Are quantitative sensitivity analysis methods always reliable?

NASA Astrophysics Data System (ADS)

Huang, X.

2016-12-01

Physical parameterizations developed to represent subgrid-scale physical processes include various uncertain parameters, leading to large uncertainties in today's Earth System Models (ESMs). Sensitivity Analysis (SA) is an efficient approach to quantitatively determine how the uncertainty of the evaluation metric can be apportioned to each parameter. Also, SA can identify the most influential parameters, as a result to reduce the high dimensional parametric space. In previous studies, some SA-based approaches, such as Sobol' and Fourier amplitude sensitivity testing (FAST), divide the parameters into sensitive and insensitive groups respectively. The first one is reserved but the other is eliminated for certain scientific study. However, these approaches ignore the disappearance of the interactive effects between the reserved parameters and the eliminated ones, which are also part of the total sensitive indices. Therefore, the wrong sensitive parameters might be identified by these traditional SA approaches and tools. In this study, we propose a dynamic global sensitivity analysis method (DGSAM), which iteratively removes the least important parameter until there are only two parameters left. We use the CLM-CASA, a global terrestrial model, as an example to verify our findings with different sample sizes ranging from 7000 to 280000. The result shows DGSAM has abilities to identify more influential parameters, which is confirmed by parameter calibration experiments using four popular optimization methods. For example, optimization using Top3 parameters filtered by DGSAM could achieve substantial improvement against Sobol' by 10%. Furthermore, the current computational cost for calibration has been reduced to 1/6 of the original one. In future, it is necessary to explore alternative SA methods emphasizing parameter interactions.

Automated Optimization of Potential Parameters

PubMed Central

Michele, Di Pierro; Ron, Elber

2013-01-01

An algorithm and software to refine parameters of empirical energy functions according to condensed phase experimental measurements are discussed. The algorithm is based on sensitivity analysis and local minimization of the differences between experiment and simulation as a function of potential parameters. It is illustrated for a toy problem of alanine dipeptide and is applied to folding of the peptide WAAAH. The helix fraction is highly sensitive to the potential parameters while the slope of the melting curve is not. The sensitivity variations make it difficult to satisfy both observations simultaneously. We conjecture that there is no set of parameters that reproduces experimental melting curves of short peptides that are modeled with the usual functional form of a force field. PMID:24015115

Sensitivity Challenge of Steep Transistors

NASA Astrophysics Data System (ADS)

Ilatikhameneh, Hesameddin; Ameen, Tarek A.; Chen, ChinYi; Klimeck, Gerhard; Rahman, Rajib

2018-04-01

Steep transistors are crucial in lowering power consumption of the integrated circuits. However, the difficulties in achieving steepness beyond the Boltzmann limit experimentally have hindered the fundamental challenges in application of these devices in integrated circuits. From a sensitivity perspective, an ideal switch should have a high sensitivity to the gate voltage and lower sensitivity to the device design parameters like oxide and body thicknesses. In this work, conventional tunnel-FET (TFET) and negative capacitance FET are shown to suffer from high sensitivity to device design parameters using full-band atomistic quantum transport simulations and analytical analysis. Although Dielectric Engineered (DE-) TFETs based on 2D materials show smaller sensitivity compared with the conventional TFETs, they have leakage issue. To mitigate this challenge, a novel DE-TFET design has been proposed and studied.

Investigation, development and application of optimal output feedback theory. Vol. 4: Measures of eigenvalue/eigenvector sensitivity to system parameters and unmodeled dynamics

NASA Technical Reports Server (NTRS)

Halyo, Nesim

1987-01-01

Some measures of eigenvalue and eigenvector sensitivity applicable to both continuous and discrete linear systems are developed and investigated. An infinite series representation is developed for the eigenvalues and eigenvectors of a system. The coefficients of the series are coupled, but can be obtained recursively using a nonlinear coupled vector difference equation. A new sensitivity measure is developed by considering the effects of unmodeled dynamics. It is shown that the sensitivity is high when any unmodeled eigenvalue is near a modeled eigenvalue. Using a simple example where the sensor dynamics have been neglected, it is shown that high feedback gains produce high eigenvalue/eigenvector sensitivity. The smallest singular value of the return difference is shown not to reflect eigenvalue sensitivity since it increases with the feedback gains. Using an upper bound obtained from the infinite series, a procedure to evaluate whether the sensitivity to parameter variations is within given acceptable bounds is developed and demonstrated by an example.

On Integral Upper Limits Assuming Power-law Spectra and the Sensitivity in High-energy Astronomy

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

Ahnen, Max L., E-mail: m.knoetig@gmail.com

The high-energy non-thermal universe is dominated by power-law-like spectra. Therefore, results in high-energy astronomy are often reported as parameters of power-law fits, or, in the case of a non-detection, as an upper limit assuming the underlying unseen spectrum behaves as a power law. In this paper, I demonstrate a simple and powerful one-to-one relation of the integral upper limit in the two-dimensional power-law parameter space into the spectrum parameter space and use this method to unravel the so-far convoluted question of the sensitivity of astroparticle telescopes.

Importance analysis for Hudson River PCB transport and fate model parameters using robust sensitivity studies

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

Zhang, S.; Toll, J.; Cothern, K.

1995-12-31

The authors have performed robust sensitivity studies of the physico-chemical Hudson River PCB model PCHEPM to identify the parameters and process uncertainties contributing the most to uncertainty in predictions of water column and sediment PCB concentrations, over the time period 1977--1991 in one segment of the lower Hudson River. The term ``robust sensitivity studies`` refers to the use of several sensitivity analysis techniques to obtain a more accurate depiction of the relative importance of different sources of uncertainty. Local sensitivity analysis provided data on the sensitivity of PCB concentration estimates to small perturbations in nominal parameter values. Range sensitivity analysismore » provided information about the magnitude of prediction uncertainty associated with each input uncertainty. Rank correlation analysis indicated which parameters had the most dominant influence on model predictions. Factorial analysis identified important interactions among model parameters. Finally, term analysis looked at the aggregate influence of combinations of parameters representing physico-chemical processes. The authors scored the results of the local and range sensitivity and rank correlation analyses. The authors considered parameters that scored high on two of the three analyses to be important contributors to PCB concentration prediction uncertainty, and treated them probabilistically in simulations. They also treated probabilistically parameters identified in the factorial analysis as interacting with important parameters. The authors used the term analysis to better understand how uncertain parameters were influencing the PCB concentration predictions. The importance analysis allowed us to reduce the number of parameters to be modeled probabilistically from 16 to 5. This reduced the computational complexity of Monte Carlo simulations, and more importantly, provided a more lucid depiction of prediction uncertainty and its causes.« less

[External respiration parameters in workers engaged in synthetic detergents production].

PubMed

Makhon'ko, M N; Trubetskov, A D

2005-01-01

The study covers results of thorough clinical and functional examination of workers engaged into contemporary chemical production. The authors studied effects caused in immunity parameters, respiratory organs and skin by sensitizing and irritating chemicals. Findings are that the most significant changes in external respiration parameters and high predisposition to respiratory diseases are associated with specific sensitizing to industrial allergen and with higher IgE levels.

Sensitivity Analysis of Biome-Bgc Model for Dry Tropical Forests of Vindhyan Highlands, India

NASA Astrophysics Data System (ADS)

Kumar, M.; Raghubanshi, A. S.

2011-08-01

A process-based model BIOME-BGC was run for sensitivity analysis to see the effect of ecophysiological parameters on net primary production (NPP) of dry tropical forest of India. The sensitivity test reveals that the forest NPP was highly sensitive to the following ecophysiological parameters: Canopy light extinction coefficient (k), Canopy average specific leaf area (SLA), New stem C : New leaf C (SC:LC), Maximum stomatal conductance (gs,max), C:N of fine roots (C:Nfr), All-sided to projected leaf area ratio and Canopy water interception coefficient (Wint). Therefore, these parameters need more precision and attention during estimation and observation in the field studies.

Sensitivity and Specificity of Eustachian Tube Function Tests in Adults

PubMed Central

Doyle, William J.; Swarts, J. Douglas; Banks, Julianne; Casselbrant, Margaretha L; Mandel, Ellen M; Alper, Cuneyt M.

2013-01-01

Objective Determine if Eustachian Tube (ET) function (ETF) tests can identify ears with physician-diagnosed ET dysfunction (ETD) in a mixed population at high sensitivity and specificity and define the inter-relatedness of ETF test parameters. Methods ETF was evaluated using the Forced-Response, Inflation-Deflation, Valsalva and Sniffing tests in 15 control ears of adult subjects after unilateral myringotomy (Group I) and in 23 ears of 19 adult subjects with ventilation tubes inserted for ETD (Group II). Data were analyzed using logistic regression including each parameter independently and then a step-down Discriminant Analysis including all ETF test parameters to predict group assignment. Factor Analysis operating over all parameters was used to explore relatedness. Results The Discriminant Analysis identified 4 ETF test parameters (Valsalva, ET opening pressure, dilatory efficiency and % positive pressure equilibrated) that together correctly assigned ears to Group II at a sensitivity of 95% and a specificity of 83%. Individual parameters representing the efficiency of ET opening during swallowing showed moderately accurate assignments of ears to their respective groups. Three factors captured approximately 98% of the variance among parameters, the first had negative loadings of the ETF structural parameters, the second had positive loadings of the muscle-assisted ET opening parameters and the third had negative loadings of the muscle-assisted ET opening parameters and positive loadings of the structural parameters. Discussion These results show that ETF tests can correctly assign individual ears to physician-diagnosed ETD with high sensitivity and specificity and that ETF test parameters can be grouped into structural-functional categories. PMID:23868429

Nuclear morphology for the detection of alterations in bronchial cells from lung cancer: an attempt to improve sensitivity and specificity.

PubMed

Fafin-Lefevre, Mélanie; Morlais, Fabrice; Guittet, Lydia; Clin, Bénédicte; Launoy, Guy; Galateau-Sallé, Françoise; Plancoulaine, Benoît; Herlin, Paulette; Letourneux, Marc

2011-08-01

To identify which morphologic or densitometric parameters are modified in cell nuclei from bronchopulmonary cancer based on 18 parameters involving shape, intensity, chromatin, texture, and DNA content and develop a bronchopulmonary cancer screening method relying on analysis of sputum sample cell nuclei. A total of 25 sputum samples from controls and 22 bronchial aspiration samples from patients presenting with bronchopulmonary cancer who were professionally exposed to cancer were used. After Feulgen staining, 18 morphologic and DNA content parameters were measured on cell nuclei, via image cytom- etry. A method was developed for analyzing distribution quantiles, compared with simply interpreting mean values, to characterize morphologic modifications in cell nuclei. Distribution analysis of parameters enabled us to distinguish 13 of 18 parameters that demonstrated significant differences between controls and cancer cases. These parameters, used alone, enabled us to distinguish two population types, with both sensitivity and specificity > 70%. Three parameters offered 100% sensitivity and specificity. When mean values offered high sensitivity and specificity, comparable or higher sensitivity and specificity values were observed for at least one of the corresponding quantiles. Analysis of modification in morphologic parameters via distribution analysis proved promising for screening bronchopulmonary cancer from sputum.

Local sensitivity analysis for inverse problems solved by singular value decomposition

USGS Publications Warehouse

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

2010-01-01

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

Pattern statistics on Markov chains and sensitivity to parameter estimation

PubMed Central

Nuel, Grégory

2006-01-01

Background: In order to compute pattern statistics in computational biology a Markov model is commonly used to take into account the sequence composition. Usually its parameter must be estimated. The aim of this paper is to determine how sensitive these statistics are to parameter estimation, and what are the consequences of this variability on pattern studies (finding the most over-represented words in a genome, the most significant common words to a set of sequences,...). Results: In the particular case where pattern statistics (overlap counting only) computed through binomial approximations we use the delta-method to give an explicit expression of σ, the standard deviation of a pattern statistic. This result is validated using simulations and a simple pattern study is also considered. Conclusion: We establish that the use of high order Markov model could easily lead to major mistakes due to the high sensitivity of pattern statistics to parameter estimation. PMID:17044916

Pattern statistics on Markov chains and sensitivity to parameter estimation.

PubMed

Nuel, Grégory

2006-10-17

In order to compute pattern statistics in computational biology a Markov model is commonly used to take into account the sequence composition. Usually its parameter must be estimated. The aim of this paper is to determine how sensitive these statistics are to parameter estimation, and what are the consequences of this variability on pattern studies (finding the most over-represented words in a genome, the most significant common words to a set of sequences,...). In the particular case where pattern statistics (overlap counting only) computed through binomial approximations we use the delta-method to give an explicit expression of sigma, the standard deviation of a pattern statistic. This result is validated using simulations and a simple pattern study is also considered. We establish that the use of high order Markov model could easily lead to major mistakes due to the high sensitivity of pattern statistics to parameter estimation.

[Application of Fourier amplitude sensitivity test in Chinese healthy volunteer population pharmacokinetic model of tacrolimus].

PubMed

Guan, Zheng; Zhang, Guan-min; Ma, Ping; Liu, Li-hong; Zhou, Tian-yan; Lu, Wei

2010-07-01

In this study, we evaluated the influence of different variance from each of the parameters on the output of tacrolimus population pharmacokinetic (PopPK) model in Chinese healthy volunteers, using Fourier amplitude sensitivity test (FAST). Besides, we estimated the index of sensitivity within whole course of blood sampling, designed different sampling times, and evaluated the quality of parameters' and the efficiency of prediction. It was observed that besides CL1/F, the index of sensitivity for all of the other four parameters (V1/F, V2/F, CL2/F and k(a)) in tacrolimus PopPK model showed relatively high level and changed fast with the time passing. With the increase of the variance of k(a), its indices of sensitivity increased obviously, associated with significant decrease in sensitivity index for the other parameters, and obvious change in peak time as well. According to the simulation of NONMEM and the comparison among different fitting results, we found that the sampling time points designed according to FAST surpassed the other time points. It suggests that FAST can access the sensitivities of model parameters effectively, and assist the design of clinical sampling times and the construction of PopPK model.

Two-step sensitivity testing of parametrized and regionalized life cycle assessments: methodology and case study.

PubMed

Mutel, Christopher L; de Baan, Laura; Hellweg, Stefanie

2013-06-04

Comprehensive sensitivity analysis is a significant tool to interpret and improve life cycle assessment (LCA) models, but is rarely performed. Sensitivity analysis will increase in importance as inventory databases become regionalized, increasing the number of system parameters, and parametrized, adding complexity through variables and nonlinear formulas. We propose and implement a new two-step approach to sensitivity analysis. First, we identify parameters with high global sensitivities for further examination and analysis with a screening step, the method of elementary effects. Second, the more computationally intensive contribution to variance test is used to quantify the relative importance of these parameters. The two-step sensitivity test is illustrated on a regionalized, nonlinear case study of the biodiversity impacts from land use of cocoa production, including a worldwide cocoa products trade model. Our simplified trade model can be used for transformable commodities where one is assessing market shares that vary over time. In the case study, the highly uncertain characterization factors for the Ivory Coast and Ghana contributed more than 50% of variance for almost all countries and years examined. The two-step sensitivity test allows for the interpretation, understanding, and improvement of large, complex, and nonlinear LCA systems.

Case-Deletion Diagnostics for Maximum Likelihood Multipoint Quantitative Trait Locus Linkage Analysis

PubMed Central

Mendoza, Maria C.B.; Burns, Trudy L.; Jones, Michael P.

2009-01-01

Objectives Case-deletion diagnostic methods are tools that allow identification of influential observations that may affect parameter estimates and model fitting conclusions. The goal of this paper was to develop two case-deletion diagnostics, the exact case deletion (ECD) and the empirical influence function (EIF), for detecting outliers that can affect results of sib-pair maximum likelihood quantitative trait locus (QTL) linkage analysis. Methods Subroutines to compute the ECD and EIF were incorporated into the maximum likelihood QTL variance estimation components of the linkage analysis program MAPMAKER/SIBS. Performance of the diagnostics was compared in simulation studies that evaluated the proportion of outliers correctly identified (sensitivity), and the proportion of non-outliers correctly identified (specificity). Results Simulations involving nuclear family data sets with one outlier showed EIF sensitivities approximated ECD sensitivities well for outlier-affected parameters. Sensitivities were high, indicating the outlier was identified a high proportion of the time. Simulations also showed the enormous computational time advantage of the EIF. Diagnostics applied to body mass index in nuclear families detected observations influential on the lod score and model parameter estimates. Conclusions The EIF is a practical diagnostic tool that has the advantages of high sensitivity and quick computation. PMID:19172086

New parameters in adaptive testing of ferromagnetic materials utilizing magnetic Barkhausen noise

NASA Astrophysics Data System (ADS)

Pal'a, Jozef; Ušák, Elemír

2016-03-01

A new method of magnetic Barkhausen noise (MBN) measurement and optimization of the measured data processing with respect to non-destructive evaluation of ferromagnetic materials was tested. Using this method we tried to found, if it is possible to enhance sensitivity and stability of measurement results by replacing the traditional MBN parameter (root mean square) with some new parameter. In the tested method, a complex set of the MBN from minor hysteresis loops is measured. Afterward, the MBN data are collected into suitably designed matrices and optimal parameters of MBN with respect to maximum sensitivity to the evaluated variable are searched. The method was verified on plastically deformed steel samples. It was shown that the proposed measuring method and measured data processing bring an improvement of the sensitivity to the evaluated variable when comparing with measuring traditional MBN parameter. Moreover, we found a parameter of MBN, which is highly resistant to the changes of applied field amplitude and at the same time it is noticeably more sensitive to the evaluated variable.

A High-Sensitivity Current Sensor Utilizing CrNi Wire and Microfiber Coils

PubMed Central

Xie, Xiaodong; Li, Jie; Sun, Li-Peng; Shen, Xiang; Jin, Long; Guan, Bai-ou

2014-01-01

We obtain an extremely high current sensitivity by wrapping a section of microfiber on a thin-diameter chromium-nickel wire. Our detected current sensitivity is as high as 220.65 nm/A2 for a structure length of only 35 μm. Such sensitivity is two orders of magnitude higher than the counterparts reported in the literature. Analysis shows that a higher resistivity or/and a thinner diameter of the metal wire may produce higher sensitivity. The effects of varying the structure parameters on sensitivity are discussed. The presented structure has potential for low-current sensing or highly electrically-tunable filtering applications. PMID:24824372

A high-sensitivity current sensor utilizing CrNi wire and microfiber coils.

PubMed

Xie, Xiaodong; Li, Jie; Sun, Li-Peng; Shen, Xiang; Jin, Long; Guan, Bai-ou

2014-05-12

We obtain an extremely high current sensitivity by wrapping a section of microfiber on a thin-diameter chromium-nickel wire. Our detected current sensitivity is as high as 220.65 nm/A2 for a structure length of only 35 μm. Such sensitivity is two orders of magnitude higher than the counterparts reported in the literature. Analysis shows that a higher resistivity or/and a thinner diameter of the metal wire may produce higher sensitivity. The effects of varying the structure parameters on sensitivity are discussed. The presented structure has potential for low-current sensing or highly electrically-tunable filtering applications.

High sensitivity tests of the standard model for electroweak interactions. [Lepton-family-number-violating decay; Michel [rho] parameter

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

Koetke, D.D.; Manweiler, R.W.; Shirvel Stanislaus, T.D.

1993-01-01

The work done on this project was focused on two LAMPF experiments. The MEGA experiment, a high-sensitivity search for the lepton-family-number-violating decay [mu] [yields] e [gamma] to a sensitivity which, measured in terms of the branching ratio, BR = [[mu] [yields] e [gamma

Algorithm sensitivity analysis and parameter tuning for tissue image segmentation pipelines

PubMed Central

Kurç, Tahsin M.; Taveira, Luís F. R.; Melo, Alba C. M. A.; Gao, Yi; Kong, Jun; Saltz, Joel H.

2017-01-01

Abstract Motivation: Sensitivity analysis and parameter tuning are important processes in large-scale image analysis. They are very costly because the image analysis workflows are required to be executed several times to systematically correlate output variations with parameter changes or to tune parameters. An integrated solution with minimum user interaction that uses effective methodologies and high performance computing is required to scale these studies to large imaging datasets and expensive analysis workflows. Results: The experiments with two segmentation workflows show that the proposed approach can (i) quickly identify and prune parameters that are non-influential; (ii) search a small fraction (about 100 points) of the parameter search space with billions to trillions of points and improve the quality of segmentation results (Dice and Jaccard metrics) by as much as 1.42× compared to the results from the default parameters; (iii) attain good scalability on a high performance cluster with several effective optimizations. Conclusions: Our work demonstrates the feasibility of performing sensitivity analyses, parameter studies and auto-tuning with large datasets. The proposed framework can enable the quantification of error estimations and output variations in image segmentation pipelines. Availability and Implementation: Source code: https://github.com/SBU-BMI/region-templates/. Contact: teodoro@unb.br Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28062445

Algorithm sensitivity analysis and parameter tuning for tissue image segmentation pipelines.

PubMed

Teodoro, George; Kurç, Tahsin M; Taveira, Luís F R; Melo, Alba C M A; Gao, Yi; Kong, Jun; Saltz, Joel H

2017-04-01

Sensitivity analysis and parameter tuning are important processes in large-scale image analysis. They are very costly because the image analysis workflows are required to be executed several times to systematically correlate output variations with parameter changes or to tune parameters. An integrated solution with minimum user interaction that uses effective methodologies and high performance computing is required to scale these studies to large imaging datasets and expensive analysis workflows. The experiments with two segmentation workflows show that the proposed approach can (i) quickly identify and prune parameters that are non-influential; (ii) search a small fraction (about 100 points) of the parameter search space with billions to trillions of points and improve the quality of segmentation results (Dice and Jaccard metrics) by as much as 1.42× compared to the results from the default parameters; (iii) attain good scalability on a high performance cluster with several effective optimizations. Our work demonstrates the feasibility of performing sensitivity analyses, parameter studies and auto-tuning with large datasets. The proposed framework can enable the quantification of error estimations and output variations in image segmentation pipelines. Source code: https://github.com/SBU-BMI/region-templates/ . teodoro@unb.br. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Sensitivity Analysis of Mechanical Parameters of Different Rock Layers to the Stability of Coal Roadway in Soft Rock Strata

PubMed Central

Zhao, Zeng-hui; Wang, Wei-ming; Gao, Xin; Yan, Ji-xing

2013-01-01

According to the geological characteristics of Xinjiang Ili mine in western area of China, a physical model of interstratified strata composed of soft rock and hard coal seam was established. Selecting the tunnel position, deformation modulus, and strength parameters of each layer as influencing factors, the sensitivity coefficient of roadway deformation to each parameter was firstly analyzed based on a Mohr-Columb strain softening model and nonlinear elastic-plastic finite element analysis. Then the effect laws of influencing factors which showed high sensitivity were further discussed. Finally, a regression model for the relationship between roadway displacements and multifactors was obtained by equivalent linear regression under multiple factors. The results show that the roadway deformation is highly sensitive to the depth of coal seam under the floor which should be considered in the layout of coal roadway; deformation modulus and strength of coal seam and floor have a great influence on the global stability of tunnel; on the contrary, roadway deformation is not sensitive to the mechanical parameters of soft roof; roadway deformation under random combinations of multi-factors can be deduced by the regression model. These conclusions provide theoretical significance to the arrangement and stability maintenance of coal roadway. PMID:24459447

Efficient estimators for likelihood ratio sensitivity indices of complex stochastic dynamics.

PubMed

Arampatzis, Georgios; Katsoulakis, Markos A; Rey-Bellet, Luc

2016-03-14

We demonstrate that centered likelihood ratio estimators for the sensitivity indices of complex stochastic dynamics are highly efficient with low, constant in time variance and consequently they are suitable for sensitivity analysis in long-time and steady-state regimes. These estimators rely on a new covariance formulation of the likelihood ratio that includes as a submatrix a Fisher information matrix for stochastic dynamics and can also be used for fast screening of insensitive parameters and parameter combinations. The proposed methods are applicable to broad classes of stochastic dynamics such as chemical reaction networks, Langevin-type equations and stochastic models in finance, including systems with a high dimensional parameter space and/or disparate decorrelation times between different observables. Furthermore, they are simple to implement as a standard observable in any existing simulation algorithm without additional modifications.

Efficient estimators for likelihood ratio sensitivity indices of complex stochastic dynamics

NASA Astrophysics Data System (ADS)

Arampatzis, Georgios; Katsoulakis, Markos A.; Rey-Bellet, Luc

2016-03-01

We demonstrate that centered likelihood ratio estimators for the sensitivity indices of complex stochastic dynamics are highly efficient with low, constant in time variance and consequently they are suitable for sensitivity analysis in long-time and steady-state regimes. These estimators rely on a new covariance formulation of the likelihood ratio that includes as a submatrix a Fisher information matrix for stochastic dynamics and can also be used for fast screening of insensitive parameters and parameter combinations. The proposed methods are applicable to broad classes of stochastic dynamics such as chemical reaction networks, Langevin-type equations and stochastic models in finance, including systems with a high dimensional parameter space and/or disparate decorrelation times between different observables. Furthermore, they are simple to implement as a standard observable in any existing simulation algorithm without additional modifications.

Efficient estimators for likelihood ratio sensitivity indices of complex stochastic dynamics

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

Arampatzis, Georgios; Katsoulakis, Markos A.; Rey-Bellet, Luc

2016-03-14

We demonstrate that centered likelihood ratio estimators for the sensitivity indices of complex stochastic dynamics are highly efficient with low, constant in time variance and consequently they are suitable for sensitivity analysis in long-time and steady-state regimes. These estimators rely on a new covariance formulation of the likelihood ratio that includes as a submatrix a Fisher information matrix for stochastic dynamics and can also be used for fast screening of insensitive parameters and parameter combinations. The proposed methods are applicable to broad classes of stochastic dynamics such as chemical reaction networks, Langevin-type equations and stochastic models in finance, including systemsmore » with a high dimensional parameter space and/or disparate decorrelation times between different observables. Furthermore, they are simple to implement as a standard observable in any existing simulation algorithm without additional modifications.« less

Sensitivity analysis and nonlinearity assessment of steam cracking furnace process

NASA Astrophysics Data System (ADS)

Rosli, M. N.; Sudibyo, Aziz, N.

2017-11-01

In this paper, sensitivity analysis and nonlinearity assessment of cracking furnace process are presented. For the sensitivity analysis, the fractional factorial design method is employed as a method to analyze the effect of input parameters, which consist of four manipulated variables and two disturbance variables, to the output variables and to identify the interaction between each parameter. The result of the factorial design method is used as a screening method to reduce the number of parameters, and subsequently, reducing the complexity of the model. It shows that out of six input parameters, four parameters are significant. After the screening is completed, step test is performed on the significant input parameters to assess the degree of nonlinearity of the system. The result shows that the system is highly nonlinear with respect to changes in an air-to-fuel ratio (AFR) and feed composition.

A geostatistics-informed hierarchical sensitivity analysis method for complex groundwater flow and transport modeling: GEOSTATISTICAL SENSITIVITY ANALYSIS

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

Dai, Heng; Chen, Xingyuan; Ye, Ming

Sensitivity analysis is an important tool for quantifying uncertainty in the outputs of mathematical models, especially for complex systems with a high dimension of spatially correlated parameters. Variance-based global sensitivity analysis has gained popularity because it can quantify the relative contribution of uncertainty from different sources. However, its computational cost increases dramatically with the complexity of the considered model and the dimension of model parameters. In this study we developed a hierarchical sensitivity analysis method that (1) constructs an uncertainty hierarchy by analyzing the input uncertainty sources, and (2) accounts for the spatial correlation among parameters at each level ofmore » the hierarchy using geostatistical tools. The contribution of uncertainty source at each hierarchy level is measured by sensitivity indices calculated using the variance decomposition method. Using this methodology, we identified the most important uncertainty source for a dynamic groundwater flow and solute transport in model at the Department of Energy (DOE) Hanford site. The results indicate that boundary conditions and permeability field contribute the most uncertainty to the simulated head field and tracer plume, respectively. The relative contribution from each source varied spatially and temporally as driven by the dynamic interaction between groundwater and river water at the site. By using a geostatistical approach to reduce the number of realizations needed for the sensitivity analysis, the computational cost of implementing the developed method was reduced to a practically manageable level. The developed sensitivity analysis method is generally applicable to a wide range of hydrologic and environmental problems that deal with high-dimensional spatially-distributed parameters.« less

Design of experiments for identification of complex biochemical systems with applications to mitochondrial bioenergetics.

PubMed

Vinnakota, Kalyan C; Beard, Daniel A; Dash, Ranjan K

2009-01-01

Identification of a complex biochemical system model requires appropriate experimental data. Models constructed on the basis of data from the literature often contain parameters that are not identifiable with high sensitivity and therefore require additional experimental data to identify those parameters. Here we report the application of a local sensitivity analysis to design experiments that will improve the identifiability of previously unidentifiable model parameters in a model of mitochondrial oxidative phosphorylation and tricaboxylic acid cycle. Experiments were designed based on measurable biochemical reactants in a dilute suspension of purified cardiac mitochondria with experimentally feasible perturbations to this system. Experimental perturbations and variables yielding the most number of parameters above a 5% sensitivity level are presented and discussed.

Assessment of Spatial Transferability of Process-Based Hydrological Model Parameters in Two Neighboring Catchments in the Himalayan Region

NASA Astrophysics Data System (ADS)

Nepal, S.

2016-12-01

The spatial transferability of the model parameters of the process-oriented distributed J2000 hydrological model was investigated in two glaciated sub-catchments of the Koshi river basin in eastern Nepal. The basins had a high degree of similarity with respect to their static landscape features. The model was first calibrated (1986-1991) and validated (1992-1997) in the Dudh Koshi sub-catchment. The calibrated and validated model parameters were then transferred to the nearby Tamor catchment (2001-2009). A sensitivity and uncertainty analysis was carried out for both sub-catchments to discover the sensitivity range of the parameters in the two catchments. The model represented the overall hydrograph well in both sub-catchments, including baseflow and medium range flows (rising and recession limbs). The efficiency results according to both Nash-Sutcliffe and the coefficient of determination was above 0.84 in both cases. The sensitivity analysis showed that the same parameter was most sensitive for Nash-Sutcliffe (ENS) and Log Nash-Sutcliffe (LNS) efficiencies in both catchments. However, there were some differences in sensitivity to ENS and LNS for moderate and low sensitive parameters, although the majority (13 out of 16 for ENS and 16 out of 16 for LNS) had a sensitivity response in a similar range. A generalized likelihood uncertainty estimation (GLUE) result suggest that most of the time the observed runoff is within the parameter uncertainty range, although occasionally the values lie outside the uncertainty range, especially during flood peaks and more in the Tamor. This may be due to the limited input data resulting from the small number of precipitation stations and lack of representative stations in high-altitude areas, as well as to model structural uncertainty. The results indicate that transfer of the J2000 parameters to a neighboring catchment in the Himalayan region with similar physiographic landscape characteristics is viable. This indicates the possibility of applying process-based J2000 model be to the ungauged catchments in the Himalayan region, which could provide important insights into the hydrological system dynamics and provide much needed information to support water resources planning and management.

Analyses of a heterogeneous lattice hydrodynamic model with low and high-sensitivity vehicles

NASA Astrophysics Data System (ADS)

Kaur, Ramanpreet; Sharma, Sapna

2018-06-01

Basic lattice model is extended to study the heterogeneous traffic by considering the optimal current difference effect on a unidirectional single lane highway. Heterogeneous traffic consisting of low- and high-sensitivity vehicles is modeled and their impact on stability of mixed traffic flow has been examined through linear stability analysis. The stability of flow is investigated in five distinct regions of the neutral stability diagram corresponding to the amount of higher sensitivity vehicles present on road. In order to investigate the propagating behavior of density waves non linear analysis is performed and near the critical point, the kink antikink soliton is obtained by driving mKdV equation. The effect of fraction parameter corresponding to high sensitivity vehicles is investigated and the results indicates that the stability rise up due to the fraction parameter. The theoretical findings are verified via direct numerical simulation.

Assessment of Wind Parameter Sensitivity on Ultimate and Fatigue Wind Turbine Loads: Preprint

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

Robertson, Amy N; Sethuraman, Latha; Jonkman, Jason

Wind turbines are designed using a set of simulations to ascertain the structural loads that the turbine could encounter. While mean hub-height wind speed is considered to vary, other wind parameters such as turbulence spectra, sheer, veer, spatial coherence, and component correlation are fixed or conditional values that, in reality, could have different characteristics at different sites and have a significant effect on the resulting loads. This paper therefore seeks to assess the sensitivity of different wind parameters on the resulting ultimate and fatigue loads on the turbine during normal operational conditions. Eighteen different wind parameters are screened using anmore » Elementary Effects approach with radial points. As expected, the results show a high sensitivity of the loads to the turbulence standard deviation in the primary wind direction, but the sensitivity to wind shear is often much greater. To a lesser extent, other wind parameters that drive loads include the coherence in the primary wind direction and veer.« less

Assessment of Wind Parameter Sensitivity on Extreme and Fatigue Wind Turbine Loads

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

Robertson, Amy N; Sethuraman, Latha; Jonkman, Jason

Wind turbines are designed using a set of simulations to ascertain the structural loads that the turbine could encounter. While mean hub-height wind speed is considered to vary, other wind parameters such as turbulence spectra, sheer, veer, spatial coherence, and component correlation are fixed or conditional values that, in reality, could have different characteristics at different sites and have a significant effect on the resulting loads. This paper therefore seeks to assess the sensitivity of different wind parameters on the resulting ultimate and fatigue loads on the turbine during normal operational conditions. Eighteen different wind parameters are screened using anmore » Elementary Effects approach with radial points. As expected, the results show a high sensitivity of the loads to the turbulence standard deviation in the primary wind direction, but the sensitivity to wind shear is often much greater. To a lesser extent, other wind parameters that drive loads include the coherence in the primary wind direction and veer.« less

Improving the analysis of slug tests

USGS Publications Warehouse

McElwee, C.D.

2002-01-01

This paper examines several techniques that have the potential to improve the quality of slug test analysis. These techniques are applicable in the range from low hydraulic conductivities with overdamped responses to high hydraulic conductivities with nonlinear oscillatory responses. Four techniques for improving slug test analysis will be discussed: use of an extended capability nonlinear model, sensitivity analysis, correction for acceleration and velocity effects, and use of multiple slug tests. The four-parameter nonlinear slug test model used in this work is shown to allow accurate analysis of slug tests with widely differing character. The parameter ?? represents a correction to the water column length caused primarily by radius variations in the wellbore and is most useful in matching the oscillation frequency and amplitude. The water column velocity at slug initiation (V0) is an additional model parameter, which would ideally be zero but may not be due to the initiation mechanism. The remaining two model parameters are A (parameter for nonlinear effects) and K (hydraulic conductivity). Sensitivity analysis shows that in general ?? and V0 have the lowest sensitivity and K usually has the highest. However, for very high K values the sensitivity to A may surpass the sensitivity to K. Oscillatory slug tests involve higher accelerations and velocities of the water column; thus, the pressure transducer responses are affected by these factors and the model response must be corrected to allow maximum accuracy for the analysis. The performance of multiple slug tests will allow some statistical measure of the experimental accuracy and of the reliability of the resulting aquifer parameters. ?? 2002 Elsevier Science B.V. All rights reserved.

Automated Processing of Dynamic Contrast-Enhanced MRI: Correlation of Advanced Pharmacokinetic Metrics with Tumor Grade in Pediatric Brain Tumors.

PubMed

Vajapeyam, S; Stamoulis, C; Ricci, K; Kieran, M; Poussaint, T Young

2017-01-01

Pharmacokinetic parameters from dynamic contrast-enhanced MR imaging have proved useful for differentiating brain tumor grades in adults. In this study, we retrospectively reviewed dynamic contrast-enhanced perfusion data from children with newly diagnosed brain tumors and analyzed the pharmacokinetic parameters correlating with tumor grade. Dynamic contrast-enhanced MR imaging data from 38 patients were analyzed by using commercially available software. Subjects were categorized into 2 groups based on pathologic analyses consisting of low-grade (World Health Organization I and II) and high-grade (World Health Organization III and IV) tumors. Pharmacokinetic parameters were compared between the 2 groups by using linear regression models. For parameters that were statistically distinct between the 2 groups, sensitivity and specificity were also estimated. Eighteen tumors were classified as low-grade, and 20, as high-grade. Transfer constant from the blood plasma into the extracellular extravascular space (K trans ), rate constant from extracellular extravascular space back into blood plasma (K ep ), and extracellular extravascular volume fraction (V e ) were all significantly correlated with tumor grade; high-grade tumors showed higher K trans , higher K ep , and lower V e . Although all 3 parameters had high specificity (range, 82%-100%), K ep had the highest specificity for both grades. Optimal sensitivity was achieved for V e , with a combined sensitivity of 76% (compared with 71% for K trans and K ep ). Pharmacokinetic parameters derived from dynamic contrast-enhanced MR imaging can effectively discriminate low- and high-grade pediatric brain tumors. © 2017 by American Journal of Neuroradiology.

Preliminary experiments on pharmacokinetic diffuse fluorescence tomography of CT-scanning mode

NASA Astrophysics Data System (ADS)

Zhang, Yanqi; Wang, Xin; Yin, Guoyan; Li, Jiao; Zhou, Zhongxing; Zhao, Huijuan; Gao, Feng; Zhang, Limin

2016-10-01

In vivo tomographic imaging of the fluorescence pharmacokinetic parameters in tissues can provide additional specific and quantitative physiological and pathological information to that of fluorescence concentration. This modality normally requires a highly-sensitive diffuse fluorescence tomography (DFT) working in dynamic way to finally extract the pharmacokinetic parameters from the measured pharmacokinetics-associated temporally-varying boundary intensity. This paper is devoted to preliminary experimental validation of our proposed direct reconstruction scheme of instantaneous sampling based pharmacokinetic-DFT: A highly-sensitive DFT system of CT-scanning mode working with parallel four photomultiplier-tube photon-counting channels is developed to generate an instantaneous sampling dataset; A direct reconstruction scheme then extracts images of the pharmacokinetic parameters using the adaptive-EKF strategy. We design a dynamic phantom that can simulate the agent metabolism in living tissue. The results of the dynamic phantom experiments verify the validity of the experiment system and reconstruction algorithms, and demonstrate that system provides good resolution, high sensitivity and quantitativeness at different pump speed.

Association of parameter, software, and hardware variation with large-scale behavior across 57,000 climate models

PubMed Central

Knight, Christopher G.; Knight, Sylvia H. E.; Massey, Neil; Aina, Tolu; Christensen, Carl; Frame, Dave J.; Kettleborough, Jamie A.; Martin, Andrew; Pascoe, Stephen; Sanderson, Ben; Stainforth, David A.; Allen, Myles R.

2007-01-01

In complex spatial models, as used to predict the climate response to greenhouse gas emissions, parameter variation within plausible bounds has major effects on model behavior of interest. Here, we present an unprecedentedly large ensemble of >57,000 climate model runs in which 10 parameters, initial conditions, hardware, and software used to run the model all have been varied. We relate information about the model runs to large-scale model behavior (equilibrium sensitivity of global mean temperature to a doubling of carbon dioxide). We demonstrate that effects of parameter, hardware, and software variation are detectable, complex, and interacting. However, we find most of the effects of parameter variation are caused by a small subset of parameters. Notably, the entrainment coefficient in clouds is associated with 30% of the variation seen in climate sensitivity, although both low and high values can give high climate sensitivity. We demonstrate that the effect of hardware and software is small relative to the effect of parameter variation and, over the wide range of systems tested, may be treated as equivalent to that caused by changes in initial conditions. We discuss the significance of these results in relation to the design and interpretation of climate modeling experiments and large-scale modeling more generally. PMID:17640921

A two-step sensitivity analysis for hydrological signatures in Jinhua River Basin, East China

NASA Astrophysics Data System (ADS)

Pan, S.; Fu, G.; Chiang, Y. M.; Xu, Y. P.

2016-12-01

Owing to model complexity and large number of parameters, calibration and sensitivity analysis are difficult processes for distributed hydrological models. In this study, a two-step sensitivity analysis approach is proposed for analyzing the hydrological signatures in Jinhua River Basin, East China, using the Distributed Hydrology-Soil-Vegetation Model (DHSVM). A rough sensitivity analysis is firstly conducted to obtain preliminary influential parameters via Analysis of Variance. The number of parameters was greatly reduced from eighteen-three to sixteen. Afterwards, the sixteen parameters are further analyzed based on a variance-based global sensitivity analysis, i.e., Sobol's sensitivity analysis method, to achieve robust sensitivity rankings and parameter contributions. Parallel-Computing is applied to reduce computational burden in variance-based sensitivity analysis. The results reveal that only a few number of model parameters are significantly sensitive, including rain LAI multiplier, lateral conductivity, porosity, field capacity, wilting point of clay loam, understory monthly LAI, understory minimum resistance and root zone depths of croplands. Finally several hydrological signatures are used for investigating the performance of DHSVM. Results show that high value of efficiency criteria didn't indicate excellent performance of hydrological signatures. For most samples from Sobol's sensitivity analysis, water yield was simulated very well. However, lowest and maximum annual daily runoffs were underestimated. Most of seven-day minimum runoffs were overestimated. Nevertheless, good performances of the three signatures above still exist in a number of samples. Analysis of peak flow shows that small and medium floods are simulated perfectly while slight underestimations happen to large floods. The work in this study helps to further multi-objective calibration of DHSVM model and indicates where to improve the reliability and credibility of model simulation.

Efficient Screening of Climate Model Sensitivity to a Large Number of Perturbed Input Parameters [plus supporting information

DOE PAGES

Covey, Curt; Lucas, Donald D.; Tannahill, John; ...

2013-07-01

Modern climate models contain numerous input parameters, each with a range of possible values. Since the volume of parameter space increases exponentially with the number of parameters N, it is generally impossible to directly evaluate a model throughout this space even if just 2-3 values are chosen for each parameter. Sensitivity screening algorithms, however, can identify input parameters having relatively little effect on a variety of output fields, either individually or in nonlinear combination.This can aid both model development and the uncertainty quantification (UQ) process. Here we report results from a parameter sensitivity screening algorithm hitherto untested in climate modeling,more » the Morris one-at-a-time (MOAT) method. This algorithm drastically reduces the computational cost of estimating sensitivities in a high dimensional parameter space because the sample size grows linearly rather than exponentially with N. It nevertheless samples over much of the N-dimensional volume and allows assessment of parameter interactions, unlike traditional elementary one-at-a-time (EOAT) parameter variation. We applied both EOAT and MOAT to the Community Atmosphere Model (CAM), assessing CAM’s behavior as a function of 27 uncertain input parameters related to the boundary layer, clouds, and other subgrid scale processes. For radiation balance at the top of the atmosphere, EOAT and MOAT rank most input parameters similarly, but MOAT identifies a sensitivity that EOAT underplays for two convection parameters that operate nonlinearly in the model. MOAT’s ranking of input parameters is robust to modest algorithmic variations, and it is qualitatively consistent with model development experience. Supporting information is also provided at the end of the full text of the article.« less

Sensitivity and specificity of eustachian tube function tests in adults.

PubMed

Doyle, William J; Swarts, J Douglas; Banks, Julianne; Casselbrant, Margaretha L; Mandel, Ellen M; Alper, Cuneyt M

2013-07-01

The study demonstrates the utility of eustachian tube (ET) function (ETF) test results for accurately assigning ears to disease state. To determine if ETF tests can identify ears with physician-diagnosed ET dysfunction (ETD) in a mixed population at high sensitivity and specificity and to define the interrelatedness of ETF test parameters. Through use of the forced-response, inflation-deflation, Valsalva, and sniffing tests, ETF was evaluated in 15 control ears of adult subjects after unilateral myringotomy (group 1) and in 23 ears of 19 adult subjects with ventilation tubes inserted for ETD (group 2). Data were analyzed using logistic regression including each parameter independently and then a step-down discriminant analysis including all ETF test parameters to predict group assignment. Factor analysis operating over all parameters was used to explore relatedness. ETF testing. ETF parameters for the forced response, inflation-deflation, Valsalva, and sniffing tests measured in 15 control ears of adult subjects after unilateral myringotomy (group 1) and in 23 ears of 19 adult subjects with ventilation tubes inserted for ETD (group 2). The discriminant analysis identified 4 ETF test parameters (Valsalva, ET opening pressure, dilatory efficiency, and percentage of positive pressure equilibrated) that together correctly assigned ears to group 2 at a sensitivity of 95% and a specificity of 83%. Individual parameters representing the efficiency of ET opening during swallowing showed moderately accurate assignments of ears to their respective groups. Three factors captured approximately 98% of the variance among parameters: the first had negative loadings of the ETF structural parameters; the second had positive loadings of the muscle-assisted ET opening parameters; and the third had negative loadings of the muscle-assisted ET opening parameters and positive loadings of the structural parameters. These results show that ETF tests can correctly assign individual ears to physician-diagnosed ETD with high sensitivity and specificity and that ETF test parameters can be grouped into structural-functional categories.

Sensitivity Analysis of an ENteric Immunity SImulator (ENISI)-Based Model of Immune Responses to Helicobacter pylori Infection

PubMed Central

Alam, Maksudul; Deng, Xinwei; Philipson, Casandra; Bassaganya-Riera, Josep; Bisset, Keith; Carbo, Adria; Eubank, Stephen; Hontecillas, Raquel; Hoops, Stefan; Mei, Yongguo; Abedi, Vida; Marathe, Madhav

2015-01-01

Agent-based models (ABM) are widely used to study immune systems, providing a procedural and interactive view of the underlying system. The interaction of components and the behavior of individual objects is described procedurally as a function of the internal states and the local interactions, which are often stochastic in nature. Such models typically have complex structures and consist of a large number of modeling parameters. Determining the key modeling parameters which govern the outcomes of the system is very challenging. Sensitivity analysis plays a vital role in quantifying the impact of modeling parameters in massively interacting systems, including large complex ABM. The high computational cost of executing simulations impedes running experiments with exhaustive parameter settings. Existing techniques of analyzing such a complex system typically focus on local sensitivity analysis, i.e. one parameter at a time, or a close “neighborhood” of particular parameter settings. However, such methods are not adequate to measure the uncertainty and sensitivity of parameters accurately because they overlook the global impacts of parameters on the system. In this article, we develop novel experimental design and analysis techniques to perform both global and local sensitivity analysis of large-scale ABMs. The proposed method can efficiently identify the most significant parameters and quantify their contributions to outcomes of the system. We demonstrate the proposed methodology for ENteric Immune SImulator (ENISI), a large-scale ABM environment, using a computational model of immune responses to Helicobacter pylori colonization of the gastric mucosa. PMID:26327290

Sensitivity Analysis of an ENteric Immunity SImulator (ENISI)-Based Model of Immune Responses to Helicobacter pylori Infection.

PubMed

Alam, Maksudul; Deng, Xinwei; Philipson, Casandra; Bassaganya-Riera, Josep; Bisset, Keith; Carbo, Adria; Eubank, Stephen; Hontecillas, Raquel; Hoops, Stefan; Mei, Yongguo; Abedi, Vida; Marathe, Madhav

2015-01-01

Agent-based models (ABM) are widely used to study immune systems, providing a procedural and interactive view of the underlying system. The interaction of components and the behavior of individual objects is described procedurally as a function of the internal states and the local interactions, which are often stochastic in nature. Such models typically have complex structures and consist of a large number of modeling parameters. Determining the key modeling parameters which govern the outcomes of the system is very challenging. Sensitivity analysis plays a vital role in quantifying the impact of modeling parameters in massively interacting systems, including large complex ABM. The high computational cost of executing simulations impedes running experiments with exhaustive parameter settings. Existing techniques of analyzing such a complex system typically focus on local sensitivity analysis, i.e. one parameter at a time, or a close "neighborhood" of particular parameter settings. However, such methods are not adequate to measure the uncertainty and sensitivity of parameters accurately because they overlook the global impacts of parameters on the system. In this article, we develop novel experimental design and analysis techniques to perform both global and local sensitivity analysis of large-scale ABMs. The proposed method can efficiently identify the most significant parameters and quantify their contributions to outcomes of the system. We demonstrate the proposed methodology for ENteric Immune SImulator (ENISI), a large-scale ABM environment, using a computational model of immune responses to Helicobacter pylori colonization of the gastric mucosa.

Parametrization study of the land multiparameter VTI elastic waveform inversion

NASA Astrophysics Data System (ADS)

He, W.; Plessix, R.-É.; Singh, S.

2018-06-01

Multiparameter inversion of seismic data remains challenging due to the trade-off between the different elastic parameters and the non-uniqueness of the solution. The sensitivity of the seismic data to a given subsurface elastic parameter depends on the source and receiver ray/wave path orientations at the subsurface point. In a high-frequency approximation, this is commonly analysed through the study of the radiation patterns that indicate the sensitivity of each parameter versus the incoming (from the source) and outgoing (to the receiver) angles. In practice, this means that the inversion result becomes sensitive to the choice of parametrization, notably because the null-space of the inversion depends on this choice. We can use a least-overlapping parametrization that minimizes the overlaps between the radiation patterns, in this case each parameter is only sensitive in a restricted angle domain, or an overlapping parametrization that contains a parameter sensitive to all angles, in this case overlaps between the radiation parameters occur. Considering a multiparameter inversion in an elastic vertically transverse isotropic medium and a complex land geological setting, we show that the inversion with the least-overlapping parametrization gives less satisfactory results than with the overlapping parametrization. The difficulties come from the complex wave paths that make difficult to predict the areas of sensitivity of each parameter. This shows that the parametrization choice should not only be based on the radiation pattern analysis but also on the angular coverage at each subsurface point that depends on geology and the acquisition layout.

Primary production sensitivity to phytoplankton light attenuation parameter increases with transient forcing

NASA Astrophysics Data System (ADS)

Kvale, Karin F.; Meissner, Katrin J.

2017-10-01

Treatment of the underwater light field in ocean biogeochemical models has been attracting increasing interest, with some models moving towards more complex parameterisations. We conduct a simple sensitivity study of a typical, highly simplified parameterisation. In our study, we vary the phytoplankton light attenuation parameter over a range constrained by data during both pre-industrial equilibrated and future climate scenario RCP8.5. In equilibrium, lower light attenuation parameters (weaker self-shading) shift net primary production (NPP) towards the high latitudes, while higher values of light attenuation (stronger shelf-shading) shift NPP towards the low latitudes. Climate forcing magnifies this relationship through changes in the distribution of nutrients both within and between ocean regions. Where and how NPP responds to climate forcing can determine the magnitude and sign of global NPP trends in this high CO2 future scenario. Ocean oxygen is particularly sensitive to parameter choice. Under higher CO2 concentrations, two simulations establish a strong biogeochemical feedback between the Southern Ocean and low-latitude Pacific that highlights the potential for regional teleconnection. Our simulations serve as a reminder that shifts in fundamental properties (e.g. light attenuation by phytoplankton) over deep time have the potential to alter global biogeochemistry.

Factors affecting the sensitivity and specificity of the Heidelberg Retina Tomograph parameters to glaucomatous progression in disc photographs.

PubMed

Saarela, Ville; Falck, Aura; Airaksinen, P Juhani; Tuulonen, Anja

2012-03-01

To evaluate the factors affecting the sensitivity and specificity of the stereometric optic nerve head (ONH) parameters of the Heidelberg Retina Tomograph (HRT) to glaucomatous progression in stereoscopic ONH photographs. The factors affecting the sensitivity and specificity of the vertical cup : disc ratio, the cup : disc area ratio, the cup volume, the rim area and a linear discriminant function to progression were analysed. These parameters were the best indicators of progression in a retrospective study of 476 eyes. The reference standard for progression was the masked evaluation of stereoscopic ONH photographs. The factors having the most significant effect on the sensitivity and specificity of the stereometric ONH parameters were the reference height difference and the mean topography standard deviation (TSD), indicating image quality. Also, the change in the TSD and age showed consistent, but variably significant, influence on all parameters tested. The sensitivity and specificity improved when there was little change in the reference height, the image quality was good and stable, and the patients were younger. The sensitivity and specificity of the vertical cup : disc ratio was improved by a large disc area and high baseline cup : disc area ratio. The rim area showed a better sensitivity and specificity for progression with a small disc area and low baseline cup : disc area ratio. The factors affecting the sensitivity and specificity of the stereometric ONH parameters to glaucomatous progression in disc photographs are essentially the same as those affecting the measurement variability of the HRT. © 2010 The Authors. Acta Ophthalmologica © 2010 Acta Ophthalmologica Scandinavica Foundation.

Testing life history predictions in a long-lived seabird: A population matrix approach with improved parameter estimation

USGS Publications Warehouse

Doherty, P.F.; Schreiber, E.A.; Nichols, J.D.; Hines, J.E.; Link, W.A.; Schenk, G.A.; Schreiber, R.W.

2004-01-01

Life history theory and associated empirical generalizations predict that population growth rate (λ) in long-lived animals should be most sensitive to adult survival; the rates to which λ is most sensitive should be those with the smallest temporal variances; and stochastic environmental events should most affect the rates to which λ is least sensitive. To date, most analyses attempting to examine these predictions have been inadequate, their validity being called into question by problems in estimating parameters, problems in estimating the variability of parameters, and problems in measuring population sensitivities to parameters. We use improved methodologies in these three areas and test these life-history predictions in a population of red-tailed tropicbirds (Phaethon rubricauda). We support our first prediction that λ is most sensitive to survival rates. However the support for the second prediction that these rates have the smallest temporal variance was equivocal. Previous support for the second prediction may be an artifact of a high survival estimate near the upper boundary of 1 and not a result of natural selection canalizing variances alone. We did not support our third prediction that effects of environmental stochasticity (El Niño) would most likely be detected in vital rates to which λ was least sensitive and which are thought to have high temporal variances. Comparative data-sets on other seabirds, within and among orders, and in other locations, are needed to understand these environmental effects.

On-fiber plasmonic interferometer for multi-parameter sensing

DOE PAGES

Zhang, Zhijian; Chen, Yongyao; Liu, Haijun; ...

2015-01-01

We demonstrate a novel miniature multi-parameter sensing device based on a plasmonic interferometer fabricated on a fiber facet in the optical communication wavelength range. This device enables the coupling between surface plasmon resonance and plasmonic interference in the structure, which are the two essential mechanisms for multi-parameter sensing. We experimentally show that these two mechanisms have distinctive responses to temperature and refractive index, rendering the device the capability of simultaneous temperature and refractive index measurement on an ultra-miniature form factor. A high refractive index sensitivity of 220 nm per refractive index unit (RIU) and a high temperature sensitivity of –60more » pm/ °C is achieved with our device.« less

Ground water flow modeling with sensitivity analyses to guide field data collection in a mountain watershed

USGS Publications Warehouse

Johnson, Raymond H.

2007-01-01

In mountain watersheds, the increased demand for clean water resources has led to an increased need for an understanding of ground water flow in alpine settings. In Prospect Gulch, located in southwestern Colorado, understanding the ground water flow system is an important first step in addressing metal loads from acid-mine drainage and acid-rock drainage in an area with historical mining. Ground water flow modeling with sensitivity analyses are presented as a general tool to guide future field data collection, which is applicable to any ground water study, including mountain watersheds. For a series of conceptual models, the observation and sensitivity capabilities of MODFLOW-2000 are used to determine composite scaled sensitivities, dimensionless scaled sensitivities, and 1% scaled sensitivity maps of hydraulic head. These sensitivities determine the most important input parameter(s) along with the location of observation data that are most useful for future model calibration. The results are generally independent of the conceptual model and indicate recharge in a high-elevation recharge zone as the most important parameter, followed by the hydraulic conductivities in all layers and recharge in the next lower-elevation zone. The most important observation data in determining these parameters are hydraulic heads at high elevations, with a depth of less than 100 m being adequate. Evaluation of a possible geologic structure with a different hydraulic conductivity than the surrounding bedrock indicates that ground water discharge to individual stream reaches has the potential to identify some of these structures. Results of these sensitivity analyses can be used to prioritize data collection in an effort to reduce time and money spend by collecting the most relevant model calibration data.

Metabolism of plasma cholesterol and lipoprotein parameters are related to a higher degree of insulin sensitivity in high HDL-C healthy normal weight subjects.

PubMed

Leança, Camila C; Nunes, Valéria S; Panzoldo, Natália B; Zago, Vanessa S; Parra, Eliane S; Cazita, Patrícia M; Jauhiainen, Matti; Passarelli, Marisa; Nakandakare, Edna R; de Faria, Eliana C; Quintão, Eder C R

2013-11-22

We have searched if plasma high density lipoprotein-cholesterol (HDL-C) concentration interferes simultaneously with whole-body cholesterol metabolism and insulin sensitivity in normal weight healthy adult subjects. We have measured the activities of several plasma components that are critically influenced by insulin and that control lipoprotein metabolism in subjects with low and high HDL-C concentrations. These parameters included cholesteryl ester transfer protein (CETP), phospholipid transfer protein (PLTP), lecithin cholesterol acyl transferase (LCAT), post-heparin lipoprotein lipase (LPL), hepatic lipase (HL), pre-beta-₁HDL, and plasma sterol markers of cholesterol synthesis and intestinal absorption. In the high-HDL-C group, we found lower plasma concentrations of triglycerides, alanine aminotransferase, insulin, HOMA-IR index, activities of LCAT and HL compared with the low HDL-C group; additionally, we found higher activity of LPL and pre-beta-₁HDL concentration in the high-HDL-C group. There were no differences in the plasma CETP and PLTP activities. These findings indicate that in healthy hyperalphalipoproteinemia subjects, several parameters that control the metabolism of plasma cholesterol and lipoproteins are related to a higher degree of insulin sensitivity.

Articular cartilage degeneration classification by means of high-frequency ultrasound.

PubMed

Männicke, N; Schöne, M; Oelze, M; Raum, K

2014-10-01

To date only single ultrasound parameters were regarded in statistical analyses to characterize osteoarthritic changes in articular cartilage and the potential benefit of using parameter combinations for characterization remains unclear. Therefore, the aim of this work was to utilize feature selection and classification of a Mankin subset score (i.e., cartilage surface and cell sub-scores) using ultrasound-based parameter pairs and investigate both classification accuracy and the sensitivity towards different degeneration stages. 40 punch biopsies of human cartilage were previously scanned ex vivo with a 40-MHz transducer. Ultrasound-based surface parameters, as well as backscatter and envelope statistics parameters were available. Logistic regression was performed with each unique US parameter pair as predictor and different degeneration stages as response variables. The best ultrasound-based parameter pair for each Mankin subset score value was assessed by highest classification accuracy and utilized in receiver operating characteristics (ROC) analysis. The classifications discriminating between early degenerations yielded area under the ROC curve (AUC) values of 0.94-0.99 (mean ± SD: 0.97 ± 0.03). In contrast, classifications among higher Mankin subset scores resulted in lower AUC values: 0.75-0.91 (mean ± SD: 0.84 ± 0.08). Variable sensitivities of the different ultrasound features were observed with respect to different degeneration stages. Our results strongly suggest that combinations of high-frequency ultrasound-based parameters exhibit potential to characterize different, particularly very early, degeneration stages of hyaline cartilage. Variable sensitivities towards different degeneration stages suggest that a concurrent estimation of multiple ultrasound-based parameters is diagnostically valuable. In-vivo application of the present findings is conceivable in both minimally invasive arthroscopic ultrasound and high-frequency transcutaneous ultrasound. Copyright © 2014 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Relative sensitivity of developmental and immune parameters in juvenile versus adult male rats after exposure to di(2-ethylhexyl) phthalate

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

Tonk, Elisa C.M., E-mail: ilse.tonk@rivm.nl; Laboratory for Health Protection Research, National Institute for Public Health and the Environment; Verhoef, Aart

The developing immune system displays a relatively high sensitivity as compared to both general toxicity parameters and to the adult immune system. In this study we have performed such comparisons using di(2-ethylhexyl) phthalate (DEHP) as a model compound. DEHP is the most abundant phthalate in the environment and perinatal exposure to DEHP has been shown to disrupt male sexual differentiation. In addition, phthalate exposure has been associated with immune dysfunction as evidenced by effects on the expression of allergy. Male wistar rats were dosed with corn oil or DEHP by gavage from postnatal day (PND) 10–50 or PND 50–90 atmore » doses between 1 and 1000 mg/kg/day. Androgen-dependent organ weights showed effects at lower dose levels in juvenile versus adult animals. Immune parameters affected included TDAR parameters in both age groups, NK activity in juvenile animals and TNF-α production by adherent splenocytes in adult animals. Immune parameters were affected at lower dose levels compared to developmental parameters. Overall, more immune parameters were affected in juvenile animals compared to adult animals and effects were observed at lower dose levels. The results of this study show a relatively higher sensitivity of juvenile versus adult rats. Furthermore, they illustrate the relative sensitivity of the developing immune system in juvenile animals as compared to general toxicity and developmental parameters. This study therefore provides further argumentation for performing dedicated developmental immune toxicity testing as a default in regulatory toxicology. -- Highlights: ► In this study we evaluate the relative sensitivities for DEHP induced effects. ► Results of this study demonstrate the age-dependency of DEHP toxicity. ► Functional immune parameters were more sensitive than structural immune parameters. ► Immune parameters were affected at lower dose levels than developmental parameters. ► Findings demonstrate the susceptibility of the developing immune system for DEHP.« less

Histogram analysis of diffusion kurtosis imaging of nasopharyngeal carcinoma: Correlation between quantitative parameters and clinical stage.

PubMed

Xu, Xiao-Quan; Ma, Gao; Wang, Yan-Jun; Hu, Hao; Su, Guo-Yi; Shi, Hai-Bin; Wu, Fei-Yun

2017-07-18

To evaluate the correlation between histogram parameters derived from diffusion-kurtosis (DK) imaging and the clinical stage of nasopharyngeal carcinoma (NPC). High T-stage (T3/4) NPC showed significantly higher Kapp-mean (P = 0.018), Kapp-median (P = 0.029) and Kapp-90th (P = 0.003) than low T-stage (T1/2) NPC. High N-stage NPC (N2/3) showed significantly lower Dapp-mean (P = 0.002), Dapp-median (P = 0.002) and Dapp-10th (P < 0.001) than low N-stage NPC (N0/1). High AJCC-stage NPC (III/IV) showed significantly lower Dapp-10th (P = 0.038) than low AJCC-stage NPC (I/II). ROC analyses indicated that Kapp-90th was optimal for predicting high T-stage (AUC, 0.759; sensitivity, 0.842; specificity, 0.607), while Dapp-10th was best for predicting high N- and AJCC-stage (N-stage, AUC, 0.841; sensitivity, 0.875; specificity, 0.807; AJCC-stage, AUC, 0.671; sensitivity, 0.800; specificity, 0.588). DK imaging data of forty-seven consecutive NPC patients were retrospectively analyzed. Apparent diffusion for Gaussian distribution (Dapp) and apparent kurtosis coefficient (Kapp) were generated using diffusion-kurtosis model. Histogram parameters, including mean, median, 10th, 90th percentiles, skewness and kurtosis of Dapp and Kapp were calculated. Patients were divided into low and high T, N and clinical stage based on American Joint Committee on Cancer (AJCC) staging system. Differences of histogram parameters between low and high T, N and AJCC stages were compared using t test. Multiple receiver operating characteristic (ROC) curves were used to determine and compare the value of significant parameters in predicting high T, N and AJCC stage, respectively. DK imaging-derived parameters correlated well with clinical stage of NPC, therefore could serve as an adjunctive imaging technique for evaluating NPC.

Effect of parameters in moving average method for event detection enhancement using phase sensitive OTDR

NASA Astrophysics Data System (ADS)

Kwon, Yong-Seok; Naeem, Khurram; Jeon, Min Yong; Kwon, Il-bum

2017-04-01

We analyze the relations of parameters in moving average method to enhance the event detectability of phase sensitive optical time domain reflectometer (OTDR). If the external events have unique frequency of vibration, then the control parameters of moving average method should be optimized in order to detect these events efficiently. A phase sensitive OTDR was implemented by a pulsed light source, which is composed of a laser diode, a semiconductor optical amplifier, an erbium-doped fiber amplifier, a fiber Bragg grating filter, and a light receiving part, which has a photo-detector and high speed data acquisition system. The moving average method is operated with the control parameters: total number of raw traces, M, number of averaged traces, N, and step size of moving, n. The raw traces are obtained by the phase sensitive OTDR with sound signals generated by a speaker. Using these trace data, the relation of the control parameters is analyzed. In the result, if the event signal has one frequency, then the optimal values of N, n are existed to detect the event efficiently.

High correlation of double Debye model parameters in skin cancer detection.

PubMed

Truong, Bao C Q; Tuan, H D; Fitzgerald, Anthony J; Wallace, Vincent P; Nguyen, H T

2014-01-01

The double Debye model can be used to capture the dielectric response of human skin in terahertz regime due to high water content in the tissue. The increased water proportion is widely considered as a biomarker of carcinogenesis, which gives rise of using this model in skin cancer detection. Therefore, the goal of this paper is to provide a specific analysis of the double Debye parameters in terms of non-melanoma skin cancer classification. Pearson correlation is applied to investigate the sensitivity of these parameters and their combinations to the variation in tumor percentage of skin samples. The most sensitive parameters are then assessed by using the receiver operating characteristic (ROC) plot to confirm their potential of classifying tumor from normal skin. Our positive outcomes support further steps to clinical application of terahertz imaging in skin cancer delineation.

Early detection of response to radiation therapy in patients with brain malignancies using conventional and high b-value diffusion-weighted magnetic resonance imaging.

PubMed

Mardor, Yael; Pfeffer, Raphael; Spiegelmann, Roberto; Roth, Yiftach; Maier, Stephan E; Nissim, Ouzi; Berger, Raanan; Glicksman, Ami; Baram, Jacob; Orenstein, Arie; Cohen, Jack S; Tichler, Thomas

2003-03-15

To study the feasibility of using diffusion-weighted magnetic resonance imaging (DWMRI), which is sensitive to the diffusion of water molecules in tissues, for detection of early tumor response to radiation therapy; and to evaluate the additional information obtained from high DWMRI, which is more sensitive to low-mobility water molecules (such as intracellular or bound water), in increasing the sensitivity to response. Standard MRI and DWMRI were acquired before and at regular intervals after initiating radiation therapy for 10 malignant brain lesions in eight patients. One week posttherapy, three of six responding lesions showed an increase in the conventional DWMRI parameters. Another three responding lesions showed no change. Four nonresponding lesions showed a decrease or no change. The early change in the diffusion parameters was enhanced by using high DWMRI. When high DWMRI was used, all responding lesions showed increase in the diffusion parameter and all nonresponding lesions showed no change or decrease. Response was determined by standard MRI 7 weeks posttherapy. The changes in the diffusion parameters measured 1 week after initiating treatment were correlated with later tumor response or no response (P <.006). This correlation was increased to P <.0006 when high DWMRI was used. The significant correlation between changes in diffusion parameters 1 week after initiating treatment and later tumor response or no response suggests the feasibility of using DWMRI for early, noninvasive prediction of tumor response. The ability to predict response may enable early termination of treatment in nonresponding patients, prevent additional toxicity, and allow for early changes in treatment.

Addressing Curse of Dimensionality in Sensitivity Analysis: How Can We Handle High-Dimensional Problems?

NASA Astrophysics Data System (ADS)

Safaei, S.; Haghnegahdar, A.; Razavi, S.

2016-12-01

Complex environmental models are now the primary tool to inform decision makers for the current or future management of environmental resources under the climate and environmental changes. These complex models often contain a large number of parameters that need to be determined by a computationally intensive calibration procedure. Sensitivity analysis (SA) is a very useful tool that not only allows for understanding the model behavior, but also helps in reducing the number of calibration parameters by identifying unimportant ones. The issue is that most global sensitivity techniques are highly computationally demanding themselves for generating robust and stable sensitivity metrics over the entire model response surface. Recently, a novel global sensitivity analysis method, Variogram Analysis of Response Surfaces (VARS), is introduced that can efficiently provide a comprehensive assessment of global sensitivity using the Variogram concept. In this work, we aim to evaluate the effectiveness of this highly efficient GSA method in saving computational burden, when applied to systems with extra-large number of input factors ( 100). We use a test function and a hydrological modelling case study to demonstrate the capability of VARS method in reducing problem dimensionality by identifying important vs unimportant input factors.

Uncertainty quantification and global sensitivity analysis of the Los Alamos sea ice model

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

Urrego-Blanco, Jorge Rolando; Urban, Nathan Mark; Hunke, Elizabeth Clare

Changes in the high-latitude climate system have the potential to affect global climate through feedbacks with the atmosphere and connections with midlatitudes. Sea ice and climate models used to understand these changes have uncertainties that need to be characterized and quantified. We present a quantitative way to assess uncertainty in complex computer models, which is a new approach in the analysis of sea ice models. We characterize parametric uncertainty in the Los Alamos sea ice model (CICE) in a standalone configuration and quantify the sensitivity of sea ice area, extent, and volume with respect to uncertainty in 39 individual modelmore » parameters. Unlike common sensitivity analyses conducted in previous studies where parameters are varied one at a time, this study uses a global variance-based approach in which Sobol' sequences are used to efficiently sample the full 39-dimensional parameter space. We implement a fast emulator of the sea ice model whose predictions of sea ice extent, area, and volume are used to compute the Sobol' sensitivity indices of the 39 parameters. Main effects and interactions among the most influential parameters are also estimated by a nonparametric regression technique based on generalized additive models. A ranking based on the sensitivity indices indicates that model predictions are most sensitive to snow parameters such as snow conductivity and grain size, and the drainage of melt ponds. Lastly, it is recommended that research be prioritized toward more accurately determining these most influential parameter values by observational studies or by improving parameterizations in the sea ice model.« less

Uncertainty quantification and global sensitivity analysis of the Los Alamos sea ice model

DOE PAGES

Urrego-Blanco, Jorge Rolando; Urban, Nathan Mark; Hunke, Elizabeth Clare; ...

2016-04-01

Changes in the high-latitude climate system have the potential to affect global climate through feedbacks with the atmosphere and connections with midlatitudes. Sea ice and climate models used to understand these changes have uncertainties that need to be characterized and quantified. We present a quantitative way to assess uncertainty in complex computer models, which is a new approach in the analysis of sea ice models. We characterize parametric uncertainty in the Los Alamos sea ice model (CICE) in a standalone configuration and quantify the sensitivity of sea ice area, extent, and volume with respect to uncertainty in 39 individual modelmore » parameters. Unlike common sensitivity analyses conducted in previous studies where parameters are varied one at a time, this study uses a global variance-based approach in which Sobol' sequences are used to efficiently sample the full 39-dimensional parameter space. We implement a fast emulator of the sea ice model whose predictions of sea ice extent, area, and volume are used to compute the Sobol' sensitivity indices of the 39 parameters. Main effects and interactions among the most influential parameters are also estimated by a nonparametric regression technique based on generalized additive models. A ranking based on the sensitivity indices indicates that model predictions are most sensitive to snow parameters such as snow conductivity and grain size, and the drainage of melt ponds. Lastly, it is recommended that research be prioritized toward more accurately determining these most influential parameter values by observational studies or by improving parameterizations in the sea ice model.« less

Uncertainty quantification and global sensitivity analysis of the Los Alamos sea ice model

NASA Astrophysics Data System (ADS)

Urrego-Blanco, Jorge R.; Urban, Nathan M.; Hunke, Elizabeth C.; Turner, Adrian K.; Jeffery, Nicole

2016-04-01

Changes in the high-latitude climate system have the potential to affect global climate through feedbacks with the atmosphere and connections with midlatitudes. Sea ice and climate models used to understand these changes have uncertainties that need to be characterized and quantified. We present a quantitative way to assess uncertainty in complex computer models, which is a new approach in the analysis of sea ice models. We characterize parametric uncertainty in the Los Alamos sea ice model (CICE) in a standalone configuration and quantify the sensitivity of sea ice area, extent, and volume with respect to uncertainty in 39 individual model parameters. Unlike common sensitivity analyses conducted in previous studies where parameters are varied one at a time, this study uses a global variance-based approach in which Sobol' sequences are used to efficiently sample the full 39-dimensional parameter space. We implement a fast emulator of the sea ice model whose predictions of sea ice extent, area, and volume are used to compute the Sobol' sensitivity indices of the 39 parameters. Main effects and interactions among the most influential parameters are also estimated by a nonparametric regression technique based on generalized additive models. A ranking based on the sensitivity indices indicates that model predictions are most sensitive to snow parameters such as snow conductivity and grain size, and the drainage of melt ponds. It is recommended that research be prioritized toward more accurately determining these most influential parameter values by observational studies or by improving parameterizations in the sea ice model.

Developing a methodology for the inverse estimation of root architectural parameters from field based sampling schemes

NASA Astrophysics Data System (ADS)

Morandage, Shehan; Schnepf, Andrea; Vanderborght, Jan; Javaux, Mathieu; Leitner, Daniel; Laloy, Eric; Vereecken, Harry

2017-04-01

Root traits are increasingly important in breading of new crop varieties. E.g., longer and fewer lateral roots are suggested to improve drought resistance of wheat. Thus, detailed root architectural parameters are important. However, classical field sampling of roots only provides more aggregated information such as root length density (coring), root counts per area (trenches) or root arrival curves at certain depths (rhizotubes). We investigate the possibility of obtaining the information about root system architecture of plants using field based classical root sampling schemes, based on sensitivity analysis and inverse parameter estimation. This methodology was developed based on a virtual experiment where a root architectural model was used to simulate root system development in a field, parameterized for winter wheat. This information provided the ground truth which is normally unknown in a real field experiment. The three sampling schemes coring, trenching, and rhizotubes where virtually applied to and aggregated information computed. Morris OAT global sensitivity analysis method was then performed to determine the most sensitive parameters of root architecture model for the three different sampling methods. The estimated means and the standard deviation of elementary effects of a total number of 37 parameters were evaluated. Upper and lower bounds of the parameters were obtained based on literature and published data of winter wheat root architectural parameters. Root length density profiles of coring, arrival curve characteristics observed in rhizotubes, and root counts in grids of trench profile method were evaluated statistically to investigate the influence of each parameter using five different error functions. Number of branches, insertion angle inter-nodal distance, and elongation rates are the most sensitive parameters and the parameter sensitivity varies slightly with the depth. Most parameters and their interaction with the other parameters show highly nonlinear effect to the model output. The most sensitive parameters will be subject to inverse estimation from the virtual field sampling data using DREAMzs algorithm. The estimated parameters can then be compared with the ground truth in order to determine the suitability of the sampling schemes to identify specific traits or parameters of the root growth model.

Results of an integrated structure-control law design sensitivity analysis

NASA Technical Reports Server (NTRS)

Gilbert, Michael G.

1988-01-01

Next generation air and space vehicle designs are driven by increased performance requirements, demanding a high level of design integration between traditionally separate design disciplines. Interdisciplinary analysis capabilities have been developed, for aeroservoelastic aircraft and large flexible spacecraft control for instance, but the requisite integrated design methods are only beginning to be developed. One integrated design method which has received attention is based on hierarchal problem decompositions, optimization, and design sensitivity analyses. This paper highlights a design sensitivity analysis method for Linear Quadratic Cost, Gaussian (LQG) optimal control laws, which predicts change in the optimal control law due to changes in fixed problem parameters using analytical sensitivity equations. Numerical results of a design sensitivity analysis for a realistic aeroservoelastic aircraft example are presented. In this example, the sensitivity of the optimally controlled aircraft's response to various problem formulation and physical aircraft parameters is determined. These results are used to predict the aircraft's new optimally controlled response if the parameter was to have some other nominal value during the control law design process. The sensitivity results are validated by recomputing the optimal control law for discrete variations in parameters, computing the new actual aircraft response, and comparing with the predicted response. These results show an improvement in sensitivity accuracy for integrated design purposes over methods which do not include changess in the optimal control law. Use of the analytical LQG sensitivity expressions is also shown to be more efficient that finite difference methods for the computation of the equivalent sensitivity information.

Discrete Adjoint Sensitivity Analysis of Hybrid Dynamical Systems With Switching [Discrete Adjoint Sensitivity Analysis of Hybrid Dynamical Systems

DOE PAGES

Zhang, Hong; Abhyankar, Shrirang; Constantinescu, Emil; ...

2017-01-24

Sensitivity analysis is an important tool for describing power system dynamic behavior in response to parameter variations. It is a central component in preventive and corrective control applications. The existing approaches for sensitivity calculations, namely, finite-difference and forward sensitivity analysis, require a computational effort that increases linearly with the number of sensitivity parameters. In this paper, we investigate, implement, and test a discrete adjoint sensitivity approach whose computational effort is effectively independent of the number of sensitivity parameters. The proposed approach is highly efficient for calculating sensitivities of larger systems and is consistent, within machine precision, with the function whosemore » sensitivity we are seeking. This is an essential feature for use in optimization applications. Moreover, our approach includes a consistent treatment of systems with switching, such as dc exciters, by deriving and implementing the adjoint jump conditions that arise from state-dependent and time-dependent switchings. The accuracy and the computational efficiency of the proposed approach are demonstrated in comparison with the forward sensitivity analysis approach. In conclusion, this paper focuses primarily on the power system dynamics, but the approach is general and can be applied to hybrid dynamical systems in a broader range of fields.« less

Discrete Adjoint Sensitivity Analysis of Hybrid Dynamical Systems With Switching [Discrete Adjoint Sensitivity Analysis of Hybrid Dynamical Systems

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

Zhang, Hong; Abhyankar, Shrirang; Constantinescu, Emil

Sensitivity analysis is an important tool for describing power system dynamic behavior in response to parameter variations. It is a central component in preventive and corrective control applications. The existing approaches for sensitivity calculations, namely, finite-difference and forward sensitivity analysis, require a computational effort that increases linearly with the number of sensitivity parameters. In this paper, we investigate, implement, and test a discrete adjoint sensitivity approach whose computational effort is effectively independent of the number of sensitivity parameters. The proposed approach is highly efficient for calculating sensitivities of larger systems and is consistent, within machine precision, with the function whosemore » sensitivity we are seeking. This is an essential feature for use in optimization applications. Moreover, our approach includes a consistent treatment of systems with switching, such as dc exciters, by deriving and implementing the adjoint jump conditions that arise from state-dependent and time-dependent switchings. The accuracy and the computational efficiency of the proposed approach are demonstrated in comparison with the forward sensitivity analysis approach. In conclusion, this paper focuses primarily on the power system dynamics, but the approach is general and can be applied to hybrid dynamical systems in a broader range of fields.« less

PREVALENCE OF METABOLIC SYNDROME IN YOUNG MEXICANS: A SENSITIVITY ANALYSIS ON ITS COMPONENTS.

PubMed

Murguía-Romero, Miguel; Jiménez-Flores, J Rafael; Sigrist-Flores, Santiago C; Tapia-Pancardo, Diana C; Jiménez-Ramos, Arnulfo; Méndez-Cruz, A René; Villalobos-Molina, Rafael

2015-07-28

obesity is a worldwide epidemic, and the high prevalence of diabetes type II (DM2) and cardiovascular disease (CVD) is in great part a consequence of that epidemic. Metabolic syndrome is a useful tool to estimate the risk of a young population to evolve to DM2 and CVD. to estimate the MetS prevalence in young Mexicans, and to evaluate each parameter as an independent indicator through a sensitivity analysis. the prevalence of MetS was estimated in 6 063 young of the México City metropolitan area. A sensitivity analysis was conducted to estimate the performance of each one of the components of MetS, as an indicator of the presence of MetS itself. Five statistical of the sensitivity analysis were calculated for each MetS component and the other parameters included: sensitivity, specificity, positive predictive value or precision, negative predictive value, and accuracy. the prevalence of MetS in Mexican young population was estimated to be 13.4%. Waist circumference presented the highest sensitivity (96.8% women; 90.0% men), blood pressure presented the highest specificity for women (97.7%) and glucose for men (91.0%). When all the five statistical are considered triglycerides is the component with the highest values, showing a value of 75% or more in four of them. Differences by sex are detected for averages of all components of MetS in young without alterations. Mexican young are highly prone to acquire MetS: 71% have at least one and up to five MetS parameters altered, and 13.4% of them have MetS. From all the five components of MetS, waist circumference presented the highest sensitivity as a predictor of MetS, and triglycerides is the best parameter if a single factor is to be taken as sole predictor of MetS in Mexican young population, triglycerides is also the parameter with the highest accuracy. Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.

Quantifying Parameter Sensitivity, Interaction and Transferability in Hydrologically Enhanced Versions of Noah-LSM over Transition Zones

NASA Technical Reports Server (NTRS)

Rosero, Enrique; Yang, Zong-Liang; Wagener, Thorsten; Gulden, Lindsey E.; Yatheendradas, Soni; Niu, Guo-Yue

2009-01-01

We use sensitivity analysis to identify the parameters that are most responsible for shaping land surface model (LSM) simulations and to understand the complex interactions in three versions of the Noah LSM: the standard version (STD), a version enhanced with a simple groundwater module (GW), and version augmented by a dynamic phenology module (DV). We use warm season, high-frequency, near-surface states and turbulent fluxes collected over nine sites in the US Southern Great Plains. We quantify changes in the pattern of sensitive parameters, the amount and nature of the interaction between parameters, and the covariance structure of the distribution of behavioral parameter sets. Using Sobol s total and first-order sensitivity indexes, we show that very few parameters directly control the variance of the model output. Significant parameter interaction occurs so that not only the optimal parameter values differ between models, but the relationships between parameters change. GW decreases parameter interaction and appears to improve model realism, especially at wetter sites. DV increases parameter interaction and decreases identifiability, implying it is overparameterized and/or underconstrained. A case study at a wet site shows GW has two functional modes: one that mimics STD and a second in which GW improves model function by decoupling direct evaporation and baseflow. Unsupervised classification of the posterior distributions of behavioral parameter sets cannot group similar sites based solely on soil or vegetation type, helping to explain why transferability between sites and models is not straightforward. This evidence suggests a priori assignment of parameters should also consider climatic differences.

Upper limb strength estimation of physically impaired persons using a musculoskeletal model: A sensitivity analysis.

PubMed

Carmichael, Marc G; Liu, Dikai

2015-01-01

Sensitivity of upper limb strength calculated from a musculoskeletal model was analyzed, with focus on how the sensitivity is affected when the model is adapted to represent a person with physical impairment. Sensitivity was calculated with respect to four muscle-tendon parameters: muscle peak isometric force, muscle optimal length, muscle pennation, and tendon slack length. Results obtained from a musculoskeletal model of average strength showed highest sensitivity to tendon slack length, followed by muscle optimal length and peak isometric force, which is consistent with existing studies. Muscle pennation angle was relatively insensitive. The analysis was repeated after adapting the musculoskeletal model to represent persons with varying severities of physical impairment. Results showed that utilizing the weakened model significantly increased the sensitivity of the calculated strength at the hand, with parameters previously insensitive becoming highly sensitive. This increased sensitivity presents a significant challenge in applications utilizing musculoskeletal models to represent impaired individuals.

The application of sensitivity analysis to models of large scale physiological systems

NASA Technical Reports Server (NTRS)

Leonard, J. I.

1974-01-01

A survey of the literature of sensitivity analysis as it applies to biological systems is reported as well as a brief development of sensitivity theory. A simple population model and a more complex thermoregulatory model illustrate the investigatory techniques and interpretation of parameter sensitivity analysis. The role of sensitivity analysis in validating and verifying models, and in identifying relative parameter influence in estimating errors in model behavior due to uncertainty in input data is presented. This analysis is valuable to the simulationist and the experimentalist in allocating resources for data collection. A method for reducing highly complex, nonlinear models to simple linear algebraic models that could be useful for making rapid, first order calculations of system behavior is presented.

CCFpams: Atmospheric stellar parameters from cross-correlation functions

NASA Astrophysics Data System (ADS)

Malavolta, Luca; Lovis, Christophe; Pepe, Francesco; Sneden, Christopher; Udry, Stephane

2017-07-01

CCFpams allows the measurement of stellar temperature, metallicity and gravity within a few seconds and in a completely automated fashion. Rather than performing comparisons with spectral libraries, the technique is based on the determination of several cross-correlation functions (CCFs) obtained by including spectral features with different sensitivity to the photospheric parameters. Literature stellar parameters of high signal-to-noise (SNR) and high-resolution HARPS spectra of FGK Main Sequence stars are used to calibrate the stellar parameters as a function of CCF areas.

Macular Diagnostic Ability in OCT for Assessing Glaucoma in High Myopia.

PubMed

Hung, Kuo-Chi; Wu, Pei-Chang; Poon, Yi-Chieh; Chang, Hsueh-Wen; Lai, Ing-Chou; Tsai, Jen-Chia; Lin, Pei-Wen; Teng, Mei-Ching

2016-02-01

To compare the diagnostic abilities of spectral-domain optical coherence tomography (SD-OCT; Spectralis OCT) and time-domain OCT (TD-OCT; Stratus OCT). Changes in macular parameters in highly myopic eyes of glaucoma patients and highly myopic eyes of glaucoma suspects were evaluated and compared. We collected data from 72 highly myopic eyes (spherical equivalent, ≤-6.0D). Forty-one eyes had perimetric glaucoma and 31 eyes were suspected to have glaucoma (control group). All eyes underwent SD-OCT and TD-OCT imaging. Area under the receiver operating characteristic (AUROC) curve and sensitivity were examined on macular volume and thickness parameters at a fixed specificity and compared between groups. The highest TD-OCT AUROC curves were found using outer inferior sector macular thickness (AUROC curve, 0.911) and volume (AUROC curve, 0.909). The highest SD-OCT AUROC curves were found using outer inferior region thickness (AUROC curve, 0.836) and volume (AUROC curve, 0.834). The difference between the two imaging modalities was not statistically significant (thickness, p = 0.141; volume, p = 0.138). The sensitivity of TD-OCT macular outer inferior average thickness was highest and was 88.2%, with a specificity of 80.4%. The sensitivity of TD-OCT average volume measurements in this same region was 76.5%, with a specificity of 91.3%. The SD-OCT average thickness measurements also had the highest sensitivity in this region, which was 78.6%, with a specificity of 82.1%. The SD-OCT volume measurements had a sensitivity of 67.9%, with a specificity of 92.3%. Both SD-OCT and TD-OCT measurements of outer inferior macular thickness and volume can differentiate between eyes of glaucoma patients and glaucoma suspects with high myopia. These independent predictors all had good sensitivity. Based on our results, SD-OCT and TD-OCT have similar diagnostic abilities. These parameters may provide useful additional data in highly myopic eyes to complement standard glaucoma diagnosis tools.

An infrared optical pacing system for high-throughput screening of cardiac electrophysiology in human cardiomyocytes (Conference Presentation)

NASA Astrophysics Data System (ADS)

McPheeters, Matt T.; Wang, Yves T.; Laurita, Kenneth R.; Jenkins, Michael W.

2017-02-01

Cardiomyocytes derived from human induced pluripotent stem cells (hiPS-HCM) have the potential to provide individualized therapies for patients and to test drug candidates for cardiac toxicity. In order for hiPS-CM to be useful for such applications, there is a need for high-throughput technology to rapidly assess cardiac electrophysiology parameters. Here, we designed and tested a fully contactless optical mapping (OM) and optical pacing (OP) system capable of imaging and point stimulation of hiPS-CM in small wells. OM allowed us to characterize cardiac electrophysiological parameters (conduction velocity, action potential duration, etc.) using voltage-sensitive dyes with high temporal and spatial resolution over the entire well. To improve OM signal-to-noise ratio, we tested a new voltage-sensitive dye (Fluovolt) for accuracy and phototoxicity. Stimulation is essential because most electrophysiological parameters are rate dependent; however, traditional methods utilizing electrical stimulation is difficult in small wells. To overcome this limitation, we utilized OP (λ = 1464 nm) to precisely control heart rate with spatial precision without the addition of exogenous agents. We optimized OP parameters (e.g., well size, pulse width, spot size) to achieve robust pacing and minimize the threshold radiant exposure. Finally, we tested system sensitivity using Flecainide, a drug with well described action on multiple electrophysiological properties.

Assessing the sensitivity of bovine tuberculosis surveillance in Canada's cattle population, 2009-2013.

PubMed

El Allaki, Farouk; Harrington, Noel; Howden, Krista

2016-11-01

The objectives of this study were (1) to estimate the annual sensitivity of Canada's bTB surveillance system and its three system components (slaughter surveillance, export testing and disease investigation) using a scenario tree modelling approach, and (2) to identify key model parameters that influence the estimates of the surveillance system sensitivity (SSSe). To achieve these objectives, we designed stochastic scenario tree models for three surveillance system components included in the analysis. Demographic data, slaughter data, export testing data, and disease investigation data from 2009 to 2013 were extracted for input into the scenario trees. Sensitivity analysis was conducted to identify key influential parameters on SSSe estimates. The median annual SSSe estimates generated from the study were very high, ranging from 0.95 (95% probability interval [PI]: 0.88-0.98) to 0.97 (95% PI: 0.93-0.99). Median annual sensitivity estimates for the slaughter surveillance component ranged from 0.95 (95% PI: 0.88-0.98) to 0.97 (95% PI: 0.93-0.99). This shows that slaughter surveillance to be the major contributor to overall surveillance system sensitivity with a high probability to detect M. bovis infection if present at a prevalence of 0.00028% or greater during the study period. The export testing and disease investigation components had extremely low component sensitivity estimates-the maximum median sensitivity estimates were 0.02 (95% PI: 0.014-0.023) and 0.0061 (95% PI: 0.0056-0.0066) respectively. The three most influential input parameters on the model's output (SSSe) were the probability of a granuloma being detected at slaughter inspection, the probability of a granuloma being present in older animals (≥12 months of age), and the probability of a granuloma sample being submitted to the laboratory. Additional studies are required to reduce the levels of uncertainty and variability associated with these three parameters influencing the surveillance system sensitivity. Crown Copyright © 2016. Published by Elsevier B.V. All rights reserved.

A sensitivity analysis of cloud properties to CLUBB parameters in the single-column Community Atmosphere Model (SCAM5)

DOE PAGES

Guo, Zhun; Wang, Minghuai; Qian, Yun; ...

2014-08-13

In this study, we investigate the sensitivity of simulated shallow cumulus and stratocumulus clouds to selected tunable parameters of Cloud Layers Unified by Binormals (CLUBB) in the single column version of Community Atmosphere Model version 5 (SCAM5). A quasi-Monte Carlo (QMC) sampling approach is adopted to effectively explore the high-dimensional parameter space and a generalized linear model is adopted to study the responses of simulated cloud fields to tunable parameters. One stratocumulus and two shallow convection cases are configured at both coarse and fine vertical resolutions in this study.. Our results show that most of the variance in simulated cloudmore » fields can be explained by a small number of tunable parameters. The parameters related to Newtonian and buoyancy-damping terms of total water flux are found to be the most influential parameters for stratocumulus. For shallow cumulus, the most influential parameters are those related to skewness of vertical velocity, reflecting the strong coupling between cloud properties and dynamics in this regime. The influential parameters in the stratocumulus case are sensitive to the choice of the vertical resolution while little sensitivity is found for the shallow convection cases, as eddy mixing length (or dissipation time scale) plays a more important role and depends more strongly on the vertical resolution in stratocumulus than in shallow convections. The influential parameters remain almost unchanged when the number of tunable parameters increases from 16 to 35. This study improves understanding of the CLUBB behavior associated with parameter uncertainties.« less

Photochemical modeling and analysis of meteorological parameters during ozone episodes in Kaohsiung, Taiwan

NASA Astrophysics Data System (ADS)

Chen, K. S.; Ho, Y. T.; Lai, C. H.; Chou, Youn-Min

The events of high ozone concentrations and meteorological conditions covering the Kaohsiung metropolitan area were investigated based on data analysis and model simulation. A photochemical grid model was employed to analyze two ozone episodes in autumn (2000) and winter (2001) seasons, each covering three consecutive days (or 72 h) in the Kaohsiung City. The potential influence of the initial and boundary conditions on model performance was assessed. Model performance can be improved by separately considering the daytime and nighttime ozone concentrations on the lateral boundary conditions of the model domain. The sensitivity analyses of ozone concentrations to the emission reductions in volatile organic compounds (VOC) and nitrogen oxides (NO x) show a VOC-sensitive regime for emission reductions to lower than 30-40% VOC and 30-50% NO x and a NO x-sensitive regime for larger percentage reductions. Meteorological parameters show that warm temperature, sufficient sunlight, low wind, and high surface pressure are distinct parameters that tend to trigger ozone episodes in polluted urban areas, like Kaohsiung.

Objectification of steering feel around straight-line driving for vehicle/tyre design

NASA Astrophysics Data System (ADS)

Kim, Jungsik; Yoon, Yong-San

2015-02-01

This paper presents the objectification techniques for the assessment of steering feel including {on-centre} feel and steering response by measurement data. Here, new objective parameters are developed by considering not only the process by which the steering feel is evaluated subjectively but also by the ergonomic perceptive sensitivity of the driver. In order to validate such objective parameters, subjective tests are carried out by professional drivers. Objective measurements are also performed for several cars at a proving ground. The linear correlation coefficients between the subjective ratings and the objective parameters are calculated. As one of new objective parameters, steering wheel angle defined by ergonomic perception sensitivity shows high correlation with the subjective questionnaires of on-center responses. Newly defined steering torque curvature also shows high correlation with the subjective questionnaires of on-center effort. These correlation results conclude that the subjective assessment of steering feel can be successfully explained and objectified by means of the suggested objective parameters.

Sensitivity analysis of eigenvalues for an electro-hydraulic servomechanism

NASA Astrophysics Data System (ADS)

Stoia-Djeska, M.; Safta, C. A.; Halanay, A.; Petrescu, C.

2012-11-01

Electro-hydraulic servomechanisms (EHSM) are important components of flight control systems and their role is to control the movement of the flying control surfaces in response to the movement of the cockpit controls. As flight-control systems, the EHSMs have a fast dynamic response, a high power to inertia ratio and high control accuracy. The paper is devoted to the study of the sensitivity for an electro-hydraulic servomechanism used for an aircraft aileron action. The mathematical model of the EHSM used in this paper includes a large number of parameters whose actual values may vary within some ranges of uncertainty. It consists in a nonlinear ordinary differential equation system composed by the mass and energy conservation equations, the actuator movement equations and the controller equation. In this work the focus is on the sensitivities of the eigenvalues of the linearized homogeneous system, which are the partial derivatives of the eigenvalues of the state-space system with respect the parameters. These are obtained using a modal approach based on the eigenvectors of the state-space direct and adjoint systems. To calculate the eigenvalues and their sensitivity the system's Jacobian and its partial derivatives with respect the parameters are determined. The calculation of the derivative of the Jacobian matrix with respect to the parameters is not a simple task and for many situations it must be done numerically. The system stability is studied in relation with three parameters: m, the equivalent inertial load of primary control surface reduced to the actuator rod; B, the bulk modulus of oil and p a pressure supply proportionality coefficient. All the sensitivities calculated in this work are in good agreement with those obtained through recalculations.

Effect of different transport observations on inverse modeling results: case study of a long-term groundwater tracer test monitored at high resolution

NASA Astrophysics Data System (ADS)

Rasa, Ehsan; Foglia, Laura; Mackay, Douglas M.; Scow, Kate M.

2013-11-01

Conservative tracer experiments can provide information useful for characterizing various subsurface transport properties. This study examines the effectiveness of three different types of transport observations for sensitivity analysis and parameter estimation of a three-dimensional site-specific groundwater flow and transport model: conservative tracer breakthrough curves (BTCs), first temporal moments of BTCs ( m 1), and tracer cumulative mass discharge ( M d) through control planes combined with hydraulic head observations ( h). High-resolution data obtained from a 410-day controlled field experiment at Vandenberg Air Force Base, California (USA), have been used. In this experiment, bromide was injected to create two adjacent plumes monitored at six different transects (perpendicular to groundwater flow) with a total of 162 monitoring wells. A total of 133 different observations of transient hydraulic head, 1,158 of BTC concentration, 23 of first moment, and 36 of mass discharge were used for sensitivity analysis and parameter estimation of nine flow and transport parameters. The importance of each group of transport observations in estimating these parameters was evaluated using sensitivity analysis, and five out of nine parameters were calibrated against these data. Results showed the advantages of using temporal moment of conservative tracer BTCs and mass discharge as observations for inverse modeling.

A global sensitivity analysis approach for morphogenesis models.

PubMed

Boas, Sonja E M; Navarro Jimenez, Maria I; Merks, Roeland M H; Blom, Joke G

2015-11-21

Morphogenesis is a developmental process in which cells organize into shapes and patterns. Complex, non-linear and multi-factorial models with images as output are commonly used to study morphogenesis. It is difficult to understand the relation between the uncertainty in the input and the output of such 'black-box' models, giving rise to the need for sensitivity analysis tools. In this paper, we introduce a workflow for a global sensitivity analysis approach to study the impact of single parameters and the interactions between them on the output of morphogenesis models. To demonstrate the workflow, we used a published, well-studied model of vascular morphogenesis. The parameters of this cellular Potts model (CPM) represent cell properties and behaviors that drive the mechanisms of angiogenic sprouting. The global sensitivity analysis correctly identified the dominant parameters in the model, consistent with previous studies. Additionally, the analysis provided information on the relative impact of single parameters and of interactions between them. This is very relevant because interactions of parameters impede the experimental verification of the predicted effect of single parameters. The parameter interactions, although of low impact, provided also new insights in the mechanisms of in silico sprouting. Finally, the analysis indicated that the model could be reduced by one parameter. We propose global sensitivity analysis as an alternative approach to study the mechanisms of morphogenesis. Comparison of the ranking of the impact of the model parameters to knowledge derived from experimental data and from manipulation experiments can help to falsify models and to find the operand mechanisms in morphogenesis. The workflow is applicable to all 'black-box' models, including high-throughput in vitro models in which output measures are affected by a set of experimental perturbations.

Uncertainty Quantification and Sensitivity Analysis in the CICE v5.1 Sea Ice Model

NASA Astrophysics Data System (ADS)

Urrego-Blanco, J. R.; Urban, N. M.

2015-12-01

Changes in the high latitude climate system have the potential to affect global climate through feedbacks with the atmosphere and connections with mid latitudes. Sea ice and climate models used to understand these changes have uncertainties that need to be characterized and quantified. In this work we characterize parametric uncertainty in Los Alamos Sea Ice model (CICE) and quantify the sensitivity of sea ice area, extent and volume with respect to uncertainty in about 40 individual model parameters. Unlike common sensitivity analyses conducted in previous studies where parameters are varied one-at-a-time, this study uses a global variance-based approach in which Sobol sequences are used to efficiently sample the full 40-dimensional parameter space. This approach requires a very large number of model evaluations, which are expensive to run. A more computationally efficient approach is implemented by training and cross-validating a surrogate (emulator) of the sea ice model with model output from 400 model runs. The emulator is used to make predictions of sea ice extent, area, and volume at several model configurations, which are then used to compute the Sobol sensitivity indices of the 40 parameters. A ranking based on the sensitivity indices indicates that model output is most sensitive to snow parameters such as conductivity and grain size, and the drainage of melt ponds. The main effects and interactions among the most influential parameters are also estimated by a non-parametric regression technique based on generalized additive models. It is recommended research to be prioritized towards more accurately determining these most influential parameters values by observational studies or by improving existing parameterizations in the sea ice model.

Preparation and Characterization of Cyclotrimethylenetrinitramine (RDX) with Reduced Sensitivity

PubMed Central

Wang, Yuqiao; Li, Xin; Chen, Shusen; Ma, Xiao; Yu, Ziyang; Jin, Shaohua; Li, Lijie; Chen, Yu

2017-01-01

The internal defects and shape of cyclotrimethylenetrinitramine (RDX) crystal are critical parameters for the preparation of reduced sensitivity RDX (RS-RDX). In the current study, RDX was re-crystallized and spheroidized to form the high-quality RDX that was further characterized by purity, apparent density, size distribution, specific surface area, impact sensitivity, and shock sensitivity. The effects of re-crystallization solvent on the growth morphology of RDX crystal were investigated by both theoretical simulation and experiment test, and consistent results were obtained. The high-quality RDX exhibited a high purity (≥99.90%), high apparent density (≥1.811 g/cm3), spherical shape, and relatively low impact sensitivity (6%). Its specific surface area was reduced more than 30%. Compared with conventional RDXs, the high-quality RDX reduced the shock sensitivities of PBXN-109 and PBXW-115 by more than 30%, indicating that it was a RS-RDX. The reduced sensitivity and good processability of the high-quality RDX would be significant in improving the performances of RDX-based PBXs. PMID:28825661

Blood parameters in Swedish dairy herds with high or low incidence of displaced abomasum or ketosis.

PubMed

Stengärde, Lena; Holtenius, Kjell; Emanuelson, Ulf; Hultgren, Jan; Niskanen, Rauni; Tråvén, Madeleine

2011-10-01

Sixty dairy herds were studied to investigate the association between long-term incidence of displaced abomasum and clinical ketosis and body condition score and blood profiles, including parameters estimating energy metabolism and hepatic lipidosis in the periparturient period and early lactation. Blood samples were taken around parturition and in early lactation from cows without apparent clinical symptoms of metabolic disorders. A difference in metabolism between high and low incidence herds was shown post-partum by a lower metabolic index (the revised Quantitative Insulin Sensitivity Check Index, RQUICKI), and tendencies for higher concentrations of glucose, insulin and non-esterified fatty acids in the high incidence herds. High incidence herds had more cows and produced on average 1400kg energy-corrected milk per cow per year more than the low incidence herds. No differences were found in parameters reflecting liver cell damage. In the first 3weeks post-partum the RQUICKI was a more sensitive marker of herds with a high incidence of displaced abomasum and clinical ketosis than any of the individual parameters, but further research is needed before practical applications of the RQUICKI can be foreseen. Copyright © 2010 Elsevier Ltd. All rights reserved.

Normalized sensitivities and parameter identifiability of in situ diffusion experiments on Callovo Oxfordian clay at Bure site

NASA Astrophysics Data System (ADS)

Samper, J.; Dewonck, S.; Zheng, L.; Yang, Q.; Naves, A.

Diffusion of inert and reactive tracers (DIR) is an experimental program performed by ANDRA at Bure underground research laboratory in Meuse/Haute Marne (France) to characterize diffusion and retention of radionuclides in Callovo-Oxfordian (C-Ox) argillite. In situ diffusion experiments were performed in vertical boreholes to determine diffusion and retention parameters of selected radionuclides. C-Ox clay exhibits a mild diffusion anisotropy due to stratification. Interpretation of in situ diffusion experiments is complicated by several non-ideal effects caused by the presence of a sintered filter, a gap between the filter and borehole wall and an excavation disturbed zone (EdZ). The relevance of such non-ideal effects and their impact on estimated clay parameters have been evaluated with numerical sensitivity analyses and synthetic experiments having similar parameters and geometric characteristics as real DIR experiments. Normalized dimensionless sensitivities of tracer concentrations at the test interval have been computed numerically. Tracer concentrations are found to be sensitive to all key parameters. Sensitivities are tracer dependent and vary with time. These sensitivities are useful to identify which are the parameters that can be estimated with less uncertainty and find the times at which tracer concentrations begin to be sensitive to each parameter. Synthetic experiments generated with prescribed known parameters have been interpreted automatically with INVERSE-CORE 2D and used to evaluate the relevance of non-ideal effects and ascertain parameter identifiability in the presence of random measurement errors. Identifiability analysis of synthetic experiments reveals that data noise makes difficult the estimation of clay parameters. Parameters of clay and EdZ cannot be estimated simultaneously from noisy data. Models without an EdZ fail to reproduce synthetic data. Proper interpretation of in situ diffusion experiments requires accounting for filter, gap and EdZ. Estimates of the effective diffusion coefficient and the porosity of clay are highly correlated, indicating that these parameters cannot be estimated simultaneously. Accurate estimation of De and porosities of clay and EdZ is only possible when the standard deviation of random noise is less than 0.01. Small errors in the volume of the circulation system do not affect clay parameter estimates. Normalized sensitivities as well as the identifiability analysis of synthetic experiments provide additional insight on inverse estimation of in situ diffusion experiments and will be of great benefit for the interpretation of real DIR in situ diffusion experiments.

Resonator graphene microfluidic antenna (RGMA) for blood glucose detection

NASA Astrophysics Data System (ADS)

Jizat, Noorlindawaty Md.; Mohamad, Su Natasha; Ishak, Muhammad Ikman

2017-09-01

Graphene is capable of highly sensitive analyte detection due to its nanoscale nature. Here we show a resonator graphene microfluidic antenna (RGMA) is used to detect the dielectric properties of aqueous glucose solution which represent the glucose level in blood. Simulation verified the high sensitivity of proposed RGMA made with aqueous glucose solutions at different concentrations. The RGMA yielded a sensor sensitivity of 0.1882GHz/mgml-1 as plotted from the slope of the linear fit from the result averages in S11 and S21 parameter, respectively. This results indicate that the proposed resonator antenna achieves high sensitivity and linear to the changes of glucose concentration.

Parametric Sensitivity Analysis of Precipitation at Global and Local Scales in the Community Atmosphere Model CAM5

DOE PAGES

Qian, Yun; Yan, Huiping; Hou, Zhangshuan; ...

2015-04-10

We investigate the sensitivity of precipitation characteristics (mean, extreme and diurnal cycle) to a set of uncertain parameters that influence the qualitative and quantitative behavior of the cloud and aerosol processes in the Community Atmosphere Model (CAM5). We adopt both the Latin hypercube and quasi-Monte Carlo sampling approaches to effectively explore the high-dimensional parameter space and then conduct two large sets of simulations. One set consists of 1100 simulations (cloud ensemble) perturbing 22 parameters related to cloud physics and convection, and the other set consists of 256 simulations (aerosol ensemble) focusing on 16 parameters related to aerosols and cloud microphysics.more » Results show that for the 22 parameters perturbed in the cloud ensemble, the six having the greatest influences on the global mean precipitation are identified, three of which (related to the deep convection scheme) are the primary contributors to the total variance of the phase and amplitude of the precipitation diurnal cycle over land. The extreme precipitation characteristics are sensitive to a fewer number of parameters. The precipitation does not always respond monotonically to parameter change. The influence of individual parameters does not depend on the sampling approaches or concomitant parameters selected. Generally the GLM is able to explain more of the parametric sensitivity of global precipitation than local or regional features. The total explained variance for precipitation is primarily due to contributions from the individual parameters (75-90% in total). The total variance shows a significant seasonal variability in the mid-latitude continental regions, but very small in tropical continental regions.« less

Flexible Carbon Nanotube Films for High Performance Strain Sensors

PubMed Central

Kanoun, Olfa; Müller, Christian; Benchirouf, Abderahmane; Sanli, Abdulkadir; Dinh, Trong Nghia; Al-Hamry, Ammar; Bu, Lei; Gerlach, Carina; Bouhamed, Ayda

2014-01-01

Compared with traditional conductive fillers, carbon nanotubes (CNTs) have unique advantages, i.e., excellent mechanical properties, high electrical conductivity and thermal stability. Nanocomposites as piezoresistive films provide an interesting approach for the realization of large area strain sensors with high sensitivity and low manufacturing costs. A polymer-based nanocomposite with carbon nanomaterials as conductive filler can be deposited on a flexible substrate of choice and this leads to mechanically flexible layers. Such sensors allow the strain measurement for both integral measurement on a certain surface and local measurement at a certain position depending on the sensor geometry. Strain sensors based on carbon nanostructures can overcome several limitations of conventional strain sensors, e.g., sensitivity, adjustable measurement range and integral measurement on big surfaces. The novel technology allows realizing strain sensors which can be easily integrated even as buried layers in material systems. In this review paper, we discuss the dependence of strain sensitivity on different experimental parameters such as composition of the carbon nanomaterial/polymer layer, type of polymer, fabrication process and processing parameters. The insights about the relationship between film parameters and electromechanical properties can be used to improve the design and fabrication of CNT strain sensors. PMID:24915183

Effect of Hydroxyl Concentration on Chemical Sensitivity of Polyvinyl Alcohol/Carbon-Black Composite Chemiresistors

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

Hughes, Robert C.; Patel, Sanjay V.; Yelton, W. Graham

1999-05-19

The sensitivity and selectivity of polyvinyl alcohol (PVA) / carbon black composite films have been found to vary depending upon the hydroxylation percentage ("-OH") of the polymer. These chemiresistors made from PVA films whose polymer backbone is 88% hydroxylated (PVA88) have a high sensitivity to water, while chemiresistors made from PVA75 have a higher sensitivity to methanol. The minor differences in polymer composition result in films with different Hildebrand volubility parameters. The relative responses of several different PVA-based chemiresistors to solvents with different volubility parameters are presented. In addition, polyvinyl acetate (PVAC) films with PVA88 are used in an arraymore » to distinguish the responses to methanol-water mixtures.« less

Sensitivity Analysis of Fatigue Crack Growth Model for API Steels in Gaseous Hydrogen.

PubMed

Amaro, Robert L; Rustagi, Neha; Drexler, Elizabeth S; Slifka, Andrew J

2014-01-01

A model to predict fatigue crack growth of API pipeline steels in high pressure gaseous hydrogen has been developed and is presented elsewhere. The model currently has several parameters that must be calibrated for each pipeline steel of interest. This work provides a sensitivity analysis of the model parameters in order to provide (a) insight to the underlying mathematical and mechanistic aspects of the model, and (b) guidance for model calibration of other API steels.

High-Pressure Oxygen Test Evaluations

NASA Technical Reports Server (NTRS)

Schwinghamer, R. J.; Key, C. F.

1974-01-01

The relevance of impact sensitivity testing to the development of the space shuttle main engine is discussed in the light of the special requirements for the engine. The background and history of the evolution of liquid and gaseous oxygen testing techniques and philosophy is discussed also. The parameters critical to reliable testing are treated in considerable detail, and test apparatus and procedures are described and discussed. Materials threshold sensitivity determination procedures are considered and a decision logic diagram for sensitivity threshold determination was plotted. Finally, high-pressure materials sensitivity test data are given for selected metallic and nonmetallic materials.

Application research on the sensitivity of porous silicon

NASA Astrophysics Data System (ADS)

Xu, Gaobin; Xi, Ye; Chen, Xing; Ma, Yuanming

2017-09-01

Applications based on sensitive property of porous silicon (PSi) were researched. As a kind of porous material, the feasibility of PSi as a getter material was studied. Five groups of samples with different parameters were prepared. The gas-sensing property of PSi was studied by the test system and suitable parameters of PSi were also discussed. Meanwhile a novel structure of humidity sensor, using porous silicon as humidity-sensitive material, based on MEMS process has been successfully designed. The humidity-sensing properties were studied by a test system. Because of the polysilicon layer deposited upon the PSi layer, the humidity sensor can realize a quick dehumidification by itself. To extend service life and reduce the effect of the environment, a passivation layer (Si3N4) was also deposited on the surface of electrodes. The result indicated the novel humidity sensor presented high sensitivity (1.1 pF/RH%), low hysteresis, low temperature coefficient (0.5%RH/°C) and high stability.

[Parameter sensitivity of simulating net primary productivity of Larix olgensis forest based on BIOME-BGC model].

PubMed

He, Li-hong; Wang, Hai-yan; Lei, Xiang-dong

2016-02-01

Model based on vegetation ecophysiological process contains many parameters, and reasonable parameter values will greatly improve simulation ability. Sensitivity analysis, as an important method to screen out the sensitive parameters, can comprehensively analyze how model parameters affect the simulation results. In this paper, we conducted parameter sensitivity analysis of BIOME-BGC model with a case study of simulating net primary productivity (NPP) of Larix olgensis forest in Wangqing, Jilin Province. First, with the contrastive analysis between field measurement data and the simulation results, we tested the BIOME-BGC model' s capability of simulating the NPP of L. olgensis forest. Then, Morris and EFAST sensitivity methods were used to screen the sensitive parameters that had strong influence on NPP. On this basis, we also quantitatively estimated the sensitivity of the screened parameters, and calculated the global, the first-order and the second-order sensitivity indices. The results showed that the BIOME-BGC model could well simulate the NPP of L. olgensis forest in the sample plot. The Morris sensitivity method provided a reliable parameter sensitivity analysis result under the condition of a relatively small sample size. The EFAST sensitivity method could quantitatively measure the impact of simulation result of a single parameter as well as the interaction between the parameters in BIOME-BGC model. The influential sensitive parameters for L. olgensis forest NPP were new stem carbon to new leaf carbon allocation and leaf carbon to nitrogen ratio, the effect of their interaction was significantly greater than the other parameter' teraction effect.

Sensitivity of MRI parameters within intervertebral discs to the severity of adolescent idiopathic scoliosis.

PubMed

Huber, Maxime; Gilbert, Guillaume; Roy, Julien; Parent, Stefan; Labelle, Hubert; Périé, Delphine

2016-11-01

To measure magnetic resonance imaging (MRI) parameters including relaxation times (T 1 ρ, T 2 ), magnetization transfer (MT) and diffusion parameters (mean diffusivity [MD], fractional anisotropy [FA]) of intervertebral discs in adolescents with idiopathic scoliosis, and to investigate the sensitivity of these MR parameters to the severity of the spine deformities. Thirteen patients with adolescent idiopathic scoliosis and three control volunteers with no history of spine disease underwent an MRI acquisition at 3T including the mapping of T 1 ρ, T 2 , MT, MD, and FA. The apical zone included all discs within the scoliotic curve while the control zone was composed of other discs. The severity was analyzed through low (<32°) versus high (>40°) Cobb angles. One-way analysis of variance (ANOVA) and agglomerative hierarchical clustering (AHC) were performed. Significant differences were found between the apical zone and the control zone for T 2 (P = 0.047), and between low and high Cobb angles for T 2 (P = 0.014) and MT (P = 0.002). AHC showed two distinct clusters, one with mainly low Cobb angles and one with mainly high Cobb angles, for the MRI parameters measured within the apical zone, with an accuracy of 0.9 and a Matthews correlation coefficient (MCC) of 0.8. Within the control zone, the AHC showed no clear classification (accuracy of 0.6 and MCC of 0.2). We successfully performed an in vivo multiparametric MRI investigation of young patients with adolescent idiopathic scoliosis. The MRI parameters measured within the intervertebral discs were found to be sensitive to intervertebral disc degeneration occurring with scoliosis and to the severity of scoliosis. J. Magn. Reson. Imaging 2016;44:1123-1131. © 2016 International Society for Magnetic Resonance in Medicine.

Mapping of bare soil surface parameters from TerraSAR-X radar images over a semi-arid region

NASA Astrophysics Data System (ADS)

Gorrab, A.; Zribi, M.; Baghdadi, N.; Lili Chabaane, Z.

2015-10-01

The goal of this paper is to analyze the sensitivity of X-band SAR (TerraSAR-X) signals as a function of different physical bare soil parameters (soil moisture, soil roughness), and to demonstrate that it is possible to estimate of both soil moisture and texture from the same experimental campaign, using a single radar signal configuration (one incidence angle, one polarization). Firstly, we analyzed statistically the relationships between X-band SAR (TerraSAR-X) backscattering signals function of soil moisture and different roughness parameters (the root mean square height Hrms, the Zs parameter and the Zg parameter) at HH polarization and for an incidence angle about 36°, over a semi-arid site in Tunisia (North Africa). Results have shown a high sensitivity of real radar data to the two soil parameters: roughness and moisture. A linear relationship is obtained between volumetric soil moisture and radar signal. A logarithmic correlation is observed between backscattering coefficient and all roughness parameters. The highest dynamic sensitivity is obtained with Zg parameter. Then, we proposed to retrieve of both soil moisture and texture using these multi-temporal X-band SAR images. Our approach is based on the change detection method and combines the seven radar images with different continuous thetaprobe measurements. To estimate soil moisture from X-band SAR data, we analyzed statistically the sensitivity between radar measurements and ground soil moisture derived from permanent thetaprobe stations. Our approaches are applied over bare soil class identified from an optical image SPOT / HRV acquired in the same period of measurements. Results have shown linear relationship for the radar signals as a function of volumetric soil moisture with high sensitivity about 0.21 dB/vol%. For estimation of change in soil moisture, we considered two options: (1) roughness variations during the three-month radar acquisition campaigns were not accounted for; (2) a simple correction for temporal variations in roughness was included. The results reveal a small improvement in the estimation of soil moisture when a correction for temporal variations in roughness is introduced. Finally, by considering the estimated temporal dynamics of soil moisture, a methodology is proposed for the retrieval of clay and sand content (expressed as percentages) in soil. Two empirical relationships were established between the mean moisture values retrieved from the seven acquired radar images and the two soil texture components over 36 test fields. Validation of the proposed approach was carried out over a second set of 34 fields, showing that highly accurate clay estimations can be achieved.

Stereometric parameters change vs. Topographic Change Analysis (TCA) agreement in Heidelberg Retina Tomography III (HRT-3) early detection of clinical significant glaucoma progression.

PubMed

Dascalu, A M; Cherecheanu, A P; Stana, D; Voinea, L; Ciuluvica, R; Savlovschi, C; Serban, D

2014-01-01

to investigate the sensitivity and specificity of the stereometric parameters change analysis vs. Topographic Change Analysis in early detection of glaucoma progression. 81 patients with POAG were monitored for 4 years (GAT monthly, SAP at every 6 months, optic disc photographs and HRT3 yearly). The exclusion criteria were other optic disc or retinal pathology; topographic standard deviation (TSD>30; inter-test variation of reference height>25 μm. The criterion for structural progression was the following: at least 20 adjacent super-pixels with a clinically significant decrease in height (>5%). 16 patients of the total 81 presented structural progression on TCA. The most useful stereometric parameters for the early detection of glaucoma progression were the following: Rim Area change (sensitivity 100%, specificity 74.2% for a "cut-off " value of -0.05), C/D Area change (sensitivity 85.7%, specificity 71.5% for a "cut off " value of 0.02), C/D linear change (sensitivity 85.7%, specificity 71.5% for a "cut-off " value of 0.02), Rim Volume change (sensitivity 71.4%, specificity 88.8% for a "cut-off " value of -0.04). RNFL Thickness change (<0) was highly sensitive (82%), but less specific for glaucoma progression (45,2%). Changes of the other stereometric parameters have a limited diagnostic value for the early detection of glaucoma progression. TCA is a valuable tool for the assessment of the structural progression in glaucoma patients and its inter-test variability is low. On long-term, the quantitative analysis according to stereometric parameters change is also very important. The most relevant parameters to detect progression are RA, C/D Area, Linear C/D and RV.

[Sensitivity analysis of AnnAGNPS model's hydrology and water quality parameters based on the perturbation analysis method].

PubMed

Xi, Qing; Li, Zhao-Fu; Luo, Chuan

2014-05-01

Sensitivity analysis of hydrology and water quality parameters has a great significance for integrated model's construction and application. Based on AnnAGNPS model's mechanism, terrain, hydrology and meteorology, field management, soil and other four major categories of 31 parameters were selected for the sensitivity analysis in Zhongtian river watershed which is a typical small watershed of hilly region in the Taihu Lake, and then used the perturbation method to evaluate the sensitivity of the parameters to the model's simulation results. The results showed that: in the 11 terrain parameters, LS was sensitive to all the model results, RMN, RS and RVC were generally sensitive and less sensitive to the output of sediment but insensitive to the remaining results. For hydrometeorological parameters, CN was more sensitive to runoff and sediment and relatively sensitive for the rest results. In field management, fertilizer and vegetation parameters, CCC, CRM and RR were less sensitive to sediment and particulate pollutants, the six fertilizer parameters (FR, FD, FID, FOD, FIP, FOP) were particularly sensitive for nitrogen and phosphorus nutrients. For soil parameters, K is quite sensitive to all the results except the runoff, the four parameters of the soil's nitrogen and phosphorus ratio (SONR, SINR, SOPR, SIPR) were less sensitive to the corresponding results. The simulation and verification results of runoff in Zhongtian watershed show a good accuracy with the deviation less than 10% during 2005- 2010. Research results have a direct reference value on AnnAGNPS model's parameter selection and calibration adjustment. The runoff simulation results of the study area also proved that the sensitivity analysis was practicable to the parameter's adjustment and showed the adaptability to the hydrology simulation in the Taihu Lake basin's hilly region and provide reference for the model's promotion in China.

GA-optimization for rapid prototype system demonstration

NASA Technical Reports Server (NTRS)

Kim, Jinwoo; Zeigler, Bernard P.

1994-01-01

An application of the Genetic Algorithm (GA) is discussed. A novel scheme of Hierarchical GA was developed to solve complicated engineering problems which require optimization of a large number of parameters with high precision. High level GAs search for few parameters which are much more sensitive to the system performance. Low level GAs search in more detail and employ a greater number of parameters for further optimization. Therefore, the complexity of the search is decreased and the computing resources are used more efficiently.

[Research on optimization of mathematical model of flow injection-hydride generation-atomic fluorescence spectrometry].

PubMed

Cui, Jian; Zhao, Xue-Hong; Wang, Yan; Xiao, Ya-Bing; Jiang, Xue-Hui; Dai, Li

2014-01-01

Flow injection-hydride generation-atomic fluorescence spectrometry was a widely used method in the industries of health, environmental, geological and metallurgical fields for the merit of high sensitivity, wide measurement range and fast analytical speed. However, optimization of this method was too difficult as there exist so many parameters affecting the sensitivity and broadening. Generally, the optimal conditions were sought through several experiments. The present paper proposed a mathematical model between the parameters and sensitivity/broadening coefficients using the law of conservation of mass according to the characteristics of hydride chemical reaction and the composition of the system, which was proved to be accurate as comparing the theoretical simulation and experimental results through the test of arsanilic acid standard solution. Finally, this paper has put a relation map between the parameters and sensitivity/broadening coefficients, and summarized that GLS volume, carrier solution flow rate and sample loop volume were the most factors affecting sensitivity and broadening coefficients. Optimizing these three factors with this relation map, the relative sensitivity was advanced by 2.9 times and relative broadening was reduced by 0.76 times. This model can provide a theoretical guidance for the optimization of the experimental conditions.

Sensitivity of breeding parameters to food supply in Black-legged Kittiwakes Rissa tridactyla

USGS Publications Warehouse

Gill, Verena A.; Hatch, Scott A.; Lanctot, Richard B.

2002-01-01

We fed Herring Clupea pallasi to pairs of Black-legged Kittiwakes Rissa tridactyla throughout the breeding season in two years at a colony in the northern Gulf of Alaska. We measured responses to supplemental feeding in a wide array of breeding parameters to gauge their relative sensitivity to food supply, and thus their potential as indicators of natural foraging conditions. Conventional measures of success (hatching, fledging and overall productivity) were more effective as indicators of food supply than behavioural attributes such as courtship feeding, chick provisioning rates and sibling aggression. However, behaviour such as nest relief during incubation and adult attendance with older chicks were also highly responsive to supplemental food and may be useful for monitoring environmental conditions in studies of shorter duration. On average, the chick-rearing stage contained more sensitive indicators of food availability than prelaying or incubation stages. Overall, rates of hatching and fledging success, and the mean duration of incubation shifts were the most food-sensitive parameters studied.

Comparison of stability and control parameters for a light, single-engine, high-winged aircraft using different flight test and parameter estimation techniques

NASA Technical Reports Server (NTRS)

Suit, W. T.; Cannaday, R. L.

1979-01-01

The longitudinal and lateral stability and control parameters for a high wing, general aviation, airplane are examined. Estimations using flight data obtained at various flight conditions within the normal range of the aircraft are presented. The estimations techniques, an output error technique (maximum likelihood) and an equation error technique (linear regression), are presented. The longitudinal static parameters are estimated from climbing, descending, and quasi steady state flight data. The lateral excitations involve a combination of rudder and ailerons. The sensitivity of the aircraft modes of motion to variations in the parameter estimates are discussed.

A model for hormonal control of the menstrual cycle: structural consistency but sensitivity with regard to data.

PubMed

Selgrade, J F; Harris, L A; Pasteur, R D

2009-10-21

This study presents a 13-dimensional system of delayed differential equations which predicts serum concentrations of five hormones important for regulation of the menstrual cycle. Parameters for the system are fit to two different data sets for normally cycling women. For these best fit parameter sets, model simulations agree well with the two different data sets but one model also has an abnormal stable periodic solution, which may represent polycystic ovarian syndrome. This abnormal cycle occurs for the model in which the normal cycle has estradiol levels at the high end of the normal range. Differences in model behavior are explained by studying hysteresis curves in bifurcation diagrams with respect to sensitive model parameters. For instance, one sensitive parameter is indicative of the estradiol concentration that promotes pituitary synthesis of a large amount of luteinizing hormone, which is required for ovulation. Also, it is observed that models with greater early follicular growth rates may have a greater risk of cycling abnormally.

Optimization of Parameter Ranges for Composite Tape Winding Process Based on Sensitivity Analysis

NASA Astrophysics Data System (ADS)

Yu, Tao; Shi, Yaoyao; He, Xiaodong; Kang, Chao; Deng, Bo; Song, Shibo

2017-08-01

This study is focus on the parameters sensitivity of winding process for composite prepreg tape. The methods of multi-parameter relative sensitivity analysis and single-parameter sensitivity analysis are proposed. The polynomial empirical model of interlaminar shear strength is established by response surface experimental method. Using this model, the relative sensitivity of key process parameters including temperature, tension, pressure and velocity is calculated, while the single-parameter sensitivity curves are obtained. According to the analysis of sensitivity curves, the stability and instability range of each parameter are recognized. Finally, the optimization method of winding process parameters is developed. The analysis results show that the optimized ranges of the process parameters for interlaminar shear strength are: temperature within [100 °C, 150 °C], tension within [275 N, 387 N], pressure within [800 N, 1500 N], and velocity within [0.2 m/s, 0.4 m/s], respectively.

High-sensitivity and large-dynamic-range refractive index sensors employing weak composite Fabry-Perot cavities.

PubMed

Chen, Pengcheng; Shu, Xuewen; Cao, Haoran; Sugden, Kate

2017-08-15

Most sensors face a common trade-off between high sensitivity and a large dynamic range. We demonstrate here an all-fiber refractometer based on a dual-cavity Fabry-Perot interferometer (FPI) that possesses the advantage of both high sensitivity and a large dynamic range. Since the two composite cavities have a large cavity length difference, one can observe both fine and coarse fringes, which correspond to the long cavity and the short cavity, respectively. The short-cavity FPI and the use of an intensity demodulation method mean that the individual fine fringe dips correspond to a series of quasi-continuous highly sensitive zones for refractive index measurement. By calculating the parameters of the composite FPI, we find that the range of the ultra-sensitive zones can be considerably adjusted to suit the end requirements. The experimental trends are in good agreement with the theoretical predictions. The co-existence of high sensitivity and a large dynamic range in a composite FPI is of great significance to practical RI measurements.

Machine Learning Predictions of a Multiresolution Climate Model Ensemble

NASA Astrophysics Data System (ADS)

Anderson, Gemma J.; Lucas, Donald D.

2018-05-01

Statistical models of high-resolution climate models are useful for many purposes, including sensitivity and uncertainty analyses, but building them can be computationally prohibitive. We generated a unique multiresolution perturbed parameter ensemble of a global climate model. We use a novel application of a machine learning technique known as random forests to train a statistical model on the ensemble to make high-resolution model predictions of two important quantities: global mean top-of-atmosphere energy flux and precipitation. The random forests leverage cheaper low-resolution simulations, greatly reducing the number of high-resolution simulations required to train the statistical model. We demonstrate that high-resolution predictions of these quantities can be obtained by training on an ensemble that includes only a small number of high-resolution simulations. We also find that global annually averaged precipitation is more sensitive to resolution changes than to any of the model parameters considered.

Diagnostic utility of F waves in clinically diagnosed patients of carpal tunnel syndrome.

PubMed

Joshi, Anand G; Gargate, Ashwini R

2013-01-01

Sensory nerve conduction velocity (SNCV) of median nerve measured across the carpal tunnel, difference between distal sensory latencies (DSLs) of median and ulnar nerves and difference between distal motor latencies (DMLs) of median and ulnar nerves are commonly used nerve conduction parameters for diagnosis of carpal tunnel syndrome (CTS). These are having high degree of sensitivity and specificity. Study of median nerve F-wave minimal latency (FWML) and difference between F-wave minimal latencies (FWMLs) of median and ulnar nerves have also been reported to be useful parameters for diagnosis of CTS. However, there is controversy regarding superiority of F-wave study for diagnosis of CTS. So the aim of present study was to compare sensitivity and specificity of median FWML and difference between FWMLs of median and ulnar nerves with that of above mentioned electrophysiological parameters and to find out which parameters are having more sensitivity and specificity, for early diagnosis of CTS. Median and ulnar nerves sensory and motor conduction, median and ulnar nerves F-wave studies were carried out bilaterally in 125 clinically diagnosed patients of carpal tunnel syndrome. These parameters were also studied in 45 age matched controls. Difference between DSLs of median and ulnar nerves, median SNCV and difference between DMLs of median and ulnar nerves were having highest sensitivity and specificity while median FWML and difference between FWMLs of median and ulnar nerves was having lowest sensitivity and specificity for diagnosis of CTS. So in conclusion F-wave study is not superior parameter for diagnosis of CTS.

High-performance Förster resonance energy transfer (FRET)-based dye-sensitized solar cells: rational design of quantum dots for wide solar-spectrum utilization.

PubMed

Lee, Eunwoo; Kim, Chanhoi; Jang, Jyongsik

2013-07-29

High-performance Förster resonance energy transfer (FRET)-based dye-sensitized solar cells (DSSCs) have been successfully fabricated through the optimized design of a CdSe/CdS quantum-dot (QD) donor and a dye acceptor. This simple approach enables quantum dots and dyes to simultaneously utilize the wide solar spectrum, thereby resulting in high conversion efficiency over a wide wavelength range. In addition, major parameters that affect the FRET interaction between donor and acceptor have been investigated including the fluorescent emission spectrum of QD, and the content of deposited QDs into the TiO2 matrix. By judicious control of these parameters, the FRET interaction can be readily optimized for high photovoltaic performance. In addition, the as-synthesized water-soluble quantum dots were highly dispersed in a nanoporous TiO2 matrix, thereby resulting in excellent contact between donors and acceptors. Importantly, high-performance FRET-based DSSCs can be prepared without any infrared (IR) dye synthetic procedures. This novel strategy offers great potential for applications of dye-sensitized solar cells. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Sensitivity analysis in economic evaluation: an audit of NICE current practice and a review of its use and value in decision-making.

PubMed

Andronis, L; Barton, P; Bryan, S

2009-06-01

To determine how we define good practice in sensitivity analysis in general and probabilistic sensitivity analysis (PSA) in particular, and to what extent it has been adhered to in the independent economic evaluations undertaken for the National Institute for Health and Clinical Excellence (NICE) over recent years; to establish what policy impact sensitivity analysis has in the context of NICE, and policy-makers' views on sensitivity analysis and uncertainty, and what use is made of sensitivity analysis in policy decision-making. Three major electronic databases, MEDLINE, EMBASE and the NHS Economic Evaluation Database, were searched from inception to February 2008. The meaning of 'good practice' in the broad area of sensitivity analysis was explored through a review of the literature. An audit was undertaken of the 15 most recent NICE multiple technology appraisal judgements and their related reports to assess how sensitivity analysis has been undertaken by independent academic teams for NICE. A review of the policy and guidance documents issued by NICE aimed to assess the policy impact of the sensitivity analysis and the PSA in particular. Qualitative interview data from NICE Technology Appraisal Committee members, collected as part of an earlier study, were also analysed to assess the value attached to the sensitivity analysis components of the economic analyses conducted for NICE. All forms of sensitivity analysis, notably both deterministic and probabilistic approaches, have their supporters and their detractors. Practice in relation to univariate sensitivity analysis is highly variable, with considerable lack of clarity in relation to the methods used and the basis of the ranges employed. In relation to PSA, there is a high level of variability in the form of distribution used for similar parameters, and the justification for such choices is rarely given. Virtually all analyses failed to consider correlations within the PSA, and this is an area of concern. Uncertainty is considered explicitly in the process of arriving at a decision by the NICE Technology Appraisal Committee, and a correlation between high levels of uncertainty and negative decisions was indicated. The findings suggest considerable value in deterministic sensitivity analysis. Such analyses serve to highlight which model parameters are critical to driving a decision. Strong support was expressed for PSA, principally because it provides an indication of the parameter uncertainty around the incremental cost-effectiveness ratio. The review and the policy impact assessment focused exclusively on documentary evidence, excluding other sources that might have revealed further insights on this issue. In seeking to address parameter uncertainty, both deterministic and probabilistic sensitivity analyses should be used. It is evident that some cost-effectiveness work, especially around the sensitivity analysis components, represents a challenge in making it accessible to those making decisions. This speaks to the training agenda for those sitting on such decision-making bodies, and to the importance of clear presentation of analyses by the academic community.

Multisite-multivariable sensitivity analysis of distributed watershed models: enhancing the perceptions from computationally frugal methods

USDA-ARS?s Scientific Manuscript database

This paper assesses the impact of different likelihood functions in identifying sensitive parameters of the highly parameterized, spatially distributed Soil and Water Assessment Tool (SWAT) watershed model for multiple variables at multiple sites. The global one-factor-at-a-time (OAT) method of Morr...

Single photon detector with high polarization sensitivity.

PubMed

Guo, Qi; Li, Hao; You, LiXing; Zhang, WeiJun; Zhang, Lu; Wang, Zhen; Xie, XiaoMing; Qi, Ming

2015-04-15

Polarization is one of the key parameters of light. Most optical detectors are intensity detectors that are insensitive to the polarization of light. A superconducting nanowire single photon detector (SNSPD) is naturally sensitive to polarization due to its nanowire structure. Previous studies focused on producing a polarization-insensitive SNSPD. In this study, by adjusting the width and pitch of the nanowire, we systematically investigate the preparation of an SNSPD with high polarization sensitivity. Subsequently, an SNSPD with a system detection efficiency of 12% and a polarization extinction ratio of 22 was successfully prepared.

The impact of standard and hard-coded parameters on the hydrologic fluxes in the Noah-MP land surface model

NASA Astrophysics Data System (ADS)

Thober, S.; Cuntz, M.; Mai, J.; Samaniego, L. E.; Clark, M. P.; Branch, O.; Wulfmeyer, V.; Attinger, S.

2016-12-01

Land surface models incorporate a large number of processes, described by physical, chemical and empirical equations. The agility of the models to react to different meteorological conditions is artificially constrained by having hard-coded parameters in their equations. Here we searched for hard-coded parameters in the computer code of the land surface model Noah with multiple process options (Noah-MP) to assess the model's agility during parameter estimation. We found 139 hard-coded values in all Noah-MP process options in addition to the 71 standard parameters. We performed a Sobol' global sensitivity analysis to variations of the standard and hard-coded parameters. The sensitivities of the hydrologic output fluxes latent heat and total runoff, their component fluxes, as well as photosynthesis and sensible heat were evaluated at twelve catchments of the Eastern United States with very different hydro-meteorological regimes. Noah-MP's output fluxes are sensitive to two thirds of its standard parameters. The most sensitive parameter is, however, a hard-coded value in the formulation of soil surface resistance for evaporation, which proved to be oversensitive in other land surface models as well. Latent heat and total runoff show very similar sensitivities towards standard and hard-coded parameters. They are sensitive to both soil and plant parameters, which means that model calibrations of hydrologic or land surface models should take both soil and plant parameters into account. Sensible and latent heat exhibit almost the same sensitivities so that calibration or sensitivity analysis can be performed with either of the two. Photosynthesis has almost the same sensitivities as transpiration, which are different from the sensitivities of latent heat. Including photosynthesis and latent heat in model calibration might therefore be beneficial. Surface runoff is sensitive to almost all hard-coded snow parameters. These sensitivities get, however, diminished in total runoff. It is thus recommended to include the most sensitive hard-coded model parameters that were exposed in this study when calibrating Noah-MP.

Inverse modeling for seawater intrusion in coastal aquifers: Insights about parameter sensitivities, variances, correlations and estimation procedures derived from the Henry problem

USGS Publications Warehouse

Sanz, E.; Voss, C.I.

2006-01-01

Inverse modeling studies employing data collected from the classic Henry seawater intrusion problem give insight into several important aspects of inverse modeling of seawater intrusion problems and effective measurement strategies for estimation of parameters for seawater intrusion. Despite the simplicity of the Henry problem, it embodies the behavior of a typical seawater intrusion situation in a single aquifer. Data collected from the numerical problem solution are employed without added noise in order to focus on the aspects of inverse modeling strategies dictated by the physics of variable-density flow and solute transport during seawater intrusion. Covariances of model parameters that can be estimated are strongly dependent on the physics. The insights gained from this type of analysis may be directly applied to field problems in the presence of data errors, using standard inverse modeling approaches to deal with uncertainty in data. Covariance analysis of the Henry problem indicates that in order to generally reduce variance of parameter estimates, the ideal places to measure pressure are as far away from the coast as possible, at any depth, and the ideal places to measure concentration are near the bottom of the aquifer between the center of the transition zone and its inland fringe. These observations are located in and near high-sensitivity regions of system parameters, which may be identified in a sensitivity analysis with respect to several parameters. However, both the form of error distribution in the observations and the observation weights impact the spatial sensitivity distributions, and different choices for error distributions or weights can result in significantly different regions of high sensitivity. Thus, in order to design effective sampling networks, the error form and weights must be carefully considered. For the Henry problem, permeability and freshwater inflow can be estimated with low estimation variance from only pressure or only concentration observations. Permeability, freshwater inflow, solute molecular diffusivity, and porosity can be estimated with roughly equivalent confidence using observations of only the logarithm of concentration. Furthermore, covariance analysis allows a logical reduction of the number of estimated parameters for ill-posed inverse seawater intrusion problems. Ill-posed problems may exhibit poor estimation convergence, have a non-unique solution, have multiple minima, or require excessive computational effort, and the condition often occurs when estimating too many or co-dependent parameters. For the Henry problem, such analysis allows selection of the two parameters that control system physics from among all possible system parameters. ?? 2005 Elsevier Ltd. All rights reserved.

A new methodology based on sensitivity analysis to simplify the recalibration of functional-structural plant models in new conditions.

PubMed

Mathieu, Amélie; Vidal, Tiphaine; Jullien, Alexandra; Wu, QiongLi; Chambon, Camille; Bayol, Benoit; Cournède, Paul-Henry

2018-06-19

Functional-structural plant models (FSPMs) describe explicitly the interactions between plants and their environment at organ to plant scale. However, the high level of description of the structure or model mechanisms makes this type of model very complex and hard to calibrate. A two-step methodology to facilitate the calibration process is proposed here. First, a global sensitivity analysis method was applied to the calibration loss function. It provided first-order and total-order sensitivity indexes that allow parameters to be ranked by importance in order to select the most influential ones. Second, the Akaike information criterion (AIC) was used to quantify the model's quality of fit after calibration with different combinations of selected parameters. The model with the lowest AIC gives the best combination of parameters to select. This methodology was validated by calibrating the model on an independent data set (same cultivar, another year) with the parameters selected in the second step. All the parameters were set to their nominal value; only the most influential ones were re-estimated. Sensitivity analysis applied to the calibration loss function is a relevant method to underline the most significant parameters in the estimation process. For the studied winter oilseed rape model, 11 out of 26 estimated parameters were selected. Then, the model could be recalibrated for a different data set by re-estimating only three parameters selected with the model selection method. Fitting only a small number of parameters dramatically increases the efficiency of recalibration, increases the robustness of the model and helps identify the principal sources of variation in varying environmental conditions. This innovative method still needs to be more widely validated but already gives interesting avenues to improve the calibration of FSPMs.

Sensitivity analysis of the parameters of an HIV/AIDS model with condom campaign and antiretroviral therapy

NASA Astrophysics Data System (ADS)

Marsudi, Hidayat, Noor; Wibowo, Ratno Bagus Edy

2017-12-01

In this article, we present a deterministic model for the transmission dynamics of HIV/AIDS in which condom campaign and antiretroviral therapy are both important for the disease management. We calculate the effective reproduction number using the next generation matrix method and investigate the local and global stability of the disease-free equilibrium of the model. Sensitivity analysis of the effective reproduction number with respect to the model parameters were carried out. Our result shows that efficacy rate of condom campaign, transmission rate for contact with the asymptomatic infective, progression rate from the asymptomatic infective to the pre-AIDS infective, transmission rate for contact with the pre-AIDS infective, ARV therapy rate, proportion of the susceptible receiving condom campaign and proportion of the pre-AIDS receiving ARV therapy are highly sensitive parameters that effect the transmission dynamics of HIV/AIDS infection.

Optimized sensitivity of Silicon-on-Insulator (SOI) strip waveguide resonator sensor

PubMed Central

TalebiFard, Sahba; Schmidt, Shon; Shi, Wei; Wu, WenXuan; Jaeger, Nicolas A. F.; Kwok, Ezra; Ratner, Daniel M.; Chrostowski, Lukas

2017-01-01

Evanescent field sensors have shown promise for biological sensing applications. In particular, Silicon-on-Insulator (SOI)-nano-photonic based resonator sensors have many advantages for lab-on-chip diagnostics, including high sensitivity for molecular detection and compatibility with CMOS foundries for high volume manufacturing. We have investigated the optimum design parameters within the fabrication constraints of Multi-Project Wafer (MPW) foundries that result in the highest sensitivity for a resonator sensor. We have demonstrated the optimum waveguide thickness needed to achieve the maximum bulk sensitivity with SOI-based resonator sensors to be 165 nm using the quasi-TM guided mode. The closest thickness offered by MPW foundry services is 150 nm. Therefore, resonators with 150 nm thick silicon waveguides were fabricated resulting in sensitivities as high as 270 nm/RIU, whereas a similar resonator sensor with a 220 nm thick waveguide demonstrated sensitivities of approximately 200 nm/RIU. PMID:28270963

Birth weight, current anthropometric markers, and high sensitivity C-reactive protein in Brazilian school children.

PubMed

Boscaini, Camile; Pellanda, Lucia Campos

2015-01-01

Studies have shown associations of birth weight with increased concentrations of high sensitivity C-reactive protein. This study assessed the relationship between birth weight, anthropometric and metabolic parameters during childhood, and high sensitivity C-reactive protein. A total of 612 Brazilian school children aged 5-13 years were included in the study. High sensitivity C-reactive protein was measured by particle-enhanced immunonephelometry. Nutritional status was assessed by body mass index, waist circumference, and skinfolds. Total cholesterol and fractions, triglycerides, and glucose were measured by enzymatic methods. Insulin sensitivity was determined by the homeostasis model assessment method. Statistical analysis included chi-square test, General Linear Model, and General Linear Model for Gamma Distribution. Body mass index, waist circumference, and skinfolds were directly associated with birth weight (P < 0.001, P = 0.001, and P = 0.015, resp.). Large for gestational age children showed higher high sensitivity C-reactive protein levels (P < 0.001) than small for gestational age. High birth weight is associated with higher levels of high sensitivity C-reactive protein, body mass index, waist circumference, and skinfolds. Large for gestational age altered high sensitivity C-reactive protein and promoted additional risk factor for atherosclerosis in these school children, independent of current nutritional status.

Chicken lines divergently selected for antibody responses to sheep red blood cells show line-specific differences in sensitivity to immunomodulation by diet. Part I: Humoral parameters.

PubMed

Adriaansen-Tennekes, R; de Vries Reilingh, G; Nieuwland, M G B; Parmentier, H K; Savelkoul, H F J

2009-09-01

Individual differences in nutrient sensitivity have been suggested to be related with differences in stress sensitivity. Here we used layer hens divergently selected for high and low specific antibody responses to SRBC (i.e., low line hens and high line hens), reflecting a genetically based differential immune competence. The parental line of these hens was randomly bred as the control line and was used as well. Recently, we showed that these selection lines differ in their stress reactivity; the low line birds show a higher hypothalamic-pituitary-adrenal (HPA) axis reactivity. To examine maternal effects and neonatal nutritional exposure on nutrient sensitivity, we studied 2 subsequent generations. This also created the opportunity to examine egg production in these birds. The 3 lines were fed 2 different nutritionally complete layer feeds for a period of 22 wk in the first generation. The second generation was fed from hatch with the experimental diets. At several time intervals, parameters reflecting humoral immunity were determined such as specific antibody to Newcastle disease and infectious bursal disease vaccines; levels of natural antibodies binding lipopolysaccharide, lipoteichoic acid, and keyhole limpet hemocyanin; and classical and alternative complement activity. The most pronounced dietary-induced effects were found in the low line birds of the first generation: specific antibody titers to Newcastle disease vaccine were significantly elevated by 1 of the 2 diets. In the second generation, significant differences were found in lipoteichoic acid natural antibodies of the control and low line hens. At the end of the observation period of egg parameters, a significant difference in egg weight was found in birds of the high line. Our results suggest that nutritional differences have immunomodulatory effects on innate and adaptive humoral immune parameters in birds with high HPA axis reactivity and affect egg production in birds with low HPA axis reactivity.

Multi-Response Parameter Interval Sensitivity and Optimization for the Composite Tape Winding Process.

PubMed

Deng, Bo; Shi, Yaoyao; Yu, Tao; Kang, Chao; Zhao, Pan

2018-01-31

The composite tape winding process, which utilizes a tape winding machine and prepreg tapes, provides a promising way to improve the quality of composite products. Nevertheless, the process parameters of composite tape winding have crucial effects on the tensile strength and void content, which are closely related to the performances of the winding products. In this article, two different object values of winding products, including mechanical performance (tensile strength) and a physical property (void content), were respectively calculated. Thereafter, the paper presents an integrated methodology by combining multi-parameter relative sensitivity analysis and single-parameter sensitivity analysis to obtain the optimal intervals of the composite tape winding process. First, the global multi-parameter sensitivity analysis method was applied to investigate the sensitivity of each parameter in the tape winding processing. Then, the local single-parameter sensitivity analysis method was employed to calculate the sensitivity of a single parameter within the corresponding range. Finally, the stability and instability ranges of each parameter were distinguished. Meanwhile, the authors optimized the process parameter ranges and provided comprehensive optimized intervals of the winding parameters. The verification test validated that the optimized intervals of the process parameters were reliable and stable for winding products manufacturing.

Multi-Response Parameter Interval Sensitivity and Optimization for the Composite Tape Winding Process

PubMed Central

Yu, Tao; Kang, Chao; Zhao, Pan

2018-01-01

The composite tape winding process, which utilizes a tape winding machine and prepreg tapes, provides a promising way to improve the quality of composite products. Nevertheless, the process parameters of composite tape winding have crucial effects on the tensile strength and void content, which are closely related to the performances of the winding products. In this article, two different object values of winding products, including mechanical performance (tensile strength) and a physical property (void content), were respectively calculated. Thereafter, the paper presents an integrated methodology by combining multi-parameter relative sensitivity analysis and single-parameter sensitivity analysis to obtain the optimal intervals of the composite tape winding process. First, the global multi-parameter sensitivity analysis method was applied to investigate the sensitivity of each parameter in the tape winding processing. Then, the local single-parameter sensitivity analysis method was employed to calculate the sensitivity of a single parameter within the corresponding range. Finally, the stability and instability ranges of each parameter were distinguished. Meanwhile, the authors optimized the process parameter ranges and provided comprehensive optimized intervals of the winding parameters. The verification test validated that the optimized intervals of the process parameters were reliable and stable for winding products manufacturing. PMID:29385048

Sensitivity of land surface modeling to parameters: An uncertainty quantification method applied to the Community Land Model

NASA Astrophysics Data System (ADS)

Ricciuto, D. M.; Mei, R.; Mao, J.; Hoffman, F. M.; Kumar, J.

2015-12-01

Uncertainties in land parameters could have important impacts on simulated water and energy fluxes and land surface states, which will consequently affect atmospheric and biogeochemical processes. Therefore, quantification of such parameter uncertainties using a land surface model is the first step towards better understanding of predictive uncertainty in Earth system models. In this study, we applied a random-sampling, high-dimensional model representation (RS-HDMR) method to analyze the sensitivity of simulated photosynthesis, surface energy fluxes and surface hydrological components to selected land parameters in version 4.5 of the Community Land Model (CLM4.5). Because of the large computational expense of conducting ensembles of global gridded model simulations, we used the results of a previous cluster analysis to select one thousand representative land grid cells for simulation. Plant functional type (PFT)-specific uniform prior ranges for land parameters were determined using expert opinion and literature survey, and samples were generated with a quasi-Monte Carlo approach-Sobol sequence. Preliminary analysis of 1024 simulations suggested that four PFT-dependent parameters (including slope of the conductance-photosynthesis relationship, specific leaf area at canopy top, leaf C:N ratio and fraction of leaf N in RuBisco) are the dominant sensitive parameters for photosynthesis, surface energy and water fluxes across most PFTs, but with varying importance rankings. On the other hand, for surface ans sub-surface runoff, PFT-independent parameters, such as the depth-dependent decay factors for runoff, play more important roles than the previous four PFT-dependent parameters. Further analysis by conditioning the results on different seasons and years are being conducted to provide guidance on how climate variability and change might affect such sensitivity. This is the first step toward coupled simulations including biogeochemical processes, atmospheric processes or both to determine the full range of sensitivity of Earth system modeling to land-surface parameters. This can facilitate sampling strategies in measurement campaigns targeted at reduction of climate modeling uncertainties and can also provide guidance on land parameter calibration for simulation optimization.

Sensitivity analysis of simulated SOA loadings using a variance-based statistical approach: SENSITIVITY ANALYSIS OF SOA

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

Shrivastava, Manish; Zhao, Chun; Easter, Richard C.

We investigate the sensitivity of secondary organic aerosol (SOA) loadings simulated by a regional chemical transport model to 7 selected tunable model parameters: 4 involving emissions of anthropogenic and biogenic volatile organic compounds, anthropogenic semi-volatile and intermediate volatility organics (SIVOCs), and NOx, 2 involving dry deposition of SOA precursor gases, and one involving particle-phase transformation of SOA to low volatility. We adopt a quasi-Monte Carlo sampling approach to effectively sample the high-dimensional parameter space, and perform a 250 member ensemble of simulations using a regional model, accounting for some of the latest advances in SOA treatments based on our recentmore » work. We then conduct a variance-based sensitivity analysis using the generalized linear model method to study the responses of simulated SOA loadings to the tunable parameters. Analysis of SOA variance from all 250 simulations shows that the volatility transformation parameter, which controls whether particle-phase transformation of SOA from semi-volatile SOA to non-volatile is on or off, is the dominant contributor to variance of simulated surface-level daytime SOA (65% domain average contribution). We also split the simulations into 2 subsets of 125 each, depending on whether the volatility transformation is turned on/off. For each subset, the SOA variances are dominated by the parameters involving biogenic VOC and anthropogenic SIVOC emissions. Furthermore, biogenic VOC emissions have a larger contribution to SOA variance when the SOA transformation to non-volatile is on, while anthropogenic SIVOC emissions have a larger contribution when the transformation is off. NOx contributes less than 4.3% to SOA variance, and this low contribution is mainly attributed to dominance of intermediate to high NOx conditions throughout the simulated domain. The two parameters related to dry deposition of SOA precursor gases also have very low contributions to SOA variance. This study highlights the large sensitivity of SOA loadings to the particle-phase transformation of SOA volatility, which is neglected in most previous models.« less

Effect of high-fructose and high-fat diets on pulmonary sensitivity, motor activity, and body composition of brown Norway rats exposed to ozone

EPA Pesticide Factsheets

pulmonary parameters, BALF biomarkers, body composition, motor activity data collected from rats exposed to ozone after high fructose or high fat diets.This dataset is associated with the following publication:Gordon , C., P. Phillips , A. Johnstone , T. Beasley , A. Ledbetter , M. Schladweiler , S. Snow, and U. Kodavanti. Effect of High Fructose and High Fat Diets on Pulmonary Sensitivity, Motor Activity, and Body Composition of Brown Norway Rats Exposed to Ozone. INHALATION TOXICOLOGY. Taylor & Francis, Inc., Philadelphia, PA, USA, 28(5): 203-15, (2016).

Application of a sensitivity analysis technique to high-order digital flight control systems

NASA Technical Reports Server (NTRS)

Paduano, James D.; Downing, David R.

1987-01-01

A sensitivity analysis technique for multiloop flight control systems is studied. This technique uses the scaled singular values of the return difference matrix as a measure of the relative stability of a control system. It then uses the gradients of these singular values with respect to system and controller parameters to judge sensitivity. The sensitivity analysis technique is first reviewed; then it is extended to include digital systems, through the derivation of singular-value gradient equations. Gradients with respect to parameters which do not appear explicitly as control-system matrix elements are also derived, so that high-order systems can be studied. A complete review of the integrated technique is given by way of a simple example: the inverted pendulum problem. The technique is then demonstrated on the X-29 control laws. Results show linear models of real systems can be analyzed by this sensitivity technique, if it is applied with care. A computer program called SVA was written to accomplish the singular-value sensitivity analysis techniques. Thus computational methods and considerations form an integral part of many of the discussions. A user's guide to the program is included. The SVA is a fully public domain program, running on the NASA/Dryden Elxsi computer.

Post-Launch Analysis of Swift's Gamma-Ray Burst Detection Sensitivity

NASA Technical Reports Server (NTRS)

Band, David L.

2005-01-01

The dependence of Swift#s detection sensitivity on a burst#s temporal and spectral properties shapes the detected burst population. Using s implified models of the detector hardware and the burst trigger syste m I find that Swift is more sensitive to long, soft bursts than CGRO# s BATSE, a reference mission because of its large burst database. Thu s Swift has increased sensitivity in the parameter space region into which time dilation and spectral redshifting shift high redshift burs ts.

Sensitivity of grounding line dynamics to basal conditions

NASA Astrophysics Data System (ADS)

Gagliardini, O.; Brondex, J.; Chauveau, G.; Gillet-chaulet, F.; Durand, G.

2017-12-01

In the context of a warming climate, the dynamical contribution of Antarctica to future sea level rise is still tainted by high uncertainties. Among the processes entering these uncertainties is the link between basal hydrology, friction and grounding line dynamics. Recent works have shown how sensitive is the response of the grounding line retreat to the choice of the form of the friction law. Indeed, starting from the same initial state, grounding line retreat rates can range over almost two orders of magnitude depending on the friction law formulation.Here, we use a phenomenological law that depends on the water pressure and allows a continuous transition from a Weertman-type friction at low water pressure to a Coulomb-type friction at high water pressure. This friction law depends on two main parameters that control the Weertman and Coulomb regimes. The range of values for these two parameters is only weakly physically constrained, and it can be shown that, for a given basal shear stress, different couples of parameters can conduct to the same sliding velocity. In addition, we show that close to the grounding line where basal water pressure is high, determining these two parameters might conduct to an ill-posed inverse problem with no solution.The aim of this presentation is to discuss a methodology to guide the choice of the two friction parameters and explore the sensitivity of the grounding line dynamics to this initial choice. We present results obtained both on a synthetic configuration used by the Marine Ice Sheet Model Intercomparison exercise and for the Amundsen sea sector using the experiments proposed by InitMIP-Antarctica, the first exercise in a series of ISMIP6 ice-sheet model intercomparison activities.

Sensitivity Testing of the NSTAR Ion Thruster

NASA Technical Reports Server (NTRS)

Sengupta, Anita; Anderson, John; Brophy, John

2007-01-01

During the Extended Life Test of the DS1 flight spare ion thruster, the engine was subjected to sensitvity testing in order to characterize the macroscopic dependence of discharge chamber sensitivity to a +\\-3% vatiation in main flow, cathode flow and beam current, and to +\\5% variation in beam and accelerator voltage, was determined for the minimum- (THO), half- (TH8) and full power (TH15) throttle levels. For each power level investigared, 16 high/low operating conditions were chosen to vary the flows, beam current, and grid voltages in in a matrix that mapped out the entire parameter space. The matrix of data generated was used to determine the partial derivative or senitivity of the dependent parameters--discharge voltage, discharge current, discharge loss, double-to-single-ion current ratio, and neutralizer-keeper voltage--to the variation in the independent parameters--main flow, cathode flow, beam current, and beam voltage. The sensititivities of each dependent parameter with respect to each independent parameter were determined using a least-square fit routine. Variation in these sensitivities with thruster runtime was recorded over the duration of the ELT, to detemine if discharge performance changed with thruster wear. Several key findings have been ascertained from the sensitivity testing. Discharge operation is most sensitve to changes in cathode flow and to a lesser degree main flow. The data also confirms that for the NSTAR configuration plasma production is limited by primary electron input due to the fixed neutral population. Key sensitivities along with their change with thruster wear (operating time) will be presented. In addition double ion content measurements with an ExB probe will also be presented to illustrate beam ion production and content sensitivity to the discharge chamber operating parameteres.

Assessing the applicability of WRF optimal parameters under the different precipitation simulations in the Greater Beijing Area

NASA Astrophysics Data System (ADS)

Di, Zhenhua; Duan, Qingyun; Wang, Chen; Ye, Aizhong; Miao, Chiyuan; Gong, Wei

2018-03-01

Forecasting skills of the complex weather and climate models have been improved by tuning the sensitive parameters that exert the greatest impact on simulated results based on more effective optimization methods. However, whether the optimal parameter values are still work when the model simulation conditions vary, which is a scientific problem deserving of study. In this study, a highly-effective optimization method, adaptive surrogate model-based optimization (ASMO), was firstly used to tune nine sensitive parameters from four physical parameterization schemes of the Weather Research and Forecasting (WRF) model to obtain better summer precipitation forecasting over the Greater Beijing Area in China. Then, to assess the applicability of the optimal parameter values, simulation results from the WRF model with default and optimal parameter values were compared across precipitation events, boundary conditions, spatial scales, and physical processes in the Greater Beijing Area. The summer precipitation events from 6 years were used to calibrate and evaluate the optimal parameter values of WRF model. Three boundary data and two spatial resolutions were adopted to evaluate the superiority of the calibrated optimal parameters to default parameters under the WRF simulations with different boundary conditions and spatial resolutions, respectively. Physical interpretations of the optimal parameters indicating how to improve precipitation simulation results were also examined. All the results showed that the optimal parameters obtained by ASMO are superior to the default parameters for WRF simulations for predicting summer precipitation in the Greater Beijing Area because the optimal parameters are not constrained by specific precipitation events, boundary conditions, and spatial resolutions. The optimal values of the nine parameters were determined from 127 parameter samples using the ASMO method, which showed that the ASMO method is very highly-efficient for optimizing WRF model parameters.

Spatial variability in sensitivity of reference crop ET to accuracy of climate data in the Texas High Plains

USDA-ARS?s Scientific Manuscript database

A detailed sensitivity analysis was conducted to determine the relative effects of measurement errors in climate data input parameters on the accuracy of calculated reference crop evapotranspiration (ET) using the ASCE-EWRI Standardized Reference ET Equation. Data for the period of 1995 to 2008, fro...

Sensitivity of echo enabled harmonic generation to sinusoidal electron beam energy structure

DOE PAGES

Hemsing, E.; Garcia, B.; Huang, Z.; ...

2017-06-19

Here, we analytically examine the bunching factor spectrum of a relativistic electron beam with sinusoidal energy structure that then undergoes an echo-enabled harmonic generation (EEHG) transformation to produce high harmonics. The performance is found to be described primarily by a simple scaling parameter. The dependence of the bunching amplitude on fluctuations of critical parameters is derived analytically, and compared with simulations. Where applicable, EEHG is also compared with high gain harmonic generation (HGHG) and we find that EEHG is generally less sensitive to several types of energy structure. In the presence of intermediate frequency modulations like those produced by themore » microbunching instability, EEHG has a substantially narrower intrinsic bunching pedestal.« less

Rapid assessment of antimicrobial resistance prevalence using a Lot Quality Assurance sampling approach.

PubMed

van Leth, Frank; den Heijer, Casper; Beerepoot, Mariëlle; Stobberingh, Ellen; Geerlings, Suzanne; Schultsz, Constance

2017-04-01

Increasing antimicrobial resistance (AMR) requires rapid surveillance tools, such as Lot Quality Assurance Sampling (LQAS). LQAS classifies AMR as high or low based on set parameters. We compared classifications with the underlying true AMR prevalence using data on 1335 Escherichia coli isolates from surveys of community-acquired urinary tract infection in women, by assessing operating curves, sensitivity and specificity. Sensitivity and specificity of any set of LQAS parameters was above 99% and between 79 and 90%, respectively. Operating curves showed high concordance of the LQAS classification with true AMR prevalence estimates. LQAS-based AMR surveillance is a feasible approach that provides timely and locally relevant estimates, and the necessary information to formulate and evaluate guidelines for empirical treatment.

Global Sensitivity of Simulated Water Balance Indicators Under Future Climate Change in the Colorado Basin

NASA Astrophysics Data System (ADS)

Bennett, Katrina E.; Urrego Blanco, Jorge R.; Jonko, Alexandra; Bohn, Theodore J.; Atchley, Adam L.; Urban, Nathan M.; Middleton, Richard S.

2018-01-01

The Colorado River Basin is a fundamentally important river for society, ecology, and energy in the United States. Streamflow estimates are often provided using modeling tools which rely on uncertain parameters; sensitivity analysis can help determine which parameters impact model results. Despite the fact that simulated flows respond to changing climate and vegetation in the basin, parameter sensitivity of the simulations under climate change has rarely been considered. In this study, we conduct a global sensitivity analysis to relate changes in runoff, evapotranspiration, snow water equivalent, and soil moisture to model parameters in the Variable Infiltration Capacity (VIC) hydrologic model. We combine global sensitivity analysis with a space-filling Latin Hypercube Sampling of the model parameter space and statistical emulation of the VIC model to examine sensitivities to uncertainties in 46 model parameters following a variance-based approach. We find that snow-dominated regions are much more sensitive to uncertainties in VIC parameters. Although baseflow and runoff changes respond to parameters used in previous sensitivity studies, we discover new key parameter sensitivities. For instance, changes in runoff and evapotranspiration are sensitive to albedo, while changes in snow water equivalent are sensitive to canopy fraction and Leaf Area Index (LAI) in the VIC model. It is critical for improved modeling to narrow uncertainty in these parameters through improved observations and field studies. This is important because LAI and albedo are anticipated to change under future climate and narrowing uncertainty is paramount to advance our application of models such as VIC for water resource management.

The Relationship of Mean Platelet Volume/Platelet Distribution Width and Duodenal Ulcer Perforation.

PubMed

Fan, Zhe; Zhuang, Chengjun

2017-03-01

Duodenal ulcer perforation (DUP) is a severe acute abdominal disease. Mean platelet volume (MPV) and platelet distribution width (PDW) are two platelet parameters, participating in many inflammatory processes. This study aims to investigate the relation of MPV/PDW and DUP. A total of 165 patients were studied retrospectively, including 21 females and 144 males. The study included two groups: 87 normal patients (control group) and 78 duodenal ulcer perforation patients (DUP group). Routine blood parameters were collected for analysis including white blood cell count (WBC), neutrophil ratio (NR), platelet count (PLT), MPV and PDW. Receiver operating curve (ROC) analysis was applied to evaluate the parameters' sensitivity. No significant differences were observed between the control group and DUP group in age and gender. WBC, NR and PDW were significantly increased in the DUP group ( P <0.001, respectively); PLT and MPV were significantly decreased in the DUP group ( P <0.001, respectively) compared to controls. MPV had the high sensitivity. Our results suggested a potential association between MPV/PDW and disease activity in DUP patients, and high sensitivity of MPV. © 2017 by the Association of Clinical Scientists, Inc.

Towards simplification of hydrologic modeling: Identification of dominant processes

USGS Publications Warehouse

Markstrom, Steven; Hay, Lauren E.; Clark, Martyn P.

2016-01-01

The Precipitation–Runoff Modeling System (PRMS), a distributed-parameter hydrologic model, has been applied to the conterminous US (CONUS). Parameter sensitivity analysis was used to identify: (1) the sensitive input parameters and (2) particular model output variables that could be associated with the dominant hydrologic process(es). Sensitivity values of 35 PRMS calibration parameters were computed using the Fourier amplitude sensitivity test procedure on 110 000 independent hydrologically based spatial modeling units covering the CONUS and then summarized to process (snowmelt, surface runoff, infiltration, soil moisture, evapotranspiration, interflow, baseflow, and runoff) and model performance statistic (mean, coefficient of variation, and autoregressive lag 1). Identified parameters and processes provide insight into model performance at the location of each unit and allow the modeler to identify the most dominant process on the basis of which processes are associated with the most sensitive parameters. The results of this study indicate that: (1) the choice of performance statistic and output variables has a strong influence on parameter sensitivity, (2) the apparent model complexity to the modeler can be reduced by focusing on those processes that are associated with sensitive parameters and disregarding those that are not, (3) different processes require different numbers of parameters for simulation, and (4) some sensitive parameters influence only one hydrologic process, while others may influence many

Performance evaluation of spectral vegetation indices using a statistical sensitivity function

USGS Publications Warehouse

Ji, Lei; Peters, Albert J.

2007-01-01

A great number of spectral vegetation indices (VIs) have been developed to estimate biophysical parameters of vegetation. Traditional techniques for evaluating the performance of VIs are regression-based statistics, such as the coefficient of determination and root mean square error. These statistics, however, are not capable of quantifying the detailed relationship between VIs and biophysical parameters because the sensitivity of a VI is usually a function of the biophysical parameter instead of a constant. To better quantify this relationship, we developed a “sensitivity function” for measuring the sensitivity of a VI to biophysical parameters. The sensitivity function is defined as the first derivative of the regression function, divided by the standard error of the dependent variable prediction. The function elucidates the change in sensitivity over the range of the biophysical parameter. The Student's t- or z-statistic can be used to test the significance of VI sensitivity. Additionally, we developed a “relative sensitivity function” that compares the sensitivities of two VIs when the biophysical parameters are unavailable.

Parameter screening: the use of a dummy parameter to identify non-influential parameters in a global sensitivity analysis

NASA Astrophysics Data System (ADS)

Khorashadi Zadeh, Farkhondeh; Nossent, Jiri; van Griensven, Ann; Bauwens, Willy

2017-04-01

Parameter estimation is a major concern in hydrological modeling, which may limit the use of complex simulators with a large number of parameters. To support the selection of parameters to include in or exclude from the calibration process, Global Sensitivity Analysis (GSA) is widely applied in modeling practices. Based on the results of GSA, the influential and the non-influential parameters are identified (i.e. parameters screening). Nevertheless, the choice of the screening threshold below which parameters are considered non-influential is a critical issue, which has recently received more attention in GSA literature. In theory, the sensitivity index of a non-influential parameter has a value of zero. However, since numerical approximations, rather than analytical solutions, are utilized in GSA methods to calculate the sensitivity indices, small but non-zero indices may be obtained for the indices of non-influential parameters. In order to assess the threshold that identifies non-influential parameters in GSA methods, we propose to calculate the sensitivity index of a "dummy parameter". This dummy parameter has no influence on the model output, but will have a non-zero sensitivity index, representing the error due to the numerical approximation. Hence, the parameters whose indices are above the sensitivity index of the dummy parameter can be classified as influential, whereas the parameters whose indices are below this index are within the range of the numerical error and should be considered as non-influential. To demonstrated the effectiveness of the proposed "dummy parameter approach", 26 parameters of a Soil and Water Assessment Tool (SWAT) model are selected to be analyzed and screened, using the variance-based Sobol' and moment-independent PAWN methods. The sensitivity index of the dummy parameter is calculated from sampled data, without changing the model equations. Moreover, the calculation does not even require additional model evaluations for the Sobol' method. A formal statistical test validates these parameter screening results. Based on the dummy parameter screening, 11 model parameters are identified as influential. Therefore, it can be denoted that the "dummy parameter approach" can facilitate the parameter screening process and provide guidance for GSA users to define a screening-threshold, with only limited additional resources. Key words: Parameter screening, Global sensitivity analysis, Dummy parameter, Variance-based method, Moment-independent method

Ensemble Solar Forecasting Statistical Quantification and Sensitivity Analysis: Preprint

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

Cheung, WanYin; Zhang, Jie; Florita, Anthony

2015-12-08

Uncertainties associated with solar forecasts present challenges to maintain grid reliability, especially at high solar penetrations. This study aims to quantify the errors associated with the day-ahead solar forecast parameters and the theoretical solar power output for a 51-kW solar power plant in a utility area in the state of Vermont, U.S. Forecasts were generated by three numerical weather prediction (NWP) models, including the Rapid Refresh, the High Resolution Rapid Refresh, and the North American Model, and a machine-learning ensemble model. A photovoltaic (PV) performance model was adopted to calculate theoretical solar power generation using the forecast parameters (e.g., irradiance,more » cell temperature, and wind speed). Errors of the power outputs were quantified using statistical moments and a suite of metrics, such as the normalized root mean squared error (NRMSE). In addition, the PV model's sensitivity to different forecast parameters was quantified and analyzed. Results showed that the ensemble model yielded forecasts in all parameters with the smallest NRMSE. The NRMSE of solar irradiance forecasts of the ensemble NWP model was reduced by 28.10% compared to the best of the three NWP models. Further, the sensitivity analysis indicated that the errors of the forecasted cell temperature attributed only approximately 0.12% to the NRMSE of the power output as opposed to 7.44% from the forecasted solar irradiance.« less

A surrogate-based sensitivity quantification and Bayesian inversion of a regional groundwater flow model

NASA Astrophysics Data System (ADS)

Chen, Mingjie; Izady, Azizallah; Abdalla, Osman A.; Amerjeed, Mansoor

2018-02-01

Bayesian inference using Markov Chain Monte Carlo (MCMC) provides an explicit framework for stochastic calibration of hydrogeologic models accounting for uncertainties; however, the MCMC sampling entails a large number of model calls, and could easily become computationally unwieldy if the high-fidelity hydrogeologic model simulation is time consuming. This study proposes a surrogate-based Bayesian framework to address this notorious issue, and illustrates the methodology by inverse modeling a regional MODFLOW model. The high-fidelity groundwater model is approximated by a fast statistical model using Bagging Multivariate Adaptive Regression Spline (BMARS) algorithm, and hence the MCMC sampling can be efficiently performed. In this study, the MODFLOW model is developed to simulate the groundwater flow in an arid region of Oman consisting of mountain-coast aquifers, and used to run representative simulations to generate training dataset for BMARS model construction. A BMARS-based Sobol' method is also employed to efficiently calculate input parameter sensitivities, which are used to evaluate and rank their importance for the groundwater flow model system. According to sensitivity analysis, insensitive parameters are screened out of Bayesian inversion of the MODFLOW model, further saving computing efforts. The posterior probability distribution of input parameters is efficiently inferred from the prescribed prior distribution using observed head data, demonstrating that the presented BMARS-based Bayesian framework is an efficient tool to reduce parameter uncertainties of a groundwater system.

Verification of the test stand for microbolometer camera in accredited laboratory

NASA Astrophysics Data System (ADS)

Krupiński, Michal; Bareła, Jaroslaw; Chmielewski, Krzysztof; Kastek, Mariusz

2017-10-01

Microbolometer belongs to the group of thermal detectors and consist of temperature sensitive resistor which is exposed to measured radiation flux. Bolometer array employs a pixel structure prepared in silicon technology. The detecting area is defined by a size of thin membrane, usually made of amorphous silicon (a-Si) or vanadium oxide (VOx). FPAs are made of a multitude of detector elements (for example 384 × 288 ), where each individual detector has different sensitivity and offset due to detector-to-detector spread in the FPA fabrication process, and additionally can change with sensor operating temperature, biasing voltage variation or temperature of the observed scene. The difference in sensitivity and offset among detectors (which is called non-uniformity) additionally with its high sensitivity, produces fixed pattern noise (FPN) on produced image. Fixed pattern noise degrades parameters of infrared cameras like sensitivity or NETD. Additionally it degrades image quality, radiometric accuracy and temperature resolution. In order to objectively compare the two infrared cameras ones must measure and compare their parameters on a laboratory test stand. One of the basic parameters for the evaluation of a designed camera is NETD. In order to examine the NETD, parameters such as sensitivity and pixels noise must be measured. To do so, ones should register the output signal from the camera in response to the radiation of black bodies at two different temperatures. The article presets an application and measuring stand for determining the parameters of microbolometers camera. Prepared measurements were compared with the result of the measurements in the Institute of Optoelectronics, MUT on a METS test stand by CI SYSTEM. This test stand consists of IR collimator, IR standard source, rotating wheel with test patterns, a computer with a video grabber card and specialized software. The parameters of thermals cameras were measure according to norms and method described in literature.

A geostatistics-informed hierarchical sensitivity analysis method for complex groundwater flow and transport modeling

NASA Astrophysics Data System (ADS)

Dai, Heng; Chen, Xingyuan; Ye, Ming; Song, Xuehang; Zachara, John M.

2017-05-01

Sensitivity analysis is an important tool for development and improvement of mathematical models, especially for complex systems with a high dimension of spatially correlated parameters. Variance-based global sensitivity analysis has gained popularity because it can quantify the relative contribution of uncertainty from different sources. However, its computational cost increases dramatically with the complexity of the considered model and the dimension of model parameters. In this study, we developed a new sensitivity analysis method that integrates the concept of variance-based method with a hierarchical uncertainty quantification framework. Different uncertain inputs are grouped and organized into a multilayer framework based on their characteristics and dependency relationships to reduce the dimensionality of the sensitivity analysis. A set of new sensitivity indices are defined for the grouped inputs using the variance decomposition method. Using this methodology, we identified the most important uncertainty source for a dynamic groundwater flow and solute transport model at the Department of Energy (DOE) Hanford site. The results indicate that boundary conditions and permeability field contribute the most uncertainty to the simulated head field and tracer plume, respectively. The relative contribution from each source varied spatially and temporally. By using a geostatistical approach to reduce the number of realizations needed for the sensitivity analysis, the computational cost of implementing the developed method was reduced to a practically manageable level. The developed sensitivity analysis method is generally applicable to a wide range of hydrologic and environmental problems that deal with high-dimensional spatially distributed input variables.

A Geostatistics-Informed Hierarchical Sensitivity Analysis Method for Complex Groundwater Flow and Transport Modeling

NASA Astrophysics Data System (ADS)

Dai, H.; Chen, X.; Ye, M.; Song, X.; Zachara, J. M.

2017-12-01

Sensitivity analysis is an important tool for development and improvement of mathematical models, especially for complex systems with a high dimension of spatially correlated parameters. Variance-based global sensitivity analysis has gained popularity because it can quantify the relative contribution of uncertainty from different sources. However, its computational cost increases dramatically with the complexity of the considered model and the dimension of model parameters. In this study we developed a new sensitivity analysis method that integrates the concept of variance-based method with a hierarchical uncertainty quantification framework. Different uncertain inputs are grouped and organized into a multi-layer framework based on their characteristics and dependency relationships to reduce the dimensionality of the sensitivity analysis. A set of new sensitivity indices are defined for the grouped inputs using the variance decomposition method. Using this methodology, we identified the most important uncertainty source for a dynamic groundwater flow and solute transport model at the Department of Energy (DOE) Hanford site. The results indicate that boundary conditions and permeability field contribute the most uncertainty to the simulated head field and tracer plume, respectively. The relative contribution from each source varied spatially and temporally. By using a geostatistical approach to reduce the number of realizations needed for the sensitivity analysis, the computational cost of implementing the developed method was reduced to a practically manageable level. The developed sensitivity analysis method is generally applicable to a wide range of hydrologic and environmental problems that deal with high-dimensional spatially-distributed input variables.

The impact of standard and hard-coded parameters on the hydrologic fluxes in the Noah-MP land surface model

NASA Astrophysics Data System (ADS)

Cuntz, Matthias; Mai, Juliane; Samaniego, Luis; Clark, Martyn; Wulfmeyer, Volker; Branch, Oliver; Attinger, Sabine; Thober, Stephan

2016-09-01

Land surface models incorporate a large number of process descriptions, containing a multitude of parameters. These parameters are typically read from tabulated input files. Some of these parameters might be fixed numbers in the computer code though, which hinder model agility during calibration. Here we identified 139 hard-coded parameters in the model code of the Noah land surface model with multiple process options (Noah-MP). We performed a Sobol' global sensitivity analysis of Noah-MP for a specific set of process options, which includes 42 out of the 71 standard parameters and 75 out of the 139 hard-coded parameters. The sensitivities of the hydrologic output fluxes latent heat and total runoff as well as their component fluxes were evaluated at 12 catchments within the United States with very different hydrometeorological regimes. Noah-MP's hydrologic output fluxes are sensitive to two thirds of its applicable standard parameters (i.e., Sobol' indexes above 1%). The most sensitive parameter is, however, a hard-coded value in the formulation of soil surface resistance for direct evaporation, which proved to be oversensitive in other land surface models as well. Surface runoff is sensitive to almost all hard-coded parameters of the snow processes and the meteorological inputs. These parameter sensitivities diminish in total runoff. Assessing these parameters in model calibration would require detailed snow observations or the calculation of hydrologic signatures of the runoff data. Latent heat and total runoff exhibit very similar sensitivities because of their tight coupling via the water balance. A calibration of Noah-MP against either of these fluxes should therefore give comparable results. Moreover, these fluxes are sensitive to both plant and soil parameters. Calibrating, for example, only soil parameters hence limit the ability to derive realistic model parameters. It is thus recommended to include the most sensitive hard-coded model parameters that were exposed in this study when calibrating Noah-MP.

Influence of speckle image reconstruction on photometric precision for large solar telescopes

NASA Astrophysics Data System (ADS)

Peck, C. L.; Wöger, F.; Marino, J.

2017-11-01

Context. High-resolution observations from large solar telescopes require adaptive optics (AO) systems to overcome image degradation caused by Earth's turbulent atmosphere. AO corrections are, however, only partial. Achieving near-diffraction limited resolution over a large field of view typically requires post-facto image reconstruction techniques to reconstruct the source image. Aims: This study aims to examine the expected photometric precision of amplitude reconstructed solar images calibrated using models for the on-axis speckle transfer functions and input parameters derived from AO control data. We perform a sensitivity analysis of the photometric precision under variations in the model input parameters for high-resolution solar images consistent with four-meter class solar telescopes. Methods: Using simulations of both atmospheric turbulence and partial compensation by an AO system, we computed the speckle transfer function under variations in the input parameters. We then convolved high-resolution numerical simulations of the solar photosphere with the simulated atmospheric transfer function, and subsequently deconvolved them with the model speckle transfer function to obtain a reconstructed image. To compute the resulting photometric precision, we compared the intensity of the original image with the reconstructed image. Results: The analysis demonstrates that high photometric precision can be obtained for speckle amplitude reconstruction using speckle transfer function models combined with AO-derived input parameters. Additionally, it shows that the reconstruction is most sensitive to the input parameter that characterizes the atmospheric distortion, and sub-2% photometric precision is readily obtained when it is well estimated.

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.

Finding the bottom and using it

PubMed Central

Sandoval, Ruben M.; Wang, Exing; Molitoris, Bruce A.

2014-01-01

Maximizing 2-photon parameters used in acquiring images for quantitative intravital microscopy, especially when high sensitivity is required, remains an open area of investigation. Here we present data on correctly setting the black level of the photomultiplier tube amplifier by adjusting the offset to allow for accurate quantitation of low intensity processes. When the black level is set too high some low intensity pixel values become zero and a nonlinear degradation in sensitivity occurs rendering otherwise quantifiable low intensity values virtually undetectable. Initial studies using a series of increasing offsets for a sequence of concentrations of fluorescent albumin in vitro revealed a loss of sensitivity for higher offsets at lower albumin concentrations. A similar decrease in sensitivity, and therefore the ability to correctly determine the glomerular permeability coefficient of albumin, occurred in vivo at higher offset. Finding the offset that yields accurate and linear data are essential for quantitative analysis when high sensitivity is required. PMID:25313346

[Temporal and spatial heterogeneity analysis of optimal value of sensitive parameters in ecological process model: The BIOME-BGC model as an example.

PubMed

Li, Yi Zhe; Zhang, Ting Long; Liu, Qiu Yu; Li, Ying

2018-01-01

The ecological process models are powerful tools for studying terrestrial ecosystem water and carbon cycle at present. However, there are many parameters for these models, and weather the reasonable values of these parameters were taken, have important impact on the models simulation results. In the past, the sensitivity and the optimization of model parameters were analyzed and discussed in many researches. But the temporal and spatial heterogeneity of the optimal parameters is less concerned. In this paper, the BIOME-BGC model was used as an example. In the evergreen broad-leaved forest, deciduous broad-leaved forest and C3 grassland, the sensitive parameters of the model were selected by constructing the sensitivity judgment index with two experimental sites selected under each vegetation type. The objective function was constructed by using the simulated annealing algorithm combined with the flux data to obtain the monthly optimal values of the sensitive parameters at each site. Then we constructed the temporal heterogeneity judgment index, the spatial heterogeneity judgment index and the temporal and spatial heterogeneity judgment index to quantitatively analyze the temporal and spatial heterogeneity of the optimal values of the model sensitive parameters. The results showed that the sensitivity of BIOME-BGC model parameters was different under different vegetation types, but the selected sensitive parameters were mostly consistent. The optimal values of the sensitive parameters of BIOME-BGC model mostly presented time-space heterogeneity to different degrees which varied with vegetation types. The sensitive parameters related to vegetation physiology and ecology had relatively little temporal and spatial heterogeneity while those related to environment and phenology had generally larger temporal and spatial heterogeneity. In addition, the temporal heterogeneity of the optimal values of the model sensitive parameters showed a significant linear correlation with the spatial heterogeneity under the three vegetation types. According to the temporal and spatial heterogeneity of the optimal values, the parameters of the BIOME-BGC model could be classified in order to adopt different parameter strategies in practical application. The conclusion could help to deeply understand the parameters and the optimal values of the ecological process models, and provide a way or reference for obtaining the reasonable values of parameters in models application.

Method-independent, Computationally Frugal Convergence Testing for Sensitivity Analysis Techniques

NASA Astrophysics Data System (ADS)

Mai, Juliane; Tolson, Bryan

2017-04-01

The increasing complexity and runtime of environmental models lead to the current situation that the calibration of all model parameters or the estimation of all of their uncertainty is often computationally infeasible. Hence, techniques to determine the sensitivity of model parameters are used to identify most important parameters or model processes. All subsequent model calibrations or uncertainty estimation procedures focus then only on these subsets of parameters and are hence less computational demanding. While the examination of the convergence of calibration and uncertainty methods is state-of-the-art, the convergence of the sensitivity methods is usually not checked. If any, bootstrapping of the sensitivity results is used to determine the reliability of the estimated indexes. Bootstrapping, however, might as well become computationally expensive in case of large model outputs and a high number of bootstraps. We, therefore, present a Model Variable Augmentation (MVA) approach to check the convergence of sensitivity indexes without performing any additional model run. This technique is method- and model-independent. It can be applied either during the sensitivity analysis (SA) or afterwards. The latter case enables the checking of already processed sensitivity indexes. To demonstrate the method independency of the convergence testing method, we applied it to three widely used, global SA methods: the screening method known as Morris method or Elementary Effects (Morris 1991, Campolongo et al., 2000), the variance-based Sobol' method (Solbol' 1993, Saltelli et al. 2010) and a derivative-based method known as Parameter Importance index (Goehler et al. 2013). The new convergence testing method is first scrutinized using 12 analytical benchmark functions (Cuntz & Mai et al. 2015) where the true indexes of aforementioned three methods are known. This proof of principle shows that the method reliably determines the uncertainty of the SA results when different budgets are used for the SA. Subsequently, we focus on the model-independency by testing the frugal method using the hydrologic model mHM (www.ufz.de/mhm) with about 50 model parameters. The results show that the new frugal method is able to test the convergence and therefore the reliability of SA results in an efficient way. The appealing feature of this new technique is the necessity of no further model evaluation and therefore enables checking of already processed (and published) sensitivity results. This is one step towards reliable and transferable, published sensitivity results.

Macular ganglion cell imaging study: glaucoma diagnostic accuracy of spectral-domain optical coherence tomography.

PubMed

Jeoung, Jin Wook; Choi, Yun Jeong; Park, Ki Ho; Kim, Dong Myung

2013-07-01

We evaluated the diagnostic accuracy of macular ganglion cell-inner plexiform layer (GCIPL) measurements using a high-definition optical coherence tomography (Cirrus HD-OCT) ganglion cell analysis algorithm for detecting early and moderate-to-severe glaucoma. Totals of 119 normal subjects and 306 glaucoma patients (164 patients with early glaucoma and 142 with moderate-to-severe glaucoma) were enrolled from the Macular Ganglion Cell Imaging Study. Macular GCIPL, peripapillary retinal nerve fiber layer (RNFL) thickness, and optic nerve head (ONH) parameters were measured in each subject. Areas under the receiver operating characteristic curves (AUROCs) were calculated and compared. Based on the internal normative database, the sensitivity and specificity for detecting early and moderate-to-severe glaucoma were calculated. There was no statistically significant difference between the AUROCs for the best OCT parameters. For detecting early glaucoma, the sensitivity of the Cirrus GCIPL parameters ranged from 26.8% to 73.2% and that of the Cirrus RNFL parameters ranged from 6.1% to 61.6%. For the early glaucoma group, the best parameter from the GCIPL generally had a higher sensitivity than those of the RNFL and ONH parameters with comparable specificity (P < 0.05, McNemar's test). There were no significant differences between the AUROCs for Cirrus GCIPL, RNFL, and ONH parameters, indicating that these maps have similar diagnostic potentials for glaucoma. The minimum GCIPL showed better glaucoma diagnostic performance than the other parameters at comparable specificities. However, other GCIPL parameters showed performances comparable to those of the RNFL parameters.

Comparison of Two Global Sensitivity Analysis Methods for Hydrologic Modeling over the Columbia River Basin

NASA Astrophysics Data System (ADS)

Hameed, M.; Demirel, M. C.; Moradkhani, H.

2015-12-01

Global Sensitivity Analysis (GSA) approach helps identify the effectiveness of model parameters or inputs and thus provides essential information about the model performance. In this study, the effects of the Sacramento Soil Moisture Accounting (SAC-SMA) model parameters, forcing data, and initial conditions are analysed by using two GSA methods: Sobol' and Fourier Amplitude Sensitivity Test (FAST). The simulations are carried out over five sub-basins within the Columbia River Basin (CRB) for three different periods: one-year, four-year, and seven-year. Four factors are considered and evaluated by using the two sensitivity analysis methods: the simulation length, parameter range, model initial conditions, and the reliability of the global sensitivity analysis methods. The reliability of the sensitivity analysis results is compared based on 1) the agreement between the two sensitivity analysis methods (Sobol' and FAST) in terms of highlighting the same parameters or input as the most influential parameters or input and 2) how the methods are cohered in ranking these sensitive parameters under the same conditions (sub-basins and simulation length). The results show the coherence between the Sobol' and FAST sensitivity analysis methods. Additionally, it is found that FAST method is sufficient to evaluate the main effects of the model parameters and inputs. Another conclusion of this study is that the smaller parameter or initial condition ranges, the more consistency and coherence between the sensitivity analysis methods results.

Gait Implications of Visual Field Damage from Glaucoma.

PubMed

Mihailovic, Aleksandra; Swenor, Bonnielin K; Friedman, David S; West, Sheila K; Gitlin, Laura N; Ramulu, Pradeep Y

2017-06-01

To evaluate fall-relevant gait features in older glaucoma patients. The GAITRite Electronic Walkway was used to define fall-related gait parameters in 239 patients with suspected or manifest glaucoma under normal usual-pace walking conditions and while carrying a cup or tray. Multiple linear regression models assessed the association between gait parameters and integrated visual field (IVF) sensitivity after controlling for age, race, sex, medications, and comorbid illness. Under normal walking conditions, worse IVF sensitivity was associated with a wider base of support (β = 0.60 cm/5 dB IVF sensitivity decrement, 95% confidence interval [CI] = 0.12-1.09, P = 0.016). Worse IVF sensitivity was not associated with slower gait speed, shorter step or stride length, or greater left-right drift under normal walking conditions ( P > 0.05 for all), but was during cup and/or tray carrying conditions ( P < 0.05 for all). Worse IVF sensitivity was positively associated with greater stride-to-stride variability in step length, stride length, and stride velocity ( P < 0.005 for all). Inferior and superior IVF sensitivity demonstrated associations with each of the above gait parameters as well, though these associations were consistently similar to, or weaker than, the associations noted for overall IVF sensitivity. Glaucoma severity was associated with several gait parameters predictive of higher fall risk in prior studies, particularly measures of stride-to-stride variability. Gait may be useful in identifying glaucoma patients at higher risk of falls, and in designing and testing interventions to prevent falls in this high-risk group. These findings could serve to inform the development of the interventions for falls prevention in glaucoma patients.

Physical nature of strain rate sensitivity of metals and alloys at high strain rates

NASA Astrophysics Data System (ADS)

Borodin, E. N.; Gruzdkov, A. A.; Mayer, A. E.; Selyutina, N. S.

2018-04-01

The role of instabilities of plastic flow at plastic deformation of various materials is one of the important cross-disciplinary problems which is equally important in physics, mechanics and material science. The strain rate sensitivities under slow and high strain rate conditions of loading have different physical nature. In the case of low strain rate, the sensitivity arising from the inertness of the defect structures evolution can be expressed by a single parameter characterizing the plasticity mechanism. In our approach, this is the value of the characteristic relaxation time. In the dynamic case, there are additional effects of “high-speed sensitivity” associated with the micro-localization of the plastic flow near the stress concentrators. In the frames of mechanical description, this requires to introduce additional strain rate sensitivity parameters, which is realized in numerous modifications of Johnson–Cook and Zerilli–Armstrong models. The consideration of both these factors is fundamental for an adequate description of the problems of dynamic deformation of highly inhomogeneous metallic materials such as steels and alloys. The measurement of the dispersion of particle velocities on the free surface of a shock-loaded material can be regarded as an experimental expression of the effect of micro-localization. This is also confirmed by our results of numerical simulation of the propagation of shock waves in a two-dimensional formulation and analytical estimations.

Can nudging be used to quantify model sensitivities in precipitation and cloud forcing?

NASA Astrophysics Data System (ADS)

Lin, Guangxing; Wan, Hui; Zhang, Kai; Qian, Yun; Ghan, Steven J.

2016-09-01

Efficient simulation strategies are crucial for the development and evaluation of high-resolution climate models. This paper evaluates simulations with constrained meteorology for the quantification of parametric sensitivities in the Community Atmosphere Model version 5 (CAM5). Two parameters are perturbed as illustrating examples: the convection relaxation time scale (TAU), and the threshold relative humidity for the formation of low-level stratiform clouds (rhminl). Results suggest that the fidelity of the constrained simulations depends on the detailed implementation of nudging and the mechanism through which the perturbed parameter affects precipitation and cloud. The relative computational costs of nudged and free-running simulations are determined by the magnitude of internal variability in the physical quantities of interest, as well as the magnitude of the parameter perturbation. In the case of a strong perturbation in convection, temperature, and/or wind nudging with a 6 h relaxation time scale leads to nonnegligible side effects due to the distorted interactions between resolved dynamics and parameterized convection, while 1 year free-running simulations can satisfactorily capture the annual mean precipitation and cloud forcing sensitivities. In the case of a relatively weak perturbation in the large-scale condensation scheme, results from 1 year free-running simulations are strongly affected by natural noise, while nudging winds effectively reduces the noise, and reasonably reproduces the sensitivities. These results indicate that caution is needed when using nudged simulations to assess precipitation and cloud forcing sensitivities to parameter changes in general circulation models. We also demonstrate that ensembles of short simulations are useful for understanding the evolution of model sensitivities.

Pressure sensitivity analysis of fiber Bragg grating sensors

NASA Astrophysics Data System (ADS)

Mrad, Nezih; Sridharan, Vasant; Kazemi, Alex

2014-09-01

Recent development in fiber optic sensing technology has mainly focused on discrete sensing, particularly, sensing systems with potential multiplexing and multi-parameter capabilities. Bragg grating fiber optic sensors have emerged as the non-disputed champion for multiplexing and simultaneous multi-parameter sensing for emerging high value structural components, advanced processing and manufacturing capabilities and increased critical infrastructure resilience applications. Although the number of potential applications for this sensing technology is large and spans the domains of medicine, manufacturing, aerospace, and public safety; critical issues such as fatigue life, sensitivity, accuracy, embeddability, material/sensor interface integrity, and universal demodulation systems still need to be addressed. The purpose of this paper is to primarily evaluate Commercial-Of-The-Shelf (COTS) Fiber Bragg Grating (FBG) sensors' sensitivity to pressure, often neglected in several applications. The COTS fiber sensitivity to pressure is further evaluated for two types of coatings (Polyimide and Acrylate), and different arrangements (arrayed and single).

The future viability of algae-derived biodiesel under economic and technical uncertainties.

PubMed

Brownbridge, George; Azadi, Pooya; Smallbone, Andrew; Bhave, Amit; Taylor, Benjamin; Kraft, Markus

2014-01-01

This study presents a techno-economic assessment of algae-derived biodiesel under economic and technical uncertainties associated with the development of algal biorefineries. A global sensitivity analysis was performed using a High Dimensional Model Representation (HDMR) method. It was found that, considering reasonable ranges over which each parameter can vary, the sensitivity of the biodiesel production cost to the key input parameters decreases in the following order: algae oil content>algae annual productivity per unit area>plant production capacity>carbon price increase rate. It was also found that the Return on Investment (ROI) is highly sensitive to the algae oil content, and to a lesser extent to the algae annual productivity, crude oil price and price increase rate, plant production capacity, and carbon price increase rate. For a large scale plant (100,000 tonnes of biodiesel per year) the production cost of biodiesel is likely to be £0.8-1.6 per kg. Copyright © 2013 Elsevier Ltd. All rights reserved.

A flexible, interpretable framework for assessing sensitivity to unmeasured confounding.

PubMed

Dorie, Vincent; Harada, Masataka; Carnegie, Nicole Bohme; Hill, Jennifer

2016-09-10

When estimating causal effects, unmeasured confounding and model misspecification are both potential sources of bias. We propose a method to simultaneously address both issues in the form of a semi-parametric sensitivity analysis. In particular, our approach incorporates Bayesian Additive Regression Trees into a two-parameter sensitivity analysis strategy that assesses sensitivity of posterior distributions of treatment effects to choices of sensitivity parameters. This results in an easily interpretable framework for testing for the impact of an unmeasured confounder that also limits the number of modeling assumptions. We evaluate our approach in a large-scale simulation setting and with high blood pressure data taken from the Third National Health and Nutrition Examination Survey. The model is implemented as open-source software, integrated into the treatSens package for the R statistical programming language. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Physiologically based pharmacokinetic modeling of a homologous series of barbiturates in the rat: a sensitivity analysis.

PubMed

Nestorov, I A; Aarons, L J; Rowland, M

1997-08-01

Sensitivity analysis studies the effects of the inherent variability and uncertainty in model parameters on the model outputs and may be a useful tool at all stages of the pharmacokinetic modeling process. The present study examined the sensitivity of a whole-body physiologically based pharmacokinetic (PBPK) model for the distribution kinetics of nine 5-n-alkyl-5-ethyl barbituric acids in arterial blood and 14 tissues (lung, liver, kidney, stomach, pancreas, spleen, gut, muscle, adipose, skin, bone, heart, brain, testes) after i.v. bolus administration to rats. The aims were to obtain new insights into the model used, to rank the model parameters involved according to their impact on the model outputs and to study the changes in the sensitivity induced by the increase in the lipophilicity of the homologues on ascending the series. Two approaches for sensitivity analysis have been implemented. The first, based on the Matrix Perturbation Theory, uses a sensitivity index defined as the normalized sensitivity of the 2-norm of the model compartmental matrix to perturbations in its entries. The second approach uses the traditional definition of the normalized sensitivity function as the relative change in a model state (a tissue concentration) corresponding to a relative change in a model parameter. Autosensitivity has been defined as sensitivity of a state to any of its parameters; cross-sensitivity as the sensitivity of a state to any other states' parameters. Using the two approaches, the sensitivity of representative tissue concentrations (lung, liver, kidney, stomach, gut, adipose, heart, and brain) to the following model parameters: tissue-to-unbound plasma partition coefficients, tissue blood flows, unbound renal and intrinsic hepatic clearance, permeability surface area product of the brain, have been analyzed. Both the tissues and the parameters were ranked according to their sensitivity and impact. The following general conclusions were drawn: (i) the overall sensitivity of the system to all parameters involved is small due to the weak connectivity of the system structure; (ii) the time course of both the auto- and cross-sensitivity functions for all tissues depends on the dynamics of the tissues themselves, e.g., the higher the perfusion of a tissue, the higher are both its cross-sensitivity to other tissues' parameters and the cross-sensitivities of other tissues to its parameters; and (iii) with a few exceptions, there is not a marked influence of the lipophilicity of the homologues on either the pattern or the values of the sensitivity functions. The estimates of the sensitivity and the subsequent tissue and parameter rankings may be extended to other drugs, sharing the same common structure of the whole body PBPK model, and having similar model parameters. Results show also that the computationally simple Matrix Perturbation Analysis should be used only when an initial idea about the sensitivity of a system is required. If comprehensive information regarding the sensitivity is needed, the numerically expensive Direct Sensitivity Analysis should be used.

Progress Towards High-Sensitivity Arrays of Detectors of Sub-mm Radiation Using Superconducting Tunnel Junctions with Integrated Radio Frequency Single-Electron Transistors

NASA Technical Reports Server (NTRS)

Stevenson, T. R.; Hsieh, W.-T.; Li, M. J.; Prober, D. E.; Rhee, K. W.; Schoelkopf, R. J.; Stahle, C. M.; Teufel, J.; Wollack, E. J.

2004-01-01

For high resolution imaging and spectroscopy in the FIR and submillimeter, space observatories will demand sensitive, fast, compact, low-power detector arrays with 104 pixels and sensitivity less than 10(exp -20) W/Hz(sup 0.5). Antenna-coupled superconducting tunnel junctions with integrated rf single-electron transistor readout amplifiers have the potential for achieving this high level of sensitivity, and can take advantage of an rf multiplexing technique. The device consists of an antenna to couple radiation into a small superconducting volume and cause quasiparticle excitations, and a single-electron transistor to measure current through junctions contacting the absorber. We describe optimization of device parameters, and results on fabrication techniques for producing devices with high yield for detector arrays. We also present modeling of expected saturation power levels, antenna coupling, and rf multiplexing schemes.

Linear-quadratic-Gaussian synthesis with reduced parameter sensitivity

NASA Technical Reports Server (NTRS)

Lin, J. Y.; Mingori, D. L.

1992-01-01

We present a method for improving the tolerance of a conventional LQG controller to parameter errors in the plant model. The improvement is achieved by introducing additional terms reflecting the structure of the parameter errors into the LQR cost function, and also the process and measurement noise models. Adjusting the sizes of these additional terms permits a trade-off between robustness and nominal performance. Manipulation of some of the additional terms leads to high gain controllers while other terms lead to low gain controllers. Conditions are developed under which the high-gain approach asymptotically recovers the robustness of the corresponding full-state feedback design, and the low-gain approach makes the closed-loop poles asymptotically insensitive to parameter errors.

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

Burrage, Clare; Copeland, Edmund J.; Hinds, E.A., E-mail: Clare.Burrage@nottingham.ac.uk, E-mail: Edmund.Copeland@nottingham.ac.uk, E-mail: Ed.Hinds@imperial.ac.uk

Theories of dark energy require a screening mechanism to explain why the associated scalar fields do not mediate observable long range fifth forces. The archetype of this is the chameleon field. Here we show that individual atoms are too small to screen the chameleon field inside a large high-vacuum chamber, and therefore can detect the field with high sensitivity. We derive new limits on the chameleon parameters from existing experiments, and show that most of the remaining chameleon parameter space is readily accessible using atom interferometry.

Computationally inexpensive identification of noninformative model parameters by sequential screening

NASA Astrophysics Data System (ADS)

Cuntz, Matthias; Mai, Juliane; Zink, Matthias; Thober, Stephan; Kumar, Rohini; Schäfer, David; Schrön, Martin; Craven, John; Rakovec, Oldrich; Spieler, Diana; Prykhodko, Vladyslav; Dalmasso, Giovanni; Musuuza, Jude; Langenberg, Ben; Attinger, Sabine; Samaniego, Luis

2015-08-01

Environmental models tend to require increasing computational time and resources as physical process descriptions are improved or new descriptions are incorporated. Many-query applications such as sensitivity analysis or model calibration usually require a large number of model evaluations leading to high computational demand. This often limits the feasibility of rigorous analyses. Here we present a fully automated sequential screening method that selects only informative parameters for a given model output. The method requires a number of model evaluations that is approximately 10 times the number of model parameters. It was tested using the mesoscale hydrologic model mHM in three hydrologically unique European river catchments. It identified around 20 informative parameters out of 52, with different informative parameters in each catchment. The screening method was evaluated with subsequent analyses using all 52 as well as only the informative parameters. Subsequent Sobol's global sensitivity analysis led to almost identical results yet required 40% fewer model evaluations after screening. mHM was calibrated with all and with only informative parameters in the three catchments. Model performances for daily discharge were equally high in both cases with Nash-Sutcliffe efficiencies above 0.82. Calibration using only the informative parameters needed just one third of the number of model evaluations. The universality of the sequential screening method was demonstrated using several general test functions from the literature. We therefore recommend the use of the computationally inexpensive sequential screening method prior to rigorous analyses on complex environmental models.

Computationally inexpensive identification of noninformative model parameters by sequential screening

NASA Astrophysics Data System (ADS)

Mai, Juliane; Cuntz, Matthias; Zink, Matthias; Thober, Stephan; Kumar, Rohini; Schäfer, David; Schrön, Martin; Craven, John; Rakovec, Oldrich; Spieler, Diana; Prykhodko, Vladyslav; Dalmasso, Giovanni; Musuuza, Jude; Langenberg, Ben; Attinger, Sabine; Samaniego, Luis

2016-04-01

Environmental models tend to require increasing computational time and resources as physical process descriptions are improved or new descriptions are incorporated. Many-query applications such as sensitivity analysis or model calibration usually require a large number of model evaluations leading to high computational demand. This often limits the feasibility of rigorous analyses. Here we present a fully automated sequential screening method that selects only informative parameters for a given model output. The method requires a number of model evaluations that is approximately 10 times the number of model parameters. It was tested using the mesoscale hydrologic model mHM in three hydrologically unique European river catchments. It identified around 20 informative parameters out of 52, with different informative parameters in each catchment. The screening method was evaluated with subsequent analyses using all 52 as well as only the informative parameters. Subsequent Sobol's global sensitivity analysis led to almost identical results yet required 40% fewer model evaluations after screening. mHM was calibrated with all and with only informative parameters in the three catchments. Model performances for daily discharge were equally high in both cases with Nash-Sutcliffe efficiencies above 0.82. Calibration using only the informative parameters needed just one third of the number of model evaluations. The universality of the sequential screening method was demonstrated using several general test functions from the literature. We therefore recommend the use of the computationally inexpensive sequential screening method prior to rigorous analyses on complex environmental models.

A three-dimensional cohesive sediment transport model with data assimilation: Model development, sensitivity analysis and parameter estimation

NASA Astrophysics Data System (ADS)

Wang, Daosheng; Cao, Anzhou; Zhang, Jicai; Fan, Daidu; Liu, Yongzhi; Zhang, Yue

2018-06-01

Based on the theory of inverse problems, a three-dimensional sigma-coordinate cohesive sediment transport model with the adjoint data assimilation is developed. In this model, the physical processes of cohesive sediment transport, including deposition, erosion and advection-diffusion, are parameterized by corresponding model parameters. These parameters are usually poorly known and have traditionally been assigned empirically. By assimilating observations into the model, the model parameters can be estimated using the adjoint method; meanwhile, the data misfit between model results and observations can be decreased. The model developed in this work contains numerous parameters; therefore, it is necessary to investigate the parameter sensitivity of the model, which is assessed by calculating a relative sensitivity function and the gradient of the cost function with respect to each parameter. The results of parameter sensitivity analysis indicate that the model is sensitive to the initial conditions, inflow open boundary conditions, suspended sediment settling velocity and resuspension rate, while the model is insensitive to horizontal and vertical diffusivity coefficients. A detailed explanation of the pattern of sensitivity analysis is also given. In ideal twin experiments, constant parameters are estimated by assimilating 'pseudo' observations. The results show that the sensitive parameters are estimated more easily than the insensitive parameters. The conclusions of this work can provide guidance for the practical applications of this model to simulate sediment transport in the study area.

Simple Electrolyzer Model Development for High-Temperature Electrolysis System Analysis Using Solid Oxide Electrolysis Cell

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

JaeHwa Koh; DuckJoo Yoon; Chang H. Oh

2010-07-01

An electrolyzer model for the analysis of a hydrogen-production system using a solid oxide electrolysis cell (SOEC) has been developed, and the effects for principal parameters have been estimated by sensitivity studies based on the developed model. The main parameters considered are current density, area specific resistance, temperature, pressure, and molar fraction and flow rates in the inlet and outlet. Finally, a simple model for a high-temperature hydrogen-production system using the solid oxide electrolysis cell integrated with very high temperature reactors is estimated.

Impact of the hard-coded parameters on the hydrologic fluxes of the land surface model Noah-MP

NASA Astrophysics Data System (ADS)

Cuntz, Matthias; Mai, Juliane; Samaniego, Luis; Clark, Martyn; Wulfmeyer, Volker; Attinger, Sabine; Thober, Stephan

2016-04-01

Land surface models incorporate a large number of processes, described by physical, chemical and empirical equations. The process descriptions contain a number of parameters that can be soil or plant type dependent and are typically read from tabulated input files. Land surface models may have, however, process descriptions that contain fixed, hard-coded numbers in the computer code, which are not identified as model parameters. Here we searched for hard-coded parameters in the computer code of the land surface model Noah with multiple process options (Noah-MP) to assess the importance of the fixed values on restricting the model's agility during parameter estimation. We found 139 hard-coded values in all Noah-MP process options, which are mostly spatially constant values. This is in addition to the 71 standard parameters of Noah-MP, which mostly get distributed spatially by given vegetation and soil input maps. We performed a Sobol' global sensitivity analysis of Noah-MP to variations of the standard and hard-coded parameters for a specific set of process options. 42 standard parameters and 75 hard-coded parameters were active with the chosen process options. The sensitivities of the hydrologic output fluxes latent heat and total runoff as well as their component fluxes were evaluated. These sensitivities were evaluated at twelve catchments of the Eastern United States with very different hydro-meteorological regimes. Noah-MP's hydrologic output fluxes are sensitive to two thirds of its standard parameters. The most sensitive parameter is, however, a hard-coded value in the formulation of soil surface resistance for evaporation, which proved to be oversensitive in other land surface models as well. Surface runoff is sensitive to almost all hard-coded parameters of the snow processes and the meteorological inputs. These parameter sensitivities diminish in total runoff. Assessing these parameters in model calibration would require detailed snow observations or the calculation of hydrologic signatures of the runoff data. Latent heat and total runoff exhibit very similar sensitivities towards standard and hard-coded parameters in Noah-MP because of their tight coupling via the water balance. It should therefore be comparable to calibrate Noah-MP either against latent heat observations or against river runoff data. Latent heat and total runoff are sensitive to both, plant and soil parameters. Calibrating only a parameter sub-set of only soil parameters, for example, thus limits the ability to derive realistic model parameters. It is thus recommended to include the most sensitive hard-coded model parameters that were exposed in this study when calibrating Noah-MP.

Identification of the most sensitive parameters in the activated sludge model implemented in BioWin software.

PubMed

Liwarska-Bizukojc, Ewa; Biernacki, Rafal

2010-10-01

In order to simulate biological wastewater treatment processes, data concerning wastewater and sludge composition, process kinetics and stoichiometry are required. Selection of the most sensitive parameters is an important step of model calibration. The aim of this work is to verify the predictability of the activated sludge model, which is implemented in BioWin software, and select its most influential kinetic and stoichiometric parameters with the help of sensitivity analysis approach. Two different measures of sensitivity are applied: the normalised sensitivity coefficient (S(i,j)) and the mean square sensitivity measure (delta(j)(msqr)). It occurs that 17 kinetic and stoichiometric parameters of the BioWin activated sludge (AS) model can be regarded as influential on the basis of S(i,j) calculations. Half of the influential parameters are associated with growth and decay of phosphorus accumulating organisms (PAOs). The identification of the set of the most sensitive parameters should support the users of this model and initiate the elaboration of determination procedures for the parameters, for which it has not been done yet. Copyright 2010 Elsevier Ltd. All rights reserved.

Monte Carlo sensitivity analysis of unknown parameters in hazardous materials transportation risk assessment.

PubMed

Pet-Armacost, J J; Sepulveda, J; Sakude, M

1999-12-01

The US Department of Transportation was interested in the risks associated with transporting Hydrazine in tanks with and without relief devices. Hydrazine is both highly toxic and flammable, as well as corrosive. Consequently, there was a conflict as to whether a relief device should be used or not. Data were not available on the impact of relief devices on release probabilities or the impact of Hydrazine on the likelihood of fires and explosions. In this paper, a Monte Carlo sensitivity analysis of the unknown parameters was used to assess the risks associated with highway transport of Hydrazine. To help determine whether or not relief devices should be used, fault trees and event trees were used to model the sequences of events that could lead to adverse consequences during transport of Hydrazine. The event probabilities in the event trees were derived as functions of the parameters whose effects were not known. The impacts of these parameters on the risk of toxic exposures, fires, and explosions were analyzed through a Monte Carlo sensitivity analysis and analyzed statistically through an analysis of variance. The analysis allowed the determination of which of the unknown parameters had a significant impact on the risks. It also provided the necessary support to a critical transportation decision even though the values of several key parameters were not known.

Sensitivity of finite helical axis parameters to temporally varying realistic motion utilizing an idealized knee model.

PubMed

Johnson, T S; Andriacchi, T P; Erdman, A G

2004-01-01

Various uses of the screw or helical axis have previously been reported in the literature in an attempt to quantify the complex displacements and coupled rotations of in vivo human knee kinematics. Multiple methods have been used by previous authors to calculate the axis parameters, and it has been theorized that the mathematical stability and accuracy of the finite helical axis (FHA) is highly dependent on experimental variability and rotation increment spacing between axis calculations. Previous research has not addressed the sensitivity of the FHA for true in vivo data collection, as required for gait laboratory analysis. This research presents a controlled series of experiments simulating continuous data collection as utilized in gait analysis to investigate the sensitivity of the three-dimensional finite screw axis parameters of rotation, displacement, orientation and location with regard to time step increment spacing, utilizing two different methods for spatial location. Six-degree-of-freedom motion parameters are measured for an idealized rigid body knee model that is constrained to a planar motion profile for the purposes of error analysis. The kinematic data are collected using a multicamera optoelectronic system combined with an error minimization algorithm known as the point cluster method. Rotation about the screw axis is seen to be repeatable, accurate and time step increment insensitive. Displacement along the axis is highly dependent on time step increment sizing, with smaller rotation angles between calculations producing more accuracy. Orientation of the axis in space is accurate with only a slight filtering effect noticed during motion reversal. Locating the screw axis by a projected point onto the screw axis from the mid-point of the finite displacement is found to be less sensitive to motion reversal than finding the intersection of the axis with a reference plane. A filtering effect of the spatial location parameters was noted for larger time step increments during periods of little or no rotation.

Cutoffs of Short-Term Heart Rate Variability Parameters in Brazilian Adolescents Male.

PubMed

Farah, Breno Quintella; Christofaro, Diego Giulliano Destro; Cavalcante, Bruno Remígio; Andrade-Lima, Aluísio; Germano-Soares, Antonio Henrique; Vanderlei, Luiz Carlos Marques; Lanza, Fernanda Cordoba; Ritti-Dias, Raphael Mendes

2018-05-15

A low heart rate variability (HRV) has been associated with cardiovascular risk factors in adolescents. However, no cut-off points are known for HRV parameters in this age group, making it difficult to use in clinical practice. Thus, the aims of the current study were to establish cutoffs of HRV parameters and to examine their association with cardiovascular risk in Brazilian adolescents male. For this reason, this cross-sectional study included 1152 adolescent boys (16.6 ± 1.2 years old). HRV measures of time (SD of all RR intervals, root mean square of the squared differences between adjacent normal RR intervals, and the percentage of adjacent intervals over 50 ms), frequency domains [low (LF) and high (HF) frequency], and Poincaré plot (SD1, SD2 and SD1/SD2 ratio) were assessed. Cardiovascular risk was assessed by sum of abdominal obesity, high blood pressure, overweight, and low physical activity level. The proposed cutoffs showed moderate to high sensitivity, specificity, and area under curve values (p < 0.05). HRV frequency parameters were statistically superior when compared to time-domain and Poincaré plot parameters. The binary logistic regression analysis indicated that all proposed HRV cutoffs were independently associated with a clustering of cardiovascular risk factors, with greater magnitude of HF and SD1/SD2 ratio (two or more risk factors: OR = 3.59 and 95% CI 1.76-7.34). In conclusion, proposed HRV cutoffs have moderate to high sensitivity in detecting of the cardiovascular risk factor and HRV frequency-domain were better discriminants of cardiovascular risk than time-domain and Poincaré plot parameters.

UNCERTAINTY AND SENSITIVITY ANALYSES FOR VERY HIGH ORDER MODELS

EPA Science Inventory

While there may in many cases be high potential for exposure of humans and ecosystems to chemicals released from a source, the degree to which this potential is realized is often uncertain. Conceptually, uncertainties are divided among parameters, model, and modeler during simula...

Photonic crystal nanofiber air-mode cavity with high Q-factor and high sensitivity for refractive index sensing

NASA Astrophysics Data System (ADS)

Ma, Xiaoxue; Chen, Xin; Nie, Hongrui; Yang, Daquan

2018-01-01

Recently, due to its superior characteristics and simple manufacture, such as small size, low loss, high sensitivity and convenience to couple, the optical fiber sensor has become one of the most promising sensors. In order to achieve the most effective realization of light propagation by changing the structure of sensors, FOM(S •Q/λres) ,which is determined by two significant variables Q-factor and sensitivity, as a trade-off parameter should be optimized to a high value. In typical sensors, a high Q can be achieved by confining the optical field in the high refractive index dielectric region to make an interaction between analytes and evanescent field of the resonant mode. However, the ignored sensitivity is relatively low with a high Q achieved, which means that the resonant wavelength shift changes non-obviously when the refractive index increases. Meanwhile, the sensitivity also leads to a less desirable FOM. Therefore, a gradient structure, which can enhance the performance of sensors by achieving high Q and high sensitivity, has been developed by Kim et al. later. Here, by introducing parabolic-tapered structure, the light field localized overlaps strongly and sufficiently with analytes. And based on a one-dimensional photonic-crystal nanofiber air-mode cavity, a creative optical fiber sensor is proposed by combining good stability and transmission characteristics of fiber and strengths of tapered structure, realizing excellent FOM {4.7 x 105 with high Q-factors (Q{106) and high sensitivities (<700 nm/RIU).

Global Sensitivity of Simulated Water Balance Indicators Under Future Climate Change in the Colorado Basin

DOE PAGES

Bennett, Katrina Eleanor; Urrego Blanco, Jorge Rolando; Jonko, Alexandra; ...

2017-11-20

The Colorado River basin is a fundamentally important river for society, ecology and energy in the United States. Streamflow estimates are often provided using modeling tools which rely on uncertain parameters; sensitivity analysis can help determine which parameters impact model results. Despite the fact that simulated flows respond to changing climate and vegetation in the basin, parameter sensitivity of the simulations under climate change has rarely been considered. In this study, we conduct a global sensitivity analysis to relate changes in runoff, evapotranspiration, snow water equivalent and soil moisture to model parameters in the Variable Infiltration Capacity (VIC) hydrologic model.more » Here, we combine global sensitivity analysis with a space-filling Latin Hypercube sampling of the model parameter space and statistical emulation of the VIC model to examine sensitivities to uncertainties in 46 model parameters following a variance-based approach.« less

Analysis of the sensitivity properties of a model of vector-borne bubonic plague.

PubMed

Buzby, Megan; Neckels, David; Antolin, Michael F; Estep, Donald

2008-09-06

Model sensitivity is a key to evaluation of mathematical models in ecology and evolution, especially in complex models with numerous parameters. In this paper, we use some recently developed methods for sensitivity analysis to study the parameter sensitivity of a model of vector-borne bubonic plague in a rodent population proposed by Keeling & Gilligan. The new sensitivity tools are based on a variational analysis involving the adjoint equation. The new approach provides a relatively inexpensive way to obtain derivative information about model output with respect to parameters. We use this approach to determine the sensitivity of a quantity of interest (the force of infection from rats and their fleas to humans) to various model parameters, determine a region over which linearization at a specific parameter reference point is valid, develop a global picture of the output surface, and search for maxima and minima in a given region in the parameter space.

Global Sensitivity of Simulated Water Balance Indicators Under Future Climate Change in the Colorado Basin

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

Bennett, Katrina Eleanor; Urrego Blanco, Jorge Rolando; Jonko, Alexandra

The Colorado River basin is a fundamentally important river for society, ecology and energy in the United States. Streamflow estimates are often provided using modeling tools which rely on uncertain parameters; sensitivity analysis can help determine which parameters impact model results. Despite the fact that simulated flows respond to changing climate and vegetation in the basin, parameter sensitivity of the simulations under climate change has rarely been considered. In this study, we conduct a global sensitivity analysis to relate changes in runoff, evapotranspiration, snow water equivalent and soil moisture to model parameters in the Variable Infiltration Capacity (VIC) hydrologic model.more » Here, we combine global sensitivity analysis with a space-filling Latin Hypercube sampling of the model parameter space and statistical emulation of the VIC model to examine sensitivities to uncertainties in 46 model parameters following a variance-based approach.« less

Sensitivity of the Eocene climate to CO2 and orbital variability

NASA Astrophysics Data System (ADS)

Keery, John S.; Holden, Philip B.; Edwards, Neil R.

2018-02-01

The early Eocene, from about 56 Ma, with high atmospheric CO2 levels, offers an analogue for the response of the Earth's climate system to anthropogenic fossil fuel burning. In this study, we present an ensemble of 50 Earth system model runs with an early Eocene palaeogeography and variation in the forcing values of atmospheric CO2 and the Earth's orbital parameters. Relationships between simple summary metrics of model outputs and the forcing parameters are identified by linear modelling, providing estimates of the relative magnitudes of the effects of atmospheric CO2 and each of the orbital parameters on important climatic features, including tropical-polar temperature difference, ocean-land temperature contrast, Asian, African and South (S.) American monsoon rains, and climate sensitivity. Our results indicate that although CO2 exerts a dominant control on most of the climatic features examined in this study, the orbital parameters also strongly influence important components of the ocean-atmosphere system in a greenhouse Earth. In our ensemble, atmospheric CO2 spans the range 280-3000 ppm, and this variation accounts for over 90 % of the effects on mean air temperature, southern winter high-latitude ocean-land temperature contrast and northern winter tropical-polar temperature difference. However, the variation of precession accounts for over 80 % of the influence of the forcing parameters on the Asian and African monsoon rainfall, and obliquity variation accounts for over 65 % of the effects on winter ocean-land temperature contrast in high northern latitudes and northern summer tropical-polar temperature difference. Our results indicate a bimodal climate sensitivity, with values of 4.36 and 2.54 °C, dependent on low or high states of atmospheric CO2 concentration, respectively, with a threshold at approximately 1000 ppm in this model, and due to a saturated vegetation-albedo feedback. Our method gives a quantitative ranking of the influence of each of the forcing parameters on key climatic model outputs, with additional spatial information from singular value decomposition providing insights into likely physical mechanisms. The results demonstrate the importance of orbital variation as an agent of change in climates of the past, and we demonstrate that emulators derived from our modelling output can be used as rapid and efficient surrogates of the full complexity model to provide estimates of climate conditions from any set of forcing parameters.

Sensitivity study and parameter optimization of OCD tool for 14nm finFET process

NASA Astrophysics Data System (ADS)

Zhang, Zhensheng; Chen, Huiping; Cheng, Shiqiu; Zhan, Yunkun; Huang, Kun; Shi, Yaoming; Xu, Yiping

2016-03-01

Optical critical dimension (OCD) measurement has been widely demonstrated as an essential metrology method for monitoring advanced IC process in the technology node of 90 nm and beyond. However, the rapidly shrunk critical dimensions of the semiconductor devices and the increasing complexity of the manufacturing process bring more challenges to OCD. The measurement precision of OCD technology highly relies on the optical hardware configuration, spectral types, and inherently interactions between the incidence of light and various materials with various topological structures, therefore sensitivity analysis and parameter optimization are very critical in the OCD applications. This paper presents a method for seeking the optimum sensitive measurement configuration to enhance the metrology precision and reduce the noise impact to the greatest extent. In this work, the sensitivity of different types of spectra with a series of hardware configurations of incidence angles and azimuth angles were investigated. The optimum hardware measurement configuration and spectrum parameter can be identified. The FinFET structures in the technology node of 14 nm were constructed to validate the algorithm. This method provides guidance to estimate the measurement precision before measuring actual device features and will be beneficial for OCD hardware configuration.

A model study of periodic breathing, stability of the neonatal respiratory system, and causes of sudden infant death syndrome.

PubMed

Tehrani, F T

1997-09-01

A mathematical model of the neonatal respiratory system has been modified and used to examine the system under various physiological conditions at different stages of maturity. The respiratory responses in hypoxia, periodic breathing and following a sign have been analyzed. The effects of different respiratory parameters on the stability of the system for normal and premature infants have been investigated. The causes of periodic breathing, apnea spells and sudden infant death syndrome for full-term and premature infants have been studied, and the results compared with the available experimental findings. The response of the infant respiratory system has been found to be highly sensitive to several parameters of the system, as indicated by the results of this study. These significant parameters are sensitivity factor of central receptors to carbon dioxide, sensitivity factor of arterial receptors to carbon dioxide, sensitivity factor of arterial receptors to oxygen, functional residual capacity of the lungs, the alveolar-arterial oxygen difference and the lungs shunt ratio. It has been shown that different parts of the respiratory controller have antagonistic effects on hypoxic periodic breathing and apnea of infancy.

Piezoresistive Cantilever Performance—Part I: Analytical Model for Sensitivity

PubMed Central

Park, Sung-Jin; Doll, Joseph C.; Pruitt, Beth L.

2010-01-01

An accurate analytical model for the change in resistance of a piezoresistor is necessary for the design of silicon piezoresistive transducers. Ion implantation requires a high-temperature oxidation or annealing process to activate the dopant atoms, and this treatment results in a distorted dopant profile due to diffusion. Existing analytical models do not account for the concentration dependence of piezoresistance and are not accurate for nonuniform dopant profiles. We extend previous analytical work by introducing two nondimensional factors, namely, the efficiency and geometry factors. A practical benefit of this efficiency factor is that it separates the process parameters from the design parameters; thus, designers may address requirements for cantilever geometry and fabrication process independently. To facilitate the design process, we provide a lookup table for the efficiency factor over an extensive range of process conditions. The model was validated by comparing simulation results with the experimentally determined sensitivities of piezoresistive cantilevers. We performed 9200 TSUPREM4 simulations and fabricated 50 devices from six unique process flows; we systematically explored the design space relating process parameters and cantilever sensitivity. Our treatment focuses on piezoresistive cantilevers, but the analytical sensitivity model is extensible to other piezoresistive transducers such as membrane pressure sensors. PMID:20336183

Piezoresistive Cantilever Performance-Part I: Analytical Model for Sensitivity.

PubMed

Park, Sung-Jin; Doll, Joseph C; Pruitt, Beth L

2010-02-01

An accurate analytical model for the change in resistance of a piezoresistor is necessary for the design of silicon piezoresistive transducers. Ion implantation requires a high-temperature oxidation or annealing process to activate the dopant atoms, and this treatment results in a distorted dopant profile due to diffusion. Existing analytical models do not account for the concentration dependence of piezoresistance and are not accurate for nonuniform dopant profiles. We extend previous analytical work by introducing two nondimensional factors, namely, the efficiency and geometry factors. A practical benefit of this efficiency factor is that it separates the process parameters from the design parameters; thus, designers may address requirements for cantilever geometry and fabrication process independently. To facilitate the design process, we provide a lookup table for the efficiency factor over an extensive range of process conditions. The model was validated by comparing simulation results with the experimentally determined sensitivities of piezoresistive cantilevers. We performed 9200 TSUPREM4 simulations and fabricated 50 devices from six unique process flows; we systematically explored the design space relating process parameters and cantilever sensitivity. Our treatment focuses on piezoresistive cantilevers, but the analytical sensitivity model is extensible to other piezoresistive transducers such as membrane pressure sensors.

Error tolerance analysis of wave diagnostic based on coherent modulation imaging in high power laser system

NASA Astrophysics Data System (ADS)

Pan, Xingchen; Liu, Cheng; Zhu, Jianqiang

2018-02-01

Coherent modulation imaging providing fast convergence speed and high resolution with single diffraction pattern is a promising technique to satisfy the urgent demands for on-line multiple parameter diagnostics with single setup in high power laser facilities (HPLF). However, the influence of noise on the final calculated parameters concerned has not been investigated yet. According to a series of simulations with twenty different sampling beams generated based on the practical parameters and performance of HPLF, the quantitative analysis based on statistical results was first investigated after considering five different error sources. We found the background noise of detector and high quantization error will seriously affect the final accuracy and different parameters have different sensitivity to different noise sources. The simulation results and the corresponding analysis provide the potential directions to further improve the final accuracy of parameter diagnostics which is critically important to its formal applications in the daily routines of HPLF.

Probing dark energy with atom interferometry

NASA Astrophysics Data System (ADS)

Burrage, Clare; Copeland, Edmund J.; Hinds, E. A.

2015-03-01

Theories of dark energy require a screening mechanism to explain why the associated scalar fields do not mediate observable long range fifth forces. The archetype of this is the chameleon field. Here we show that individual atoms are too small to screen the chameleon field inside a large high-vacuum chamber, and therefore can detect the field with high sensitivity. We derive new limits on the chameleon parameters from existing experiments, and show that most of the remaining chameleon parameter space is readily accessible using atom interferometry.

An analysis of sensitivity of CLIMEX parameters in mapping species potential distribution and the broad-scale changes observed with minor variations in parameters values: an investigation using open-field Solanum lycopersicum and Neoleucinodes elegantalis as an example

NASA Astrophysics Data System (ADS)

da Silva, Ricardo Siqueira; Kumar, Lalit; Shabani, Farzin; Picanço, Marcelo Coutinho

2018-04-01

A sensitivity analysis can categorize levels of parameter influence on a model's output. Identifying parameters having the most influence facilitates establishing the best values for parameters of models, providing useful implications in species modelling of crops and associated insect pests. The aim of this study was to quantify the response of species models through a CLIMEX sensitivity analysis. Using open-field Solanum lycopersicum and Neoleucinodes elegantalis distribution records, and 17 fitting parameters, including growth and stress parameters, comparisons were made in model performance by altering one parameter value at a time, in comparison to the best-fit parameter values. Parameters that were found to have a greater effect on the model results are termed "sensitive". Through the use of two species, we show that even when the Ecoclimatic Index has a major change through upward or downward parameter value alterations, the effect on the species is dependent on the selection of suitability categories and regions of modelling. Two parameters were shown to have the greatest sensitivity, dependent on the suitability categories of each species in the study. Results enhance user understanding of which climatic factors had a greater impact on both species distributions in our model, in terms of suitability categories and areas, when parameter values were perturbed by higher or lower values, compared to the best-fit parameter values. Thus, the sensitivity analyses have the potential to provide additional information for end users, in terms of improving management, by identifying the climatic variables that are most sensitive.

Stimulus Sensitivity of a Spiking Neural Network Model

NASA Astrophysics Data System (ADS)

Chevallier, Julien

2018-02-01

Some recent papers relate the criticality of complex systems to their maximal capacity of information processing. In the present paper, we consider high dimensional point processes, known as age-dependent Hawkes processes, which have been used to model spiking neural networks. Using mean-field approximation, the response of the network to a stimulus is computed and we provide a notion of stimulus sensitivity. It appears that the maximal sensitivity is achieved in the sub-critical regime, yet almost critical for a range of biologically relevant parameters.

Sensitivity of acoustic nonlinearity parameter to the microstructural changes in cement-based materials

NASA Astrophysics Data System (ADS)

Kim, Gun; Kim, Jin-Yeon; Kurtis, Kimberly E.; Jacobs, Laurence J.

2015-03-01

This research experimentally investigates the sensitivity of the acoustic nonlinearity parameter to microcracks in cement-based materials. Based on the second harmonic generation (SHG) technique, an experimental setup using non-contact, air-coupled detection is used to receive the consistent Rayleigh surface waves. To induce variations in the extent of microscale cracking in two types of specimens (concrete and mortar), shrinkage reducing admixture (SRA), is used in one set, while a companion specimen is prepared without SRA. A 50 kHz wedge transducer and a 100 kHz air-coupled transducer are implemented for the generation and detection of nonlinear Rayleigh waves. It is shown that the air-coupled detection method provides more repeatable fundamental and second harmonic amplitudes of the propagating Rayleigh waves. The obtained amplitudes are then used to calculate the relative nonlinearity parameter βre, the ratio of the second harmonic amplitude to the square of the fundamental amplitude. The experimental results clearly demonstrate that the nonlinearity parameter (βre) is highly sensitive to the microstructural changes in cement-based materials than the Rayleigh phase velocity and attenuation and that SRA has great potential to avoid shrinkage cracking in cement-based materials.

Sensitivity analysis of conservative and reactive stream transient storage models applied to field data from multiple-reach experiments

USGS Publications Warehouse

Gooseff, M.N.; Bencala, K.E.; Scott, D.T.; Runkel, R.L.; McKnight, Diane M.

2005-01-01

The transient storage model (TSM) has been widely used in studies of stream solute transport and fate, with an increasing emphasis on reactive solute transport. In this study we perform sensitivity analyses of a conservative TSM and two different reactive solute transport models (RSTM), one that includes first-order decay in the stream and the storage zone, and a second that considers sorption of a reactive solute on streambed sediments. Two previously analyzed data sets are examined with a focus on the reliability of these RSTMs in characterizing stream and storage zone solute reactions. Sensitivities of simulations to parameters within and among reaches, parameter coefficients of variation, and correlation coefficients are computed and analyzed. Our results indicate that (1) simulated values have the greatest sensitivity to parameters within the same reach, (2) simulated values are also sensitive to parameters in reaches immediately upstream and downstream (inter-reach sensitivity), (3) simulated values have decreasing sensitivity to parameters in reaches farther downstream, and (4) in-stream reactive solute data provide adequate data to resolve effective storage zone reaction parameters, given the model formulations. Simulations of reactive solutes are shown to be equally sensitive to transport parameters and effective reaction parameters of the model, evidence of the control of physical transport on reactive solute dynamics. Similar to conservative transport analysis, reactive solute simulations appear to be most sensitive to data collected during the rising and falling limb of the concentration breakthrough curve. ?? 2005 Elsevier Ltd. All rights reserved.

In-Situ Characterization of Tissue Blood Flow, Blood Content, and Water State Using New Techniques in Magnetic Resonance Imaging.

NASA Astrophysics Data System (ADS)

Conturo, Thomas Edward

Tissue blood flow, blood content, and water state have been characterized in-situ with new nuclear magnetic resonance imaging techniques. The sensitivities of standard techniques to the physiologic tissue parameters spin density (N_{rm r}) and relaxation times (T_1 and T_2 ) are mathematically defined. A new driven inversion method is developed so that tissue T_1 and T_2 changes produce cooperative intensity changes, yielding high contrast, high signal to noise, and sensitivity to a wider range of tissue parameters. The actual tissue parameters were imaged by automated collection of multiple-echo data having multiple T _1 dependence. Data are simultaneously fit by three-parameters to a closed-form expression, producing lower inter-parameter correlation and parameter noise than in separate T_1 or T_2 methods or pre-averaged methods. Accurate parameters are obtained at different field strengths. Parametric images of pathology demonstrate high sensitivity to tissue heterogeneity, and water content is determined in many tissues. Erythrocytes were paramagnetically labeled to study blood content and relaxation mechanisms. Liver and spleen relaxation were enhanced following 10% exchange of animal blood volumes. Rapid water exchange between intracellular and extracellular compartments was validated. Erythrocytes occupied 12.5% of renal cortex volume, and blood content was uniform in the liver, spleen and kidney. The magnitude and direction of flow velocity was then imaged. To eliminate directional artifacts, a bipolar gradient technique sensitized to flow in different directions was developed. Phase angle was reconstructed instead of intensity since the former has a 2pi -fold higher dynamic range. Images of flow through curves demonstrated secondary flow with a centrifugally-biased laminar profile and stationary velocity peaks along the curvature. Portal vein flow velocities were diminished or reversed in cirrhosis. Image artifacts have been characterized and removed. The foldover in magnified images was eliminated by exciting limited regions with orthogonal pi/2 and pi pulses. Off-midline regions were imaged by tandemly offsetting the phase-encoding and excitation. Artifacts due to non-steady-state conditions were demonstrated. The approach to steady state was defined by operators and vectors, and any repeated series of RF pulses was proven to produce a steady-state. The vector difference between the magnetization and its steady state value is relatively constant during the approach. The repetition time relative to T_1 is the main determinant of approach rate, and off-resonant RF pulses incoherent with the magnetization produce a more rapid approach than on-resonant pulses.

Kinematic sensitivity of robot manipulators

NASA Technical Reports Server (NTRS)

Vuskovic, Marko I.

1989-01-01

Kinematic sensitivity vectors and matrices for open-loop, n degrees-of-freedom manipulators are derived. First-order sensitivity vectors are defined as partial derivatives of the manipulator's position and orientation with respect to its geometrical parameters. The four-parameter kinematic model is considered, as well as the five-parameter model in case of nominally parallel joint axes. Sensitivity vectors are expressed in terms of coordinate axes of manipulator frames. Second-order sensitivity vectors, the partial derivatives of first-order sensitivity vectors, are also considered. It is shown that second-order sensitivity vectors can be expressed as vector products of the first-order sensitivity vectors.

Monte Carlo sensitivity analysis of land surface parameters using the Variable Infiltration Capacity model

NASA Astrophysics Data System (ADS)

Demaria, Eleonora M.; Nijssen, Bart; Wagener, Thorsten

2007-06-01

Current land surface models use increasingly complex descriptions of the processes that they represent. Increase in complexity is accompanied by an increase in the number of model parameters, many of which cannot be measured directly at large spatial scales. A Monte Carlo framework was used to evaluate the sensitivity and identifiability of ten parameters controlling surface and subsurface runoff generation in the Variable Infiltration Capacity model (VIC). Using the Monte Carlo Analysis Toolbox (MCAT), parameter sensitivities were studied for four U.S. watersheds along a hydroclimatic gradient, based on a 20-year data set developed for the Model Parameter Estimation Experiment (MOPEX). Results showed that simulated streamflows are sensitive to three parameters when evaluated with different objective functions. Sensitivity of the infiltration parameter (b) and the drainage parameter (exp) were strongly related to the hydroclimatic gradient. The placement of vegetation roots played an important role in the sensitivity of model simulations to the thickness of the second soil layer (thick2). Overparameterization was found in the base flow formulation indicating that a simplified version could be implemented. Parameter sensitivity was more strongly dictated by climatic gradients than by changes in soil properties. Results showed how a complex model can be reduced to a more parsimonious form, leading to a more identifiable model with an increased chance of successful regionalization to ungauged basins. Although parameter sensitivities are strictly valid for VIC, this model is representative of a wider class of macroscale hydrological models. Consequently, the results and methodology will have applicability to other hydrological models.

Delineating parameter unidentifiabilities in complex models

NASA Astrophysics Data System (ADS)

Raman, Dhruva V.; Anderson, James; Papachristodoulou, Antonis

2017-03-01

Scientists use mathematical modeling as a tool for understanding and predicting the properties of complex physical systems. In highly parametrized models there often exist relationships between parameters over which model predictions are identical, or nearly identical. These are known as structural or practical unidentifiabilities, respectively. They are hard to diagnose and make reliable parameter estimation from data impossible. They furthermore imply the existence of an underlying model simplification. We describe a scalable method for detecting unidentifiabilities, as well as the functional relations defining them, for generic models. This allows for model simplification, and appreciation of which parameters (or functions thereof) cannot be estimated from data. Our algorithm can identify features such as redundant mechanisms and fast time-scale subsystems, as well as the regimes in parameter space over which such approximations are valid. We base our algorithm on a quantification of regional parametric sensitivity that we call `multiscale sloppiness'. Traditionally, the link between parametric sensitivity and the conditioning of the parameter estimation problem is made locally, through the Fisher information matrix. This is valid in the regime of infinitesimal measurement uncertainty. We demonstrate the duality between multiscale sloppiness and the geometry of confidence regions surrounding parameter estimates made where measurement uncertainty is non-negligible. Further theoretical relationships are provided linking multiscale sloppiness to the likelihood-ratio test. From this, we show that a local sensitivity analysis (as typically done) is insufficient for determining the reliability of parameter estimation, even with simple (non)linear systems. Our algorithm can provide a tractable alternative. We finally apply our methods to a large-scale, benchmark systems biology model of necrosis factor (NF)-κ B , uncovering unidentifiabilities.

Wideband MRE and static mechanical indentation of human liver specimen: sensitivity of viscoelastic constants to the alteration of tissue structure in hepatic fibrosis.

PubMed

Reiter, Rolf; Freise, Christian; Jöhrens, Korinna; Kamphues, Carsten; Seehofer, Daniel; Stockmann, Martin; Somasundaram, Rajan; Asbach, Patrick; Braun, Jürgen; Samani, Abbas; Sack, Ingolf

2014-05-07

Despite the success of elastography in grading hepatic fibrosis by stiffness related noninvasive markers the relationship between viscoelastic constants in the liver and tissue structure remains unclear. We therefore studied the mechanical properties of 16 human liver specimens with different degrees of fibrosis, inflammation and steatosis by wideband magnetic resonance elastography (MRE) and static indentation experiments providing the specimens׳ static Young׳s modulus (E), dynamic storage modulus (G') and dynamic loss modulus (G″). A frequency-independent shear modulus μ and a powerlaw exponent α were obtained by fitting G' and G″ using the two-parameter sprinpot model. The mechanical parameters were compared to the specimens׳ histology derived parameters such as degree of Fibrosis (F), inflammation score and fat score, amount of hydroxyproline (HYP) used for quantification of collagen, blood markers and presurgery in vivo function tests. The frequency averaged parameters G', G″ and μ were significantly correlated with F (G': R=0.762, G″: R=0.830; μ: R=0.744; all P<0.01) and HYP (G': R=0.712; G″: R=0.720; μ: R=0.731; all P<0.01). The powerlaw exponent α displayed an inverse correlation with F (R=-0.590, P=0.034) and a trend of inverse correlation with HYP (R=-0.470, P=0.089). The static Young׳s modulus E was less correlated with F (R=0.587, P=0.022) and not sensitive to HYP. Although inflammation was highly correlated with F (R=0.773, P<0.001), no interaction was discernable between inflammation and mechanical parameters measured in this study. Other histological and blood markers as well as liver function test were correlated with neither F nor the measured mechanical parameters. In conclusion, viscoelastic constants measured by wideband MRE are highly sensitive to histologically proven fibrosis. Our results suggest that, in addition to the amount of connective tissue, subtle structural changes of the viscoelastic matrix determine the sensitivity of mechanical tissue properties to hepatic fibrosis. Copyright © 2014 Elsevier Ltd. All rights reserved.

Quantitative Analysis of Swallowing Function Between Dysphagia Patients and Healthy Subjects Using High-Resolution Manometry

PubMed Central

2017-01-01

Objective To compare swallowing function between healthy subjects and patients with pharyngeal dysphagia using high resolution manometry (HRM) and to evaluate the usefulness of HRM for detecting pharyngeal dysphagia. Methods Seventy-five patients with dysphagia and 28 healthy subjects were included in this study. Diagnosis of dysphagia was confirmed by a videofluoroscopy. HRM was performed to measure pressure and timing information at the velopharynx (VP), tongue base (TB), and upper esophageal sphincter (UES). HRM parameters were compared between dysphagia and healthy groups. Optimal threshold values of significant HRM parameters for dysphagia were determined. Results VP maximal pressure, TB maximal pressure, UES relaxation duration, and UES resting pressure were lower in the dysphagia group than those in healthy group. UES minimal pressure was higher in dysphagia group than in the healthy group. Receiver operating characteristic (ROC) analyses were conducted to validate optimal threshold values for significant HRM parameters to identify patients with pharyngeal dysphagia. With maximal VP pressure at a threshold value of 144.0 mmHg, dysphagia was identified with 96.4% sensitivity and 74.7% specificity. With maximal TB pressure at a threshold value of 158.0 mmHg, dysphagia was identified with 96.4% sensitivity and 77.3% specificity. At a threshold value of 2.0 mmHg for UES minimal pressure, dysphagia was diagnosed at 74.7% sensitivity and 60.7% specificity. Lastly, UES relaxation duration of <0.58 seconds had 85.7% sensitivity and 65.3% specificity, and UES resting pressure of <75.0 mmHg had 89.3% sensitivity and 90.7% specificity for identifying dysphagia. Conclusion We present evidence that HRM could be a useful evaluation tool for detecting pharyngeal dysphagia. PMID:29201816

Quantitative Analysis of Swallowing Function Between Dysphagia Patients and Healthy Subjects Using High-Resolution Manometry.

PubMed

Park, Chul-Hyun; Kim, Don-Kyu; Lee, Yong-Taek; Yi, Youbin; Lee, Jung-Sang; Kim, Kunwoo; Park, Jung Ho; Yoon, Kyung Jae

2017-10-01

To compare swallowing function between healthy subjects and patients with pharyngeal dysphagia using high resolution manometry (HRM) and to evaluate the usefulness of HRM for detecting pharyngeal dysphagia. Seventy-five patients with dysphagia and 28 healthy subjects were included in this study. Diagnosis of dysphagia was confirmed by a videofluoroscopy. HRM was performed to measure pressure and timing information at the velopharynx (VP), tongue base (TB), and upper esophageal sphincter (UES). HRM parameters were compared between dysphagia and healthy groups. Optimal threshold values of significant HRM parameters for dysphagia were determined. VP maximal pressure, TB maximal pressure, UES relaxation duration, and UES resting pressure were lower in the dysphagia group than those in healthy group. UES minimal pressure was higher in dysphagia group than in the healthy group. Receiver operating characteristic (ROC) analyses were conducted to validate optimal threshold values for significant HRM parameters to identify patients with pharyngeal dysphagia. With maximal VP pressure at a threshold value of 144.0 mmHg, dysphagia was identified with 96.4% sensitivity and 74.7% specificity. With maximal TB pressure at a threshold value of 158.0 mmHg, dysphagia was identified with 96.4% sensitivity and 77.3% specificity. At a threshold value of 2.0 mmHg for UES minimal pressure, dysphagia was diagnosed at 74.7% sensitivity and 60.7% specificity. Lastly, UES relaxation duration of <0.58 seconds had 85.7% sensitivity and 65.3% specificity, and UES resting pressure of <75.0 mmHg had 89.3% sensitivity and 90.7% specificity for identifying dysphagia. We present evidence that HRM could be a useful evaluation tool for detecting pharyngeal dysphagia.

Persistent oscillations and backward bifurcation in a malaria model with varying human and mosquito populations: implications for control.

PubMed

Ngonghala, Calistus N; Teboh-Ewungkem, Miranda I; Ngwa, Gideon A

2015-06-01

We derive and study a deterministic compartmental model for malaria transmission with varying human and mosquito populations. Our model considers disease-related deaths, asymptomatic immune humans who are also infectious, as well as mosquito demography, reproduction and feeding habits. Analysis of the model reveals the existence of a backward bifurcation and persistent limit cycles whose period and size is determined by two threshold parameters: the vectorial basic reproduction number Rm, and the disease basic reproduction number R0, whose size can be reduced by reducing Rm. We conclude that malaria dynamics are indeed oscillatory when the methodology of explicitly incorporating the mosquito's demography, feeding and reproductive patterns is considered in modeling the mosquito population dynamics. A sensitivity analysis reveals important control parameters that can affect the magnitudes of Rm and R0, threshold quantities to be taken into consideration when designing control strategies. Both Rm and the intrinsic period of oscillation are shown to be highly sensitive to the mosquito's birth constant λm and the mosquito's feeding success probability pw. Control of λm can be achieved by spraying, eliminating breeding sites or moving them away from human habitats, while pw can be controlled via the use of mosquito repellant and insecticide-treated bed-nets. The disease threshold parameter R0 is shown to be highly sensitive to pw, and the intrinsic period of oscillation is also sensitive to the rate at which reproducing mosquitoes return to breeding sites. A global sensitivity and uncertainty analysis reveals that the ability of the mosquito to reproduce and uncertainties in the estimations of the rates at which exposed humans become infectious and infectious humans recover from malaria are critical in generating uncertainties in the disease classes.

Predicting uncertainty in future marine ice sheet volume using Bayesian statistical methods

NASA Astrophysics Data System (ADS)

Davis, A. D.

2015-12-01

The marine ice instability can trigger rapid retreat of marine ice streams. Recent observations suggest that marine ice systems in West Antarctica have begun retreating. However, unknown ice dynamics, computationally intensive mathematical models, and uncertain parameters in these models make predicting retreat rate and ice volume difficult. In this work, we fuse current observational data with ice stream/shelf models to develop probabilistic predictions of future grounded ice sheet volume. Given observational data (e.g., thickness, surface elevation, and velocity) and a forward model that relates uncertain parameters (e.g., basal friction and basal topography) to these observations, we use a Bayesian framework to define a posterior distribution over the parameters. A stochastic predictive model then propagates uncertainties in these parameters to uncertainty in a particular quantity of interest (QoI)---here, the volume of grounded ice at a specified future time. While the Bayesian approach can in principle characterize the posterior predictive distribution of the QoI, the computational cost of both the forward and predictive models makes this effort prohibitively expensive. To tackle this challenge, we introduce a new Markov chain Monte Carlo method that constructs convergent approximations of the QoI target density in an online fashion, yielding accurate characterizations of future ice sheet volume at significantly reduced computational cost.Our second goal is to attribute uncertainty in these Bayesian predictions to uncertainties in particular parameters. Doing so can help target data collection, for the purpose of constraining the parameters that contribute most strongly to uncertainty in the future volume of grounded ice. For instance, smaller uncertainties in parameters to which the QoI is highly sensitive may account for more variability in the prediction than larger uncertainties in parameters to which the QoI is less sensitive. We use global sensitivity analysis to help answer this question, and make the computation of sensitivity indices computationally tractable using a combination of polynomial chaos and Monte Carlo techniques.

Classification of bladder cancer cell lines using Raman spectroscopy: a comparison of excitation wavelength, sample substrate and statistical algorithms

NASA Astrophysics Data System (ADS)

Kerr, Laura T.; Adams, Aine; O'Dea, Shirley; Domijan, Katarina; Cullen, Ivor; Hennelly, Bryan M.

2014-05-01

Raman microspectroscopy can be applied to the urinary bladder for highly accurate classification and diagnosis of bladder cancer. This technique can be applied in vitro to bladder epithelial cells obtained from urine cytology or in vivo as an optical biopsy" to provide results in real-time with higher sensitivity and specificity than current clinical methods. However, there exists a high degree of variability across experimental parameters which need to be standardised before this technique can be utilized in an everyday clinical environment. In this study, we investigate different laser wavelengths (473 nm and 532 nm), sample substrates (glass, fused silica and calcium fluoride) and multivariate statistical methods in order to gain insight into how these various experimental parameters impact on the sensitivity and specificity of Raman cytology.

An Image Encryption Algorithm Utilizing Julia Sets and Hilbert Curves

PubMed Central

Sun, Yuanyuan; Chen, Lina; Xu, Rudan; Kong, Ruiqing

2014-01-01

Image encryption is an important and effective technique to protect image security. In this paper, a novel image encryption algorithm combining Julia sets and Hilbert curves is proposed. The algorithm utilizes Julia sets’ parameters to generate a random sequence as the initial keys and gets the final encryption keys by scrambling the initial keys through the Hilbert curve. The final cipher image is obtained by modulo arithmetic and diffuse operation. In this method, it needs only a few parameters for the key generation, which greatly reduces the storage space. Moreover, because of the Julia sets’ properties, such as infiniteness and chaotic characteristics, the keys have high sensitivity even to a tiny perturbation. The experimental results indicate that the algorithm has large key space, good statistical property, high sensitivity for the keys, and effective resistance to the chosen-plaintext attack. PMID:24404181

A new approach to identify the sensitivity and importance of physical parameters combination within numerical models using the Lund-Potsdam-Jena (LPJ) model as an example

NASA Astrophysics Data System (ADS)

Sun, Guodong; Mu, Mu

2017-05-01

An important source of uncertainty, which causes further uncertainty in numerical simulations, is that residing in the parameters describing physical processes in numerical models. Therefore, finding a subset among numerous physical parameters in numerical models in the atmospheric and oceanic sciences, which are relatively more sensitive and important parameters, and reducing the errors in the physical parameters in this subset would be a far more efficient way to reduce the uncertainties involved in simulations. In this context, we present a new approach based on the conditional nonlinear optimal perturbation related to parameter (CNOP-P) method. The approach provides a framework to ascertain the subset of those relatively more sensitive and important parameters among the physical parameters. The Lund-Potsdam-Jena (LPJ) dynamical global vegetation model was utilized to test the validity of the new approach in China. The results imply that nonlinear interactions among parameters play a key role in the identification of sensitive parameters in arid and semi-arid regions of China compared to those in northern, northeastern, and southern China. The uncertainties in the numerical simulations were reduced considerably by reducing the errors of the subset of relatively more sensitive and important parameters. The results demonstrate that our approach not only offers a new route to identify relatively more sensitive and important physical parameters but also that it is viable to then apply "target observations" to reduce the uncertainties in model parameters.

MOVES sensitivity analysis update : Transportation Research Board Summer Meeting 2012 : ADC-20 Air Quality Committee

DOT National Transportation Integrated Search

2012-01-01

OVERVIEW OF PRESENTATION : Evaluation Parameters : EPAs Sensitivity Analysis : Comparison to Baseline Case : MOVES Sensitivity Run Specification : MOVES Sensitivity Input Parameters : Results : Uses of Study

Sensitivity Analysis of Hydraulic Head to Locations of Model Boundaries

DOE PAGES

Lu, Zhiming

2018-01-30

Sensitivity analysis is an important component of many model activities in hydrology. Numerous studies have been conducted in calculating various sensitivities. Most of these sensitivity analysis focus on the sensitivity of state variables (e.g. hydraulic head) to parameters representing medium properties such as hydraulic conductivity or prescribed values such as constant head or flux at boundaries, while few studies address the sensitivity of the state variables to some shape parameters or design parameters that control the model domain. Instead, these shape parameters are typically assumed to be known in the model. In this study, based on the flow equation, wemore » derive the equation (and its associated initial and boundary conditions) for sensitivity of hydraulic head to shape parameters using continuous sensitivity equation (CSE) approach. These sensitivity equations can be solved numerically in general or analytically in some simplified cases. Finally, the approach has been demonstrated through two examples and the results are compared favorably to those from analytical solutions or numerical finite difference methods with perturbed model domains, while numerical shortcomings of the finite difference method are avoided.« less

Sensitivity Analysis of Hydraulic Head to Locations of Model Boundaries

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

Lu, Zhiming

Sensitivity analysis is an important component of many model activities in hydrology. Numerous studies have been conducted in calculating various sensitivities. Most of these sensitivity analysis focus on the sensitivity of state variables (e.g. hydraulic head) to parameters representing medium properties such as hydraulic conductivity or prescribed values such as constant head or flux at boundaries, while few studies address the sensitivity of the state variables to some shape parameters or design parameters that control the model domain. Instead, these shape parameters are typically assumed to be known in the model. In this study, based on the flow equation, wemore » derive the equation (and its associated initial and boundary conditions) for sensitivity of hydraulic head to shape parameters using continuous sensitivity equation (CSE) approach. These sensitivity equations can be solved numerically in general or analytically in some simplified cases. Finally, the approach has been demonstrated through two examples and the results are compared favorably to those from analytical solutions or numerical finite difference methods with perturbed model domains, while numerical shortcomings of the finite difference method are avoided.« less

Evolution of Geometric Sensitivity Derivatives from Computer Aided Design Models

NASA Technical Reports Server (NTRS)

Jones, William T.; Lazzara, David; Haimes, Robert

2010-01-01

The generation of design parameter sensitivity derivatives is required for gradient-based optimization. Such sensitivity derivatives are elusive at best when working with geometry defined within the solid modeling context of Computer-Aided Design (CAD) systems. Solid modeling CAD systems are often proprietary and always complex, thereby necessitating ad hoc procedures to infer parameter sensitivity. A new perspective is presented that makes direct use of the hierarchical associativity of CAD features to trace their evolution and thereby track design parameter sensitivity. In contrast to ad hoc methods, this method provides a more concise procedure following the model design intent and determining the sensitivity of CAD geometry directly to its respective defining parameters.

Association of pentraxin and high-sensitive C-reactive protein as inflammatory biomarkers in patients with chronic periodontitis and peripheral arterial disease.

PubMed

Boyapati, Ramanarayana; Chinthalapani, Srikanth; Ramisetti, Arpita; Salavadhi, Shyam Sunder; Ramachandran, Radhika

2018-01-01

Inflammation is a common feature of both peripheral artery disease (PAD) and periodontal disease. The aim of this study is to evaluate the relationship between PAD and periodontal disease by examining the levels of inflammatory cytokines, pentraxin-3 (PTX-3), and high-sensitive C-reactive protein from serum. A total of 50 patients were included in this cross-sectional study. Patients were divided into two groups: those with PAD (test group) and those with the non-PAD group (control group) based on ankle-brachial index values. Periodontal examinations and biochemical analysis for PTX-3 and high-sensitive C-reactive protein were performed to compare the two groups. All the obtained data were sent for statistical analyses using SPSS version 18. In the clinical parameters, there is statistically significant difference present between plaque index, clinical attachment loss, and periodontal inflammatory surface area with higher mean values in patients with PAD having periodontitis. There is statistical significant ( P < 0.01) difference in all biochemical parameters ( P < 0.05) considered in the study between PAD patients and non-PAD patients with higher mean values of total cholesterol (TC), low-density lipoprotein (LDL), high-sensitive C-reactive protein (hs-CRP), and PTX-3. PTX-3 and acute-phase cytokine such as hs-CRP can be regarded as one of the best indicators to show the association between the PAD and periodontitis followed by hs-CRP, TC, very LDL (VLDL), and LDL. However, high-density lipoprotein (HDL) is a poor indicator for its association with chronic periodontitis and PAD.

Predicting individual contrast sensitivity functions from acuity and letter contrast sensitivity measurements

PubMed Central

Thurman, Steven M.; Davey, Pinakin Gunvant; McCray, Kaydee Lynn; Paronian, Violeta; Seitz, Aaron R.

2016-01-01

Contrast sensitivity (CS) is widely used as a measure of visual function in both basic research and clinical evaluation. There is conflicting evidence on the extent to which measuring the full contrast sensitivity function (CSF) offers more functionally relevant information than a single measurement from an optotype CS test, such as the Pelli–Robson chart. Here we examine the relationship between functional CSF parameters and other measures of visual function, and establish a framework for predicting individual CSFs with effectively a zero-parameter model that shifts a standard-shaped template CSF horizontally and vertically according to independent measurements of high contrast acuity and letter CS, respectively. This method was evaluated for three different CSF tests: a chart test (CSV-1000), a computerized sine-wave test (M&S Sine Test), and a recently developed adaptive test (quick CSF). Subjects were 43 individuals with healthy vision or impairment too mild to be considered low vision (acuity range of −0.3 to 0.34 logMAR). While each test demands a slightly different normative template, results show that individual subject CSFs can be predicted with roughly the same precision as test–retest repeatability, confirming that individuals predominantly differ in terms of peak CS and peak spatial frequency. In fact, these parameters were sufficiently related to empirical measurements of acuity and letter CS to permit accurate estimation of the entire CSF of any individual with a deterministic model (zero free parameters). These results demonstrate that in many cases, measuring the full CSF may provide little additional information beyond letter acuity and contrast sensitivity. PMID:28006065

Uncertainty Quantification and Regional Sensitivity Analysis of Snow-related Parameters in the Canadian LAnd Surface Scheme (CLASS)

NASA Astrophysics Data System (ADS)

Badawy, B.; Fletcher, C. G.

2017-12-01

The parameterization of snow processes in land surface models is an important source of uncertainty in climate simulations. Quantifying the importance of snow-related parameters, and their uncertainties, may therefore lead to better understanding and quantification of uncertainty within integrated earth system models. However, quantifying the uncertainty arising from parameterized snow processes is challenging due to the high-dimensional parameter space, poor observational constraints, and parameter interaction. In this study, we investigate the sensitivity of the land simulation to uncertainty in snow microphysical parameters in the Canadian LAnd Surface Scheme (CLASS) using an uncertainty quantification (UQ) approach. A set of training cases (n=400) from CLASS is used to sample each parameter across its full range of empirical uncertainty, as determined from available observations and expert elicitation. A statistical learning model using support vector regression (SVR) is then constructed from the training data (CLASS output variables) to efficiently emulate the dynamical CLASS simulations over a much larger (n=220) set of cases. This approach is used to constrain the plausible range for each parameter using a skill score, and to identify the parameters with largest influence on the land simulation in CLASS at global and regional scales, using a random forest (RF) permutation importance algorithm. Preliminary sensitivity tests indicate that snow albedo refreshment threshold and the limiting snow depth, below which bare patches begin to appear, have the highest impact on snow output variables. The results also show a considerable reduction of the plausible ranges of the parameters values and hence reducing their uncertainty ranges, which can lead to a significant reduction of the model uncertainty. The implementation and results of this study will be presented and discussed in details.

A novel photonic crystal fiber Mach-Zehnder interferometer for enhancing refractive index measurement sensitivity

NASA Astrophysics Data System (ADS)

Zhao, Yong; Xia, Feng; Hu, Hai-feng; Chen, Mao-qing

2017-11-01

A novel refractive index (RI) sensor based on photonic crystal fiber Mach-Zehnder interferometer (PCF-MZI) was proposed. It was realized by cascading a section of PCF with half-taper collapse regions (HTCRs) between two single mode fibers (SMFs). The relationship between RI sensitivity and interference length of the PCF-MZI was firstly investigated. Both simulation and experimental results showed that RI sensitivity increased with the increase of interference length. Afterwards, influence of HTCR parameters on RI sensitivity was experimentally investigated to further improve the sensitivity. With intensification of arc discharge intensity in HTCR fabrication process, HTCR with larger maximum taper diameter and longer collapsed region length was obtained, which enhanced evanescent field of the PCF-MZI and then generated higher RI sensitivity. Consequently, a high RI sensitivity of 181.96 nm/refractive index unit (RIU) was achieved in the RI range of 1.3333-1.3574. Increasing arc discharge intensity in HTCR fabrication process has the capacity to improve RI sensitivity of PCF-MZI and meanwhile provides higher mechanical strength and longer sensor life compared to the traditional method of tapering the fiber, which improves the RI sensitivity at the cost of reducing mechanical strength of the sensor. This PCF-MZI was characterized by high RI sensitivity, ease of fabrication, high mechanical strength, and robustness.

A global sensitivity analysis of crop virtual water content

NASA Astrophysics Data System (ADS)

Tamea, S.; Tuninetti, M.; D'Odorico, P.; Laio, F.; Ridolfi, L.

2015-12-01

The concepts of virtual water and water footprint are becoming widely used in the scientific literature and they are proving their usefulness in a number of multidisciplinary contexts. With such growing interest a measure of data reliability (and uncertainty) is becoming pressing but, as of today, assessments of data sensitivity to model parameters, performed at the global scale, are not known. This contribution aims at filling this gap. Starting point of this study is the evaluation of the green and blue virtual water content (VWC) of four staple crops (i.e. wheat, rice, maize, and soybean) at a global high resolution scale. In each grid cell, the crop VWC is given by the ratio between the total crop evapotranspiration over the growing season and the crop actual yield, where evapotranspiration is determined with a detailed daily soil water balance and actual yield is estimated using country-based data, adjusted to account for spatial variability. The model provides estimates of the VWC at a 5x5 arc minutes and it improves on previous works by using the newest available data and including multi-cropping practices in the evaluation. The model is then used as the basis for a sensitivity analysis, in order to evaluate the role of model parameters in affecting the VWC and to understand how uncertainties in input data propagate and impact the VWC accounting. In each cell, small changes are exerted to one parameter at a time, and a sensitivity index is determined as the ratio between the relative change of VWC and the relative change of the input parameter with respect to its reference value. At the global scale, VWC is found to be most sensitive to the planting date, with a positive (direct) or negative (inverse) sensitivity index depending on the typical season of crop planting date. VWC is also markedly dependent on the length of the growing period, with an increase in length always producing an increase of VWC, but with higher spatial variability for rice than for other crops. The sensitivity to the reference evapotranspiration is highly variable with the considered crop and ranges from positive values (for soybean), to negative values (for rice and maize) and near-zero values for wheat. This variability reflects the different yield response factors of crops, which expresses their tolerance to water stress.

Parametric sensitivity analysis of an agro-economic model of management of irrigation water

NASA Astrophysics Data System (ADS)

El Ouadi, Ihssan; Ouazar, Driss; El Menyari, Younesse

2015-04-01

The current work aims to build an analysis and decision support tool for policy options concerning the optimal allocation of water resources, while allowing a better reflection on the issue of valuation of water by the agricultural sector in particular. Thus, a model disaggregated by farm type was developed for the rural town of Ait Ben Yacoub located in the east Morocco. This model integrates economic, agronomic and hydraulic data and simulates agricultural gross margin across in this area taking into consideration changes in public policy and climatic conditions, taking into account the competition for collective resources. To identify the model input parameters that influence over the results of the model, a parametric sensitivity analysis is performed by the "One-Factor-At-A-Time" approach within the "Screening Designs" method. Preliminary results of this analysis show that among the 10 parameters analyzed, 6 parameters affect significantly the objective function of the model, it is in order of influence: i) Coefficient of crop yield response to water, ii) Average daily gain in weight of livestock, iii) Exchange of livestock reproduction, iv) maximum yield of crops, v) Supply of irrigation water and vi) precipitation. These 6 parameters register sensitivity indexes ranging between 0.22 and 1.28. Those results show high uncertainties on these parameters that can dramatically skew the results of the model or the need to pay particular attention to their estimates. Keywords: water, agriculture, modeling, optimal allocation, parametric sensitivity analysis, Screening Designs, One-Factor-At-A-Time, agricultural policy, climate change.

Imperfection sensitivity of pressured buckling of biopolymer spherical shells

NASA Astrophysics Data System (ADS)

Zhang, Lei; Ru, C. Q.

2016-06-01

Imperfection sensitivity is essential for mechanical behavior of biopolymer shells [such as ultrasound contrast agents (UCAs) and spherical viruses] characterized by high geometric heterogeneity. In this work, an imperfection sensitivity analysis is conducted based on a refined shell model recently developed for spherical biopolymer shells of high structural heterogeneity and thickness nonuniformity. The influence of related parameters (including the ratio of radius to average shell thickness, the ratio of transverse shear modulus to in-plane shear modulus, and the ratio of effective bending thickness to average shell thickness) on imperfection sensitivity is examined for pressured buckling. Our results show that the ratio of effective bending thickness to average shell thickness has a major effect on the imperfection sensitivity, while the effect of the ratio of transverse shear modulus to in-plane shear modulus is usually negligible. For example, with physically realistic parameters for typical imperfect spherical biopolymer shells, the present model predicts that actual maximum external pressure could be reduced to as low as 60% of that of a perfect UCA spherical shell or 55%-65% of that of a perfect spherical virus shell, respectively. The moderate imperfection sensitivity of spherical biopolymer shells with physically realistic imperfection is largely attributed to the fact that biopolymer shells are relatively thicker (defined by smaller radius-to-thickness ratio) and therefore practically realistic imperfection amplitude normalized by thickness is very small as compared to that of classical elastic thin shells which have much larger radius-to-thickness ratio.

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.

Manufacturing error sensitivity analysis and optimal design method of cable-network antenna structures

NASA Astrophysics Data System (ADS)

Zong, Yali; Hu, Naigang; Duan, Baoyan; Yang, Guigeng; Cao, Hongjun; Xu, Wanye

2016-03-01

Inevitable manufacturing errors and inconsistency between assumed and actual boundary conditions can affect the shape precision and cable tensions of a cable-network antenna, and even result in failure of the structure in service. In this paper, an analytical sensitivity analysis method of the shape precision and cable tensions with respect to the parameters carrying uncertainty was studied. Based on the sensitivity analysis, an optimal design procedure was proposed to alleviate the effects of the parameters that carry uncertainty. The validity of the calculated sensitivities is examined by those computed by a finite difference method. Comparison with a traditional design method shows that the presented design procedure can remarkably reduce the influence of the uncertainties on the antenna performance. Moreover, the results suggest that especially slender front net cables, thick tension ties, relatively slender boundary cables and high tension level can improve the ability of cable-network antenna structures to resist the effects of the uncertainties on the antenna performance.

Chromatic and achromatic visual fields in relation to choroidal thickness in patients with high myopia: A pilot study.

PubMed

García-Domene, M C; Luque, M J; Díez-Ajenjo, M A; Desco-Esteban, M C; Artigas, J M

2018-02-01

To analyse the relationship between the choroidal thickness and the visual perception of patients with high myopia but without retinal damage. All patients underwent ophthalmic evaluation including a slit lamp examination and dilated ophthalmoscopy, subjective refraction, best corrected visual acuity, axial length, optical coherence tomography, contrast sensitivity function and sensitivity of the visual pathways. We included eleven eyes of subjects with high myopia. There are statistical correlations between choroidal thickness and almost all the contrast sensitivity values. The sensitivity of magnocellular and koniocellular pathways is the most affected, and the homogeneity of the sensibility of the magnocellular pathway depends on the choroidal thickness; when the thickness decreases, the sensitivity impairment extends from the center to the periphery of the visual field. Patients with high myopia without any fundus changes have visual impairments. We have found that choroidal thickness correlates with perceptual parameters such as contrast sensitivity or mean defect and pattern standard deviation of the visual fields of some visual pathways. Our study shows that the magnocellular and koniocellular pathways are the most affected, so that these patients have impairment in motion perception and blue-yellow contrast perception. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Performance of the high-sensitivity troponin assay in diagnosing acute myocardial infarction: systematic review and meta-analysis

PubMed Central

Al-Saleh, Ayman; Alazzoni, Ashraf; Al Shalash, Saleh; Ye, Chenglin; Mbuagbaw, Lawrence; Thabane, Lehana; Jolly, Sanjit S.

2014-01-01

Background High-sensitivity cardiac troponin assays have been adopted by many clinical centres worldwide; however, clinicians are uncertain how to interpret the results. We sought to assess the utility of these assays in diagnosing acute myocardial infarction (MI). Methods We carried out a systematic review and meta-analysis of studies comparing high-sensitivity with conventional assays of cardiac troponin levels among adults with suspected acute MI in the emergency department. We searched MEDLINE, EMBASE and Cochrane databases up to April 2013 and used bivariable random-effects modelling to obtain summary parameters for diagnostic accuracy. Results We identified 9 studies that assessed the use of high-sensitivity troponin T assays (n = 9186 patients). The summary sensitivity of these tests in diagnosing acute MI at presentation to the emergency department was estimated to be 0.94 (95% confidence interval [CI] 0.89–0.97); for conventional tests, it was 0.72 (95% CI 0.63–0.79). The summary specificity was 0.73 (95% CI 0.64–0.81) for the high-sensitivity assay compared with 0.95 (95% CI 0.93–0.97) for the conventional assay. The differences in estimates of the summary sensitivity and specificity between the high-sensitivity and conventional assays were statistically significant (p < 0.01). The area under the curve was similar for both tests carried out 3–6 hours after presentation. Three studies assessed the use of high-sensitivity troponin I assays and showed similar results. Interpretation Used at presentation to the emergency department, the high-sensitivity cardiac troponin assay has improved sensitivity, but reduced specificity, compared with the conventional troponin assay. With repeated measurements over 6 hours, the area under the curve is similar for both tests, indicating that the major advantage of the high-sensitivity test is early diagnosis. PMID:25295240

Progress Towards High-Sensitivity Arrays of Detectors of Sub-mm Radiation using Superconducting Tunnel Junctions with Radio-Frequency Single-Electron Transistors

NASA Technical Reports Server (NTRS)

Stevenson, T. R.; Hsieh, W.-T.; Li, M. J.; Stahle, C. M.; Wollack, E. J.; Schoelkopf, R. J.; Krebs, Carolyn (Technical Monitor)

2002-01-01

The science drivers for the SPIRIT/SPECS missions demand sensitive, fast, compact, low-power, large-format detector arrays for high resolution imaging and spectroscopy in the far infrared and submillimeter. Detector arrays with 10,000 pixels and sensitivity less than 10(exp 20)-20 W/Hz(exp 20)0.5 are needed. Antenna-coupled superconducting tunnel junction detectors with integrated rf single-electron transistor readout amplifiers have the potential for achieving this high level of sensitivity, and can take advantage of an rf multiplexing technique when forming arrays. The device consists of an antenna structure to couple radiation into a small superconducting volume and cause quasiparticle excitations, and a single-electron transistor to measure currents through tunnel junction contacts to the absorber volume. We will describe optimization of device parameters, and recent results on fabrication techniques for producing devices with high yield for detector arrays. We will also present modeling of expected saturation power levels, antenna coupling, and rf multiplexing schemes.

Physically-based modelling of high magnitude torrent events with uncertainty quantification

NASA Astrophysics Data System (ADS)

Wing-Yuen Chow, Candace; Ramirez, Jorge; Zimmermann, Markus; Keiler, Margreth

2017-04-01

High magnitude torrent events are associated with the rapid propagation of vast quantities of water and available sediment downslope where human settlements may be established. Assessing the vulnerability of built structures to these events is a part of consequence analysis, where hazard intensity is related to the degree of loss sustained. The specific contribution of the presented work describes a procedure simulate these damaging events by applying physically-based modelling and to include uncertainty information about the simulated results. This is a first step in the development of vulnerability curves based on several intensity parameters (i.e. maximum velocity, sediment deposition depth and impact pressure). The investigation process begins with the collection, organization and interpretation of detailed post-event documentation and photograph-based observation data of affected structures in three sites that exemplify the impact of highly destructive mudflows and flood occurrences on settlements in Switzerland. Hazard intensity proxies are then simulated with the physically-based FLO-2D model (O'Brien et al., 1993). Prior to modelling, global sensitivity analysis is conducted to support a better understanding of model behaviour, parameterization and the quantification of uncertainties (Song et al., 2015). The inclusion of information describing the degree of confidence in the simulated results supports the credibility of vulnerability curves developed with the modelled data. First, key parameters are identified and selected based on literature review. Truncated a priori ranges of parameter values were then defined by expert solicitation. Local sensitivity analysis is performed based on manual calibration to provide an understanding of the parameters relevant to the case studies of interest. Finally, automated parameter estimation is performed to comprehensively search for optimal parameter combinations and associated values, which are evaluated using the observed data collected in the first stage of the investigation. O'Brien, J.S., Julien, P.Y., Fullerton, W. T., 1993. Two-dimensional water flood and mudflow simulation. Journal of Hydraulic Engineering 119(2): 244-261.
 Song, X., Zhang, J., Zhan, C., Xuan, Y., Ye, M., Xu C., 2015. Global sensitivity analysis in hydrological modeling: Review of concepts, methods, theoretical frameworks, Journal of Hydrology 523: 739-757.

Parameter sensitivity and identifiability for a biogeochemical model of hypoxia in the northern Gulf of Mexico

EPA Science Inventory

Local sensitivity analyses and identifiable parameter subsets were used to describe numerical constraints of a hypoxia model for bottom waters of the northern Gulf of Mexico. The sensitivity of state variables differed considerably with parameter changes, although most variables ...

MOESHA: A genetic algorithm for automatic calibration and estimation of parameter uncertainty and sensitivity of hydrologic models

EPA Science Inventory

Characterization of uncertainty and sensitivity of model parameters is an essential and often overlooked facet of hydrological modeling. This paper introduces an algorithm called MOESHA that combines input parameter sensitivity analyses with a genetic algorithm calibration routin...

Effects of periodontal therapy on C-reactive protein and HDL in serum of subjects with periodontitis.

PubMed

Leite, Anne Carolina Eleutério; Carneiro, Valéria Martins de Araújo; Guimarães, Maria do Carmo Machado

2014-01-01

To investigate the effects of nonsurgical periodontal therapy on levels of high-sensitivity C-reactive protein in the sera and its association with body mass index and high density lipoprotein in subjects with severe periodontitis. Sera from 28 subjects (mean age: 34.36±6.24; 32% men) with severe periodontitis and 27 healthy controls (mean age: 33.18±6.42; 33% men) were collected prior to periodontal therapy. Blood samples were obtained from 23 subjects who completed therapy (9-12 months). Oral and systemic parameters such as the number of blood cells, glucose examination, lipid profile, and high-sensitivity C-reactive protein levels accessed by high-sensitivity immunonephelometry assay, were included. Before therapy, in the periodontitis group, the ratio of subjects with high-sensitivity C-reactive protein <0.3 mg/dL was statistically lower than in the control group (P<0.0216). After therapy, the ratio of subjects with high-sensitivity C-reactive protein <0.3 mg/dL was significantly higher (65.22%) (P<0.0339). The mean value for body mass index was statistically lower in subjects with high-sensitivity C-reactive protein <0.3 mg/dL (24.63±4.19), compared with those with high-sensitivity C-reactive protein >0.3 mg/dL (28.91±6.03) (P<0.0411). High density lipoprotein presented a mean value statistically higher after therapy (P<0.0027). In systemically healthy subjects with periodontitis, periodontal therapy was associated with decreased levels of circulating high-sensitivity C-reactive protein and increase of high density lipoprotein in serum. The clinical trial was registered at http://www.clinicaltrials.gov.br/, No. RBR-24T799.

High-resolution high-sensitivity and truly distributed optical frequency domain reflectometry for structural crack detection

NASA Astrophysics Data System (ADS)

Li, Wenhai; Bao, Xiaoyi; Chen, Liang

2014-05-01

Optical Frequency Domain Reflectometry (OFDR) with the use of polarization maintaining fiber (PMF) is capable of distinguishing strain and temperature, which is critical for successful field applications such as structural health monitoring (SHM) and smart material. Location-dependent measurement sensitivities along PMF are compensated by cross- and auto-correlations measurements of the spectra form a distributed parameter matrix. Simultaneous temperature and strain measurement accuracy of 1μstrain and 0.1°C is achieved with 2.5mm spatial resolution in over 180m range.

[Vulnerability to atmospheric and geomagnetic factors of the body functions in healthy male dwellers of the Russian North].

PubMed

Markov, A L; Zenchenko, T A; Solonin, Iu G; Boĭko, E R

2013-01-01

In April 2009 through to November 2011, a Mars-500 satellite study of Russian Northerners (Syktyvkar citizens) was performed using the standard ECOSAN-2007 procedure evaluating the atmospheric and geomagnetic susceptibility of the main body functional parameters. Seventeen essentially healthy men at the age of 25 to 46 years were investigated. Statistical data treatment included correlation and single-factor analysis of variance. Comparison of the number of statistical correlations of the sum of all functional parameters for participants showed that most often they were sensitive to atmospheric pressure, temperature, relative humidity and oxygen partial pressure (29-35 %), and geomagnetic activity (28 %). Dependence of the functional parameters on the rate of temperature and pressure change was weak and comparable with random coincidence (11 %). Among the hemodynamic parameters, systolic pressure was particularly sensitive to space and terrestrial weather variations (29 %); sensitivity of heart rate and diastolic pressure were determined in 25 % and 21 % of participants, respectively. Among the heart rate variability parameters (HRV) the largest number of statistically reliable correlations was determined for the centralization index (32 %) and high-frequency HRV spectrum (31 %); index of the regulatory systems activity was least dependable (19 %). Life index, maximal breath-holding and Ckibinskaya's cardiorespiratory index are also susceptible. Individual responses of the functional parameters to terrestrial and space weather changes varied with partidpants which points to the necessity of individual approach to evaluation of person's reactions to environmental changes.

Sensitivity of Honeybee Hygroreceptors to Slow Humidity Changes and Temporal Humidity Variation Detected in High Resolution by Mobile Measurements

PubMed Central

Tichy, Harald; Kallina, Wolfgang

2014-01-01

The moist cell and the dry cell on the antenna of the male honeybee were exposed to humidities slowly rising and falling at rates between –1.5%/s and +1.5%/s and at varying amplitudes in the 10 to 90% humidity range. The two cells respond to these slow humidity oscillations with oscillations in impulse frequency which depend not only on instantaneous humidity but also on the rate with which humidity changes. The impulse frequency of each cell was plotted as a function of these two parameters and regression planes were fitted to the data points of single oscillation periods. The regression slopes, which estimate sensitivity, rose with the amplitude of humidity oscillations. During large-amplitude oscillations, moist and dry cell sensitivity for instantaneous humidity and its rate of change was high. During small-amplitude oscillations, their sensitivity for both parameters was low, less exactly reflecting humidity fluctuations. Nothing is known about the spatial and temporal humidity variations a honeybee may encounter when flying through natural environments. Microclimatic parameters (absolute humidity, temperature, wind speed) were measured from an automobile traveling through different landscapes of Lower Austria. Landscape type affected extremes and mean values of humidity. Differences between peaks and troughs of humidity fluctuations were generally smaller in open grassy fields or deciduous forests than in edge habitats or forest openings. Overall, fluctuation amplitudes were small. In this part of the stimulus range, hygroreceptor sensitivity is not optimal for encoding instantaneous humidity and the rate of humidity change. It seems that honeybee's hygroreceptors are specialized for detecting large-amplitude fluctuations that are relevant for a specific behavior, namely, maintaining a sufficiently stable state of water balance. The results suggest that optimal sensitivity of both hygroreceptors is shaped not only by humidity oscillation amplitudes but also according to their impact on behavior. PMID:24901985

Method-independent, Computationally Frugal Convergence Testing for Sensitivity Analysis Techniques

NASA Astrophysics Data System (ADS)

Mai, J.; Tolson, B.

2017-12-01

The increasing complexity and runtime of environmental models lead to the current situation that the calibration of all model parameters or the estimation of all of their uncertainty is often computationally infeasible. Hence, techniques to determine the sensitivity of model parameters are used to identify most important parameters. All subsequent model calibrations or uncertainty estimation procedures focus then only on these subsets of parameters and are hence less computational demanding. While the examination of the convergence of calibration and uncertainty methods is state-of-the-art, the convergence of the sensitivity methods is usually not checked. If any, bootstrapping of the sensitivity results is used to determine the reliability of the estimated indexes. Bootstrapping, however, might as well become computationally expensive in case of large model outputs and a high number of bootstraps. We, therefore, present a Model Variable Augmentation (MVA) approach to check the convergence of sensitivity indexes without performing any additional model run. This technique is method- and model-independent. It can be applied either during the sensitivity analysis (SA) or afterwards. The latter case enables the checking of already processed sensitivity indexes. To demonstrate the method's independency of the convergence testing method, we applied it to two widely used, global SA methods: the screening method known as Morris method or Elementary Effects (Morris 1991) and the variance-based Sobol' method (Solbol' 1993). The new convergence testing method is first scrutinized using 12 analytical benchmark functions (Cuntz & Mai et al. 2015) where the true indexes of aforementioned three methods are known. This proof of principle shows that the method reliably determines the uncertainty of the SA results when different budgets are used for the SA. The results show that the new frugal method is able to test the convergence and therefore the reliability of SA results in an efficient way. The appealing feature of this new technique is the necessity of no further model evaluation and therefore enables checking of already processed sensitivity results. This is one step towards reliable and transferable, published sensitivity results.

Analysis of sensitivity of simulated recharge to selected parameters for seven watersheds modeled using the precipitation-runoff modeling system

USGS Publications Warehouse

Ely, D. Matthew

2006-01-01

Recharge is a vital component of the ground-water budget and methods for estimating it range from extremely complex to relatively simple. The most commonly used techniques, however, are limited by the scale of application. One method that can be used to estimate ground-water recharge includes process-based models that compute distributed water budgets on a watershed scale. These models should be evaluated to determine which model parameters are the dominant controls in determining ground-water recharge. Seven existing watershed models from different humid regions of the United States were chosen to analyze the sensitivity of simulated recharge to model parameters. Parameter sensitivities were determined using a nonlinear regression computer program to generate a suite of diagnostic statistics. The statistics identify model parameters that have the greatest effect on simulated ground-water recharge and that compare and contrast the hydrologic system responses to those parameters. Simulated recharge in the Lost River and Big Creek watersheds in Washington State was sensitive to small changes in air temperature. The Hamden watershed model in west-central Minnesota was developed to investigate the relations that wetlands and other landscape features have with runoff processes. Excess soil moisture in the Hamden watershed simulation was preferentially routed to wetlands, instead of to the ground-water system, resulting in little sensitivity of any parameters to recharge. Simulated recharge in the North Fork Pheasant Branch watershed, Wisconsin, demonstrated the greatest sensitivity to parameters related to evapotranspiration. Three watersheds were simulated as part of the Model Parameter Estimation Experiment (MOPEX). Parameter sensitivities for the MOPEX watersheds, Amite River, Louisiana and Mississippi, English River, Iowa, and South Branch Potomac River, West Virginia, were similar and most sensitive to small changes in air temperature and a user-defined flow routing parameter. Although the primary objective of this study was to identify, by geographic region, the importance of the parameter value to the simulation of ground-water recharge, the secondary objectives proved valuable for future modeling efforts. The value of a rigorous sensitivity analysis can (1) make the calibration process more efficient, (2) guide additional data collection, (3) identify model limitations, and (4) explain simulated results.

Sensitivity analysis of periodic errors in heterodyne interferometry

NASA Astrophysics Data System (ADS)

Ganguly, Vasishta; Kim, Nam Ho; Kim, Hyo Soo; Schmitz, Tony

2011-03-01

Periodic errors in heterodyne displacement measuring interferometry occur due to frequency mixing in the interferometer. These nonlinearities are typically characterized as first- and second-order periodic errors which cause a cyclical (non-cumulative) variation in the reported displacement about the true value. This study implements an existing analytical periodic error model in order to identify sensitivities of the first- and second-order periodic errors to the input parameters, including rotational misalignments of the polarizing beam splitter and mixing polarizer, non-orthogonality of the two laser frequencies, ellipticity in the polarizations of the two laser beams, and different transmission coefficients in the polarizing beam splitter. A local sensitivity analysis is first conducted to examine the sensitivities of the periodic errors with respect to each input parameter about the nominal input values. Next, a variance-based approach is used to study the global sensitivities of the periodic errors by calculating the Sobol' sensitivity indices using Monte Carlo simulation. The effect of variation in the input uncertainty on the computed sensitivity indices is examined. It is seen that the first-order periodic error is highly sensitive to non-orthogonality of the two linearly polarized laser frequencies, while the second-order error is most sensitive to the rotational misalignment between the laser beams and the polarizing beam splitter. A particle swarm optimization technique is finally used to predict the possible setup imperfections based on experimentally generated values for periodic errors.

Performance mapping of a 30 cm engineering model thruster

NASA Technical Reports Server (NTRS)

Poeschel, R. L.; Vahrenkamp, R. P.

1975-01-01

A 30 cm thruster representative of the engineering model design has been tested over a wide range of operating parameters to document performance characteristics such as electrical and propellant efficiencies, double ion and beam divergence thrust loss, component equilibrium temperatures, operational stability, etc. Data obtained show that optimum power throttling, in terms of maximum thruster efficiency, is not highly sensitive to parameter selection. Consequently, considerations of stability, discharge chamber erosion, thrust losses, etc. can be made the determining factors for parameter selection in power throttling operations. Options in parameter selection based on these considerations are discussed.

Quantifying Key Climate Parameter Uncertainties Using an Earth System Model with a Dynamic 3D Ocean

NASA Astrophysics Data System (ADS)

Olson, R.; Sriver, R. L.; Goes, M. P.; Urban, N.; Matthews, D.; Haran, M.; Keller, K.

2011-12-01

Climate projections hinge critically on uncertain climate model parameters such as climate sensitivity, vertical ocean diffusivity and anthropogenic sulfate aerosol forcings. Climate sensitivity is defined as the equilibrium global mean temperature response to a doubling of atmospheric CO2 concentrations. Vertical ocean diffusivity parameterizes sub-grid scale ocean vertical mixing processes. These parameters are typically estimated using Intermediate Complexity Earth System Models (EMICs) that lack a full 3D representation of the oceans, thereby neglecting the effects of mixing on ocean dynamics and meridional overturning. We improve on these studies by employing an EMIC with a dynamic 3D ocean model to estimate these parameters. We carry out historical climate simulations with the University of Victoria Earth System Climate Model (UVic ESCM) varying parameters that affect climate sensitivity, vertical ocean mixing, and effects of anthropogenic sulfate aerosols. We use a Bayesian approach whereby the likelihood of each parameter combination depends on how well the model simulates surface air temperature and upper ocean heat content. We use a Gaussian process emulator to interpolate the model output to an arbitrary parameter setting. We use Markov Chain Monte Carlo method to estimate the posterior probability distribution function (pdf) of these parameters. We explore the sensitivity of the results to prior assumptions about the parameters. In addition, we estimate the relative skill of different observations to constrain the parameters. We quantify the uncertainty in parameter estimates stemming from climate variability, model and observational errors. We explore the sensitivity of key decision-relevant climate projections to these parameters. We find that climate sensitivity and vertical ocean diffusivity estimates are consistent with previously published results. The climate sensitivity pdf is strongly affected by the prior assumptions, and by the scaling parameter for the aerosols. The estimation method is computationally fast and can be used with more complex models where climate sensitivity is diagnosed rather than prescribed. The parameter estimates can be used to create probabilistic climate projections using the UVic ESCM model in future studies.

Taking the Next Step: Using Water Quality Data in a Decision Support System for County, State, and Federal Land Managers

NASA Astrophysics Data System (ADS)

Raby, K. S.; Williams, M. W.

2004-12-01

Each passing year amplifies the demands placed on communities across the US in terms of population growth, increased tourism, and stresses resulting from escalated use. The conflicting concerns of recreational users, local citizens, environmentalists, and traditional economic interests cause land managers to contend with controversial decisions regarding development and protection of watersheds. Local history and culture, politics, economic goals, and science are all influential factors in land use decision making. Here we report on a scientific study to determine the sensitivity of alpine areas, and the adaptation of this study into a decision support framework. We use water quality data as an indicator of ecosystem health across a variety of alpine and subalpine landscapes, and input this information into a spatially-based decision support tool that planners can use to make informed land use decisions. We develop this tool in a case study in San Juan County, Colorado, a site chosen because its largest town, Silverton, is a small mountain community experiencing a recent surge in tourism and development, and its fragile high elevation locale makes it more sensitive to environmental changes. Extensive field surveys were conducted in priority drainages throughout the county to map the spatial distribution and aerial extent of landscape types during the summers of 2003 and 2004. Surface water samples were collected and analyzed for inorganic and organic solutes, and water quality values were associated with different land covers to enable sensitivity analysis at the landscape scale. Water quality results for each watershed were entered into a module linked to a geographic information system (GIS), which displays maps of sensitive areas based on criteria selected by the user. The decision support system initially incorporates two major water quality parameters: acid neutralizing capacity (ANC) and nitrate (NO3-) concentration, and several categories of sensitivity were created based on ANC and NO3- levels (e.g., pristine, slightly sensitive, moderately sensitive, highly sensitive, sensitive but unimpacted, disturbance impacted). We based threshold concentrations for these water quality parameters on first principles developed at the Niwot Ridge LTER site. Additional parameters such as specific conductance, base cation concentration, sulfate concentration, and dissolved organic carbon concentration may be added for a particular landscape type. Superimposed on this categorization, federal, state, and county planners are able to make decisions about the degree of potential impairment or enhancement produced by a particular project, or the maximum level of acceptable impairment to a particular area. Because water quality parameters are correlated with landscape types, the model returns a map of the watershed, partitioned by landscape type, presenting the sensitivity level of each area. This format provides land use managers with spatial criteria for project implementation.

Characterizing Graphene-modified Electrodes for Interfacing with Arduino®-based Devices.

PubMed

Arris, Farrah Aida; Ithnin, Mohamad Hafiz; Salim, Wan Wardatul Amani Wan

2016-08-01

Portable low-cost platform and sensing systems for identification and quantitative measurement are in high demand for various environmental monitoring applications, especially in field work. Quantifying parameters in the field requires both minimal sample handling and a device capable of performing measurements with high sensitivity and stability. Furthermore, the one-device-fits-all concept is useful for continuous monitoring of multiple parameters. Miniaturization of devices can be achieved by introducing graphene as part of the transducer in an electrochemical sensor. In this project, we characterize graphene deposition methods on glassy-carbon electrodes (GCEs) with the goal of interfacing with an Arduino-based user-friendly microcontroller. We found that a galvanostatic electrochemical method yields the highest peak current of 10 mA, promising a highly sensitive electrochemical sensor. An Atlas Scientific™ printed circuit board (PCB) was connected to an Arduino® microcontroller using a multi-circuit connection that can be interfaced with graphene-based electrochemical sensors for environmental monitoring.

A sensitivity analysis of process design parameters, commodity prices and robustness on the economics of odour abatement technologies.

PubMed

Estrada, José M; Kraakman, N J R Bart; Lebrero, Raquel; Muñoz, Raúl

2012-01-01

The sensitivity of the economics of the five most commonly applied odour abatement technologies (biofiltration, biotrickling filtration, activated carbon adsorption, chemical scrubbing and a hybrid technology consisting of a biotrickling filter coupled with carbon adsorption) towards design parameters and commodity prices was evaluated. Besides, the influence of the geographical location on the Net Present Value calculated for a 20 years lifespan (NPV20) of each technology and its robustness towards typical process fluctuations and operational upsets were also assessed. This comparative analysis showed that biological techniques present lower operating costs (up to 6 times) and lower sensitivity than their physical/chemical counterparts, with the packing material being the key parameter affecting their operating costs (40-50% of the total operating costs). The use of recycled or partially treated water (e.g. secondary effluent in wastewater treatment plants) offers an opportunity to significantly reduce costs in biological techniques. Physical/chemical technologies present a high sensitivity towards H2S concentration, which is an important drawback due to the fluctuating nature of malodorous emissions. The geographical analysis evidenced high NPV20 variations around the world for all the technologies evaluated, but despite the differences in wage and price levels, biofiltration and biotrickling filtration are always the most cost-efficient alternatives (NPV20). When, in an economical evaluation, the robustness is as relevant as the overall costs (NPV20), the hybrid technology would move up next to BTF as the most preferred technologies. Copyright © 2012 Elsevier Inc. All rights reserved.

Characterization and durability testing of plasma-sprayed zirconia-yttria and hafnia-yttria thermal barrier coatings. Part 2: Effect of spray parameters on the performance of several hafnia-yttria and zirconia-yttria coatings

NASA Technical Reports Server (NTRS)

Miller, Robert A.; Leissler, George W.

1993-01-01

This is the second of two reports which discuss initial experiments on thermal barrier coatings prepared and tested in newly upgraded plasma spray and burner rig test facilities at LeRC. The first report, part 1, describes experiments designed to establish the spray parameters for the baseline zirconia-yttria coating. Coating quality was judged primarily by the response to burner rig exposure, together with a variety of other characterization approaches including thermal diffusivity measurements. That portion of the study showed that the performance of the baseline NASA coating was not strongly sensitive to processing parameters. In this second part of the study, new hafnia-yttria coatings were evaluated with respect to both baseline and alternate zirconia-yttria coatings. The hafnia-yttria and the alternate zirconia-yttria coatings were very sensitive to plasma-spray parameters in that high-quality coatings were obtained only when specific parameters were used. The reasons for this important observation are not understood.

Optimization of processing parameters on the controlled growth of ZnO nanorod arrays for the performance improvement of solid-state dye-sensitized solar cells

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

Lee, Yi-Mu, E-mail: ymlee@nuu.edu.t; Yang, Hsi-Wen

2011-03-15

High-transparency and high quality ZnO nanorod arrays were grown on the ITO substrates by a two-step chemical bath deposition (CBD) method. The effects of processing parameters including reaction temperature (25-95 {sup o}C) and solution concentration (0.01-0.1 M) on the crystal growth, alignment, optical and electrical properties were systematically investigated. It has been found that these process parameters are critical for the growth, orientation and aspect ratio of the nanorod arrays, showing different structural and optical properties. Experimental results reveal that the hexagonal ZnO nanorod arrays prepared under reaction temperature of 95 {sup o}C and solution concentration of 0.03 M possessmore » highest aspect ratio of {approx}21, and show the well-aligned orientation and optimum optical properties. Moreover the ZnO nanorod arrays based heterojunction electrodes and the solid-state dye-sensitized solar cells (SS-DSSCs) were fabricated with an improved optoelectrical performance. -- Graphical abstract: The ZnO nanorod arrays demonstrate well-alignment, high aspect ratio (L/D{approx}21) and excellent optical transmittance by low-temperature chemical bath deposition (CBD). Display Omitted Research highlights: > Investigate the processing parameters of CBD on the growth of ZnO nanorod arrays. > Optimization of CBD process parameters: 0.03 M solution concentration and reaction temperature of 95 {sup o}C. > The prepared ZnO samples possess well-alignment and high aspect ratio (L/D{approx}21). > An n-ZnO/p-NiO heterojunction: great rectifying behavior and low leakage current. > SS-DSSC has J{sub SC} of 0.31 mA/cm{sup 2} and V{sub OC} of 590 mV, and an improved {eta} of 0.059%.« less

Highly sensitive biochemical sensor utilizing Bragg grating in submicron Si/SiO2 waveguides

NASA Astrophysics Data System (ADS)

Tripathi, Saurabh Mani; Kumar, Arun; Meunier, Jean-Pierre; Marin, Emmanuel

2009-05-01

We present a novel highly sensitive biochemical sensor based on a Bragg grating written in the cladding region of a submicron planar Si/SiO2 waveguide. Owing to the high refractive index contrast at the Si/SiO2 boundary the TM modal power is relatively high in low refractive index sensing region, leading to higher sensitivity in this configuration [1]. Waveguide parameters have been optimized to obtain maximum modal power in the sensing region (PSe) and an optimum core width corresponding to maximum sensitivity is found to exist while operating in TM mode configuration, as has been shown in Fig. 1. It has been found that operating in TM mode configuration at optimum core width the structure exhibits extremely high sensitivity, ~ 5×10-6 RIU - 1.35×10-6 RIU for the ambient refractive indices between 1.33 - 1.63. Such high sensitivities are typically attainable for Surface Plasmon Polariton (SPP) based biosensors and is much higher than any non SPP based sensors. Being free from any metallic layer or bulky prism the structure is easy to realize. Owing to its simple structure and small dimensions the proposed sensor can be integrated with planar lightwave circuits and could be used in handy lab-on-a-chip devices. The device may find application in highly sensitive biological/chemical sensing areas in civil and defense sectors where analyzing the samples at the point of need is required rather than sending it to some centralized laboratory.

Social stress reactivity alters reward and punishment learning

PubMed Central

Frank, Michael J.; Allen, John J. B.

2011-01-01

To examine how stress affects cognitive functioning, individual differences in trait vulnerability (punishment sensitivity) and state reactivity (negative affect) to social evaluative threat were examined during concurrent reinforcement learning. Lower trait-level punishment sensitivity predicted better reward learning and poorer punishment learning; the opposite pattern was found in more punishment sensitive individuals. Increasing state-level negative affect was directly related to punishment learning accuracy in highly punishment sensitive individuals, but these measures were inversely related in less sensitive individuals. Combined electrophysiological measurement, performance accuracy and computational estimations of learning parameters suggest that trait and state vulnerability to stress alter cortico-striatal functioning during reinforcement learning, possibly mediated via medio-frontal cortical systems. PMID:20453038

Social stress reactivity alters reward and punishment learning.

PubMed

Cavanagh, James F; Frank, Michael J; Allen, John J B

2011-06-01

To examine how stress affects cognitive functioning, individual differences in trait vulnerability (punishment sensitivity) and state reactivity (negative affect) to social evaluative threat were examined during concurrent reinforcement learning. Lower trait-level punishment sensitivity predicted better reward learning and poorer punishment learning; the opposite pattern was found in more punishment sensitive individuals. Increasing state-level negative affect was directly related to punishment learning accuracy in highly punishment sensitive individuals, but these measures were inversely related in less sensitive individuals. Combined electrophysiological measurement, performance accuracy and computational estimations of learning parameters suggest that trait and state vulnerability to stress alter cortico-striatal functioning during reinforcement learning, possibly mediated via medio-frontal cortical systems.

Experimental study on the measurement of uranium casting enrichment by time-dependent coincidence method

NASA Astrophysics Data System (ADS)

Xie, Wen-Xiong; Li, Jian-Sheng; Gong, Jian; Zhu, Jian-Yu; Huang, Po

2013-10-01

Based on the time-dependent coincidence method, a preliminary experiment has been performed on uranium metal castings with similar quality (about 8-10 kg) and shape (hemispherical shell) in different enrichments using neutron from Cf fast fission chamber and timing DT accelerator. Groups of related parameters can be obtained by analyzing the features of time-dependent coincidence counts between source-detector and two detectors to characterize the fission signal. These parameters have high sensitivity to the enrichment, the sensitivity coefficient (defined as (ΔR/Δm)/R¯) can reach 19.3% per kg of 235U. We can distinguish uranium castings with different enrichments to hold nuclear weapon verification.

Development of Standard Fuel Models in Boreal Forests of Northeast China through Calibration and Validation

PubMed Central

Cai, Longyan; He, Hong S.; Wu, Zhiwei; Lewis, Benard L.; Liang, Yu

2014-01-01

Understanding the fire prediction capabilities of fuel models is vital to forest fire management. Various fuel models have been developed in the Great Xing'an Mountains in Northeast China. However, the performances of these fuel models have not been tested for historical occurrences of wildfires. Consequently, the applicability of these models requires further investigation. Thus, this paper aims to develop standard fuel models. Seven vegetation types were combined into three fuel models according to potential fire behaviors which were clustered using Euclidean distance algorithms. Fuel model parameter sensitivity was analyzed by the Morris screening method. Results showed that the fuel model parameters 1-hour time-lag loading, dead heat content, live heat content, 1-hour time-lag SAV(Surface Area-to-Volume), live shrub SAV, and fuel bed depth have high sensitivity. Two main sensitive fuel parameters: 1-hour time-lag loading and fuel bed depth, were determined as adjustment parameters because of their high spatio-temporal variability. The FARSITE model was then used to test the fire prediction capabilities of the combined fuel models (uncalibrated fuel models). FARSITE was shown to yield an unrealistic prediction of the historical fire. However, the calibrated fuel models significantly improved the capabilities of the fuel models to predict the actual fire with an accuracy of 89%. Validation results also showed that the model can estimate the actual fires with an accuracy exceeding 56% by using the calibrated fuel models. Therefore, these fuel models can be efficiently used to calculate fire behaviors, which can be helpful in forest fire management. PMID:24714164

Investigation on Two Forms of Temperature-Sensing Parameters for Fluorescence Intensity Ratio Thermometry Based on Thermal Coupled Theory.

PubMed

Jia, Mochen; Liu, Guofeng; Sun, Zhen; Fu, Zuoling; Xu, Weiguo

2018-02-05

Absolute temperature sensitivity (S a ) reflects the precision of sensors that belong to the same mechanism, whereas relative temperature sensitivity (S r ) is used to compare sensors from different mechanisms. For the fluorescence intensity ratio (FIR) thermometry based on two thermally coupled energy levels of one rare earth (RE) ion, we define a new ratio as the temperature-sensing parameter that can vary greatly with temperature in some circumstances, which can obtain higher S a without changing S r . Further discussion is made on the conditions under which these two forms of temperature-sensing parameters can be used to achieve higher S a for biomedical temperature sensing. Based on the new ratio as the temperature-sensing parameter, the S a and S r of the BaTiO 3 : 0.01%Pr 3+ , 8%Yb 3+ nanoparticles at 313 K reach as high as 0.1380 K -1 and 1.23% K -1 , respectively. Similarly, the S a and S r of the BaTiO 3 : 1%Er 3+ , 3%Yb 3+ nanoparticles at 313 K are as high as 0.0413 K -1 and 1.05% K -1 , respectively. By flexibly choosing the two ratios as the temperature-sensing parameter, higher S a can be obtained at the target temperature, which means higher precision for the FIR thermometers.

Global sensitivity analysis for identifying important parameters of nitrogen nitrification and denitrification under model uncertainty and scenario uncertainty

NASA Astrophysics Data System (ADS)

Chen, Zhuowei; Shi, Liangsheng; Ye, Ming; Zhu, Yan; Yang, Jinzhong

2018-06-01

Nitrogen reactive transport modeling is subject to uncertainty in model parameters, structures, and scenarios. By using a new variance-based global sensitivity analysis method, this paper identifies important parameters for nitrogen reactive transport with simultaneous consideration of these three uncertainties. A combination of three scenarios of soil temperature and two scenarios of soil moisture creates a total of six scenarios. Four alternative models describing the effect of soil temperature and moisture content are used to evaluate the reduction functions used for calculating actual reaction rates. The results show that for nitrogen reactive transport problem, parameter importance varies substantially among different models and scenarios. Denitrification and nitrification process is sensitive to soil moisture content status rather than to the moisture function parameter. Nitrification process becomes more important at low moisture content and low temperature. However, the changing importance of nitrification activity with respect to temperature change highly relies on the selected model. Model-averaging is suggested to assess the nitrification (or denitrification) contribution by reducing the possible model error. Despite the introduction of biochemical heterogeneity or not, fairly consistent parameter importance rank is obtained in this study: optimal denitrification rate (Kden) is the most important parameter; reference temperature (Tr) is more important than temperature coefficient (Q10); empirical constant in moisture response function (m) is the least important one. Vertical distribution of soil moisture but not temperature plays predominant role controlling nitrogen reaction. This study provides insight into the nitrogen reactive transport modeling and demonstrates an effective strategy of selecting the important parameters when future temperature and soil moisture carry uncertainties or when modelers face with multiple ways of establishing nitrogen models.

Analysis and amelioration about the cross-sensitivity of a high resolution MOEMS accelerometer based on diffraction grating

NASA Astrophysics Data System (ADS)

Lu, Qianbo; Bai, Jian; Wang, Kaiwei; Lou, Shuqi; Jiao, Xufen; Han, Dandan

2016-10-01

Cross-sensitivity is a crucial parameter since it detrimentally affect the performance of an accelerometer, especially for a high resolution accelerometer. In this paper, a suite of analytical and finite-elements-method (FEM) models for characterizing the mechanism and features of the cross-sensitivity of a single-axis MOEMS accelerometer composed of a diffraction grating and a micromachined mechanical sensing chip are presented, which have not been systematically investigated yet. The mechanism and phenomena of the cross-sensitivity of this type MOEMS accelerometer based on diffraction grating differ quite a lot from the traditional ones owing to the identical sensing principle. By analyzing the models, some ameliorations and the modified design are put forward to suppress the cross-sensitivity. The modified design, achieved by double sides etching on a specific double-substrate-layer silicon-on-insulator (SOI) wafer, is validated to have a far smaller cross-sensitivity compared with the design previously reported in the literature. Moreover, this design can suppress the cross-sensitivity dramatically without compromising the acceleration sensitivity and resolution.

Comprehensive Monte-Carlo simulator for optimization of imaging parameters for high sensitivity detection of skin cancer at the THz

NASA Astrophysics Data System (ADS)

Ney, Michael; Abdulhalim, Ibrahim

2016-03-01

Skin cancer detection at its early stages has been the focus of a large number of experimental and theoretical studies during the past decades. Among these studies two prominent approaches presenting high potential are reflectometric sensing at the THz wavelengths region and polarimetric imaging techniques in the visible wavelengths. While THz radiation contrast agent and source of sensitivity to cancer related tissue alterations was considered to be mainly the elevated water content in the cancerous tissue, the polarimetric approach has been verified to enable cancerous tissue differentiation based on cancer induced structural alterations to the tissue. Combining THz with the polarimetric approach, which is considered in this study, is examined in order to enable higher detection sensitivity than previously pure reflectometric THz measurements. For this, a comprehensive MC simulation of radiative transfer in a complex skin tissue model fitted for the THz domain that considers the skin`s stratified structure, tissue material optical dispersion modeling, surface roughness, scatterers, and substructure organelles has been developed. Additionally, a narrow beam Mueller matrix differential analysis technique is suggested for assessing skin cancer induced changes in the polarimetric image, enabling the tissue model and MC simulation to be utilized for determining the imaging parameters resulting in maximal detection sensitivity.

Temperature-independent fiber-Bragg-grating-based atmospheric pressure sensor

NASA Astrophysics Data System (ADS)

Zhang, Zhiguo; Shen, Chunyan; Li, Luming

2018-03-01

Atmospheric pressure is an important way to achieve a high degree of measurement for modern aircrafts, moreover, it is also an indispensable parameter in the meteorological telemetry system. With the development of society, people are increasingly concerned about the weather. Accurate and convenient atmospheric pressure parameters can provide strong support for meteorological analysis. However, electronic atmospheric pressure sensors currently in application suffer from several shortcomings. After an analysis and discussion, we propose an innovative structural design, in which a vacuum membrane box and a temperature-independent strain sensor based on an equal strength cantilever beam structure and fiber Bragg grating (FBG) sensors are used. We provide experimental verification of that the atmospheric pressure sensor device has the characteristics of a simple structure, lack of an external power supply, automatic temperature compensation, and high sensitivity. The sensor system has good sensitivity, which can be up to 100 nm/MPa, and repeatability. In addition, the device exhibits desired hysteresis.

Theoretical Studies on Structures and Relative Stability for Polynitrohexaazaadamantanes

NASA Astrophysics Data System (ADS)

Xu, Xiao-juan; Xiao, He-ming; Wang, Gui-xiang; Ju, Xue-hai

2006-10-01

The density function theory at the B3LYP/6-31G* level was employed to study the structures, including the total energies (EZPE), the geometries, the oxygen balances (OB100), the dipole moments, of polynitro-hexaazaadamantanes (PNHAAs) and the potential candidates of high energy density compounds (HEDCs). The structural parameters of PNHAAs, such as the the maximum N—NO2 bond length (LBmax), the least N—N Mulliken population (BN—N), the least negative charge on the nitro group (QNO2) and OB100, were studied to predict their relative stability or sensitivity (the easiness for initiating a detonation, high sensitivity means low stability). It was found that the same conclusion was drawn from the four parameters. With the number of nitro groups increasing, the stabilities of these compounds decrease. OB100 failed in identifying the isomers, but the EZPE energy and the dipole moment were considered to give more reliable results for the isomers.

Sensitivity analysis of infectious disease models: methods, advances and their application

PubMed Central

Wu, Jianyong; Dhingra, Radhika; Gambhir, Manoj; Remais, Justin V.

2013-01-01

Sensitivity analysis (SA) can aid in identifying influential model parameters and optimizing model structure, yet infectious disease modelling has yet to adopt advanced SA techniques that are capable of providing considerable insights over traditional methods. We investigate five global SA methods—scatter plots, the Morris and Sobol’ methods, Latin hypercube sampling-partial rank correlation coefficient and the sensitivity heat map method—and detail their relative merits and pitfalls when applied to a microparasite (cholera) and macroparasite (schistosomaisis) transmission model. The methods investigated yielded similar results with respect to identifying influential parameters, but offered specific insights that vary by method. The classical methods differed in their ability to provide information on the quantitative relationship between parameters and model output, particularly over time. The heat map approach provides information about the group sensitivity of all model state variables, and the parameter sensitivity spectrum obtained using this method reveals the sensitivity of all state variables to each parameter over the course of the simulation period, especially valuable for expressing the dynamic sensitivity of a microparasite epidemic model to its parameters. A summary comparison is presented to aid infectious disease modellers in selecting appropriate methods, with the goal of improving model performance and design. PMID:23864497

Dynamical sensitivity control of a single-spin quantum sensor.

PubMed

Lazariev, Andrii; Arroyo-Camejo, Silvia; Rahane, Ganesh; Kavatamane, Vinaya Kumar; Balasubramanian, Gopalakrishnan

2017-07-26

The Nitrogen-Vacancy (NV) defect in diamond is a unique quantum system that offers precision sensing of nanoscale physical quantities at room temperature beyond the current state-of-the-art. The benchmark parameters for nanoscale magnetometry applications are sensitivity, spectral resolution, and dynamic range. Under realistic conditions the NV sensors controlled by conventional sensing schemes suffer from limitations of these parameters. Here we experimentally show a new method called dynamical sensitivity control (DYSCO) that boost the benchmark parameters and thus extends the practical applicability of the NV spin for nanoscale sensing. In contrast to conventional dynamical decoupling schemes, where π pulse trains toggle the spin precession abruptly, the DYSCO method allows for a smooth, analog modulation of the quantum probe's sensitivity. Our method decouples frequency selectivity and spectral resolution unconstrained over the bandwidth (1.85 MHz-392 Hz in our experiments). Using DYSCO we demonstrate high-accuracy NV magnetometry without |2π| ambiguities, an enhancement of the dynamic range by a factor of 4 · 10 3 , and interrogation times exceeding 2 ms in off-the-shelf diamond. In a broader perspective the DYSCO method provides a handle on the inherent dynamics of quantum systems offering decisive advantages for NV centre based applications notably in quantum information and single molecule NMR/MRI.

Temperature compensation via cooperative stability in protein degradation

NASA Astrophysics Data System (ADS)

Peng, Yuanyuan; Hasegawa, Yoshihiko; Noman, Nasimul; Iba, Hitoshi

2015-08-01

Temperature compensation is a notable property of circadian oscillators that indicates the insensitivity of the oscillator system's period to temperature changes; the underlying mechanism, however, is still unclear. We investigated the influence of protein dimerization and cooperative stability in protein degradation on the temperature compensation ability of two oscillators. Here, cooperative stability means that high-order oligomers are more stable than their monomeric counterparts. The period of an oscillator is affected by the parameters of the dynamic system, which in turn are influenced by temperature. We adopted the Repressilator and the Atkinson oscillator to analyze the temperature sensitivity of their periods. Phase sensitivity analysis was employed to evaluate the period variations of different models induced by perturbations to the parameters. Furthermore, we used experimental data provided by other studies to determine the reasonable range of parameter temperature sensitivity. We then applied the linear programming method to the oscillatory systems to analyze the effects of protein dimerization and cooperative stability on the temperature sensitivity of their periods, which reflects the ability of temperature compensation in circadian rhythms. Our study explains the temperature compensation mechanism for circadian clocks. Compared with the no-dimer mathematical model and linear model for protein degradation, our theoretical results show that the nonlinear protein degradation caused by cooperative stability is more beneficial for realizing temperature compensation of the circadian clock.

Signal noise ratio analysis and on-orbit performance estimation of a solar occultation Fourier transform spectrometer

NASA Astrophysics Data System (ADS)

Li, Bicen; Xu, Pengmei; Hou, Lizhou; Wang, Caiqin

2017-10-01

Taking the advantages of high spectral resolution, high sensitivity and wide spectral coverage, space borne Fourier transform infrared spectrometer (FTS) plays more and more important role in atmospheric composition sounding. The combination of solar occultation and FTS technique improves the sensitivity of instrument. To achieve both high spectral resolution and high signal to noise ratio (SNR), reasonable allocation and optimization for instrument parameters are the foundation and difficulty. The solar occultation FTS (SOFTS) is a high spectral resolution (0.03 cm-1) FTS operating from 2.4 to 13.3 μm (750-4100cm-1), which will determine the altitude profile information of typical 10-100km for temperature, pressure, and the volume mixing ratios for several dozens of atmospheric compositions. As key performance of SOFTS, SNR is crucially important to high accuracy retrieval of atmospheric composition, which is required to be no less than 100:1 at the radiance of 5800K blackbody. Based on the study of various parameters and its interacting principle, according to interference theory and operation principle of time modulated FTS, a simulation model of FTS SNR has been built, which considers satellite orbit, spectral radiometric features of sun and atmospheric composition, optical system, interferometer and its control system, measurement duration, detector sensitivity, noise of detector and electronic system and so on. According to the testing results of SNR at the illuminating of 1000 blackbody, the on-orbit SNR performance of SOFTS is estimated, which can meet the mission requirement.

Further comments on sensitivities, parameter estimation, and sampling design in one-dimensional analysis of solute transport in porous media

USGS Publications Warehouse

Knopman, Debra S.; Voss, Clifford I.

1988-01-01

Sensitivities of solute concentration to parameters associated with first-order chemical decay, boundary conditions, initial conditions, and multilayer transport are examined in one-dimensional analytical models of transient solute transport in porous media. A sensitivity is a change in solute concentration resulting from a change in a model parameter. Sensitivity analysis is important because minimum information required in regression on chemical data for the estimation of model parameters by regression is expressed in terms of sensitivities. Nonlinear regression models of solute transport were tested on sets of noiseless observations from known models that exceeded the minimum sensitivity information requirements. Results demonstrate that the regression models consistently converged to the correct parameters when the initial sets of parameter values substantially deviated from the correct parameters. On the basis of the sensitivity analysis, several statements may be made about design of sampling for parameter estimation for the models examined: (1) estimation of parameters associated with solute transport in the individual layers of a multilayer system is possible even when solute concentrations in the individual layers are mixed in an observation well; (2) when estimating parameters in a decaying upstream boundary condition, observations are best made late in the passage of the front near a time chosen by adding the inverse of an hypothesized value of the source decay parameter to the estimated mean travel time at a given downstream location; (3) estimation of a first-order chemical decay parameter requires observations to be made late in the passage of the front, preferably near a location corresponding to a travel time of √2 times the half-life of the solute; and (4) estimation of a parameter relating to spatial variability in an initial condition requires observations to be made early in time relative to passage of the solute front.

Periodical rocking long period gratings in PANDA fibers for high temperature and refractive index sensing

NASA Astrophysics Data System (ADS)

Jin, Wa; Bi, Wei-hong; Fu, Xing-hu; Fu, Guang-wei

2017-09-01

We report periodical rocking long period gratings (PR-LPGs) in PANDA fibers fabricated with CO2 laser. The PR-LPGs achieve very high coupling efficiency of 19 dB with 12 periods and a 3.5° twist angle in just one scanning cycle, which is much more effective than the conventional CO2 laser fabrication technique. This type of LPGs exhibits polarization-selective resonance dips which demonstrate different sensitivities to environmental parameters. The high temperature and external refractive index sensitivities are measured simultaneously, so it can be used as a wavelength-selective polarization filter and sensor.

Why morphology matters in birds and UAV's: How scale affects attitude wind sensitivity

NASA Astrophysics Data System (ADS)

Gamble, L. L.; Inman, D. J.

2017-11-01

Although natural fliers have been shown to morph their geometry to adapt to unfavorable wind loading, there exists heavy skepticism within the aviation community regarding the benefits and necessity of morphing aircraft technology. Here, we develop a vector derivation that characterizes how high winds affect the overall flight velocity and sideslip for both natural and manmade fliers. This derivation is formulated in such a way that only a single non-dimensional velocity parameter is needed to quantify the response. We show mathematically that in high winds, low-altitude fliers are more prone to substantial changes in the sideslip angle, struggle to maintain gliding velocity, and experience five times the peak sideslip sensitivity when compared to high-altitude fliers. In order to counteract these adverse changes, low-altitude fliers require a high degree of controllability which can be achieved through extreme morphological changes. The results presented here highlight the importance of integrating morphing concepts into future low-altitude aircraft designs and provide a formulation to help designers decide whether or not to pursue adaptive morphing technology based on a single readily determinable parameter.

Sensitivity to Rhythmic Parameters in Dyslexic Children: A Comparison of Hungarian and English

ERIC Educational Resources Information Center

Suranyi, Zsuzsanna; Csepe, Valeria; Richardson, Ulla; Thomson, Jennifer M.; Honbolygo, Ferenc; Goswami, Usha

2009-01-01

It has been proposed that sensitivity to the parameters underlying speech rhythm may be important in setting up well-specified phonological representations in the mental lexicon. However, different acoustic parameters may contribute differentially to rhythm and stress in different languages. Here we contrast sensitivity to one such cue, amplitude…

Generalized sensitivity analysis of the minimal model of the intravenous glucose tolerance test.

PubMed

Munir, Mohammad

2018-06-01

Generalized sensitivity functions characterize the sensitivity of the parameter estimates with respect to the nominal parameters. We observe from the generalized sensitivity analysis of the minimal model of the intravenous glucose tolerance test that the measurements of insulin, 62 min after the administration of the glucose bolus into the experimental subject's body, possess no information about the parameter estimates. The glucose measurements possess the information about the parameter estimates up to three hours. These observations have been verified by the parameter estimation of the minimal model. The standard errors of the estimates and crude Monte Carlo process also confirm this observation. Copyright © 2018 Elsevier Inc. All rights reserved.

High Sensitivity Refractive Index Sensor Based on Dual-Core Photonic Crystal Fiber with Hexagonal Lattice.

PubMed

Wang, Haiyang; Yan, Xin; Li, Shuguang; An, Guowen; Zhang, Xuenan

2016-10-08

A refractive index sensor based on dual-core photonic crystal fiber (PCF) with hexagonal lattice is proposed. The effects of geometrical parameters of the PCF on performances of the sensor are investigated by using the finite element method (FEM). Two fiber cores are separated by two air holes filled with the analyte whose refractive index is in the range of 1.33-1.41. Numerical simulation results show that the highest sensitivity can be up to 22,983 nm/RIU(refractive index unit) when the analyte refractive index is 1.41. The lowest sensitivity can reach to 21,679 nm/RIU when the analyte refractive index is 1.33. The sensor we proposed has significant advantages in the field of biomolecule detection as it provides a wide-range of detection with high sensitivity.

High Sensitivity Refractive Index Sensor Based on Dual-Core Photonic Crystal Fiber with Hexagonal Lattice

PubMed Central

Wang, Haiyang; Yan, Xin; Li, Shuguang; An, Guowen; Zhang, Xuenan

2016-01-01

A refractive index sensor based on dual-core photonic crystal fiber (PCF) with hexagonal lattice is proposed. The effects of geometrical parameters of the PCF on performances of the sensor are investigated by using the finite element method (FEM). Two fiber cores are separated by two air holes filled with the analyte whose refractive index is in the range of 1.33–1.41. Numerical simulation results show that the highest sensitivity can be up to 22,983 nm/RIU(refractive index unit) when the analyte refractive index is 1.41. The lowest sensitivity can reach to 21,679 nm/RIU when the analyte refractive index is 1.33. The sensor we proposed has significant advantages in the field of biomolecule detection as it provides a wide-range of detection with high sensitivity. PMID:27740607

All-optical on-chip sensor for high refractive index sensing

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

Liu, Yazhao; Kavli Institute of Nanoscience, Delft University of Technology, Lorentzweg 1, 2628 CJ, Delft; Salemink, H. W. M., E-mail: H.Salemink@science.ru.nl

2015-01-19

A highly sensitive sensor design based on two-dimensional photonic crystal cavity is demonstrated. The geometric structure of the cavity is modified to gain a high quality factor, which enables a sensitive refractive index sensing. A group of slots with optimized parameters is created in the cavity. The existence of the slots enhances the light-matter interactions between confined photons and analytes. The interactions result in large wavelength shifts in the transmission spectra and are denoted by high sensitivities. Experiments show that a change in refractive index of Δn ∼ 0.12 between water and oil sample 1 causes a spectral shift of 23.5 nm, andmore » the spectral shift between two oil samples is 5.1 nm for Δn ∼ 0.039. These results are in good agreement with simulations, which are 21.3 and 7.39 nm for the same index changes.« less

Modeling sugar cane yield with a process-based model from site to continental scale: uncertainties arising from model structure and parameter values

NASA Astrophysics Data System (ADS)

Valade, A.; Ciais, P.; Vuichard, N.; Viovy, N.; Huth, N.; Marin, F.; Martiné, J.-F.

2014-01-01

Agro-Land Surface Models (agro-LSM) have been developed from the integration of specific crop processes into large-scale generic land surface models that allow calculating the spatial distribution and variability of energy, water and carbon fluxes within the soil-vegetation-atmosphere continuum. When developing agro-LSM models, a particular attention must be given to the effects of crop phenology and management on the turbulent fluxes exchanged with the atmosphere, and the underlying water and carbon pools. A part of the uncertainty of Agro-LSM models is related to their usually large number of parameters. In this study, we quantify the parameter-values uncertainty in the simulation of sugar cane biomass production with the agro-LSM ORCHIDEE-STICS, using a multi-regional approach with data from sites in Australia, La Réunion and Brazil. In ORCHIDEE-STICS, two models are chained: STICS, an agronomy model that calculates phenology and management, and ORCHIDEE, a land surface model that calculates biomass and other ecosystem variables forced by STICS' phenology. First, the parameters that dominate the uncertainty of simulated biomass at harvest date are determined through a screening of 67 different parameters of both STICS and ORCHIDEE on a multi-site basis. Secondly, the uncertainty of harvested biomass attributable to those most sensitive parameters is quantified and specifically attributed to either STICS (phenology, management) or to ORCHIDEE (other ecosystem variables including biomass) through distinct Monte-Carlo runs. The uncertainty on parameter values is constrained using observations by calibrating the model independently at seven sites. In a third step, a sensitivity analysis is carried out by varying the most sensitive parameters to investigate their effects at continental scale. A Monte-Carlo sampling method associated with the calculation of Partial Ranked Correlation Coefficients is used to quantify the sensitivity of harvested biomass to input parameters on a continental scale across the large regions of intensive sugar cane cultivation in Australia and Brazil. Ten parameters driving most of the uncertainty in the ORCHIDEE-STICS modeled biomass at the 7 sites are identified by the screening procedure. We found that the 10 most sensitive parameters control phenology (maximum rate of increase of LAI) and root uptake of water and nitrogen (root profile and root growth rate, nitrogen stress threshold) in STICS, and photosynthesis (optimal temperature of photosynthesis, optimal carboxylation rate), radiation interception (extinction coefficient), and transpiration and respiration (stomatal conductance, growth and maintenance respiration coefficients) in ORCHIDEE. We find that the optimal carboxylation rate and photosynthesis temperature parameters contribute most to the uncertainty in harvested biomass simulations at site scale. The spatial variation of the ranked correlation between input parameters and modeled biomass at harvest is well explained by rain and temperature drivers, suggesting climate-mediated different sensitivities of modeled sugar cane yield to the model parameters, for Australia and Brazil. This study reveals the spatial and temporal patterns of uncertainty variability for a highly parameterized agro-LSM and calls for more systematic uncertainty analyses of such models.

Modeling sugarcane yield with a process-based model from site to continental scale: uncertainties arising from model structure and parameter values

NASA Astrophysics Data System (ADS)

Valade, A.; Ciais, P.; Vuichard, N.; Viovy, N.; Caubel, A.; Huth, N.; Marin, F.; Martiné, J.-F.

2014-06-01

Agro-land surface models (agro-LSM) have been developed from the integration of specific crop processes into large-scale generic land surface models that allow calculating the spatial distribution and variability of energy, water and carbon fluxes within the soil-vegetation-atmosphere continuum. When developing agro-LSM models, particular attention must be given to the effects of crop phenology and management on the turbulent fluxes exchanged with the atmosphere, and the underlying water and carbon pools. A part of the uncertainty of agro-LSM models is related to their usually large number of parameters. In this study, we quantify the parameter-values uncertainty in the simulation of sugarcane biomass production with the agro-LSM ORCHIDEE-STICS, using a multi-regional approach with data from sites in Australia, La Réunion and Brazil. In ORCHIDEE-STICS, two models are chained: STICS, an agronomy model that calculates phenology and management, and ORCHIDEE, a land surface model that calculates biomass and other ecosystem variables forced by STICS phenology. First, the parameters that dominate the uncertainty of simulated biomass at harvest date are determined through a screening of 67 different parameters of both STICS and ORCHIDEE on a multi-site basis. Secondly, the uncertainty of harvested biomass attributable to those most sensitive parameters is quantified and specifically attributed to either STICS (phenology, management) or to ORCHIDEE (other ecosystem variables including biomass) through distinct Monte Carlo runs. The uncertainty on parameter values is constrained using observations by calibrating the model independently at seven sites. In a third step, a sensitivity analysis is carried out by varying the most sensitive parameters to investigate their effects at continental scale. A Monte Carlo sampling method associated with the calculation of partial ranked correlation coefficients is used to quantify the sensitivity of harvested biomass to input parameters on a continental scale across the large regions of intensive sugarcane cultivation in Australia and Brazil. The ten parameters driving most of the uncertainty in the ORCHIDEE-STICS modeled biomass at the 7 sites are identified by the screening procedure. We found that the 10 most sensitive parameters control phenology (maximum rate of increase of LAI) and root uptake of water and nitrogen (root profile and root growth rate, nitrogen stress threshold) in STICS, and photosynthesis (optimal temperature of photosynthesis, optimal carboxylation rate), radiation interception (extinction coefficient), and transpiration and respiration (stomatal conductance, growth and maintenance respiration coefficients) in ORCHIDEE. We find that the optimal carboxylation rate and photosynthesis temperature parameters contribute most to the uncertainty in harvested biomass simulations at site scale. The spatial variation of the ranked correlation between input parameters and modeled biomass at harvest is well explained by rain and temperature drivers, suggesting different climate-mediated sensitivities of modeled sugarcane yield to the model parameters, for Australia and Brazil. This study reveals the spatial and temporal patterns of uncertainty variability for a highly parameterized agro-LSM and calls for more systematic uncertainty analyses of such models.

Impact of the time scale of model sensitivity response on coupled model parameter estimation

NASA Astrophysics Data System (ADS)

Liu, Chang; Zhang, Shaoqing; Li, Shan; Liu, Zhengyu

2017-11-01

That a model has sensitivity responses to parameter uncertainties is a key concept in implementing model parameter estimation using filtering theory and methodology. Depending on the nature of associated physics and characteristic variability of the fluid in a coupled system, the response time scales of a model to parameters can be different, from hourly to decadal. Unlike state estimation, where the update frequency is usually linked with observational frequency, the update frequency for parameter estimation must be associated with the time scale of the model sensitivity response to the parameter being estimated. Here, with a simple coupled model, the impact of model sensitivity response time scales on coupled model parameter estimation is studied. The model includes characteristic synoptic to decadal scales by coupling a long-term varying deep ocean with a slow-varying upper ocean forced by a chaotic atmosphere. Results show that, using the update frequency determined by the model sensitivity response time scale, both the reliability and quality of parameter estimation can be improved significantly, and thus the estimated parameters make the model more consistent with the observation. These simple model results provide a guideline for when real observations are used to optimize the parameters in a coupled general circulation model for improving climate analysis and prediction initialization.

Utilization of Short-Simulations for Tuning High-Resolution Climate Model

NASA Astrophysics Data System (ADS)

Lin, W.; Xie, S.; Ma, P. L.; Rasch, P. J.; Qian, Y.; Wan, H.; Ma, H. Y.; Klein, S. A.

2016-12-01

Many physical parameterizations in atmospheric models are sensitive to resolution. Tuning the models that involve a multitude of parameters at high resolution is computationally expensive, particularly when relying primarily on multi-year simulations. This work describes a complementary set of strategies for tuning high-resolution atmospheric models, using ensembles of short simulations to reduce the computational cost and elapsed time. Specifically, we utilize the hindcast approach developed through the DOE Cloud Associated Parameterization Testbed (CAPT) project for high-resolution model tuning, which is guided by a combination of short (< 10 days ) and longer ( 1 year) Perturbed Parameters Ensemble (PPE) simulations at low resolution to identify model feature sensitivity to parameter changes. The CAPT tests have been found to be effective in numerous previous studies in identifying model biases due to parameterized fast physics, and we demonstrate that it is also useful for tuning. After the most egregious errors are addressed through an initial "rough" tuning phase, longer simulations are performed to "hone in" on model features that evolve over longer timescales. We explore these strategies to tune the DOE ACME (Accelerated Climate Modeling for Energy) model. For the ACME model at 0.25° resolution, it is confirmed that, given the same parameters, major biases in global mean statistics and many spatial features are consistent between Atmospheric Model Intercomparison Project (AMIP)-type simulations and CAPT-type hindcasts, with just a small number of short-term simulations for the latter over the corresponding season. The use of CAPT hindcasts to find parameter choice for the reduction of large model biases dramatically improves the turnaround time for the tuning at high resolution. Improvement seen in CAPT hindcasts generally translates to improved AMIP-type simulations. An iterative CAPT-AMIP tuning approach is therefore adopted during each major tuning cycle, with the former to survey the likely responses and narrow the parameter space, and the latter to verify the results in climate context along with assessment in greater detail once an educated set of parameter choice is selected. Limitations on using short-term simulations for tuning climate model are also discussed.

Searches for millisecond pulsations in low-mass X-ray binaries

NASA Technical Reports Server (NTRS)

Wood, K. S.; Hertz, P.; Norris, J. P.; Vaughan, B. A.; Michelson, P. F.; Mitsuda, K.; Lewin, W. H. G.; Van Paradijs, J.; Penninx, W.; Van Der Klis, M.

1991-01-01

High-sensitivity search techniques for millisecond periods are presented and applied to data from the Japanese satellite Ginga and HEAO 1. The search is optimized for pulsed signals whose period, drift rate, and amplitude conform with what is expected for low-class X-ray binary (LMXB) sources. Consideration is given to how the current understanding of LMXBs guides the search strategy and sets these parameter limits. An optimized one-parameter coherence recovery technique (CRT) developed for recovery of phase coherence is presented. This technique provides a large increase in sensitivity over the method of incoherent summation of Fourier power spectra. The range of spin periods expected from LMXB phenomenology is discussed, the necessary constraints on the application of CRT are described in terms of integration time and orbital parameters, and the residual power unrecovered by the quadratic approximation for realistic cases is estimated.

A mixture theory model of fluid and solute transport in the microvasculature of normal and malignant tissues. II: Factor sensitivity analysis, calibration, and validation.

PubMed

Schuff, M M; Gore, J P; Nauman, E A

2013-12-01

The treatment of cancerous tumors is dependent upon the delivery of therapeutics through the blood by means of the microcirculation. Differences in the vasculature of normal and malignant tissues have been recognized, but it is not fully understood how these differences affect transport and the applicability of existing mathematical models has been questioned at the microscale due to the complex rheology of blood and fluid exchange with the tissue. In addition to determining an appropriate set of governing equations it is necessary to specify appropriate model parameters based on physiological data. To this end, a two stage sensitivity analysis is described which makes it possible to determine the set of parameters most important to the model's calibration. In the first stage, the fluid flow equations are examined and a sensitivity analysis is used to evaluate the importance of 11 different model parameters. Of these, only four substantially influence the intravascular axial flow providing a tractable set that could be calibrated using red blood cell velocity data from the literature. The second stage also utilizes a sensitivity analysis to evaluate the importance of 14 model parameters on extravascular flux. Of these, six exhibit high sensitivity and are integrated into the model calibration using a response surface methodology and experimental intra- and extravascular accumulation data from the literature (Dreher et al. in J Natl Cancer Inst 98(5):335-344, 2006). The model exhibits good agreement with the experimental results for both the mean extravascular concentration and the penetration depth as a function of time for inert dextran over a wide range of molecular weights.

An Improved Interferometric Calibration Method Based on Independent Parameter Decomposition

NASA Astrophysics Data System (ADS)

Fan, J.; Zuo, X.; Li, T.; Chen, Q.; Geng, X.

2018-04-01

Interferometric SAR is sensitive to earth surface undulation. The accuracy of interferometric parameters plays a significant role in precise digital elevation model (DEM). The interferometric calibration is to obtain high-precision global DEM by calculating the interferometric parameters using ground control points (GCPs). However, interferometric parameters are always calculated jointly, making them difficult to decompose precisely. In this paper, we propose an interferometric calibration method based on independent parameter decomposition (IPD). Firstly, the parameters related to the interferometric SAR measurement are determined based on the three-dimensional reconstruction model. Secondly, the sensitivity of interferometric parameters is quantitatively analyzed after the geometric parameters are completely decomposed. Finally, each interferometric parameter is calculated based on IPD and interferometric calibration model is established. We take Weinan of Shanxi province as an example and choose 4 TerraDEM-X image pairs to carry out interferometric calibration experiment. The results show that the elevation accuracy of all SAR images is better than 2.54 m after interferometric calibration. Furthermore, the proposed method can obtain the accuracy of DEM products better than 2.43 m in the flat area and 6.97 m in the mountainous area, which can prove the correctness and effectiveness of the proposed IPD based interferometric calibration method. The results provide a technical basis for topographic mapping of 1 : 50000 and even larger scale in the flat area and mountainous area.

Global Sensitivity Analysis for Identifying Important Parameters of Nitrogen Nitrification and Denitrification under Model and Scenario Uncertainties

NASA Astrophysics Data System (ADS)

Ye, M.; Chen, Z.; Shi, L.; Zhu, Y.; Yang, J.

2017-12-01

Nitrogen reactive transport modeling is subject to uncertainty in model parameters, structures, and scenarios. While global sensitivity analysis is a vital tool for identifying the parameters important to nitrogen reactive transport, conventional global sensitivity analysis only considers parametric uncertainty. This may result in inaccurate selection of important parameters, because parameter importance may vary under different models and modeling scenarios. By using a recently developed variance-based global sensitivity analysis method, this paper identifies important parameters with simultaneous consideration of parametric uncertainty, model uncertainty, and scenario uncertainty. In a numerical example of nitrogen reactive transport modeling, a combination of three scenarios of soil temperature and two scenarios of soil moisture leads to a total of six scenarios. Four alternative models are used to evaluate reduction functions used for calculating actual rates of nitrification and denitrification. The model uncertainty is tangled with scenario uncertainty, as the reduction functions depend on soil temperature and moisture content. The results of sensitivity analysis show that parameter importance varies substantially between different models and modeling scenarios, which may lead to inaccurate selection of important parameters if model and scenario uncertainties are not considered. This problem is avoided by using the new method of sensitivity analysis in the context of model averaging and scenario averaging. The new method of sensitivity analysis can be applied to other problems of contaminant transport modeling when model uncertainty and/or scenario uncertainty are present.

Considerations in high resolution skeletal muscle DTI using single-shot EPI with stimulated echo preparation and SENSE

PubMed Central

Karampinos, Dimitrios C.; Banerjee, Suchandrima; King, Kevin F.; Link, Thomas M.; Majumdar, Sharmila

2011-01-01

Previous studies have shown that skeletal muscle diffusion tensor imaging (DTI) can non-invasively probe changes in the muscle fiber architecture and microstructure in diseased and damaged muscles. However, DTI fiber reconstruction in small muscles and in muscle regions close to aponeuroses and tendons remains challenging because of partial volume effects. Increasing the spatial resolution of skeletal muscle single-shot diffusion weighted (DW)-EPI can be hindered by the inherently low SNR of muscle DW-EPI due to the short muscle T2 and the high sensitivity of single-shot EPI to off-resonance effects and T2* blurring. In the present work, eddy-current compensated diffusion-weighted stimulated echo preparation is combined with sensitivity encoding (SENSE) to maintain good SNR properties and reduce the sensitivity to distortions and T2* blurring in high resolution skeletal muscle single-shot DW-EPI. An analytical framework is developed for optimizing the reduction factor and diffusion weighting time to achieve maximum SNR. Arguments for the selection of the experimental parameters are then presented considering the compromise between SNR, B0-induced distortions, T2* blurring effects and tissue incoherent motion effects. Based on the selected parameters in a high resolution skeletal muscle single-shot DW-EPI protocol, imaging protocols at lower acquisition matrix sizes are defined with matched bandwidth in the phase-encoding direction and SNR. In vivo results show that high resolution skeletal muscle DTI with minimized sensitivity to geometric distortions and T2* blurring is feasible using the proposed methodology. In particular, a significant benefit is demonstrated from reducing partial volume effects on resolving multi-pennate muscles and muscles with small cross sections in calf muscle DTI. PMID:22081519

Regional body fat distribution and metabolic profile in postmenopausal women.

PubMed

Piché, Marie-Eve; Lapointe, Annie; Weisnagel, S John; Corneau, Louise; Nadeau, André; Bergeron, Jean; Lemieux, Simone

2008-08-01

The aim of the study was to examine how body fat distribution variables were associated with metabolic parameters in a sample of 113 postmenopausal women not receiving hormone therapy (56.9 +/- 4.4 years, 28.4 +/- 5.1 kg/m(2)). Body fat distribution variables (visceral adipose tissue [AT], subcutaneous AT, and total midthigh AT) were measured using computed tomography; body fat mass was assessed by hydrostatic weighing; insulin sensitivity was determined with the euglycemic-hyperinsulinemic clamp; fasting plasma glucose (FPG) and 2-hour plasma glucose (2hPG) concentrations were measured by a 75-g oral glucose load; and (high-sensitivity) C-reactive protein (hs-CRP) was measured using a highly sensitive assay. After controlling for fat mass, visceral AT was positively associated with plasma triglyceride, hs-CRP, FPG, and 2hPG, and negatively associated with high-density lipoprotein cholesterol (HDL-C) and insulin sensitivity. Total midthigh AT was negatively associated with apolipoprotein B, FPG, and 2hPG, and positively associated with insulin sensitivity. Stepwise multiple regression analyses including abdominal visceral AT, subcutaneous AT and total midthigh AT as independent variables showed that abdominal visceral AT best predicted the variance in plasma triglyceride, HDL-C, low-density lipoprotein peak particle size, hs-CRP, FPG, 2hPG, and insulin sensitivity. Abdominal subcutaneous AT was a significant predictor of only insulin sensitivity, whereas total midthigh AT predicted HDL-C, low-density lipoprotein peak particle size, and apolipoprotein B. These multivariate analyses also indicated that total midthigh AT was favorably related to these outcomes, whereas abdominal visceral AT and subcutaneous AT were unfavorably related. These results confirmed that abdominal visceral fat is a critical correlate of metabolic parameters in postmenopausal women. In addition, a higher proportion of AT located in the total midthigh depot is associated with a favorable metabolic profile.

Plausibility and parameter sensitivity of micro-finite element-based joint load prediction at the proximal femur.

PubMed

Synek, Alexander; Pahr, Dieter H

2018-06-01

A micro-finite element-based method to estimate the bone loading history based on bone architecture was recently presented in the literature. However, a thorough investigation of the parameter sensitivity and plausibility of this method to predict joint loads is still missing. The goals of this study were (1) to analyse the parameter sensitivity of the joint load predictions at one proximal femur and (2) to assess the plausibility of the results by comparing load predictions of ten proximal femora to in vivo hip joint forces measured with instrumented prostheses (available from www.orthoload.com ). Joint loads were predicted by optimally scaling the magnitude of four unit loads (inclined [Formula: see text] to [Formula: see text] with respect to the vertical axis) applied to micro-finite element models created from high-resolution computed tomography scans ([Formula: see text]m voxel size). Parameter sensitivity analysis was performed by varying a total of nine parameters and showed that predictions of the peak load directions (range 10[Formula: see text]-[Formula: see text]) are more robust than the predicted peak load magnitudes (range 2344.8-4689.5 N). Comparing the results of all ten femora with the in vivo loading data of ten subjects showed that peak loads are plausible both in terms of the load direction (in vivo: [Formula: see text], predicted: [Formula: see text]) and magnitude (in vivo: [Formula: see text], predicted: [Formula: see text]). Overall, this study suggests that micro-finite element-based joint load predictions are both plausible and robust in terms of the predicted peak load direction, but predicted load magnitudes should be interpreted with caution.

Material and morphology parameter sensitivity analysis in particulate composite materials

NASA Astrophysics Data System (ADS)

Zhang, Xiaoyu; Oskay, Caglar

2017-12-01

This manuscript presents a novel parameter sensitivity analysis framework for damage and failure modeling of particulate composite materials subjected to dynamic loading. The proposed framework employs global sensitivity analysis to study the variance in the failure response as a function of model parameters. In view of the computational complexity of performing thousands of detailed microstructural simulations to characterize sensitivities, Gaussian process (GP) surrogate modeling is incorporated into the framework. In order to capture the discontinuity in response surfaces, the GP models are integrated with a support vector machine classification algorithm that identifies the discontinuities within response surfaces. The proposed framework is employed to quantify variability and sensitivities in the failure response of polymer bonded particulate energetic materials under dynamic loads to material properties and morphological parameters that define the material microstructure. Particular emphasis is placed on the identification of sensitivity to interfaces between the polymer binder and the energetic particles. The proposed framework has been demonstrated to identify the most consequential material and morphological parameters under vibrational and impact loads.

Considerations in high-resolution skeletal muscle diffusion tensor imaging using single-shot echo planar imaging with stimulated-echo preparation and sensitivity encoding.

PubMed

Karampinos, Dimitrios C; Banerjee, Suchandrima; King, Kevin F; Link, Thomas M; Majumdar, Sharmila

2012-05-01

Previous studies have shown that skeletal muscle diffusion tensor imaging (DTI) can noninvasively probe changes in the muscle fiber architecture and microstructure in diseased and damaged muscles. However, DTI fiber reconstruction in small muscles and in muscle regions close to aponeuroses and tendons remains challenging because of partial volume effects. Increasing the spatial resolution of skeletal muscle single-shot diffusion-weighted echo planar imaging (DW-EPI) can be hindered by the inherently low signal-to-noise ratio (SNR) of muscle DW-EPI because of the short muscle T(2) and the high sensitivity of single-shot EPI to off-resonance effects and T(2)* blurring. In this article, eddy current-compensated diffusion-weighted stimulated-echo preparation is combined with sensitivity encoding (SENSE) to maintain good SNR properties and to reduce the sensitivity to distortions and T(2)* blurring in high-resolution skeletal muscle single-shot DW-EPI. An analytical framework is developed to optimize the reduction factor and diffusion weighting time to achieve maximum SNR. Arguments for the selection of the experimental parameters are then presented considering the compromise between SNR, B(0)-induced distortions, T(2)* blurring effects and tissue incoherent motion effects. On the basis of the selected parameters in a high-resolution skeletal muscle single-shot DW-EPI protocol, imaging protocols at lower acquisition matrix sizes are defined with matched bandwidth in the phase-encoding direction and SNR. In  vivo results show that high-resolution skeletal muscle DTI with minimized sensitivity to geometric distortions and T(2)* blurring is feasible using the proposed methodology. In particular, a significant benefit is demonstrated from a reduction in partial volume effects for resolving multi-pennate muscles and muscles with small cross-sections in calf muscle DTI. Copyright © 2011 John Wiley & Sons, Ltd.

Effects of atorvastatin treatment on left ventricular diastolic function in peritoneal dialysis patients-The ALEVENT clinical trial.

PubMed

Wu, Cho-Kai; Yeh, Chih-Fan; Chiang, Jiun-Yang; Lin, Ting-Tse; Wu, Yi-Fan; Chiang, Chih-Kang; Kao, Tze-Wah; Hung, Kuan-Yu; Huang, Jenq-Wen

Left ventricular diastolic dysfunction (LVDD) is common among patients undergoing peritoneal dialysis (PD). Increased levels of inflammatory biomarkers, such as high-sensitivity C-reactive protein, predict the development of LVDD. We hypothesized that PD patients with elevated high-sensitivity C-reactive protein levels might benefit from statin treatment for LVDD and designed a randomized clinical trial to prove the hypothesis. We screened 213 PD patients and randomly assigned 32 men and women with low-density lipoprotein cholesterol levels <130 mg/dL, high-sensitivity C-reactive protein levels of ≥1.5 mg/L, and LVDD, diagnosed by conventional and tissue Doppler imaging (TDI) echocardiography, to treatment with atorvastatin, 40 mg daily, or without. The primary end points were changes in TDI diastolic parameters or global strain imaging diastolic parameters. Atorvastatin reduced low-density lipoprotein cholesterol levels by 43% and high-sensitivity C-reactive protein levels by 45% (both P < .001). Follow-up TDI showed significant improvement of early mitral flow velocities divided by early diastolic peak velocities of the mitral annulus at the medial and lateral site (Nominal change for E/E medial : -5.01 ± 6.36 vs 1.80 ± 6.59 for atorvastatin and control, respectively, P = .02). There was also a significant improvement in global strain imaging after atorvastatin treatment (global strain rate, -17.12 ± 1.42 vs -14.61 ± 1.78 for atorvastatin and control, respectively, P = .002 and E/SR IVR , 462.35 ± 110.54 vs 634.09 ± 116.81, P = .003). In this trial of PD patients without hyperlipidemia but with elevated high-sensitivity C-reactive protein levels and LVDD, atorvastatin significantly improved cardiac diastolic function (ClinicalTrials.gov number, NCT01503671). Copyright © 2017. Published by Elsevier Inc.

Reduction of low frequency vibration of truck driver and seating system through system parameter identification, sensitivity analysis and active control

NASA Astrophysics Data System (ADS)

Wang, Xu; Bi, Fengrong; Du, Haiping

2018-05-01

This paper aims to develop an 5-degree-of-freedom driver and seating system model for optimal vibration control. A new method for identification of the driver seating system parameters from experimental vibration measurement has been developed. The parameter sensitivity analysis has been conducted considering the random excitation frequency and system parameter uncertainty. The most and least sensitive system parameters for the transmissibility ratio have been identified. The optimised PID controllers have been developed to reduce the driver's body vibration.

Rapid Debris Analysis Project Task 3 Final Report - Sensitivity of Fallout to Source Parameters, Near-Detonation Environment Material Properties, Topography, and Meteorology

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

Goldstein, Peter

2014-01-24

This report describes the sensitivity of predicted nuclear fallout to a variety of model input parameters, including yield, height of burst, particle and activity size distribution parameters, wind speed, wind direction, topography, and precipitation. We investigate sensitivity over a wide but plausible range of model input parameters. In addition, we investigate a specific example with a relatively narrow range to illustrate the potential for evaluating uncertainties in predictions when there are more precise constraints on model parameters.

Novel multichannel surface plasmon resonance photonic crystal fiber biosensor

NASA Astrophysics Data System (ADS)

Hameed, Mohamed Farhat O.; Alrayk, Yassmin K. A.; Shaalan, A. A.; El Deeb, Walid S.; Obayya, S. S. A.

2016-04-01

In this paper, a novel design of highly sensitive biosensor based on photonic crystal fiber is presented and analyzed using full vectorial finite element method. The suggested design depends on using silver layer as a plasmonic active material coated by a gold layer to protect silver oxidation. The reported sensor is based on the detection using the quasi transverse electric (TE) and quasi transverse magnetic (TM) modes which offers the possibility of multi-channel/multi-analyte sensing. The sensor geometrical parameters are optimized to achieve high sensitivity for the two polarized modes. High refractive index sensitivity of about 4750 nm/RIU (refractive index unit) and 4300 nm/RIU with corresponding resolutions of 2.1×10-5 RIU, and 2.33×10-5 RIU can be obtained for the quasi TM and quasi TE modes, respectively.

Nanostructured Tungsten Oxide Composite for High-Performance Gas Sensors

PubMed Central

Feng-Chen, Siyuan; Aldalbahi, Ali; Feng, Peter Xianping

2015-01-01

We report the results of composite tungsten oxide nanowires-based gas sensors. The morphologic surface, crystallographic structures, and chemical compositions of the obtained nanowires have been investigated using scanning electron microscopy (SEM), X-ray diffraction (XRD), and Raman scattering, respectively. The experimental measurements reveal that each wire consists of crystalline nanoparticles with an average diameter of less than 250 nm. By using the synthesized nanowires, highly sensitive prototypic gas sensors have been designed and fabricated. The dependence of the sensitivity of tungsten oxide nanowires to the methane and hydrogen gases as a function of time has been obtained. Various sensing parameters such as sensitivity, response time, stability, and repeatability were investigated in order to reveal the sensing ability. PMID:26512670

Nervous System Sensitization as a Predictor of Outcome in the Treatment of Peripheral Musculoskeletal Conditions: A Systematic Review.

PubMed

O'Leary, Helen; Smart, Keith M; Moloney, Niamh A; Doody, Catherine M

2017-02-01

Research suggests that peripheral and central nervous system sensitization can contribute to the overall pain experience in peripheral musculoskeletal (MSK) conditions. It is unclear, however, whether sensitization of the nervous system results in poorer outcomes following the treatment. This systematic review investigated whether nervous system sensitization in peripheral MSK conditions predicts poorer clinical outcomes in response to a surgical or conservative intervention. Four electronic databases were searched to identify the relevant studies. Eligible studies had a prospective design, with a follow-up assessing the outcome in terms of pain or disability. Studies that used baseline indices of nervous system sensitization were included, such as quantitative sensory testing (QST) or questionnaires that measured centrally mediated symptoms. Thirteen studies met the inclusion criteria, of which six were at a high risk of bias. The peripheral MSK conditions investigated were knee and hip osteoarthritis, shoulder pain, and elbow tendinopathy. QST parameters indicative of sensitization (lower electrical pain thresholds, cold hyperalgesia, enhanced temporal summation, lower punctate sharpness thresholds) were associated with negative outcome (more pain or disability) in 5 small exploratory studies. Larger studies that accounted for multiple confounders in design and analysis did not support a predictive relationship between QST parameters and outcome. Two studies used self-report measures to capture comorbid centrally mediated symptoms, and found higher questionnaire scores were independently predictive of more persistent pain following a total joint arthroplasty. This systematic review found insufficient evidence to support an independent predictive relationship between QST measures of nervous system sensitization and treatment outcome. Self-report measures demonstrated better predictive ability. Further high-quality prognostic research is warranted. © 2016 World Institute of Pain.

Feasibility of high-resolution one-dimensional relaxation imaging at low magnetic field using a single-sided NMR scanner applied to articular cartilage

NASA Astrophysics Data System (ADS)

Rössler, Erik; Mattea, Carlos; Stapf, Siegfried

2015-02-01

Low field Nuclear Magnetic Resonance increases the contrast of the longitudinal relaxation rate in many biological tissues; one prominent example is hyaline articular cartilage. In order to take advantage of this increased contrast and to profile the depth-dependent variations, high resolution parameter measurements are carried out which can be of critical importance in an early diagnosis of cartilage diseases such as osteoarthritis. However, the maximum achievable spatial resolution of parameter profiles is limited by factors such as sensor geometry, sample curvature, and diffusion limitation. In this work, we report on high-resolution single-sided NMR scanner measurements with a commercial device, and quantify these limitations. The highest achievable spatial resolution on the used profiler, and the lateral dimension of the sensitive volume were determined. Since articular cartilage samples are usually bent, we also focus on averaging effects inside the horizontally aligned sensitive volume and their impact on the relaxation profiles. Taking these critical parameters into consideration, depth-dependent relaxation time profiles with the maximum achievable vertical resolution of 20 μm are discussed, and are correlated with diffusion coefficient profiles in hyaline articular cartilage in order to reconstruct T2 maps from the diffusion-weighted CPMG decays of apparent relaxation rates.

Strain Sensors with Adjustable Sensitivity by Tailoring the Microstructure of Graphene Aerogel/PDMS Nanocomposites.

PubMed

Wu, Shuying; Ladani, Raj B; Zhang, Jin; Ghorbani, Kamran; Zhang, Xuehua; Mouritz, Adrian P; Kinloch, Anthony J; Wang, Chun H

2016-09-21

Strain sensors with high elastic limit and high sensitivity are required to meet the rising demand for wearable electronics. Here, we present the fabrication of highly sensitive strain sensors based on nanocomposites consisting of graphene aerogel (GA) and polydimethylsiloxane (PDMS), with the primary focus being to tune the sensitivity of the sensors by tailoring the cellular microstructure through controlling the manufacturing processes. The resultant nanocomposite sensors exhibit a high sensitivity with a gauge factor of up to approximately 61.3. Of significant importance is that the sensitivity of the strain sensors can be readily altered by changing the concentration of the precursor (i.e., an aqueous dispersion of graphene oxide) and the freezing temperature used to process the GA. The results reveal that these two parameters control the cell size and cell-wall thickness of the resultant GA, which may be correlated to the observed variations in the sensitivities of the strain sensors. The higher is the concentration of graphene oxide, then the lower is the sensitivity of the resultant nanocomposite strain sensor. Upon increasing the freezing temperature from -196 to -20 °C, the sensitivity increases and reaches a maximum value of 61.3 at -50 °C and then decreases with a further increase in freezing temperature to -20 °C. Furthermore, the strain sensors offer excellent durability and stability, with their piezoresistivities remaining virtually unchanged even after 10 000 cycles of high-strain loading-unloading. These novel findings pave the way to custom design strain sensors with a desirable piezoresistive behavior.

Results of an integrated structure/control law design sensitivity analysis

NASA Technical Reports Server (NTRS)

Gilbert, Michael G.

1989-01-01

A design sensitivity analysis method for Linear Quadratic Cost, Gaussian (LQG) optimal control laws, which predicts change in the optimal control law due to changes in fixed problem parameters using analytical sensitivity equations is discussed. Numerical results of a design sensitivity analysis for a realistic aeroservoelastic aircraft example are presented. In this example, the sensitivity of the optimally controlled aircraft's response to various problem formulation and physical aircraft parameters is determined. These results are used to predict the aircraft's new optimally controlled response if the parameter was to have some other nominal value during the control law design process. The sensitivity results are validated by recomputing the optimal control law for discrete variations in parameters, computing the new actual aircraft response, and comparing with the predicted response. These results show an improvement in sensitivity accuracy for integrated design purposes over methods which do not include changes in the optimal control law. Use of the analytical LQG sensitivity expressions is also shown to be more efficient than finite difference methods for the computation of the equivalent sensitivity information.

Global Sensitivity Applied to Dynamic Combined Finite Discrete Element Methods for Fracture Simulation

NASA Astrophysics Data System (ADS)

Godinez, H. C.; Rougier, E.; Osthus, D.; Srinivasan, G.

2017-12-01

Fracture propagation play a key role for a number of application of interest to the scientific community. From dynamic fracture processes like spall and fragmentation in metals and detection of gas flow in static fractures in rock and the subsurface, the dynamics of fracture propagation is important to various engineering and scientific disciplines. In this work we implement a global sensitivity analysis test to the Hybrid Optimization Software Suite (HOSS), a multi-physics software tool based on the combined finite-discrete element method, that is used to describe material deformation and failure (i.e., fracture and fragmentation) under a number of user-prescribed boundary conditions. We explore the sensitivity of HOSS for various model parameters that influence how fracture are propagated through a material of interest. The parameters control the softening curve that the model relies to determine fractures within each element in the mesh, as well a other internal parameters which influence fracture behavior. The sensitivity method we apply is the Fourier Amplitude Sensitivity Test (FAST), which is a global sensitivity method to explore how each parameter influence the model fracture and to determine the key model parameters that have the most impact on the model. We present several sensitivity experiments for different combination of model parameters and compare against experimental data for verification.

Identifying key sources of uncertainty in the modelling of greenhouse gas emissions from wastewater treatment.

PubMed

Sweetapple, Christine; Fu, Guangtao; Butler, David

2013-09-01

This study investigates sources of uncertainty in the modelling of greenhouse gas emissions from wastewater treatment, through the use of local and global sensitivity analysis tools, and contributes to an in-depth understanding of wastewater treatment modelling by revealing critical parameters and parameter interactions. One-factor-at-a-time sensitivity analysis is used to screen model parameters and identify those with significant individual effects on three performance indicators: total greenhouse gas emissions, effluent quality and operational cost. Sobol's method enables identification of parameters with significant higher order effects and of particular parameter pairs to which model outputs are sensitive. Use of a variance-based global sensitivity analysis tool to investigate parameter interactions enables identification of important parameters not revealed in one-factor-at-a-time sensitivity analysis. These interaction effects have not been considered in previous studies and thus provide a better understanding wastewater treatment plant model characterisation. It was found that uncertainty in modelled nitrous oxide emissions is the primary contributor to uncertainty in total greenhouse gas emissions, due largely to the interaction effects of three nitrogen conversion modelling parameters. The higher order effects of these parameters are also shown to be a key source of uncertainty in effluent quality. Copyright © 2013 Elsevier Ltd. All rights reserved.

Application of identified sensitive physical parameters in reducing the uncertainty of numerical simulation

NASA Astrophysics Data System (ADS)

Sun, Guodong; Mu, Mu

2016-04-01

An important source of uncertainty, which then causes further uncertainty in numerical simulations, is that residing in the parameters describing physical processes in numerical models. There are many physical parameters in numerical models in the atmospheric and oceanic sciences, and it would cost a great deal to reduce uncertainties in all physical parameters. Therefore, finding a subset of these parameters, which are relatively more sensitive and important parameters, and reducing the errors in the physical parameters in this subset would be a far more efficient way to reduce the uncertainties involved in simulations. In this context, we present a new approach based on the conditional nonlinear optimal perturbation related to parameter (CNOP-P) method. The approach provides a framework to ascertain the subset of those relatively more sensitive and important parameters among the physical parameters. The Lund-Potsdam-Jena (LPJ) dynamical global vegetation model was utilized to test the validity of the new approach. The results imply that nonlinear interactions among parameters play a key role in the uncertainty of numerical simulations in arid and semi-arid regions of China compared to those in northern, northeastern and southern China. The uncertainties in the numerical simulations were reduced considerably by reducing the errors of the subset of relatively more sensitive and important parameters. The results demonstrate that our approach not only offers a new route to identify relatively more sensitive and important physical parameters but also that it is viable to then apply "target observations" to reduce the uncertainties in model parameters.

In silico designing of power conversion efficient organic lead dyes for solar cells using todays innovative approaches to assure renewable energy for future

NASA Astrophysics Data System (ADS)

Kar, Supratik; Roy, Juganta K.; Leszczynski, Jerzy

2017-06-01

Advances in solar cell technology require designing of new organic dye sensitizers for dye-sensitized solar cells with high power conversion efficiency to circumvent the disadvantages of silicon-based solar cells. In silico studies including quantitative structure-property relationship analysis combined with quantum chemical analysis were employed to understand the primary electron transfer mechanism and photo-physical properties of 273 arylamine organic dyes from 11 diverse chemical families explicit to iodine electrolyte. The direct quantitative structure-property relationship models enable identification of the essential electronic and structural attributes necessary for quantifying the molecular prerequisites of 11 classes of arylamine organic dyes, responsible for high power conversion efficiency of dye-sensitized solar cells. Tetrahydroquinoline, N,N'-dialkylaniline and indoline have been least explored classes under arylamine organic dyes for dye-sensitized solar cells. Therefore, the identified properties from the corresponding quantitative structure-property relationship models of the mentioned classes were employed in designing of "lead dyes". Followed by, a series of electrochemical and photo-physical parameters were computed for designed dyes to check the required variables for electron flow of dye-sensitized solar cells. The combined computational techniques yielded seven promising lead dyes each for all three chemical classes considered. Significant (130, 183, and 46%) increment in predicted %power conversion efficiency was observed comparing with the existing dye with highest experimental %power conversion efficiency value for tetrahydroquinoline, N,N'-dialkylaniline and indoline, respectively maintaining required electrochemical parameters.

Methods for Probabilistic Radiological Dose Assessment at a High-Level Radioactive Waste Repository.

NASA Astrophysics Data System (ADS)

Maheras, Steven James

Methods were developed to assess and evaluate the uncertainty in offsite and onsite radiological dose at a high-level radioactive waste repository to show reasonable assurance that compliance with applicable regulatory requirements will be achieved. Uncertainty in offsite dose was assessed by employing a stochastic precode in conjunction with Monte Carlo simulation using an offsite radiological dose assessment code. Uncertainty in onsite dose was assessed by employing a discrete-event simulation model of repository operations in conjunction with an occupational radiological dose assessment model. Complementary cumulative distribution functions of offsite and onsite dose were used to illustrate reasonable assurance. Offsite dose analyses were performed for iodine -129, cesium-137, strontium-90, and plutonium-239. Complementary cumulative distribution functions of offsite dose were constructed; offsite dose was lognormally distributed with a two order of magnitude range. However, plutonium-239 results were not lognormally distributed and exhibited less than one order of magnitude range. Onsite dose analyses were performed for the preliminary inspection, receiving and handling, and the underground areas of the repository. Complementary cumulative distribution functions of onsite dose were constructed and exhibited less than one order of magnitude range. A preliminary sensitivity analysis of the receiving and handling areas was conducted using a regression metamodel. Sensitivity coefficients and partial correlation coefficients were used as measures of sensitivity. Model output was most sensitive to parameters related to cask handling operations. Model output showed little sensitivity to parameters related to cask inspections.

Anisotropic rotational diffusion studied by passage saturation transfer electron paramagnetic resonance

NASA Astrophysics Data System (ADS)

Robinson, Bruce H.; Dalton, Larry R.

1980-01-01

The stochastic Liouville equation for the spin density matrix is modified to consider the effects of Brownian anisotropic rotational diffusion upon electron paramagnetic resonance (EPR) and saturation transfer electron paramagnetic resonance (ST-EPR) spectra. Spectral shapes and the ST-EPR parameters L″/L, C'/C, and H″/H defined by Thomas, Dalton, and Hyde at X-band microwave frequencies [J. Chem. Phys. 65, 3006 (1976)] are examined and discussed in terms of the rotational times τ∥ and τ⊥ and in terms of other defined correlation times for systems characterized by magnetic tensors of axial symmetry and for systems characterized by nonaxially symmetric magnetic tensors. For nearly axially symmetric magnetic tensors, such as nitroxide spin labels studied employing 1-3 GHz microwaves, ST-EPR spectra for systems undergoing anisotropic rotational diffusion are virtually indistinguishable from spectra for systems characterized by isotropic diffusion. For nonaxially symmetric magnetic tensors, such as nitroxide spin labels studied employing 8-35 GHz microwaves, the high field region of the ST-EPR spectra, and hence the H″/H parameter, will be virtually indistinguishable from spectra, and parameter values, obtained for isotropic diffusion. On the other hand, the central spectral region at x-band microwave frequencies, and hence the C'/C parameter, is sensitive to the anisotropic diffusion model provided that a unique and static relationship exists between the magnetic and diffusion tensors. Random labeling or motion of the spin label relative to the biomolecule whose hydrodynamic properties are to be investigated will destroy spectral sensitivity to anisotropic motion. The sensitivity to anisotropic motion is enhanced in proceeding to 35 GHz with the increased sensitivity evident in the low field half of the EPR and ST-EPR spectra. The L″/L parameter is thus a meaningful indicator of anisotropic motion when compared with H″/H parameter analysis. However, consideration of spectral shapes suggests that the C'/C parameter definition is not meaningfully extended from 9.5 to 35 GHz. Alternative definitions of the L″/L and C'/C parameters are proposed for those microwave frequencies for which the electron Zeeman anisotropy is comparable to or greater than the electron-nitrogen nuclear hyperfine anisotropy.

Application of fuzzy logic approach for wind erosion hazard mapping in Laghouat region (Algeria) using remote sensing and GIS

NASA Astrophysics Data System (ADS)

Saadoud, Djouher; Hassani, Mohamed; Martin Peinado, Francisco José; Guettouche, Mohamed Saïd

2018-06-01

Wind erosion is one of the most serious environmental problems in Algeria that threatens human activities and socio-economic development. The main goal of this study is to apply a fuzzy logic approach to wind erosion sensitivity mapping in the Laghouat region, Algeria. Six causative factors, obtained by applying fuzzy membership functions to each used parameter, are considered: soil, vegetation cover, wind factor, soil dryness, land topography and land cover sensitivity. Different fuzzy operators (AND, OR, SUM, PRODUCT, and GAMMA) are applied to generate wind-erosion hazard map. Success rate curves reveal that the fuzzy gamma (γ) operator, with γ equal to 0.9, gives the best prediction accuracy with an area under curve of 85.2%. The resulting wind-erosion sensitivity map delineates the area into different zones of five relative sensitivity classes: very high, high, moderate, low and very low. The estimated result was verified by field measurements and the high statistically significant value of a chi-square test.

High sensitivity pressure transducer based on the phase characteristics of GMI magnetic sensors

NASA Astrophysics Data System (ADS)

Benavides, L. S.; Costa Silva, E.; Costa Monteiro, E.; Hall Barbosa, C. R.

2018-03-01

This paper presents a new configuration for a GMI pressure transducer based on the reading of the phase characteristics of GMI sensor, intended for biomedical applications. The development process of this new class of magnetic field transducers is discussed, beginning with the definition of the ideal conditioning of the GMI sensor elements (dc level and frequency of the excitation current and sample length) and continuing with computational simulations of the full electronic circuit performed using the experimental data obtained from measured GMI curves, and have shown that the improvement in the sensitivity of GMI magnetometers is larger when phase-based transducers are used instead of magnitude-based transducers. Parameters of interest of the developed prototype are thoroughly analyzed, such as: sensitivity, linearity and frequency response. Also, the spectral noise density of the developed pressure transducer is evaluated and its resolution in the passband is estimated. A low-cost GMI pressure transducer was developed, presenting high resolution, high sensitivity and a frequency bandwidth compatible to the desired biomedical applications.

Comparison of gating dynamics of different IP3R channels with immune algorithm searching for channel parameter distributions

NASA Astrophysics Data System (ADS)

Cai, Xiuhong; Li, Xiang; Qi, Hong; Wei, Fang; Chen, Jianyong; Shuai, Jianwei

2016-10-01

The gating properties of the inositol 1, 4, 5-trisphosphate (IP3) receptor (IP3R) are determined by the binding and unbinding capability of Ca2+ ions and IP3 messengers. With the patch clamp experiments, the stationary properties have been discussed for Xenopus oocyte type-1 IP3R (Oo-IP3R1), type-3 IP3R (Oo-IP3R3) and Spodoptera frugiperda IP3R (Sf-IP3R). In this paper, in order to provide insights about the relation between the observed gating characteristics and the gating parameters in different IP3Rs, we apply the immune algorithm to fit the parameters of a modified DeYoung-Keizer model. By comparing the fitting parameter distributions of three IP3Rs, we suggest that the three types of IP3Rs have the similar open sensitivity in responding to IP3. The Oo-IP3R3 channel is easy to open in responding to low Ca2+ concentration, while Sf-IP3R channel is easily inhibited in responding to high Ca2+ concentration. We also show that the IP3 binding rate is not a sensitive parameter for stationary gating dynamics for three IP3Rs, but the inhibitory Ca2+ binding/unbinding rates are sensitive parameters for gating dynamics for both Oo-IP3R1 and Oo-IP3R3 channels. Such differences may be important in generating the spatially and temporally complex Ca2+ oscillations in cells. Our study also demonstrates that the immune algorithm can be applied for model parameter searching in biological systems.

High-sensitivity silicon nanowire phototransistors

NASA Astrophysics Data System (ADS)

Tan, Siew Li; Zhao, Xingyan; Dan, Yaping

2014-08-01

Silicon nanowires (SiNWs) have emerged as a promising material for high-sensitivity photodetection in the UV, visible and near-infrared spectral ranges. In this work, we demonstrate novel planar SiNW phototransistors on silicon-oninsulator (SOI) substrate using CMOS-compatible processes. The device consists of a bipolar transistor structure with an optically-injected base region. The electronic and optical properties of the SiNW phototransistors are investigated. Preliminary simulation and experimental results show that nanowire geometry, doping densities and surface states have considerable effects on the device performance, and that a device with optimized parameters can potentially outperform conventional Si photodetectors.

Simulation of the influence of aerosol particles on Stokes parameters of polarized skylight

NASA Astrophysics Data System (ADS)

Li, L.; Li, Z. Q.; Wendisch, M.

2014-03-01

Microphysical properties and chemical compositions of aerosol particles determine polarized radiance distribution in the atmosphere. In this paper, the influences of different aerosol properties (particle size, shape, real and imaginary parts of refractive index) on Stokes parameters of polarized skylight in the solar principal and almucantar planes are studied by using vector radiative transfer simulations. The results show high sensitivity of the normalized Stokes parameters due to fine particle size, shape and real part of refractive index of aerosols. It is possible to utilize the strength variations at the peak positions of the normalized Stokes parameters in the principal and almucantar planes to identify aerosol types.

Preserving Differential Privacy in Degree-Correlation based Graph Generation

PubMed Central

Wang, Yue; Wu, Xintao

2014-01-01

Enabling accurate analysis of social network data while preserving differential privacy has been challenging since graph features such as cluster coefficient often have high sensitivity, which is different from traditional aggregate functions (e.g., count and sum) on tabular data. In this paper, we study the problem of enforcing edge differential privacy in graph generation. The idea is to enforce differential privacy on graph model parameters learned from the original network and then generate the graphs for releasing using the graph model with the private parameters. In particular, we develop a differential privacy preserving graph generator based on the dK-graph generation model. We first derive from the original graph various parameters (i.e., degree correlations) used in the dK-graph model, then enforce edge differential privacy on the learned parameters, and finally use the dK-graph model with the perturbed parameters to generate graphs. For the 2K-graph model, we enforce the edge differential privacy by calibrating noise based on the smooth sensitivity, rather than the global sensitivity. By doing this, we achieve the strict differential privacy guarantee with smaller magnitude noise. We conduct experiments on four real networks and compare the performance of our private dK-graph models with the stochastic Kronecker graph generation model in terms of utility and privacy tradeoff. Empirical evaluations show the developed private dK-graph generation models significantly outperform the approach based on the stochastic Kronecker generation model. PMID:24723987

Selecting Sensitive Parameter Subsets in Dynamical Models With Application to Biomechanical System Identification.

PubMed

Ramadan, Ahmed; Boss, Connor; Choi, Jongeun; Peter Reeves, N; Cholewicki, Jacek; Popovich, John M; Radcliffe, Clark J

2018-07-01

Estimating many parameters of biomechanical systems with limited data may achieve good fit but may also increase 95% confidence intervals in parameter estimates. This results in poor identifiability in the estimation problem. Therefore, we propose a novel method to select sensitive biomechanical model parameters that should be estimated, while fixing the remaining parameters to values obtained from preliminary estimation. Our method relies on identifying the parameters to which the measurement output is most sensitive. The proposed method is based on the Fisher information matrix (FIM). It was compared against the nonlinear least absolute shrinkage and selection operator (LASSO) method to guide modelers on the pros and cons of our FIM method. We present an application identifying a biomechanical parametric model of a head position-tracking task for ten human subjects. Using measured data, our method (1) reduced model complexity by only requiring five out of twelve parameters to be estimated, (2) significantly reduced parameter 95% confidence intervals by up to 89% of the original confidence interval, (3) maintained goodness of fit measured by variance accounted for (VAF) at 82%, (4) reduced computation time, where our FIM method was 164 times faster than the LASSO method, and (5) selected similar sensitive parameters to the LASSO method, where three out of five selected sensitive parameters were shared by FIM and LASSO methods.

How Sensitive Are Transdermal Transport Predictions by Microscopic Stratum Corneum Models to Geometric and Transport Parameter Input?

PubMed

Wen, Jessica; Koo, Soh Myoung; Lape, Nancy

2018-02-01

While predictive models of transdermal transport have the potential to reduce human and animal testing, microscopic stratum corneum (SC) model output is highly dependent on idealized SC geometry, transport pathway (transcellular vs. intercellular), and penetrant transport parameters (e.g., compound diffusivity in lipids). Most microscopic models are limited to a simple rectangular brick-and-mortar SC geometry and do not account for variability across delivery sites, hydration levels, and populations. In addition, these models rely on transport parameters obtained from pure theory, parameter fitting to match in vivo experiments, and time-intensive diffusion experiments for each compound. In this work, we develop a microscopic finite element model that allows us to probe model sensitivity to variations in geometry, transport pathway, and hydration level. Given the dearth of experimentally-validated transport data and the wide range in theoretically-predicted transport parameters, we examine the model's response to a variety of transport parameters reported in the literature. Results show that model predictions are strongly dependent on all aforementioned variations, resulting in order-of-magnitude differences in lag times and permeabilities for distinct structure, hydration, and parameter combinations. This work demonstrates that universally predictive models cannot fully succeed without employing experimentally verified transport parameters and individualized SC structures. Copyright © 2018 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Design of highly sensitive multichannel bimetallic photonic crystal fiber biosensor

NASA Astrophysics Data System (ADS)

Hameed, Mohamed Farhat O.; Alrayk, Yassmin K. A.; Shaalan, Abdelhamid A.; El Deeb, Walid S.; Obayya, Salah S. A.

2016-10-01

A design of a highly sensitive multichannel biosensor based on photonic crystal fiber is proposed and analyzed. The suggested design has a silver layer as a plasmonic material coated by a gold layer to protect silver oxidation. The reported sensor is based on detection using the quasi transverse electric (TE) and quasi transverse magnetic (TM) modes, which offers the possibility of multichannel/multianalyte sensing. The numerical results are obtained using a finite element method with perfect matched layer boundary conditions. The sensor geometrical parameters are optimized to achieve high sensitivity for the two polarized modes. High-refractive index sensitivity of about 4750 nm/RIU (refractive index unit) and 4300 nm/RIU with corresponding resolutions of 2.1×10-5 RIU, and 2.33×10-5 RIU can be obtained according to the quasi TM and quasi TE modes of the proposed sensor, respectively. Further, the reported design can be used as a self-calibration biosensor within an unknown analyte refractive index ranging from 1.33 to 1.35 with high linearity and high accuracy. Moreover, the suggested biosensor has advantages in terms of compactness and better integration of microfluidics setup, waveguide, and metallic layers into a single structure.

Evaluation of Uncertainty and Sensitivity in Environmental Modeling at a Radioactive Waste Management Site

NASA Astrophysics Data System (ADS)

Stockton, T. B.; Black, P. K.; Catlett, K. M.; Tauxe, J. D.

2002-05-01

Environmental modeling is an essential component in the evaluation of regulatory compliance of radioactive waste management sites (RWMSs) at the Nevada Test Site in southern Nevada, USA. For those sites that are currently operating, further goals are to support integrated decision analysis for the development of acceptance criteria for future wastes, as well as site maintenance, closure, and monitoring. At these RWMSs, the principal pathways for release of contamination to the environment are upward towards the ground surface rather than downwards towards the deep water table. Biotic processes, such as burrow excavation and plant uptake and turnover, dominate this upward transport. A combined multi-pathway contaminant transport and risk assessment model was constructed using the GoldSim modeling platform. This platform facilitates probabilistic analysis of environmental systems, and is especially well suited for assessments involving radionuclide decay chains. The model employs probabilistic definitions of key parameters governing contaminant transport, with the goals of quantifying cumulative uncertainty in the estimation of performance measures and providing information necessary to perform sensitivity analyses. This modeling differs from previous radiological performance assessments (PAs) in that the modeling parameters are intended to be representative of the current knowledge, and the uncertainty in that knowledge, of parameter values rather than reflective of a conservative assessment approach. While a conservative PA may be sufficient to demonstrate regulatory compliance, a parametrically honest PA can also be used for more general site decision-making. In particular, a parametrically honest probabilistic modeling approach allows both uncertainty and sensitivity analyses to be explicitly coupled to the decision framework using a single set of model realizations. For example, sensitivity analysis provides a guide for analyzing the value of collecting more information by quantifying the relative importance of each input parameter in predicting the model response. However, in these complex, high dimensional eco-system models, represented by the RWMS model, the dynamics of the systems can act in a non-linear manner. Quantitatively assessing the importance of input variables becomes more difficult as the dimensionality, the non-linearities, and the non-monotonicities of the model increase. Methods from data mining such as Multivariate Adaptive Regression Splines (MARS) and the Fourier Amplitude Sensitivity Test (FAST) provide tools that can be used in global sensitivity analysis in these high dimensional, non-linear situations. The enhanced interpretability of model output provided by the quantitative measures estimated by these global sensitivity analysis tools will be demonstrated using the RWMS model.

Modelling ecological and human exposure to POPs in Venice lagoon - Part II: Quantitative uncertainty and sensitivity analysis in coupled exposure models.

PubMed

Radomyski, Artur; Giubilato, Elisa; Ciffroy, Philippe; Critto, Andrea; Brochot, Céline; Marcomini, Antonio

2016-11-01

The study is focused on applying uncertainty and sensitivity analysis to support the application and evaluation of large exposure models where a significant number of parameters and complex exposure scenarios might be involved. The recently developed MERLIN-Expo exposure modelling tool was applied to probabilistically assess the ecological and human exposure to PCB 126 and 2,3,7,8-TCDD in the Venice lagoon (Italy). The 'Phytoplankton', 'Aquatic Invertebrate', 'Fish', 'Human intake' and PBPK models available in MERLIN-Expo library were integrated to create a specific food web to dynamically simulate bioaccumulation in various aquatic species and in the human body over individual lifetimes from 1932 until 1998. MERLIN-Expo is a high tier exposure modelling tool allowing propagation of uncertainty on the model predictions through Monte Carlo simulation. Uncertainty in model output can be further apportioned between parameters by applying built-in sensitivity analysis tools. In this study, uncertainty has been extensively addressed in the distribution functions to describe the data input and the effect on model results by applying sensitivity analysis techniques (screening Morris method, regression analysis, and variance-based method EFAST). In the exposure scenario developed for the Lagoon of Venice, the concentrations of 2,3,7,8-TCDD and PCB 126 in human blood turned out to be mainly influenced by a combination of parameters (half-lives of the chemicals, body weight variability, lipid fraction, food assimilation efficiency), physiological processes (uptake/elimination rates), environmental exposure concentrations (sediment, water, food) and eating behaviours (amount of food eaten). In conclusion, this case study demonstrated feasibility of MERLIN-Expo to be successfully employed in integrated, high tier exposure assessment. Copyright © 2016 Elsevier B.V. All rights reserved.

Sensitivity Analysis for Steady State Groundwater Flow Using Adjoint Operators

NASA Astrophysics Data System (ADS)

Sykes, J. F.; Wilson, J. L.; Andrews, R. W.

1985-03-01

Adjoint sensitivity theory is currently being considered as a potential method for calculating the sensitivity of nuclear waste repository performance measures to the parameters of the system. For groundwater flow systems, performance measures of interest include piezometric heads in the vicinity of a waste site, velocities or travel time in aquifers, and mass discharge to biosphere points. The parameters include recharge-discharge rates, prescribed boundary heads or fluxes, formation thicknesses, and hydraulic conductivities. The derivative of a performance measure with respect to the system parameters is usually taken as a measure of sensitivity. To calculate sensitivities, adjoint sensitivity equations are formulated from the equations describing the primary problem. The solution of the primary problem and the adjoint sensitivity problem enables the determination of all of the required derivatives and hence related sensitivity coefficients. In this study, adjoint sensitivity theory is developed for equations of two-dimensional steady state flow in a confined aquifer. Both the primary flow equation and the adjoint sensitivity equation are solved using the Galerkin finite element method. The developed computer code is used to investigate the regional flow parameters of the Leadville Formation of the Paradox Basin in Utah. The results illustrate the sensitivity of calculated local heads to the boundary conditions. Alternatively, local velocity related performance measures are more sensitive to hydraulic conductivities.

Parametric study of a canard-configured transport using conceptual design optimization

NASA Technical Reports Server (NTRS)

Arbuckle, P. D.; Sliwa, S. M.

1985-01-01

Constrained-parameter optimization is used to perform optimal conceptual design of both canard and conventional configurations of a medium-range transport. A number of design constants and design constraints are systematically varied to compare the sensitivities of canard and conventional configurations to a variety of technology assumptions. Main-landing-gear location and canard surface high-lift performance are identified as critical design parameters for a statically stable, subsonic, canard-configured transport.

Population viability analysis of Lower Missouri River shovelnose sturgeon with initial application to the pallid sturgeon

USGS Publications Warehouse

Bajer, P.G.; Wildhaber, M.L.

2007-01-01

Demographic models for the shovelnose (Scaphirhynchus platorynchus) and pallid (S. albus) sturgeons in the Lower Missouri River were developed to conduct sensitivity analyses for both populations. Potential effects of increased fishing mortality on the shovelnose sturgeon were also evaluated. Populations of shovelnose and pallid sturgeon were most sensitive to age-0 mortality rates as well as mortality rates of juveniles and young adults. Overall, fecundity was a less sensitive parameter. However, increased fecundity effectively balanced higher mortality among sensitive age classes in both populations. Management that increases population-level fecundity and improves survival of age-0, juveniles, and young adults should most effectively benefit both populations. Evaluation of reproductive values indicated that populations of pallid sturgeon dominated by ages ≥35 could rapidly lose their potential for growth, particularly if recruitment remains low. Under the initial parameter values portraying current conditions the population of shovelnose sturgeon was predicted to decline by 1.65% annually, causing the commercial yield to also decline. Modeling indicated that the commercial yield could increase substantially if exploitation of females in ages ≤12 was highly restricted.

Sensitivity of Rayleigh wave ellipticity and implications for surface wave inversion

NASA Astrophysics Data System (ADS)

Cercato, Michele

2018-04-01

The use of Rayleigh wave ellipticity has gained increasing popularity in recent years for investigating earth structures, especially for near-surface soil characterization. In spite of its widespread application, the sensitivity of the ellipticity function to the soil structure has been rarely explored in a comprehensive and systematic manner. To this end, a new analytical method is presented for computing the sensitivity of Rayleigh wave ellipticity with respect to the structural parameters of a layered elastic half-space. This method takes advantage of the minor decomposition of the surface wave eigenproblem and is numerically stable at high frequency. This numerical procedure allowed to retrieve the sensitivity for typical near surface and crustal geological scenarios, pointing out the key parameters for ellipticity interpretation under different circumstances. On this basis, a thorough analysis is performed to assess how ellipticity data can efficiently complement surface wave dispersion information in a joint inversion algorithm. The results of synthetic and real-world examples are illustrated to analyse quantitatively the diagnostic potential of the ellipticity data with respect to the soil structure, focusing on the possible sources of misinterpretation in data inversion.

New PCR diagnostic systems for the detection and quantification of porcine cytomegalovirus (PCMV).

PubMed

Morozov, Vladimir A; Morozov, Alexey V; Denner, Joachim

2016-05-01

Pigs are frequently infected with porcine cytomegalovirus (PCMV). Infected adult animals may not present with symptoms of disease, and the virus remains latent. However, the virus may be transmitted to human recipients receiving pig transplants. Recently, it was shown that pig-to-non-human-primate xenotransplantations showed 2 to 3 times lower transplant survival when the donor pig was infected with PCMV. Therefore, highly sensitive methods are required to select virus-free pigs and to examine xenotransplants. Seven previously established PCR detection systems targeting the DNA polymerase gene of PCMV were examined by comparison of thermodynamic parameters of oligonucleotides, and new diagnostic nested PCR and real-time PCR systems with improved parameters and high sensitivity were established. The detection limit of conventional PCR was estimated to be 15 copies, and that of the nested PCR was 5 copies. The sensitivity of the real-time PCR with a TaqMan probe was two copies. An equal efficiency of the newly established detection systems was shown by parallel testing of DNA from sera and blood of six pigs, identifying the same animals as PCMV infected. These new diagnostic PCR systems will improve the detection of PCMV and therefore increase the safety of porcine xenotransplants.

The performance of magnetic resonance imaging in the detection of triangular fibrocartilage complex injury: a meta-analysis.

PubMed

Wang, Z X; Chen, S L; Wang, Q Q; Liu, B; Zhu, J; Shen, J

2015-06-01

The aim of this study was to evaluate the accuracy of magnetic resonance imaging in the detection of triangular fibrocartilage complex injury through a meta-analysis. A comprehensive literature search was conducted before 1 April 2014. All studies comparing magnetic resonance imaging results with arthroscopy or open surgery findings were reviewed, and 25 studies that satisfied the eligibility criteria were included. Data were pooled to yield pooled sensitivity and specificity, which were respectively 0.83 and 0.82. In detection of central and peripheral tears, magnetic resonance imaging had respectively a pooled sensitivity of 0.90 and 0.88 and a pooled specificity of 0.97 and 0.97. Six high-quality studies using Ringler's recommended magnetic resonance imaging parameters were selected for analysis to determine whether optimal imaging protocols yielded better results. The pooled sensitivity and specificity of these six studies were 0.92 and 0.82, respectively. The overall accuracy of magnetic resonance imaging was acceptable. For peripheral tears, the pooled data showed a relatively high accuracy. Magnetic resonance imaging with appropriate parameters are an ideal method for diagnosing different types of triangular fibrocartilage complex tears. © The Author(s) 2015.

Distributed Evaluation of Local Sensitivity Analysis (DELSA), with application to hydrologic models

USGS Publications Warehouse

Rakovec, O.; Hill, Mary C.; Clark, M.P.; Weerts, A. H.; Teuling, A. J.; Uijlenhoet, R.

2014-01-01

This paper presents a hybrid local-global sensitivity analysis method termed the Distributed Evaluation of Local Sensitivity Analysis (DELSA), which is used here to identify important and unimportant parameters and evaluate how model parameter importance changes as parameter values change. DELSA uses derivative-based “local” methods to obtain the distribution of parameter sensitivity across the parameter space, which promotes consideration of sensitivity analysis results in the context of simulated dynamics. This work presents DELSA, discusses how it relates to existing methods, and uses two hydrologic test cases to compare its performance with the popular global, variance-based Sobol' method. The first test case is a simple nonlinear reservoir model with two parameters. The second test case involves five alternative “bucket-style” hydrologic models with up to 14 parameters applied to a medium-sized catchment (200 km2) in the Belgian Ardennes. Results show that in both examples, Sobol' and DELSA identify similar important and unimportant parameters, with DELSA enabling more detailed insight at much lower computational cost. For example, in the real-world problem the time delay in runoff is the most important parameter in all models, but DELSA shows that for about 20% of parameter sets it is not important at all and alternative mechanisms and parameters dominate. Moreover, the time delay was identified as important in regions producing poor model fits, whereas other parameters were identified as more important in regions of the parameter space producing better model fits. The ability to understand how parameter importance varies through parameter space is critical to inform decisions about, for example, additional data collection and model development. The ability to perform such analyses with modest computational requirements provides exciting opportunities to evaluate complicated models as well as many alternative models.

Optimization of single photon detection model based on GM-APD

NASA Astrophysics Data System (ADS)

Chen, Yu; Yang, Yi; Hao, Peiyu

2017-11-01

One hundred kilometers high precision laser ranging hopes the detector has very strong detection ability for very weak light. At present, Geiger-Mode of Avalanche Photodiode has more use. It has high sensitivity and high photoelectric conversion efficiency. Selecting and designing the detector parameters according to the system index is of great importance to the improvement of photon detection efficiency. Design optimization requires a good model. In this paper, we research the existing Poisson distribution model, and consider the important detector parameters of dark count rate, dead time, quantum efficiency and so on. We improve the optimization of detection model, select the appropriate parameters to achieve optimal photon detection efficiency. The simulation is carried out by using Matlab and compared with the actual test results. The rationality of the model is verified. It has certain reference value in engineering applications.

Sensitivity and specificity of univariate MRI analysis of experimentally degraded cartilage under clinical imaging conditions.

PubMed

Lukas, Vanessa A; Fishbein, Kenneth W; Reiter, David A; Lin, Ping-Chang; Schneider, Erika; Spencer, Richard G

2015-07-01

To evaluate the sensitivity and specificity of classification of pathomimetically degraded bovine nasal cartilage at 3 Tesla and 37°C using univariate MRI measurements of both pure parameter values and intensities of parameter-weighted images. Pre- and posttrypsin degradation values of T1 , T2 , T2 *, magnetization transfer ratio (MTR), and apparent diffusion coefficient (ADC), and corresponding weighted images, were analyzed. Classification based on the Euclidean distance was performed and the quality of classification was assessed through sensitivity, specificity and accuracy (ACC). The classifiers with the highest accuracy values were ADC (ACC = 0.82 ± 0.06), MTR (ACC = 0.78 ± 0.06), T1 (ACC = 0.99 ± 0.01), T2 derived from a three-dimensional (3D) spin-echo sequence (ACC = 0.74 ± 0.05), and T2 derived from a 2D spin-echo sequence (ACC = 0.77 ± 0.06), along with two of the diffusion-weighted signal intensities (b = 333 s/mm(2) : ACC = 0.80 ± 0.05; b = 666 s/mm(2) : ACC = 0.85 ± 0.04). In particular, T1 values differed substantially between the groups, resulting in atypically high classification accuracy. The second-best classifier, diffusion weighting with b = 666 s/mm(2) , as well as all other parameters evaluated, exhibited substantial overlap between pre- and postdegradation groups, resulting in decreased accuracies. Classification according to T1 values showed excellent test characteristics (ACC = 0.99), with several other parameters also showing reasonable performance (ACC > 0.70). Of these, diffusion weighting is particularly promising as a potentially practical clinical modality. As in previous work, we again find that highly statistically significant group mean differences do not necessarily translate into accurate clinical classification rules. © 2014 Wiley Periodicals, Inc.

Ag Nanoparticles-enhanced Fluorescence of Terbium-Deferasirox Complexes for the Highly Sensitive Determination of Deferasirox.

PubMed

Abolhasani, Jafar; Naderali, Roza; Hassanzadeh, Javad

2016-01-01

We describe the effect of different sized gold and silver nanoparticles on the terbium sensitized fluorescence of deferasirox. It is indicated that silver nanostructures, especially 18 nm Ag nanoparticles (AgNPs), have a remarkable amplifying effect compared to Au nanoparticles. Based on this observation, a highly sensitive and selective method was developed for the determination of deferasirox. Effects of various parameters like AgNPs and Tb(3+) concentration and pH of media were investigated. Under the optimal conditions, a calibration curve was plotted as the fluorescence intensities versus the concentration of deferasirox in the range of 0.1 to 200 nmol L(-1), and detection limit of 0.03 nmol L(-1) was obtained. The method has good linearity, recovery, reproducibility and sensitivity, and was satisfactorily applied for the determination of deferasirox in urine and pharmaceutical samples.

Highly sensitive nanostructure SnO2 based gas sensor for environmental pollutants

NASA Astrophysics Data System (ADS)

Korgaokar, Sushil; Moradiya, Meet; Prajapati, Om; Thakkar, Pranav; Pala, Jay; Savaliya, Chirag; Parikh, Sachin; Markna, J. H.

2017-05-01

A major quantity of pollutants are produced from industries and vehicles in the form of gas. New approaches are needed to solve well-known environmental pollutants like CO, CO2, NO2, SOx. Therefore detection with effective gas sensors is a vital part of pollution prevention efforts. There is a need to develop fast, rapid, cost-effective, highly sensitive, low power, and non-intrusive rugged sensors that can be easily installed. In the present study, nanostructured SnO2 used as a sensitive material in the devices and synthesized using hydrothermal process. The detailed development of the fabrication of SnO2 nanostructures gas sensor is described, which shows the remarkable change in the sensing properties with varying particle size. Additionally, we have used X-ray diffraction, scanning electron microscopy (SEM) for characterization and carefully examined the relative parameters like response magnitude (sensitivity) and selectivity of SnO2 nano structures with different particle size.

Calibration of a complex activated sludge model for the full-scale wastewater treatment plant.

PubMed

Liwarska-Bizukojc, Ewa; Olejnik, Dorota; Biernacki, Rafal; Ledakowicz, Stanislaw

2011-08-01

In this study, the results of the calibration of the complex activated sludge model implemented in BioWin software for the full-scale wastewater treatment plant are presented. Within the calibration of the model, sensitivity analysis of its parameters and the fractions of carbonaceous substrate were performed. In the steady-state and dynamic calibrations, a successful agreement between the measured and simulated values of the output variables was achieved. Sensitivity analysis revealed that upon the calculations of normalized sensitivity coefficient (S(i,j)) 17 (steady-state) or 19 (dynamic conditions) kinetic and stoichiometric parameters are sensitive. Most of them are associated with growth and decay of ordinary heterotrophic organisms and phosphorus accumulating organisms. The rankings of ten most sensitive parameters established on the basis of the calculations of the mean square sensitivity measure (δ(msqr)j) indicate that irrespective of the fact, whether the steady-state or dynamic calibration was performed, there is an agreement in the sensitivity of parameters.

Quantifying the importance of spatial resolution and other factors through global sensitivity analysis of a flood inundation model

NASA Astrophysics Data System (ADS)

Thomas Steven Savage, James; Pianosi, Francesca; Bates, Paul; Freer, Jim; Wagener, Thorsten

2016-11-01

Where high-resolution topographic data are available, modelers are faced with the decision of whether it is better to spend computational resource on resolving topography at finer resolutions or on running more simulations to account for various uncertain input factors (e.g., model parameters). In this paper we apply global sensitivity analysis to explore how influential the choice of spatial resolution is when compared to uncertainties in the Manning's friction coefficient parameters, the inflow hydrograph, and those stemming from the coarsening of topographic data used to produce Digital Elevation Models (DEMs). We apply the hydraulic model LISFLOOD-FP to produce several temporally and spatially variable model outputs that represent different aspects of flood inundation processes, including flood extent, water depth, and time of inundation. We find that the most influential input factor for flood extent predictions changes during the flood event, starting with the inflow hydrograph during the rising limb before switching to the channel friction parameter during peak flood inundation, and finally to the floodplain friction parameter during the drying phase of the flood event. Spatial resolution and uncertainty introduced by resampling topographic data to coarser resolutions are much more important for water depth predictions, which are also sensitive to different input factors spatially and temporally. Our findings indicate that the sensitivity of LISFLOOD-FP predictions is more complex than previously thought. Consequently, the input factors that modelers should prioritize will differ depending on the model output assessed, and the location and time of when and where this output is most relevant.

Design and numerical analysis of highly sensitive Au-MoS2-graphene based hybrid surface plasmon resonance biosensor

NASA Astrophysics Data System (ADS)

Rahman, M. Saifur; Anower, Md. Shamim; Hasan, Md. Rabiul; Hossain, Md. Biplob; Haque, Md. Ismail

2017-08-01

We demonstrate a highly sensitive Au-MoS2-Graphene based hybrid surface plasmon resonance (SPR) biosensor for the detection of DNA hybridization. The performance parameters of the proposed sensor are investigated in terms of sensitivity, detection accuracy and quality factor at operating wavelength of 633 nm. We observed in the numerical study that sensitivity can be greatly increased by adding MoS2 layer in the middle of a Graphene-on-Au layer. It is shown that by using single layer of MoS2 in between gold and graphene layer, the proposed biosensor exhibits simultaneously high sensitivity of 87.8 deg/RIU, high detection accuracy of 1.28 and quality factor of 17.56 with gold layer thickness of 50 nm. This increased performance is due to the absorption ability and optical characteristics of graphene biomolecules and high fluorescence quenching ability of MoS2. On the basis of changing in SPR angle and minimum reflectance, the proposed sensor can sense nucleotides bonding happened between double-stranded DNA (dsDNA) helix structures. Therefore, this sensor can successfully detect the hybridization of target DNAs to the probe DNAs pre-immobilized on the Au-MoS2-Graphene hybrid with capability of distinguishing single-base mismatch.

The visceral adiposity index is associated with insulin sensitivity and IGF-I levels in adults with growth hormone deficiency.

PubMed

Ciresi, Alessandro; Radellini, Stefano; Guarnotta, Valentina; Giordano, Carla

2017-06-01

The visceral adiposity index, based on anthropometric and metabolic parameters, has been shown to be related to adipose tissue function and insulin sensitivity. We aimed to evaluate the performance of the visceral adiposity index in adult patients with growth hormone deficiency. We enrolled 52 patients(mean age 51 ± 13 years) with newly diagnosed growth hormone deficiency and 50 matched healthy subjects as controls at baseline. At baseline and after 12 and 24 months of treatment we evaluated anthropometric measures, lipid profile, glucose and insulin during an oral glucose tolerance test, hemoglobin A1c, homeostasis model assessment estimate of insulin resistance, quantitative insulin sensitivity check index, insulin sensitivity index Matsuda, insulin-like growth factor-I and visceral adiposity index. At baseline growth hormone deficiency patients showed higher waist circumference (p < 0.001), low-density lipoprotein cholesterol (p < 0.001) and visceral adiposity index (p = 0.003) with lower insulin sensitivity index (p = 0.007) and high-density lipoprotein cholesterol (p = 0.001) than controls. During growth hormone treatment we observed a significant increase in insulin-like growth factor-I (p < 0.001), high-density lipoprotein (p < 0.001) with a trend toward increase in insulin sensitivity index (p = 0.055) and a significant decrease in total cholesterol (p < 0.001) and visceral adiposity index (p < 0.001), while no significant changes were observed in other clinical and metabolic parameters. The visceral adiposity index was the only parameter that significantly correlated with growth hormone peak at diagnosis (p < 0.001) and with insulin-like growth factor-I and insulin sensitivity index both at diagnosis (p = 0.009 and p < 0.001) and after 12 (p = 0.026 and p = 0.001) and 24 months (p < 0.001 and p = 0.001) of treatment. The visceral adiposity index, which has shown to be associated with both insulin-like growth factor-I and insulin sensitivity, proved to be the most reliable index of metabolic perturbation, among the most common indexes of adiposity assessment and a marker of benefit during treatment in adult growth hormone deficiency patients.

Uncertainty and Sensitivity Analyses of a Pebble Bed HTGR Loss of Cooling Event

DOE PAGES

Strydom, Gerhard

2013-01-01

The Very High Temperature Reactor Methods Development group at the Idaho National Laboratory identified the need for a defensible and systematic uncertainty and sensitivity approach in 2009. This paper summarizes the results of an uncertainty and sensitivity quantification investigation performed with the SUSA code, utilizing the International Atomic Energy Agency CRP 5 Pebble Bed Modular Reactor benchmark and the INL code suite PEBBED-THERMIX. Eight model input parameters were selected for inclusion in this study, and after the input parameters variations and probability density functions were specified, a total of 800 steady state and depressurized loss of forced cooling (DLOFC) transientmore » PEBBED-THERMIX calculations were performed. The six data sets were statistically analyzed to determine the 5% and 95% DLOFC peak fuel temperature tolerance intervals with 95% confidence levels. It was found that the uncertainties in the decay heat and graphite thermal conductivities were the most significant contributors to the propagated DLOFC peak fuel temperature uncertainty. No significant differences were observed between the results of Simple Random Sampling (SRS) or Latin Hypercube Sampling (LHS) data sets, and use of uniform or normal input parameter distributions also did not lead to any significant differences between these data sets.« less

Phytoplankton competition and coexistence: Intrinsic ecosystem dynamics and impact of vertical mixing

NASA Astrophysics Data System (ADS)

Perruche, Coralie; Rivière, Pascal; Pondaven, Philippe; Carton, Xavier

2010-04-01

This paper aims at studying analytically the functioning of a very simple ecosystem model with two phytoplankton species. First, using the dynamical system theory, we determine its nonlinear equilibria, their stability and characteristic timescales with a focus on phytoplankton competition. Particular attention is paid to the model sensitivity to parameter change. Then, the influence of vertical mixing and sinking of detritus on the vertically-distributed ecosystem model is investigated. The analytical results reveal a high diversity of ecosystem structures with fixed points and limit cycles that are mainly sensitive to variations of light intensity and total amount of nitrogen matter. The sensitivity to other parameters such as re-mineralisation, growth and grazing rates is also specified. Besides, the equilibrium analysis shows a complete segregation of the two phytoplankton species in the whole parameter space. The embedding of our ecosystem model into a one-dimensional numerical model with diffusion turns out to allow coexistence between phytoplankton species, providing a possible solution to the 'paradox of plankton' in the sense that it prevents the competitive exclusion of one phytoplankton species. These results improve our knowledge of the factors that control the structure and functioning of plankton communities.

An investigation of using an RQP based method to calculate parameter sensitivity derivatives

NASA Technical Reports Server (NTRS)

Beltracchi, Todd J.; Gabriele, Gary A.

1989-01-01

Estimation of the sensitivity of problem functions with respect to problem variables forms the basis for many of our modern day algorithms for engineering optimization. The most common application of problem sensitivities has been in the calculation of objective function and constraint partial derivatives for determining search directions and optimality conditions. A second form of sensitivity analysis, parameter sensitivity, has also become an important topic in recent years. By parameter sensitivity, researchers refer to the estimation of changes in the modeling functions and current design point due to small changes in the fixed parameters of the formulation. Methods for calculating these derivatives have been proposed by several authors (Armacost and Fiacco 1974, Sobieski et al 1981, Schmit and Chang 1984, and Vanderplaats and Yoshida 1985). Two drawbacks to estimating parameter sensitivities by current methods have been: (1) the need for second order information about the Lagrangian at the current point, and (2) the estimates assume no change in the active set of constraints. The first of these two problems is addressed here and a new algorithm is proposed that does not require explicit calculation of second order information.

How often do sensitivity analyses for economic parameters change cost-utility analysis conclusions?

PubMed

Schackman, Bruce R; Gold, Heather Taffet; Stone, Patricia W; Neumann, Peter J

2004-01-01

There is limited evidence about the extent to which sensitivity analysis has been used in the cost-effectiveness literature. Sensitivity analyses for health-related QOL (HR-QOL), cost and discount rate economic parameters are of particular interest because they measure the effects of methodological and estimation uncertainties. To investigate the use of sensitivity analyses in the pharmaceutical cost-utility literature in order to test whether a change in economic parameters could result in a different conclusion regarding the cost effectiveness of the intervention analysed. Cost-utility analyses of pharmaceuticals identified in a prior comprehensive audit (70 articles) were reviewed and further audited. For each base case for which sensitivity analyses were reported (n = 122), up to two sensitivity analyses for HR-QOL (n = 133), cost (n = 99), and discount rate (n = 128) were examined. Article mentions of thresholds for acceptable cost-utility ratios were recorded (total 36). Cost-utility ratios were denominated in US dollars for the year reported in each of the original articles in order to determine whether a different conclusion would have been indicated at the time the article was published. Quality ratings from the original audit for articles where sensitivity analysis results crossed the cost-utility ratio threshold above the base-case result were compared with those that did not. The most frequently mentioned cost-utility thresholds were $US20,000/QALY, $US50,000/QALY, and $US100,000/QALY. The proportions of sensitivity analyses reporting quantitative results that crossed the threshold above the base-case results (or where the sensitivity analysis result was dominated) were 31% for HR-QOL sensitivity analyses, 20% for cost-sensitivity analyses, and 15% for discount-rate sensitivity analyses. Almost half of the discount-rate sensitivity analyses did not report quantitative results. Articles that reported sensitivity analyses where results crossed the cost-utility threshold above the base-case results (n = 25) were of somewhat higher quality, and were more likely to justify their sensitivity analysis parameters, than those that did not (n = 45), but the overall quality rating was only moderate. Sensitivity analyses for economic parameters are widely reported and often identify whether choosing different assumptions leads to a different conclusion regarding cost effectiveness. Changes in HR-QOL and cost parameters should be used to test alternative guideline recommendations when there is uncertainty regarding these parameters. Changes in discount rates less frequently produce results that would change the conclusion about cost effectiveness. Improving the overall quality of published studies and describing the justifications for parameter ranges would allow more meaningful conclusions to be drawn from sensitivity analyses.

Rational selection of experimental readout and intervention sites for reducing uncertainties in computational model predictions.

PubMed

Flassig, Robert J; Migal, Iryna; der Zalm, Esther van; Rihko-Struckmann, Liisa; Sundmacher, Kai

2015-01-16

Understanding the dynamics of biological processes can substantially be supported by computational models in the form of nonlinear ordinary differential equations (ODE). Typically, this model class contains many unknown parameters, which are estimated from inadequate and noisy data. Depending on the ODE structure, predictions based on unmeasured states and associated parameters are highly uncertain, even undetermined. For given data, profile likelihood analysis has been proven to be one of the most practically relevant approaches for analyzing the identifiability of an ODE structure, and thus model predictions. In case of highly uncertain or non-identifiable parameters, rational experimental design based on various approaches has shown to significantly reduce parameter uncertainties with minimal amount of effort. In this work we illustrate how to use profile likelihood samples for quantifying the individual contribution of parameter uncertainty to prediction uncertainty. For the uncertainty quantification we introduce the profile likelihood sensitivity (PLS) index. Additionally, for the case of several uncertain parameters, we introduce the PLS entropy to quantify individual contributions to the overall prediction uncertainty. We show how to use these two criteria as an experimental design objective for selecting new, informative readouts in combination with intervention site identification. The characteristics of the proposed multi-criterion objective are illustrated with an in silico example. We further illustrate how an existing practically non-identifiable model for the chlorophyll fluorescence induction in a photosynthetic organism, D. salina, can be rendered identifiable by additional experiments with new readouts. Having data and profile likelihood samples at hand, the here proposed uncertainty quantification based on prediction samples from the profile likelihood provides a simple way for determining individual contributions of parameter uncertainties to uncertainties in model predictions. The uncertainty quantification of specific model predictions allows identifying regions, where model predictions have to be considered with care. Such uncertain regions can be used for a rational experimental design to render initially highly uncertain model predictions into certainty. Finally, our uncertainty quantification directly accounts for parameter interdependencies and parameter sensitivities of the specific prediction.

Parameter Optimization for Selected Correlation Analysis of Intracranial Pathophysiology.

PubMed

Faltermeier, Rupert; Proescholdt, Martin A; Bele, Sylvia; Brawanski, Alexander

2015-01-01

Recently we proposed a mathematical tool set, called selected correlation analysis, that reliably detects positive and negative correlations between arterial blood pressure (ABP) and intracranial pressure (ICP). Such correlations are associated with severe impairment of the cerebral autoregulation and intracranial compliance, as predicted by a mathematical model. The time resolved selected correlation analysis is based on a windowing technique combined with Fourier-based coherence calculations and therefore depends on several parameters. For real time application of this method at an ICU it is inevitable to adjust this mathematical tool for high sensitivity and distinct reliability. In this study, we will introduce a method to optimize the parameters of the selected correlation analysis by correlating an index, called selected correlation positive (SCP), with the outcome of the patients represented by the Glasgow Outcome Scale (GOS). For that purpose, the data of twenty-five patients were used to calculate the SCP value for each patient and multitude of feasible parameter sets of the selected correlation analysis. It could be shown that an optimized set of parameters is able to improve the sensitivity of the method by a factor greater than four in comparison to our first analyses.

Parameter Optimization for Selected Correlation Analysis of Intracranial Pathophysiology

PubMed Central

Faltermeier, Rupert; Proescholdt, Martin A.; Bele, Sylvia; Brawanski, Alexander

2015-01-01

Recently we proposed a mathematical tool set, called selected correlation analysis, that reliably detects positive and negative correlations between arterial blood pressure (ABP) and intracranial pressure (ICP). Such correlations are associated with severe impairment of the cerebral autoregulation and intracranial compliance, as predicted by a mathematical model. The time resolved selected correlation analysis is based on a windowing technique combined with Fourier-based coherence calculations and therefore depends on several parameters. For real time application of this method at an ICU it is inevitable to adjust this mathematical tool for high sensitivity and distinct reliability. In this study, we will introduce a method to optimize the parameters of the selected correlation analysis by correlating an index, called selected correlation positive (SCP), with the outcome of the patients represented by the Glasgow Outcome Scale (GOS). For that purpose, the data of twenty-five patients were used to calculate the SCP value for each patient and multitude of feasible parameter sets of the selected correlation analysis. It could be shown that an optimized set of parameters is able to improve the sensitivity of the method by a factor greater than four in comparison to our first analyses. PMID:26693250

High-sensitivity liquid refractive-index sensor based on a Mach-Zehnder interferometer with a double-slot hybrid plasmonic waveguide.

PubMed

Sun, Xu; Dai, Daoxin; Thylén, Lars; Wosinski, Lech

2015-10-05

A Mach-Zehnder Interferometer (MZI) liquid sensor, employing ultra-compact double-slot hybrid plasmonic (DSHP) waveguide as active sensing arm, is developed. Numerical results show that extremely large optical confinement factor of the tested analytes (as high as 88%) can be obtained by DSHP waveguide with optimized geometrical parameters, which is larger than both, conventional SOI waveguides and plasmonic slot waveguides with same widths. As for MZI sensor with 40μm long DSHP active sensing area, the sensitivity can reach as high value as 1061nm/RIU (refractive index unit). The total loss, excluding the coupling loss of the grating coupler, is around 4.5dB.

Effect of Operating Parameters on a Dual-Stage High Velocity Oxygen Fuel Thermal Spray System

NASA Astrophysics Data System (ADS)

Khan, Mohammed N.; Shamim, Tariq

2014-08-01

High velocity oxygen fuel (HVOF) thermal spray systems are being used to apply coatings to prevent surface degradation. The coatings of temperature sensitive materials such as titanium and copper, which have very low melting points, cannot be applied using a single-stage HVOF system. Therefore, a dual-stage HVOF system has been introduced and modeled computationally. The dual-spray system provides an easy control of particle oxidation by introducing a mixing chamber. In addition to the materials being sprayed, the thermal spray coating quality depends to a large extent on flow behavior of reacting gases and the particle dynamics. The present study investigates the influence of various operating parameters on the performance of a dual-stage thermal spray gun. The objective is to develop a predictive understanding of various parameters. The gas flow field and the free jet are modeled by considering the conservation of mass, momentum, and energy with the turbulence and the equilibrium combustion sub models. The particle phase is decoupled from the gas phase due to very low particle volume fractions. The results demonstrate the advantage of a dual-stage system over a single-stage system especially for the deposition of temperature sensitive materials.

Framework for making better predictions by directly estimating variables' predictivity.

PubMed

Lo, Adeline; Chernoff, Herman; Zheng, Tian; Lo, Shaw-Hwa

2016-12-13

We propose approaching prediction from a framework grounded in the theoretical correct prediction rate of a variable set as a parameter of interest. This framework allows us to define a measure of predictivity that enables assessing variable sets for, preferably high, predictivity. We first define the prediction rate for a variable set and consider, and ultimately reject, the naive estimator, a statistic based on the observed sample data, due to its inflated bias for moderate sample size and its sensitivity to noisy useless variables. We demonstrate that the [Formula: see text]-score of the PR method of VS yields a relatively unbiased estimate of a parameter that is not sensitive to noisy variables and is a lower bound to the parameter of interest. Thus, the PR method using the [Formula: see text]-score provides an effective approach to selecting highly predictive variables. We offer simulations and an application of the [Formula: see text]-score on real data to demonstrate the statistic's predictive performance on sample data. We conjecture that using the partition retention and [Formula: see text]-score can aid in finding variable sets with promising prediction rates; however, further research in the avenue of sample-based measures of predictivity is much desired.

Framework for making better predictions by directly estimating variables’ predictivity

PubMed Central

Chernoff, Herman; Lo, Shaw-Hwa

2016-01-01

We propose approaching prediction from a framework grounded in the theoretical correct prediction rate of a variable set as a parameter of interest. This framework allows us to define a measure of predictivity that enables assessing variable sets for, preferably high, predictivity. We first define the prediction rate for a variable set and consider, and ultimately reject, the naive estimator, a statistic based on the observed sample data, due to its inflated bias for moderate sample size and its sensitivity to noisy useless variables. We demonstrate that the I-score of the PR method of VS yields a relatively unbiased estimate of a parameter that is not sensitive to noisy variables and is a lower bound to the parameter of interest. Thus, the PR method using the I-score provides an effective approach to selecting highly predictive variables. We offer simulations and an application of the I-score on real data to demonstrate the statistic’s predictive performance on sample data. We conjecture that using the partition retention and I-score can aid in finding variable sets with promising prediction rates; however, further research in the avenue of sample-based measures of predictivity is much desired. PMID:27911830

Uncertainty Quantification and Assessment of CO2 Leakage in Groundwater Aquifers

NASA Astrophysics Data System (ADS)

Carroll, S.; Mansoor, K.; Sun, Y.; Jones, E.

2011-12-01

Complexity of subsurface aquifers and the geochemical reactions that control drinking water compositions complicate our ability to estimate the impact of leaking CO2 on groundwater quality. We combined lithologic field data from the High Plains Aquifer, numerical simulations, and uncertainty quantification analysis to assess the role of aquifer heterogeneity and physical transport on the extent of CO2 impacted plume over a 100-year period. The High Plains aquifer is a major aquifer over much of the central United States where CO2 may be sequestered in depleted oil and gas reservoirs or deep saline formations. Input parameters considered included, aquifer heterogeneity, permeability, porosity, regional groundwater flow, CO2 and TDS leakage rates over time, and the number of leakage source points. Sensitivity analysis suggest that variations in sand and clay permeability, correlation lengths, van Genuchten parameters, and CO2 leakage rate have the greatest impact on impacted volume or maximum distance from the leak source. A key finding is that relative sensitivity of the parameters changes over the 100-year period. Reduced order models developed from regression of the numerical simulations show that volume of the CO2-impacted aquifer increases over time with 2 order of magnitude variance.

Parameter Estimation and Sensitivity Analysis of an Urban Surface Energy Balance Parameterization at a Tropical Suburban Site

NASA Astrophysics Data System (ADS)

Harshan, S.; Roth, M.; Velasco, E.

2014-12-01

Forecasting of the urban weather and climate is of great importance as our cities become more populated and considering the combined effects of global warming and local land use changes which make urban inhabitants more vulnerable to e.g. heat waves and flash floods. In meso/global scale models, urban parameterization schemes are used to represent the urban effects. However, these schemes require a large set of input parameters related to urban morphological and thermal properties. Obtaining all these parameters through direct measurements are usually not feasible. A number of studies have reported on parameter estimation and sensitivity analysis to adjust and determine the most influential parameters for land surface schemes in non-urban areas. Similar work for urban areas is scarce, in particular studies on urban parameterization schemes in tropical cities have so far not been reported. In order to address above issues, the town energy balance (TEB) urban parameterization scheme (part of the SURFEX land surface modeling system) was subjected to a sensitivity and optimization/parameter estimation experiment at a suburban site in, tropical Singapore. The sensitivity analysis was carried out as a screening test to identify the most sensitive or influential parameters. Thereafter, an optimization/parameter estimation experiment was performed to calibrate the input parameter. The sensitivity experiment was based on the "improved Sobol's global variance decomposition method" . The analysis showed that parameters related to road, roof and soil moisture have significant influence on the performance of the model. The optimization/parameter estimation experiment was performed using the AMALGM (a multi-algorithm genetically adaptive multi-objective method) evolutionary algorithm. The experiment showed a remarkable improvement compared to the simulations using the default parameter set. The calibrated parameters from this optimization experiment can be used for further model validation studies to identify inherent deficiencies in model physics.

Sensitivities of Greenland ice sheet volume inferred from an ice sheet adjoint model

NASA Astrophysics Data System (ADS)

Heimbach, P.; Bugnion, V.

2009-04-01

We present a new and original approach to understanding the sensitivity of the Greenland ice sheet to key model parameters and environmental conditions. At the heart of this approach is the use of an adjoint ice sheet model. Since its introduction by MacAyeal (1992), the adjoint method has become widespread to fit ice stream models to the increasing number and diversity of satellite observations, and to estimate uncertain model parameters such as basal conditions. However, no attempt has been made to extend this method to comprehensive ice sheet models. As a first step toward the use of adjoints of comprehensive three-dimensional ice sheet models we have generated an adjoint of the ice sheet model SICOPOLIS of Greve (1997). The adjoint was generated by means of the automatic differentiation (AD) tool TAF. The AD tool generates exact source code representing the tangent linear and adjoint model of the nonlinear parent model provided. Model sensitivities are given by the partial derivatives of a scalar-valued model diagnostic with respect to the controls, and can be efficiently calculated via the adjoint. By way of example, we determine the sensitivity of the total Greenland ice volume to various control variables, such as spatial fields of basal flow parameters, surface and basal forcings, and initial conditions. Reliability of the adjoint was tested through finite-difference perturbation calculations for various control variables and perturbation regions. Besides confirming qualitative aspects of ice sheet sensitivities, such as expected regional variations, we detect regions where model sensitivities are seemingly unexpected or counter-intuitive, albeit ``real'' in the sense of actual model behavior. An example is inferred regions where sensitivities of ice sheet volume to basal sliding coefficient are positive, i.e. where a local increase in basal sliding parameter increases the ice sheet volume. Similarly, positive ice temperature sensitivities in certain parts of the ice sheet are found (in most regions it is negativ, i.e. an increase in temperature decreases ice sheet volume), the detection of which seems highly unlikely if only conventional perturbation experiments had been used. An effort to generate an efficient adjoint with the newly developed open-source AD tool OpenAD is also under way. Available adjoint code generation tools now open up a variety of novel model applications, notably with regard to sensitivity and uncertainty analyses and ice sheet state estimation or data assimilation.

Parameter regionalization of a monthly water balance model for the conterminous United States

USGS Publications Warehouse

Bock, Andrew R.; Hay, Lauren E.; McCabe, Gregory J.; Markstrom, Steven L.; Atkinson, R. Dwight

2016-01-01

A parameter regionalization scheme to transfer parameter values from gaged to ungaged areas for a monthly water balance model (MWBM) was developed and tested for the conterminous United States (CONUS). The Fourier Amplitude Sensitivity Test, a global-sensitivity algorithm, was implemented on a MWBM to generate parameter sensitivities on a set of 109 951 hydrologic response units (HRUs) across the CONUS. The HRUs were grouped into 110 calibration regions based on similar parameter sensitivities. Subsequently, measured runoff from 1575 streamgages within the calibration regions were used to calibrate the MWBM parameters to produce parameter sets for each calibration region. Measured and simulated runoff at the 1575 streamgages showed good correspondence for the majority of the CONUS, with a median computed Nash–Sutcliffe efficiency coefficient of 0.76 over all streamgages. These methods maximize the use of available runoff information, resulting in a calibrated CONUS-wide application of the MWBM suitable for providing estimates of water availability at the HRU resolution for both gaged and ungaged areas of the CONUS.

Parameter regionalization of a monthly water balance model for the conterminous United States

NASA Astrophysics Data System (ADS)

Bock, Andrew R.; Hay, Lauren E.; McCabe, Gregory J.; Markstrom, Steven L.; Atkinson, R. Dwight

2016-07-01

A parameter regionalization scheme to transfer parameter values from gaged to ungaged areas for a monthly water balance model (MWBM) was developed and tested for the conterminous United States (CONUS). The Fourier Amplitude Sensitivity Test, a global-sensitivity algorithm, was implemented on a MWBM to generate parameter sensitivities on a set of 109 951 hydrologic response units (HRUs) across the CONUS. The HRUs were grouped into 110 calibration regions based on similar parameter sensitivities. Subsequently, measured runoff from 1575 streamgages within the calibration regions were used to calibrate the MWBM parameters to produce parameter sets for each calibration region. Measured and simulated runoff at the 1575 streamgages showed good correspondence for the majority of the CONUS, with a median computed Nash-Sutcliffe efficiency coefficient of 0.76 over all streamgages. These methods maximize the use of available runoff information, resulting in a calibrated CONUS-wide application of the MWBM suitable for providing estimates of water availability at the HRU resolution for both gaged and ungaged areas of the CONUS.

An epidemiologic simulation model of the spread and control of highly pathogenic avian influenza (H5N1) among commercial and backyard poultry flocks in South Carolina, United States.

PubMed

Patyk, Kelly A; Helm, Julie; Martin, Michael K; Forde-Folle, Kimberly N; Olea-Popelka, Francisco J; Hokanson, John E; Fingerlin, Tasha; Reeves, Aaron

2013-07-01

Epidemiologic simulation modeling of highly pathogenic avian influenza (HPAI) outbreaks provides a useful conceptual framework with which to estimate the consequences of HPAI outbreaks and to evaluate disease control strategies. The purposes of this study were to establish detailed and informed input parameters for an epidemiologic simulation model of the H5N1 strain of HPAI among commercial and backyard poultry in the state of South Carolina in the United States using a highly realistic representation of this poultry population; to estimate the consequences of an outbreak of HPAI in this population with a model constructed from these parameters; and to briefly evaluate the sensitivity of model outcomes to several parameters. Parameters describing disease state durations; disease transmission via direct contact, indirect contact, and local-area spread; and disease detection, surveillance, and control were established through consultation with subject matter experts, a review of the current literature, and the use of several computational tools. The stochastic model constructed from these parameters produced simulated outbreaks ranging from 2 to 111 days in duration (median 25 days), during which 1 to 514 flocks were infected (median 28 flocks). Model results were particularly sensitive to the rate of indirect contact that occurs among flocks. The baseline model established in this study can be used in the future to evaluate various control strategies, as a tool for emergency preparedness and response planning, and to assess the costs associated with disease control and the economic consequences of a disease outbreak. Published by Elsevier B.V.

Sampled-Data Techniques Applied to a Digital Controller for an Altitude Autopilot

NASA Technical Reports Server (NTRS)

Schmidt, Stanley F.; Harper, Eleanor V.

1959-01-01

Sampled-data theory, using the Z transformation, is applied to the design of a digital controller for an aircraft-altitude autopilot. Particular attention is focused on the sensitivity of the design to parameter variations and the abruptness of the response, that is, the normal acceleration required to carry out a transient maneuver. Consideration of these two characteristics of the system has shown that the finite settling time design method produces an unacceptable system, primarily because of the high sensitivity of the response to parameter variations, although abruptness can be controlled by increasing the sampling period. Also demonstrated is the importance of having well-damped poles or zeros if cancellation is attempted in the design methods. A different method of smoothing the response and obtaining a design which is not excessively sensitive is proposed, and examples are carried through to demonstrate the validity of the procedure. This method is based on design concepts of continuous systems, and it is shown that if no pole-zero cancellations are allowed in the design, one can obtain a response which is not too abrupt, is relatively insensitive to parameter variations, and is not sensitive to practical limits on control-surface rate. This particular design also has the simplest possible pulse transfer function for the digital controller. Simulation techniques and root loci are used for the verification of the design philosophy.

Simultaneous measurement of magnetic field and temperature based on an etched TCFMI cascaded with an FBG

NASA Astrophysics Data System (ADS)

Yan, Guofeng; Zhang, Liang; He, Sailing

2016-04-01

In this paper, a dual-parameter measurement scheme based on an etched thin core fiber modal interferometer (TCMI) cascaded with a fiber Bragg grating (FBG) is proposed and experimentally demonstrated for simultaneous measurement of magnetic field and temperature. The magnetic field and temperature responses of the packaged TCFMI were first investigated, which showed that the magnetic field sensitivity could be highly enhanced by decreasing of the TCF diameter and the temperature-cross sensitivities were up to 3-7 Oe/°C at 1550 nm. Then, the theoretical analysis and experimental demonstration of the proposed dual-parameter sensing scheme were conducted. Experimental results show that, the reflection of the FBG has a magnetic field intensity and temperature sensitivities of -0.017 dB/Oe and 0.133 dB/°C, respectively, while the Bragg wavelength of the FBG is insensitive to magnetic field and has a temperature sensitivity of 13.23 pm/°C. Thus by using the sensing matrix method, the intensity of the magnetic field and the temperature variance can be measured, which enables magnetic field sensing under strict temperature environments. In the on-off time response test, the fabricated sensor exhibited high repeatability and short response time of ∼19.4 s. Meanwhile the reflective sensing probe type is more compact and practical for applications in hard-to-reach conditions.

Development, sensitivity and uncertainty analysis of LASH model

USDA-ARS?s Scientific Manuscript database

Many hydrologic models have been developed to help manage natural resources all over the world. Nevertheless, most models have presented a high complexity regarding data base requirements, as well as, many calibration parameters. This has brought serious difficulties for applying them in watersheds ...

Iterative integral parameter identification of a respiratory mechanics model.

PubMed

Schranz, Christoph; Docherty, Paul D; Chiew, Yeong Shiong; Möller, Knut; Chase, J Geoffrey

2012-07-18

Patient-specific respiratory mechanics models can support the evaluation of optimal lung protective ventilator settings during ventilation therapy. Clinical application requires that the individual's model parameter values must be identified with information available at the bedside. Multiple linear regression or gradient-based parameter identification methods are highly sensitive to noise and initial parameter estimates. Thus, they are difficult to apply at the bedside to support therapeutic decisions. An iterative integral parameter identification method is applied to a second order respiratory mechanics model. The method is compared to the commonly used regression methods and error-mapping approaches using simulated and clinical data. The clinical potential of the method was evaluated on data from 13 Acute Respiratory Distress Syndrome (ARDS) patients. The iterative integral method converged to error minima 350 times faster than the Simplex Search Method using simulation data sets and 50 times faster using clinical data sets. Established regression methods reported erroneous results due to sensitivity to noise. In contrast, the iterative integral method was effective independent of initial parameter estimations, and converged successfully in each case tested. These investigations reveal that the iterative integral method is beneficial with respect to computing time, operator independence and robustness, and thus applicable at the bedside for this clinical application.

Peak high-frequency HRV and peak alpha frequency higher in PTSD.

PubMed

Wahbeh, Helané; Oken, Barry S

2013-03-01

Posttraumatic stress disorder (PTSD) is difficult to treat and current PTSD treatments are not effective for all people. Despite limited evidence for its efficacy, some clinicians have implemented biofeedback for PTSD treatment. As a first step in constructing an effective biofeedback treatment program, we assessed respiration, electroencephalography (EEG) and heart rate variability (HRV) as potential biofeedback parameters for a future clinical trial. This cross-sectional study included 86 veterans; 59 with and 27 without PTSD. Data were collected on EEG measures, HRV, and respiration rate during an attentive resting state. Measures were analyzed to assess sensitivity to PTSD status and the relationship to PTSD symptoms. Peak alpha frequency was higher in the PTSD group (F(1,84) = 6.14, p = 0.01). Peak high-frequency HRV was lower in the PTSD group (F(2,78) = 26.5, p < 0.00005) when adjusting for respiration rate. All other EEG and HRV measures and respiration were not different between groups. Peak high-frequency HRV and peak alpha frequency are sensitive to PTSD status and may be potential biofeedback parameters for future PTSD clinical trials.

Peak High-Frequency HRV and Peak Alpha Frequency Higher in PTSD

PubMed Central

Oken, Barry S.

2012-01-01

Posttraumatic stress disorder (PTSD) is difficult to treat and current PTSD treatments are not effective for all people. Despite limited evidence for its efficacy, some clinicians have implemented biofeedback for PTSD treatment. As a first step in constructing an effective biofeedback treatment program, we assessed respiration, electroencephalography (EEG) and heart rate variability (HRV) as potential biofeedback parameters for a future clinical trial. This cross-sectional study included 86 veterans; 59 with and 27 without PTSD. Data were collected on EEG measures, HRV, and respiration rate during an attentive resting state. Measures were analyzed to assess sensitivity to PTSD status and the relationship to PTSD symptoms. Peak alpha frequency was higher in the PTSD group (F(1,84) = 6.14, p = 0.01). Peak high-frequency HRV was lower in the PTSD group (F(2,78) = 26.5, p<0.00005) when adjusting for respiration rate. All other EEG and HRV measures and respiration were not different between groups. Peak high-frequency HRV and peak alpha frequency are sensitive to PTSD status and may be potential biofeedback parameters for future PTSD clinical trials. PMID:23178990

A Global Sensitivity Analysis Method on Maximum Tsunami Wave Heights to Potential Seismic Source Parameters

NASA Astrophysics Data System (ADS)

Ren, Luchuan

2015-04-01

A Global Sensitivity Analysis Method on Maximum Tsunami Wave Heights to Potential Seismic Source Parameters Luchuan Ren, Jianwei Tian, Mingli Hong Institute of Disaster Prevention, Sanhe, Heibei Province, 065201, P.R. China It is obvious that the uncertainties of the maximum tsunami wave heights in offshore area are partly from uncertainties of the potential seismic tsunami source parameters. A global sensitivity analysis method on the maximum tsunami wave heights to the potential seismic source parameters is put forward in this paper. The tsunami wave heights are calculated by COMCOT ( the Cornell Multi-grid Coupled Tsunami Model), on the assumption that an earthquake with magnitude MW8.0 occurred at the northern fault segment along the Manila Trench and triggered a tsunami in the South China Sea. We select the simulated results of maximum tsunami wave heights at specific sites in offshore area to verify the validity of the method proposed in this paper. For ranking importance order of the uncertainties of potential seismic source parameters (the earthquake's magnitude, the focal depth, the strike angle, dip angle and slip angle etc..) in generating uncertainties of the maximum tsunami wave heights, we chose Morris method to analyze the sensitivity of the maximum tsunami wave heights to the aforementioned parameters, and give several qualitative descriptions of nonlinear or linear effects of them on the maximum tsunami wave heights. We quantitatively analyze the sensitivity of the maximum tsunami wave heights to these parameters and the interaction effects among these parameters on the maximum tsunami wave heights by means of the extended FAST method afterward. The results shows that the maximum tsunami wave heights are very sensitive to the earthquake magnitude, followed successively by the epicenter location, the strike angle and dip angle, the interactions effect between the sensitive parameters are very obvious at specific site in offshore area, and there exist differences in importance order in generating uncertainties of the maximum tsunami wave heights for same group parameters at different specific sites in offshore area. These results are helpful to deeply understand the relationship between the tsunami wave heights and the seismic tsunami source parameters. Keywords: Global sensitivity analysis; Tsunami wave height; Potential seismic tsunami source parameter; Morris method; Extended FAST method

Sensitivity analysis and uncertainty estimation in ash concentration simulations and tephra deposit daily forecasted at Mt. Etna, in Italy

NASA Astrophysics Data System (ADS)

Prestifilippo, Michele; Scollo, Simona; Tarantola, Stefano

2015-04-01

The uncertainty in volcanic ash forecasts may depend on our knowledge of the model input parameters and our capability to represent the dynamic of an incoming eruption. Forecasts help governments to reduce risks associated with volcanic eruptions and for this reason different kinds of analysis that help to understand the effect that each input parameter has on model outputs are necessary. We present an iterative approach based on the sequential combination of sensitivity analysis, parameter estimation procedure and Monte Carlo-based uncertainty analysis, applied to the lagrangian volcanic ash dispersal model PUFF. We modify the main input parameters as the total mass, the total grain-size distribution, the plume thickness, the shape of the eruption column, the sedimentation models and the diffusion coefficient, perform thousands of simulations and analyze the results. The study is carried out on two different Etna scenarios: the sub-plinian eruption of 22 July 1998 that formed an eruption column rising 12 km above sea level and lasted some minutes and the lava fountain eruption having features similar to the 2011-2013 events that produced eruption column high up to several kilometers above sea level and lasted some hours. Sensitivity analyses and uncertainty estimation results help us to address the measurements that volcanologists should perform during volcanic crisis to reduce the model uncertainty.

Uncertainty and sensitivity analysis of fission gas behavior in engineering-scale fuel modeling

DOE PAGES

Pastore, Giovanni; Swiler, L. P.; Hales, Jason D.; ...

2014-10-12

The role of uncertainties in fission gas behavior calculations as part of engineering-scale nuclear fuel modeling is investigated using the BISON fuel performance code and a recently implemented physics-based model for the coupled fission gas release and swelling. Through the integration of BISON with the DAKOTA software, a sensitivity analysis of the results to selected model parameters is carried out based on UO2 single-pellet simulations covering different power regimes. The parameters are varied within ranges representative of the relative uncertainties and consistent with the information from the open literature. The study leads to an initial quantitative assessment of the uncertaintymore » in fission gas behavior modeling with the parameter characterization presently available. Also, the relative importance of the single parameters is evaluated. Moreover, a sensitivity analysis is carried out based on simulations of a fuel rod irradiation experiment, pointing out a significant impact of the considered uncertainties on the calculated fission gas release and cladding diametral strain. The results of the study indicate that the commonly accepted deviation between calculated and measured fission gas release by a factor of 2 approximately corresponds to the inherent modeling uncertainty at high fission gas release. Nevertheless, higher deviations may be expected for values around 10% and lower. Implications are discussed in terms of directions of research for the improved modeling of fission gas behavior for engineering purposes.« less

Sensitivity analysis of the add-on price estimate for the edge-defined film-fed growth process

NASA Technical Reports Server (NTRS)

Mokashi, A. R.; Kachare, A. H.

1981-01-01

The analysis is in terms of cost parameters and production parameters. The cost parameters include equipment, space, direct labor, materials, and utilities. The production parameters include growth rate, process yield, and duty cycle. A computer program was developed specifically to do the sensitivity analysis.

Scalable Online Network Modeling and Simulation

DTIC Science & Technology

2005-08-01

ONLINE NETWORK MODELING AND SIMULATION 6. AUTHOR(S) Boleslaw Szymanski , Shivkumar Kalyanaraman, Biplab Sikdar and Christopher Carothers 5...performance for a wide range of parameter values (parameter sensitivity), understanding of protocol stability and dynamics, and studying feature ...a wide range of parameter values (parameter sensitivity), understanding of protocol stability and dynamics, and studying feature interactions

Development of a generalized perturbation theory method for sensitivity analysis using continuous-energy Monte Carlo methods

DOE PAGES

Perfetti, Christopher M.; Rearden, Bradley T.

2016-03-01

The sensitivity and uncertainty analysis tools of the ORNL SCALE nuclear modeling and simulation code system that have been developed over the last decade have proven indispensable for numerous application and design studies for nuclear criticality safety and reactor physics. SCALE contains tools for analyzing the uncertainty in the eigenvalue of critical systems, but cannot quantify uncertainty in important neutronic parameters such as multigroup cross sections, fuel fission rates, activation rates, and neutron fluence rates with realistic three-dimensional Monte Carlo simulations. A more complete understanding of the sources of uncertainty in these design-limiting parameters could lead to improvements in processmore » optimization, reactor safety, and help inform regulators when setting operational safety margins. A novel approach for calculating eigenvalue sensitivity coefficients, known as the CLUTCH method, was recently explored as academic research and has been found to accurately and rapidly calculate sensitivity coefficients in criticality safety applications. The work presented here describes a new method, known as the GEAR-MC method, which extends the CLUTCH theory for calculating eigenvalue sensitivity coefficients to enable sensitivity coefficient calculations and uncertainty analysis for a generalized set of neutronic responses using high-fidelity continuous-energy Monte Carlo calculations. Here, several criticality safety systems were examined to demonstrate proof of principle for the GEAR-MC method, and GEAR-MC was seen to produce response sensitivity coefficients that agreed well with reference direct perturbation sensitivity coefficients.« less

Adjoint sensitivity analysis of plasmonic structures using the FDTD method.

PubMed

Zhang, Yu; Ahmed, Osman S; Bakr, Mohamed H

2014-05-15

We present an adjoint variable method for estimating the sensitivities of arbitrary responses with respect to the parameters of dispersive discontinuities in nanoplasmonic devices. Our theory is formulated in terms of the electric field components at the vicinity of perturbed discontinuities. The adjoint sensitivities are computed using at most one extra finite-difference time-domain (FDTD) simulation regardless of the number of parameters. Our approach is illustrated through the sensitivity analysis of an add-drop coupler consisting of a square ring resonator between two parallel waveguides. The computed adjoint sensitivities of the scattering parameters are compared with those obtained using the accurate but computationally expensive central finite difference approach.

Reduction and Uncertainty Analysis of Chemical Mechanisms Based on Local and Global Sensitivities

NASA Astrophysics Data System (ADS)

Esposito, Gaetano

Numerical simulations of critical reacting flow phenomena in hypersonic propulsion devices require accurate representation of finite-rate chemical kinetics. The chemical kinetic models available for hydrocarbon fuel combustion are rather large, involving hundreds of species and thousands of reactions. As a consequence, they cannot be used in multi-dimensional computational fluid dynamic calculations in the foreseeable future due to the prohibitive computational cost. In addition to the computational difficulties, it is also known that some fundamental chemical kinetic parameters of detailed models have significant level of uncertainty due to limited experimental data available and to poor understanding of interactions among kinetic parameters. In the present investigation, local and global sensitivity analysis techniques are employed to develop a systematic approach of reducing and analyzing detailed chemical kinetic models. Unlike previous studies in which skeletal model reduction was based on the separate analysis of simple cases, in this work a novel strategy based on Principal Component Analysis of local sensitivity values is presented. This new approach is capable of simultaneously taking into account all the relevant canonical combustion configurations over different composition, temperature and pressure conditions. Moreover, the procedure developed in this work represents the first documented inclusion of non-premixed extinction phenomena, which is of great relevance in hypersonic combustors, in an automated reduction algorithm. The application of the skeletal reduction to a detailed kinetic model consisting of 111 species in 784 reactions is demonstrated. The resulting reduced skeletal model of 37--38 species showed that the global ignition/propagation/extinction phenomena of ethylene-air mixtures can be predicted within an accuracy of 2% of the full detailed model. The problems of both understanding non-linear interactions between kinetic parameters and identifying sources of uncertainty affecting relevant reaction pathways are usually addressed by resorting to Global Sensitivity Analysis (GSA) techniques. In particular, the most sensitive reactions controlling combustion phenomena are first identified using the Morris Method and then analyzed under the Random Sampling -- High Dimensional Model Representation (RS-HDMR) framework. The HDMR decomposition shows that 10% of the variance seen in the extinction strain rate of non-premixed flames is due to second-order effects between parameters, whereas the maximum concentration of acetylene, a key soot precursor, is affected by mostly only first-order contributions. Moreover, the analysis of the global sensitivity indices demonstrates that improving the accuracy of the reaction rates including the vinyl radical, C2H3, can drastically reduce the uncertainty of predicting targeted flame properties. Finally, the back-propagation of the experimental uncertainty of the extinction strain rate to the parameter space is also performed. This exercise, achieved by recycling the numerical solutions of the RS-HDMR, shows that some regions of the parameter space have a high probability of reproducing the experimental value of the extinction strain rate between its own uncertainty bounds. Therefore this study demonstrates that the uncertainty analysis of bulk flame properties can effectively provide information on relevant chemical reactions.

Macular versus Retinal Nerve Fiber Layer Parameters for Diagnosing Manifest Glaucoma: A Systematic Review of Diagnostic Accuracy Studies.

PubMed

Oddone, Francesco; Lucenteforte, Ersilia; Michelessi, Manuele; Rizzo, Stanislao; Donati, Simone; Parravano, Mariacristina; Virgili, Gianni

2016-05-01

Macular parameters have been proposed as an alternative to retinal nerve fiber layer (RNFL) parameters to diagnose glaucoma. Comparing the diagnostic accuracy of macular parameters, specifically the ganglion cell complex (GCC) and ganglion cell inner plexiform layer (GCIPL), with the accuracy of RNFL parameters for detecting manifest glaucoma is important to guide clinical practice and future research. Studies using spectral domain optical coherence tomography (SD OCT) and reporting macular parameters were included if they allowed the extraction of accuracy data for diagnosing manifest glaucoma, as confirmed with automated perimetry or a clinician's optic nerve head (ONH) assessment. Cross-sectional cohort studies and case-control studies were included. The QUADAS 2 tool was used to assess methodological quality. Only direct comparisons of macular versus RNFL parameters (i.e., in the same study) were conducted. Summary sensitivity and specificity of each macular or RNFL parameter were reported, and the relative diagnostic odds ratio (DOR) was calculated in hierarchical summary receiver operating characteristic (HSROC) models to compare them. Thirty-four studies investigated macular parameters using RTVue OCT (Optovue Inc., Fremont, CA) (19 studies, 3094 subjects), Cirrus OCT (Carl Zeiss Meditec Inc., Dublin, CA) (14 studies, 2164 subjects), or 3D Topcon OCT (Topcon, Inc., Tokyo, Japan) (4 studies, 522 subjects). Thirty-two of these studies allowed comparisons between macular and RNFL parameters. Studies generally reported sensitivities at fixed specificities, more commonly 0.90 or 0.95, with sensitivities of most best-performing parameters between 0.65 and 0.75. For all OCT devices, compared with RNFL parameters, macular parameters were similarly or slightly less accurate for detecting glaucoma at the highest reported specificity, which was confirmed in analyses at the lowest specificity. Included studies suffered from limitations, especially the case-control study design, which is known to overestimate accuracy. However, this flaw is less relevant as a source of bias in direct comparisons conducted within studies. With the use of OCT, RNFL parameters are still preferable to macular parameters for diagnosing manifest glaucoma, but the differences are small. Because of high heterogeneity, direct comparative or randomized studies of OCT devices or OCT parameters and diagnostic strategies are essential. Copyright © 2016 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

SU-E-T-249: Determining the Sensitivity of Beam Profile Parameters for Detecting Energy Changes in Flattening Filter-Free Beams

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

Mooney, K; Yaddanapudi, S; Mutic, S

2015-06-15

Purpose: To identify the beam profile parameters that can be used to detect energy changes in a flattening filter-free photon beams. Methods: Flattening filter-free beam profiles (inline, crossline, and diagonals) were measured for multiple field sizes (25×25cm and 10×10cm) at 6MV on a clinical system (Truebeam, Varian Medical Systems Palo Alto CA). Profiles were acquired for baseline energy and detuned beams by changing the bending magnet current (BMC), above and below baseline. The following profile parameters were measured: flatness (off-axis ratio at 80% of field size), symmetry, uniformity, slope, and the off-axis ratio (OAR) at several off-axis distances. Tolerance valuesmore » were determined from repeated measurements. Each parameter was evaluated for sensitivity to the induced beam changes, and the minimum detectable BMC change was calculated for each parameter by calculating the change in BMC that would Result in a change in the parameter above the measurement tolerance. Results: Tolerance values for the parameters were-Flatness≤0.1%; Symmetry≤0.4%; Uniformity≤0.01%; Slope≤ 0.001%/mm. The measurements made with a field size of 25cm and a depth of d=1.5cm showed the greatest sensitivity to bending magnet current variations. Uniformity had the highest sensitivity, able to detect a change in BMC of BMC=0.02A. The OARs and slope were sensitive to the magnitude and direction of BMC change. The sensitivity in the flatness parameter was BMC=0.04A; slope was sensitive to BMC=0.05A. The sensitivity decreased for OARs measured closer to central axis-BMC(8cm)=0.23A; BMC(5cm)=0.47A; BMC(2cm)=1.35A. Symmetry was not sensitive to changes in BMC. Conclusion: These tests allow for better QA of FFF beams by setting tolerance levels to beam parameter baseline values which reflect variations in machine calibration. Uniformity is most sensitive to BMC changes, while OARs provide information about magnitude and direction of miscalibration. Research funding provided by Varian Medical Systems. Dr. Sasa Mutic receives compensation for providing patient safety training services from Varian Medical Systems, the sponsor of this study.« less

Mössbauer studies of malaria

NASA Astrophysics Data System (ADS)

Bauminger, E. R.; Ginsburg, H.; Ofer, S.; Yayon, A.

1983-12-01

Mössbauer studies of rat and human erythrocytes infected by malarial parasites have been carried out. Different parameters of the pigment iron were obtained in human and rat infected red blood cells. No difference was found between the parameters obtained in rat erythrocytes infected by drug sensitive and drug resistant strains of p. berghei, both before and after the treatment with chloroquine. The pigment was shown to contain a trivalent, high spin iron compound, which is different from hematin.

Evaluation of Uncertainty in Constituent Input Parameters for Modeling the Fate of RDX

DTIC Science & Technology

2015-07-01

exercise was to evaluate the importance of chemical -specific model input parameters, the impacts of their uncertainty, and the potential benefits of... chemical -specific inputs for RDX that were determined to be sensitive with relatively high uncertainty: these included the soil-water linear...Koc for organic chemicals . The EFS values provided for log Koc of RDX were 1.72 and 1.95. OBJECTIVE: TREECS™ (http://el.erdc.usace.army.mil/treecs

Exploring sensitivity of a multistate occupancy model to inform management decisions

USGS Publications Warehouse

Green, A.W.; Bailey, L.L.; Nichols, J.D.

2011-01-01

Dynamic occupancy models are often used to investigate questions regarding the processes that influence patch occupancy and are prominent in the fields of population and community ecology and conservation biology. Recently, multistate occupancy models have been developed to investigate dynamic systems involving more than one occupied state, including reproductive states, relative abundance states and joint habitat-occupancy states. Here we investigate the sensitivities of the equilibrium-state distribution of multistate occupancy models to changes in transition rates. We develop equilibrium occupancy expressions and their associated sensitivity metrics for dynamic multistate occupancy models. To illustrate our approach, we use two examples that represent common multistate occupancy systems. The first example involves a three-state dynamic model involving occupied states with and without successful reproduction (California spotted owl Strix occidentalis occidentalis), and the second involves a novel way of using a multistate occupancy approach to accommodate second-order Markov processes (wood frog Lithobates sylvatica breeding and metamorphosis). In many ways, multistate sensitivity metrics behave in similar ways as standard occupancy sensitivities. When equilibrium occupancy rates are low, sensitivity to parameters related to colonisation is high, while sensitivity to persistence parameters is greater when equilibrium occupancy rates are high. Sensitivities can also provide guidance for managers when estimates of transition probabilities are not available. Synthesis and applications. Multistate models provide practitioners a flexible framework to define multiple, distinct occupied states and the ability to choose which state, or combination of states, is most relevant to questions and decisions about their own systems. In addition to standard multistate occupancy models, we provide an example of how a second-order Markov process can be modified to fit a multistate framework. Assuming the system is near equilibrium, our sensitivity analyses illustrate how to investigate the sensitivity of the system-specific equilibrium state(s) to changes in transition rates. Because management will typically act on these transition rates, sensitivity analyses can provide valuable information about the potential influence of different actions and when it may be prudent to shift the focus of management among the various transition rates. ?? 2011 The Authors. Journal of Applied Ecology ?? 2011 British Ecological Society.

Impact of the irregular microgeometry of polyurethane foam on the macroscopic acoustic behavior predicted by a unit-cell model.

PubMed

Doutres, O; Ouisse, M; Atalla, N; Ichchou, M

2014-10-01

This paper deals with the prediction of the macroscopic sound absorption behavior of highly porous polyurethane foams using two unit-cell microstructure-based models recently developed by Doutres, Atalla, and Dong [J. Appl. Phys. 110, 064901 (2011); J. Appl. Phys. 113, 054901 (2013)]. In these models, the porous material is idealized as a packing of a tetrakaidecahedra unit-cell representative of the disordered network that constitutes the porous frame. The non-acoustic parameters involved in the classical Johnson-Champoux-Allard model (i.e., porosity, airflow resistivity, tortuosity, etc.) are derived from characteristic properties of the unit-cell and semi-empirical relationships. A global sensitivity analysis is performed on these two models in order to investigate how the variability associated with the measured unit-cell characteristics affects the models outputs. This allows identification of the possible limitations of a unit-cell micro-macro approach due to microstructure irregularity. The sensitivity analysis mainly shows that for moderately and highly reticulated polyurethane foams, the strut length parameter is the key parameter since it greatly impacts three important non-acoustic parameters and causes large uncertainty on the sound absorption coefficient even if its measurement variability is moderate. For foams with a slight inhomogeneity and anisotropy, a micro-macro model associated to cell size measurements should be preferred.

WE-D-BRE-07: Variance-Based Sensitivity Analysis to Quantify the Impact of Biological Uncertainties in Particle Therapy

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

Kamp, F.; Brueningk, S.C.; Wilkens, J.J.

Purpose: In particle therapy, treatment planning and evaluation are frequently based on biological models to estimate the relative biological effectiveness (RBE) or the equivalent dose in 2 Gy fractions (EQD2). In the context of the linear-quadratic model, these quantities depend on biological parameters (α, β) for ions as well as for the reference radiation and on the dose per fraction. The needed biological parameters as well as their dependency on ion species and ion energy typically are subject to large (relative) uncertainties of up to 20–40% or even more. Therefore it is necessary to estimate the resulting uncertainties in e.g.more » RBE or EQD2 caused by the uncertainties of the relevant input parameters. Methods: We use a variance-based sensitivity analysis (SA) approach, in which uncertainties in input parameters are modeled by random number distributions. The evaluated function is executed 10{sup 4} to 10{sup 6} times, each run with a different set of input parameters, randomly varied according to their assigned distribution. The sensitivity S is a variance-based ranking (from S = 0, no impact, to S = 1, only influential part) of the impact of input uncertainties. The SA approach is implemented for carbon ion treatment plans on 3D patient data, providing information about variations (and their origin) in RBE and EQD2. Results: The quantification enables 3D sensitivity maps, showing dependencies of RBE and EQD2 on different input uncertainties. The high number of runs allows displaying the interplay between different input uncertainties. The SA identifies input parameter combinations which result in extreme deviations of the result and the input parameter for which an uncertainty reduction is the most rewarding. Conclusion: The presented variance-based SA provides advantageous properties in terms of visualization and quantification of (biological) uncertainties and their impact. The method is very flexible, model independent, and enables a broad assessment of uncertainties. Supported by DFG grant WI 3745/1-1 and DFG cluster of excellence: Munich-Centre for Advanced Photonics.« less

Modeling and sensitivity analysis of mass transfer in active multilayer polymeric film for food applications

NASA Astrophysics Data System (ADS)

Bedane, T.; Di Maio, L.; Scarfato, P.; Incarnato, L.; Marra, F.

2015-12-01

The barrier performance of multilayer polymeric films for food applications has been significantly improved by incorporating oxygen scavenging materials. The scavenging activity depends on parameters such as diffusion coefficient, solubility, concentration of scavenger loaded and the number of available reactive sites. These parameters influence the barrier performance of the film in different ways. Virtualization of the process is useful to characterize, design and optimize the barrier performance based on physical configuration of the films. Also, the knowledge of values of parameters is important to predict the performances. Inverse modeling and sensitivity analysis are sole way to find reasonable values of poorly defined, unmeasured parameters and to analyze the most influencing parameters. Thus, the objective of this work was to develop a model to predict barrier properties of multilayer film incorporated with reactive layers and to analyze and characterize their performances. Polymeric film based on three layers of Polyethylene terephthalate (PET), with a core reactive layer, at different thickness configurations was considered in the model. A one dimensional diffusion equation with reaction was solved numerically to predict the concentration of oxygen diffused into the polymer taking into account the reactive ability of the core layer. The model was solved using commercial software for different film layer configurations and sensitivity analysis based on inverse modeling was carried out to understand the effect of physical parameters. The results have shown that the use of sensitivity analysis can provide physical understanding of the parameters which highly affect the gas permeation into the film. Solubility and the number of available reactive sites were the factors mainly influencing the barrier performance of three layered polymeric film. Multilayer films slightly modified the steady transport properties in comparison to net PET, giving a small reduction in the permeability and oxygen transfer rate values. Scavenging capacity of the multilayer film increased linearly with the increase of the reactive layer thickness and the oxygen absorption reaction at short times decreased proportionally with the thickness of the external PET layer.

Modeling and sensitivity analysis of mass transfer in active multilayer polymeric film for food applications

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

Bedane, T.; Di Maio, L.; Scarfato, P.

The barrier performance of multilayer polymeric films for food applications has been significantly improved by incorporating oxygen scavenging materials. The scavenging activity depends on parameters such as diffusion coefficient, solubility, concentration of scavenger loaded and the number of available reactive sites. These parameters influence the barrier performance of the film in different ways. Virtualization of the process is useful to characterize, design and optimize the barrier performance based on physical configuration of the films. Also, the knowledge of values of parameters is important to predict the performances. Inverse modeling and sensitivity analysis are sole way to find reasonable values ofmore » poorly defined, unmeasured parameters and to analyze the most influencing parameters. Thus, the objective of this work was to develop a model to predict barrier properties of multilayer film incorporated with reactive layers and to analyze and characterize their performances. Polymeric film based on three layers of Polyethylene terephthalate (PET), with a core reactive layer, at different thickness configurations was considered in the model. A one dimensional diffusion equation with reaction was solved numerically to predict the concentration of oxygen diffused into the polymer taking into account the reactive ability of the core layer. The model was solved using commercial software for different film layer configurations and sensitivity analysis based on inverse modeling was carried out to understand the effect of physical parameters. The results have shown that the use of sensitivity analysis can provide physical understanding of the parameters which highly affect the gas permeation into the film. Solubility and the number of available reactive sites were the factors mainly influencing the barrier performance of three layered polymeric film. Multilayer films slightly modified the steady transport properties in comparison to net PET, giving a small reduction in the permeability and oxygen transfer rate values. Scavenging capacity of the multilayer film increased linearly with the increase of the reactive layer thickness and the oxygen absorption reaction at short times decreased proportionally with the thickness of the external PET layer.« less

Global Sensitivity Analysis of Environmental Models: Convergence, Robustness and Validation

NASA Astrophysics Data System (ADS)

Sarrazin, Fanny; Pianosi, Francesca; Khorashadi Zadeh, Farkhondeh; Van Griensven, Ann; Wagener, Thorsten

2015-04-01

Global Sensitivity Analysis aims to characterize the impact that variations in model input factors (e.g. the parameters) have on the model output (e.g. simulated streamflow). In sampling-based Global Sensitivity Analysis, the sample size has to be chosen carefully in order to obtain reliable sensitivity estimates while spending computational resources efficiently. Furthermore, insensitive parameters are typically identified through the definition of a screening threshold: the theoretical value of their sensitivity index is zero but in a sampling-base framework they regularly take non-zero values. There is little guidance available for these two steps in environmental modelling though. The objective of the present study is to support modellers in making appropriate choices, regarding both sample size and screening threshold, so that a robust sensitivity analysis can be implemented. We performed sensitivity analysis for the parameters of three hydrological models with increasing level of complexity (Hymod, HBV and SWAT), and tested three widely used sensitivity analysis methods (Elementary Effect Test or method of Morris, Regional Sensitivity Analysis, and Variance-Based Sensitivity Analysis). We defined criteria based on a bootstrap approach to assess three different types of convergence: the convergence of the value of the sensitivity indices, of the ranking (the ordering among the parameters) and of the screening (the identification of the insensitive parameters). We investigated the screening threshold through the definition of a validation procedure. The results showed that full convergence of the value of the sensitivity indices is not necessarily needed to rank or to screen the model input factors. Furthermore, typical values of the sample sizes that are reported in the literature can be well below the sample sizes that actually ensure convergence of ranking and screening.

Obtaining changes in calibration-coil to seismometer output constants using sine waves

USGS Publications Warehouse

Ringler, Adam T.; Hutt, Charles R.; Gee, Lind S.; Sandoval, Leo D.; Wilson, David C.

2013-01-01

The midband sensitivity of a broadband seismometer is one of the most commonly used parameters from station metadata. Thus, it is critical for station operators to robustly estimate this quantity with a high degree of accuracy. We develop an in situ method for estimating changes in sensitivity using sine‐wave calibrations, assuming the calibration coil and its drive are stable over time and temperature. This approach has been used in the past for passive instruments (e.g., geophones) but has not been applied, to our knowledge, to derive sensitivities of modern force‐feedback broadband seismometers. We are able to detect changes in sensitivity to well within 1%, and our method is capable of detecting these sensitivity changes using any frequency of sine calibration within the passband of the instrument.

Predictive Uncertainty And Parameter Sensitivity Of A Sediment-Flux Model: Nitrogen Flux and Sediment Oxygen Demand

EPA Science Inventory

Estimating model predictive uncertainty is imperative to informed environmental decision making and management of water resources. This paper applies the Generalized Sensitivity Analysis (GSA) to examine parameter sensitivity and the Generalized Likelihood Uncertainty Estimation...

High Sensitive Precise 3D Accelerometer for Solar System Exploration with Unmanned Spacecrafts

NASA Astrophysics Data System (ADS)

Savenko, Y. V.; Demyanenko, P. O.; Zinkovskiy, Y. F.

Solutions of several space and geophysical tasks require creating high sensitive precise accelerometers with sensitivity in order of 10 -13 g. These several tasks are following: inertial navigation of the Earth and Space; gravimetry nearby the Earth and into Space; geology; geophysics; seismology etc. Accelerometers (gravimeters and gradientmeters) with required sensitivity are not available now. The best accelerometers in the world have sensitivity worth on 4-5 orders. It has been developed a new class of fiber-optical sensors (FOS) with light pulse modulation. These sensors have super high threshold sensitivity and wide (up to 10 orders) dynamic range, and can be used as a base for creating of measurement units of physical values as 3D superhigh sensitive precise accelerometers of linear accelerations that is suitable for highest requirements. The principle of operation of the FOS is organically combined with a digital signal processing. It allows decreasing hardware of the accelerometer due to using a usual air-borne or space-borne computer; correcting the influence of natural, design, technological drawbacks of FOS on measured results; neutralising the influence of extraordinary situations available during using of FOS; decreasing the influence of internal and external destabilising factors (as for FOS), such as oscillation of environment temperature, instability of pendulum cycle frequency of sensitive element of the accelerometer etc. We were conducted a quantitative estimation of precise opportunities of analogue FOS in structure of fiber optical measuring devices (FOMD) for elementary FOMD with analogue FOS built on modern element basis of fiber optics (FO), at following assumptions: absolute parameter stability of devices of FOS measuring path; single transmission band of registration path; maximum possible inserted in optical fiber (OF) a radiated power. Even at such idealized assumptions, a calculated value in limit reached minimum inaccuracy of measuring, by analogue FOS, has been ˜ 10-4 %. Substantially accessible values are yet worse on 2-3 order. The reason of poor precise performances of measurers on the basis of analogue FOS is metrologically poor quality of a stream of optical radiation carrying out role of the carrier and receptor of the information. It is a high level of photon noise and a small blanket intensity level. First reason reflects the fact of discreteness of flow of high-energy photons, and it is consequence of second one - smallness, on absolute value, of inserted power into OF from available radiation sources (RS). Works on improvement of FO elements are carrying out. Certainly, it will be created RS allow to insert enough of power into standard OF. But simple increasing of optical flow power in measuring path of FOS will not be able to decide radically the problem of increasing of measuring prices: with raising of power in proportion of square root of its value there is raising a power of photon noises - 1000-times increase of power promises only 30-times increase of measuring precise; insertion into OF more large power (˜ 1 W for standard silicon OF) causes an appearance of non-linear effects in it, which destroying an operating principle of analogue FOS. Thus, it is needed to constatate impossibility of building, at that time, measurers of analogue FOS, concurated with traditional (electrical) measurers on measuring precise. At that all, advantages of FO, as basis of building of FO MD requires to find ways for decision of these problems. Analysis of problem of sensitivity of usual (analogue) FOS has brought us to conclusion about necessity of reviewing of principles of information signal forming in FOS and principles its next electronic processing. For radical increasing of accuracy of measurements with using FOS it is necessary to refuse analogue modulation of optical flow and to transfer to discreet its modulations, entering thus in optical flow new, non-optical, parameters, which will serve as recipients of the information. It allows to save up all advantages of FOS (carrier of information, as earlier, remains an optical flow), but problem of accuracy of measurements now will not be more connected with problem of measurement of low power intensity of optical flow - it is transferred from area of optical measurements in other, non-optical area, where there is no this problem, or it had been solved duly. It had been developed a new class of FOS with pulse modulation of radiation flow intensity at the Department of Design and Production of Redioelectronic Systems of National Technical University of Ukraine ``Kiev Polytechnic Institute''. PFOS have benefit differ from usual analogue FOS on high threshold sensitivity and wide dynamic range of measured values. As example there are described design and performances of proposed 3D accelerometer. High precision of accelerometer measurements on PFOS is provided by following: possibility of high precision measurements of time intervals, which serve as informative parameters in output pulse signal of PFOS; possibility of creating a high quality quartz oscillating system, which serves as sensitive element of PFOS; insensitiveness of metrological performances of the accelerometer to any parameter instabilities (time, temperature, etc.) of optical and electrical elements in measuring path of PFOS; digital processing of PFOS signal practically excludes processing errors; principle insensitiveness of PFOS to electromagnetic noises of any nature and any intensity; possibility of direct correction of measuring results, during their processing, for taking into account and excluding undesirable influences of any destabilizing factors are acting on PFOS. Quasi stationary approach The developed 3D accelerometer on PFOS of extra low accelerations has unique technical performances, that confirms our conclusions about potentially high metrological abilities of pulse FOS. It has the following performances (calculated): threshold sensitivity is (10 -9 ldots 10 -13) g (threshold is determine by customer with determination of sizes of sensor and electronic processing unit); dynamic range is 10 7 ldots 10 9 ; frequency range is 0 ldots 10 Hz; mass is 50 grams; size: length is 120 mm and diameter is 20 mm In addition, that it can be used as accelerometer properly, on its base it is possible to create the strapdown inertial systems (SIS) for spacecraft. Flight control is carried out in accordance to flight programe of spacecraft without support connection with external reference objects. These SIS allow: - direct control over changes of orbital parameter or flight track, caused by action of extra low but long time external force factors (braking action of planet atmosphere remains, sun wind pressure, etc.) on spacecraft; - checking correction of orbital parameters (spacecraft track) by including of low power spaceborne engine; The developed accelerometer can be also used as high sensitive gravimeter for geophysical investigations and geological explorations - anywhere, where it is required to measure extra low deviation of terrestrial gravity value. High sensitivity of described accelerometers allows to create, on its base, gradientometers of real system for investigation of Planet gravity field heterogeneity from spacecraft orbit. This opens possibilities of practical solution of number important tasks of Planet physics.

Quantitative pre-clinical screening of therapeutics for joint diseases using contrast enhanced micro-computed tomography.

PubMed

Willett, N J; Thote, T; Hart, M; Moran, S; Guldberg, R E; Kamath, R V

2016-09-01

The development of effective therapies for cartilage protection has been limited by a lack of efficient quantitative cartilage imaging modalities in pre-clinical in vivo models. Our objectives were two-fold: first, to validate a new contrast-enhanced 3D imaging analysis technique, equilibrium partitioning of an ionic contrast agent-micro computed tomography (EPIC-μCT), in a rat medial meniscal transection (MMT) osteoarthritis (OA) model; and second, to quantitatively assess the sensitivity of EPIC-μCT to detect the effects of matrix metalloproteinase inhibitor (MMPi) therapy on cartilage degeneration. Rats underwent MMT surgery and tissues were harvested at 1, 2, and 3 weeks post-surgery or rats received an MMPi or vehicle treatment and tissues harvested 3 weeks post-surgery. Parameters of disease progression were evaluated using histopathology and EPIC-μCT. Correlations and power analyses were performed to compare the techniques. EPIC-μCT was shown to provide simultaneous 3D quantification of multiple parameters, including cartilage degeneration and osteophyte formation. In MMT animals treated with MMPi, OA progression was attenuated, as measured by 3D parameters such as lesion volume and osteophyte size. A post-hoc power analysis showed that 3D parameters for EPIC-μCT were more sensitive than 2D parameters requiring fewer animals to detect a therapeutic effect of MMPi. 2D parameters were comparable between EPIC-μCT and histopathology. This study demonstrated that EPIC-μCT has high sensitivity to provide 3D structural and compositional measurements of cartilage and bone in the joint. EPIC-μCT can be used in combination with histology to provide a comprehensive analysis to screen new potential therapies. Copyright © 2016 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Combined determination of highly sensitive troponin T and copeptin for early exclusion of acute myocardial infarction: first experience in an emergency department of a general hospital.

PubMed

Lotze, Ulrich; Lemm, Holger; Heyer, Anke; Müller, Karin

2011-01-01

The purpose of this observational study was to test the diagnostic performance of the Elecsys® troponin T high-sensitive system combined with copeptin measurement for early exclusion of acute myocardial infarction (MI) in clinical practice. Troponin T high-sensitive (diagnostic cutoff: <14 pg/mL) and copeptin (diagnostic cutoff: <14 pmol/L) levels were determined at admission in addition to other routine laboratory parameters in patients with suspected acute MI presenting to the emergency department of a general hospital over a period of five months. Data from 142 consecutive patients (mean age 71.2 ± 13.5 years, 76 men) were analyzed. Final diagnoses were acute MI in 13 patients (nine ST elevation MI, four non-ST elevation MI, 9.2%) unstable angina pectoris in three (2.1%), cardiac symptoms not primarily associated with myocardial ischemia in 79 (55.6%), and noncardiac disease in 47 patients (33.1%). The patients with acute MI were younger and had higher troponin T high-sensitive and copeptin values than patients without acute MI. Seventeen patients had very high copeptin values (>150 pmol/L), one of whom had a level of >700 pmol/L and died of pulmonary embolism. A troponin T high-sensitive level of <14 pg/mL in combination with copeptin <14 pmol/L at initial presentation ruled out acute MI in 45 of the 142 patients (31.7%), each with a sensitivity and negative predictive value of 100%. According to this early experience, a single determination of troponin T high-sensitive and copeptin may enable early and accurate exclusion of acute MI in one third of patients, even in an emergency department of a general hospital.

Ecohydrological controls over water budgets in floodplain meadows

NASA Astrophysics Data System (ADS)

Morris, Paul J.; Verhoef, Anne; Macdonald, David M. J.; Gardner, Cate M.; Punalekar, Suvarna M.; Tatarenko, Irina; Gowing, David

2013-04-01

Floodplain meadows are important ecosystems, characterised by high plant species richness including rare species. Fine-scale partitioning along soil hydrological gradients allows many species to co-exist. Concerns exist that even modest changes to soil hydrological regime as a result of changes in management or climate may endanger floodplain meadows communities. As such, understanding the interaction between biological and physical controls over floodplain meadow water budgets is important to understanding their likely vulnerability or resilience. Floodplain meadow plant communities are highly heterogeneous, leading to patchy landscapes with distinct vegetation. However, it is unclear whether this patchiness in plant distribution is likely to translate into heterogeneous soil-vegetation-atmosphere transfer (SVAT) rates of water and heat, or whether floodplain meadows can reasonably be treated as internally homogeneous in physical terms despite this patchy vegetation. We used a SVAT model, the Soil-Water-Atmosphere-Plants (SWAP) model by J.C. van Dam and co-workers, to explore the controls over the partitioning of water budgets in floodplain meadows. We conducted our research at Yarnton Mead on the River Thames in Oxfordshire, one of the UK's best remaining examples of a floodplain meadow, and which is still managed and farmed in a low-intensity mixed-use manner. We used soil and plant data from our site to parameterise SWAP; we drove the model using in-situ half-hourly meteorological data. We analysed the model's sensitivity to a range of soil and plant parameters - informed by our measurements - in order to assess the effects of different plant communities on SVAT fluxes. We used a novel method to simulate water-table dynamics at the site; the simulated water tables provide a lower boundary condition for SWAP's hydrological submodel. We adjusted the water-table model's parameters so as to represent areas of the mead with contrasting topography, and so different heights above the river level and different moisture and drainage regimes. The model was most sensitive to changes in the parameters that define the water-table model. Plant above-ground parameters, such as leaf area index and canopy height also had strong influences on simulated fluxes. The model exhibited low sensitivity to plant root parameters; this was particularly true during wet periods when the simulated plant communities were oxygen stressed. Changes in soil texture profile exhibited an intermediate level of control over SVAT fluxes. Our findings indicate that unlike in environments with deep water tables, such as drylands and headwater basins, high-quality water-table data with decimetre or even centimetre accuracy are important to accurate simulation of SVAT fluxes. Future studies that seek to simulate SVAT fluxes in shallow groundwater systems should either use high frequency, high-quality water-table observations as part of the driving data set, or should ensure that water-table dynamics and their interactions with surface processes can be simulated in a robust and physically meaningful manner. The low sensitivity of our model to plant root parameters reflects the proximity of the water table to the ground surface and the fact that the simulated plant community is rarely water-stressed, and again contrasts with findings from existing SVAT model research in environments with deep water tables.

Analyzing Single Giant Unilamellar Vesicles With a Slotline-Based RF Nanometer Sensor

DOE PAGES

Cui, Yan; Kenworthy, Anne K.; Edidin, Michael; ...

2016-03-11

Novel techniques that enable reagent free detection and analysis of single cells are of great interest for the development of biological and medical sciences, as well as point-of-care health service technologies. Highly sensitive and broadband RF sensors are promising candidates for such a technique. In this paper, we present a highly sensitive and tunable RF sensor, which is based on interference processes and built with a 100-nm slotline structure. The highly concentrated RF fields, up to ~ 1.76×10 7 V/m, enable strong interactions between giant unilamellar vesicles (GUVs) and fields for high-sensitivity operations. We also provide two modeling approaches tomore » extract cell dielectric properties from measured scattering parameters. GUVs of different molecular compositions are synthesized and analyzed with the RF sensor at ~ 2, ~ 2.5, and ~ 2.8 GHz with an initial |S 21| min of ~ -100 dB. Corresponding GUV dielectric properties are obtained. Finally, a one-dimensional scanning of single GUV is also demonstrated.« less

Extremely Elastic Wearable Carbon Nanotube Fiber Strain Sensor for Monitoring of Human Motion.

PubMed

Ryu, Seongwoo; Lee, Phillip; Chou, Jeffrey B; Xu, Ruize; Zhao, Rong; Hart, Anastasios John; Kim, Sang-Gook

2015-06-23

The increasing demand for wearable electronic devices has made the development of highly elastic strain sensors that can monitor various physical parameters an essential factor for realizing next generation electronics. Here, we report an ultrahigh stretchable and wearable device fabricated from dry-spun carbon nanotube (CNT) fibers. Stretching the highly oriented CNT fibers grown on a flexible substrate (Ecoflex) induces a constant decrease in the conductive pathways and contact areas between nanotubes depending on the stretching distance; this enables CNT fibers to behave as highly sensitive strain sensors. Owing to its unique structure and mechanism, this device can be stretched by over 900% while retaining high sensitivity, responsiveness, and durability. Furthermore, the device with biaxially oriented CNT fiber arrays shows independent cross-sensitivity, which facilitates simultaneous measurement of strains along multiple axes. We demonstrated potential applications of the proposed device, such as strain gauge, single and multiaxial detecting motion sensors. These devices can be incorporated into various motion detecting systems where their applications are limited to their strain.

Assessing soil erosion using USLE model and MODIS data in the Guangdong, China

NASA Astrophysics Data System (ADS)

Gao, Feng; Wang, Yunpeng; Yang, Jingxue

2017-07-01

In this study, soil erosion in the Guangdong, China during 2012 was quantitatively assessed using Universal Soil Loss Equation (USLE). The parameters of the model were calculated using GIS and MODIS data. The spatial distribution of the average annual soil loss on grid basis was mapped. The estimated average annual soil erosion in Guangdong in 2012 is about 2294.47t/ (km2.a). Four high sensitive area of soil erosion in Guangdong in 2012 was found. The key factors of these four high sensitive areas of soil erosion were significantly contributed to the land cover types, rainfall and Economic development and human activities.

Resonant optical transducers for in-situ gas detection

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

Bond, Tiziana C.; Cole, Garrett; Goddard, Lynford

Configurations for in-situ gas detection are provided, and include miniaturized photonic devices, low-optical-loss, guided-wave structures and state-selective adsorption coatings. High quality factor semiconductor resonators have been demonstrated in different configurations, such as micro-disks, micro-rings, micro-toroids, and photonic crystals with the properties of very narrow NIR transmission bands and sensitivity up to 10.sup.-9 (change in complex refractive index). The devices are therefore highly sensitive to changes in optical properties to the device parameters and can be tunable to the absorption of the chemical species of interest. Appropriate coatings applied to the device enhance state-specific molecular detection.

Resonant optical transducers for in-situ gas detection

DOEpatents

Bond, Tiziana C; Cole, Garrett; Goddard, Lynford

2016-06-28

Configurations for in-situ gas detection are provided, and include miniaturized photonic devices, low-optical-loss, guided-wave structures and state-selective adsorption coatings. High quality factor semiconductor resonators have been demonstrated in different configurations, such as micro-disks, micro-rings, micro-toroids, and photonic crystals with the properties of very narrow NIR transmission bands and sensitivity up to 10.sup.-9 (change in complex refractive index). The devices are therefore highly sensitive to changes in optical properties to the device parameters and can be tunable to the absorption of the chemical species of interest. Appropriate coatings applied to the device enhance state-specific molecular detection.

Estimation of the level of anxiety in rats: differences in results of open-field test, elevated plus-maze test, and Vogel's conflict test.

PubMed

Sudakov, S K; Nazarova, G A; Alekseeva, E V; Bashkatova, V G

2013-07-01

We compared individual anxiety assessed by three standard tests, open-field test, elevated plus-maze test, and Vogel conflict drinking test, in the same animals. No significant correlations between the main anxiety parameters were found in these three experimental models. Groups of animals with high and low anxiety rats were formed by a single parameter and subsequent selection of two extreme groups (10%). It was found that none of the tests could be used for reliable estimation of individual anxiety in rats. The individual anxiety level with high degree of confidence was determined in high-anxiety and low-anxiety rats demonstrating behavioral parameters above and below the mean values in all tests used. Therefore, several tests should be used for evaluation of the individual anxiety or sensitivity to emotional stress.

Sensitivity of Rooftop PV Projections in the SunShot Vision Study to Market Assumptions

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

Drury, E.; Denholm, P.; Margolis, R.

2013-01-01

The SunShot Vision Study explored the potential growth of solar markets if solar prices decreased by about 75% from 2010 to 2020. The SolarDS model was used to simulate rooftop PV demand for this study, based on several PV market assumptions--future electricity rates, customer access to financing, and others--in addition to the SunShot PV price projections. This paper finds that modeled PV demand is highly sensitive to several non-price market assumptions, particularly PV financing parameters.

Stepwise sensitivity analysis from qualitative to quantitative: Application to the terrestrial hydrological modeling of a Conjunctive Surface-Subsurface Process (CSSP) land surface model

NASA Astrophysics Data System (ADS)

Gan, Yanjun; Liang, Xin-Zhong; Duan, Qingyun; Choi, Hyun Il; Dai, Yongjiu; Wu, Huan

2015-06-01

An uncertainty quantification framework was employed to examine the sensitivities of 24 model parameters from a newly developed Conjunctive Surface-Subsurface Process (CSSP) land surface model (LSM). The sensitivity analysis (SA) was performed over 18 representative watersheds in the contiguous United States to examine the influence of model parameters in the simulation of terrestrial hydrological processes. Two normalized metrics, relative bias (RB) and Nash-Sutcliffe efficiency (NSE), were adopted to assess the fit between simulated and observed streamflow discharge (SD) and evapotranspiration (ET) for a 14 year period. SA was conducted using a multiobjective two-stage approach, in which the first stage was a qualitative SA using the Latin Hypercube-based One-At-a-Time (LH-OAT) screening, and the second stage was a quantitative SA using the Multivariate Adaptive Regression Splines (MARS)-based Sobol' sensitivity indices. This approach combines the merits of qualitative and quantitative global SA methods, and is effective and efficient for understanding and simplifying large, complex system models. Ten of the 24 parameters were identified as important across different watersheds. The contribution of each parameter to the total response variance was then quantified by Sobol' sensitivity indices. Generally, parameter interactions contribute the most to the response variance of the CSSP, and only 5 out of 24 parameters dominate model behavior. Four photosynthetic and respiratory parameters are shown to be influential to ET, whereas reference depth for saturated hydraulic conductivity is the most influential parameter for SD in most watersheds. Parameter sensitivity patterns mainly depend on hydroclimatic regime, as well as vegetation type and soil texture. This article was corrected on 26 JUN 2015. See the end of the full text for details.

Winter wheat yield estimation of remote sensing research based on WOFOST crop model and leaf area index assimilation

NASA Astrophysics Data System (ADS)

Chen, Yanling; Gong, Adu; Li, Jing; Wang, Jingmei

2017-04-01

Accurate crop growth monitoring and yield predictive information are significant to improve the sustainable development of agriculture and ensure the security of national food. Remote sensing observation and crop growth simulation models are two new technologies, which have highly potential applications in crop growth monitoring and yield forecasting in recent years. However, both of them have limitations in mechanism or regional application respectively. Remote sensing information can not reveal crop growth and development, inner mechanism of yield formation and the affection of environmental meteorological conditions. Crop growth simulation models have difficulties in obtaining data and parameterization from single-point to regional application. In order to make good use of the advantages of these two technologies, the coupling technique of remote sensing information and crop growth simulation models has been studied. Filtering and optimizing model parameters are key to yield estimation by remote sensing and crop model based on regional crop assimilation. Winter wheat of GaoCheng was selected as the experiment object in this paper. And then the essential data was collected, such as biochemical data and farmland environmental data and meteorological data about several critical growing periods. Meanwhile, the image of environmental mitigation small satellite HJ-CCD was obtained. In this paper, research work and major conclusions are as follows. (1) Seven vegetation indexes were selected to retrieve LAI, and then linear regression model was built up between each of these indexes and the measured LAI. The result shows that the accuracy of EVI model was the highest (R2=0.964 at anthesis stage and R2=0.920 at filling stage). Thus, EVI as the most optimal vegetation index to predict LAI in this paper. (2) EFAST method was adopted in this paper to conduct the sensitive analysis to the 26 initial parameters of the WOFOST model and then a sensitivity index was constructed to evaluate the influence of each parameter mentioned above on the winter wheat yield formation. Finally, six parameters that sensitivity index more than 0.1 as sensitivity factors were chose, which are TSUM1, SLATB1, SLATB2, SPAN, EFFTB3 and TMPF4. To other parameters, we confirmed them via practical measurement and calculation, available literature or WOFOST default. Eventually, we completed the regulation of WOFOST parameters. (3) Look-up table algorithm was used to realize single-point yield estimation through the assimilation of the WOFOST model and the retrieval LAI. This simulation achieved a high accuracy which perfectly meet the purpose of assimilation (R2=0.941 and RMSE=194.58kg/hm2). In this paper, the optimum value of sensitivity parameters were confirmed and the estimation of single-point yield were finished. Key words: yield estimation of winter wheat, LAI, WOFOST crop growth model, assimilation

Feasibility of high-resolution one-dimensional relaxation imaging at low magnetic field using a single-sided NMR scanner applied to articular cartilage.

PubMed

Rössler, Erik; Mattea, Carlos; Stapf, Siegfried

2015-02-01

Low field Nuclear Magnetic Resonance increases the contrast of the longitudinal relaxation rate in many biological tissues; one prominent example is hyaline articular cartilage. In order to take advantage of this increased contrast and to profile the depth-dependent variations, high resolution parameter measurements are carried out which can be of critical importance in an early diagnosis of cartilage diseases such as osteoarthritis. However, the maximum achievable spatial resolution of parameter profiles is limited by factors such as sensor geometry, sample curvature, and diffusion limitation. In this work, we report on high-resolution single-sided NMR scanner measurements with a commercial device, and quantify these limitations. The highest achievable spatial resolution on the used profiler, and the lateral dimension of the sensitive volume were determined. Since articular cartilage samples are usually bent, we also focus on averaging effects inside the horizontally aligned sensitive volume and their impact on the relaxation profiles. Taking these critical parameters into consideration, depth-dependent relaxation time profiles with the maximum achievable vertical resolution of 20 μm are discussed, and are correlated with diffusion coefficient profiles in hyaline articular cartilage in order to reconstruct T(2) maps from the diffusion-weighted CPMG decays of apparent relaxation rates. Copyright © 2014 Elsevier Inc. All rights reserved.

Enhancing coronary Wave Intensity Analysis robustness by high order central finite differences.

PubMed

Rivolo, Simone; Asrress, Kaleab N; Chiribiri, Amedeo; Sammut, Eva; Wesolowski, Roman; Bloch, Lars Ø; Grøndal, Anne K; Hønge, Jesper L; Kim, Won Y; Marber, Michael; Redwood, Simon; Nagel, Eike; Smith, Nicolas P; Lee, Jack

2014-09-01

Coronary Wave Intensity Analysis (cWIA) is a technique capable of separating the effects of proximal arterial haemodynamics from cardiac mechanics. Studies have identified WIA-derived indices that are closely correlated with several disease processes and predictive of functional recovery following myocardial infarction. The cWIA clinical application has, however, been limited by technical challenges including a lack of standardization across different studies and the derived indices' sensitivity to the processing parameters. Specifically, a critical step in WIA is the noise removal for evaluation of derivatives of the acquired signals, typically performed by applying a Savitzky-Golay filter, to reduce the high frequency acquisition noise. The impact of the filter parameter selection on cWIA output, and on the derived clinical metrics (integral areas and peaks of the major waves), is first analysed. The sensitivity analysis is performed either by using the filter as a differentiator to calculate the signals' time derivative or by applying the filter to smooth the ensemble-averaged waveforms. Furthermore, the power-spectrum of the ensemble-averaged waveforms contains little high-frequency components, which motivated us to propose an alternative approach to compute the time derivatives of the acquired waveforms using a central finite difference scheme. The cWIA output and consequently the derived clinical metrics are significantly affected by the filter parameters, irrespective of its use as a smoothing filter or a differentiator. The proposed approach is parameter-free and, when applied to the 10 in-vivo human datasets and the 50 in-vivo animal datasets, enhances the cWIA robustness by significantly reducing the outcome variability (by 60%).

Optimization of mass spectrometry acquisition parameters for determination of polycarbonate additives, degradation products, and colorants migrating from food contact materials to chocolate.

PubMed

Bignardi, Chiara; Cavazza, Antonella; Laganà, Carmen; Salvadeo, Paola; Corradini, Claudio

2018-01-01

The interest towards "substances of emerging concerns" referred to objects intended to come into contact with food is recently growing. Such substances can be found in traces in simulants and in food products put in contact with plastic materials. In this context, it is important to set up analytical systems characterized by high sensitivity and to improve detection parameters to enhance signals. This work was aimed at optimizing a method based on UHPLC coupled to high resolution mass spectrometry to quantify the most common plastic additives, and able to detect the presence of polymers degradation products and coloring agents migrating from plastic re-usable containers. The optimization of mass spectrometric parameter settings for quantitative analysis of additives has been achieved by a chemometric approach, using a full factorial and d-optimal experimental designs, allowing to evaluate possible interactions between the investigated parameters. Results showed that the optimized method was characterized by improved features in terms of sensitivity respect to existing methods and was successfully applied to the analysis of a complex model food system such as chocolate put in contact with 14 polycarbonate tableware samples. A new procedure for sample pre-treatment was carried out and validated, showing high reliability. Results reported, for the first time, the presence of several molecules migrating to chocolate, in particular belonging to plastic additives, such Cyasorb UV5411, Tinuvin 234, Uvitex OB, and oligomers, whose amount was found to be correlated to age and degree of damage of the containers. Copyright © 2017 John Wiley & Sons, Ltd.

Dakota, a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis :

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

Adams, Brian M.; Ebeida, Mohamed Salah; Eldred, Michael S.

The Dakota (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a exible and extensible interface between simulation codes and iterative analysis methods. Dakota contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quanti cation with sampling, reliability, and stochastic expansion methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components requiredmore » for iterative systems analyses, the Dakota toolkit provides a exible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a user's manual for the Dakota software and provides capability overviews and procedures for software execution, as well as a variety of example studies.« less

Flexible and self-powered temperature-pressure dual-parameter sensors using microstructure-frame-supported organic thermoelectric materials.

PubMed

Zhang, Fengjiao; Zang, Yaping; Huang, Dazhen; Di, Chong-an; Zhu, Daoben

2015-09-21

Skin-like temperature- and pressure-sensing capabilities are essential features for the next generation of artificial intelligent products. Previous studies of e-skin and smart elements have focused on flexible pressure sensors, whereas the simultaneous and sensitive detection of temperature and pressure with a single device remains a challenge. Here we report developing flexible dual-parameter temperature-pressure sensors based on microstructure-frame-supported organic thermoelectric (MFSOTE) materials. The effective transduction of temperature and pressure stimuli into two independent electrical signals permits the instantaneous sensing of temperature and pressure with an accurate temperature resolution of <0.1 K and a high-pressure-sensing sensitivity of up to 28.9 kPa(-1). More importantly, these dual-parameter sensors can be self-powered with outstanding sensing performance. The excellent sensing properties of MFSOTE-based devices, together with their unique advantages of low cost and large-area fabrication, make MFSOTE materials possess promising applications in e-skin and health-monitoring elements.

Sensitivity analysis of discharge patterns of subthalamic nucleus in the model of basal ganglia in Parkinson disease.

PubMed

Singh, Jyotsna; Singh, Phool; Malik, Vikas

2017-01-01

Parkinson disease alters the information patterns in movement related pathways in brain. Experimental results performed on rats show that the activity patterns changes from single spike activity to mixed burst mode in Parkinson disease. However the cause of this change in activity pattern is not yet completely understood. Subthalamic nucleus is one of the main nuclei involved in the origin of motor dysfunction in Parkinson disease. In this paper, a single compartment conductance based model is considered which focuses on subthalamic nucleus and synaptic input from globus pallidus (external). This model shows highly nonlinear behavior with respect to various intrinsic parameters. Behavior of model has been presented with the help of activity patterns generated in healthy and Parkinson condition. These patterns have been compared by calculating their correlation coefficient for different values of intrinsic parameters. Results display that the activity patterns are very sensitive to various intrinsic parameters and calcium shows some promising results which provide insights into the motor dysfunction.

Flexible and self-powered temperature-pressure dual-parameter sensors using microstructure-frame-supported organic thermoelectric materials

NASA Astrophysics Data System (ADS)

Zhang, Fengjiao; Zang, Yaping; Huang, Dazhen; di, Chong-An; Zhu, Daoben

2015-09-01

Skin-like temperature- and pressure-sensing capabilities are essential features for the next generation of artificial intelligent products. Previous studies of e-skin and smart elements have focused on flexible pressure sensors, whereas the simultaneous and sensitive detection of temperature and pressure with a single device remains a challenge. Here we report developing flexible dual-parameter temperature-pressure sensors based on microstructure-frame-supported organic thermoelectric (MFSOTE) materials. The effective transduction of temperature and pressure stimuli into two independent electrical signals permits the instantaneous sensing of temperature and pressure with an accurate temperature resolution of <0.1 K and a high-pressure-sensing sensitivity of up to 28.9 kPa-1. More importantly, these dual-parameter sensors can be self-powered with outstanding sensing performance. The excellent sensing properties of MFSOTE-based devices, together with their unique advantages of low cost and large-area fabrication, make MFSOTE materials possess promising applications in e-skin and health-monitoring elements.

Optical identification of subjects at high risk for developing breast cancer

NASA Astrophysics Data System (ADS)

Taroni, Paola; Quarto, Giovanna; Pifferi, Antonio; Ieva, Francesca; Paganoni, Anna Maria; Abbate, Francesca; Balestreri, Nicola; Menna, Simona; Cassano, Enrico; Cubeddu, Rinaldo

2013-06-01

A time-domain multiwavelength (635 to 1060 nm) optical mammography was performed on 147 subjects with recent x-ray mammograms available, and average breast tissue composition (water, lipid, collagen, oxy- and deoxyhemoglobin) and scattering parameters (amplitude a and slope b) were estimated. Correlation was observed between optically derived parameters and mammographic density [Breast Imaging and Reporting Data System (BI-RADS) categories], which is a strong risk factor for breast cancer. A regression logistic model was obtained to best identify high-risk (BI-RADS 4) subjects, based on collagen content and scattering parameters. The model presents a total misclassification error of 12.3%, sensitivity of 69%, specificity of 94%, and simple kappa of 0.84, which compares favorably even with intraradiologist assignments of BI-RADS categories.

Parameter sensitivity analysis of a lumped-parameter model of a chain of lymphangions in series.

PubMed

Jamalian, Samira; Bertram, Christopher D; Richardson, William J; Moore, James E

2013-12-01

Any disruption of the lymphatic system due to trauma or injury can lead to edema. There is no effective cure for lymphedema, partly because predictive knowledge of lymphatic system reactions to interventions is lacking. A well-developed model of the system could greatly improve our understanding of its function. Lymphangions, defined as the vessel segment between two valves, are the individual pumping units. Based on our previous lumped-parameter model of a chain of lymphangions, this study aimed to identify the parameters that affect the system output the most using a sensitivity analysis. The system was highly sensitive to minimum valve resistance, such that variations in this parameter caused an order-of-magnitude change in time-average flow rate for certain values of imposed pressure difference. Average flow rate doubled when contraction frequency was increased within its physiological range. Optimum lymphangion length was found to be some 13-14.5 diameters. A peak of time-average flow rate occurred when transmural pressure was such that the pressure-diameter loop for active contractions was centered near maximum passive vessel compliance. Increasing the number of lymphangions in the chain improved the pumping in the presence of larger adverse pressure differences. For a given pressure difference, the optimal number of lymphangions increased with the total vessel length. These results indicate that further experiments to estimate valve resistance more accurately are necessary. The existence of an optimal value of transmural pressure may provide additional guidelines for increasing pumping in areas affected by edema.

Activation and quenching of the phototransduction cascade in retinal cones as inferred from electrophysiology and mathematical modeling

PubMed Central

Astakhova, Luba; Firsov, Michael

2015-01-01

Purpose To experimentally identify and quantify factors responsible for the lower sensitivity of retinal cones compared to rods. Methods Electrical responses of frog rods and fish (Carassius) cones to short flashes of light were recorded using the suction pipette technique. A fast solution changer was used to apply a solution that fixed intracellular Ca2+ concentration at the prestimulus level, thereby disabling Ca2+ feedback, to the outer segment (OS). The results were analyzed with a specially designed mathematical model of phototransduction. The model included all basic processes of activation and quenching of the phototransduction cascade but omitted unnecessary mechanistic details of each step. Results Judging from the response versus intensity curves, Carassius cones were two to three orders of magnitude less sensitive than frog rods. There was a large scatter in sensitivity among individual cones, with red-sensitive cones being on average approximately two times less sensitive than green-sensitive ones. The scatter was mostly due to different signal amplification, since the kinetic parameters of the responses among cones were far less variable than sensitivity. We argue that the generally accepted definition of the biochemical amplification in phototransduction cannot be used for comparing amplification in rods and cones, since it depends on an irrelevant factor, that is, the cell’s volume. We also show that the routinely used simplified parabolic curve fitting to an initial phase of the response leads to a few-fold underestimate of the amplification. We suggest a new definition of the amplification that only includes molecular parameters of the cascade activation, and show how it can be derived from experimental data. We found that the mathematical model with unrestrained parameters can yield an excellent fit to experimental responses. However, the fits with wildly different sets of parameters can be virtually indistinguishable, and therefore cannot provide meaningful data on underlying mechanisms. Based on results of Ca2+-clamp experiments, we developed an approach to strongly constrain the values of many key parameters that set the time course and sensitivity of the photoresponse (such as the dark turnover rate of cGMP, rates of turnoffs of the photoactivated visual pigment and phosphodiesterase, and kinetics of Ca2+ feedback). We show that applying these constraints to our mathematical model enables accurate determination of the biochemical amplification in phototransduction. It appeared that, contrary to many suggestions, maximum biochemical amplification derived for “best” Carassius cones was as high as in frog rods. On the other hand, all turnoff and recovery reactions in cones proceeded approximately 10 times faster than in rods. Conclusions The main cause of the differing sensitivity of rods and cones is cones’ ability to terminate their photoresponse faster. PMID:25866462

Mesoporous titania-vertical nanorod films with interfacial engineering for high performance dye-sensitized solar cells.

PubMed

Ahmed, Irfan; Fakharuddin, Azhar; Wali, Qamar; Bin Zainun, Ayib Rosdi; Ismail, Jamil; Jose, Rajan

2015-03-13

Working electrode (WE) fabrication offers significant challenges in terms of achieving high-efficiency dye-sensitized solar cells (DSCs). We have combined the beneficial effects of vertical nanorods grown on conducting glass substrate for charge transport and mesoporous particles for dye loading and have achieved a high photoconversion efficiency of (η) > 11% with an internal quantum efficiency of ∼93% in electrode films of thickness ∼7 ± 0.5 μm. Controlling the interface between the vertical nanorods and the mesoporous film is a crucial step in attaining high η. We identify three parameters, viz., large surface area of nanoparticles, increased light scattering of the nanorod-nanoparticle layer, and superior charge transport of nanorods, that simultaneously contribute to the improved photovoltaic performance of the WE developed.

Parameter regionalization of a monthly water balance model for the conterminous United States

NASA Astrophysics Data System (ADS)

Bock, A. R.; Hay, L. E.; McCabe, G. J.; Markstrom, S. L.; Atkinson, R. D.

2015-09-01

A parameter regionalization scheme to transfer parameter values and model uncertainty information from gaged to ungaged areas for a monthly water balance model (MWBM) was developed and tested for the conterminous United States (CONUS). The Fourier Amplitude Sensitivity Test, a global-sensitivity algorithm, was implemented on a MWBM to generate parameter sensitivities on a set of 109 951 hydrologic response units (HRUs) across the CONUS. The HRUs were grouped into 110 calibration regions based on similar parameter sensitivities. Subsequently, measured runoff from 1575 streamgages within the calibration regions were used to calibrate the MWBM parameters to produce parameter sets for each calibration region. Measured and simulated runoff at the 1575 streamgages showed good correspondence for the majority of the CONUS, with a median computed Nash-Sutcliffe Efficiency coefficient of 0.76 over all streamgages. These methods maximize the use of available runoff information, resulting in a calibrated CONUS-wide application of the MWBM suitable for providing estimates of water availability at the HRU resolution for both gaged and ungaged areas of the CONUS.

Epidermis Microstructure Inspired Graphene Pressure Sensor with Random Distributed Spinosum for High Sensitivity and Large Linearity.

PubMed

Pang, Yu; Zhang, Kunning; Yang, Zhen; Jiang, Song; Ju, Zhenyi; Li, Yuxing; Wang, Xuefeng; Wang, Danyang; Jian, Muqiang; Zhang, Yingying; Liang, Renrong; Tian, He; Yang, Yi; Ren, Tian-Ling

2018-03-27

Recently, wearable pressure sensors have attracted tremendous attention because of their potential applications in monitoring physiological signals for human healthcare. Sensitivity and linearity are the two most essential parameters for pressure sensors. Although various designed micro/nanostructure morphologies have been introduced, the trade-off between sensitivity and linearity has not been well balanced. Human skin, which contains force receptors in a reticular layer, has a high sensitivity even for large external stimuli. Herein, inspired by the skin epidermis with high-performance force sensing, we have proposed a special surface morphology with spinosum microstructure of random distribution via the combination of an abrasive paper template and reduced graphene oxide. The sensitivity of the graphene pressure sensor with random distribution spinosum (RDS) microstructure is as high as 25.1 kPa -1 in a wide linearity range of 0-2.6 kPa. Our pressure sensor exhibits superior comprehensive properties compared with previous surface-modified pressure sensors. According to simulation and mechanism analyses, the spinosum microstructure and random distribution contribute to the high sensitivity and large linearity range, respectively. In addition, the pressure sensor shows promising potential in detecting human physiological signals, such as heartbeat, respiration, phonation, and human motions of a pushup, arm bending, and walking. The wearable pressure sensor array was further used to detect gait states of supination, neutral, and pronation. The RDS microstructure provides an alternative strategy to improve the performance of pressure sensors and extend their potential applications in monitoring human activities.

AMH MEASUREMENT VERSUS OVARIAN ULTRASOUND IN THE DIAGNOSIS OF POLYCYSTIC OVARY SYNDROME IN DIFFERENT PHENOTYPES.

PubMed

Carmina, Enrico; Campagna, Anna M; Fruzzetti, Franca; Lobo, Rogerio A

2016-03-01

This study was designed to assess the value of serum anti-Müllerian hormone (AMH) in the diagnosis of polycystic ovary syndrome (PCOS) in various phenotypes and to assess ovarian ultrasound parameters. We performed a retrospective matched controlled study of 113 females with various PCOS phenotypes and 47 matched controls. The diagnostic utility of AMH measurement and ovarian ultrasound were compared. Using receiver operating characteristic (ROC) curve analyses, the threshold for AMH (>4.7 ng/mL) and ultrasound parameters (follicle number per ovary [FNPO] >22 and ovarian volume [OV] >8 cc) were established. In the entire cohort, AMH had a low sensitivity of 79%; while FNPO and OV were 93% and 68%, respectively. Specificities ranged from 85 to 96%. In classic anovulatory PCOS, AMH exhibited a sensitivity of 91%, and for FNPO and OV the corresponding sensitivities were 92% and 72%. In the ovulatory phenotype, AMH sensitivity was only 50%, while FNPO and OV were 95% and 50%, respectively. In the nonhyperandrogenic phenotype, the sensitivity of AMH was 53% while those for FNPO and OV were 93% and 67%. AMH does not appear to be helpful for all subjects with PCOS but may be of some value in those who are anovulatory. However, FNPO was highly sensitive in all phenotypes, and was the single best criterion assessed for all subjects, suggesting the important role of ultrasound.

Can nonstandard interactions jeopardize the hierarchy sensitivity of DUNE?

NASA Astrophysics Data System (ADS)

Deepthi, K. N.; Goswami, Srubabati; Nath, Newton

2017-10-01

We study the effect of nonstandard interactions (NSIs) on the propagation of neutrinos through the Earth's matter and how it affects the hierarchy sensitivity of the DUNE experiment. We emphasize the special case when the diagonal NSI parameter ɛe e=-1 , nullifying the standard matter effect. We show that if, in addition, C P violation is maximal then this gives rise to an exact intrinsic hierarchy degeneracy in the appearance channel, irrespective of the baseline and energy. Introduction of the off diagonal NSI parameter, ɛe τ, shifts the position of this degeneracy to a different ɛe e. Moreover the unknown magnitude and phases of the off diagonal NSI parameters can give rise to additional degeneracies. Overall, given the current model independent limits on NSI parameters, the hierarchy sensitivity of DUNE can get seriously impacted. However, a more precise knowledge of the NSI parameters, especially ɛe e, can give rise to an improved sensitivity. Alternatively, if a NSI exists in nature, and still DUNE shows hierarchy sensitivity, certain ranges of the NSI parameters can be excluded. Additionally, we briefly discuss the implications of ɛe e=-1 (in the Earth) on the Mikheyev-Smirnov-Wolfenstein effect in the Sun.

Histogram analysis of diffusion kurtosis imaging derived maps may distinguish between low and high grade gliomas before surgery.

PubMed

Qi, Xi-Xun; Shi, Da-Fa; Ren, Si-Xie; Zhang, Su-Ya; Li, Long; Li, Qing-Chang; Guan, Li-Ming

2018-04-01

To investigate the value of histogram analysis of diffusion kurtosis imaging (DKI) maps in the evaluation of glioma grading. A total of 39 glioma patients who underwent preoperative magnetic resonance imaging (MRI) were classified into low-grade (13 cases) and high-grade (26 cases) glioma groups. Parametric DKI maps were derived, and histogram metrics between low- and high-grade gliomas were analysed. The optimum diagnostic thresholds of the parameters, area under the receiver operating characteristic curve (AUC), sensitivity, and specificity were achieved using a receiver operating characteristic (ROC). Significant differences were observed not only in 12 metrics of histogram DKI parameters (P<0.05), but also in mean diffusivity (MD) and mean kurtosis (MK) values, including age as a covariate (F=19.127, P<0.001 and F=20.894, P<0.001, respectively), between low- and high-grade gliomas. Mean MK was the best independent predictor of differentiating glioma grades (B=18.934, 22.237 adjusted for age, P<0.05). The partial correlation coefficient between fractional anisotropy (FA) and kurtosis fractional anisotropy (KFA) was 0.675 (P<0.001). The AUC of the mean MK, sensitivity, and specificity were 0.925, 88.5% and 84.6%, respectively. DKI parameters can effectively distinguish between low- and high-grade gliomas. Mean MK is the best independent predictor of differentiating glioma grades. • DKI is a new and important method. • DKI can provide additional information on microstructural architecture. • Histogram analysis of DKI may be more effective in glioma grading.

Radial magnetic resonance imaging (MRI) using a rotating radiofrequency (RF) coil at 9.4 T.

PubMed

Li, Mingyan; Weber, Ewald; Jin, Jin; Hugger, Thimo; Tesiram, Yasvir; Ullmann, Peter; Stark, Simon; Fuentes, Miguel; Junge, Sven; Liu, Feng; Crozier, Stuart

2018-02-01

The rotating radiofrequency coil (RRFC) has been developed recently as an alternative approach to multi-channel phased-array coils. The single-element RRFC avoids inter-channel coupling and allows a larger coil element with better B 1 field penetration when compared with an array counterpart. However, dedicated image reconstruction algorithms require accurate estimation of temporally varying coil sensitivities to remove artefacts caused by coil rotation. Various methods have been developed to estimate unknown sensitivity profiles from a few experimentally measured sensitivity maps, but these methods become problematic when the RRFC is used as a transceiver coil. In this work, a novel and practical radial encoding method is introduced for the RRFC to facilitate image reconstruction without the measurement or estimation of rotation-dependent sensitivity profiles. Theoretical analyses suggest that the rotation-dependent sensitivities of the RRFC can be used to create a uniform profile with careful choice of sampling positions and imaging parameters. To test this new imaging method, dedicated electronics were designed and built to control the RRFC speed and hence positions in synchrony with imaging parameters. High-quality phantom and animal images acquired on a 9.4 T pre-clinical scanner demonstrate the feasibility and potential of this new RRFC method. Copyright © 2017 John Wiley & Sons, Ltd.

Modeling and sensitivity analysis on the transport of aluminum oxide nanoparticles in saturated sand: effects of ionic strength, flow rate, and nanoparticle concentration.

PubMed

Rahman, Tanzina; Millwater, Harry; Shipley, Heather J

2014-11-15

Aluminum oxide nanoparticles have been widely used in various consumer products and there are growing concerns regarding their exposure in the environment. This study deals with the modeling, sensitivity analysis and uncertainty quantification of one-dimensional transport of nano-sized (~82 nm) aluminum oxide particles in saturated sand. The transport of aluminum oxide nanoparticles was modeled using a two-kinetic-site model with a blocking function. The modeling was done at different ionic strengths, flow rates, and nanoparticle concentrations. The two sites representing fast and slow attachments along with a blocking term yielded good agreement with the experimental results from the column studies of aluminum oxide nanoparticles. The same model was used to simulate breakthrough curves under different conditions using experimental data and calculated 95% confidence bounds of the generated breakthroughs. The sensitivity analysis results showed that slow attachment was the most sensitive parameter for high influent concentrations (e.g. 150 mg/L Al2O3) and the maximum solid phase retention capacity (related to blocking function) was the most sensitive parameter for low concentrations (e.g. 50 mg/L Al2O3). Copyright © 2014 Elsevier B.V. All rights reserved.

Optimization Under Uncertainty for Electronics Cooling Design

NASA Astrophysics Data System (ADS)

Bodla, Karthik K.; Murthy, Jayathi Y.; Garimella, Suresh V.

Optimization under uncertainty is a powerful methodology used in design and optimization to produce robust, reliable designs. Such an optimization methodology, employed when the input quantities of interest are uncertain, produces output uncertainties, helping the designer choose input parameters that would result in satisfactory thermal solutions. Apart from providing basic statistical information such as mean and standard deviation in the output quantities, auxiliary data from an uncertainty based optimization, such as local and global sensitivities, help the designer decide the input parameter(s) to which the output quantity of interest is most sensitive. This helps the design of experiments based on the most sensitive input parameter(s). A further crucial output of such a methodology is the solution to the inverse problem - finding the allowable uncertainty range in the input parameter(s), given an acceptable uncertainty range in the output quantity of interest...

Cell death, perfusion and electrical parameters are critical in models of hepatic radiofrequency ablation

PubMed Central

Hall, Sheldon K.; Ooi, Ean H.; Payne, Stephen J.

2015-01-01

Abstract Purpose: A sensitivity analysis has been performed on a mathematical model of radiofrequency ablation (RFA) in the liver. The purpose of this is to identify the most important parameters in the model, defined as those that produce the largest changes in the prediction. This is important in understanding the role of uncertainty and when comparing the model predictions to experimental data. Materials and methods: The Morris method was chosen to perform the sensitivity analysis because it is ideal for models with many parameters or that take a significant length of time to obtain solutions. A comprehensive literature review was performed to obtain ranges over which the model parameters are expected to vary, crucial input information. Results: The most important parameters in predicting the ablation zone size in our model of RFA are those representing the blood perfusion, electrical conductivity and the cell death model. The size of the 50 °C isotherm is sensitive to the electrical properties of tissue while the heat source is active, and to the thermal parameters during cooling. Conclusions: The parameter ranges chosen for the sensitivity analysis are believed to represent all that is currently known about their values in combination. The Morris method is able to compute global parameter sensitivities taking into account the interaction of all parameters, something that has not been done before. Research is needed to better understand the uncertainties in the cell death, electrical conductivity and perfusion models, but the other parameters are only of second order, providing a significant simplification. PMID:26000972

First- and Second-Order Sensitivity Analysis of a P-Version Finite Element Equation Via Automatic Differentiation

NASA Technical Reports Server (NTRS)

Hou, Gene

1998-01-01

Sensitivity analysis is a technique for determining derivatives of system responses with respect to design parameters. Among many methods available for sensitivity analysis, automatic differentiation has been proven through many applications in fluid dynamics and structural mechanics to be an accurate and easy method for obtaining derivatives. Nevertheless, the method can be computational expensive and can require a high memory space. This project will apply an automatic differentiation tool, ADIFOR, to a p-version finite element code to obtain first- and second- order then-nal derivatives, respectively. The focus of the study is on the implementation process and the performance of the ADIFOR-enhanced codes for sensitivity analysis in terms of memory requirement, computational efficiency, and accuracy.

Association between serum lipids, glucose tolerance, and insulin sensitivity during 12 months of celiprolol treatment.

PubMed

Malminiemi, K

1995-04-01

The study was undertaken to evaluate the development and association of parameters related to the metabolic syndrome during celiprolol treatment. Hyperinsulinemic euglycemic clamp and independent oral glucose tolerance tests (OGTT) were performed on 25 nondiabetic patients with controlled hypertension and dyslipidemia. The tests were carried out during the patients' previous antihypertensive monotherapy (beta- or Ca-blocker, or an ACE inhibitor), and after 6 and 12 months of celiprolol treatment. About one third of patients were randomized to a control group in which treatment was kept unchanged. Insulin sensitivity index (ISI), measured by the euglycemic clamp test, increased 35% in the celiprolol group at 6 months and remained at that level at 12 months, independent of the previous treatment (p = 0.03, compared to the change in the control group). During a 2 hour OGTT, incremental glucose area under the curve (AUC) decreased from 4.5 to 1.9 hr x mmol/l during 6 months of celiprolol treatment, and decreased further to 1.5 hr x mmol/l at 12 months (p < 0.001). Insulin AUC decreased from 113 to 72 hr x mU/l, and decreased further to 68 hr x mU/l (p < 0.01). All insulin parameters in OGTT were highly significant (p < 0.0001) and inversely associated with ISI. Insulin AUC had the best linear correlation with ISI (r = -0.682, p < 0.0001). Glucose parameters in OGTT correlated only weakly and inversely with insulin sensitivity. From the fasting serum lipids, triglycerides showed an inverse (p < 0.001) and HDL a weak (p < 0.05) positive association with ISI. Four out of 20 metabolic, clinical, and demographic parameters proved to be independently significant predictors for ISI in multiple regression analysis. These were insulin AUC, fasting insulin levels, triglyceride values, and age. The coefficient of determination in this four-parameter linear model was 69%. In this preliminary, observer-masked trial with a limited control group, celiprolol improved the impaired insulin sensitivity and glucose tolerance of dyslipidemic hypertensive patients. A fairly predictive model can be formulated to evaluate the peripheral insulin sensitivity of hypertensive patients with suspected metabolic syndrome using OGTT with serum insulin determinations.

Effect of aerosol microphysical properties on polarization of skylight: sensitivity study and measurements.

PubMed

Boesche, Eyk; Stammes, Piet; Ruhtz, Thomas; Preusker, Réne; Fischer, Juergen

2006-12-01

We analyze the sensitivity of the degree of linear polarization in the Sun's principal plane as a function of aerosol microphysical parameters: the real and imaginary parts of the refractive index, the median radius and geometric standard deviation of the bimodal size distribution (both fine and coarse modes), and the relative number weight of the fine mode at a wavelength of 675 nm. We use Mie theory for single-scattering simulations and the doubling-adding method with the inclusion of polarization for multiple scattering. It is shown that the behavior of the degree of linear polarization is highly sensitive to both the small mode of the bimodal size distribution and the real part of the refractive index of aerosols, as well as to the aerosol optical thickness; whereas not all parameters influence the polarization equally. A classification of the importance of the input parameters is given. This sensitivity study is applied to an analysis of ground-based polarization measurements. For the passive remote sensing of microphysical and optical properties of aerosols, a ground-based spectral polarization measuring system was built, which aims to measure the Stokes parameters I, Q, and U in the visible (from 410 to 789 nm) and near-infrared (from 674 to 995 nm) spectral range with a spectral resolution of 7 nm in the visible and 2.4 nm in the near infrared. We compare polarization measurements taken with radiative transfer simulations under both clear- and hazy-sky conditions in an urban area (Cabauw, The Netherlands, 51.58 degrees N, 4.56 degrees E). Conclusions about the microphysical properties of aerosol are drawn from the comparison.

Quantitative sensory testing response patterns to capsaicin- and ultraviolet-B–induced local skin hypersensitization in healthy subjects: a machine-learned analysis

PubMed Central

Lötsch, Jörn; Geisslinger, Gerd; Heinemann, Sarah; Lerch, Florian; Oertel, Bruno G.; Ultsch, Alfred

2018-01-01

Abstract The comprehensive assessment of pain-related human phenotypes requires combinations of nociceptive measures that produce complex high-dimensional data, posing challenges to bioinformatic analysis. In this study, we assessed established experimental models of heat hyperalgesia of the skin, consisting of local ultraviolet-B (UV-B) irradiation or capsaicin application, in 82 healthy subjects using a variety of noxious stimuli. We extended the original heat stimulation by applying cold and mechanical stimuli and assessing the hypersensitization effects with a clinically established quantitative sensory testing (QST) battery (German Research Network on Neuropathic Pain). This study provided a 246 × 10-sized data matrix (82 subjects assessed at baseline, following UV-B application, and following capsaicin application) with respect to 10 QST parameters, which we analyzed using machine-learning techniques. We observed statistically significant effects of the hypersensitization treatments in 9 different QST parameters. Supervised machine-learned analysis implemented as random forests followed by ABC analysis pointed to heat pain thresholds as the most relevantly affected QST parameter. However, decision tree analysis indicated that UV-B additionally modulated sensitivity to cold. Unsupervised machine-learning techniques, implemented as emergent self-organizing maps, hinted at subgroups responding to topical application of capsaicin. The distinction among subgroups was based on sensitivity to pressure pain, which could be attributed to sex differences, with women being more sensitive than men. Thus, while UV-B and capsaicin share a major component of heat pain sensitization, they differ in their effects on QST parameter patterns in healthy subjects, suggesting a lack of redundancy between these models. PMID:28700537

FDG-PET/CT lymph node staging after neoadjuvant chemotherapy in patients with adenocarcinoma of the esophageal-gastric junction.

PubMed

Fencl, Pavel; Belohlavek, Otakar; Harustiak, Tomas; Zemanova, Milada

2016-11-01

The aim of the analysis was to assess the accuracy of various FDG-PET/CT parameters in staging lymph nodes after neoadjuvant chemotherapy. In this prospective study, 74 patients with adenocarcinoma of the esophageal-gastric junction were examined by FDG-PET/CT in the course of their neoadjuvant chemotherapy given before surgical treatment. Data from the final FDG-PET/CT examinations were compared with the histology from the surgical specimens (gold standard). The accuracy was calculated for four FDG-PET/CT parameters: (1) hypermetabolic nodes, (2) large nodes, (3) large-and-medium large nodes, and (4) hypermetabolic or large nodes. In 74 patients, a total of 1540 lymph nodes were obtained by surgery, and these were grouped into 287 regions according to topographic origin. Five hundred and two nodes were imaged by FDG-PET/CT and were grouped into these same regions for comparison. In the analysis, (1) hypermetabolic nodes, (2) large nodes, (3) large-and-medium large nodes, and (4) hypermetabolic or large nodes identified metastases in particular regions with sensitivities of 11.6%, 2.9%, 21.7%, and 13.0%, respectively; specificity was 98.6%, 94.5%, 74.8%, and 93.6%, respectively. The best accuracy of 77.7% reached the parameter of hypermetabolic nodes. Accuracy decreased to 62.0% when also smaller nodes (medium-large) were taken for the parameter of metastases. FDG-PET/CT proved low sensitivity and high specificity. Low sensitivity was based on low detection rate (32.6%) when compared nodes imaged by FDG-PET/CT to nodes found by surgery, and in inability to detect micrometastases. Sensitivity increased when also medium-large LNs were taken for positive, but specificity and accuracy decreased.

Heterodyne lock-in thermography of early demineralized in dental tissues

NASA Astrophysics Data System (ADS)

Wang, Fei; Liu, Jun-yan; Mohummad, Oliullah; Wang, Xiao-chun; Wang, Yang

2017-12-01

Heterodyne lock-in thermography (HeLIT) is a highly sensitive method to detect early demineralized in dental tissues, which is based on nonlinear photothermal phenomena of dental tissues. In this paper, the nonlinear photothermal phenomena of dental tissues was introduced, and then the system of HeLIT was developed. The relationship between laser modulated parameters (modulated frequency and laser intensity) and heterodyne lock-in thermal wave signal was investigated. The comparison between HeLIT and homodyne lock-in thermography (HoLIT) for detecting the different types of dental caries (smooth surface caries, proximal surface caries and occlusal surface caries) were carried out. Experimental results illustrate that the HeLIT has the merits of high sensitivity and high specificity in detecting different types of early caries.

Crack Growth Properties of Sealing Glasses

NASA Technical Reports Server (NTRS)

Salem, Jonathan A.; Tandon, R.

2008-01-01

The crack growth properties of several sealing glasses were measured using constant stress rate testing in 2% and 95% RH (relative humidity). Crack growth parameters measured in high humidity are systematically smaller (n and B) than those measured in low humidity, and velocities for dry environments are approx. 100x lower than for wet environments. The crack velocity is very sensitivity to small changes in RH at low RH. Confidence intervals on parameters that were estimated from propagation of errors were comparable to those from Monte Carlo simulation.

Highly sensitive image-derived indices of water-stressed plants using hyperspectral imaging in SWIR and histogram analysis

PubMed Central

Kim, David M.; Zhang, Hairong; Zhou, Haiying; Du, Tommy; Wu, Qian; Mockler, Todd C.; Berezin, Mikhail Y.

2015-01-01

The optical signature of leaves is an important monitoring and predictive parameter for a variety of biotic and abiotic stresses, including drought. Such signatures derived from spectroscopic measurements provide vegetation indices – a quantitative method for assessing plant health. However, the commonly used metrics suffer from low sensitivity. Relatively small changes in water content in moderately stressed plants demand high-contrast imaging to distinguish affected plants. We present a new approach in deriving sensitive indices using hyperspectral imaging in a short-wave infrared range from 800 nm to 1600 nm. Our method, based on high spectral resolution (1.56 nm) instrumentation and image processing algorithms (quantitative histogram analysis), enables us to distinguish a moderate water stress equivalent of 20% relative water content (RWC). The identified image-derived indices 15XX nm/14XX nm (i.e. 1529 nm/1416 nm) were superior to common vegetation indices, such as WBI, MSI, and NDWI, with significantly better sensitivity, enabling early diagnostics of plant health. PMID:26531782

High-frequency phase shift measurement greatly enhances the sensitivity of QCM immunosensors.

PubMed

March, Carmen; García, José V; Sánchez, Ángel; Arnau, Antonio; Jiménez, Yolanda; García, Pablo; Manclús, Juan J; Montoya, Ángel

2015-03-15

In spite of being widely used for in liquid biosensing applications, sensitivity improvement of conventional (5-20MHz) quartz crystal microbalance (QCM) sensors remains an unsolved challenging task. With the help of a new electronic characterization approach based on phase change measurements at a constant fixed frequency, a highly sensitive and versatile high fundamental frequency (HFF) QCM immunosensor has successfully been developed and tested for its use in pesticide (carbaryl and thiabendazole) analysis. The analytical performance of several immunosensors was compared in competitive immunoassays taking carbaryl insecticide as the model analyte. The highest sensitivity was exhibited by the 100MHz HFF-QCM carbaryl immunosensor. When results were compared with those reported for 9MHz QCM, analytical parameters clearly showed an improvement of one order of magnitude for sensitivity (estimated as the I50 value) and two orders of magnitude for the limit of detection (LOD): 30μgl(-1) vs 0.66μgL(-1)I50 value and 11μgL(-1) vs 0.14μgL(-1) LOD, for 9 and 100MHz, respectively. For the fungicide thiabendazole, I50 value was roughly the same as that previously reported for SPR under the same biochemical conditions, whereas LOD improved by a factor of 2. The analytical performance achieved by high frequency QCM immunosensors surpassed those of conventional QCM and SPR, closely approaching the most sensitive ELISAs. The developed 100MHz QCM immunosensor strongly improves sensitivity in biosensing, and therefore can be considered as a very promising new analytical tool for in liquid applications where highly sensitive detection is required. Copyright © 2014 Elsevier B.V. All rights reserved.

Adaptation of an urban land surface model to a tropical suburban area: Offline evaluation, sensitivity analysis, and optimization of TEB/ISBA (SURFEX)

NASA Astrophysics Data System (ADS)

Harshan, Suraj

The main objective of the present thesis is the improvement of the TEB/ISBA (SURFEX) urban land surface model (ULSM) through comprehensive evaluation, sensitivity analysis, and optimization experiments using energy balance and radiative and air temperature data observed during 11 months at a tropical sub-urban site in Singapore. Overall the performance of the model is satisfactory, with a small underestimation of net radiation and an overestimation of sensible heat flux. Weaknesses in predicting the latent heat flux are apparent with smaller model values during daytime and the model also significantly underpredicts both the daytime peak and nighttime storage heat. Surface temperatures of all facets are generally overpredicted. Significant variation exists in the model behaviour between dry and wet seasons. The vegetation parametrization used in the model is inadequate to represent the moisture dynamics, producing unrealistically low latent heat fluxes during a particularly dry period. The comprehensive evaluation of the USLM shows the need for accurate estimation of input parameter values for present site. Since obtaining many of these parameters through empirical methods is not feasible, the present study employed a two step approach aimed at providing information about the most sensitive parameters and an optimized parameter set from model calibration. Two well established sensitivity analysis methods (global: Sobol and local: Morris) and a state-of-the-art multiobjective evolutionary algorithm (Borg) were employed for sensitivity analysis and parameter estimation. Experiments were carried out for three different weather periods. The analysis indicates that roof related parameters are the most important ones in controlling the behaviour of the sensible heat flux and net radiation flux, with roof and road albedo as the most influential parameters. Soil moisture initialization parameters are important in controlling the latent heat flux. The built (town) fraction has a significant influence on all fluxes considered. Comparison between the Sobol and Morris methods shows similar sensitivities, indicating the robustness of the present analysis and that the Morris method can be employed as a computationally cheaper alternative of Sobol's method. Optimization as well as the sensitivity experiments for the three periods (dry, wet and mixed), show a noticeable difference in parameter sensitivity and parameter convergence, indicating inadequacies in model formulation. Existence of a significant proportion of less sensitive parameters might be indicating an over-parametrized model. Borg MOEA showed great promise in optimizing the input parameters set. The optimized model modified using the site specific values for thermal roughness length parametrization shows an improvement in the performances of outgoing longwave radiation flux, overall surface temperature, heat storage flux and sensible heat flux.

A semi-phenomenological model to predict the acoustic behavior of fully and partially reticulated polyurethane foams

NASA Astrophysics Data System (ADS)

Doutres, Olivier; Atalla, Noureddine; Dong, Kevin

2013-02-01

This paper proposes simple semi-phenomenological models to predict the sound absorption efficiency of highly porous polyurethane foams from microstructure characterization. In a previous paper [J. Appl. Phys. 110, 064901 (2011)], the authors presented a 3-parameter semi-phenomenological model linking the microstructure properties of fully and partially reticulated isotropic polyurethane foams (i.e., strut length l, strut thickness t, and reticulation rate Rw) to the macroscopic non-acoustic parameters involved in the classical Johnson-Champoux-Allard model (i.e., porosity ϕ, airflow resistivity σ, tortuosity α∝, viscous Λ, and thermal Λ' characteristic lengths). The model was based on existing scaling laws, validated for fully reticulated polyurethane foams, and improved using both geometrical and empirical approaches to account for the presence of membrane closing the pores. This 3-parameter model is applied to six polyurethane foams in this paper and is found highly sensitive to the microstructure characterization; particularly to strut's dimensions. A simplified micro-/macro model is then presented. It is based on the cell size Cs and reticulation rate Rw only, assuming that the geometric ratio between strut length l and strut thickness t is known. This simplified model, called the 2-parameter model, considerably simplifies the microstructure characterization procedure. A comparison of the two proposed semi-phenomenological models is presented using six polyurethane foams being either fully or partially reticulated, isotropic or anisotropic. It is shown that the 2-parameter model is less sensitive to measurement uncertainties compared to the original model and allows a better estimation of polyurethane foams sound absorption behavior.

Sensitivity analysis of urban flood flows to hydraulic controls

NASA Astrophysics Data System (ADS)

Chen, Shangzhi; Garambois, Pierre-André; Finaud-Guyot, Pascal; Dellinger, Guilhem; Terfous, Abdelali; Ghenaim, Abdallah

2017-04-01

Flooding represents one of the most significant natural hazards on each continent and particularly in highly populated areas. Improving the accuracy and robustness of prediction systems has become a priority. However, in situ measurements of floods remain difficult while a better understanding of flood flow spatiotemporal dynamics along with dataset for model validations appear essential. The present contribution is based on a unique experimental device at the scale 1/200, able to produce urban flooding with flood flows corresponding to frequent to rare return periods. The influence of 1D Saint Venant and 2D Shallow water model input parameters on simulated flows is assessed using global sensitivity analysis (GSA). The tested parameters are: global and local boundary conditions (water heights and discharge), spatially uniform or distributed friction coefficient and or porosity respectively tested in various ranges centered around their nominal values - calibrated thanks to accurate experimental data and related uncertainties. For various experimental configurations a variance decomposition method (ANOVA) is used to calculate spatially distributed Sobol' sensitivity indices (Si's). The sensitivity of water depth to input parameters on two main streets of the experimental device is presented here. Results show that the closer from the downstream boundary condition on water height, the higher the Sobol' index as predicted by hydraulic theory for subcritical flow, while interestingly the sensitivity to friction decreases. The sensitivity indices of all lateral inflows, representing crossroads in 1D, are also quantified in this study along with their asymptotic trends along flow distance. The relationship between lateral discharge magnitude and resulting sensitivity index of water depth is investigated. Concerning simulations with distributed friction coefficients, crossroad friction is shown to have much higher influence on upstream water depth profile than street friction coefficients. This methodology could be applied to any urban flood configuration in order to better understand flow dynamics and repartition but also guide model calibration in the light of flow controls.

Supplementary data of “Impacts of mesic and xeric urban vegetation on outdoor thermal comfort and microclimate in Phoenix, AZ”

PubMed Central

Song, Jiyun; Wang, Zhi-Hua

2015-01-01

An advanced Markov-Chain Monte Carlo approach called Subset Simulation is described in Au and Beck (2001) [1] was used to quantify parameter uncertainty and model sensitivity of the urban land-atmospheric framework, viz. the coupled urban canopy model-single column model (UCM-SCM). The results show that the atmospheric dynamics are sensitive to land surface conditions. The most sensitive parameters are dimensional parameters, i.e. roof width, aspect ratio, roughness length of heat and momentum, since these parameters control the magnitude of sensible heat flux. The relative insensitive parameters are hydrological parameters since the lawns or green roofs in urban areas are regularly irrigated so that the water availability for evaporation is never constrained. PMID:26702421

AN OVERVIEW OF THE UNCERTAINTY ANALYSIS, SENSITIVITY ANALYSIS, AND PARAMETER ESTIMATION (UA/SA/PE) API AND HOW TO IMPLEMENT IT

EPA Science Inventory

The Application Programming Interface (API) for Uncertainty Analysis, Sensitivity Analysis, and
Parameter Estimation (UA/SA/PE API) (also known as Calibration, Optimization and Sensitivity and Uncertainty (CUSO)) was developed in a joint effort between several members of both ...

Retinal sensitivity and choroidal thickness in high myopia.

PubMed

Zaben, Ahmad; Zapata, Miguel Á; Garcia-Arumi, Jose

2015-03-01

To estimate the association between choroidal thickness in the macular area and retinal sensitivity in eyes with high myopia. This investigation was a transversal study of patients with high myopia, all of whom had their retinal sensitivity measured with macular integrity assessment microperimetry. The choroidal thicknesses in the macular area were then measured by optical coherence tomography, and statistical correlations between their functionality and the anatomical structuralism, as assessed by both types of measurements, were analyzed. Ninety-six eyes from 77 patients with high myopia were studied. The patients had a mean age ± standard deviation of 38.9 ± 13.2 years, with spherical equivalent values ranging from -6.00 diopter to -20.00 diopter (8.74 ± 2.73 diopter). The mean central choroidal thickness was 159.00 ± 50.57. The mean choroidal thickness was directly correlated with sensitivity (r = 0.306; P = 0.004) and visual acuity but indirectly correlated with the spherical equivalent values and patient age. The mean sensitivity was not significantly correlated with the macular foveal thickness (r = -0.174; P = 0.101) or with the overall macular thickness (r = 0.103; P = 0.334); furthermore, the mean sensitivity was significantly correlated with visual acuity (r = 0.431; P < 0.001) and the spherical equivalent values (r = -0.306; P = 0.003). Retinal sensitivity in highly myopic eyes is directly correlated with choroidal thickness and does not seem to be associated with retinal thickness. Thus, in patients with high myopia, accurate measurements of choroidal thickness may provide more accurate information about this pathologic condition because choroidal thickness correlates to a greater degree with the functional parameters, patient age, and spherical equivalent values.

[Long-term outcome analysis of subjective and objective parameters after breast reduction in 159 cases: Patients judge differently from plastic surgeons].

PubMed

Osinga, Rik; Babst, Doris; Bodmer, Elvira S; Link, Bjoern C; Fritsche, Elmar; Hug, Urs

2017-12-01

This work assessed both subjective and objective postoperative parameters after breast reduction surgery and compared between patients and plastic surgeons. After an average postoperative observation period of 6.7 ± 2.7 (2 - 13) years, 159 out of 259 patients (61 %) were examined. The mean age at the time of surgery was 37 ± 14 (15 - 74) years. The postoperative anatomy of the breast and other anthropometric parameters were measured in cm with the patient in an upright position. The visual analogue scale (VAS) values for symmetry, size, shape, type of scar and overall satisfaction both from the patient's and from four plastic surgeons' perspectives were assessed and compared. Patients rated the postoperative result significantly better than surgeons. Good subjective ratings by patients for shape, symmetry and sensitivity correlated with high scores for overall assessment. Shape had the strongest influence on overall satisfaction (regression coefficient 0.357; p < 0.001), followed by symmetry (regression coefficient 0.239; p < 0.001) and sensitivity (regression coefficient 0.109; p = 0.040) of the breast. The better the subjective rating for symmetry by the patient, the smaller the measured difference of the jugulum-mamillary distance between left and right (regression coefficient -0.773; p = 0.002) and the smaller the difference in height of the lowest part of the breast between left and right (regression coefficient -0.465; p = 0.035). There was no significant correlation between age, weight, height, BMI, resected weight of the breast, postoperative breast size or type of scar with overall satisfaction. After breast reduction surgery, long-term outcome is rated significantly better by patients than by plastic surgeons. Good subjective ratings by patients for shape, symmetry and sensitivity correlated with high scores for overall assessment. Shape had the strongest influence on overall satisfaction, followed by symmetry and sensitivity of the breast. Postoperative size of the breast, resection weight, type of scar, age or BMI was not of significant influence. Symmetry was the only assessed subjective parameter of this study that could be objectified by postoperative measurements. Georg Thieme Verlag KG Stuttgart · New York.

Improving the performance of a pyramid wavefront sensor with modal sensitivity compensation.

PubMed

Korkiakoski, Visa; Vérinaud, Christophe; Le Louarn, Miska

2008-01-01

We describe a solution to increase the performance of a pyramid wavefront sensor (P-WFS) under bad seeing conditions. We show that most of the issues involve a reduced sensitivity that depends on the magnitude of the high frequency atmospheric distortions. We demonstrate in end-to-end closed loop adaptive optics simulations that with a modal sensitivity compensation method a high-order system with a nonmodulated P-WFS is robust in conditions with the Fried parameter r 0 at 0.5 microm in the range of 0.05-0.10 m. We also show that the method makes it possible to use a modal predictive control system to reach a total performance improvement of 0.06-0.45 in Strehl ratio at 1.6 microm. Especially at r 0=0.05 m the gain is dramatic.

Guided-Mode-Leaky-Mode-Guided-Mode Fiber Interferometer and Its High Sensitivity Refractive Index Sensing Technology.

PubMed

Wang, Qi; Li, Chunyue; Zhao, Chengwu; Li, Weizheng

2016-06-01

A cascaded symmetrical dual-taper Mach-Zehnder interferometer structure based on guided-mode and leaky-mode interference is proposed in this paper. Firstly, the interference spectrum characteristics of interferometer has been analyzed by the Finite Difference-Beam Propagation Method (FD-BPM). When the diameter of taper waist is 20 μm-30 μm, dual-taper length is 1 mm and taper distance is 4 cm-6 cm, the spectral contrast is higher, which is suitable for sensing. Secondly, experimental research on refractive index sensitivity is carried out. A refractive index sensitivity of 62.78 nm/RIU (refractive index unit) can achieved in the RI range of 1.3333-1.3792 (0%~25% NaCl solution), when the sensor structure parameters meet the following conditions: diameter of taper waist is 24 μm, dual-taper length is 837 μm and taper distance is 5.5 cm. The spectrum contrast is 0.8 and measurement resolution is 1.6 × 10(-5) RIU. The simulation analysis is highly consistent with experimental results. Research shows that the sensor has promising application in low RI fields where high-precision measurement is required due to its high sensitivity and stability.

Uncertainty analysis of vegetation distribution in the northern high latitudes during the 21st century with a dynamic vegetation model.

PubMed

Jiang, Yueyang; Zhuang, Qianlai; Schaphoff, Sibyll; Sitch, Stephen; Sokolov, Andrei; Kicklighter, David; Melillo, Jerry

2012-03-01

This study aims to assess how high-latitude vegetation may respond under various climate scenarios during the 21st century with a focus on analyzing model parameters induced uncertainty and how this uncertainty compares to the uncertainty induced by various climates. The analysis was based on a set of 10,000 Monte Carlo ensemble Lund-Potsdam-Jena (LPJ) simulations for the northern high latitudes (45(o)N and polewards) for the period 1900-2100. The LPJ Dynamic Global Vegetation Model (LPJ-DGVM) was run under contemporary and future climates from four Special Report Emission Scenarios (SRES), A1FI, A2, B1, and B2, based on the Hadley Centre General Circulation Model (GCM), and six climate scenarios, X901M, X902L, X903H, X904M, X905L, and X906H from the Integrated Global System Model (IGSM) at the Massachusetts Institute of Technology (MIT). In the current dynamic vegetation model, some parameters are more important than others in determining the vegetation distribution. Parameters that control plant carbon uptake and light-use efficiency have the predominant influence on the vegetation distribution of both woody and herbaceous plant functional types. The relative importance of different parameters varies temporally and spatially and is influenced by climate inputs. In addition to climate, these parameters play an important role in determining the vegetation distribution in the region. The parameter-based uncertainties contribute most to the total uncertainty. The current warming conditions lead to a complexity of vegetation responses in the region. Temperate trees will be more sensitive to climate variability, compared with boreal forest trees and C3 perennial grasses. This sensitivity would result in a unanimous northward greenness migration due to anomalous warming in the northern high latitudes. Temporally, boreal needleleaved evergreen plants are projected to decline considerably, and a large portion of C3 perennial grass is projected to disappear by the end of the 21st century. In contrast, the area of temperate trees would increase, especially under the most extreme A1FI scenario. As the warming continues, the northward greenness expansion in the Arctic region could continue.

Novel capsaicin-induced parameters of microcirculation in migraine patients revealed by imaging photoplethysmography.

PubMed

Kamshilin, Alexei A; Volynsky, Maxim A; Khayrutdinova, Olga; Nurkhametova, Dilyara; Babayan, Laura; Amelin, Alexander V; Mamontov, Oleg V; Giniatullin, Rashid

2018-06-18

The non-invasive biomarkers of migraine can help to develop the personalized medication of this disorder. In testing of the antimigraine drugs the capsaicin-induced skin redness with activated TRPV1 receptors in sensory neurons associated with the release of the migraine mediator CGRP has already been widely used. Fourteen migraine patients (mean age 34.6 ± 10.2 years) and 14 healthy volunteers (mean age 29.9 ± 9.7 years) participated in the experiment. A new arrangement of imaging photoplethysmography recently developed by us was used here to discover novel sensitive parameters of dermal blood flow during capsaicin applications in migraine patients. Blood pulsation amplitude (BPA) observed as optical-intensity waveform varying synchronously with heartbeat was used for detailed exploration of microcirculatory perfusion induced by capsicum patch application. The BPA signals, once having appeared after certain latent period, were progressively rising until being saturated. Capsaicin-induced high BPA areas were distributed unevenly under the patch, forming "hot spots." Interestingly the hot spots were much more variable in migraine patients than in the control group. In contrast to BPA, a slow component of waveforms related to the skin redness changed significantly less than BPA highlighting the latter parameter as the potential sensitive biomarker of capsaicin-induced activation of the blood flow. Thus, in migraine patients, there is a non-uniform (both in space and in time) reaction to capsaicin, resulting in highly variable openings of skin capillaries. BPA dynamics measured by imaging photoplethysmography could serve as a novel sensitive non-invasive biomarker of migraine-associated changes in microcirculation.

Tracking Electroencephalographic Changes Using Distributions of Linear Models: Application to Propofol-Based Depth of Anesthesia Monitoring.

PubMed

Kuhlmann, Levin; Manton, Jonathan H; Heyse, Bjorn; Vereecke, Hugo E M; Lipping, Tarmo; Struys, Michel M R F; Liley, David T J

2017-04-01

Tracking brain states with electrophysiological measurements often relies on short-term averages of extracted features and this may not adequately capture the variability of brain dynamics. The objective is to assess the hypotheses that this can be overcome by tracking distributions of linear models using anesthesia data, and that anesthetic brain state tracking performance of linear models is comparable to that of a high performing depth of anesthesia monitoring feature. Individuals' brain states are classified by comparing the distribution of linear (auto-regressive moving average-ARMA) model parameters estimated from electroencephalographic (EEG) data obtained with a sliding window to distributions of linear model parameters for each brain state. The method is applied to frontal EEG data from 15 subjects undergoing propofol anesthesia and classified by the observers assessment of alertness/sedation (OAA/S) scale. Classification of the OAA/S score was performed using distributions of either ARMA parameters or the benchmark feature, Higuchi fractal dimension. The highest average testing sensitivity of 59% (chance sensitivity: 17%) was found for ARMA (2,1) models and Higuchi fractal dimension achieved 52%, however, no statistical difference was observed. For the same ARMA case, there was no statistical difference if medians are used instead of distributions (sensitivity: 56%). The model-based distribution approach is not necessarily more effective than a median/short-term average approach, however, it performs well compared with a distribution approach based on a high performing anesthesia monitoring measure. These techniques hold potential for anesthesia monitoring and may be generally applicable for tracking brain states.

Biochemical effects of chlorpyrifos on two developmental stages of Xenopus laevis.

PubMed

Richards, Sean M; Kendall, Ron J

2002-09-01

Abstract-The effects of a 96-h static exposure to chlorpyrifos were examined in two developmental stages of larval Xenopus laevis (premetamorph and metamorph). Measures of effect included mortality, deformity, cholinesterase (ChE) activity, and DNA and protein concentration. All parameters indicated that metamorphs were more sensitive than were premetamorphs. For larvae exposed as premetamorphs, the median lethal concentration and median effective concentration were 14.6 mg/L and 1.71 mg/L; for those exposed as metamorphs, values were 0.56 mg/L and 0.24 mg/L, respectively. Cholinesterase activity was the most sensitive biochemical parameter. Exposure to chlorpyrifos at 0.01 mg/L caused significant decreases in the ChE activity of metamorphs; 0.1 mg/L significantly decreased premetamorph ChE activity. Metamorph DNA was significantly decreased at 0.1 mg/L; premetamorph DNA was not reduced until exposure to 1.0 mg/L. Whole-body protein was the least sensitive biochemical measure of effect. Premetamorphs did not experience a reduction in protein concentrations. Metamorph protein concentration was significantly decreased at 1.0 mg/L. Based on current surface water data, the most sensitive effect would not have a high probability (< or = 4.2%) of occurring in the environment.

Techno-economic sensitivity study of heliostat field parameters for micro-gas turbine CSP

NASA Astrophysics Data System (ADS)

Landman, Willem A.; Gauché, Paul; Dinter, Frank; Myburgh, J. T.

2017-06-01

Concentrating solar power systems based on micro-gas turbines potentially offer numerous benefits should they become commercially viable. Heliostat fields for such systems have unique requirements in that the number of heliostats and the focal ratios are typically much lower than conventional central receiver systems. This paper presents a techno-economic sensitivity study of heliostat field parameters for a micro-gas turbine central receiver system. A 100 kWe minitower system is considered for the base case and a one-at-a-time strategy is used to investigate parameter sensitivities. Increasing heliostat focal ratios are found to have significant optical performance benefits due to both a reduction in astigmatic aberrations and a reduction in the number of facet focal lengths required; confirming the hypothesis that smaller heliostats offer a techno-economic advantage. Fixed Horizontal Axis tracking mechanism is shown to outperform the conventional Azimuth Zenith tracking mechanism in high density heliostat fields. Although several improvements to heliostat field performance are discussed, the capex fraction of the heliostat field for such system is shown to be almost half that of a conventional central receiver system and optimum utilization of the higher capex components, namely; the receiver and turbine subsystems, are more rewarding than that of the heliostat field.

Torsional Vibration in the National Wind Technology Center’s 2.5-Megawatt Dynamometer

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

Sethuraman, Latha; Keller, Jonathan; Wallen, Robb

2016-08-31

This report documents the torsional drivetrain dynamics of the NWTC's 2.5-megawatt dynamometer as identified experimentally and as calculated using lumped parameter models using known inertia and stiffness parameters. The report is presented in two parts beginning with the identification of the primary torsional modes followed by the investigation of approaches to damp the torsional vibrations. The key mechanical parameters for the lumped parameter models and justification for the element grouping used in the derivation of the torsional modes are presented. The sensitivities of the torsional modes to different test article properties are discussed. The oscillations observed from the low-speed andmore » generator torque measurements were used to identify the extent of damping inherently achieved through active and passive compensation techniques. A simplified Simulink model of the dynamometer test article integrating the electro-mechanical power conversion and control features was established to emulate the torque behavior that was observed during testing. The torque response in the high-speed, low-speed, and generator shafts were tested and validated against experimental measurements involving step changes in load with the dynamometer operating under speed-regulation mode. The Simulink model serves as a ready reference to identify the torque sensitivities to various system parameters and to explore opportunities to improve torsional damping under different conditions.« less

Development of high strength, high temperature ceramics

NASA Technical Reports Server (NTRS)

Hall, W. B.

1982-01-01

Improvement in the high-pressure turbopumps, both fuel and oxidizer, in the Space Shuttle main engine were considered. The operation of these pumps is limited by temperature restrictions of the metallic components used in these pumps. Ceramic materials that retain strength at high temperatures and appear to be promising candidates for use as turbine blades and impellers are discussed. These high strength materials are sensitive to many related processing parameters such as impurities, sintering aids, reaction aids, particle size, processing temperature, and post thermal treatment. The specific objectives of the study were to: (1) identify and define the processing parameters that affect the properties of Si3N4 ceramic materials, (2) design and assembly equipment required for processing high strength ceramics, (3) design and assemble test apparatus for evaluating the high temperature properties of Si3N4, and (4) conduct a research program of manufacturing and evaluating Si3N4 materials as applicable to rocket engine applications.

Origin of the sensitivity in modeling the glide behaviour of dislocations

DOE PAGES

Pei, Zongrui; Stocks, George Malcolm

2018-03-26

The sensitivity in predicting glide behaviour of dislocations has been a long-standing problem in the framework of the Peierls-Nabarro model. The predictions of both the model itself and the analytic formulas based on it are too sensitive to the input parameters. In order to reveal the origin of this important problem in materials science, a new empirical-parameter-free formulation is proposed in the same framework. Unlike previous formulations, it includes only a limited small set of parameters all of which can be determined by convergence tests. Under special conditions the new formulation is reduced to its classic counterpart. In the lightmore » of this formulation, new relationships between Peierls stresses and the input parameters are identified, where the sensitivity is greatly reduced or even removed.« less

Visible-blind ultraviolet photodetectors on porous silicon carbide substrates

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

Naderi, N.; Hashim, M.R., E-mail: roslan@usm.my

2013-06-01

Highlights: • Highly reliable UV detectors are fabricated on porous silicon carbide substrates. • The optical properties of samples are enhanced by increasing the current density. • The optimized sample exhibits enhanced sensitivity to the incident UV radiation. - Abstract: Highly reliable visible-blind ultraviolet (UV) photodetectors were successfully fabricated on porous silicon carbide (PSC) substrates. High responsivity and high photoconductive gain were observed in a metal–semiconductor–metal ultraviolet photodetector that was fabricated on an optimized PSC substrate. The PSC samples were prepared via the UV-assisted photo-electrochemical etching of an n-type hexagonal silicon carbide (6H-SiC) substrate using different etching current densities. Themore » optical results showed that the current density is an outstanding etching parameter that controls the porosity and uniformity of PSC substrates. A highly porous substrate was synthesized using a suitable etching current density to enhance its light absorption, thereby improving the sensitivity of UV detector with this substrate. The electrical characteristics of fabricated devices on optimized PSC substrates exhibited enhanced sensitivity and responsivity to the incident radiation.« less

UNCERTAINTY AND SENSITIVITY ANALYSES FOR INTEGRATED HUMAN HEALTH AND ECOLOGICAL RISK ASSESSMENT OF HAZARDOUS WASTE DISPOSAL

EPA Science Inventory

While there is a high potential for exposure of humans and ecosystems to chemicals released from hazardous waste sites, the degree to which this potential is realized is often uncertain. Conceptually divided among parameter, model, and modeler uncertainties imparted during simula...

Dielectric elastomer for stretchable sensors: influence of the design and material properties

NASA Astrophysics Data System (ADS)

Jean-Mistral, C.; Iglesias, S.; Pruvost, S.; Duchet-Rumeau, J.; Chesné, S.

2016-04-01

Dielectric elastomers exhibit extended capabilities as flexible sensors for the detection of load distributions, pressure or huge deformations. Tracking the human movements of the fingers or the arms could be useful for the reconstruction of sporting gesture, or to control a human-like robot. Proposing new measurements methods are addressed in a number of publications leading to improving the sensitivity and accuracy of the sensing method. Generally, the associated modelling remains simple (RC or RC transmission line). The material parameters are considered constant or having a negligible effect which can lead to serious reduction of accuracy. Comparisons between measurements and modelling require care and skill, and could be tricky. Thus, we propose here a comprehensive modelling, taking into account the influence of the material properties on the performances of the dielectric elastomer sensor (DES). Various parameters influencing the characteristics of the sensors have been identified: dielectric constant, hyper-elasticity. The variations of these parameters as a function of the strain impact the linearity and sensitivity of the sensor of few percent. The sensitivity of the DES is also evaluated changing geometrical parameters (initial thickness) and its design (rectangular and dog-bone shapes). We discuss the impact of the shape regarding stress. Finally, DES including a silicone elastomer sandwiched between two high conductive stretchable electrodes, were manufactured and investigated. Classic and reliable LCR measurements are detailed. Experimental results validate our numerical model of large strain sensor (>50%).

Optimal observables for multiparameter seismic tomography

NASA Astrophysics Data System (ADS)

Bernauer, Moritz; Fichtner, Andreas; Igel, Heiner

2014-08-01

We propose a method for the design of seismic observables with maximum sensitivity to a target model parameter class, and minimum sensitivity to all remaining parameter classes. The resulting optimal observables thereby minimize interparameter trade-offs in multiparameter inverse problems. Our method is based on the linear combination of fundamental observables that can be any scalar measurement extracted from seismic waveforms. Optimal weights of the fundamental observables are determined with an efficient global search algorithm. While most optimal design methods assume variable source and/or receiver positions, our method has the flexibility to operate with a fixed source-receiver geometry, making it particularly attractive in studies where the mobility of sources and receivers is limited. In a series of examples we illustrate the construction of optimal observables, and assess the potentials and limitations of the method. The combination of Rayleigh-wave traveltimes in four frequency bands yields an observable with strongly enhanced sensitivity to 3-D density structure. Simultaneously, sensitivity to S velocity is reduced, and sensitivity to P velocity is eliminated. The original three-parameter problem thereby collapses into a simpler two-parameter problem with one dominant parameter. By defining parameter classes to equal earth model properties within specific regions, our approach mimics the Backus-Gilbert method where data are combined to focus sensitivity in a target region. This concept is illustrated using rotational ground motion measurements as fundamental observables. Forcing dominant sensitivity in the near-receiver region produces an observable that is insensitive to the Earth structure at more than a few wavelengths' distance from the receiver. This observable may be used for local tomography with teleseismic data. While our test examples use a small number of well-understood fundamental observables, few parameter classes and a radially symmetric earth model, the method itself does not impose such restrictions. It can easily be applied to large numbers of fundamental observables and parameters classes, as well as to 3-D heterogeneous earth models.

Are LOD and LOQ Reliable Parameters for Sensitivity Evaluation of Spectroscopic Methods?

PubMed

Ershadi, Saba; Shayanfar, Ali

2018-03-22

The limit of detection (LOD) and the limit of quantification (LOQ) are common parameters to assess the sensitivity of analytical methods. In this study, the LOD and LOQ of previously reported terbium sensitized analysis methods were calculated by different methods, and the results were compared with sensitivity parameters [lower limit of quantification (LLOQ)] of U.S. Food and Drug Administration guidelines. The details of the calibration curve and standard deviation of blank samples of three different terbium-sensitized luminescence methods for the quantification of mycophenolic acid, enrofloxacin, and silibinin were used for the calculation of LOD and LOQ. A comparison of LOD and LOQ values calculated by various methods and LLOQ shows a considerable difference. The significant difference of the calculated LOD and LOQ with various methods and LLOQ should be considered in the sensitivity evaluation of spectroscopic methods.

Assessing the sensitivity of a land-surface scheme to the parameter values using a single column model

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

Pitman, A.J.

The sensitivity of a land-surface scheme (the Biosphere Atmosphere Transfer Scheme, BATS) to its parameter values was investigated using a single column model. Identifying which parameters were important in controlling the turbulent energy fluxes, temperature, soil moisture, and runoff was dependent upon many factors. In the simulation of a nonmoisture-stressed tropical forest, results were dependent on a combination of reservoir terms (soil depth, root distribution), flux efficiency terms (roughness length, stomatal resistance), and available energy (albedo). If moisture became limited, the reservoir terms increased in importance because the total fluxes predicted depended on moisture availability and not on the ratemore » of transfer between the surface and the atmosphere. The sensitivity shown by BATS depended on which vegetation type was being simulated, which variable was used to determine sensitivity, the magnitude and sign of the parameter change, the climate regime (precipitation amount and frequency), and soil moisture levels and proximity to wilting. The interactions between these factors made it difficult to identify the most important parameters in BATS. Therefore, this paper does not argue that a particular set of parameters is important in BATS, rather it shows that no general ranking of parameters is possible. It is also emphasized that using `stand-alone` forcing to examine the sensitivity of a land-surface scheme to perturbations, in either parameters or the atmosphere, is unreliable due to the lack of surface-atmospheric feedbacks.« less

Parameter optimization, sensitivity, and uncertainty analysis of an ecosystem model at a forest flux tower site in the United States

USGS Publications Warehouse

Wu, Yiping; Liu, Shuguang; Huang, Zhihong; Yan, Wende

2014-01-01

Ecosystem models are useful tools for understanding ecological processes and for sustainable management of resources. In biogeochemical field, numerical models have been widely used for investigating carbon dynamics under global changes from site to regional and global scales. However, it is still challenging to optimize parameters and estimate parameterization uncertainty for complex process-based models such as the Erosion Deposition Carbon Model (EDCM), a modified version of CENTURY, that consider carbon, water, and nutrient cycles of ecosystems. This study was designed to conduct the parameter identifiability, optimization, sensitivity, and uncertainty analysis of EDCM using our developed EDCM-Auto, which incorporated a comprehensive R package—Flexible Modeling Framework (FME) and the Shuffled Complex Evolution (SCE) algorithm. Using a forest flux tower site as a case study, we implemented a comprehensive modeling analysis involving nine parameters and four target variables (carbon and water fluxes) with their corresponding measurements based on the eddy covariance technique. The local sensitivity analysis shows that the plant production-related parameters (e.g., PPDF1 and PRDX) are most sensitive to the model cost function. Both SCE and FME are comparable and performed well in deriving the optimal parameter set with satisfactory simulations of target variables. Global sensitivity and uncertainty analysis indicate that the parameter uncertainty and the resulting output uncertainty can be quantified, and that the magnitude of parameter-uncertainty effects depends on variables and seasons. This study also demonstrates that using the cutting-edge R functions such as FME can be feasible and attractive for conducting comprehensive parameter analysis for ecosystem modeling.

An investigation of new methods for estimating parameter sensitivities

NASA Technical Reports Server (NTRS)

Beltracchi, Todd J.; Gabriele, Gary A.

1988-01-01

Parameter sensitivity is defined as the estimation of changes in the modeling functions and the design variables due to small changes in the fixed parameters of the formulation. There are currently several methods for estimating parameter sensitivities requiring either difficult to obtain second order information, or do not return reliable estimates for the derivatives. Additionally, all the methods assume that the set of active constraints does not change in a neighborhood of the estimation point. If the active set does in fact change, than any extrapolations based on these derivatives may be in error. The objective here is to investigate more efficient new methods for estimating parameter sensitivities when the active set changes. The new method is based on the recursive quadratic programming (RQP) method and in conjunction a differencing formula to produce estimates of the sensitivities. This is compared to existing methods and is shown to be very competitive in terms of the number of function evaluations required. In terms of accuracy, the method is shown to be equivalent to a modified version of the Kuhn-Tucker method, where the Hessian of the Lagrangian is estimated using the BFS method employed by the RPQ algorithm. Inital testing on a test set with known sensitivities demonstrates that the method can accurately calculate the parameter sensitivity. To handle changes in the active set, a deflection algorithm is proposed for those cases where the new set of active constraints remains linearly independent. For those cases where dependencies occur, a directional derivative is proposed. A few simple examples are included for the algorithm, but extensive testing has not yet been performed.

A Wearable and Highly Sensitive Graphene Strain Sensor for Precise Home-Based Pulse Wave Monitoring.

PubMed

Yang, Tingting; Jiang, Xin; Zhong, Yujia; Zhao, Xuanliang; Lin, Shuyuan; Li, Jing; Li, Xinming; Xu, Jianlong; Li, Zhihong; Zhu, Hongwei

2017-07-28

Profuse medical information about cardiovascular properties can be gathered from pulse waveforms. Therefore, it is desirable to design a smart pulse monitoring device to achieve noninvasive and real-time acquisition of cardiovascular parameters. The majority of current pulse sensors are usually bulky or insufficient in sensitivity. In this work, a graphene-based skin-like sensor is explored for pulse wave sensing with features of easy use and wearing comfort. Moreover, the adjustment of the substrate stiffness and interfacial bonding accomplish the optimal balance between sensor linearity and signal sensitivity, as well as measurement of the beat-to-beat radial arterial pulse. Compared with the existing bulky and nonportable clinical instruments, this highly sensitive and soft sensing patch not only provides primary sensor interface to human skin, but also can objectively and accurately detect the subtle pulse signal variations in a real-time fashion, such as pulse waveforms with different ages, pre- and post-exercise, thus presenting a promising solution to home-based pulse monitoring.

Sensitive zone parameters and curvature radius evaluation for polymer optical fiber curvature sensors

NASA Astrophysics Data System (ADS)

Leal-Junior, Arnaldo G.; Frizera, Anselmo; José Pontes, Maria

2018-03-01

Polymer optical fibers (POFs) are suitable for applications such as curvature sensors, strain, temperature, liquid level, among others. However, for enhancing sensitivity, many polymer optical fiber curvature sensors based on intensity variation require a lateral section. Lateral section length, depth, and surface roughness have great influence on the sensor sensitivity, hysteresis, and linearity. Moreover, the sensor curvature radius increase the stress on the fiber, which leads on variation of the sensor behavior. This paper presents the analysis relating the curvature radius and lateral section length, depth and surface roughness with the sensor sensitivity, hysteresis and linearity for a POF curvature sensor. Results show a strong correlation between the decision parameters behavior and the performance for sensor applications based on intensity variation. Furthermore, there is a trade-off among the sensitive zone length, depth, surface roughness, and curvature radius with the sensor desired performance parameters, which are minimum hysteresis, maximum sensitivity, and maximum linearity. The optimization of these parameters is applied to obtain a sensor with sensitivity of 20.9 mV/°, linearity of 0.9992 and hysteresis below 1%, which represent a better performance of the sensor when compared with the sensor without the optimization.

Influence of Powder Injection Parameters in High-Pressure Cold Spray

NASA Astrophysics Data System (ADS)

Ozdemir, Ozan C.; Widener, Christian A.

2017-10-01

High-pressure cold spray systems are becoming widely accepted for use in the structural repair of surface defects of expensive machinery parts used in industrial and military equipment. The deposition quality of cold spray repairs is typically validated using coupon testing and through destructive analysis of mock-ups or first articles for a defined set of parameters. In order to provide a reliable repair, it is important to not only maintain the same processing parameters, but also to have optimum fixed parameters, such as the particle injection location. This study is intended to provide insight into the sensitivity of the way that the powder is injected upstream of supersonic nozzles in high-pressure cold spray systems and the effects of variations in injection parameters on the nature of the powder particle kinetics. Experimentally validated three-dimensional computational fluid dynamics (3D CFD) models are implemented to study the particle impact conditions for varying powder feeder tube size, powder feeder tube axial misalignment, and radial powder feeder injection location on the particle velocity and the deposition shape of aluminum alloy 6061. Outputs of the models are statistically analyzed to explore the shape of the spray plume distribution and resulting coating buildup.

Histogram analysis of T2*-based pharmacokinetic imaging in cerebral glioma grading.

PubMed

Liu, Hua-Shan; Chiang, Shih-Wei; Chung, Hsiao-Wen; Tsai, Ping-Huei; Hsu, Fei-Ting; Cho, Nai-Yu; Wang, Chao-Ying; Chou, Ming-Chung; Chen, Cheng-Yu

2018-03-01

To investigate the feasibility of histogram analysis of the T2*-based permeability parameter volume transfer constant (K trans ) for glioma grading and to explore the diagnostic performance of the histogram analysis of K trans and blood plasma volume (v p ). We recruited 31 and 11 patients with high- and low-grade gliomas, respectively. The histogram parameters of K trans and v p , derived from the first-pass pharmacokinetic modeling based on the T2* dynamic susceptibility-weighted contrast-enhanced perfusion-weighted magnetic resonance imaging (T2* DSC-PW-MRI) from the entire tumor volume, were evaluated for differentiating glioma grades. Histogram parameters of K trans and v p showed significant differences between high- and low-grade gliomas and exhibited significant correlations with tumor grades. The mean K trans derived from the T2* DSC-PW-MRI had the highest sensitivity and specificity for differentiating high-grade gliomas from low-grade gliomas compared with other histogram parameters of K trans and v p . Histogram analysis of T2*-based pharmacokinetic imaging is useful for cerebral glioma grading. The histogram parameters of the entire tumor K trans measurement can provide increased accuracy with additional information regarding microvascular permeability changes for identifying high-grade brain tumors. Copyright © 2017 Elsevier B.V. All rights reserved.

Influences of Cutting Speed and Material Mechanical Properties on Chip Deformation and Fracture during High-Speed Cutting of Inconel 718.

PubMed

Wang, Bing; Liu, Zhanqiang; Hou, Xin; Zhao, Jinfu

2018-03-21

The paper aims to investigate the influences of material constitutive and fracture parameters in addition to cutting speed on chip formation during high-speed cutting of Inconel 718. Finite element analyses for chip formation are conducted with Johnson-Cook constitutive and fracture models. Meanwhile, experiments of high-speed orthogonal cutting are performed to verify the simulation results with cutting speeds ranging from 50 m/min to 7000 m/min. The research indicates that the chip morphology transforms from serrated to fragmented at the cutting speed of 7000 m/min due to embrittlement of the workpiece material under ultra-high cutting speeds. The parameter of shear localization sensitivity is put forward to describe the influences of material mechanical properties on serrated chip formation. The results demonstrate that the effects of initial yield stress and thermal softening coefficient on chip shear localization are much more remarkable than the other constitutive parameters. For the material fracture parameters, the effects of initial fracture strain and exponential factor of stress state on chip shear localization are more much prominent. This paper provides guidance for controlling chip formation through the adjustment of material mechanical properties and the selection of appropriate cutting parameters.

Influences of Cutting Speed and Material Mechanical Properties on Chip Deformation and Fracture during High-Speed Cutting of Inconel 718

PubMed Central

Hou, Xin; Zhao, Jinfu

2018-01-01

The paper aims to investigate the influences of material constitutive and fracture parameters in addition to cutting speed on chip formation during high-speed cutting of Inconel 718. Finite element analyses for chip formation are conducted with Johnson–Cook constitutive and fracture models. Meanwhile, experiments of high-speed orthogonal cutting are performed to verify the simulation results with cutting speeds ranging from 50 m/min to 7000 m/min. The research indicates that the chip morphology transforms from serrated to fragmented at the cutting speed of 7000 m/min due to embrittlement of the workpiece material under ultra-high cutting speeds. The parameter of shear localization sensitivity is put forward to describe the influences of material mechanical properties on serrated chip formation. The results demonstrate that the effects of initial yield stress and thermal softening coefficient on chip shear localization are much more remarkable than the other constitutive parameters. For the material fracture parameters, the effects of initial fracture strain and exponential factor of stress state on chip shear localization are more much prominent. This paper provides guidance for controlling chip formation through the adjustment of material mechanical properties and the selection of appropriate cutting parameters. PMID:29561770

Test Method Variability in Slow Crack Growth Properties of Sealing Glasses

NASA Technical Reports Server (NTRS)

Salem, J. A.; Tandon, R.

2010-01-01

The crack growth properties of several sealing glasses were measured by using constant stress rate testing in 2 and 95 percent RH (relative humidity). Crack growth parameters measured in high humidity are systematically smaller (n and B) than those measured in low humidity, and crack velocities for dry environments are 100x lower than for wet environments. The crack velocity is very sensitive to small changes in RH at low RH. Biaxial and uniaxial stress states produced similar parameters. Confidence intervals on crack growth parameters that were estimated from propagation of errors solutions were comparable to those from Monte Carlo simulation. Use of scratch-like and indentation flaws produced similar crack growth parameters when residual stresses were considered.

Identification of contact and respiratory sensitizers according to IL-4 receptor α expression and IL-2 production

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

Goutet, Michèle, E-mail: michele.goutet@inrs.fr; Pépin, Elsa; Langonné, Isabelle

2012-04-15

Identification of allergenic chemicals is an important occupational safety issue. While several methods exist to identify contact sensitizers, there is currently no validated model to predict the potential of chemicals to act as respiratory sensitizers. Previously, we reported that cytometry analysis of the local immune responses induced in mice dermally exposed to the respiratory sensitizer trimellitic anhydride (TMA 10%) and contact sensitizer dinitrochlorobenzene (DNCB 1%) could identify divergent expression of several immune parameters. The present study confirms, first, that IgE-positive B cells, MHC class II molecules, interleukin (IL)-2, IL-4 and IL-4Rα can differentiate the allergic reactions caused by high dosesmore » of strong respiratory (TMA, phthalic anhydride and toluene diisocyanate) and contact sensitizers (DNCB, dinitrofluorobenzene and oxazolone). The second part of the study was designed to test the robustness of these markers when classing the weakly immunogenic chemicals most often encountered. Six respiratory allergens, including TMA (2.5%), five contact allergens, including DNCB (0.25%), and two irritants were compared at doses of equivalent immunogenicity. The results indicated that IL-4Rα and IL-2 can be reliably used to discriminate sensitizers. Respiratory sensitizers induced markedly higher IL-4Rα levels than contact allergens, while irritants had no effect on this parameter. Inversely, contact allergens tended to induce higher percentages of IL-2{sup +}CD8{sup +} cells than respiratory allergens. In contrast, the markers MHC-II, IgE and IL-4 were not able to classify chemicals with low immunogenic potential. In conclusion, IL-4Rα and IL-2 have the potential to be used in classifying a variety of chemical allergens. -- Highlights: ► Identification of chemical allergens is an important occupational safety issue. ► There is currently no model to predict the potential of chemicals to induce asthma. ► We analyze immune responses induced in mice by a variety of chemical sensitizers. ► IL-2 and IL-4R alpha show potential to discriminate between both types of allergens. ► This method could be applied to highly and weakly immunogenic chemicals.« less

Optimization for minimum sensitivity to uncertain parameters

NASA Technical Reports Server (NTRS)

Pritchard, Jocelyn I.; Adelman, Howard M.; Sobieszczanski-Sobieski, Jaroslaw

1994-01-01

A procedure to design a structure for minimum sensitivity to uncertainties in problem parameters is described. The approach is to minimize directly the sensitivity derivatives of the optimum design with respect to fixed design parameters using a nested optimization procedure. The procedure is demonstrated for the design of a bimetallic beam for minimum weight with insensitivity to uncertainties in structural properties. The beam is modeled with finite elements based on two dimensional beam analysis. A sequential quadratic programming procedure used as the optimizer supplies the Lagrange multipliers that are used to calculate the optimum sensitivity derivatives. The method was perceived to be successful from comparisons of the optimization results with parametric studies.

Detection of Volatile Organic Compounds by Self-assembled Monolayer Coated Sensor Array with Concentration-independent Fingerprints

PubMed Central

Chang, Ye; Tang, Ning; Qu, Hemi; Liu, Jing; Zhang, Daihua; Zhang, Hao; Pang, Wei; Duan, Xuexin

2016-01-01

In this paper, we have modeled and analyzed affinities and kinetics of volatile organic compounds (VOCs) adsorption (and desorption) on various surface chemical groups using multiple self-assembled monolayers (SAMs) functionalized film bulk acoustic resonator (FBAR) array. The high-frequency and micro-scale resonator provides improved sensitivity in the detections of VOCs at trace levels. With the study of affinities and kinetics, three concentration-independent intrinsic parameters (monolayer adsorption capacity, adsorption energy constant and desorption rate) of gas-surface interactions are obtained to contribute to a multi-parameter fingerprint library of VOC analytes. Effects of functional group’s properties on gas-surface interactions are also discussed. The proposed sensor array with concentration-independent fingerprint library shows potential as a portable electronic nose (e-nose) system for VOCs discrimination and gas-sensitive materials selections. PMID:27045012

Improving temporal resolution and speed sensitivity of laser speckle contrast analysis imaging based on noise reduction with an anisotropic diffusion filter

NASA Astrophysics Data System (ADS)

Song, Lipei; Wang, Xueyan; Zhang, Ru; Zhang, Kuanshou; Zhou, Zhen; Elson, Daniel S.

2018-07-01

The fluctuation of contrast caused by statistical noise degenerates the temporal/spatial resolution of laser speckle contrast imaging (LSCI) and limits the maximum speed when imaging. In this study, we investigated the application of the anisotropic diffusion filter (ADF) to temporal LSCI and found that the edge magnitude parameter of the ADF can be determined by the mean of the contrast image. Because the edge magnitude parameter is usually denoted as K, we term this the K-constant ADF (KC-ADF) and show that temporal sensitivity is improved when imaging because of the enhanced signal-to-noise ratio when using the KC-ADF in small-animal experiments. The cardiac cycle of a rat as high as 390 bpm can be imaged with an industrial camera.

Improving and Understanding Climate Models: Scale-Aware Parameterization of Cloud Water Inhomogeneity and Sensitivity of MJO Simulation to Physical Parameters in a Convection Scheme

NASA Astrophysics Data System (ADS)

Xie, Xin

Microphysics and convection parameterizations are two key components in a climate model to simulate realistic climatology and variability of cloud distribution and the cycles of energy and water. When a model has varying grid size or simulations have to be run with different resolutions, scale-aware parameterization is desirable so that we do not have to tune model parameters tailored to a particular grid size. The subgrid variability of cloud hydrometers is known to impact microphysics processes in climate models and is found to highly depend on spatial scale. A scale- aware liquid cloud subgrid variability parameterization is derived and implemented in the Community Earth System Model (CESM) in this study using long-term radar-based ground measurements from the Atmospheric Radiation Measurement (ARM) program. When used in the default CESM1 with the finite-volume dynamic core where a constant liquid inhomogeneity parameter was assumed, the newly developed parameterization reduces the cloud inhomogeneity in high latitudes and increases it in low latitudes. This is due to both the smaller grid size in high latitudes, and larger grid size in low latitudes in the longitude-latitude grid setting of CESM as well as the variation of the stability of the atmosphere. The single column model and general circulation model (GCM) sensitivity experiments show that the new parameterization increases the cloud liquid water path in polar regions and decreases it in low latitudes. Current CESM1 simulation suffers from the bias of both the pacific double ITCZ precipitation and weak Madden-Julian oscillation (MJO). Previous studies show that convective parameterization with multiple plumes may have the capability to alleviate such biases in a more uniform and physical way. A multiple-plume mass flux convective parameterization is used in Community Atmospheric Model (CAM) to investigate the sensitivity of MJO simulations. We show that MJO simulation is sensitive to entrainment rate specification. We found that shallow plumes can generate and sustain the MJO propagation in the model.

Evaluation of habitat suitability index models by global sensitivity and uncertainty analyses: a case study for submerged aquatic vegetation

USGS Publications Warehouse

Zajac, Zuzanna; Stith, Bradley M.; Bowling, Andrea C.; Langtimm, Catherine A.; Swain, Eric D.

2015-01-01

Habitat suitability index (HSI) models are commonly used to predict habitat quality and species distributions and are used to develop biological surveys, assess reserve and management priorities, and anticipate possible change under different management or climate change scenarios. Important management decisions may be based on model results, often without a clear understanding of the level of uncertainty associated with model outputs. We present an integrated methodology to assess the propagation of uncertainty from both inputs and structure of the HSI models on model outputs (uncertainty analysis: UA) and relative importance of uncertain model inputs and their interactions on the model output uncertainty (global sensitivity analysis: GSA). We illustrate the GSA/UA framework using simulated hydrology input data from a hydrodynamic model representing sea level changes and HSI models for two species of submerged aquatic vegetation (SAV) in southwest Everglades National Park: Vallisneria americana (tape grass) and Halodule wrightii (shoal grass). We found considerable spatial variation in uncertainty for both species, but distributions of HSI scores still allowed discrimination of sites with good versus poor conditions. Ranking of input parameter sensitivities also varied spatially for both species, with high habitat quality sites showing higher sensitivity to different parameters than low-quality sites. HSI models may be especially useful when species distribution data are unavailable, providing means of exploiting widely available environmental datasets to model past, current, and future habitat conditions. The GSA/UA approach provides a general method for better understanding HSI model dynamics, the spatial and temporal variation in uncertainties, and the parameters that contribute most to model uncertainty. Including an uncertainty and sensitivity analysis in modeling efforts as part of the decision-making framework will result in better-informed, more robust decisions.

Sensitivity of the two-dimensional shearless mixing layer to the initial turbulent kinetic energy and integral length scale

NASA Astrophysics Data System (ADS)

Fathali, M.; Deshiri, M. Khoshnami

2016-04-01

The shearless mixing layer is generated from the interaction of two homogeneous isotropic turbulence (HIT) fields with different integral scales ℓ1 and ℓ2 and different turbulent kinetic energies E1 and E2. In this study, the sensitivity of temporal evolutions of two-dimensional, incompressible shearless mixing layers to the parametric variations of ℓ1/ℓ2 and E1/E2 is investigated. The sensitivity methodology is based on the nonintrusive approach; using direct numerical simulation and generalized polynomial chaos expansion. The analysis is carried out at Reℓ 1=90 for the high-energy HIT region and different integral length scale ratios 1 /4 ≤ℓ1/ℓ2≤4 and turbulent kinetic energy ratios 1 ≤E1/E2≤30 . It is found that the most influential parameter on the variability of the mixing layer evolution is the turbulent kinetic energy while variations of the integral length scale show a negligible influence on the flow field variability. A significant level of anisotropy and intermittency is observed in both large and small scales. In particular, it is found that large scales have higher levels of intermittency and sensitivity to the variations of ℓ1/ℓ2 and E1/E2 compared to the small scales. Reconstructed response surfaces of the flow field intermittency and the turbulent penetration depth show monotonic dependence on ℓ1/ℓ2 and E1/E2 . The mixing layer growth rate and the mixing efficiency both show sensitive dependence on the initial condition parameters. However, the probability density function of these quantities shows relatively small solution variations in response to the variations of the initial condition parameters.

Switch of Sensitivity Dynamics Revealed with DyGloSA Toolbox for Dynamical Global Sensitivity Analysis as an Early Warning for System's Critical Transition

PubMed Central

Baumuratova, Tatiana; Dobre, Simona; Bastogne, Thierry; Sauter, Thomas

2013-01-01

Systems with bifurcations may experience abrupt irreversible and often unwanted shifts in their performance, called critical transitions. For many systems like climate, economy, ecosystems it is highly desirable to identify indicators serving as early warnings of such regime shifts. Several statistical measures were recently proposed as early warnings of critical transitions including increased variance, autocorrelation and skewness of experimental or model-generated data. The lack of automatized tool for model-based prediction of critical transitions led to designing DyGloSA – a MATLAB toolbox for dynamical global parameter sensitivity analysis (GPSA) of ordinary differential equations models. We suggest that the switch in dynamics of parameter sensitivities revealed by our toolbox is an early warning that a system is approaching a critical transition. We illustrate the efficiency of our toolbox by analyzing several models with bifurcations and predicting the time periods when systems can still avoid going to a critical transition by manipulating certain parameter values, which is not detectable with the existing SA techniques. DyGloSA is based on the SBToolbox2 and contains functions, which compute dynamically the global sensitivity indices of the system by applying four main GPSA methods: eFAST, Sobol's ANOVA, PRCC and WALS. It includes parallelized versions of the functions enabling significant reduction of the computational time (up to 12 times). DyGloSA is freely available as a set of MATLAB scripts at http://bio.uni.lu/systems_biology/software/dyglosa. It requires installation of MATLAB (versions R2008b or later) and the Systems Biology Toolbox2 available at www.sbtoolbox2.org. DyGloSA can be run on Windows and Linux systems, -32 and -64 bits. PMID:24367574

Switch of sensitivity dynamics revealed with DyGloSA toolbox for dynamical global sensitivity analysis as an early warning for system's critical transition.

PubMed

Baumuratova, Tatiana; Dobre, Simona; Bastogne, Thierry; Sauter, Thomas

2013-01-01

Systems with bifurcations may experience abrupt irreversible and often unwanted shifts in their performance, called critical transitions. For many systems like climate, economy, ecosystems it is highly desirable to identify indicators serving as early warnings of such regime shifts. Several statistical measures were recently proposed as early warnings of critical transitions including increased variance, autocorrelation and skewness of experimental or model-generated data. The lack of automatized tool for model-based prediction of critical transitions led to designing DyGloSA - a MATLAB toolbox for dynamical global parameter sensitivity analysis (GPSA) of ordinary differential equations models. We suggest that the switch in dynamics of parameter sensitivities revealed by our toolbox is an early warning that a system is approaching a critical transition. We illustrate the efficiency of our toolbox by analyzing several models with bifurcations and predicting the time periods when systems can still avoid going to a critical transition by manipulating certain parameter values, which is not detectable with the existing SA techniques. DyGloSA is based on the SBToolbox2 and contains functions, which compute dynamically the global sensitivity indices of the system by applying four main GPSA methods: eFAST, Sobol's ANOVA, PRCC and WALS. It includes parallelized versions of the functions enabling significant reduction of the computational time (up to 12 times). DyGloSA is freely available as a set of MATLAB scripts at http://bio.uni.lu/systems_biology/software/dyglosa. It requires installation of MATLAB (versions R2008b or later) and the Systems Biology Toolbox2 available at www.sbtoolbox2.org. DyGloSA can be run on Windows and Linux systems, -32 and -64 bits.

Identification of sensitive parameters of a tropical forest in Southern Mexico to improve the understanding of C-band radar images

NASA Astrophysics Data System (ADS)

Monsivais-Huertero, A.; Jimenez-Escalona, J. C.; Ramos, J.; Zempoaltecatl-Ramirez, E.

2013-05-01

Forest areas cover the 32% of the Mexican territory. Due to their geographical location, Mexico presents heterogeneous climatic and topographic conditions. The country is divided into two different regions: an arid /semiarid zone (North) and a tropical/temperate zone (South). Due to the effects of climate change, Mexico has been affected in two ways. In the North, there has been a desertification of regions as result of the absence of rainfall and a low rate of soil moisture. On the other hand, in the South, there has been an increase in the intensity of rainfall causing serious flooding. Another effect is the excessive deforestation in Southern Mexico. The FAO has determined that Mexico could present one of the highest losses of forest areas mainly in temperate and subtropical ecosystems. The Biosphere Reserve of Calakmul is the protected area with the largest surface of tropical forest in Mexico. The Biosphere Reserve of Calakmul is located in the state of Campeche that the flora and fauna are being affected. The type of vegetation located in the reserve of Calakmul Biosphere is rainforest with high spatial density and highly heterogeneous due to multiple plant species and the impact of human activities in the area. The satellite remote sensing techniques becomes a very useful tool to monitor the area because a large area can be covered. To understand the radar images, the identification of sensitive parameters governing the radar signal is necessary. With the launch of the satellites Radarsat-2, ASAR-Envisat and ALOSPalSAR, significant progress has been done in the interpretation of satellite radar images. Directly applying physical models becomes a problem due to the large number of input parameters in the models, together with the difficulty in measuring these parameters in the field. The models developed so far have been applied and validated for homogeneous forests with low or average spatial density of trees. This is why it is recommended in a comprehensive validation of the models for heterogeneous forests with a high density of trees, such as Calakmul. This paper presents a methodology for identifying sensitive parameters governing the scenes backscatter vegetables reserve Calakmul Biosphere from a physical model.

Exploring the impact of forcing error characteristics on physically based snow simulations within a global sensitivity analysis framework

NASA Astrophysics Data System (ADS)

Raleigh, M. S.; Lundquist, J. D.; Clark, M. P.

2015-07-01

Physically based models provide insights into key hydrologic processes but are associated with uncertainties due to deficiencies in forcing data, model parameters, and model structure. Forcing uncertainty is enhanced in snow-affected catchments, where weather stations are scarce and prone to measurement errors, and meteorological variables exhibit high variability. Hence, there is limited understanding of how forcing error characteristics affect simulations of cold region hydrology and which error characteristics are most important. Here we employ global sensitivity analysis to explore how (1) different error types (i.e., bias, random errors), (2) different error probability distributions, and (3) different error magnitudes influence physically based simulations of four snow variables (snow water equivalent, ablation rates, snow disappearance, and sublimation). We use the Sobol' global sensitivity analysis, which is typically used for model parameters but adapted here for testing model sensitivity to coexisting errors in all forcings. We quantify the Utah Energy Balance model's sensitivity to forcing errors with 1 840 000 Monte Carlo simulations across four sites and five different scenarios. Model outputs were (1) consistently more sensitive to forcing biases than random errors, (2) generally less sensitive to forcing error distributions, and (3) critically sensitive to different forcings depending on the relative magnitude of errors. For typical error magnitudes found in areas with drifting snow, precipitation bias was the most important factor for snow water equivalent, ablation rates, and snow disappearance timing, but other forcings had a more dominant impact when precipitation uncertainty was due solely to gauge undercatch. Additionally, the relative importance of forcing errors depended on the model output of interest. Sensitivity analysis can reveal which forcing error characteristics matter most for hydrologic modeling.

Research and design of photovoltaic power monitoring system based on Zig Bee

NASA Astrophysics Data System (ADS)

Zhu, Lijuan; Yun, Zhonghua; Bianbawangdui; Bianbaciren

2018-01-01

In order to monitor and study the impact of environmental parameters on photovoltaic cells, a photovoltaic cell monitoring system based on ZigBee is designed. The system uses ZigBee wireless communication technology to achieve real-time acquisition of P-I-V curves and environmental parameters of terminal nodes, and transfer the data to the coordinator, the coordinator communicates with the STM32 through the serial port. In addition, STM32 uses the serial port to transfer data to the host computer written by LabVIEW, and the collected data is displayed in real time, as well as stored in the background database. The experimental results show that the system has a stable performance, accurate measurement, high sensitivity, high reliability, can better realize real-time collection of photovoltaic cell characteristics and environmental parameters.

Association of circulating sTRAIL and high-sensitivity CRP with type 2 diabetic nephropathy and foot ulcers

PubMed Central

Arık, Hasan Onur; Yalcin, Arzu Didem; Gumuslu, Saadet; Genç, Gizem Esra; Turan, Adil; Sanlioglu, Ahter Dilsad

2013-01-01

Background Hyperglycemia is among the potent factors that may induce or facilitate apoptosis. TNF-Related Apoptosis-Inducing Factor (TRAIL) is known for its apoptotic and immunomodulatory effects that have recently been correlated with diabetes. We examined serum-soluble TRAIL (sTRAIL) and high-sensitivity CRP (hs-CRP) levels and their association with various distinct parameters in type 2 diabetic nephropathy patients with diabetic foot disease. Material/Methods Twenty-two diabetic nephropathy patients with foot ulcers were enrolled in our study. Patients had been diagnosed with diabetes at age 24±10.58 years. Circulating sTRAIL and Hs-CRP levels were compared with control values, and possible correlations were investigated with parameters such as age, Wagner’s Grade (WG), BMI, HbA1c, and creatinine. Results Serum sTRAIL levels were significantly reduced in the patient group, compared to healthy subjects. High HsCRP levels correlated with age, and WGS correlated with BMI and creatinine levels. Conclusions Significantly suppressed sTRAIL levels in diabetic nephropathy patients with foot ulcers compared to healthy controls suggest a protective role for TRAIL in the disease setting. PMID:23986130

Modelling of intermittent microwave convective drying: parameter sensitivity

NASA Astrophysics Data System (ADS)

Zhang, Zhijun; Qin, Wenchao; Shi, Bin; Gao, Jingxin; Zhang, Shiwei

2017-06-01

The reliability of the predictions of a mathematical model is a prerequisite to its utilization. A multiphase porous media model of intermittent microwave convective drying is developed based on the literature. The model considers the liquid water, gas and solid matrix inside of food. The model is simulated by COMSOL software. Its sensitivity parameter is analysed by changing the parameter values by ±20%, with the exception of several parameters. The sensitivity analysis of the process of the microwave power level shows that each parameter: ambient temperature, effective gas diffusivity, and evaporation rate constant, has significant effects on the process. However, the surface mass, heat transfer coefficient, relative and intrinsic permeability of the gas, and capillary diffusivity of water do not have a considerable effect. The evaporation rate constant has minimal parameter sensitivity with a ±20% value change, until it is changed 10-fold. In all results, the temperature and vapour pressure curves show the same trends as the moisture content curve. However, the water saturation at the medium surface and in the centre show different results. Vapour transfer is the major mass transfer phenomenon that affects the drying process.

An automatic and effective parameter optimization method for model tuning

NASA Astrophysics Data System (ADS)

Zhang, T.; Li, L.; Lin, Y.; Xue, W.; Xie, F.; Xu, H.; Huang, X.

2015-05-01

Physical parameterizations in General Circulation Models (GCMs), having various uncertain parameters, greatly impact model performance and model climate sensitivity. Traditional manual and empirical tuning of these parameters is time consuming and ineffective. In this study, a "three-step" methodology is proposed to automatically and effectively obtain the optimum combination of some key parameters in cloud and convective parameterizations according to a comprehensive objective evaluation metrics. Different from the traditional optimization methods, two extra steps, one determines parameter sensitivity and the other chooses the optimum initial value of sensitive parameters, are introduced before the downhill simplex method to reduce the computational cost and improve the tuning performance. Atmospheric GCM simulation results show that the optimum combination of these parameters determined using this method is able to improve the model's overall performance by 9%. The proposed methodology and software framework can be easily applied to other GCMs to speed up the model development process, especially regarding unavoidable comprehensive parameters tuning during the model development stage.

Towards a Better Understanding of Water Stores and Fluxes: Model Observation Synthesis in a Snowmelt Dominated Research Watershed

NASA Astrophysics Data System (ADS)

Ryken, A.; Gochis, D.; Carroll, R. W. H.; Bearup, L. A.; Williams, K. H.; Maxwell, R. M.

2017-12-01

The hydrology of high-elevation, mountainous regions is poorly represented in Earth Systems Models (ESMs). In addition to regulating downstream water delivery, these ecosystems play an important role in the storage and land-atmosphere exchange of carbon and water. Water balances are sensitive to the amount of water stored in the snowpack (SWE) and the amount of water leaving the system in the form of evapotranspiration—two pieces of the hydrologic cycle that are difficult to observe and model in heterogeneous mountainous regions due to spatially variant weather patterns. In an effort to resolve this hydrologic gap in ESMs, this study seeks to better understand the interactions between groundwater, carbon flux, and the lower atmosphere in these high-altitude environments through integration of field observations and model simulations. We compare model simulations to field observations to elucidate process performance combined with a sensitivity analysis to better understand parameter uncertainty. Observations from a meteorological station in the East River Basin are used to force an integrated single-column hydrologic model, ParFlow-CLM. This met station is co-located with an eddy covariance tower, which, along with snow surveys, is used to better constrain the water, carbon, and energy fluxes in the coupled land-atmosphere model to increase our understanding of high-altitude headwaters. Preliminary results suggest the model compares well to the eddy covariance tower and field observations, shown through both correct magnitude and timing of peak SWE along with similar magnitudes and diurnal patterns of heat and water fluxes. Initial sensitivity analysis results show that an increase in temperature leads to a decrease in peak SWE as well as an increase in latent heat revealing a sensitivity of the model to air temperature. Further sensitivity analysis will help us understand more parameter uncertainty. Through obtaining more accurate and higher resolution meteorological data and applying it to a coupled hydrologic model, this study can lead to better representation of mountainous environments in all ESMs.

Non-robust numerical simulations of analogue extension experiments

NASA Astrophysics Data System (ADS)

Naliboff, John; Buiter, Susanne

2016-04-01

Numerical and analogue models of lithospheric deformation provide significant insight into the tectonic processes that lead to specific structural and geophysical observations. As these two types of models contain distinct assumptions and tradeoffs, investigations drawing conclusions from both can reveal robust links between first-order processes and observations. Recent studies have focused on detailed comparisons between numerical and analogue experiments in both compressional and extensional tectonics, sometimes involving multiple lithospheric deformation codes and analogue setups. While such comparisons often show good agreement on first-order deformation styles, results frequently diverge on second-order structures, such as shear zone dip angles or spacing, and in certain cases even on first-order structures. Here, we present finite-element experiments that are designed to directly reproduce analogue "sandbox" extension experiments at the cm-scale. We use material properties and boundary conditions that are directly taken from analogue experiments and use a Drucker-Prager failure model to simulate shear zone formation in sand. We find that our numerical experiments are highly sensitive to numerous numerical parameters. For example, changes to the numerical resolution, velocity convergence parameters and elemental viscosity averaging commonly produce significant changes in first- and second-order structures accommodating deformation. The sensitivity of the numerical simulations to small parameter changes likely reflects a number of factors, including, but not limited to, high angles of internal friction assigned to sand, complex, unknown interactions between the brittle sand (used as an upper crust equivalent) and viscous silicone (lower crust), highly non-linear strain weakening processes and poor constraints on the cohesion of sand. Our numerical-analogue comparison is hampered by (a) an incomplete knowledge of the fine details of sand failure and sand properties, and (b) likely limitations to the use of a continuum Drucker-Prager model for representing shear zone formation in sand. In some cases our numerical experiments provide reasonable fits to first-order structures observed in the analogue experiments, but the numerical sensitivity to small parameter variations leads us to conclude that the numerical experiments are not robust.

Angle-selective optical filter for highly sensitive reflection photoplethysmogram

PubMed Central

Hwang, Chan-Sol; Yang, Sung-Pyo; Jang, Kyung-Won; Park, Jung-Woo; Jeong, Ki-Hun

2017-01-01

We report an angle-selective optical filter (ASOF) for highly sensitive reflection photoplethysmography (PPG) sensors. The ASOF features slanted aluminum (Al) micromirror arrays embedded in transparent polymer resin, which effectively block scattered light under human tissue. The device microfabrication was done by using geometry-guided resist reflow of polymer micropatterns, polydimethylsiloxane replica molding, and oblique angle deposition of thin Al film. The angular transmittance through the ASOF is precisely controlled by the angle of micromirrors. For the mirror angle of 30 degrees, the ASOF accepts an incident light between - 90 to + 50 degrees and the maximum transmittance at - 55 degrees. The ASOF exhibits the substantial reduction of both the in-band noise of PPG signals over a factor of two and the low-frequency noise by three times. Consequently, this filter allows distinguishing the diastolic peak that allows miscellaneous parameters with diverse vascular information. This optical filter provides a new opportunity for highly sensitive PPG monitoring or miscellaneous optical tomography. PMID:29082070

Sensitive Adsorptive Voltammetric Method for Determination of Bisphenol A by Gold Nanoparticle/Polyvinylpyrrolidone-Modified Pencil Graphite Electrode

PubMed Central

Yaman, Yesim Tugce; Abaci, Serdar

2016-01-01

A novel electrochemical sensor gold nanoparticle (AuNP)/polyvinylpyrrolidone (PVP) modified pencil graphite electrode (PGE) was developed for the ultrasensitive determination of Bisphenol A (BPA). The gold nanoparticles were electrodeposited by constant potential electrolysis and PVP was attached by passive adsorption onto the electrode surface. The electrode surfaces were characterized by electrochemical impedance spectroscopy (EIS) and scanning electron microscopy (SEM). The parameters that affected the experimental conditions were researched and optimized. The AuNP/PVP/PGE sensor provided high sensitivity and selectivity for BPA recognition by using square wave adsorptive stripping voltammetry (SWAdSV). Under optimized conditions, the detection limit was found to be 1.0 nM. This new sensor system offered the advantages of simple fabrication which aided the expeditious replication, low cost, fast response, high sensitivity and low background current for BPA. This new sensor system was successfully tested for the detection of the amount of BPA in bottled drinking water with high reliability. PMID:27231912

Statistical sensitivity analysis of a simple nuclear waste repository model

NASA Astrophysics Data System (ADS)

Ronen, Y.; Lucius, J. L.; Blow, E. M.

1980-06-01

A preliminary step in a comprehensive sensitivity analysis of the modeling of a nuclear waste repository. The purpose of the complete analysis is to determine which modeling parameters and physical data are most important in determining key design performance criteria and then to obtain the uncertainty in the design for safety considerations. The theory for a statistical screening design methodology is developed for later use in the overall program. The theory was applied to the test case of determining the relative importance of the sensitivity of near field temperature distribution in a single level salt repository to modeling parameters. The exact values of the sensitivities to these physical and modeling parameters were then obtained using direct methods of recalculation. The sensitivity coefficients found to be important for the sample problem were thermal loading, distance between the spent fuel canisters and their radius. Other important parameters were those related to salt properties at a point of interest in the repository.

On the sensitivity analysis of porous material models

NASA Astrophysics Data System (ADS)

Ouisse, Morvan; Ichchou, Mohamed; Chedly, Slaheddine; Collet, Manuel

2012-11-01

Porous materials are used in many vibroacoustic applications. Different available models describe their behaviors according to materials' intrinsic characteristics. For instance, in the case of porous material with rigid frame, and according to the Champoux-Allard model, five parameters are employed. In this paper, an investigation about this model sensitivity to parameters according to frequency is conducted. Sobol and FAST algorithms are used for sensitivity analysis. A strong parametric frequency dependent hierarchy is shown. Sensitivity investigations confirm that resistivity is the most influent parameter when acoustic absorption and surface impedance of porous materials with rigid frame are considered. The analysis is first performed on a wide category of porous materials, and then restricted to a polyurethane foam analysis in order to illustrate the impact of the reduction of the design space. In a second part, a sensitivity analysis is performed using the Biot-Allard model with nine parameters including mechanical effects of the frame and conclusions are drawn through numerical simulations.

High sensitivity phase retrieval method in grating-based x-ray phase contrast imaging

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

Wu, Zhao; Gao, Kun; Chen, Jian

2015-02-15

Purpose: Grating-based x-ray phase contrast imaging is considered as one of the most promising techniques for future medical imaging. Many different methods have been developed to retrieve phase signal, among which the phase stepping (PS) method is widely used. However, further practical implementations are hindered, due to its complex scanning mode and high radiation dose. In contrast, the reverse projection (RP) method is a novel fast and low dose extraction approach. In this contribution, the authors present a quantitative analysis of the noise properties of the refraction signals retrieved by the two methods and compare their sensitivities. Methods: Using themore » error propagation formula, the authors analyze theoretically the signal-to-noise ratios (SNRs) of the refraction images retrieved by the two methods. Then, the sensitivities of the two extraction methods are compared under an identical exposure dose. Numerical experiments are performed to validate the theoretical results and provide some quantitative insight. Results: The SNRs of the two methods are both dependent on the system parameters, but in different ways. Comparison between their sensitivities reveals that for the refraction signal, the RP method possesses a higher sensitivity, especially in the case of high visibility and/or at the edge of the object. Conclusions: Compared with the PS method, the RP method has a superior sensitivity and provides refraction images with a higher SNR. Therefore, one can obtain highly sensitive refraction images in grating-based phase contrast imaging. This is very important for future preclinical and clinical implementations.« less

Complex interactions between climate change and toxicants: evidence that temperature variability increases sensitivity to cadmium.

PubMed

Kimberly, David A; Salice, Christopher J

2014-07-01

The Intergovernmental Panel on Climate Change projects that global climate change will have significant impacts on environmental conditions including potential effects on sensitivity of organisms to environmental contaminants. The objective of this study was to test the climate-induced toxicant sensitivity (CITS) hypothesis in which acclimation to altered climate parameters increases toxicant sensitivity. Adult Physa pomilia snails were acclimated to a near optimal 22 °C or a high-normal 28 °C for 28 days. After 28 days, snails from each temperature group were challenged with either low (150 μg/L) or high (300 μg/L) cadmium at each temperature (28 or 22 °C). In contrast to the CITS hypothesis, we found that acclimation temperature did not have a strong influence on cadmium sensitivity except at the high cadmium test concentration where snails acclimated to 28 °C were more cadmium tolerant. However, snails that experienced a switch in temperature for the cadmium challenge, regardless of the switch direction, were the most sensitive to cadmium. Within the snails that were switched between temperatures, snails acclimated at 28 °C and then exposed to high cadmium at 22 °C exhibited significantly greater mortality than those snails acclimated to 22 °C and then exposed to cadmium at 28 °C. Our results point to the importance of temperature variability in increasing toxicant sensitivity but also suggest a potentially complex cost of temperature acclimation. Broadly, the type of temporal stressor exposures we simulated may reduce overall plasticity in responses to stress ultimately rendering populations more vulnerable to adverse effects.

High Frequency QRS ECG Accurately Detects Cardiomyopathy

NASA Technical Reports Server (NTRS)

Schlegel, Todd T.; Arenare, Brian; Poulin, Gregory; Moser, Daniel R.; Delgado, Reynolds

2005-01-01

High frequency (HF, 150-250 Hz) analysis over the entire QRS interval of the ECG is more sensitive than conventional ECG for detecting myocardial ischemia. However, the accuracy of HF QRS ECG for detecting cardiomyopathy is unknown. We obtained simultaneous resting conventional and HF QRS 12-lead ECGs in 66 patients with cardiomyopathy (EF = 23.2 plus or minus 6.l%, mean plus or minus SD) and in 66 age- and gender-matched healthy controls using PC-based ECG software recently developed at NASA. The single most accurate ECG parameter for detecting cardiomyopathy was an HF QRS morphological score that takes into consideration the total number and severity of reduced amplitude zones (RAZs) present plus the clustering of RAZs together in contiguous leads. This RAZ score had an area under the receiver operator curve (ROC) of 0.91, and was 88% sensitive, 82% specific and 85% accurate for identifying cardiomyopathy at optimum score cut-off of 140 points. Although conventional ECG parameters such as the QRS and QTc intervals were also significantly longer in patients than controls (P less than 0.001, BBBs excluded), these conventional parameters were less accurate (area under the ROC = 0.77 and 0.77, respectively) than HF QRS morphological parameters for identifying underlying cardiomyopathy. The total amplitude of the HF QRS complexes, as measured by summed root mean square voltages (RMSVs), also differed between patients and controls (33.8 plus or minus 11.5 vs. 41.5 plus or minus 13.6 mV, respectively, P less than 0.003), but this parameter was even less accurate in distinguishing the two groups (area under ROC = 0.67) than the HF QRS morphologic and conventional ECG parameters. Diagnostic accuracy was optimal (86%) when the RAZ score from the HF QRS ECG and the QTc interval from the conventional ECG were used simultaneously with cut-offs of greater than or equal to 40 points and greater than or equal to 445 ms, respectively. In conclusion 12-lead HF QRS ECG employing RAZ scoring is a simple, accurate and inexpensive screening technique for cardiomyopathy. Although HF QRS ECG is highly sensitive for cardiomyopathy, its specificity may be compromised in patients with cardiac pathologies other than cardiomyopathy, such as uncomplicated coronary artery disease or multiple coronary disease risk factors. Further studies are required to determine whether HF QRS might be useful for monitoring cardiomyopathy severity or the efficacy of therapy in a longitudinal fashion.

A glucose concentration and temperature sensor based on long period fiber gratings induced by electric-arc discharge

NASA Astrophysics Data System (ADS)

Du, Chao; Wang, Qi

2017-10-01

As one of the key parameters in biological and chemical reactions, glucose concentration objectively reflects the characteristics of reactions, so the real-time monitoring of glucose concentration is important in the field of biochemical. Meanwhile, the influence from temperature should be considered. The fiber sensors have been studied extensively for decades due to the advantages of small size, immunity to electromagnetic interference and high sensitivity, which are suitable for the application of biochemical sensing. A long period fiber grating (LPFG) sensor induced by electric-arc discharge has been fabricated and demonstrated for simultaneous measurement of glucose concentration and temperature. The proposed sensor was fabricated by inscribing a sing mode fiber (SMF) with periodic electric-arc discharge technology. During the fabrication process, the electric-arc discharge technology was produced by a commercial fusion splicer, and the period of inscribed LPFG was determined by the movement of translation stages. A serials of periodic geometrical deformations would be formed in SMF after the fabrication, and the discharge intensity and discharge time can be adjusted though the fusion splicer settings screen. The core mode can be coupled into the cladding modes at certain wavelength when they satisfy the phase-matching conditions, and there will be several resonance dips in the transmission spectrum in LPFG. The resonance dips formed by the coupling between cladding modes and core mode have different sensitivity responses, so the simultaneous measurement for multi-parameter can be realized by monitoring the wavelength shifts of the resonance dips. Compared with the LPFG based on conventional SMF, the glucose concentration sensitivity has been obviously enhanced by etching the cladding with hydrofluoric acid solution. Based on the independent measured results, a dual-parameter measurement matrix has been built for signal demodulation. Because of the easy fabrication, low cost, small size and high sensitivity, the sensor is promising to be used for the biochemical sensing field where simultaneous measurement of glucose concentration and temperature is required.

An adaptive least-squares global sensitivity method and application to a plasma-coupled combustion prediction with parametric correlation

NASA Astrophysics Data System (ADS)

Tang, Kunkun; Massa, Luca; Wang, Jonathan; Freund, Jonathan B.

2018-05-01

We introduce an efficient non-intrusive surrogate-based methodology for global sensitivity analysis and uncertainty quantification. Modified covariance-based sensitivity indices (mCov-SI) are defined for outputs that reflect correlated effects. The overall approach is applied to simulations of a complex plasma-coupled combustion system with disparate uncertain parameters in sub-models for chemical kinetics and a laser-induced breakdown ignition seed. The surrogate is based on an Analysis of Variance (ANOVA) expansion, such as widely used in statistics, with orthogonal polynomials representing the ANOVA subspaces and a polynomial dimensional decomposition (PDD) representing its multi-dimensional components. The coefficients of the PDD expansion are obtained using a least-squares regression, which both avoids the direct computation of high-dimensional integrals and affords an attractive flexibility in choosing sampling points. This facilitates importance sampling using a Bayesian calibrated posterior distribution, which is fast and thus particularly advantageous in common practical cases, such as our large-scale demonstration, for which the asymptotic convergence properties of polynomial expansions cannot be realized due to computation expense. Effort, instead, is focused on efficient finite-resolution sampling. Standard covariance-based sensitivity indices (Cov-SI) are employed to account for correlation of the uncertain parameters. Magnitude of Cov-SI is unfortunately unbounded, which can produce extremely large indices that limit their utility. Alternatively, mCov-SI are then proposed in order to bound this magnitude ∈ [ 0 , 1 ]. The polynomial expansion is coupled with an adaptive ANOVA strategy to provide an accurate surrogate as the union of several low-dimensional spaces, avoiding the typical computational cost of a high-dimensional expansion. It is also adaptively simplified according to the relative contribution of the different polynomials to the total variance. The approach is demonstrated for a laser-induced turbulent combustion simulation model, which includes parameters with correlated effects.

Frequency-domain full-waveform inversion with non-linear descent directions

NASA Astrophysics Data System (ADS)

Geng, Yu; Pan, Wenyong; Innanen, Kristopher A.

2018-05-01

Full-waveform inversion (FWI) is a highly non-linear inverse problem, normally solved iteratively, with each iteration involving an update constructed through linear operations on the residuals. Incorporating a flexible degree of non-linearity within each update may have important consequences for convergence rates, determination of low model wavenumbers and discrimination of parameters. We examine one approach for doing so, wherein higher order scattering terms are included within the sensitivity kernel during the construction of the descent direction, adjusting it away from that of the standard Gauss-Newton approach. These scattering terms are naturally admitted when we construct the sensitivity kernel by varying not the current but the to-be-updated model at each iteration. Linear and/or non-linear inverse scattering methodologies allow these additional sensitivity contributions to be computed from the current data residuals within any given update. We show that in the presence of pre-critical reflection data, the error in a second-order non-linear update to a background of s0 is, in our scheme, proportional to at most (Δs/s0)3 in the actual parameter jump Δs causing the reflection. In contrast, the error in a standard Gauss-Newton FWI update is proportional to (Δs/s0)2. For numerical implementation of more complex cases, we introduce a non-linear frequency-domain scheme, with an inner and an outer loop. A perturbation is determined from the data residuals within the inner loop, and a descent direction based on the resulting non-linear sensitivity kernel is computed in the outer loop. We examine the response of this non-linear FWI using acoustic single-parameter synthetics derived from the Marmousi model. The inverted results vary depending on data frequency ranges and initial models, but we conclude that the non-linear FWI has the capability to generate high-resolution model estimates in both shallow and deep regions, and to converge rapidly, relative to a benchmark FWI approach involving the standard gradient.

Prediction of oxidation parameters of purified Kilka fish oil including gallic acid and methyl gallate by adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network.

PubMed

Asnaashari, Maryam; Farhoosh, Reza; Farahmandfar, Reza

2016-10-01

As a result of concerns regarding possible health hazards of synthetic antioxidants, gallic acid and methyl gallate may be introduced as natural antioxidants to improve oxidative stability of marine oil. Since conventional modelling could not predict the oxidative parameters precisely, artificial neural network (ANN) and neuro-fuzzy inference system (ANFIS) modelling with three inputs, including type of antioxidant (gallic acid and methyl gallate), temperature (35, 45 and 55 °C) and concentration (0, 200, 400, 800 and 1600 mg L(-1) ) and four outputs containing induction period (IP), slope of initial stage of oxidation curve (k1 ) and slope of propagation stage of oxidation curve (k2 ) and peroxide value at the IP (PVIP ) were performed to predict the oxidation parameters of Kilka oil triacylglycerols and were compared to multiple linear regression (MLR). The results showed ANFIS was the best model with high coefficient of determination (R(2)  = 0.99, 0.99, 0.92 and 0.77 for IP, k1 , k2 and PVIP , respectively). So, the RMSE and MAE values for IP were 7.49 and 4.92 in ANFIS model. However, they were to be 15.95 and 10.88 and 34.14 and 3.60 for the best MLP structure and MLR, respectively. So, MLR showed the minimum accuracy among the constructed models. Sensitivity analysis based on the ANFIS model suggested a high sensitivity of oxidation parameters, particularly the induction period on concentrations of gallic acid and methyl gallate due to their high antioxidant activity to retard oil oxidation and enhanced Kilka oil shelf life. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Enhancing coronary Wave Intensity Analysis robustness by high order central finite differences

PubMed Central

Rivolo, Simone; Asrress, Kaleab N.; Chiribiri, Amedeo; Sammut, Eva; Wesolowski, Roman; Bloch, Lars Ø.; Grøndal, Anne K.; Hønge, Jesper L.; Kim, Won Y.; Marber, Michael; Redwood, Simon; Nagel, Eike; Smith, Nicolas P.; Lee, Jack

2014-01-01

Background Coronary Wave Intensity Analysis (cWIA) is a technique capable of separating the effects of proximal arterial haemodynamics from cardiac mechanics. Studies have identified WIA-derived indices that are closely correlated with several disease processes and predictive of functional recovery following myocardial infarction. The cWIA clinical application has, however, been limited by technical challenges including a lack of standardization across different studies and the derived indices' sensitivity to the processing parameters. Specifically, a critical step in WIA is the noise removal for evaluation of derivatives of the acquired signals, typically performed by applying a Savitzky–Golay filter, to reduce the high frequency acquisition noise. Methods The impact of the filter parameter selection on cWIA output, and on the derived clinical metrics (integral areas and peaks of the major waves), is first analysed. The sensitivity analysis is performed either by using the filter as a differentiator to calculate the signals' time derivative or by applying the filter to smooth the ensemble-averaged waveforms. Furthermore, the power-spectrum of the ensemble-averaged waveforms contains little high-frequency components, which motivated us to propose an alternative approach to compute the time derivatives of the acquired waveforms using a central finite difference scheme. Results and Conclusion The cWIA output and consequently the derived clinical metrics are significantly affected by the filter parameters, irrespective of its use as a smoothing filter or a differentiator. The proposed approach is parameter-free and, when applied to the 10 in-vivo human datasets and the 50 in-vivo animal datasets, enhances the cWIA robustness by significantly reducing the outcome variability (by 60%). PMID:25187852

Classification of toxicity effects of biotransformed hepatic drugs using whale optimized support vector machines.

PubMed

Tharwat, Alaa; Moemen, Yasmine S; Hassanien, Aboul Ella

2017-04-01

Measuring toxicity is an important step in drug development. Nevertheless, the current experimental methods used to estimate the drug toxicity are expensive and time-consuming, indicating that they are not suitable for large-scale evaluation of drug toxicity in the early stage of drug development. Hence, there is a high demand to develop computational models that can predict the drug toxicity risks. In this study, we used a dataset that consists of 553 drugs that biotransformed in liver. The toxic effects were calculated for the current data, namely, mutagenic, tumorigenic, irritant and reproductive effect. Each drug is represented by 31 chemical descriptors (features). The proposed model consists of three phases. In the first phase, the most discriminative subset of features is selected using rough set-based methods to reduce the classification time while improving the classification performance. In the second phase, different sampling methods such as Random Under-Sampling, Random Over-Sampling and Synthetic Minority Oversampling Technique (SMOTE), BorderLine SMOTE and Safe Level SMOTE are used to solve the problem of imbalanced dataset. In the third phase, the Support Vector Machines (SVM) classifier is used to classify an unknown drug into toxic or non-toxic. SVM parameters such as the penalty parameter and kernel parameter have a great impact on the classification accuracy of the model. In this paper, Whale Optimization Algorithm (WOA) has been proposed to optimize the parameters of SVM, so that the classification error can be reduced. The experimental results proved that the proposed model achieved high sensitivity to all toxic effects. Overall, the high sensitivity of the WOA+SVM model indicates that it could be used for the prediction of drug toxicity in the early stage of drug development. Copyright © 2017 Elsevier Inc. All rights reserved.

MODFLOW-2000, the U.S. Geological Survey modular ground-water model; user guide to the observation, sensitivity, and parameter-estimation processes and three post-processing programs

USGS Publications Warehouse

Hill, Mary C.; Banta, E.R.; Harbaugh, A.W.; Anderman, E.R.

2000-01-01

This report documents the Observation, Sensitivity, and Parameter-Estimation Processes of the ground-water modeling computer program MODFLOW-2000. The Observation Process generates model-calculated values for comparison with measured, or observed, quantities. A variety of statistics is calculated to quantify this comparison, including a weighted least-squares objective function. In addition, a number of files are produced that can be used to compare the values graphically. The Sensitivity Process calculates the sensitivity of hydraulic heads throughout the model with respect to specified parameters using the accurate sensitivity-equation method. These are called grid sensitivities. If the Observation Process is active, it uses the grid sensitivities to calculate sensitivities for the simulated values associated with the observations. These are called observation sensitivities. Observation sensitivities are used to calculate a number of statistics that can be used (1) to diagnose inadequate data, (2) to identify parameters that probably cannot be estimated by regression using the available observations, and (3) to evaluate the utility of proposed new data. The Parameter-Estimation Process uses a modified Gauss-Newton method to adjust values of user-selected input parameters in an iterative procedure to minimize the value of the weighted least-squares objective function. Statistics produced by the Parameter-Estimation Process can be used to evaluate estimated parameter values; statistics produced by the Observation Process and post-processing program RESAN-2000 can be used to evaluate how accurately the model represents the actual processes; statistics produced by post-processing program YCINT-2000 can be used to quantify the uncertainty of model simulated values. Parameters are defined in the Ground-Water Flow Process input files and can be used to calculate most model inputs, such as: for explicitly defined model layers, horizontal hydraulic conductivity, horizontal anisotropy, vertical hydraulic conductivity or vertical anisotropy, specific storage, and specific yield; and, for implicitly represented layers, vertical hydraulic conductivity. In addition, parameters can be defined to calculate the hydraulic conductance of the River, General-Head Boundary, and Drain Packages; areal recharge rates of the Recharge Package; maximum evapotranspiration of the Evapotranspiration Package; pumpage or the rate of flow at defined-flux boundaries of the Well Package; and the hydraulic head at constant-head boundaries. The spatial variation of model inputs produced using defined parameters is very flexible, including interpolated distributions that require the summation of contributions from different parameters. Observations can include measured hydraulic heads or temporal changes in hydraulic heads, measured gains and losses along head-dependent boundaries (such as streams), flows through constant-head boundaries, and advective transport through the system, which generally would be inferred from measured concentrations. MODFLOW-2000 is intended for use on any computer operating system. The program consists of algorithms programmed in Fortran 90, which efficiently performs numerical calculations and is fully compatible with the newer Fortran 95. The code is easily modified to be compatible with FORTRAN 77. Coordination for multiple processors is accommodated using Message Passing Interface (MPI) commands. The program is designed in a modular fashion that is intended to support inclusion of new capabilities.

Composite laminate failure parameter optimization through four-point flexure experimentation and analysis

DOE PAGES

Nelson, Stacy; English, Shawn; Briggs, Timothy

2016-05-06

Fiber-reinforced composite materials offer light-weight solutions to many structural challenges. In the development of high-performance composite structures, a thorough understanding is required of the composite materials themselves as well as methods for the analysis and failure prediction of the relevant composite structures. However, the mechanical properties required for the complete constitutive definition of a composite material can be difficult to determine through experimentation. Therefore, efficient methods are necessary that can be used to determine which properties are relevant to the analysis of a specific structure and to establish a structure's response to a material parameter that can only be definedmore » through estimation. The objectives of this paper deal with demonstrating the potential value of sensitivity and uncertainty quantification techniques during the failure analysis of loaded composite structures; and the proposed methods are applied to the simulation of the four-point flexural characterization of a carbon fiber composite material. Utilizing a recently implemented, phenomenological orthotropic material model that is capable of predicting progressive composite damage and failure, a sensitivity analysis is completed to establish which material parameters are truly relevant to a simulation's outcome. Then, a parameter study is completed to determine the effect of the relevant material properties' expected variations on the simulated four-point flexural behavior as well as to determine the value of an unknown material property. This process demonstrates the ability to formulate accurate predictions in the absence of a rigorous material characterization effort. Finally, the presented results indicate that a sensitivity analysis and parameter study can be used to streamline the material definition process as the described flexural characterization was used for model validation.« less

High Sensitivity and High Detection Specificity of Gold-Nanoparticle-Grafted Nanostructured Silicon Mass Spectrometry for Glucose Analysis.

PubMed

Tsao, Chia-Wen; Yang, Zhi-Jie

2015-10-14

Desorption/ionization on silicon (DIOS) is a high-performance matrix-free mass spectrometry (MS) analysis method that involves using silicon nanostructures as a matrix for MS desorption/ionization. In this study, gold nanoparticles grafted onto a nanostructured silicon (AuNPs-nSi) surface were demonstrated as a DIOS-MS analysis approach with high sensitivity and high detection specificity for glucose detection. A glucose sample deposited on the AuNPs-nSi surface was directly catalyzed to negatively charged gluconic acid molecules on a single AuNPs-nSi chip for MS analysis. The AuNPs-nSi surface was fabricated using two electroless deposition steps and one electroless etching step. The effects of the electroless fabrication parameters on the glucose detection efficiency were evaluated. Practical application of AuNPs-nSi MS glucose analysis in urine samples was also demonstrated in this study.

Investigation of uncertainty in CO 2 reservoir models: A sensitivity analysis of relative permeability parameter values

DOE PAGES

Yoshida, Nozomu; Levine, Jonathan S.; Stauffer, Philip H.

2016-03-22

Numerical reservoir models of CO 2 injection in saline formations rely on parameterization of laboratory-measured pore-scale processes. Here, we have performed a parameter sensitivity study and Monte Carlo simulations to determine the normalized change in total CO 2 injected using the finite element heat and mass-transfer code (FEHM) numerical reservoir simulator. Experimentally measured relative permeability parameter values were used to generate distribution functions for parameter sampling. The parameter sensitivity study analyzed five different levels for each of the relative permeability model parameters. All but one of the parameters changed the CO 2 injectivity by <10%, less than the geostatistical uncertainty that applies to all large subsurface systems due to natural geophysical variability and inherently small sample sizes. The exception was the end-point CO 2 relative permeability, kmore » $$0\\atop{r}$$ CO2, the maximum attainable effective CO 2 permeability during CO 2 invasion, which changed CO2 injectivity by as much as 80%. Similarly, Monte Carlo simulation using 1000 realizations of relative permeability parameters showed no relationship between CO 2 injectivity and any of the parameters but k$$0\\atop{r}$$ CO2, which had a very strong (R 2 = 0.9685) power law relationship with total CO 2 injected. Model sensitivity to k$$0\\atop{r}$$ CO2 points to the importance of accurate core flood and wettability measurements.« less

Investigation of uncertainty in CO 2 reservoir models: A sensitivity analysis of relative permeability parameter values

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

Yoshida, Nozomu; Levine, Jonathan S.; Stauffer, Philip H.

Numerical reservoir models of CO 2 injection in saline formations rely on parameterization of laboratory-measured pore-scale processes. Here, we have performed a parameter sensitivity study and Monte Carlo simulations to determine the normalized change in total CO 2 injected using the finite element heat and mass-transfer code (FEHM) numerical reservoir simulator. Experimentally measured relative permeability parameter values were used to generate distribution functions for parameter sampling. The parameter sensitivity study analyzed five different levels for each of the relative permeability model parameters. All but one of the parameters changed the CO 2 injectivity by <10%, less than the geostatistical uncertainty that applies to all large subsurface systems due to natural geophysical variability and inherently small sample sizes. The exception was the end-point CO 2 relative permeability, kmore » $$0\\atop{r}$$ CO2, the maximum attainable effective CO 2 permeability during CO 2 invasion, which changed CO2 injectivity by as much as 80%. Similarly, Monte Carlo simulation using 1000 realizations of relative permeability parameters showed no relationship between CO 2 injectivity and any of the parameters but k$$0\\atop{r}$$ CO2, which had a very strong (R 2 = 0.9685) power law relationship with total CO 2 injected. Model sensitivity to k$$0\\atop{r}$$ CO2 points to the importance of accurate core flood and wettability measurements.« less

Point-contact sensors: New prospects for a nanoscale-sensitive technique

NASA Astrophysics Data System (ADS)

Kamarchuk, G. V.; Pospelov, A. P.; Yeremenko, A. V.; Faulques, E. C.; Yanson, I. K.

2006-11-01

Point contacts have been discovered to present excellent and unprecedented characteristics when used as gas sensors. A novel concept has been tested successfully and opens the way to useful applications. Copper point contacts were investigated in gas media such as NOx, HCl, H2S and human breath. They reveal high sensitivity to these gases: the measured signal increases by 2-3 orders of magnitude upon gas exposure. Sensor parameters are fully restored when gas action ceases. Stable reproducibility of experimental results was observed after several exposure cycles onto the investigated point contacts.

Development of nanosensors in nuclear technology

NASA Astrophysics Data System (ADS)

Hassan, Thamir A. A.

2017-01-01

Selectivity, sensitivity, and stability (three S parameters) are developed as a new range of sensor this provided instruments for harsh, radioactive waste polluted environment monitoring. Isotope effect is very effective for nuclear radiation sensors preparation.in this presentation are reviewed of the development of Nanosensors in nuclear technology, such as high temperature boron and its compounds with suitable physical and chemical features as sensitive element for temperature and nuclear sensor, Boron isotopes based semiconductor nanosensors and studies of the mechanism of the removal uranium from radioactive wastewater with graphene oxide (GO).

Uncertainty Analysis of Runoff Simulations and Parameter Identifiability in the Community Land Model – Evidence from MOPEX Basins

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

Huang, Maoyi; Hou, Zhangshuan; Leung, Lai-Yung R.

2013-12-01

With the emergence of earth system models as important tools for understanding and predicting climate change and implications to mitigation and adaptation, it has become increasingly important to assess the fidelity of the land component within earth system models to capture realistic hydrological processes and their response to the changing climate and quantify the associated uncertainties. This study investigates the sensitivity of runoff simulations to major hydrologic parameters in version 4 of the Community Land Model (CLM4) by integrating CLM4 with a stochastic exploratory sensitivity analysis framework at 20 selected watersheds from the Model Parameter Estimation Experiment (MOPEX) spanning amore » wide range of climate and site conditions. We found that for runoff simulations, the most significant parameters are those related to the subsurface runoff parameterizations. Soil texture related parameters and surface runoff parameters are of secondary significance. Moreover, climate and soil conditions play important roles in the parameter sensitivity. In general, site conditions within water-limited hydrologic regimes and with finer soil texture result in stronger sensitivity of output variables, such as runoff and its surface and subsurface components, to the input parameters in CLM4. This study demonstrated the feasibility of parameter inversion for CLM4 using streamflow observations to improve runoff simulations. By ranking the significance of the input parameters, we showed that the parameter set dimensionality could be reduced for CLM4 parameter calibration under different hydrologic and climatic regimes so that the inverse problem is less ill posed.« less

Systematic parameter estimation and sensitivity analysis using a multidimensional PEMFC model coupled with DAKOTA.

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

Wang, Chao Yang; Luo, Gang; Jiang, Fangming

2010-05-01

Current computational models for proton exchange membrane fuel cells (PEMFCs) include a large number of parameters such as boundary conditions, material properties, and numerous parameters used in sub-models for membrane transport, two-phase flow and electrochemistry. In order to successfully use a computational PEMFC model in design and optimization, it is important to identify critical parameters under a wide variety of operating conditions, such as relative humidity, current load, temperature, etc. Moreover, when experimental data is available in the form of polarization curves or local distribution of current and reactant/product species (e.g., O2, H2O concentrations), critical parameters can be estimated inmore » order to enable the model to better fit the data. Sensitivity analysis and parameter estimation are typically performed using manual adjustment of parameters, which is also common in parameter studies. We present work to demonstrate a systematic approach based on using a widely available toolkit developed at Sandia called DAKOTA that supports many kinds of design studies, such as sensitivity analysis as well as optimization and uncertainty quantification. In the present work, we couple a multidimensional PEMFC model (which is being developed, tested and later validated in a joint effort by a team from Penn State Univ. and Sandia National Laboratories) with DAKOTA through the mapping of model parameters to system responses. Using this interface, we demonstrate the efficiency of performing simple parameter studies as well as identifying critical parameters using sensitivity analysis. Finally, we show examples of optimization and parameter estimation using the automated capability in DAKOTA.« less

Enabling Predictive Simulation and UQ of Complex Multiphysics PDE Systems by the Development of Goal-Oriented Variational Sensitivity Analysis and a-Posteriori Error Estimation Methods

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

Estep, Donald

2015-11-30

This project addressed the challenge of predictive computational analysis of strongly coupled, highly nonlinear multiphysics systems characterized by multiple physical phenomena that span a large range of length- and time-scales. Specifically, the project was focused on computational estimation of numerical error and sensitivity analysis of computational solutions with respect to variations in parameters and data. In addition, the project investigated the use of accurate computational estimates to guide efficient adaptive discretization. The project developed, analyzed and evaluated new variational adjoint-based techniques for integration, model, and data error estimation/control and sensitivity analysis, in evolutionary multiphysics multiscale simulations.

A novel Bayesian approach to accounting for uncertainty in fMRI-derived estimates of cerebral oxygen metabolism fluctuations

PubMed Central

Simon, Aaron B.; Dubowitz, David J.; Blockley, Nicholas P.; Buxton, Richard B.

2016-01-01

Calibrated blood oxygenation level dependent (BOLD) imaging is a multimodal functional MRI technique designed to estimate changes in cerebral oxygen metabolism from measured changes in cerebral blood flow and the BOLD signal. This technique addresses fundamental ambiguities associated with quantitative BOLD signal analysis; however, its dependence on biophysical modeling creates uncertainty in the resulting oxygen metabolism estimates. In this work, we developed a Bayesian approach to estimating the oxygen metabolism response to a neural stimulus and used it to examine the uncertainty that arises in calibrated BOLD estimation due to the presence of unmeasured model parameters. We applied our approach to estimate the CMRO2 response to a visual task using the traditional hypercapnia calibration experiment as well as to estimate the metabolic response to both a visual task and hypercapnia using the measurement of baseline apparent R2′ as a calibration technique. Further, in order to examine the effects of cerebral spinal fluid (CSF) signal contamination on the measurement of apparent R2′, we examined the effects of measuring this parameter with and without CSF-nulling. We found that the two calibration techniques provided consistent estimates of the metabolic response on average, with a median R2′-based estimate of the metabolic response to CO2 of 1.4%, and R2′- and hypercapnia-calibrated estimates of the visual response of 27% and 24%, respectively. However, these estimates were sensitive to different sources of estimation uncertainty. The R2′-calibrated estimate was highly sensitive to CSF contamination and to uncertainty in unmeasured model parameters describing flow-volume coupling, capillary bed characteristics, and the iso-susceptibility saturation of blood. The hypercapnia-calibrated estimate was relatively insensitive to these parameters but highly sensitive to the assumed metabolic response to CO2. PMID:26790354

A novel Bayesian approach to accounting for uncertainty in fMRI-derived estimates of cerebral oxygen metabolism fluctuations.

PubMed

Simon, Aaron B; Dubowitz, David J; Blockley, Nicholas P; Buxton, Richard B

2016-04-01

Calibrated blood oxygenation level dependent (BOLD) imaging is a multimodal functional MRI technique designed to estimate changes in cerebral oxygen metabolism from measured changes in cerebral blood flow and the BOLD signal. This technique addresses fundamental ambiguities associated with quantitative BOLD signal analysis; however, its dependence on biophysical modeling creates uncertainty in the resulting oxygen metabolism estimates. In this work, we developed a Bayesian approach to estimating the oxygen metabolism response to a neural stimulus and used it to examine the uncertainty that arises in calibrated BOLD estimation due to the presence of unmeasured model parameters. We applied our approach to estimate the CMRO2 response to a visual task using the traditional hypercapnia calibration experiment as well as to estimate the metabolic response to both a visual task and hypercapnia using the measurement of baseline apparent R2' as a calibration technique. Further, in order to examine the effects of cerebral spinal fluid (CSF) signal contamination on the measurement of apparent R2', we examined the effects of measuring this parameter with and without CSF-nulling. We found that the two calibration techniques provided consistent estimates of the metabolic response on average, with a median R2'-based estimate of the metabolic response to CO2 of 1.4%, and R2'- and hypercapnia-calibrated estimates of the visual response of 27% and 24%, respectively. However, these estimates were sensitive to different sources of estimation uncertainty. The R2'-calibrated estimate was highly sensitive to CSF contamination and to uncertainty in unmeasured model parameters describing flow-volume coupling, capillary bed characteristics, and the iso-susceptibility saturation of blood. The hypercapnia-calibrated estimate was relatively insensitive to these parameters but highly sensitive to the assumed metabolic response to CO2. Copyright © 2016 Elsevier Inc. All rights reserved.

Sensitivity of Beam Parameters to a Station C Solenoid Scan on Axis II

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

Schulze, Martin E.

Magnet scans are a standard technique for determining beam parameters in accelerators. Beam parameters are inferred from spot size measurements using a model of the beam optics. The sensitivity of the measured beam spot size to the beam parameters is investigated for typical DARHT Axis II beam energies and currents. In a typical S4 solenoid scan, the downstream transport is tuned to achieve a round beam at Station C with an envelope radius of about 1.5 cm with a very small divergence with S4 off. The typical beam energy and current are 16.0 MeV and 1.625 kA. Figures 1-3 showmore » the sensitivity of the bean size at Station C to the emittance, initial radius and initial angle respectively. To better understand the relative sensitivity of the beam size to the emittance, initial radius and initial angle, linear regressions were performed for each parameter as a function of the S4 setting. The results are shown in Figure 4. The measured slope was scaled to have a maximum value of 1 in order to present the relative sensitivities in a single plot. Figure 4 clearly shows the beam size at the minimum of the S4 scan is most sensitive to emittance and relatively insensitive to initial radius and angle as expected. The beam emittance is also very sensitive to the beam size of the converging beam and becomes insensitive to the beam size of the diverging beam. Measurements of the beam size of the diverging beam provide the greatest sensitivity to the initial beam radius and to a lesser extent the initial beam angle. The converging beam size is initially very sensitive to the emittance and initial angle at low S4 currents. As the S4 current is increased the sensitivity to the emittance remains strong while the sensitivity to the initial angle diminishes.« less

A High-Sensitivity Potentiometric 65-nm CMOS ISFET Sensor for Rapid E. coli Screening.

PubMed

Jiang, Yu; Liu, Xu; Dang, Tran Chien; Huang, Xiwei; Feng, Hao; Zhang, Qing; Yu, Hao

2018-04-01

Foodborne bacteria, inducing outbreaks of infection or poisoning, have posed great threats to food safety. Potentiometric sensors can identify bacteria levels in food by measuring medium's pH changes. However, most of these sensors face the limitation of low sensitivity and high cost. In this paper, we developed a high-sensitivity ion-sensitive field-effect transistor sensor. It is small sized, cost-efficient, and can be massively fabricated in a standard 65-nm complementary metal-oxide-semiconductor process. A subthreshold pH-to-time-to-voltage conversion scheme was proposed to improve the sensitivity. Furthermore, design parameters, such as chemical sensing area, transistor size, and discharging time, were optimized to enhance the performance. The intrinsic sensitivity of passivation membrane was calculated as 33.2 mV/pH. It was amplified to 123.8 mV/pH with a 0.01-pH resolution, which greatly exceeded 6.3 mV/pH observed in a traditional source-follower based readout structure. The sensing system was applied to Escherichia coli (E. coli) detection with densities ranging from 14 to 140 cfu/mL. Compared to the conventional direct plate counting method (24 h), more efficient sixfold smaller screening time (4 h) was achieved to differentiate samples' E. coli levels. The demonstrated portable, time-saving, and low-cost prescreen system has great potential for food safety detection.

Multi-modal approach using Raman spectroscopy and optical coherence tomography for the discrimination of colonic adenocarcinoma from normal colon

PubMed Central

Ashok, Praveen C.; Praveen, Bavishna B.; Bellini, Nicola; Riches, Andrew; Dholakia, Kishan; Herrington, C. Simon

2013-01-01

We report a multimodal optical approach using both Raman spectroscopy and optical coherence tomography (OCT) in tandem to discriminate between colonic adenocarcinoma and normal colon. Although both of these non-invasive techniques are capable of discriminating between normal and tumour tissues, they are unable individually to provide both the high specificity and high sensitivity required for disease diagnosis. We combine the chemical information derived from Raman spectroscopy with the texture parameters extracted from OCT images. The sensitivity obtained using Raman spectroscopy and OCT individually was 89% and 78% respectively and the specificity was 77% and 74% respectively. Combining the information derived using the two techniques increased both sensitivity and specificity to 94% demonstrating that combining complementary optical information enhances diagnostic accuracy. These data demonstrate that multimodal optical analysis has the potential to achieve accurate non-invasive cancer diagnosis. PMID:24156073

Adiposity as a full mediator of the influence of cardiorespiratory fitness and inflammation in schoolchildren: The FUPRECOL Study.

PubMed

Garcia-Hermoso, A; Agostinis-Sobrinho, C; Mota, J; Santos, R M; Correa-Bautista, J E; Ramírez-Vélez, R

2017-06-01

Studies in the paediatric population have shown inconsistent associations between cardiorespiratory fitness and inflammation independently of adiposity. The purpose of this study was (i) to analyse the combined association of cardiorespiratory fitness and adiposity with high-sensitivity C-reactive protein (hs-CRP), and (ii) to determine whether adiposity acts as a mediator on the association between cardiorespiratory fitness and hs-CRP in children and adolescents. This cross-sectional study included 935 (54.7% girls) healthy children and adolescents from Bogotá, Colombia. The 20 m shuttle run test was used to estimate cardiorespiratory fitness. We assessed the following adiposity parameters: body mass index, waist circumference, and fat mass index and the sum of subscapular and triceps skinfold thickness. High sensitivity assays were used to obtain hs-CRP. Linear regression models were fitted for mediation analyses examined whether the association between cardiorespiratory fitness and hs-CRP was mediated by each of adiposity parameters according to Baron and Kenny procedures. Lower levels of hs-CRP were associated with the best schoolchildren profiles (high cardiorespiratory fitness + low adiposity) (p for trend <0.001 in the four adiposity parameters), compared with unfit and overweight (low cardiorespiratory fitness + high adiposity) counterparts. Linear regression models suggest a full mediation of adiposity on the association between cardiorespiratory fitness and hs-CRP levels. Our findings seem to emphasize the importance of obesity prevention in childhood, suggesting that having high levels of cardiorespiratory fitness may not counteract the negative consequences ascribed to adiposity on hs-CRP. Copyright © 2017 The Italian Society of Diabetology, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition, and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved.

Nonlinear mathematical modeling and sensitivity analysis of hydraulic drive unit

NASA Astrophysics Data System (ADS)

Kong, Xiangdong; Yu, Bin; Quan, Lingxiao; Ba, Kaixian; Wu, Liujie

2015-09-01

The previous sensitivity analysis researches are not accurate enough and also have the limited reference value, because those mathematical models are relatively simple and the change of the load and the initial displacement changes of the piston are ignored, even experiment verification is not conducted. Therefore, in view of deficiencies above, a nonlinear mathematical model is established in this paper, including dynamic characteristics of servo valve, nonlinear characteristics of pressure-flow, initial displacement of servo cylinder piston and friction nonlinearity. The transfer function block diagram is built for the hydraulic drive unit closed loop position control, as well as the state equations. Through deriving the time-varying coefficient items matrix and time-varying free items matrix of sensitivity equations respectively, the expression of sensitivity equations based on the nonlinear mathematical model are obtained. According to structure parameters of hydraulic drive unit, working parameters, fluid transmission characteristics and measured friction-velocity curves, the simulation analysis of hydraulic drive unit is completed on the MATLAB/Simulink simulation platform with the displacement step 2 mm, 5 mm and 10 mm, respectively. The simulation results indicate that the developed nonlinear mathematical model is sufficient by comparing the characteristic curves of experimental step response and simulation step response under different constant load. Then, the sensitivity function time-history curves of seventeen parameters are obtained, basing on each state vector time-history curve of step response characteristic. The maximum value of displacement variation percentage and the sum of displacement variation absolute values in the sampling time are both taken as sensitivity indexes. The sensitivity indexes values above are calculated and shown visually in histograms under different working conditions, and change rules are analyzed. Then the sensitivity indexes values of four measurable parameters, such as supply pressure, proportional gain, initial position of servo cylinder piston and load force, are verified experimentally on test platform of hydraulic drive unit, and the experimental research shows that the sensitivity analysis results obtained through simulation are approximate to the test results. This research indicates each parameter sensitivity characteristics of hydraulic drive unit, the performance-affected main parameters and secondary parameters are got under different working conditions, which will provide the theoretical foundation for the control compensation and structure optimization of hydraulic drive unit.

Rapid Airplane Parametric Input Design (RAPID)

NASA Technical Reports Server (NTRS)

Smith, Robert E.

1995-01-01

RAPID is a methodology and software system to define a class of airplane configurations and directly evaluate surface grids, volume grids, and grid sensitivity on and about the configurations. A distinguishing characteristic which separates RAPID from other airplane surface modellers is that the output grids and grid sensitivity are directly applicable in CFD analysis. A small set of design parameters and grid control parameters govern the process which is incorporated into interactive software for 'real time' visual analysis and into batch software for the application of optimization technology. The computed surface grids and volume grids are suitable for a wide range of Computational Fluid Dynamics (CFD) simulation. The general airplane configuration has wing, fuselage, horizontal tail, and vertical tail components. The double-delta wing and tail components are manifested by solving a fourth order partial differential equation (PDE) subject to Dirichlet and Neumann boundary conditions. The design parameters are incorporated into the boundary conditions and therefore govern the shapes of the surfaces. The PDE solution yields a smooth transition between boundaries. Surface grids suitable for CFD calculation are created by establishing an H-type topology about the configuration and incorporating grid spacing functions in the PDE equation for the lifting components and the fuselage definition equations. User specified grid parameters govern the location and degree of grid concentration. A two-block volume grid about a configuration is calculated using the Control Point Form (CPF) technique. The interactive software, which runs on Silicon Graphics IRIS workstations, allows design parameters to be continuously varied and the resulting surface grid to be observed in real time. The batch software computes both the surface and volume grids and also computes the sensitivity of the output grid with respect to the input design parameters by applying the precompiler tool ADIFOR to the grid generation program. The output of ADIFOR is a new source code containing the old code plus expressions for derivatives of specified dependent variables (grid coordinates) with respect to specified independent variables (design parameters). The RAPID methodology and software provide a means of rapidly defining numerical prototypes, grids, and grid sensitivity of a class of airplane configurations. This technology and software is highly useful for CFD research for preliminary design and optimization processes.

Close-packed Arrays of Transition-edge X-ray Microcalorimeters with High Spectral Resolution at 5.9 keV

NASA Technical Reports Server (NTRS)

Iyomoto, N.; Bandler, S. R.; Brekosky, R. P.; Brown, A.-D.; Chervenak, J. A.; Finkbeiner, F. M.; Kelley, R. L.; Kilbourne, C. A.; Porter, F. S.; Sadleir, J. E.;

A novel approach to Hough Transform for implementation in fast triggers

NASA Astrophysics Data System (ADS)

Pozzobon, Nicola; Montecassiano, Fabio; Zotto, Pierluigi

2016-10-01

Telescopes of position sensitive detectors are common layouts in charged particles tracking, and programmable logic devices, such as FPGAs, represent a viable choice for the real-time reconstruction of track segments in such detector arrays. A compact implementation of the Hough Transform for fast triggers in High Energy Physics, exploiting a parameter reduction method, is proposed, targeting the reduction of the needed storage or computing resources in current, or next future, state-of-the-art FPGA devices, while retaining high resolution over a wide range of track parameters. The proposed approach is compared to a Standard Hough Transform with particular emphasis on their application to muon detectors. In both cases, an original readout implementation is modeled.

An automatic and effective parameter optimization method for model tuning

NASA Astrophysics Data System (ADS)

Zhang, T.; Li, L.; Lin, Y.; Xue, W.; Xie, F.; Xu, H.; Huang, X.

2015-11-01

Physical parameterizations in general circulation models (GCMs), having various uncertain parameters, greatly impact model performance and model climate sensitivity. Traditional manual and empirical tuning of these parameters is time-consuming and ineffective. In this study, a "three-step" methodology is proposed to automatically and effectively obtain the optimum combination of some key parameters in cloud and convective parameterizations according to a comprehensive objective evaluation metrics. Different from the traditional optimization methods, two extra steps, one determining the model's sensitivity to the parameters and the other choosing the optimum initial value for those sensitive parameters, are introduced before the downhill simplex method. This new method reduces the number of parameters to be tuned and accelerates the convergence of the downhill simplex method. Atmospheric GCM simulation results show that the optimum combination of these parameters determined using this method is able to improve the model's overall performance by 9 %. The proposed methodology and software framework can be easily applied to other GCMs to speed up the model development process, especially regarding unavoidable comprehensive parameter tuning during the model development stage.

Information sensitivity functions to assess parameter information gain and identifiability of dynamical systems.

PubMed

Pant, Sanjay

2018-05-01

A new class of functions, called the 'information sensitivity functions' (ISFs), which quantify the information gain about the parameters through the measurements/observables of a dynamical system are presented. These functions can be easily computed through classical sensitivity functions alone and are based on Bayesian and information-theoretic approaches. While marginal information gain is quantified by decrease in differential entropy, correlations between arbitrary sets of parameters are assessed through mutual information. For individual parameters, these information gains are also presented as marginal posterior variances, and, to assess the effect of correlations, as conditional variances when other parameters are given. The easy to interpret ISFs can be used to (a) identify time intervals or regions in dynamical system behaviour where information about the parameters is concentrated; (b) assess the effect of measurement noise on the information gain for the parameters; (c) assess whether sufficient information in an experimental protocol (input, measurements and their frequency) is available to identify the parameters; (d) assess correlation in the posterior distribution of the parameters to identify the sets of parameters that are likely to be indistinguishable; and (e) assess identifiability problems for particular sets of parameters. © 2018 The Authors.

Sensitivity analysis of TRX-2 lattice parameters with emphasis on epithermal /sup 238/U capture. Final report

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

Tomlinson, E.T.; deSaussure, G.; Weisbin, C.R.

1977-03-01

The main purpose of the study is the determination of the sensitivity of TRX-2 thermal lattice performance parameters to nuclear cross section data, particularly the epithermal resonance capture cross section of /sup 238/U. An energy-dependent sensitivity profile was generated for each of the performance parameters, to the most important cross sections of the various isotopes in the lattice. Uncertainties in the calculated values of the performance parameters due to estimated uncertainties in the basic nuclear data, deduced in this study, were shown to be small compared to the uncertainties in the measured values of the performance parameter and compared tomore » differences among calculations based upon the same data but with different methodologies.« less

Highly sensitive and quantitative detection of rare pathogens through agarose droplet microfluidic emulsion PCR at the single-cell level.

PubMed

Zhu, Zhi; Zhang, Wenhua; Leng, Xuefei; Zhang, Mingxia; Guan, Zhichao; Lu, Jiangquan; Yang, Chaoyong James

2012-10-21

Genetic alternations can serve as highly specific biomarkers to distinguish fatal bacteria or cancer cells from their normal counterparts. However, these mutations normally exist in very rare amount in the presence of a large excess of non-mutated analogs. Taking the notorious pathogen E. coli O157:H7 as the target analyte, we have developed an agarose droplet-based microfluidic ePCR method for highly sensitive, specific and quantitative detection of rare pathogens in the high background of normal bacteria. Massively parallel singleplex and multiplex PCR at the single-cell level in agarose droplets have been successfully established. Moreover, we challenged the system with rare pathogen detection and realized the sensitive and quantitative analysis of a single E. coli O157:H7 cell in the high background of 100,000 excess normal K12 cells. For the first time, we demonstrated rare pathogen detection through agarose droplet microfluidic ePCR. Such a multiplex single-cell agarose droplet amplification method enables ultra-high throughput and multi-parameter genetic analysis of large population of cells at the single-cell level to uncover the stochastic variations in biological systems.

Study of plasma parameters in a pulsed plasma accelerator using triple Langmuir probe

NASA Astrophysics Data System (ADS)

Borthakur, S.; Talukdar, N.; Neog, N. K.; Borthakur, T. K.

2018-01-01

A Triple Langmuir Probe (TLP) has been used to study plasma parameters of a transient plasma produced in a newly developed Pulsed Plasma Accelerator system. In this experiment, a TLP with a capacitor based current mode biasing circuit was used that instantaneously gives voltage traces in an oscilloscope which are directly proportional to the plasma electron temperature and density. The electron temperature (Te) and plasma density (ne) of the plasma are measured with the help of this probe and found to be 24.13 eV and 3.34 × 1021/m3 at the maximum energy (-15 kV) of the system, respectively. An attempt was also made to analyse the time-dependent fluctuations in plasma parameters detected by the highly sensitive triple probe. In addition to this, the variation of these parameters under different discharge voltages was studied. The information obtained from these parameters is the initial diagnostics of a new device which is to be dedicated to study the impact of high heat flux plasma stream upon material surfaces inside an ITER like tokamak.

Design of nanostructured-based glucose biosensors

NASA Astrophysics Data System (ADS)

Komirisetty, Archana; Williams, Frances; Pradhan, Aswini; Konda, Rajini B.; Dondapati, Hareesh; Samantaray, Diptirani

2012-04-01

This paper presents the design of glucose sensors that will be integrated with advanced nano-materials, bio-coatings and electronics to create novel devices that are highly sensitive, inexpensive, accurate, and reliable. In the work presented, a glucose biosensor and its fabrication process flow have been designed. The device is based on electrochemical sensing using a working electrode with bio-functionalized zinc oxide (ZnO) nano-rods. Among all metal oxide nanostructures, ZnO nano-materials play a significant role as a sensing element in biosensors due to their properties such as high isoelectric point (IEP), fast electron transfer, non-toxicity, biocompatibility, and chemical stability which are very crucial parameters to achieve high sensitivity. Amperometric enzyme electrodes based on glucose oxidase (GOx) are used due to their stability and high selectivity to glucose. The device also consists of silicon dioxide and titanium layers as well as platinum working and counter electrodes and a silver/silver chloride reference electrode. Currently, the biosensors are being fabricated using the process flow developed. Once completed, the sensors will be bio-functionalized and tested to characterize their performance, including their sensitivity and stability.

BSA-coated nanoparticles for improved SERS-based intracellular pH sensing.

PubMed

Zheng, Xiao-Shan; Hu, Pei; Cui, Yan; Zong, Cheng; Feng, Jia-Min; Wang, Xin; Ren, Bin

2014-12-16

Local microenvironment pH sensing is one of the key parameters for the understanding of many biological processes. As a noninvasive and high sensitive technique, surface-enhanced Raman spectroscopy (SERS) has attracted considerable interest in the detection of the local pH of live cells. We herein develop a facile way to prepare Au-(4-MPy)-BSA (AMB) pH nanosensor. The 4-MPy (4-mercaptopyridine) was used as the pH sensing molecule. The modification of the nanoparticles with BSA not only provides a high sensitive response to pH changes ranging from pH 4.0 to 9.0 but also exhibits a high sensitivity and good biocompatibility, stability, and reliability in various solutions (including the solutions of high ionic strength or with complex composition such as the cell culture medium), both in the aggregation state or after long-term storage. The AMB pH nanosensor shows great advantages for reliable intracellular pH analysis and has been successfully used to monitor the pH distribution of live cells and can address the grand challenges in SERS-based pH sensing for practical biological applications.

Effect of Temperature and Dynamic Loading on the Mechanical Properties of Copper-Alloyed High-Strength Interstitial-Free Steel

NASA Astrophysics Data System (ADS)

Rana, R.; Singh, S. B.; Bleck, W.; Mohanty, O. N.

2009-04-01

Crash resistance and formability relevant mechanical properties of a copper-alloyed interstitial-free (IF) steel processed under various conditions of batch annealing (BA), continuous annealing (CA), and postcontinuous annealing aging have been studied in a wide range of strain rate (3.33 × 10-4 to 200 s-1) and temperature (-100 °C to +20 °C). These properties have been compared with similarly processed traditional mild and high-strength IF steels. Assessment of various parameters such as strength, elongation, strain rate sensitivity of stress, strain-hardening capacity, temperature sensitivity of stress, activation volume, and specific energy absorption of all these steels implies that copper-alloyed IF steel is soft and formable in CA condition. It can be made stronger and more crash resistant than the conventional mild- or high-strength IF steels when aged to peak strength after CA. Room-temperature strain rate sensitivity of stress of the investigated steels exhibits a two-stage behavior. Copper in solution in ferrite causes solid solution softening at low temperatures (≤20 °C) and at high strain rates (200 s-1).

Nerium oleander indirect leaf photosynthesis and light harvesting reductions after clipping injury or Spodoptera eridania herbivory: High sensitivity to injury

USDA-ARS?s Scientific Manuscript database

Variable indirect photosynthetic rate (Pn) responses occur on injured leaves after insect herbivory. It is important to understand factors that influence indirect Pn reductions after injury. The current study examines the relationship between gas exchange and chlorophyll a fluorescence parameters wi...

Sensitivity of bandpass filters using recirculating delay-line structures

NASA Astrophysics Data System (ADS)

Heyde, Eric C.

1996-12-01

Recirculating delay lines have value notably as sensors and optical signal processors. Most useful applications depend on a high-finesse response from a network. A proof that, with given response parameters, more complex systems can produce behavior that is more stable to the effects of nonidealities than a single recirculating loop is presented.

Application of design sensitivity analysis for greater improvement on machine structural dynamics

NASA Technical Reports Server (NTRS)

Yoshimura, Masataka

1987-01-01

Methodologies are presented for greatly improving machine structural dynamics by using design sensitivity analyses and evaluative parameters. First, design sensitivity coefficients and evaluative parameters of structural dynamics are described. Next, the relations between the design sensitivity coefficients and the evaluative parameters are clarified. Then, design improvement procedures of structural dynamics are proposed for the following three cases: (1) addition of elastic structural members, (2) addition of mass elements, and (3) substantial charges of joint design variables. Cases (1) and (2) correspond to the changes of the initial framework or configuration, and (3) corresponds to the alteration of poor initial design variables. Finally, numerical examples are given for demonstrating the availability of the methods proposed.

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

PubMed

Xu, Li; Jiang, Yong; Qiu, Rong

2018-01-01

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