Function (RBF) networks, and use them to emulate analog classifiers with standard databases of face and hand-writing digits. Formal analysis and experiments show how we can exploit adaptive structures and properties of the input space to compensate the effects of device mismatch at the application level, thus reducing the design overhead of traditional layout techniques. Results are also directly extensible to multiple application domains using linear subspace methods. Copyright © 2014 Elsevier Ltd. All rights reserved.

Extraction optimization of mucilage from Basil (Ocimum basilicum L.) seeds using response surface methodology.

PubMed

Nazir, Sadaf; Wani, Idrees Ahmed; Masoodi, Farooq Ahmad

2017-05-01

Aqueous extraction of basil seed mucilage was optimized using response surface methodology. A Central Composite Rotatable Design (CCRD) for modeling of three independent variables: temperature (40-91 °C); extraction time (1.6-3.3 h) and water/seed ratio (18:1-77:1) was used to study the response for yield. Experimental values for extraction yield ranged from 7.86 to 20.5 g/100 g. Extraction yield was significantly ( P  < 0.05) affected by all the variables. Temperature and water/seed ratio were found to have pronounced effect while the extraction time was found to have minor possible effects. Graphical optimization determined the optimal conditions for the extraction of mucilage. The optimal condition predicted an extraction yield of 20.49 g/100 g at 56.7 °C, 1.6 h, and a water/seed ratio of 66.84:1. Optimal conditions were determined to obtain highest extraction yield. Results indicated that water/seed ratio was the most significant parameter, followed by temperature and time.

Appraisal on the wound healing activity of different extracts obtained from Aegle marmelos and Mucuna pruriens by in vivo experimental models.

PubMed

Toppo, F A; Pawar, R S

2016-01-01

The use of a simple and reproducible model is inevitable for an objective statement of the effects of external factors on wound healing. Hence, the present study was conducted to evaluate wound healing activities of sequential different extracts of Aegle marmelos leaves (AM) and Mucuna pruriens seeds (MP) by in vivo experimental models. Wistar albino rats were subjected to excision, incision and dead space wounds measuring approximately 250 mm2, 3 cm and implanting sterilized polyvinyl chloride tube on the back of each rat near either side of the vertebral column respectively. The experimental animals were randomized into eight groups (n = 6), control, standard and treatment groups. Hydrogel of different extracts were applied topically once daily. The parameters observed were percentage of wound contraction, epithelization period, tensile strength, hydroxyproline content of the granulation tissue, and histological changes during wound healing. The statistical study revealed that in excision, incision, and dead space wound models all formulations have significant (P < 0.01) wound healing potential. However, methanolic extract formulation was found to be superior to all other treatments as evidenced by rapid wound contraction, lesser number of days required for complete epithelization, increased tensile strength and significant increase in hydroxyproline content. As compared to the reference standard treated group the wound healing process of the experimental groups was decelerated. All extracts obtained from AM and MP facilitated the wound healing process in all experimental models.

Electroencephalography Based Fusion Two-Dimensional (2D)-Convolution Neural Networks (CNN) Model for Emotion Recognition System.

PubMed

Kwon, Yea-Hoon; Shin, Sae-Byuk; Kim, Shin-Dug

2018-04-30

The purpose of this study is to improve human emotional classification accuracy using a convolution neural networks (CNN) model and to suggest an overall method to classify emotion based on multimodal data. We improved classification performance by combining electroencephalogram (EEG) and galvanic skin response (GSR) signals. GSR signals are preprocessed using by the zero-crossing rate. Sufficient EEG feature extraction can be obtained through CNN. Therefore, we propose a suitable CNN model for feature extraction by tuning hyper parameters in convolution filters. The EEG signal is preprocessed prior to convolution by a wavelet transform while considering time and frequency simultaneously. We use a database for emotion analysis using the physiological signals open dataset to verify the proposed process, achieving 73.4% accuracy, showing significant performance improvement over the current best practice models.

Optimisation of Ethanol-Reflux Extraction of Saponins from Steamed Panax notoginseng by Response Surface Methodology and Evaluation of Hematopoiesis Effect.

PubMed

Hu, Yupiao; Cui, Xiuming; Zhang, Zejun; Chen, Lijuan; Zhang, Yiming; Wang, Chengxiao; Yang, Xiaoyan; Qu, Yuan; Xiong, Yin

2018-05-17

The present study aims to optimize the ethanol-reflux extraction conditions for extracting saponins from steamed Panax notoginseng (SPN). Four variables including the extraction time (0.5⁻2.5 h), ethanol concentration (50⁻90%), water to solid ratio (W/S, 8⁻16), and times of extraction (1⁻5) were investigated by using the Box-Behnken design response surface methodology (BBD-RSM). For each response, a second-order polynomial model with high R² values (>0.9690) was developed using multiple linear regression analysis and the optimum conditions to maximize the yield (31.96%), content (70.49 mg/g), and antioxidant activity (EC 50 value of 0.0421 mg/mL) for saponins extracted from SPN were obtained with a extraction time of 1.51 h, ethanol concentration of 60%, extraction done 3 times, and a W/S of 10. The experimental values were in good consistency with the predicted ones. In addition, the extracted SPN saponins could significantly increase the levels of blood routine parameters compared with the model group (p < 0.01) and there was no significant difference in the hematopoiesis effect between the SPN group and the SPN saponins group, of which the dose was 15 times lower than the former one. It is suggested that the SPN saponins extracted by the optimized method had similar functions of "blood tonifying" at a much lower dose.

Parameter estimation for lithium ion batteries

NASA Astrophysics Data System (ADS)

Santhanagopalan, Shriram

With an increase in the demand for lithium based batteries at the rate of about 7% per year, the amount of effort put into improving the performance of these batteries from both experimental and theoretical perspectives is increasing. There exist a number of mathematical models ranging from simple empirical models to complicated physics-based models to describe the processes leading to failure of these cells. The literature is also rife with experimental studies that characterize the various properties of the system in an attempt to improve the performance of lithium ion cells. However, very little has been done to quantify the experimental observations and relate these results to the existing mathematical models. In fact, the best of the physics based models in the literature show as much as 20% discrepancy when compared to experimental data. The reasons for such a big difference include, but are not limited to, numerical complexities involved in extracting parameters from experimental data and inconsistencies in interpreting directly measured values for the parameters. In this work, an attempt has been made to implement simplified models to extract parameter values that accurately characterize the performance of lithium ion cells. The validity of these models under a variety of experimental conditions is verified using a model discrimination procedure. Transport and kinetic properties are estimated using a non-linear estimation procedure. The initial state of charge inside each electrode is also maintained as an unknown parameter, since this value plays a significant role in accurately matching experimental charge/discharge curves with model predictions and is not readily known from experimental data. The second part of the dissertation focuses on parameters that change rapidly with time. For example, in the case of lithium ion batteries used in Hybrid Electric Vehicle (HEV) applications, the prediction of the State of Charge (SOC) of the cell under a variety of road conditions is important. An algorithm to predict the SOC in time intervals as small as 5 ms is of critical demand. In such cases, the conventional non-linear estimation procedure is not time-effective. There exist methodologies in the literature, such as those based on fuzzy logic; however, these techniques require a lot of computational storage space. Consequently, it is not possible to implement such techniques on a micro-chip for integration as a part of a real-time device. The Extended Kalman Filter (EKF) based approach presented in this work is a first step towards developing an efficient method to predict online, the State of Charge of a lithium ion cell based on an electrochemical model. The final part of the dissertation focuses on incorporating uncertainty in parameter values into electrochemical models using the polynomial chaos theory (PCT).

Sensitivity of drainage morphometry based hydrological response (GIUH) of a river basin to the spatial resolution of DEM data

NASA Astrophysics Data System (ADS)

Sahoo, Ramendra; Jain, Vikrant

2018-02-01

Drainage network pattern and its associated morphometric ratios are some of the important plan form attributes of a drainage basin. Extraction of these attributes for any basin is usually done by spatial analysis of the elevation data of that basin. These planform attributes are further used as input data for studying numerous process-response interactions inside the physical premise of the basin. One of the important uses of the morphometric ratios is its usage in the derivation of hydrologic response of a basin using GIUH concept. Hence, accuracy of the basin hydrological response to any storm event depends upon the accuracy with which, the morphometric ratios can be estimated. This in turn, is affected by the spatial resolution of the source data, i.e. the digital elevation model (DEM). We have estimated the sensitivity of the morphometric ratios and the GIUH derived hydrograph parameters, to the resolution of source data using a 30 meter and a 90 meter DEM. The analysis has been carried out for 50 drainage basins in a mountainous catchment. A simple and comprehensive algorithm has been developed for estimation of the morphometric indices from a stream network. We have calculated all the morphometric parameters and the hydrograph parameters for each of these basins extracted from two different DEMs, with different spatial resolutions. Paired t-test and Sign test were used for the comparison. Our results didn't show any statistically significant difference among any of the parameters calculated from the two source data. Along with the comparative study, a first-hand empirical analysis about the frequency distribution of the morphometric and hydrologic response parameters has also been communicated. Further, a comparison with other hydrological models suggests that plan form morphometry based GIUH model is more consistent with resolution variability in comparison to topographic based hydrological model.

Nonlinear Acoustical Assessment of Precipitate Nucleation

NASA Technical Reports Server (NTRS)

Cantrell, John H.; Yost, William T.

2004-01-01

The purpose of the present work is to show that measurements of the acoustic nonlinearity parameter in heat treatable alloys as a function of heat treatment time can provide quantitative information about the kinetics of precipitate nucleation and growth in such alloys. Generally, information on the kinetics of phase transformations is obtained from time-sequenced electron microscopical examination and differential scanning microcalorimetry. The present nonlinear acoustical assessment of precipitation kinetics is based on the development of a multiparameter analytical model of the effects on the nonlinearity parameter of precipitate nucleation and growth in the alloy system. A nonlinear curve fit of the model equation to the experimental data is then used to extract the kinetic parameters related to the nucleation and growth of the targeted precipitate. The analytical model and curve fit is applied to the assessment of S' precipitation in aluminum alloy 2024 during artificial aging from the T4 to the T6 temper.

Comparison of Atmospheric Parameters Derived from In-Situ and Hyper-/Multispectral Remote Sensing Data of Beautiful Bavarian Lakes

NASA Astrophysics Data System (ADS)

Riedel, S.; Gege, P.; Schneider, M.; Pfug, B.; Oppelt, N.

2016-08-01

Atmospheric correction is a critical step and can be a limiting factor in the extraction of aquatic ecosystem parameters from remote sensing data of coastal and lake waters. Atmospheric correction models commonly in use for open ocean water and land surfaces can lead to large errors when applied to hyperspectral images taken from satellite or aircraft. The main problems arise from uncertainties in aerosol parameters and neglecting the adjacency effect, which originates from multiple scattering of upwelling radiance from the surrounding land. To better understand the challenges for developing an atmospheric correction model suitable for lakes, we compare atmospheric parameters derived from Sentinel- 2A and airborne hyperspectral data (HySpex) of two Bavarian lakes (Klostersee, Lake Starnberg) with in-situ measurements performed with RAMSES and Ibsen spectrometer systems and a Microtops sun photometer.

A three-dimensional virtual environment for modeling mechanical cardiopulmonary interactions.

PubMed

Kaye, J M; Primiano, F P; Metaxas, D N

1998-06-01

We have developed a real-time computer system for modeling mechanical physiological behavior in an interactive, 3-D virtual environment. Such an environment can be used to facilitate exploration of cardiopulmonary physiology, particularly in situations that are difficult to reproduce clinically. We integrate 3-D deformable body dynamics with new, formal models of (scalar) cardiorespiratory physiology, associating the scalar physiological variables and parameters with the corresponding 3-D anatomy. Our framework enables us to drive a high-dimensional system (the 3-D anatomical models) from one with fewer parameters (the scalar physiological models) because of the nature of the domain and our intended application. Our approach is amenable to modeling patient-specific circumstances in two ways. First, using CT scan data, we apply semi-automatic methods for extracting and reconstructing the anatomy to use in our simulations. Second, our scalar physiological models are defined in terms of clinically measurable, patient-specific parameters. This paper describes our approach, problems we have encountered and a sample of results showing normal breathing and acute effects of pneumothoraces.

Optimization and uncertainty assessment of strongly nonlinear groundwater models with high parameter dimensionality

NASA Astrophysics Data System (ADS)

Keating, Elizabeth H.; Doherty, John; Vrugt, Jasper A.; Kang, Qinjun

2010-10-01

Highly parameterized and CPU-intensive groundwater models are increasingly being used to understand and predict flow and transport through aquifers. Despite their frequent use, these models pose significant challenges for parameter estimation and predictive uncertainty analysis algorithms, particularly global methods which usually require very large numbers of forward runs. Here we present a general methodology for parameter estimation and uncertainty analysis that can be utilized in these situations. Our proposed method includes extraction of a surrogate model that mimics key characteristics of a full process model, followed by testing and implementation of a pragmatic uncertainty analysis technique, called null-space Monte Carlo (NSMC), that merges the strengths of gradient-based search and parameter dimensionality reduction. As part of the surrogate model analysis, the results of NSMC are compared with a formal Bayesian approach using the DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm. Such a comparison has never been accomplished before, especially in the context of high parameter dimensionality. Despite the highly nonlinear nature of the inverse problem, the existence of multiple local minima, and the relatively large parameter dimensionality, both methods performed well and results compare favorably with each other. Experiences gained from the surrogate model analysis are then transferred to calibrate the full highly parameterized and CPU intensive groundwater model and to explore predictive uncertainty of predictions made by that model. The methodology presented here is generally applicable to any highly parameterized and CPU-intensive environmental model, where efficient methods such as NSMC provide the only practical means for conducting predictive uncertainty analysis.

Simulation modeling for stratified breast cancer screening - a systematic review of cost and quality of life assumptions.

PubMed

Arnold, Matthias

2017-12-02

The economic evaluation of stratified breast cancer screening gains momentum, but produces also very diverse results. Systematic reviews so far focused on modeling techniques and epidemiologic assumptions. However, cost and utility parameters received only little attention. This systematic review assesses simulation models for stratified breast cancer screening based on their cost and utility parameters in each phase of breast cancer screening and care. A literature review was conducted to compare economic evaluations with simulation models of personalized breast cancer screening. Study quality was assessed using reporting guidelines. Cost and utility inputs were extracted, standardized and structured using a care delivery framework. Studies were then clustered according to their study aim and parameters were compared within the clusters. Eighteen studies were identified within three study clusters. Reporting quality was very diverse in all three clusters. Only two studies in cluster 1, four studies in cluster 2 and one study in cluster 3 scored high in the quality appraisal. In addition to the quality appraisal, this review assessed if the simulation models were consistent in integrating all relevant phases of care, if utility parameters were consistent and methodological sound and if cost were compatible and consistent in the actual parameters used for screening, diagnostic work up and treatment. Of 18 studies, only three studies did not show signs of potential bias. This systematic review shows that a closer look into the cost and utility parameter can help to identify potential bias. Future simulation models should focus on integrating all relevant phases of care, using methodologically sound utility parameters and avoiding inconsistent cost parameters.

Estimating Discharge in Low-Order Rivers With High-Resolution Aerial Imagery

NASA Astrophysics Data System (ADS)

King, Tyler V.; Neilson, Bethany T.; Rasmussen, Mitchell T.

2018-02-01

Remote sensing of river discharge promises to augment in situ gauging stations, but the majority of research in this field focuses on large rivers (>50 m wide). We present a method for estimating volumetric river discharge in low-order (<50 m wide) rivers from remotely sensed data by coupling high-resolution imagery with one-dimensional hydraulic modeling at so-called virtual gauging stations. These locations were identified as locations where the river contracted under low flows, exposing a substantial portion of the river bed. Topography of the exposed river bed was photogrammetrically extracted from high-resolution aerial imagery while the geometry of the remaining inundated portion of the channel was approximated based on adjacent bank topography and maximum depth assumptions. Full channel bathymetry was used to create hydraulic models that encompassed virtual gauging stations. Discharge for each aerial survey was estimated with the hydraulic model by matching modeled and remotely sensed wetted widths. Based on these results, synthetic width-discharge rating curves were produced for each virtual gauging station. In situ observations were used to determine the accuracy of wetted widths extracted from imagery (mean error 0.36 m), extracted bathymetry (mean vertical RMSE 0.23 m), and discharge (mean percent error 7% with a standard deviation of 6%). Sensitivity analyses were conducted to determine the influence of inundated channel bathymetry and roughness parameters on estimated discharge. Comparison of synthetic rating curves produced through sensitivity analyses show that reasonable ranges of parameter values result in mean percent errors in predicted discharges of 12%-27%.

Development and biological evaluation of Gymnema sylvestre extract-loaded nonionic surfactant-based niosomes.

PubMed

Kamble, Bhagyashree; Talreja, Seema; Gupta, Ankur; Patil, Dada; Pathak, Deepa; Moothedath, Ismail; Duraiswamy, Basavan

2013-08-01

To develop and characterize Gymnema sylvestre extract-loaded niosomes using nonionic surfactants, and to evaluate their antihyperglycemic efficacy in comparison with the parent extract. Nonionic surfactant-based G. sylvestre extract-loaded niosomes were prepared using the thin-film hydration method. The optimized formulation was screened for entrapment efficiency of the constituents, as well as other parameters such as release kinetics, vesicle size, zeta-potential and stability studies. The parent extract and optimized niosomal formulation were evaluated for their antihyperglycemic potential in an alloxan-induced diabetic animal model. Niosomes prepared using Span™ 40 (SD Fine Chemicals Ltd, Mumbai, India) provided sterically stable vesicles 229.5 nm in size with zeta-potential and entrapment efficiency of 150.86 mV and 85.3 ± 4.5%, respectively. The surface morphology of vesicles was confirmed to be spherical by scanning electron microscopy studies. An in vitro release study demonstrated 77.4% of phytoconstituents release within 24 h. The niosome formulation demonstrated significant blood glucose level reduction in an oral glucose tolerance test, and increased antihyperglycemic activity compared with the parent extract in an alloxan-induced diabetic model. This study reveals the merits of G. sylvestre extract-loaded niosomes, and justifies the potential of niosomes for improving the efficacy of G. sylvestre extract as antidiabetic. Original submitted 30 March 2012; Revised submitted 29 August 2012; Published online 24 December 2012.

Astrophysical Model Selection in Gravitational Wave Astronomy

NASA Technical Reports Server (NTRS)

Adams, Matthew R.; Cornish, Neil J.; Littenberg, Tyson B.

2012-01-01

Theoretical studies in gravitational wave astronomy have mostly focused on the information that can be extracted from individual detections, such as the mass of a binary system and its location in space. Here we consider how the information from multiple detections can be used to constrain astrophysical population models. This seemingly simple problem is made challenging by the high dimensionality and high degree of correlation in the parameter spaces that describe the signals, and by the complexity of the astrophysical models, which can also depend on a large number of parameters, some of which might not be directly constrained by the observations. We present a method for constraining population models using a hierarchical Bayesian modeling approach which simultaneously infers the source parameters and population model and provides the joint probability distributions for both. We illustrate this approach by considering the constraints that can be placed on population models for galactic white dwarf binaries using a future space-based gravitational wave detector. We find that a mission that is able to resolve approximately 5000 of the shortest period binaries will be able to constrain the population model parameters, including the chirp mass distribution and a characteristic galaxy disk radius to within a few percent. This compares favorably to existing bounds, where electromagnetic observations of stars in the galaxy constrain disk radii to within 20%.

[Application of CWT to extract characteristic monitoring parameters during spine surgery].

PubMed

Chen, Penghui; Wu, Baoming; Hu, Yong

2005-10-01

It is necessary to monitor intraoperative spinal function in order to prevent spinal neurological deficit during spine surgery. This study aims to extract characteristic electrophysiological monitoring parameters during surgical treatment of scoliosis. The problem, "the monitoring parameters in time domain are of great variability and are sensitive to noise", may also be solved in this study. By use of continuous wavelet transform to analyze the intraoperative cortical somatosensory evoked potential (CSEP), three new characteristic monitoring parameters in time-frequency domain (TFD) are extracted. The results indicate that the variability of CSEP characteristic parameters in TFD is lower than the variability of those in time domain. Therefore, the TFD characteristic monitoring parameters are more stable and reliable parameters of latency and amplitude in time domain. The application of TFD monitoring parameters during spine surgery may avoid spinal injury effectively.

Extraction of Rocky Desertification from Disp Imagery: a Case Study of Liupanshui, Guizhou, China

NASA Astrophysics Data System (ADS)

Zhou, G.; Wu, Z.; Wang, W.; Shi, Y.; Mao, G.; Huang, Y.; Jia, B.; Gao, G.; Chen, P.

2017-09-01

Karst rocky desertification is a typical type of land degradation in Guizhou Province, China. It causes great ecological and economical implications to the local people. This paper utilized the declassified intelligence satellite photography (DISP) of 1960s to extract the karst rocky desertification area to analyze the early situation of karst rocky desertification in Liupanshui, Guizhou, China. Due to the lack of ground control points and parameters of the satellite, a polynomial orthographic correction model with considering altitude difference correction is proposed for orthorectification of DISP imagery. With the proposed model, the 96 DISP images from four missions are orthorectified. The images are assembled into a seamless image map of the karst area of Guizhou, China. The assembled image map is produced to thematic map of karst rocky desertification by visual interpretation in Liupanshui city. With the assembled image map, extraction of rocky desertification is conducted.

A Model Parameter Extraction Method for Dielectric Barrier Discharge Ozone Chamber using Differential Evolution

NASA Astrophysics Data System (ADS)

Amjad, M.; Salam, Z.; Ishaque, K.

2014-04-01

In order to design an efficient resonant power supply for ozone gas generator, it is necessary to accurately determine the parameters of the ozone chamber. In the conventional method, the information from Lissajous plot is used to estimate the values of these parameters. However, the experimental setup for this purpose can only predict the parameters at one operating frequency and there is no guarantee that it results in the highest ozone gas yield. This paper proposes a new approach to determine the parameters using a search and optimization technique known as Differential Evolution (DE). The desired objective function of DE is set at the resonance condition and the chamber parameter values can be searched regardless of experimental constraints. The chamber parameters obtained from the DE technique are validated by experiment.

Machine Learning Techniques for Global Sensitivity Analysis in Climate Models

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Simplified and quick electrical modeling for dye sensitized solar cells: An experimental and theoretical investigation

NASA Astrophysics Data System (ADS)

de Andrade, Rocelito Lopes; de Oliveira, Matheus Costa; Kohlrausch, Emerson Cristofer; Santos, Marcos José Leite

2018-05-01

This work presents a new and simple method for determining IPH (current source dependent on luminance), I0 (reverse saturation current), n (ideality factor), RP and RS, (parallel and series resistance) to build an electrical model for dye sensitized solar cells (DSSCs). The electrical circuit parameters used in the simulation and to generate theoretical curves for the single diode electrical model were extracted from I-V curves of assembled DSSCs. Model validation was performed by assembling five different types of DSSCs and evaluating the following parameters: effect of a TiO2 blocking/adhesive layer, thickness of the TiO2 layer and the presence of a light scattering layer. In addition, irradiance, temperature, series and parallel resistance, ideality factor and reverse saturation current were simulated.

Parameters optimization of supercritical fluid-CO2 extracts of frankincense using response surface methodology and its pharmacodynamics effects.

PubMed

Zhou, Jing; Ma, Xing-miao; Qiu, Bi-Han; Chen, Jun-xia; Bian, Lin; Pan, Lin-mei

2013-01-01

The volatile oil parts of frankincense (Boswellia carterii Birdw.) were extracted with supercritical carbon dioxide under constant pressure (15, 20, or 25 MPa) and fixed temperature (40, 50, or 60°C), given time (60, 90, or 120 min) aiming at the acquisition of enriched fractions containing octyl acetate, compounds of pharmaceutical interest. A mathematical model was created by Box-Behnken design, a popular template for response surface methodology, for the extraction process. The response value was characterized by synthetical score, which comprised yields accounting for 20% and content of octyl acetate for 80%. The content of octyl acetate was determined by GC. The supercritical fluid extraction showed higher selectivity than conventional steam distillation. Supercritical fluid-CO(2) for extracting frankincense under optimum condition was of great validity, which was also successfully verified by the pharmacological experiments. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Extraction of gelatin from salmon (Salmo salar) fish skin using trypsin-aided process: optimization by Plackett-Burman and response surface methodological approaches.

PubMed

Fan, HuiYin; Dumont, Marie-Josée; Simpson, Benjamin K

2017-11-01

Gelatin from salmon ( Salmo salar ) skin with high molecular weight protein chains ( α -chains) was extracted using trypsin-aided process. Response surface methodology was used to optimise the extraction parameters. Yield, hydroxyproline content and protein electrophoretic profile via sodium dodecyl sulfate-polyacrylamide gel electrophoresis analysis of gelatin were used as responses in the optimization study. The optimum conditions were determined as: trypsin concentration at 1.49 U/g; extraction temperature at 45 °C; and extraction time at 6 h 16 min. This response surface optimized model was significant and produced an experimental value (202.04 ± 8.64%) in good agreement with the predicted value (204.19%). Twofold higher yields of gelatin with high molecular weight protein chains were achieved in the optimized process with trypsin treatment when compared to the process without trypsin.

Optimization of Supercritical Carbon Dioxide Extraction of Eucommia ulmoides Seed Oil and Quality Evaluation of the Oil.

PubMed

Zhang, Zhen-Shan; Liu, Yu-Lan; Che, Li-Ming

2018-03-01

Supercritical carbon dioxide extraction (SC-CO 2 ) technology was used to extract oil from Eucommia ulmoides seed. The optimum conditions and significant parameters in SC-CO 2 were obtained using response surface methodology (RSM). The qualities of the extracted oil were evaluated by physicochemical properties, fatty acid composition, vitamin E composition. It was found that the optimum extraction parameters were at pressure of 37 MPa, temperature of 40°C, extraction time of 125 min and CO 2 flow rate of 2.6 SL/min. Pressure, temperature and time were identified as significant parameter effecting on extraction yield. The importance of evaluated parameters decreased in the order of pressure > extraction time > temperature > CO 2 flow rate. GC analysis indicated that E. ulmoides seed oil contained about 61% of linolenic acid and its fatty acid composition was similar with that of flaxseed oil and perilla oil. The content and composition of vitamin E was determined using HPLC. The E. ulmoides seed oil was rich in vitamin E (190.72 mg/100 g), the predominant vitamin E isomers were γ- tocopherol and δ- tocopherol, which accounted for 70.87% and 24.81% of the total vitamin E, respectively. The high yield and good physicochemical properties of extracted oil support the notion that SC-CO 2 technology is an effective technique for extracting oil from E. ulmoides seed.

Simulating the dynamics of polycyclic aromatic hydrocarbon (PAH) in contaminated soil through composting by COP-Compost model.

PubMed

Zhang, Yuan; Guan, Yidong; Shi, Qi

2015-02-01

Organic pollutants (OPs) are potentially present in composts, and the assessment of their content and bioaccessibility in these composts is of paramount importance to minimize the risk of soil contamination and improve soil fertility. In this work, integration of the dynamics of organic carbon (OC) and OPs in an overall experimental framework is first proposed and adopted to validate the applicability of the COP-Compost model and to calibrate the model parameters on the basis of what has been achieved with the COP-Compost model. The COP-Compost model was evaluated via composting experiments containing 16 US Environmental Protection Agency (USEPA) polycyclic aromatic hydrocarbons (PAHs) and the sorption coefficient (Kd) values of two types of OP: fluorenthene (FLT) and pyrene (PHE). In our study, these compounds are used to characterize the sequential extraction and are quantified as soluble, sorbed, and non-extractable fractions. The model was calibrated, and coupling the OC and OP modules improved the simulation of the OP behavior and bioaccessibility during composting. The results show good agreement between the simulated and experimental results describing the evolution of different organic pollutants using the OP module, as well as the coupling module. However, no clear relationship is found between the Kd and the property of organic fractions. Further estimation of parameters is still necessary to modify the insufficiency of this present research.

Variable frame rate transmission - A review of methodology and application to narrow-band LPC speech coding

NASA Astrophysics Data System (ADS)

Viswanathan, V. R.; Makhoul, J.; Schwartz, R. M.; Huggins, A. W. F.

1982-04-01

The variable frame rate (VFR) transmission methodology developed, implemented, and tested in the years 1973-1978 for efficiently transmitting linear predictive coding (LPC) vocoder parameters extracted from the input speech at a fixed frame rate is reviewed. With the VFR method, parameters are transmitted only when their values have changed sufficiently over the interval since their preceding transmission. Two distinct approaches to automatic implementation of the VFR method are discussed. The first bases the transmission decisions on comparisons between the parameter values of the present frame and the last transmitted frame. The second, which is based on a functional perceptual model of speech, compares the parameter values of all the frames that lie in the interval between the present frame and the last transmitted frame against a linear model of parameter variation over that interval. Also considered is the application of VFR transmission to the design of narrow-band LPC speech coders with average bit rates of 2000-2400 bts/s.

Hierarchial mark-recapture models: a framework for inference about demographic processes

USGS Publications Warehouse

Link, W.A.; Barker, R.J.

2004-01-01

The development of sophisticated mark-recapture models over the last four decades has provided fundamental tools for the study of wildlife populations, allowing reliable inference about population sizes and demographic rates based on clearly formulated models for the sampling processes. Mark-recapture models are now routinely described by large numbers of parameters. These large models provide the next challenge to wildlife modelers: the extraction of signal from noise in large collections of parameters. Pattern among parameters can be described by strong, deterministic relations (as in ultrastructural models) but is more flexibly and credibly modeled using weaker, stochastic relations. Trend in survival rates is not likely to be manifest by a sequence of values falling precisely on a given parametric curve; rather, if we could somehow know the true values, we might anticipate a regression relation between parameters and explanatory variables, in which true value equals signal plus noise. Hierarchical models provide a useful framework for inference about collections of related parameters. Instead of regarding parameters as fixed but unknown quantities, we regard them as realizations of stochastic processes governed by hyperparameters. Inference about demographic processes is based on investigation of these hyperparameters. We advocate the Bayesian paradigm as a natural, mathematically and scientifically sound basis for inference about hierarchical models. We describe analysis of capture-recapture data from an open population based on hierarchical extensions of the Cormack-Jolly-Seber model. In addition to recaptures of marked animals, we model first captures of animals and losses on capture, and are thus able to estimate survival probabilities w (i.e., the complement of death or permanent emigration) and per capita growth rates f (i.e., the sum of recruitment and immigration rates). Covariation in these rates, a feature of demographic interest, is explicitly described in the model.

Parameter estimation for compact binary coalescence signals with the first generation gravitational-wave detector network

NASA Astrophysics Data System (ADS)

Aasi, J.; Abadie, J.; Abbott, B. P.; Abbott, R.; Abbott, T. D.; Abernathy, M.; Accadia, T.; Acernese, F.; Adams, C.; Adams, T.; Addesso, P.; Adhikari, R.; Affeldt, C.; Agathos, M.; Agatsuma, K.; Ajith, P.; Allen, B.; Allocca, A.; Amador Ceron, E.; Amariutei, D.; Anderson, S. B.; Anderson, W. G.; Arai, K.; Araya, M. C.; Ast, S.; Aston, S. M.; Astone, P.; Atkinson, D.; Aufmuth, P.; Aulbert, C.; Aylott, B. E.; Babak, S.; Baker, P.; Ballardin, G.; Ballmer, S.; Bao, Y.; Barayoga, J. C. B.; Barker, D.; Barone, F.; Barr, B.; Barsotti, L.; Barsuglia, M.; Barton, M. A.; Bartos, I.; Bassiri, R.; Bastarrika, M.; Basti, A.; Batch, J.; Bauchrowitz, J.; Bauer, Th. S.; Bebronne, M.; Beck, D.; Behnke, B.; Bejger, M.; Beker, M. G.; Bell, A. S.; Bell, C.; Belopolski, I.; Benacquista, M.; Berliner, J. M.; Bertolini, A.; Betzwieser, J.; Beveridge, N.; Beyersdorf, P. T.; Bhadbade, T.; Bilenko, I. A.; Billingsley, G.; Birch, J.; Biswas, R.; Bitossi, M.; Bizouard, M. A.; Black, E.; Blackburn, J. K.; Blackburn, L.; Blair, D.; Bland, B.; Blom, M.; Bock, O.; Bodiya, T. P.; Bogan, C.; Bond, C.; Bondarescu, R.; Bondu, F.; Bonelli, L.; Bonnand, R.; Bork, R.; Born, M.; Boschi, V.; Bose, S.; Bosi, L.; Bouhou, B.; Braccini, S.; Bradaschia, C.; Brady, P. R.; Braginsky, V. B.; Branchesi, M.; Brau, J. E.; Breyer, J.; Briant, T.; Bridges, D. O.; Brillet, A.; Brinkmann, M.; Brisson, V.; Britzger, M.; Brooks, A. F.; Brown, D. A.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Burguet–Castell, J.; Buskulic, D.; Buy, C.; Byer, R. L.; Cadonati, L.; Cagnoli, G.; Calloni, E.; Camp, J. B.; Campsie, P.; Cannon, K.; Canuel, B.; Cao, J.; Capano, C. D.; Carbognani, F.; Carbone, L.; Caride, S.; Caudill, S.; Cavaglià, M.; Cavalier, F.; Cavalieri, R.; Cella, G.; Cepeda, C.; Cesarini, E.; Chalermsongsak, T.; Charlton, P.; Chassande-Mottin, E.; Chen, W.; Chen, X.; Chen, Y.; Chincarini, A.; Chiummo, A.; Cho, H. S.; Chow, J.; Christensen, N.; Chua, S. S. Y.; Chung, C. T. Y.; Chung, S.; Ciani, G.; Clara, F.; Clark, D. E.; Clark, J. A.; Clayton, J. H.; Cleva, F.; Coccia, E.; Cohadon, P.-F.; Colacino, C. N.; Colla, A.; Colombini, M.; Conte, A.; Conte, R.; Cook, D.; Corbitt, T. R.; Cordier, M.; Cornish, N.; Corsi, A.; Costa, C. A.; Coughlin, M.; Coulon, J.-P.; Couvares, P.; Coward, D. M.; Cowart, M.; Coyne, D. C.; Creighton, J. D. E.; Creighton, T. D.; Cruise, A. M.; Cumming, A.; Cunningham, L.; Cuoco, E.; Cutler, R. M.; Dahl, K.; Damjanic, M.; Danilishin, S. L.; D'Antonio, S.; Danzmann, K.; Dattilo, V.; Daudert, B.; Daveloza, H.; Davier, M.; Daw, E. J.; Dayanga, T.; De Rosa, R.; DeBra, D.; Debreczeni, G.; Degallaix, J.; Del Pozzo, W.; Dent, T.; Dergachev, V.; DeRosa, R.; Dhurandhar, S.; Di Fiore, L.; Di Lieto, A.; Di Palma, I.; Di Paolo Emilio, M.; Di Virgilio, A.; Díaz, M.; Dietz, A.; Donovan, F.; Dooley, K. L.; Doravari, S.; Dorsher, S.; Drago, M.; Drever, R. W. P.; Driggers, J. C.; Du, Z.; Dumas, J.-C.; Dwyer, S.; Eberle, T.; Edgar, M.; Edwards, M.; Effler, A.; Ehrens, P.; Endrőczi, G.; Engel, R.; Etzel, T.; Evans, K.; Evans, M.; Evans, T.; Factourovich, M.; Fafone, V.; Fairhurst, S.; Farr, B. F.; Farr, W. M.; Favata, M.; Fazi, D.; Fehrmann, H.; Feldbaum, D.; Feroz, F.; Ferrante, I.; Ferrini, F.; Fidecaro, F.; Finn, L. S.; Fiori, I.; Fisher, R. P.; Flaminio, R.; Foley, S.; Forsi, E.; Forte, L. A.; Fotopoulos, N.; Fournier, J.-D.; Franc, J.; Franco, S.; Frasca, S.; Frasconi, F.; Frede, M.; Frei, M. A.; Frei, Z.; Freise, A.; Frey, R.; Fricke, T. T.; Friedrich, D.; Fritschel, P.; Frolov, V. V.; Fujimoto, M.-K.; Fulda, P. J.; Fyffe, M.; Gair, J.; Galimberti, M.; Gammaitoni, L.; Garcia, J.; Garufi, F.; Gáspár, M. E.; Gelencser, G.; Gemme, G.; Genin, E.; Gennai, A.; Gergely, L. Á.; Ghosh, S.; Giaime, J. A.; Giampanis, S.; Giardina, K. D.; Giazotto, A.; Gil-Casanova, S.; Gill, C.; Gleason, J.; Goetz, E.; González, G.; Gorodetsky, M. L.; Goßler, S.; Gouaty, R.; Graef, C.; Graff, P. B.; Granata, M.; Grant, A.; Gray, C.; Greenhalgh, R. J. S.; Gretarsson, A. M.; Griffo, C.; Grote, H.; Grover, K.; Grunewald, S.; Guidi, G. M.; Guido, C.; Gupta, R.; Gustafson, E. K.; Gustafson, R.; Hallam, J. M.; Hammer, D.; Hammond, G.; Hanks, J.; Hanna, C.; Hanson, J.; Harms, J.; Harry, G. M.; Harry, I. W.; Harstad, E. D.; Hartman, M. T.; Haster, C.-J.; Haughian, K.; Hayama, K.; Hayau, J.-F.; Heefner, J.; Heidmann, A.; Heintze, M. C.; Heitmann, H.; Hello, P.; Hemming, G.; Hendry, M. A.; Heng, I. S.; Heptonstall, A. W.; Herrera, V.; Heurs, M.; Hewitson, M.; Hild, S.; Hoak, D.; Hodge, K. A.; Holt, K.; Holtrop, M.; Hong, T.; Hooper, S.; Hough, J.; Howell, E. J.; Hughey, B.; Husa, S.; Huttner, S. H.; Huynh-Dinh, T.; Ingram, D. R.; Inta, R.; Isogai, T.; Ivanov, A.; Izumi, K.; Jacobson, M.; James, E.; Jang, Y. J.; Jaranowski, P.; Jesse, E.; Johnson, W. W.; Jones, D. I.; Jones, R.; Jonker, R. J. G.; Ju, L.; Kalmus, P.; Kalogera, V.; Kandhasamy, S.; Kang, G.; Kanner, J. B.; Kasprzack, M.; Kasturi, R.; Katsavounidis, E.; Katzman, W.; Kaufer, H.; Kaufman, K.; Kawabe, K.; Kawamura, S.; Kawazoe, F.; Keitel, D.; Kelley, D.; Kells, W.; Keppel, D. G.; Keresztes, Z.; Khalaidovski, A.; Khalili, F. Y.; Khazanov, E. A.; Kim, B. K.; Kim, C.; Kim, H.; Kim, K.; Kim, N.; Kim, Y. M.; King, P. J.; Kinzel, D. L.; Kissel, J. S.; Klimenko, S.; Kline, J.; Kokeyama, K.; Kondrashov, V.; Koranda, S.; Korth, W. Z.; Kowalska, I.; Kozak, D.; Kringel, V.; Krishnan, B.; Królak, A.; Kuehn, G.; Kumar, P.; Kumar, R.; Kurdyumov, R.; Kwee, P.; Lam, P. K.; Landry, M.; Langley, A.; Lantz, B.; Lastzka, N.; Lawrie, C.; Lazzarini, A.; Le Roux, A.; Leaci, P.; Lee, C. H.; Lee, H. K.; Lee, H. M.; Leong, J. R.; Leonor, I.; Leroy, N.; Letendre, N.; Lhuillier, V.; Li, J.; Li, T. G. F.; Lindquist, P. E.; Litvine, V.; Liu, Y.; Liu, Z.; Lockerbie, N. A.; Lodhia, D.; Logue, J.; Lorenzini, M.; Loriette, V.; Lormand, M.; Losurdo, G.; Lough, J.; Lubinski, M.; Lück, H.; Lundgren, A. P.; Macarthur, J.; Macdonald, E.; Machenschalk, B.; MacInnis, M.; Macleod, D. M.; Mageswaran, M.; Mailand, K.; Majorana, E.; Maksimovic, I.; Malvezzi, V.; Man, N.; Mandel, I.; Mandic, V.; Mantovani, M.; Marchesoni, F.; Marion, F.; Márka, S.; Márka, Z.; Markosyan, A.; Maros, E.; Marque, J.; Martelli, F.; Martin, I. W.; Martin, R. M.; Marx, J. N.; Mason, K.; Masserot, A.; Matichard, F.; Matone, L.; Matzner, R. A.; Mavalvala, N.; Mazzolo, G.; McCarthy, R.; McClelland, D. E.; McGuire, S. C.; McIntyre, G.; McIver, J.; Meadors, G. D.; Mehmet, M.; Meier, T.; Melatos, A.; Melissinos, A. C.; Mendell, G.; Menéndez, D. F.; Mercer, R. A.; Meshkov, S.; Messenger, C.; Meyer, M. S.; Miao, H.; Michel, C.; Milano, L.; Miller, J.; Minenkov, Y.; Mingarelli, C. M. F.; Mitrofanov, V. P.; Mitselmakher, G.; Mittleman, R.; Moe, B.; Mohan, M.; Mohapatra, S. R. P.; Moraru, D.; Moreno, G.; Morgado, N.; Morgia, A.; Mori, T.; Morriss, S. R.; Mosca, S.; Mossavi, K.; Mours, B.; Mow–Lowry, C. M.; Mueller, C. L.; Mueller, G.; Mukherjee, S.; Mullavey, A.; Müller-Ebhardt, H.; Munch, J.; Murphy, D.; Murray, P. G.; Mytidis, A.; Nash, T.; Naticchioni, L.; Necula, V.; Nelson, J.; Neri, I.; Newton, G.; Nguyen, T.; Nishizawa, A.; Nitz, A.; Nocera, F.; Nolting, D.; Normandin, M. E.; Nuttall, L.; Ochsner, E.; O'Dell, J.; Oelker, E.; Ogin, G. H.; Oh, J. J.; Oh, S. H.; Oldenberg, R. G.; O'Reilly, B.; O'Shaughnessy, R.; Osthelder, C.; Ott, C. D.; Ottaway, D. J.; Ottens, R. S.; Overmier, H.; Owen, B. J.; Page, A.; Palladino, L.; Palomba, C.; Pan, Y.; Pankow, C.; Paoletti, F.; Paoletti, R.; Papa, M. A.; Parisi, M.; Pasqualetti, A.; Passaquieti, R.; Passuello, D.; Pedraza, M.; Penn, S.; Perreca, A.; Persichetti, G.; Phelps, M.; Pichot, M.; Pickenpack, M.; Piergiovanni, F.; Pierro, V.; Pihlaja, M.; Pinard, L.; Pinto, I. M.; Pitkin, M.; Pletsch, H. J.; Plissi, M. V.; Poggiani, R.; Pöld, J.; Postiglione, F.; Poux, C.; Prato, M.; Predoi, V.; Prestegard, T.; Price, L. R.; Prijatelj, M.; Principe, M.; Privitera, S.; Prodi, G. A.; Prokhorov, L. G.; Puncken, O.; Punturo, M.; Puppo, P.; Quetschke, V.; Quitzow-James, R.; Raab, F. J.; Rabeling, D. S.; Rácz, I.; Radkins, H.; Raffai, P.; Rakhmanov, M.; Ramet, C.; Rankins, B.; Rapagnani, P.; Raymond, V.; Re, V.; Reed, C. M.; Reed, T.; Regimbau, T.; Reid, S.; Reitze, D. H.; Ricci, F.; Riesen, R.; Riles, K.; Roberts, M.; Robertson, N. A.; Robinet, F.; Robinson, C.; Robinson, E. L.; Rocchi, A.; Roddy, S.; Rodriguez, C.; Rodruck, M.; Rolland, L.; Rollins, J. G.; Romano, R.; Romie, J. H.; Rosińska, D.; Röver, C.; Rowan, S.; Rüdiger, A.; Ruggi, P.; Ryan, K.; Salemi, F.; Sammut, L.; Sandberg, V.; Sankar, S.; Sannibale, V.; Santamaría, L.; Santiago-Prieto, I.; Santostasi, G.; Saracco, E.; Sassolas, B.; Sathyaprakash, B. S.; Saulson, P. R.; Savage, R. L.; Schilling, R.; Schnabel, R.; Schofield, R. M. S.; Schulz, B.; Schutz, B. F.; Schwinberg, P.; Scott, J.; Scott, S. M.; Seifert, F.; Sellers, D.; Sentenac, D.; Sergeev, A.; Shaddock, D. A.; Shaltev, M.; Shapiro, B.; Shawhan, P.; Shoemaker, D. H.; Sidery, T. L.; Siemens, X.; Sigg, D.; Simakov, D.; Singer, A.; Singer, L.; Sintes, A. M.; Skelton, G. R.; Slagmolen, B. J. J.; Slutsky, J.; Smith, J. R.; Smith, M. R.; Smith, R. J. E.; Smith-Lefebvre, N. D.; Somiya, K.; Sorazu, B.; Speirits, F. C.; Sperandio, L.; Stefszky, M.; Steinert, E.; Steinlechner, J.; Steinlechner, S.; Steplewski, S.; Stochino, A.; Stone, R.; Strain, K. A.; Strigin, S. E.; Stroeer, A. S.; Sturani, R.; Stuver, A. L.; Summerscales, T. Z.; Sung, M.; Susmithan, S.; Sutton, P. J.; Swinkels, B.; Szeifert, G.; Tacca, M.; Taffarello, L.; Talukder, D.; Tanner, D. B.; Tarabrin, S. P.; Taylor, R.; ter Braack, A. P. M.; Thomas, P.; Thorne, K. A.; Thorne, K. S.; Thrane, E.; Thüring, A.; Titsler, C.; Tokmakov, K. V.; Tomlinson, C.; Toncelli, A.; Tonelli, M.; Torre, O.; Torres, C. V.; Torrie, C. I.; Tournefier, E.; Travasso, F.; Traylor, G.; Tse, M.; Ugolini, D.; Vahlbruch, H.; Vajente, G.; van den Brand, J. F. J.; Van Den Broeck, C.; van der Putten, S.; van Veggel, A. A.; Vass, S.; Vasuth, M.; Vaulin, R.; Vavoulidis, M.; Vecchio, A.; Vedovato, G.; Veitch, J.; Veitch, P. J.; Venkateswara, K.; Verkindt, D.; Vetrano, F.; Viceré, A.; Villar, A. E.; Vinet, J.-Y.; Vitale, S.; Vocca, H.; Vorvick, C.; Vyatchanin, S. P.; Wade, A.; Wade, L.; Wade, M.; Waldman, S. J.; Wallace, L.; Wan, Y.; Wang, M.; Wang, X.; Wanner, A.; Ward, R. L.; Was, M.; Weinert, M.; Weinstein, A. J.; Weiss, R.; Welborn, T.; Wen, L.; Wessels, P.; West, M.; Westphal, T.; Wette, K.; Whelan, J. T.; Whitcomb, S. E.; White, D. J.; Whiting, B. F.; Wiesner, K.; Wilkinson, C.; Willems, P. A.; Williams, L.; Williams, R.; Willke, B.; Wimmer, M.; Winkelmann, L.; Winkler, W.; Wipf, C. C.; Wiseman, A. G.; Wittel, H.; Woan, G.; Wooley, R.; Worden, J.; Yablon, J.; Yakushin, I.; Yamamoto, H.; Yamamoto, K.; Yancey, C. C.; Yang, H.; Yeaton-Massey, D.; Yoshida, S.; Yvert, M.; Zadrożny, A.; Zanolin, M.; Zendri, J.-P.; Zhang, F.; Zhang, L.; Zhao, C.; Zotov, N.; Zucker, M. E.; Zweizig, J.

2013-09-01

Compact binary systems with neutron stars or black holes are one of the most promising sources for ground-based gravitational-wave detectors. Gravitational radiation encodes rich information about source physics; thus parameter estimation and model selection are crucial analysis steps for any detection candidate events. Detailed models of the anticipated waveforms enable inference on several parameters, such as component masses, spins, sky location and distance, that are essential for new astrophysical studies of these sources. However, accurate measurements of these parameters and discrimination of models describing the underlying physics are complicated by artifacts in the data, uncertainties in the waveform models and in the calibration of the detectors. Here we report such measurements on a selection of simulated signals added either in hardware or software to the data collected by the two LIGO instruments and the Virgo detector during their most recent joint science run, including a “blind injection” where the signal was not initially revealed to the collaboration. We exemplify the ability to extract information about the source physics on signals that cover the neutron-star and black-hole binary parameter space over the component mass range 1M⊙-25M⊙ and the full range of spin parameters. The cases reported in this study provide a snapshot of the status of parameter estimation in preparation for the operation of advanced detectors.

A GUI-based Tool for Bridging the Gap between Models and Process-Oriented Studies

NASA Astrophysics Data System (ADS)

Kornfeld, A.; Van der Tol, C.; Berry, J. A.

2014-12-01

Models used for simulation of photosynthesis and transpiration by canopies of terrestrial plants typically have subroutines such as STOMATA.F90, PHOSIB.F90 or BIOCHEM.m that solve for photosynthesis and associated processes. Key parameters such as the Vmax for Rubisco and temperature response parameters are required by these subroutines. These are often taken from the literature or determined by separate analysis of gas exchange experiments. It is useful to note however that subroutines can be extracted and run as standalone models to simulate leaf responses collected in gas exchange experiments. Furthermore, there are excellent non-linear fitting tools that can be used to optimize the parameter values in these models to fit the observations. Ideally the Vmax fit in this way should be the same as that determined by a separate analysis, but it may not because of interactions with other kinetic constants and the temperature dependence of these in the full subroutine. We submit that it is more useful to fit the complete model to the calibration experiments rather as disaggregated constants. We designed a graphical user interface (GUI) based tool that uses gas exchange photosynthesis data to directly estimate model parameters in the SCOPE (Soil Canopy Observation, Photochemistry and Energy fluxes) model and, at the same time, allow researchers to change parameters interactively to visualize how variation in model parameters affect predicted outcomes such as photosynthetic rates, electron transport, and chlorophyll fluorescence. We have also ported some of this functionality to an Excel spreadsheet, which could be used as a teaching tool to help integrate process-oriented and model-oriented studies.

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.

A parametric model and estimation techniques for the inharmonicity and tuning of the piano.

PubMed

Rigaud, François; David, Bertrand; Daudet, Laurent

2013-05-01

Inharmonicity of piano tones is an essential property of their timbre that strongly influences the tuning, leading to the so-called octave stretching. It is proposed in this paper to jointly model the inharmonicity and tuning of pianos on the whole compass. While using a small number of parameters, these models are able to reflect both the specificities of instrument design and tuner's practice. An estimation algorithm is derived that can run either on a set of isolated note recordings, but also on chord recordings, assuming that the played notes are known. It is applied to extract parameters highlighting some tuner's choices on different piano types and to propose tuning curves for out-of-tune pianos or piano synthesizers.

Chemical short-range order and lattice deformations in MgyTi1-yHx thin films probed by hydrogenography

NASA Astrophysics Data System (ADS)

Gremaud, R.; Baldi, A.; Gonzalez-Silveira, M.; Dam, B.; Griessen, R.

2008-04-01

A multisite lattice gas approach is used to model pressure-optical-transmission isotherms (PTIs) recorded by hydrogenography on MgyTi1-yHx sputtered thin films. The model reproduces the measured PTIs well and allows us to determine the chemical short-range order parameter s . The s values are in good agreement with those determined from extended x-ray absorption fine structure measurements. Additionally, the PTI multisite modeling yields a parameter L that accounts for the local lattice deformations with respect to the average MgyTi1-y lattice given by Vegard’s law. It is thus possible to extract two essential characteristics of a metastable alloy from hydrogenographic data.

Multi-scale quantum point contact model for filamentary conduction in resistive random access memories devices

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

Lian, Xiaojuan, E-mail: xjlian2005@gmail.com; Cartoixà, Xavier; Miranda, Enrique

2014-06-28

We depart from first-principle simulations of electron transport along paths of oxygen vacancies in HfO{sub 2} to reformulate the Quantum Point Contact (QPC) model in terms of a bundle of such vacancy paths. By doing this, the number of model parameters is reduced and a much clearer link between the microscopic structure of the conductive filament (CF) and its electrical properties can be provided. The new multi-scale QPC model is applied to two different HfO{sub 2}-based devices operated in the unipolar and bipolar resistive switching (RS) modes. Extraction of the QPC model parameters from a statistically significant number of CFsmore » allows revealing significant structural differences in the CF of these two types of devices and RS modes.« less

An Analysis Method for Superconducting Resonator Parameter Extraction with Complex Baseline Removal

NASA Technical Reports Server (NTRS)

Cataldo, Giuseppe

2014-01-01

A new semi-empirical model is proposed for extracting the quality (Q) factors of arrays of superconducting microwave kinetic inductance detectors (MKIDs). The determination of the total internal and coupling Q factors enables the computation of the loss in the superconducting transmission lines. The method used allows the simultaneous analysis of multiple interacting discrete resonators with the presence of a complex spectral baseline arising from reflections in the system. The baseline removal allows an unbiased estimate of the device response as measured in a cryogenic instrumentation setting.

Modelling and analysis of creep deformation and fracture in a 1 Cr 1/2 Mo ferritic steel

NASA Astrophysics Data System (ADS)

Dyson, B. F.; Osgerby, D.

A quantitative model, based upon a proposed new mechanism of creep deformation in particle-hardened alloys, has been validated by analysis of creep data from a 13CrMo 4 4 (1Cr 1/2 Mo) material tested under a range of stresses and temperatures. The methodology that has been used to extract the model parameters quantifies, as a first approximation, only the main degradation (damage) processes - in the case of the 1CR 1/2 Mo steel, these are considered to be the parallel operation of particle-coarsening and a progressively increasing stress due to a constant-load boundary condition. These 'global' model parameters can then be modified (only slightly) as required to obtain a detailed description and 'fit' to the rupture lifetime and strain/time trajectory of any individual test. The global model parameter approach may be thought of as predicting average behavior and the detailed fits as taking account of uncertainties (scatter) due to variability in the material. Using the global parameter dataset, predictions have also been made of behavior under biaxial stressing; constant straining rate; constant total strain (stress relaxation) and the likely success or otherwise of metallographic and mechanical remanent lifetime procedures.

Automated numerical simulation of biological pattern formation based on visual feedback simulation framework

PubMed Central

Sun, Mingzhu; Xu, Hui; Zeng, Xingjuan; Zhao, Xin

2017-01-01

There are various fantastic biological phenomena in biological pattern formation. Mathematical modeling using reaction-diffusion partial differential equation systems is employed to study the mechanism of pattern formation. However, model parameter selection is both difficult and time consuming. In this paper, a visual feedback simulation framework is proposed to calculate the parameters of a mathematical model automatically based on the basic principle of feedback control. In the simulation framework, the simulation results are visualized, and the image features are extracted as the system feedback. Then, the unknown model parameters are obtained by comparing the image features of the simulation image and the target biological pattern. Considering two typical applications, the visual feedback simulation framework is applied to fulfill pattern formation simulations for vascular mesenchymal cells and lung development. In the simulation framework, the spot, stripe, labyrinthine patterns of vascular mesenchymal cells, the normal branching pattern and the branching pattern lacking side branching for lung branching are obtained in a finite number of iterations. The simulation results indicate that it is easy to achieve the simulation targets, especially when the simulation patterns are sensitive to the model parameters. Moreover, this simulation framework can expand to other types of biological pattern formation. PMID:28225811

Automated numerical simulation of biological pattern formation based on visual feedback simulation framework.

PubMed

Sun, Mingzhu; Xu, Hui; Zeng, Xingjuan; Zhao, Xin

2017-01-01

There are various fantastic biological phenomena in biological pattern formation. Mathematical modeling using reaction-diffusion partial differential equation systems is employed to study the mechanism of pattern formation. However, model parameter selection is both difficult and time consuming. In this paper, a visual feedback simulation framework is proposed to calculate the parameters of a mathematical model automatically based on the basic principle of feedback control. In the simulation framework, the simulation results are visualized, and the image features are extracted as the system feedback. Then, the unknown model parameters are obtained by comparing the image features of the simulation image and the target biological pattern. Considering two typical applications, the visual feedback simulation framework is applied to fulfill pattern formation simulations for vascular mesenchymal cells and lung development. In the simulation framework, the spot, stripe, labyrinthine patterns of vascular mesenchymal cells, the normal branching pattern and the branching pattern lacking side branching for lung branching are obtained in a finite number of iterations. The simulation results indicate that it is easy to achieve the simulation targets, especially when the simulation patterns are sensitive to the model parameters. Moreover, this simulation framework can expand to other types of biological pattern formation.

Toward a New Brewing Control Chart for the 21st Century.

PubMed

Melrose, John; Roman-Corrochano, Borja; Montoya-Guerra, Marcela; Bakalis, Serafim

2018-04-23

This paper describes new results from a base model of brewing from a bed of packed coffee grains. The model solves for the diffusion of soluble species out of a distribution of particles into the flow through the bed pore space. It requires a limited set of input parameters. It gives a simple picture of the basic physics of coffee brewing and sets out a set of reduced variables for this process. The importance of bed extraction efficiency is elucidated. A coffee brewing control chart has been widely used to describe the region of ideal coffee brewing for some 50 years. A new chart is needed, however, one that connects actual brewing conditions (weight, flow rate, brew time, grind, etc.) to the yield and strength of brews. The paper shows a new approach to brewing control charts, including brew time and bed extraction efficiency as control parameters. Using the base model, an example chart will be given for a particular grind ratio of coarse to fine particles, and an "espresso regime" will be picked out. From such a chart yield, volume and strength of a brew can be read off at will.

Determination of key diffusion and partition parameters and their use in migration modelling of benzophenone from low-density polyethylene (LDPE) into different foodstuffs.

PubMed

Maia, Joaquim; Rodríguez-Bernaldo de Quirós, Ana; Sendón, Raquel; Cruz, José Manuel; Seiler, Annika; Franz, Roland; Simoneau, Catherine; Castle, Laurence; Driffield, Malcolm; Mercea, Peter; Oldring, Peter; Tosa, Valer; Paseiro, Perfecto

2016-01-01

The mass transport process (migration) of a model substance, benzophenone (BZP), from LDPE into selected foodstuffs at three temperatures was studied. A mathematical model based on Fick's Second Law of Diffusion was used to simulate the migration process and a good correlation between experimental and predicted values was found. The acquired results contribute to a better understanding of this phenomenon and the parameters so-derived were incorporated into the migration module of the recently launched FACET tool (Flavourings, Additives and Food Contact Materials Exposure Tool). The migration tests were carried out at different time-temperature conditions, and BZP was extracted from LDPE and analysed by HPLC-DAD. With all data, the parameters for migration modelling (diffusion and partition coefficients) were calculated. Results showed that the diffusion coefficients (within both the polymer and the foodstuff) are greatly affected by the temperature and food's physical state, whereas the partition coefficient was affected significantly only by food characteristics, particularly fat content.

Bayesian parameter estimation for stochastic models of biological cell migration

NASA Astrophysics Data System (ADS)

Dieterich, Peter; Preuss, Roland

2013-08-01

Cell migration plays an essential role under many physiological and patho-physiological conditions. It is of major importance during embryonic development and wound healing. In contrast, it also generates negative effects during inflammation processes, the transmigration of tumors or the formation of metastases. Thus, a reliable quantification and characterization of cell paths could give insight into the dynamics of these processes. Typically stochastic models are applied where parameters are extracted by fitting models to the so-called mean square displacement of the observed cell group. We show that this approach has several disadvantages and problems. Therefore, we propose a simple procedure directly relying on the positions of the cell's trajectory and the covariance matrix of the positions. It is shown that the covariance is identical with the spatial aging correlation function for the supposed linear Gaussian models of Brownian motion with drift and fractional Brownian motion. The technique is applied and illustrated with simulated data showing a reliable parameter estimation from single cell paths.

A hierarchical pyramid method for managing large-scale high-resolution drainage networks extracted from DEM

NASA Astrophysics Data System (ADS)

Bai, Rui; Tiejian, Li; Huang, Yuefei; Jiaye, Li; Wang, Guangqian; Yin, Dongqin

2015-12-01

The increasing resolution of Digital Elevation Models (DEMs) and the development of drainage network extraction algorithms make it possible to develop high-resolution drainage networks for large river basins. These vector networks contain massive numbers of river reaches with associated geographical features, including topological connections and topographical parameters. These features create challenges for efficient map display and data management. Of particular interest are the requirements of data management for multi-scale hydrological simulations using multi-resolution river networks. In this paper, a hierarchical pyramid method is proposed, which generates coarsened vector drainage networks from the originals iteratively. The method is based on the Horton-Strahler's (H-S) order schema. At each coarsening step, the river reaches with the lowest H-S order are pruned, and their related sub-basins are merged. At the same time, the topological connections and topographical parameters of each coarsened drainage network are inherited from the former level using formulas that are presented in this study. The method was applied to the original drainage networks of a watershed in the Huangfuchuan River basin extracted from a 1-m-resolution airborne LiDAR DEM and applied to the full Yangtze River basin in China, which was extracted from a 30-m-resolution ASTER GDEM. In addition, a map-display and parameter-query web service was published for the Mississippi River basin, and its data were extracted from the 30-m-resolution ASTER GDEM. The results presented in this study indicate that the developed method can effectively manage and display massive amounts of drainage network data and can facilitate multi-scale hydrological simulations.

Preliminary evaluation of in vitro cytotoxicity and in vivo antitumor activity of Xanthium strumarium in transplantable tumors in mice.

PubMed

Aranjani, Jesil Mathew; Manuel, Atulya; Mallikarjuna Rao, Chamallamudi; Udupa, Nayanabhirama; Rao, Josyula Venkata; Joy, Ann Mary; Gandhi, Prajay; Radhakrishnan, Ethiraj Kannat

2013-01-01

In the present study, active fractions of the methanolic extract of Xanthium strumarium (XS) showing potent cytotoxicity were determined using microculture tetrazolium (MTT) and sulforhodamine B (SRB) assays in selected cancer cell lines. The active fractions viz., chloroform soluble fraction of root (CEXSR), hexane soluble fraction of leaf (HEXSL), hexane soluble fraction of fruits (HEXSF) and chloroform soluble fraction of fruits (CEXSF) of XS were tested in transplantable animal tumor models for their antitumor potential. Dalton's ascitic lymphoma (DLA) cells were used to induce solid and liquid (ascites) tumor in mice. The tumor bearing animals were treated with active fractions at two dose levels (100 and 200 mg/kg). The antitumor activities of the active fractions in tumor bearing animals were monitored with parameters such as body weight and increase in life-span as well as biochemical and hematological modalities (in the case of liquid tumor). Tumor incidence and tumor volume were the parameters monitored in the case of the solid tumor model. The results were analyzed by one-way ANOVA followed by Tukey's post hoc test. The extracts were found to increase the life-span of tumor bearing animals and restore the altered hematological and biochemical parameters significantly.

Voxel-Based 3-D Tree Modeling from Lidar Images for Extracting Tree Structual Information

NASA Astrophysics Data System (ADS)

Hosoi, F.

2014-12-01

Recently, lidar (light detection and ranging) has been used to extracting tree structural information. Portable scanning lidar systems can capture the complex shape of individual trees as a 3-D point-cloud image. 3-D tree models reproduced from the lidar-derived 3-D image can be used to estimate tree structural parameters. We have proposed the voxel-based 3-D modeling for extracting tree structural parameters. One of the tree parameters derived from the voxel modeling is leaf area density (LAD). We refer to the method as the voxel-based canopy profiling (VCP) method. In this method, several measurement points surrounding the canopy and optimally inclined laser beams are adopted for full laser beam illumination of whole canopy up to the internal. From obtained lidar image, the 3-D information is reproduced as the voxel attributes in the 3-D voxel array. Based on the voxel attributes, contact frequency of laser beams on leaves is computed and LAD in each horizontal layer is obtained. This method offered accurate LAD estimation for individual trees and woody canopy trees. For more accurate LAD estimation, the voxel model was constructed by combining airborne and portable ground-based lidar data. The profiles obtained by the two types of lidar complemented each other, thus eliminating blind regions and yielding more accurate LAD profiles than could be obtained by using each type of lidar alone. Based on the estimation results, we proposed an index named laser beam coverage index, Ω, which relates to the lidar's laser beam settings and a laser beam attenuation factor. It was shown that this index can be used for adjusting measurement set-up of lidar systems and also used for explaining the LAD estimation error using different types of lidar systems. Moreover, we proposed a method to estimate woody material volume as another application of the voxel tree modeling. In this method, voxel solid model of a target tree was produced from the lidar image, which is composed of consecutive voxels that filled the outer surface and the interior of the stem and large branches. From the model, the woody material volume of any part of the target tree can be directly calculated easily by counting the number of corresponding voxels and multiplying the result by the per-voxel volume.

MLBCD: a machine learning tool for big clinical data.

PubMed

Luo, Gang

2015-01-01

Predictive modeling is fundamental for extracting value from large clinical data sets, or "big clinical data," advancing clinical research, and improving healthcare. Machine learning is a powerful approach to predictive modeling. Two factors make machine learning challenging for healthcare researchers. First, before training a machine learning model, the values of one or more model parameters called hyper-parameters must typically be specified. Due to their inexperience with machine learning, it is hard for healthcare researchers to choose an appropriate algorithm and hyper-parameter values. Second, many clinical data are stored in a special format. These data must be iteratively transformed into the relational table format before conducting predictive modeling. This transformation is time-consuming and requires computing expertise. This paper presents our vision for and design of MLBCD (Machine Learning for Big Clinical Data), a new software system aiming to address these challenges and facilitate building machine learning predictive models using big clinical data. The paper describes MLBCD's design in detail. By making machine learning accessible to healthcare researchers, MLBCD will open the use of big clinical data and increase the ability to foster biomedical discovery and improve care.

Prevention of renal dysfunction by nutraceuticals prepared from oil rich plant foods

PubMed Central

Al-Okbi, Sahar Y.; Mohamed, Doha A.; Hamed, Thanaa E.; Esmail, Reham SH.; Donya, Souria M.

2014-01-01

Objective To investigate the protective effect of extracts prepared from avocado, walnut, flaxseed and Eruca sativa seeds in a rat model of kidney dysfunction induced by intraperitoneal cisplatin. Methods Ethanol and petroleum ether extracts mixture was prepared from each plant. Six groups of rats were conducted; control healthy, cisplatin group and four test groups where rats were given daily oral dose of each extract mixture before cisplatin injection. Different biochemical and cytogenetic parameters and kidney histopathology were determined. Acute toxicity was tested for the nutraceuticals. Total phenolic contents, fatty acids (FA) and unsaponifiable matter were assessed in the extracts. Results Walnut ethanol extract showed the highest content of total phenolic. FA analysis revealed that all the studied plants were rich in unsaturated FA. Gas-liquid chromatographic investigation of the unsaponifiable matter showed the presence of campesterol, stigmasterol and β-sitosterol in all the studied plants. Cisplatin treatment induced significant increase in plasma urea, creatinine and malondialdehyde along with significant reduction of plasma albumin, total protein, catalase and total antioxidant as well as reduction in creatinine clearance. Histopathological examination proved the induction of kidney dysfunction. Some sorts of chromosomal aberration and sperm-shape abnormalities were noticed after cisplatin treatment. Administration of extracts mixtures produced improvements in biochemical, histopathological and cytogenetic parameters. Conclusions Administration of the studied nutraceuticals proved to possess protective role against cisplatin-induced nephrotoxicity, chromosomal aberration and abnormal sperms. All studied nutraceuticals showed complete safety. PMID:25183331

Verification of reflectance models in turbid waters

NASA Technical Reports Server (NTRS)

Tanis, F. J.; Lyzenga, D. R.

1981-01-01

Inherent optical parameters of very turbid waters were used to evaluate existing water reflectance models. Measured upwelling radiance spectra and Monte Carlo simulations of the radiative transfer equations were compared with results from models based upon two flow, quasi-single scattering, augmented isotropic scattering, and power series approximation. Each model was evaluated for three separate components of upwelling radiance: (1) direct sunlight; (2) diffuse skylight; and (3) internally reflected light. Limitations of existing water reflectance models as applied to turbid waters and possible applications to the extraction of water constituent information are discussed.

Extracting Forest Canopy Characteristics from Remote Sensing Imagery: Implications for Sentinel-2 Mission

NASA Astrophysics Data System (ADS)

Gholizadeh, Asa; Kopaekova, Veronika; Rogass, Christian; Mielke, Christian; Misurec, Jan

2016-08-01

Systematic quantification and monitoring of forest biophysical and biochemical variables is required to assess the response of ecosystems to climate change. Remote sensing has been introduced as a time and cost- efficient way to carry out large scale monitoring of vegetation parameters. Red-Edge Position (REP) is a hyperspectrally detectable parameter which is sensitive to vegetation Chl. In the current study, REP was modelled for the Norway spruce forest canopy resampled to HyMap and Sentinel-2 spectral resolution as well as calculated from the real HyMap and Sentinel-2 simulated data. Different REP extraction methods (4PLI, PF, LE, 4PLIH and 4PLIS) were assessed. The study showed the way for effective utilization of the forthcoming hyper and superspectral remote sensing sensors from orbit to monitor vegetation attributes.

Applications of acoustic-gravity waves numerical modeling to tsunami signals observed by gravimetry satellites in very low orbit

NASA Astrophysics Data System (ADS)

Brissaud, Q.; Garcia, R.; Sladen, A.; Martin, R.; Komatitsch, D.

2016-12-01

Acoustic and gravity waves propagating in planetary atmospheres have been studied intensively as markers of specific phenomena (tectonic events, explosions) or as contributors to atmosphere dynamics. To get a better understanding of the physics behind these dynamic processes, both acoustic and gravity waves propagation should be modeled in an attenuating and windy 3D atmosphere from the ground all the way to the upper thermosphere. Thus, in order to provide an efficient numerical tool at the regional or global scale we introduce a high-order finite-difference time domain (FDTD) approach that relies on the linearized compressible Navier-Stokes equations with spatially non constant physical parameters (density, viscosities and speed of sound) and background velocities (wind). We present applications of these simulations to the propagation of gravity waves generated by tsunamis for realistic cases for which atmospheric models are extracted from empirical models including variations with altitude of atmospheric parameters, and tsunami forcing at the ocean surface is extracted from shallow water simulations. We describe the specific difficulties induced by the size of the simulation, the boundary conditions and the spherical geometry and compare the simulation outputs to data gathered by gravimetric satellites crossing gravity waves generated by tsunamis.

Development of a helicon ion source: Simulations and preliminary experiments.

PubMed

Afsharmanesh, M; Habibi, M

2018-03-01

In the present context, the extraction system of a helicon ion source has been simulated and constructed. Results of the ion source commissioning at up to 20 kV are presented as well as simulations of an ion beam extraction system. Argon current of more than 200 μA at up to 20 kV is extracted and is characterized with a Faraday cup and beam profile monitoring grid. By changing different ion source parameters such as RF power, extraction voltage, and working pressure, an ion beam with current distribution exhibiting a central core has been detected. Jump transition of ion beam current emerges at the RF power near to 700 W, which reveals that the helicon mode excitation has reached this power. Furthermore, measuring the emission line intensity of Ar ii at 434.8 nm is the other way we have used for demonstrating the mode transition from inductively coupled plasma to helicon. Due to asymmetrical longitudinal power absorption of a half-helix helicon antenna, it is used for the ion source development. The modeling of the plasma part of the ion source has been carried out using a code, HELIC. Simulations are carried out by taking into account a Gaussian radial plasma density profile and for plasma densities in range of 10 18 -10 19 m -3 . Power absorption spectrum and the excited helicon mode number are obtained. Longitudinal RF power absorption for two different antenna positions is compared. Our results indicate that positioning the antenna near to the plasma electrode is desirable for the ion beam extraction. The simulation of the extraction system was performed with the ion optical code IBSimu, making it the first helicon ion source extraction designed with the code. Ion beam emittance and Twiss parameters of the ellipse emittance are calculated at different iterations and mesh sizes, and the best values of the mesh size and iteration number have been obtained for the calculations. The simulated ion beam extraction system has been evaluated using optimized parameters such as the gap distance between electrodes, electrodes aperture, and extraction voltage. The gap distance, ground electrode aperture, and extraction voltage have been changed between 3 and 9 mm, 2-6.5 mm, and 10-35 kV in the simulations, respectively.

Development of a helicon ion source: Simulations and preliminary experiments

NASA Astrophysics Data System (ADS)

Afsharmanesh, M.; Habibi, M.

2018-03-01

In the present context, the extraction system of a helicon ion source has been simulated and constructed. Results of the ion source commissioning at up to 20 kV are presented as well as simulations of an ion beam extraction system. Argon current of more than 200 μA at up to 20 kV is extracted and is characterized with a Faraday cup and beam profile monitoring grid. By changing different ion source parameters such as RF power, extraction voltage, and working pressure, an ion beam with current distribution exhibiting a central core has been detected. Jump transition of ion beam current emerges at the RF power near to 700 W, which reveals that the helicon mode excitation has reached this power. Furthermore, measuring the emission line intensity of Ar ii at 434.8 nm is the other way we have used for demonstrating the mode transition from inductively coupled plasma to helicon. Due to asymmetrical longitudinal power absorption of a half-helix helicon antenna, it is used for the ion source development. The modeling of the plasma part of the ion source has been carried out using a code, HELIC. Simulations are carried out by taking into account a Gaussian radial plasma density profile and for plasma densities in range of 1018-1019 m-3. Power absorption spectrum and the excited helicon mode number are obtained. Longitudinal RF power absorption for two different antenna positions is compared. Our results indicate that positioning the antenna near to the plasma electrode is desirable for the ion beam extraction. The simulation of the extraction system was performed with the ion optical code IBSimu, making it the first helicon ion source extraction designed with the code. Ion beam emittance and Twiss parameters of the ellipse emittance are calculated at different iterations and mesh sizes, and the best values of the mesh size and iteration number have been obtained for the calculations. The simulated ion beam extraction system has been evaluated using optimized parameters such as the gap distance between electrodes, electrodes aperture, and extraction voltage. The gap distance, ground electrode aperture, and extraction voltage have been changed between 3 and 9 mm, 2-6.5 mm, and 10-35 kV in the simulations, respectively.

Box-Behnken design based statistical modeling for ultrasound-assisted extraction of corn silk polysaccharide.

PubMed

Prakash Maran, J; Manikandan, S; Thirugnanasambandham, K; Vigna Nivetha, C; Dinesh, R

2013-01-30

In this study, ultrasound assisted extraction (UAE) conditions on the yield of polysaccharide from corn silk were studied using three factors, three level Box-Behnken response surface design. Process parameters, which affect the efficiency of UAE such as extraction temperature (40-60 °C), time (10-30 min) and solid-liquid ratio (1:10-1:30 g/ml) were investigated. The results showed that, the extraction conditions have significant effects on extraction yield of polysaccharide. The obtained experimental data were fitted to a second-order polynomial equation using multiple regression analysis with high coefficient of determination value (R(2)) of 0.994. An optimization study using Derringer's desired function methodology was performed and the optimal conditions based on both individual and combinations of all independent variables (extraction temperature of 56 °C, time of 17 min and solid-liquid ratio of 1:20 g/ml) were determined with maximum polysaccharide yield of 6.06%, which was confirmed through validation experiments. Copyright © 2012 Elsevier Ltd. All rights reserved.

CFD simulation of copper(II) extraction with TFA in non-dispersive hollow fiber membrane contactors.

PubMed

Muhammad, Amir; Younas, Mohammad; Rezakazemi, Mashallah

2018-04-01

This study presents computational fluid dynamics (CFD) simulation of dispersion-free liquid-liquid extraction of copper(II) with trifluoroacetylacetone (TFA) in hollow fiber membrane contactor (HFMC). Mass and momentum balance Navier-Stokes equations were coupled to address the transport of copper(II) solute across membrane contactor. Model equations were simulated using COMSOL Multiphysics™. The simulation was run to study the detailed concentration distribution of copper(II) and to investigate the effects of various parameters like membrane characteristics, partition coefficient, and flow configuration on extraction efficiency. Once-through extraction was found to be increased from 10 to 100% when partition coefficient was raised from 1 to 10. Similarly, the extraction efficiency was almost doubled when porosity to tortuosity ratio of membrane was increased from 0.05 to 0.81. Furthermore, the study revealed that CFD can be used as an effective optimization tool for the development of economical membrane-based dispersion-free extraction processes.

Oil extraction from sheanut (Vitellaria paradoxa Gaertn C.F.) kernels assisted by microwaves.

PubMed

Nde, Divine B; Boldor, Dorin; Astete, Carlos; Muley, Pranjali; Xu, Zhimin

2016-03-01

Shea butter, is highly solicited in cosmetics, pharmaceuticals, chocolates and biodiesel formulations. Microwave assisted extraction (MAE) of butter from sheanut kernels was carried using the Doehlert's experimental design. Factors studied were microwave heating time, temperature and solvent/solute ratio while the responses were the quantity of oil extracted and the acid number. Second order models were established to describe the influence of experimental parameters on the responses studied. Under optimum MAE conditions of heating time 23 min, temperature 75 °C and solvent/solute ratio 4:1 more than 88 % of the oil with a free fatty acid (FFA) value less than 2, was extracted compared to the 10 h and solvent/solute ratio of 10:1 required for soxhlet extraction. Scanning electron microscopy was used to elucidate the effect of microwave heating on the kernels' microstructure. Substantial reduction in extraction time and volumes of solvent used and oil of suitable quality are the main benefits derived from the MAE process.

Supercritical fluid extraction of plant flavors and fragrances.

PubMed

Capuzzo, Andrea; Maffei, Massimo E; Occhipinti, Andrea

2013-06-19

Supercritical fluid extraction (SFE) of plant material with solvents like CO₂, propane, butane, or ethylene is a topic of growing interest. SFE allows the processing of plant material at low temperatures, hence limiting thermal degradation, and avoids the use of toxic solvents. Although today SFE is mainly used for decaffeination of coffee and tea as well as production of hop extracts on a large scale, there is also a growing interest in this extraction method for other industrial applications operating at different scales. In this review we update the literature data on SFE technology, with particular reference to flavors and fragrance, by comparing traditional extraction techniques of some industrial medicinal and aromatic crops with SFE. Moreover, we describe the biological activity of SFE extracts by describing their insecticidal, acaricidal, antimycotic, antimicrobial, cytotoxic and antioxidant properties. Finally, we discuss the process modelling, mass-transfer mechanisms, kinetics parameters and thermodynamic by giving an overview of SFE potential in the flavors and fragrances arena.

Mapping axonal density and average diameter using non-monotonic time-dependent gradient-echo MRI

NASA Astrophysics Data System (ADS)

Nunes, Daniel; Cruz, Tomás L.; Jespersen, Sune N.; Shemesh, Noam

2017-04-01

White Matter (WM) microstructures, such as axonal density and average diameter, are crucial to the normal function of the Central Nervous System (CNS) as they are closely related with axonal conduction velocities. Conversely, disruptions of these microstructural features may result in severe neurological deficits, suggesting that their noninvasive mapping could be an important step towards diagnosing and following pathophysiology. Whereas diffusion based MRI methods have been proposed to map these features, they typically entail the application of powerful gradients, which are rarely available in the clinic, or extremely long acquisition schemes to extract information from parameter-intensive models. In this study, we suggest that simple and time-efficient multi-gradient-echo (MGE) MRI can be used to extract the axon density from susceptibility-driven non-monotonic decay in the time-dependent signal. We show, both theoretically and with simulations, that a non-monotonic signal decay will occur for multi-compartmental microstructures - such as axons and extra-axonal spaces, which were here used as a simple model for the microstructure - and that, for axons parallel to the main magnetic field, the axonal density can be extracted. We then experimentally demonstrate in ex-vivo rat spinal cords that its different tracts - characterized by different microstructures - can be clearly contrasted using the MGE-derived maps. When the quantitative results are compared against ground-truth histology, they reflect the axonal fraction (though with a bias, as evident from Bland-Altman analysis). As well, the extra-axonal fraction can be estimated. The results suggest that our model is oversimplified, yet at the same time evidencing a potential and usefulness of the approach to map underlying microstructures using a simple and time-efficient MRI sequence. We further show that a simple general-linear-model can predict the average axonal diameters from the four model parameters, and map these average axonal diameters in the spinal cords. While clearly further modelling and theoretical developments are necessary, we conclude that salient WM microstructural features can be extracted from simple, SNR-efficient multi-gradient echo MRI, and that this paves the way towards easier estimation of WM microstructure in vivo.

Mapping axonal density and average diameter using non-monotonic time-dependent gradient-echo MRI.

PubMed

Nunes, Daniel; Cruz, Tomás L; Jespersen, Sune N; Shemesh, Noam

2017-04-01

White Matter (WM) microstructures, such as axonal density and average diameter, are crucial to the normal function of the Central Nervous System (CNS) as they are closely related with axonal conduction velocities. Conversely, disruptions of these microstructural features may result in severe neurological deficits, suggesting that their noninvasive mapping could be an important step towards diagnosing and following pathophysiology. Whereas diffusion based MRI methods have been proposed to map these features, they typically entail the application of powerful gradients, which are rarely available in the clinic, or extremely long acquisition schemes to extract information from parameter-intensive models. In this study, we suggest that simple and time-efficient multi-gradient-echo (MGE) MRI can be used to extract the axon density from susceptibility-driven non-monotonic decay in the time-dependent signal. We show, both theoretically and with simulations, that a non-monotonic signal decay will occur for multi-compartmental microstructures - such as axons and extra-axonal spaces, which were here used as a simple model for the microstructure - and that, for axons parallel to the main magnetic field, the axonal density can be extracted. We then experimentally demonstrate in ex-vivo rat spinal cords that its different tracts - characterized by different microstructures - can be clearly contrasted using the MGE-derived maps. When the quantitative results are compared against ground-truth histology, they reflect the axonal fraction (though with a bias, as evident from Bland-Altman analysis). As well, the extra-axonal fraction can be estimated. The results suggest that our model is oversimplified, yet at the same time evidencing a potential and usefulness of the approach to map underlying microstructures using a simple and time-efficient MRI sequence. We further show that a simple general-linear-model can predict the average axonal diameters from the four model parameters, and map these average axonal diameters in the spinal cords. While clearly further modelling and theoretical developments are necessary, we conclude that salient WM microstructural features can be extracted from simple, SNR-efficient multi-gradient echo MRI, and that this paves the way towards easier estimation of WM microstructure in vivo. Copyright © 2017 Elsevier Inc. All rights reserved.

High performance curcumin subcritical water extraction from turmeric (Curcuma longa L.).

PubMed

Valizadeh Kiamahalleh, Mohammad; Najafpour-Darzi, Ghasem; Rahimnejad, Mostafa; Moghadamnia, Ali Akbar; Valizadeh Kiamahalleh, Meisam

2016-06-01

Curcumin is a hydrophobic polyphenolic compound derived from turmeric rhizome, which consists about 2-5% of the total rhizome content and is a more valuable component of turmeric. For reducing the drawbacks of conventional extraction (using organic solvents) of curcumin, the water as a clean solvent was used for extracting curcumin. Subcritical water extraction (SWE) experimental setup was fabricated in a laboratory scale and the influences of some parameters (e.g. extraction temperature, particle size, retention time and pressure) on the yield of extraction were investigated. Optimum extraction conditions such as SWE pressure of 10bar, extractive temperature of 140°C, particle size of 0.71mm and retention time of 14min were defined. The maximum amount of curcumin extracted at the optimum condition was 3.8wt%. The yield of curcumin extraction was more than 76wt% with regards to the maximum possible curcumin content of turmeric, as known to be 5%. The scanning electron microscope (SEM) images from the outer surface of turmeric, before and after extraction, clearly demonstrated the effect of each parameter; changes in porosity and hardness of turmeric that is directly related to the amount of extracted curcumin in process optimization of the extraction parameters. Copyright © 2016 Elsevier B.V. All rights reserved.

Extraction of Peace River bitumen using supercritical ethane

NASA Astrophysics Data System (ADS)

Rose, Jeffrey Lawrence

2000-10-01

As the supply of conventional crude oil continues to decline, petroleum companies are looking for alternative hydrocarbon sources. The vast reserves of heavy oil and bitumen located in northern Alberta are among the alternatives. The challenge facing engineers is to develop a process for recovering this oil which is economic, efficient and environmentally acceptable. Supercritical fluid extraction is one method being investigated which could potentially meet all of these criteria. In this study, Peace River bitumen was extracted using supercritical ethane. The bitumen was mixed with sand and packed into a semi-batch extractor. Ethane contacted the bitumen/sand mixture and the fraction of the bitumen soluble in the ethane was removed and subsequently collected in a two phase separator. The flow of ethane was such that the experiments were governed by equilibrium and not mass transfer. Experimental temperatures and pressures were varied in order to observe the effect of these parameters on the mass and composition of the extracted material. The extraction yields increased as the temperature decreased and pressure increased. Samples were collected at various time intervals to measure changes in the properties of the extracted bitumen over the duration of the process. As the extraction proceeded, the samples became heavier and more viscous. The bitumen feed was characterised and the experimental data was then modelled using the Peng-Robinson equation of state. The characterisation process involved the distillation of the bitumen into five fractions. The distillation curve and density of each fraction was measured and this data was used in conjunction with correlations to determine the critical properties of the bitumen. Interaction parameters in the equation of state were then optimised until the predicted composition of extracted bitumen matched the experimental results.

Detection and classification of subject-generated artifacts in EEG signals using autoregressive models.

PubMed

Lawhern, Vernon; Hairston, W David; McDowell, Kaleb; Westerfield, Marissa; Robbins, Kay

2012-07-15

We examine the problem of accurate detection and classification of artifacts in continuous EEG recordings. Manual identification of artifacts, by means of an expert or panel of experts, can be tedious, time-consuming and infeasible for large datasets. We use autoregressive (AR) models for feature extraction and characterization of EEG signals containing several kinds of subject-generated artifacts. AR model parameters are scale-invariant features that can be used to develop models of artifacts across a population. We use a support vector machine (SVM) classifier to discriminate among artifact conditions using the AR model parameters as features. Results indicate reliable classification among several different artifact conditions across subjects (approximately 94%). These results suggest that AR modeling can be a useful tool for discriminating among artifact signals both within and across individuals. Copyright © 2012 Elsevier B.V. All rights reserved.

Optimisation of the supercritical extraction of toxic elements in fish oil.

PubMed

Hajeb, P; Jinap, S; Shakibazadeh, Sh; Afsah-Hejri, L; Mohebbi, G H; Zaidul, I S M

2014-01-01

This study aims to optimise the operating conditions for the supercritical fluid extraction (SFE) of toxic elements from fish oil. The SFE operating parameters of pressure, temperature, CO2 flow rate and extraction time were optimised using a central composite design (CCD) of response surface methodology (RSM). High coefficients of determination (R²) (0.897-0.988) for the predicted response surface models confirmed a satisfactory adjustment of the polynomial regression models with the operation conditions. The results showed that the linear and quadratic terms of pressure and temperature were the most significant (p < 0.05) variables affecting the overall responses. The optimum conditions for the simultaneous elimination of toxic elements comprised a pressure of 61 MPa, a temperature of 39.8ºC, a CO₂ flow rate of 3.7 ml min⁻¹ and an extraction time of 4 h. These optimised SFE conditions were able to produce fish oil with the contents of lead, cadmium, arsenic and mercury reduced by up to 98.3%, 96.1%, 94.9% and 93.7%, respectively. The fish oil extracted under the optimised SFE operating conditions was of good quality in terms of its fatty acid constituents.

Antioxidant, antihyperglycemic, and antidyslipidemic effects of Brazilian-native fruit extracts in an animal model of insulin resistance.

PubMed

de Souza Cardoso, Juliane; Oliveira, Pathise Souto; Bona, Natália Pontes; Vasconcellos, Flávia Aleixo; Baldissarelli, Jucimara; Vizzotto, Marcia; Soares, Mayara Sandrielly Pereira; Ramos, Vanessa Plasse; Spanevello, Roselia Maria; Lencina, Claiton Leoneti; Tavares, Rejane Giacomelli; Stefanello, Francieli Moro

2018-12-01

Insulin resistance (IR) plays an important role in the development of many diseases, such as diabetes mellitus. Therefore, the aim of the present study was to evaluate the effects of the extracts from fruits native to Brazil on metabolic parameters and hepatic oxidative markers in an animal model of insulin resistance induced by dexamethasone (DEX). Wistar rats received water or extracts of Eugenia uniflora or Psidium cattleianum, once a day for 21 days. For the last 5 days, the rats received an intraperitoneal injection of saline or DEX. DEX caused a reduction in body weight gain and relative pancreatic weight, as well as glucose intolerance, and an increase in serum glucose and triacylglycerol levels. The extracts were found to prevent hyperglycemia and hypertriglyceridemia. DEX caused an increase in the levels of thiobarbituric acid-reactive substances and reactive oxygen species production in the liver of rats, and both extracts prevented these changes. In addition, hepatic glutathione peroxidase activity was reduced by DEX. However, total thiol content and activities of catalase, superoxide dismutase, and delta-aminolevulinate dehydratase were not altered in any of the tested groups. Fruit extracts of E. uniflora and P. cattleianum exhibited considerable antihyperglycemic, antidyslipidemic, and antioxidant effects, and may be useful in the therapeutic management of alterations due to IR.

Comprehensive capacitance-voltage analysis including quantum effects for high-k interfaces on germanium and other alternative channel materials

NASA Astrophysics Data System (ADS)

Anwar, Sarkar R. M.

High mobility alternative channel materials to silicon are critical to the continued scaling of metal oxide semiconductor (MOS) devices. However, before they can be incorporated into advanced devices, some major issues need to be solved. The high mobility materials suffer from lower allowable thermal budgets compared to Si (before desorption and defect formation becomes an issue) and the absence of a good quality native oxide has further increased the interest in the use of high-k dielectrics. However, the high interface state density and high electric fields at these semiconductor/high-k interfaces can significantly impact the capacitance-voltage (C-V) profile, and current C-V modeling software cannot account for these effects. This in turn affects the parameters extracted from the C-V data of the high mobility semiconductor/high-k interface, which are crucial to fully understand the interface properties and expedite process development. To address this issue, we developed a model which takes into account quantum corrections which can be applied to a number of these alternative channel materials including SixGe1-x, Ge, InGaAs, and GaAs. The C-V simulation using this QM correction model is orders of magnitude faster compared to a full band Schrodinger-Poisson solver. The simulated C-V is directly benchmarked to a self consistent Schrodinger-Poisson solution for each bulk semiconductor material, and from the benchmarking process the QM correction parameters are extracted. The full program, C-V Alternative Channel Extraction (CV ACE), incorporates a quantum mechanical correction model, along with the interface state density model, and can extract device parameters such as equivalent oxide thickness (EOT), doping density and flat band voltage (Vfb) as well as the interface state density profile using multiple measurements performed at different frequencies and temperatures, simultaneously. The program was used to analyze experimentally measured C-V profiles and the extracted device parameters show excellent agreement with the known device structure and previously published results. CV ACE has been applied in the development of a process flow for germanium interface passivation in Ge based MOS devices using a GeOx interlayer. A post atomic layer deposition (ALD) plasma oxidation (PPO) process was developed using radio frequency (RF) plasma in a plasma enhanced chemical vapor deposition (PECVD) chamber and demonstrated significant surface passivation. Various gases were investigated and 1% O2/Ar was found to reduce the growth rate and provide excellent control over the degradation of EOT. A 100 W plasma with 1% O2/Ar was found to provide the best combination of EOT and low Dit and is concluded to be the optimum process for PPO of germanium surfaces. CV ACE and PPO were also utilized to investigate other process development challenges. A study of the impact of low temperature anneals on Ge-based MOS devices was found to result in a degradation of the electrical thickness and a change in fixed charge, indicating that the process window is very narrow and at much lower temperatures than for Si.

Computer-Aided System Engineering and Analysis (CASE/A) Programmer's Manual, Version 5.0

NASA Technical Reports Server (NTRS)

Knox, J. C.

1996-01-01

The Computer Aided System Engineering and Analysis (CASE/A) Version 5.0 Programmer's Manual provides the programmer and user with information regarding the internal structure of the CASE/A 5.0 software system. CASE/A 5.0 is a trade study tool that provides modeling/simulation capabilities for analyzing environmental control and life support systems and active thermal control systems. CASE/A has been successfully used in studies such as the evaluation of carbon dioxide removal in the space station. CASE/A modeling provides a graphical and command-driven interface for the user. This interface allows the user to construct a model by placing equipment components in a graphical layout of the system hardware, then connect the components via flow streams and define their operating parameters. Once the equipment is placed, the simulation time and other control parameters can be set to run the simulation based on the model constructed. After completion of the simulation, graphical plots or text files can be obtained for evaluation of the simulation results over time. Additionally, users have the capability to control the simulation and extract information at various times in the simulation (e.g., control equipment operating parameters over the simulation time or extract plot data) by using "User Operations (OPS) Code." This OPS code is written in FORTRAN with a canned set of utility subroutines for performing common tasks. CASE/A version 5.0 software runs under the VAX VMS(Trademark) environment. It utilizes the Tektronics 4014(Trademark) graphics display system and the VTIOO(Trademark) text manipulation/display system.

Discriminating the Mediterranean Pinus spp. using the land surface phenology extracted from the whole MODIS NDVI time series and machine learning algorithms

NASA Astrophysics Data System (ADS)

Rodriguez-Galiano, Victor; Aragones, David; Caparros-Santiago, Jose A.; Navarro-Cerrillo, Rafael M.

2017-10-01

Land surface phenology (LSP) can improve the characterisation of forest areas and their change processes. The aim of this work was: i) to characterise the temporal dynamics in Mediterranean Pinus forests, and ii) to evaluate the potential of LSP for species discrimination. The different experiments were based on 679 mono-specific plots for the 5 native species on the Iberian Peninsula: P. sylvestris, P. pinea, P. halepensis, P. nigra and P. pinaster. The entire MODIS NDVI time series (2000-2016) of the MOD13Q1 product was used to characterise phenology. The following phenological parameters were extracted: the start, end and median days of the season, and the length of the season in days, as well as the base value, maximum value, amplitude and integrated value. Multi-temporal metrics were calculated to synthesise the inter-annual variability of the phenological parameters. The species were discriminated by the application of Random Forest (RF) classifiers from different subsets of variables: model 1) NDVI-smoothed time series, model 2) multi-temporal metrics of the phenological parameters, and model 3) multi-temporal metrics and the auxiliary physical variables (altitude, slope, aspect and distance to the coastline). Model 3 was the best, with an overall accuracy of 82%, a kappa coefficient of 0.77 and whose most important variables were: elevation, coast distance, and the end and start days of the growing season. The species that presented the largest errors was P. nigra, (kappa= 0.45), having locations with a similar behaviour to P. sylvestris or P. pinaster.

Model-based conifer crown surface reconstruction from multi-ocular high-resolution aerial imagery

NASA Astrophysics Data System (ADS)

Sheng, Yongwei

2000-12-01

Tree crown parameters such as width, height, shape and crown closure are desirable in forestry and ecological studies, but they are time-consuming and labor intensive to measure in the field. The stereoscopic capability of high-resolution aerial imagery provides a way to crown surface reconstruction. Existing photogrammetric algorithms designed to map terrain surfaces, however, cannot adequately extract crown surfaces, especially for steep conifer crowns. Considering crown surface reconstruction in a broader context of tree characterization from aerial images, we develop a rigorous perspective tree image formation model to bridge image-based tree extraction and crown surface reconstruction, and an integrated model-based approach to conifer crown surface reconstruction. Based on the fact that most conifer crowns are in a solid geometric form, conifer crowns are modeled as a generalized hemi-ellipsoid. Both the automatic and semi-automatic approaches are investigated to optimal tree model development from multi-ocular images. The semi-automatic 3D tree interpreter developed in this thesis is able to efficiently extract reliable tree parameters and tree models in complicated tree stands. This thesis starts with a sophisticated stereo matching algorithm, and incorporates tree models to guide stereo matching. The following critical problems are addressed in the model-based surface reconstruction process: (1) the problem of surface model composition from tree models, (2) the occlusion problem in disparity prediction from tree models, (3) the problem of integrating the predicted disparities into image matching, (4) the tree model edge effect reduction on the disparity map, (5) the occlusion problem in orthophoto production, and (6) the foreshortening problem in image matching, which is very serious for conifer crown surfaces. Solutions to the above problems are necessary for successful crown surface reconstruction. The model-based approach was applied to recover the canopy surface of a dense redwood stand using tri-ocular high-resolution images scanned from 1:2,400 aerial photographs. The results demonstrate the approach's ability to reconstruct complicated stands. The model-based approach proposed in this thesis is potentially applicable to other surfaces recovering problems with a priori knowledge about objects.

Identification of material parameters for plasticity models: A comparative study on the finite element model updating and the virtual fields method

NASA Astrophysics Data System (ADS)

Martins, J. M. P.; Thuillier, S.; Andrade-Campos, A.

2018-05-01

The identification of material parameters, for a given constitutive model, can be seen as the first step before any practical application. In the last years, the field of material parameters identification received an important boost with the development of full-field measurement techniques, such as Digital Image Correlation. These techniques enable the use of heterogeneous displacement/strain fields, which contain more information than the classical homogeneous tests. Consequently, different techniques have been developed to extract material parameters from full-field measurements. In this study, two of these techniques are addressed, the Finite Element Model Updating (FEMU) and the Virtual Fields Method (VFM). The main idea behind FEMU is to update the parameters of a constitutive model implemented in a finite element model until both numerical and experimental results match, whereas VFM makes use of the Principle of Virtual Work and does not require any finite element simulation. Though both techniques proved their feasibility in linear and non-linear constitutive models, it is rather difficult to rank their robustness in plasticity. The purpose of this work is to perform a comparative study in the case of elasto-plastic models. Details concerning the implementation of each strategy are presented. Moreover, a dedicated code for VFM within a large strain framework is developed. The reconstruction of the stress field is performed through a user subroutine. A heterogeneous tensile test is considered to compare FEMU and VFM strategies.

Validation of pore network simulations of ex-situ water distributions in a gas diffusion layer of proton exchange membrane fuel cells with X-ray tomographic images

NASA Astrophysics Data System (ADS)

Agaesse, Tristan; Lamibrac, Adrien; Büchi, Felix N.; Pauchet, Joel; Prat, Marc

2016-11-01

Understanding and modeling two-phase flows in the gas diffusion layer (GDL) of proton exchange membrane fuel cells are important in order to improve fuel cells performance. They are scientifically challenging because of the peculiarities of GDLs microstructures. In the present work, simulations on a pore network model are compared to X-ray tomographic images of water distributions during an ex-situ water invasion experiment. A method based on watershed segmentation was developed to extract a pore network from the 3D segmented image of the dry GDL. Pore network modeling and a full morphology model were then used to perform two-phase simulations and compared to the experimental data. The results show good agreement between experimental and simulated microscopic water distributions. Pore network extraction parameters were also benchmarked using the experimental data and results from full morphology simulations.

Micromechanical Modeling of Storage Particles in Lithium Ion Batteries

NASA Astrophysics Data System (ADS)

Purkayastha, Rajlakshmi Tarun

The effect of stress on storage particles within a lithium ion battery, while acknowledged, is not understood very well. In this work three non-dimensional parameters were identified which govern the stress response within a spherical storage particle. These parameters are developed using material properties such as the diffusion coefficient, particle radius, partial molar volume and Young's modulus. Stress maps are then generated for various values of these parameters for fixed rates of insertion, applying boundary conditions similar to those found in a battery. Stress and concentration profiles for various values of these parameters show the coupling between stress and concentration is magnified depending on the values of the parameters. These maps can be used for different materials, depending on the value of the dimensionless parameters. The value of maximum stress generated is calculated for extraction as well as insertion of lithium into the particle. The model was then used to study to ellipsoidal particles in order to ascertain the effect of geometry on the maximum stress within the particle. By performing a parameter study, we can identify those materials for which particular aspect ratios of ellipsoids are more beneficial, in terms of reducing stress. We find that the stress peaks at certain aspect ratios, mostly at 2 and 1/ 2 . A parameter study was also performed on cubic particle. The values of maximum stresses for both insertion and extraction of lithium were plotted as contour plots. It was seen that the material parameters influenced the location of the maximum stress, with the maximum stress occurring either at the center of the edge between two faces or the point at the center of a face. Newer materials such as silicon are being touted as new lithium storage materials for batteries due to their higher capacity. Their tendency to rapidly loose capacity in a short period of time has led to a variety designs such are the use of carbon nanotubes or the use of coatings in order to mitigate the large expansion and stresses, which leads to spalling off of the material. We therefore extended the results for spherical storage particles to include the presence of an additional layer of material surrounding the storage particle. We perform a parameter study to see at which material properties are most beneficial in reducing stresses within the particle, and the results were tabulated. It was seen that thicker layers can lead to mitigation in the value of maximum stresses. A simple fracture analysis was carried out and the material parameters which would most likely cause crack growth to occur were identified. Finally an integrated 2-D model of a lithium ion battery was developed to study the mechanical stress in storage particles as a function of material properties. The effect of morphology on the stress and lithium concentration is studied for the case of extraction of lithium in terms of the previously developed non-dimensional parameters. Both, particles functioning in isolation were studied, as well as in closely-packed systems. The results show that the particle distance from the separator, in combination with the material properties of the particle, is critical in predicting the stress generated within the particle.

Flavonoid-rich fraction of the Monodora tenuifolia seed extract attenuates behavioural alterations and oxidative damage in forced-swim stressed rats.

PubMed

Ekeanyanwu, Raphael Chukwuma; Njoku, Obioma Uzoma

2015-03-01

The antidepressant effects of the flavonoid-rich fraction of Monodora tenuifolia seed extract were examined by assessing the extent of attenuation of behavioural alterations and oxidative damage in the rats that were stressed by forced swim test. Compared with the model control group, the altered behavioural parameters were attenuated significantly (P < 0.05) in the group treated with the flavonoid-rich fraction (100 and 200 mg·kg(-1)), comparable to the group treated with the standard drug, fluoxetine (10 mg·kg(-1)). The flavonoid-rich fraction and fluoxetine improved significantly (P < 0.05) the activities of the antioxidant enzymes such as superoxide dismutase and catalase as well as other biochemical parameters such as reduced glutathione, protein, and nitrite in the brain of the stressed rats. These results suggested that the flavonoid-rich fraction of Monodora tenuifolia seed extract exerted the antidepressant-like effects which could be useful in the management of stress induced disease. Copyright © 2015 China Pharmaceutical University. Published by Elsevier B.V. All rights reserved.

Maximum likelihood identification and optimal input design for identifying aircraft stability and control derivatives

NASA Technical Reports Server (NTRS)

Stepner, D. E.; Mehra, R. K.

1973-01-01

A new method of extracting aircraft stability and control derivatives from flight test data is developed based on the maximum likelihood cirterion. It is shown that this new method is capable of processing data from both linear and nonlinear models, both with and without process noise and includes output error and equation error methods as special cases. The first application of this method to flight test data is reported for lateral maneuvers of the HL-10 and M2/F3 lifting bodies, including the extraction of stability and control derivatives in the presence of wind gusts. All the problems encountered in this identification study are discussed. Several different methods (including a priori weighting, parameter fixing and constrained parameter values) for dealing with identifiability and uniqueness problems are introduced and the results given. The method for the design of optimal inputs for identifying the parameters of linear dynamic systems is also given. The criterion used for the optimization is the sensitivity of the system output to the unknown parameters. Several simple examples are first given and then the results of an extensive stability and control dervative identification simulation for a C-8 aircraft are detailed.

Effect of ultrasound on the supercritical CO2 extraction of bioactive compounds from dedo de moça pepper (Capsicum baccatum L. var. pendulum).

PubMed

Dias, Arthur Luiz Baião; Arroio Sergio, Camilla Scarelli; Santos, Philipe; Barbero, Gerardo Fernandéz; Rezende, Camila Alves; Martínez, Julian

2016-07-01

Extracts with bioactive compounds were obtained from the red pepper variety "dedo de moça" (Capsicum baccatum L. var. pendulum) through supercritical fluid extraction with carbon dioxide assisted by ultrasound (SFE-US). The process was tested at pressures of 15, 20 and 25 MPa; temperatures of 40, 50 and 60 °C, and ultrasonic powers of 200, 400 and 600 W applied during 40, 60 and 80 min of extraction. The CO2 mass flow rate was fixed at 1.7569 × 10(-4) kg/s. Global yield, phenolic content, antioxidant capacity and capsaicinoid concentration were evaluated in the extracts. The application of ultrasound raised the global extraction yield of SFE up to 45%. The phenolic content of the extract increased with the application of higher ultrasound power and radiation time. The capsaicinoid yield was also enhanced with ultrasound up to 12%. However, the antioxidant capacity did not increase with the ultrasound application. The BET-based model and the broken and intact cell model fitted well to the kinetic SFE curves. The BET-based model with three adjustable parameters resulted in the best fits to the experimental data. Field emission scanning electron microscopy (FESEM) images showed that SFE disturbed the vegetable matrix, releasing particles from the inner region of the plant cells to their surface. When the ultrasound was applied this effect was more pronounced. On the other hand, cracks, fissures or any sign of rupture were not identified on the sample surface. Copyright © 2016 Elsevier B.V. All rights reserved.

Current Thermal Emission from Photonic Nanostructures Composed of TA, W, GE, and HFO2 Thin Films

DTIC Science & Technology

2015-03-01

absorptive wavelength bands in the SWIR to LWIR range. Ellipsometric measurements and models were used in order to extract the optical constants of thin...parts of the complex dielectric function of tungsten at 294 K (room temperature) , 1100 K, 1600 K as calculated from the Drude model , Eq (25...real part and k is the imaginary. Values were obtained using the Drude model , Eq (25), with the measured optical parameters in Table 1 from [67] at

Ethanolic extracts of Inula viscosa, Salix alba and Quercus calliprinos, negatively affect the development of the entomopathogenic nematode, Heterorhabditis bacteriophora - A model to compare gastro-intestinal nematodes developmental effect.

PubMed

Santhi, Velayudhan Satheeja; Salame, Liora; Dvash, Levana; Muklada, Hussein; Azaizeh, Hassan; Mreny, Raghda; Awwad, Safaa; Markovics, Alex; Landau, Serge Yan; Glazer, Itamar

2017-05-01

Heterorhabditis bacteriophora can represent a model system for herbal medication against gastro-intestinal strongylid parasites in determining the recovery and development due to their unique parasitic infectious cycle. The fact that plant extracts impair nematode development is known but their differential impact on stages of the life cycle of H. bacteriophora has never been investigated. We examined the developmental stages resumed from eggs, young juveniles (J 1-3 ), infective juveniles (IJs), young and adult hermaphrodites of H. bacteriophora upon exposure to crude ethanolic extracts of Inula viscosa, Salix alba, and Quercus calliprinos at concentrations of 600, 1200, and 2400ppm. Our results showed that plant extracts were highly toxic to the survival of the eggs and young juveniles J 1 to J 3 at all concentrations. The plant extracts inhibited their development and were associated with low reproduction parameters (i.e. fecundity and viability of eggs). The IJs, J 4 , young and developed hermaphrodites displayed concentration-dependent negative effect on development with less egg count, poor vulval muscle development, loss of egg laying capacity and progeny development by matricidal hatching. Plant extract of I. viscosa at low (600ppm) concentration did not impair vulval development. These results suggest that these plant extracts show potential for the control of parasitic rhabditids. Copyright © 2017 Elsevier Inc. All rights reserved.

Design, Modeling, and Measurement of a Metamaterial Electromagnetic Field Concentrator

DTIC Science & Technology

2012-03-22

techniques to Kramers- Kronig relationship that do not appear to have this limitation [34, 67]. AFIT’s rapid design method utilizes several of these...extraction of metamaterial parameters based on Kramers- Kronig relationship,” IEEE Theory Tech. Soc., 58(10):2646–2653, 2010. [68] Teixeira, F. L. and W

Characterizing optical properties and spatial heterogeneity of human ovarian tissue using spatial frequency domain imaging

NASA Astrophysics Data System (ADS)

Nandy, Sreyankar; Mostafa, Atahar; Kumavor, Patrick D.; Sanders, Melinda; Brewer, Molly; Zhu, Quing

2016-10-01

A spatial frequency domain imaging (SFDI) system was developed for characterizing ex vivo human ovarian tissue using wide-field absorption and scattering properties and their spatial heterogeneities. Based on the observed differences between absorption and scattering images of different ovarian tissue groups, six parameters were quantitatively extracted. These are the mean absorption and scattering, spatial heterogeneities of both absorption and scattering maps measured by a standard deviation, and a fitting error of a Gaussian model fitted to normalized mean Radon transform of the absorption and scattering maps. A logistic regression model was used for classification of malignant and normal ovarian tissues. A sensitivity of 95%, specificity of 100%, and area under the curve of 0.98 were obtained using six parameters extracted from the SFDI images. The preliminary results demonstrate the diagnostic potential of the SFDI method for quantitative characterization of wide-field optical properties and the spatial distribution heterogeneity of human ovarian tissue. SFDI could be an extremely robust and valuable tool for evaluation of the ovary and detection of neoplastic changes of ovarian cancer.

SS-mPMG and SS-GA: tools for finding pathways and dynamic simulation of metabolic networks.

PubMed

Katsuragi, Tetsuo; Ono, Naoaki; Yasumoto, Keiichi; Altaf-Ul-Amin, Md; Hirai, Masami Y; Sriyudthsak, Kansuporn; Sawada, Yuji; Yamashita, Yui; Chiba, Yukako; Onouchi, Hitoshi; Fujiwara, Toru; Naito, Satoshi; Shiraishi, Fumihide; Kanaya, Shigehiko

2013-05-01

Metabolomics analysis tools can provide quantitative information on the concentration of metabolites in an organism. In this paper, we propose the minimum pathway model generator tool for simulating the dynamics of metabolite concentrations (SS-mPMG) and a tool for parameter estimation by genetic algorithm (SS-GA). SS-mPMG can extract a subsystem of the metabolic network from the genome-scale pathway maps to reduce the complexity of the simulation model and automatically construct a dynamic simulator to evaluate the experimentally observed behavior of metabolites. Using this tool, we show that stochastic simulation can reproduce experimentally observed dynamics of amino acid biosynthesis in Arabidopsis thaliana. In this simulation, SS-mPMG extracts the metabolic network subsystem from published databases. The parameters needed for the simulation are determined using a genetic algorithm to fit the simulation results to the experimental data. We expect that SS-mPMG and SS-GA will help researchers to create relevant metabolic networks and carry out simulations of metabolic reactions derived from metabolomics data.

Integration of Genetic Algorithms and Fuzzy Logic for Urban Growth Modeling

NASA Astrophysics Data System (ADS)

Foroutan, E.; Delavar, M. R.; Araabi, B. N.

2012-07-01

Urban growth phenomenon as a spatio-temporal continuous process is subject to spatial uncertainty. This inherent uncertainty cannot be fully addressed by the conventional methods based on the Boolean algebra. Fuzzy logic can be employed to overcome this limitation. Fuzzy logic preserves the continuity of dynamic urban growth spatially by choosing fuzzy membership functions, fuzzy rules and the fuzzification-defuzzification process. Fuzzy membership functions and fuzzy rule sets as the heart of fuzzy logic are rather subjective and dependent on the expert. However, due to lack of a definite method for determining the membership function parameters, certain optimization is needed to tune the parameters and improve the performance of the model. This paper integrates genetic algorithms and fuzzy logic as a genetic fuzzy system (GFS) for modeling dynamic urban growth. The proposed approach is applied for modeling urban growth in Tehran Metropolitan Area in Iran. Historical land use/cover data of Tehran Metropolitan Area extracted from the 1988 and 1999 Landsat ETM+ images are employed in order to simulate the urban growth. The extracted land use classes of the year 1988 include urban areas, street, vegetation areas, slope and elevation used as urban growth physical driving forces. Relative Operating Characteristic (ROC) curve as an fitness function has been used to evaluate the performance of the GFS algorithm. The optimum membership function parameter is applied for generating a suitability map for the urban growth. Comparing the suitability map and real land use map of 1999 gives the threshold value for the best suitability map which can simulate the land use map of 1999. The simulation outcomes in terms of kappa of 89.13% and overall map accuracy of 95.58% demonstrated the efficiency and reliability of the proposed model.

Decoding tactile afferent activity to obtain an estimate of instantaneous force and torque applied to the fingerpad

PubMed Central

Birznieks, Ingvars; Redmond, Stephen J.

2015-01-01

Dexterous manipulation is not possible without sensory information about object properties and manipulative forces. Fundamental neuroscience has been unable to demonstrate how information about multiple stimulus parameters may be continuously extracted, concurrently, from a population of tactile afferents. This is the first study to demonstrate this, using spike trains recorded from tactile afferents innervating the monkey fingerpad. A multiple-regression model, requiring no a priori knowledge of stimulus-onset times or stimulus combination, was developed to obtain continuous estimates of instantaneous force and torque. The stimuli consisted of a normal-force ramp (to a plateau of 1.8, 2.2, or 2.5 N), on top of which −3.5, −2.0, 0, +2.0, or +3.5 mNm torque was applied about the normal to the skin surface. The model inputs were sliding windows of binned spike counts recorded from each afferent. Models were trained and tested by 15-fold cross-validation to estimate instantaneous normal force and torque over the entire stimulation period. With the use of the spike trains from 58 slow-adapting type I and 25 fast-adapting type I afferents, the instantaneous normal force and torque could be estimated with small error. This study demonstrated that instantaneous force and torque parameters could be reliably extracted from a small number of tactile afferent responses in a real-time fashion with stimulus combinations that the model had not been exposed to during training. Analysis of the model weights may reveal how interactions between stimulus parameters could be disentangled for complex population responses and could be used to test neurophysiologically relevant hypotheses about encoding mechanisms. PMID:25948866

An online peak extraction algorithm for ion mobility spectrometry data.

PubMed

Kopczynski, Dominik; Rahmann, Sven

2015-01-01

Ion mobility (IM) spectrometry (IMS), coupled with multi-capillary columns (MCCs), has been gaining importance for biotechnological and medical applications because of its ability to detect and quantify volatile organic compounds (VOC) at low concentrations in the air or in exhaled breath at ambient pressure and temperature. Ongoing miniaturization of spectrometers creates the need for reliable data analysis on-the-fly in small embedded low-power devices. We present the first fully automated online peak extraction method for MCC/IMS measurements consisting of several thousand individual spectra. Each individual spectrum is processed as it arrives, removing the need to store the measurement before starting the analysis, as is currently the state of the art. Thus the analysis device can be an inexpensive low-power system such as the Raspberry Pi. The key idea is to extract one-dimensional peak models (with four parameters) from each spectrum and then merge these into peak chains and finally two-dimensional peak models. We describe the different algorithmic steps in detail and evaluate the online method against state-of-the-art peak extraction methods.

Practices in Wound Healing Studies of Plants

PubMed Central

Thakur, Rupesh; Jain, Nitika; Pathak, Raghvendra; Sandhu, Sardul Singh

2011-01-01

Wounds are the result of injuries to the skin that disrupt the other soft tissue. Healing of a wound is a complex and protracted process of tissue repair and remodeling in response to injury. Various plant products have been used in treatment of wounds over the years. Wound healing herbal extracts promote blood clotting, fight infection, and accelerate the healing of wounds. Phytoconstituents derived from plants need to be identified and screened for antimicrobial activity for management of wounds. The in vitro assays are useful, quick, and relatively inexpensive. Small animals provide a multitude of model choices for various human wound conditions. The study must be conducted after obtaining approval of the Ethics Committee and according to the guidelines for care and use of animals. The prepared formulations of herbal extract can be evaluated by various physicopharmaceutical parameters. The wound healing efficacies of various herbal extracts have been evaluated in excision, incision, dead space, and burn wound models. In vitro and in vivo assays are stepping stones to well-controlled clinical trials of herbal extracts. PMID:21716711

Modeling spray/puddle dissolution processes for deep-ultraviolet acid-hardened resists

NASA Astrophysics Data System (ADS)

Hutchinson, John M.; Das, Siddhartha; Qian, Qi-De; Gaw, Henry T.

1993-10-01

A study of the dissolution behavior of acid-hardened resists (AHR) was undertaken for spray and spray/puddle development processes. The Site Services DSM-100 end-point detection system is used to measure both spray and puddle dissolution data for a commercially available deep-ultraviolet AHR resist, Shipley SNR-248. The DSM allows in situ measurement of dissolution rate on the wafer chuck and hence allows parameter extraction for modeling spray and puddle processes. The dissolution data for spray and puddle processes was collected across a range of exposure dose and postexposure bake temperature. The development recipe was varied to decouple the contribution of the spray and puddle modes to the overall dissolution characteristics. The mechanisms involved in spray versus puddle dissolution and the impact of spray versus puddle dissolution on process performance metrics has been investigated. We used the effective-dose-modeling approach and the measurement capability of the DSM-100 and developed a lumped parameter model for acid-hardened resists that incorporates the effects of exposure, postexposure bake temperature and time, and development condition. The PARMEX photoresist-modeling program is used to determine parameters for the spray and for the puddle process. The lumped parameter AHR model developed showed good agreement with experimental data.

Determination of morphological parameters of biological cells by analysis of scattered-light distributions

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

Burger, D.E.

1979-11-01

The extraction of morphological parameters from biological cells by analysis of light-scatter patterns is described. A light-scattering measurement system has been designed and constructed that allows one to visually examine and photographically record biological cells or cell models and measure the light-scatter pattern of an individual cell or cell model. Using a laser or conventional illumination, the imaging system consists of a modified microscope with a 35 mm camera attached to record the cell image or light-scatter pattern. Models of biological cells were fabricated. The dynamic range and angular distributions of light scattered from these models was compared to calculatedmore » distributions. Spectrum analysis techniques applied on the light-scatter data give the sought after morphological cell parameters. These results compared favorably to shape parameters of the fabricated cell models confirming the mathematical model procedure. For nucleated biological material, correct nuclear and cell eccentricity as well as the nuclear and cytoplasmic diameters were determined. A method for comparing the flow equivalent of nuclear and cytoplasmic size to the actual dimensions is shown. This light-scattering experiment provides baseline information for automated cytology. In its present application, it involves correlating average size as measured in flow cytology to the actual dimensions determined from this technique. (ERB)« less

Beyond clay - using selective extractions to improve predictions of soil carbon content

NASA Astrophysics Data System (ADS)

Rasmussen, C.; Berhe, A. A.; Blankinship, J. C.; Crow, S. E.; Druhan, J. L.; Heckman, K. A.; Keiluweit, M.; Lawrence, C. R.; Marin-Spiotta, E.; Plante, A. F.; Schaedel, C.; Schimel, J.; Sierra, C. A.; Thompson, A.; Wagai, R.; Wieder, W. R.

2016-12-01

A central component of modern soil carbon (C) models is the use of clay content to scale the relative partitioning of decomposing plant material to respiration and mineral stabilized soil C. However, numerous pedon to plot scale studies indicate that other soil mineral parameters, such as Fe- or Al-oxyhydroxide content and specific surface area, may be more effective than clay alone for predicting soil C content and stabilization. Here we directly address the following question: Are there soil physicochemical parameters that represent mineral C association and soil C content that can replace or be used in conjunction with clay content as scalars in soil C models. We explored the relationship of soil C content to a number of soil physicochemical and physiographic parameters using the National Cooperative Soil Survey database that contains horizon level data for > 62,000 pedons spanning global ecoregions and geographic areas. The data indicated significant variation in the degree of correlation among soil C, clay and Fe-/Al-oxyhydroxides with increasing moisture variability. Specifically, dry, water-limited systems (PET/MAP > 1) presented strong positive correlations between clay and soil C, that decreased significantly to little or no correlation in wet, energy-limited systems (PET/MAP < 1). In contrast, the correlation of soil C to oxalate extractable Al+Fe increased significantly with increasing moisture availability. This pattern was particularly well expressed for subsurface B horizons. Multivariate analyses indicated similar patterns, with clear climate and ecosystem level variation in the degree of correlation among soil C and soil physicochemical properties. The results indicate a need to modify current soil C models to incorporate additional C partitioning parameters that better account for climate and ecoregion variability in C stabilization mechanisms.

Reliable inference of light curve parameters in the presence of systematics

NASA Astrophysics Data System (ADS)

Gibson, Neale P.

2016-10-01

Time-series photometry and spectroscopy of transiting exoplanets allow us to study their atmospheres. Unfortunately, the required precision to extract atmospheric information surpasses the design specifications of most general purpose instrumentation. This results in instrumental systematics in the light curves that are typically larger than the target precision. Systematics must therefore be modelled, leaving the inference of light-curve parameters conditioned on the subjective choice of systematics models and model-selection criteria. Here, I briefly review the use of systematics models commonly used for transmission and emission spectroscopy, including model selection, marginalisation over models, and stochastic processes. These form a hierarchy of models with increasing degree of objectivity. I argue that marginalisation over many systematics models is a minimal requirement for robust inference. Stochastic models provide even more flexibility and objectivity, and therefore produce the most reliable results. However, no systematics models are perfect, and the best strategy is to compare multiple methods and repeat observations where possible.

Efficient extraction strategies of tea (Camellia sinensis) biomolecules.

PubMed

Banerjee, Satarupa; Chatterjee, Jyotirmoy

2015-06-01

Tea is a popular daily beverage worldwide. Modulation and modifications of its basic components like catechins, alkaloids, proteins and carbohydrate during fermentation or extraction process changes organoleptic, gustatory and medicinal properties of tea. Through these processes increase or decrease in yield of desired components are evident. Considering the varied impacts of parameters in tea production, storage and processes that affect the yield, extraction of tea biomolecules at optimized condition is thought to be challenging. Implementation of technological advancements in green chemistry approaches can minimize the deviation retaining maximum qualitative properties in environment friendly way. Existed extraction processes with optimization parameters of tea have been discussed in this paper including its prospects and limitations. This exhaustive review of various extraction parameters, decaffeination process of tea and large scale cost effective isolation of tea components with aid of modern technology can assist people to choose extraction condition of tea according to necessity.

Parameterization of aquatic ecosystem functioning and its natural variation: Hierarchical Bayesian modelling of plankton food web dynamics

NASA Astrophysics Data System (ADS)

Norros, Veera; Laine, Marko; Lignell, Risto; Thingstad, Frede

2017-10-01

Methods for extracting empirically and theoretically sound parameter values are urgently needed in aquatic ecosystem modelling to describe key flows and their variation in the system. Here, we compare three Bayesian formulations for mechanistic model parameterization that differ in their assumptions about the variation in parameter values between various datasets: 1) global analysis - no variation, 2) separate analysis - independent variation and 3) hierarchical analysis - variation arising from a shared distribution defined by hyperparameters. We tested these methods, using computer-generated and empirical data, coupled with simplified and reasonably realistic plankton food web models, respectively. While all methods were adequate, the simulated example demonstrated that a well-designed hierarchical analysis can result in the most accurate and precise parameter estimates and predictions, due to its ability to combine information across datasets. However, our results also highlighted sensitivity to hyperparameter prior distributions as an important caveat of hierarchical analysis. In the more complex empirical example, hierarchical analysis was able to combine precise identification of parameter values with reasonably good predictive performance, although the ranking of the methods was less straightforward. We conclude that hierarchical Bayesian analysis is a promising tool for identifying key ecosystem-functioning parameters and their variation from empirical datasets.

Constraints on Average Radial Anisotropy in the Lower Mantle

NASA Astrophysics Data System (ADS)

Trampert, J.; De Wit, R. W. L.; Kaeufl, P.; Valentine, A. P.

2014-12-01

Quantifying uncertainties in seismological models is challenging, yet ideally quality assessment is an integral part of the inverse method. We invert centre frequencies for spheroidal and toroidal modes for three parameters of average radial anisotropy, density and P- and S-wave velocities in the lower mantle. We adopt a Bayesian machine learning approach to extract the information on the earth model that is available in the normal mode data. The method is flexible and allows us to infer probability density functions (pdfs), which provide a quantitative description of our knowledge of the individual earth model parameters. The parameters describing shear- and P-wave anisotropy show little deviations from isotropy, but the intermediate parameter η carries robust information on negative anisotropy of ~1% below 1900 km depth. The mass density in the deep mantle (below 1900 km) shows clear positive deviations from existing models. Other parameters (P- and shear-wave velocities) are close to PREM. Our results require that the average mantle is about 150K colder than commonly assumed adiabats and consist of a mixture of about 60% perovskite and 40% ferropericlase containing 10-15% iron. The anisotropy favours a specific orientation of the two minerals. This observation has important consequences for the nature of mantle flow.

Therapeutic Efficacy of Topically Applied Antioxidant Medicinal Plant Extracts in a Mouse Model of Experimental Dry Eye

PubMed Central

Lee, Jee Bum; Li, Ying; Choi, Ji Suk; Lee, Hyo Seok

2016-01-01

Purpose. To investigate the therapeutic effects of topical administration of antioxidant medicinal plant extracts in a mouse model of experimental dry eye (EDE). Methods. Eye drops containing balanced salt solution (BSS) or 0.001%, 0.01%, and 0.1% extracts were applied for the treatment of EDE. Tear volume, tear film break-up time (BUT), and corneal fluorescein staining scores were measured 10 days after desiccating stress. In addition, we evaluated the levels of interleukin- (IL-) 1β, tumor necrosis factor- (TNF-) α, IL-6, interferon- (IFN-) γ, and IFN-γ associated chemokines, percentage of CD4+C-X-C chemokine receptor type 3 positive (CXCR3+) T cells, goblet cell density, number of 4-hydroxy-2-nonenal (4-HNE) positive cells, and extracellular reactive oxygen species (ROS) production. Results. Compared to the EDE and BSS control groups, the mice treated with topical application of the 0.1% extract showed significant improvements in all clinical parameters, IL-1β, IL-6, TNF-α, and IFN-γ levels, percentage of CD4+CXCR3+ T cells, goblet cell density, number of 4-HNE-positive cells, and extracellular ROS production (P < 0.05). Conclusions. Topical application of 0.1% medicinal plant extracts improved clinical signs, decreased inflammation, and ameliorated oxidative stress marker and ROS production on the ocular surface of the EDE model mice. PMID:27313829

Multiphysics and Thermal Response Models to Improve Accuracy of Local Temperature Estimation in Rat Cortex under Microwave Exposure

PubMed Central

Kodera, Sachiko; Gomez-Tames, Jose; Hirata, Akimasa; Masuda, Hiroshi; Arima, Takuji; Watanabe, Soichi

2017-01-01

The rapid development of wireless technology has led to widespread concerns regarding adverse human health effects caused by exposure to electromagnetic fields. Temperature elevation in biological bodies is an important factor that can adversely affect health. A thermophysiological model is desired to quantify microwave (MW) induced temperature elevations. In this study, parameters related to thermophysiological responses for MW exposures were estimated using an electromagnetic-thermodynamics simulation technique. To the authors’ knowledge, this is the first study in which parameters related to regional cerebral blood flow in a rat model were extracted at a high degree of accuracy through experimental measurements for localized MW exposure at frequencies exceeding 6 GHz. The findings indicate that the improved modeling parameters yield computed results that match well with the measured quantities during and after exposure in rats. It is expected that the computational model will be helpful in estimating the temperature elevation in the rat brain at multiple observation points (that are difficult to measure simultaneously) and in explaining the physiological changes in the local cortex region. PMID:28358345

Constraining the symmetry energy with heavy-ion collisions and Bayesian analysis

NASA Astrophysics Data System (ADS)

Tsang, C. Y.; Jhang, G.; Morfouace, P.; Lynch, W. G.; Tsang, M. B.; HiRA Collaboration

2017-09-01

To extract constraints on symmetry energy terms in nuclear Equation of State (EoS), data from heavy ion reactions, are often compared to calculations from transport models. As multiple model input parameters are needed in the transport model, it is necessary to do multi-parameter analysis to understand the relationship especially if strong correlations exist among the parameters. In this talk, I will discuss how four symmetry energy parameters, So, (Symmetry energy) and L (slope) at saturation density as well as the nucleon scaler effective mass (ms*) and the nucleon effective mass splitting, (FI) are obtained by comparing transport mode results with experimental data such as isospin diffusions and n/p spectral ratios using MADAI Bayesian analysis software. Probability of each parameter having a certain value given experimental data can be calculated with Bayes theorem by Markov Chain Monte Carlo integration. Results using single and double ratios of neutron and proton spectra from 124Sn +124Sn, 112Sn +112Sn collisions at 120 MeV/u as well as isospin diffusion from Sn +Sn isotopes, at 50 and 35 MeV/u will be presented. This research is supported by the National Science Foundation under Grant No. PHY-1565546.

Three-dimensional modeling of tea-shoots using images and models.

PubMed

Wang, Jian; Zeng, Xianyin; Liu, Jianbing

2011-01-01

In this paper, a method for three-dimensional modeling of tea-shoots with images and calculation models is introduced. The process is as follows: the tea shoots are photographed with a camera, color space conversion is conducted, using an improved algorithm that is based on color and regional growth to divide the tea shoots in the images, and the edges of the tea shoots extracted with the help of edge detection; after that, using the divided tea-shoot images, the three-dimensional coordinates of the tea shoots are worked out and the feature parameters extracted, matching and calculation conducted according to the model database, and finally the three-dimensional modeling of tea-shoots is completed. According to the experimental results, this method can avoid a lot of calculations and has better visual effects and, moreover, performs better in recovering the three-dimensional information of the tea shoots, thereby providing a new method for monitoring the growth of and non-destructive testing of tea shoots.

A multiscale Markov random field model in wavelet domain for image segmentation

NASA Astrophysics Data System (ADS)

Dai, Peng; Cheng, Yu; Wang, Shengchun; Du, Xinyu; Wu, Dan

2017-07-01

The human vision system has abilities for feature detection, learning and selective attention with some properties of hierarchy and bidirectional connection in the form of neural population. In this paper, a multiscale Markov random field model in the wavelet domain is proposed by mimicking some image processing functions of vision system. For an input scene, our model provides its sparse representations using wavelet transforms and extracts its topological organization using MRF. In addition, the hierarchy property of vision system is simulated using a pyramid framework in our model. There are two information flows in our model, i.e., a bottom-up procedure to extract input features and a top-down procedure to provide feedback controls. The two procedures are controlled simply by two pyramidal parameters, and some Gestalt laws are also integrated implicitly. Equipped with such biological inspired properties, our model can be used to accomplish different image segmentation tasks, such as edge detection and region segmentation.

21SSD: a new public 21-cm EoR database

NASA Astrophysics Data System (ADS)

Eames, Evan; Semelin, Benoît

2018-05-01

With current efforts inching closer to detecting the 21-cm signal from the Epoch of Reionization (EoR), proper preparation will require publicly available simulated models of the various forms the signal could take. In this work we present a database of such models, available at 21ssd.obspm.fr. The models are created with a fully-coupled radiative hydrodynamic simulation (LICORICE), and are created at high resolution (10243). We also begin to analyse and explore the possible 21-cm EoR signals (with Power Spectra and Pixel Distribution Functions), and study the effects of thermal noise on our ability to recover the signal out to high redshifts. Finally, we begin to explore the concepts of `distance' between different models, which represents a crucial step towards optimising parameter space sampling, training neural networks, and finally extracting parameter values from observations.

Ultrasound assisted extraction of polysaccharides from Lentinus edodes and its anti-hepatitis B activity in vitro.

PubMed

Zhao, Yong-Ming; Yang, Jian-Ming; Liu, Ying-Hui; Zhao, Ming; Wang, Jin

2018-02-01

The aim of this study was to optimize the extraction process of polysaccharides from the fruiting bodies of Lentinus edodes and investigate its anti-hepatitis B virus activity. The extracting parameters including ultrasonic power (240-320W), extraction temperature (40-60°C) and extraction time (15-25min) was optimized by using three-variable-three-level Box-Behnken design based on the single-factor experiments. Data analysis results showed that the optimal conditions for extracting LEPs were an extraction temperature of 45°C, extraction time of 21min and ultrasonic power of 290W. Under these optimal conditions, the experimental yield of LEPs was 9.75%, a 1.62-fold increase compared with conventional heat water extraction (HWE). In addition, crude polysaccharides were purified to obtain two fractions (LEP-1 and LEP-2). Chemical analysis showed that these components were rich in glucose, arabinose and mannose. Furthermore, HepG2.2.15 cells were used as in vitro models to evaluate their anti-hepatitis B virus (HBV) activity. The results suggest that LEPs possesses potent anti-HBV activity in vitro. Copyright © 2017 Elsevier B.V. All rights reserved.

Modeling the mechanical properties of ultra-thin polymer films [Structural modeling of films of atomic scale thickness

DOE PAGES

Espinosa-Loza, Francisco; Stadermann, Michael; Aracne-Ruddle, Chantel; ...

2017-11-16

A modeling method to extract the mechanical properties of ultra-thin films (10–100 nm thick) from experimental data generated by indentation of freestanding circular films using a spherical indenter is presented. The relationship between the mechanical properties of the film and experimental parameters including load, and deflection are discussed in the context of a constitutive material model, test variables, and analytical approaches. As a result, elastic and plastic regimes are identified by comparison of finite element simulation and experimental data.

Modeling the mechanical properties of ultra-thin polymer films [Structural modeling of films of atomic scale thickness

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

Espinosa-Loza, Francisco; Stadermann, Michael; Aracne-Ruddle, Chantel

A modeling method to extract the mechanical properties of ultra-thin films (10–100 nm thick) from experimental data generated by indentation of freestanding circular films using a spherical indenter is presented. The relationship between the mechanical properties of the film and experimental parameters including load, and deflection are discussed in the context of a constitutive material model, test variables, and analytical approaches. As a result, elastic and plastic regimes are identified by comparison of finite element simulation and experimental data.

Stochastic mechanical model of vocal folds for producing jitter and for identifying pathologies through real voices.

PubMed

Cataldo, E; Soize, C

2018-06-06

Jitter, in voice production applications, is a random phenomenon characterized by the deviation of the glottal cycle length with respect to a mean value. Its study can help in identifying pathologies related to the vocal folds according to the values obtained through the different ways to measure it. This paper aims to propose a stochastic model, considering three control parameters, to generate jitter based on a deterministic one-mass model for the dynamics of the vocal folds and to identify parameters from the stochastic model taking into account real voice signals experimentally obtained. To solve the corresponding stochastic inverse problem, the cost function used is based on the distance between probability density functions of the random variables associated with the fundamental frequencies obtained by the experimental voices and the simulated ones, and also on the distance between features extracted from the voice signals, simulated and experimental, to calculate jitter. The results obtained show that the model proposed is valid and some samples of voices are synthesized considering the identified parameters for normal and pathological cases. The strategy adopted is also a novelty and mainly because a solution was obtained. In addition to the use of three parameters to construct the model of jitter, it is the discussion of a parameter related to the bandwidth of the power spectral density function of the stochastic process to measure the quality of the signal generated. A study about the influence of all the main parameters is also performed. The identification of the parameters of the model considering pathological cases is maybe of all novelties introduced by the paper the most interesting. Copyright © 2018 Elsevier Ltd. All rights reserved.

An algorithm for automatic parameter adjustment for brain extraction in BrainSuite

NASA Astrophysics Data System (ADS)

Rajagopal, Gautham; Joshi, Anand A.; Leahy, Richard M.

2017-02-01

Brain Extraction (classification of brain and non-brain tissue) of MRI brain images is a crucial pre-processing step necessary for imaging-based anatomical studies of the human brain. Several automated methods and software tools are available for performing this task, but differences in MR image parameters (pulse sequence, resolution) and instrumentand subject-dependent noise and artefacts affect the performance of these automated methods. We describe and evaluate a method that automatically adapts the default parameters of the Brain Surface Extraction (BSE) algorithm to optimize a cost function chosen to reflect accurate brain extraction. BSE uses a combination of anisotropic filtering, Marr-Hildreth edge detection, and binary morphology for brain extraction. Our algorithm automatically adapts four parameters associated with these steps to maximize the brain surface area to volume ratio. We evaluate the method on a total of 109 brain volumes with ground truth brain masks generated by an expert user. A quantitative evaluation of the performance of the proposed algorithm showed an improvement in the mean (s.d.) Dice coefficient from 0.8969 (0.0376) for default parameters to 0.9509 (0.0504) for the optimized case. These results indicate that automatic parameter optimization can result in significant improvements in definition of the brain mask.

Pectin from Husk Tomato (Physalis ixocarpa Brot.): Rheological behavior at different extraction conditions.

PubMed

Morales-Contreras, Blanca E; Rosas-Flores, Walfred; Contreras-Esquivel, Juan C; Wicker, Louise; Morales-Castro, Juliana

2018-01-01

A rheological study was carried out to evaluate formulations of test dispersions and gels of high methoxyl pectins (HTHMP) obtained at different conditions from husk tomato waste (Physalis ixocarpa Brot.). The effect of extraction agent (hydrochloric acid or citric acid), blanching time (10 or 15min) and extraction time (15, 20 or 25min) on the rheology of the tested samples was evaluated. Flow behavior and activation energy were evaluated on the test dispersions, while (E a ) frequency sweeps, temperature sweep, creep-recovery test and penetration test were performed on the gels. HTHMP dispersions showed shear thinning flow behavior, while showing a good fit to Cross model. Extraction agent, blanching time and extraction time did not have effect on Cross parameters (η z , η∞, C, and m). E a decreased as blanching time and extraction time increased. Frequency sweeps revealed high dependence on frequency for both G' and G", while temperature sweeps (25- 95°C) showed thermostable husk tomato pectin gels. Hydrocloric acid (HCl) extracted pectin gels showed stronger structure than citric acid (CA) gels. Copyright © 2017 Elsevier Ltd. All rights reserved.

Modeling of efficient light extraction in light-pipes through specular surfaces with elliptical and lineal front shapes

NASA Astrophysics Data System (ADS)

Sánchez-Guerrero, Guillermo E.; Viera-González, Perla M.; Ceballos-Herrera, Daniel E.; Martínez-Guerra, Edgar

2016-09-01

Extraction light in light-pipes with different specular surfaces was analyzed. In the analysis, the impact of the surface shape in all properties of the extracted light in order to obtain an efficient extraction and a uniform illumination using a LED as light source. Also, several parameters of the specular surface to obtain spatial uniformity inside the light-pipe are considered. In this case, the simulation was made for a rectangular light­pipe. One objective of this work is to compare how the front face shape of the specular surface can affect the extraction of light in the lateral face of the light-pipe, only straight and elliptical front faces were used in this work and the comparison between them at different tilts and lengths were made. The main purpose of the front face was extract the light uniformly at the lateral face and this was done by studying simulations on OpticStudio Zemax. The results show how the extraction length is lower in the elliptical front but its total power performs better than the line front.

S parameter and pseudo Nambu-Goldstone boson mass from lattice QCD.

PubMed

Shintani, E; Aoki, S; Fukaya, H; Hashimoto, S; Kaneko, T; Matsufuru, H; Onogi, T; Yamada, N

2008-12-12

We present a lattice calculation of L10, one of the low-energy constants in chiral perturbation theory, and the charged-neutral pion squared-mass splitting, using dynamical overlap fermion. The exact chiral symmetry of the overlap fermion allows us to reliably extract these quantities from the difference of the vacuum polarization functions for vector and axial-vector currents. In the context of the technicolor models, these two quantities are read as the S parameter and the pseudo Nambu-Goldstone boson mass, respectively, and play an important role in discriminating the models from others. This calculation can serve as a feasibility study of the lattice techniques for more general technicolor gauge theories.

Accuracy of Reaction Cross Section for Exotic Nuclei in Glauber Model Based on MCMC Diagnostics

NASA Astrophysics Data System (ADS)

Rueter, Keiti; Novikov, Ivan

2017-01-01

Parameters of a nuclear density distribution for an exotic nuclei with halo or skin structures can be determined from the experimentally measured reaction cross-section. In the presented work, to extract parameters such as nuclear size information for a halo and core, we compare experimental data on reaction cross-sections with values obtained using expressions of the Glauber Model. These calculations are performed using a Markov Chain Monte Carlo algorithm. We discuss the accuracy of the Monte Carlo approach and its dependence on k*, the power law turnover point in the discreet power spectrum of the random number sequence and on the lag-1 autocorrelation time of the random number sequence.

Latest astronomical constraints on some non-linear parametric dark energy models

NASA Astrophysics Data System (ADS)

Yang, Weiqiang; Pan, Supriya; Paliathanasis, Andronikos

2018-04-01

We consider non-linear redshift-dependent equation of state parameters as dark energy models in a spatially flat Friedmann-Lemaître-Robertson-Walker universe. To depict the expansion history of the universe in such cosmological scenarios, we take into account the large-scale behaviour of such parametric models and fit them using a set of latest observational data with distinct origin that includes cosmic microwave background radiation, Supernove Type Ia, baryon acoustic oscillations, redshift space distortion, weak gravitational lensing, Hubble parameter measurements from cosmic chronometers, and finally the local Hubble constant from Hubble space telescope. The fitting technique avails the publicly available code Cosmological Monte Carlo (COSMOMC), to extract the cosmological information out of these parametric dark energy models. From our analysis, it follows that those models could describe the late time accelerating phase of the universe, while they are distinguished from the Λ-cosmology.

3D refraction correction and extraction of clinical parameters from spectral domain optical coherence tomography of the cornea.

PubMed

Zhao, Mingtao; Kuo, Anthony N; Izatt, Joseph A

2010-04-26

Capable of three-dimensional imaging of the cornea with micrometer-scale resolution, spectral domain-optical coherence tomography (SDOCT) offers potential advantages over Placido ring and Scheimpflug photography based systems for accurate extraction of quantitative keratometric parameters. In this work, an SDOCT scanning protocol and motion correction algorithm were implemented to minimize the effects of patient motion during data acquisition. Procedures are described for correction of image data artifacts resulting from 3D refraction of SDOCT light in the cornea and from non-idealities of the scanning system geometry performed as a pre-requisite for accurate parameter extraction. Zernike polynomial 3D reconstruction and a recursive half searching algorithm (RHSA) were implemented to extract clinical keratometric parameters including anterior and posterior radii of curvature, central cornea optical power, central corneal thickness, and thickness maps of the cornea. Accuracy and repeatability of the extracted parameters obtained using a commercial 859nm SDOCT retinal imaging system with a corneal adapter were assessed using a rigid gas permeable (RGP) contact lens as a phantom target. Extraction of these parameters was performed in vivo in 3 patients and compared to commercial Placido topography and Scheimpflug photography systems. The repeatability of SDOCT central corneal power measured in vivo was 0.18 Diopters, and the difference observed between the systems averaged 0.1 Diopters between SDOCT and Scheimpflug photography, and 0.6 Diopters between SDOCT and Placido topography.

Combination of poroelasticity theory and constant strain rate test in modelling land subsidence due to groundwater extraction

NASA Astrophysics Data System (ADS)

Pham, Tien Hung; Rühaak, Wolfram; Sass, Ingo

2017-04-01

Extensive groundwater extraction leads to a drawdown of the ground water table. Consequently, soil effective stress increases and can cause land subsidence. Analysis of land subsidence generally requires a numerical model based on poroelasticity theory, which was first proposed by Biot (1941). In the review of regional land subsidence accompanying groundwater extraction, Galloway and Burbey (2011) stated that more research and application is needed in coupling of stress-dependent land subsidence process. In geotechnical field, the constant rate of strain tests (CRS) was first introduced in 1969 (Smith and Wahls 1969) and was standardized in 1982 through the designation D4186-82 by American Society for Testing and Materials. From the reading values of CRS tests, the stress-dependent parameters of poroelasticity model can be calculated. So far, there is no research to link poroelasticity theory with CRS tests in modelling land subsidence due to groundwater extraction. One dimensional CRS tests using conventional compression cell and three dimension CRS tests using Rowe cell were performed. The tests were also modelled by using finite element method with mixed elements. Back analysis technique is used to find the suitable values of hydraulic conductivity and bulk modulus that depend on the stress or void ratio. Finally, the obtained results are used in land subsidence models. Biot, M. A. (1941). "General theory of three-dimensional consolidation." Journal of applied physics 12(2): 155-164. Galloway, D. L. and T. J. Burbey (2011). "Review: Regional land subsidence accompanying groundwater extraction." Hydrogeology Journal 19(8): 1459-1486. Smith, R. E. and H. E. Wahls (1969). "Consolidation under constant rates of strain." Journal of Soil Mechanics & Foundations Div.

Determination of heat capacity of ionic liquid based nanofluids using group method of data handling technique

NASA Astrophysics Data System (ADS)

Sadi, Maryam

2018-01-01

In this study a group method of data handling model has been successfully developed to predict heat capacity of ionic liquid based nanofluids by considering reduced temperature, acentric factor and molecular weight of ionic liquids, and nanoparticle concentration as input parameters. In order to accomplish modeling, 528 experimental data points extracted from the literature have been divided into training and testing subsets. The training set has been used to predict model coefficients and the testing set has been applied for model validation. The ability and accuracy of developed model, has been evaluated by comparison of model predictions with experimental values using different statistical parameters such as coefficient of determination, mean square error and mean absolute percentage error. The mean absolute percentage error of developed model for training and testing sets are 1.38% and 1.66%, respectively, which indicate excellent agreement between model predictions and experimental data. Also, the results estimated by the developed GMDH model exhibit a higher accuracy when compared to the available theoretical correlations.

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

Harmon, S; Jeraj, R; Galavis, P

Purpose: Sensitivity of PET-derived texture features to reconstruction methods has been reported for features extracted from axial planes; however, studies often utilize three dimensional techniques. This work aims to quantify the impact of multi-plane (3D) vs. single-plane (2D) feature extraction on radiomics-based analysis, including sensitivity to reconstruction parameters and potential loss of spatial information. Methods: Twenty-three patients with solid tumors underwent [{sup 18}F]FDG PET/CT scans under identical protocols. PET data were reconstructed using five sets of reconstruction parameters. Tumors were segmented using an automatic, in-house algorithm robust to reconstruction variations. 50 texture features were extracted using two Methods: 2D patchesmore » along axial planes and 3D patches. For each method, sensitivity of features to reconstruction parameters was calculated as percent difference relative to the average value across reconstructions. Correlations between feature values were compared when using 2D and 3D extraction. Results: 21/50 features showed significantly different sensitivity to reconstruction parameters when extracted in 2D vs 3D (wilcoxon α<0.05), assessed by overall range of variation, Rangevar(%). Eleven showed greater sensitivity to reconstruction in 2D extraction, primarily first-order and co-occurrence features (average Rangevar increase 83%). The remaining ten showed higher variation in 3D extraction (average Range{sub var}increase 27%), mainly co-occurence and greylevel run-length features. Correlation of feature value extracted in 2D and feature value extracted in 3D was poor (R<0.5) in 12/50 features, including eight co-occurrence features. Feature-to-feature correlations in 2D were marginally higher than 3D, ∣R∣>0.8 in 16% and 13% of all feature combinations, respectively. Larger sensitivity to reconstruction parameters were seen for inter-feature correlation in 2D(σ=6%) than 3D (σ<1%) extraction. Conclusion: Sensitivity and correlation of various texture features were shown to significantly differ between 2D and 3D extraction. Additionally, inter-feature correlations were more sensitive to reconstruction variation using single-plane extraction. This work highlights a need for standardized feature extraction/selection techniques in radiomics.« less

Plant extract: a promising biomatrix for ecofriendly, controlled synthesis of silver nanoparticles.

PubMed

Borase, Hemant P; Salunke, Bipinchandra K; Salunkhe, Rahul B; Patil, Chandrashekhar D; Hallsworth, John E; Kim, Beom S; Patil, Satish V

2014-05-01

Uses of plants extracts are found to be more advantageous over chemical, physical and microbial (bacterial, fungal, algal) methods for silver nanoparticles (AgNPs) synthesis. In phytonanosynthesis, biochemical diversity of plant extract, non-pathogenicity, low cost and flexibility in reaction parameters are accounted for high rate of AgNPs production with different shape, size and applications. At the same time, care has to be taken to select suitable phytofactory for AgNPs synthesis based on certain parameters such as easy availability, large-scale nanosynthesis potential and non-toxic nature of plant extract. This review focuses on synthesis of AgNPs with particular emphasis on biological synthesis using plant extracts. Some points have been given on selection of plant extract for AgNPs synthesis and case studies on AgNPs synthesis using different plant extracts. Reaction parameters contributing to higher yield of nanoparticles are presented here. Synthesis mechanisms and overview of present and future applications of plant-extract-synthesized AgNPs are also discussed here. Limitations associated with use of AgNPs are summarised in the present review.

Fracture characterization by hybrid enumerative search and Gauss-Newton least-squares inversion methods

NASA Astrophysics Data System (ADS)

Alkharji, Mohammed N.

Most fracture characterization methods provide a general description of the fracture parameters as part of the reservoirs parameters; the fracture interaction and geometry within the reservoir is given less attention. T-Matrix and Linear Slip effective medium fracture models are implemented to invert the elastic tensor for the parameters and geometries of the fractures within the reservoir. The fracture inverse problem has an ill-posed, overdetermined, underconstrained rank-deficit system of equations. Least-squares inverse methods are used to solve the problem. A good starting initial model for the parameters is a key factor in the reliability of the inversion. Most methods assume that the starting parameters are close to the solution to avoid inaccurate local minimum solutions. The prior knowledge of the fracture parameters and their geometry is not available. We develop a hybrid, enumerative and Gauss-Newton, method that estimates the fracture parameters and geometry from the elastic tensor with no prior knowledge of the initial parameter values. The fracture parameters are separated into two groups. The first group contains the fracture parameters with no prior information, and the second group contains the parameters with known prior information. Different models are generated from the first group parameters by sampling the solution space over a predefined range of possible solutions for each parameter. Each model generated by the first group is fixed and used as a starting model to invert for the second group of parameters using the Gauss-Newton method. The least-squares residual between the observed elastic tensor and the estimated elastic tensor is calculated for each model. The model parameters that yield the least-squares residual corresponds to the correct fracture reservoir parameters and geometry. Two synthetic examples of fractured reservoirs with oil and gas saturations were inverted with no prior information about the fracture properties. The results showed that the hybrid algorithm successfully predicted the fracture parametrization, geometry, and the fluid content within the modeled reservoir. The method was also applied on an elastic tensor extracted from the Weyburn field in Saskatchewan, Canada. The solution suggested no presence of fractures but only a VTI system caused by the shale layering in the targeted reservoir, this interpretation is supported by other Weyburn field data.

LESTO: an Open Source GIS-based toolbox for LiDAR analysis

NASA Astrophysics Data System (ADS)

Franceschi, Silvia; Antonello, Andrea; Tonon, Giustino

2015-04-01

During the last five years different research institutes and private companies stared to implement new algorithms to analyze and extract features from LiDAR data but only a few of them also created a public available software. In the field of forestry there are different examples of software that can be used to extract the vegetation parameters from LiDAR data, unfortunately most of them are closed source (even if free), which means that the source code is not shared with the public for anyone to look at or make changes to. In 2014 we started the development of the library LESTO (LiDAR Empowered Sciences Toolbox Opensource): a set of modules for the analysis of LiDAR point cloud with an Open Source approach with the aim of improving the performance of the extraction of the volume of biomass and other vegetation parameters on large areas for mixed forest structures. LESTO contains a set of modules for data handling and analysis implemented within the JGrassTools spatial processing library. The main subsections are dedicated to 1) preprocessing of LiDAR raw data mainly in LAS format (utilities and filtering); 2) creation of raster derived products; 3) flight-lines identification and normalization of the intensity values; 4) tools for extraction of vegetation and buildings. The core of the LESTO library is the extraction of the vegetation parameters. We decided to follow the single tree based approach starting with the implementation of some of the most used algorithms in literature. These have been tweaked and applied on LiDAR derived raster datasets (DTM, DSM) as well as point clouds of raw data. The methods range between the simple extraction of tops and crowns from local maxima, the region growing method, the watershed method and individual tree segmentation on point clouds. The validation procedure consists in finding the matching between field and LiDAR-derived measurements at individual tree and plot level. An automatic validation procedure has been developed considering an Optimizer Algorithm based on Particle Swarm (PS) and a matching procedure which takes the position and the height of the extracted trees respect to the measured ones and iteratively tries to improve the candidate solution changing the models' parameters. Example of application of the LESTO tools will be presented on test sites. Test area consists in a series of circular sampling plots randomly selected from a 50x50 m regular grid within a buffer zone of 150 m from the forest road. Other studies on the same sites take as reference measurements of position, diameter, species and height and proposed allometric relationships. These allometric relationship were obtained for each species deriving the stem volume of single trees based on height and diameter at breast height. LESTO is integrated in the JGrassTools project and available for download at www.jgrasstools.org. A simple and easy to use graphical interface to run the models is available at https://github.com/moovida/STAGE/releases.

Kinematic model for the space-variant image motion of star sensors under dynamical conditions

NASA Astrophysics Data System (ADS)

Liu, Chao-Shan; Hu, Lai-Hong; Liu, Guang-Bin; Yang, Bo; Li, Ai-Jun

2015-06-01

A kinematic description of a star spot in the focal plane is presented for star sensors under dynamical conditions, which involves all necessary parameters such as the image motion, velocity, and attitude parameters of the vehicle. Stars at different locations of the focal plane correspond to the slightly different orientation and extent of motion blur, which characterize the space-variant point spread function. Finally, the image motion, the energy distribution, and centroid extraction are numerically investigated using the kinematic model under dynamic conditions. A centroid error of eight successive iterations <0.002 pixel is used as the termination criterion for the Richardson-Lucy deconvolution algorithm. The kinematic model of a star sensor is useful for evaluating the compensation algorithms of motion-blurred images.