Estimation of regression laws for ground motion parameters using as case of study the Amatrice earthquake

NASA Astrophysics Data System (ADS)

Tiberi, Lara; Costa, Giovanni

2017-04-01

The possibility to directly associate the damages to the ground motion parameters is always a great challenge, in particular for civil protections. Indeed a ground motion parameter, estimated in near real time that can express the damages occurred after an earthquake, is fundamental to arrange the first assistance after an event. The aim of this work is to contribute to the estimation of the ground motion parameter that better describes the observed intensity, immediately after an event. This can be done calculating for each ground motion parameter estimated in a near real time mode a regression law which correlates the above-mentioned parameter to the observed macro-seismic intensity. This estimation is done collecting high quality accelerometric data in near field, filtering them at different frequency steps. The regression laws are calculated using two different techniques: the non linear least-squares (NLLS) Marquardt-Levenberg algorithm and the orthogonal distance methodology (ODR). The limits of the first methodology are the needed of initial values for the parameters a and b (set 1.0 in this study), and the constraint that the independent variable must be known with greater accuracy than the dependent variable. While the second algorithm is based on the estimation of the errors perpendicular to the line, rather than just vertically. The vertical errors are just the errors in the 'y' direction, so only for the dependent variable whereas the perpendicular errors take into account errors for both the variables, the dependent and the independent. This makes possible also to directly invert the relation, so the a and b values can be used also to express the gmps as function of I. For each law the standard deviation and R2 value are estimated in order to test the quality and the reliability of the found relation. The Amatrice earthquake of 24th August of 2016 is used as case of study to test the goodness of the calculated regression laws.

CALCULATION OF NONLINEAR CONFIDENCE AND PREDICTION INTERVALS FOR GROUND-WATER FLOW MODELS.

USGS Publications Warehouse

Cooley, Richard L.; Vecchia, Aldo V.

1987-01-01

A method is derived to efficiently compute nonlinear confidence and prediction intervals on any function of parameters derived as output from a mathematical model of a physical system. The method is applied to the problem of obtaining confidence and prediction intervals for manually-calibrated ground-water flow models. To obtain confidence and prediction intervals resulting from uncertainties in parameters, the calibrated model and information on extreme ranges and ordering of the model parameters within one or more independent groups are required. If random errors in the dependent variable are present in addition to uncertainties in parameters, then calculation of prediction intervals also requires information on the extreme range of error expected. A simple Monte Carlo method is used to compute the quantiles necessary to establish probability levels for the confidence and prediction intervals. Application of the method to a hypothetical example showed that inclusion of random errors in the dependent variable in addition to uncertainties in parameters can considerably widen the prediction intervals.

Impact of the calibration period on the conceptual rainfall-runoff model parameter estimates

NASA Astrophysics Data System (ADS)

Todorovic, Andrijana; Plavsic, Jasna

2015-04-01

A conceptual rainfall-runoff model is defined by its structure and parameters, which are commonly inferred through model calibration. Parameter estimates depend on objective function(s), optimisation method, and calibration period. Model calibration over different periods may result in dissimilar parameter estimates, while model efficiency decreases outside calibration period. Problem of model (parameter) transferability, which conditions reliability of hydrologic simulations, has been investigated for decades. In this paper, dependence of the parameter estimates and model performance on calibration period is analysed. The main question that is addressed is: are there any changes in optimised parameters and model efficiency that can be linked to the changes in hydrologic or meteorological variables (flow, precipitation and temperature)? Conceptual, semi-distributed HBV-light model is calibrated over five-year periods shifted by a year (sliding time windows). Length of the calibration periods is selected to enable identification of all parameters. One water year of model warm-up precedes every simulation, which starts with the beginning of a water year. The model is calibrated using the built-in GAP optimisation algorithm. The objective function used for calibration is composed of Nash-Sutcliffe coefficient for flows and logarithms of flows, and volumetric error, all of which participate in the composite objective function with approximately equal weights. Same prior parameter ranges are used in all simulations. The model is calibrated against flows observed at the Slovac stream gauge on the Kolubara River in Serbia (records from 1954 to 2013). There are no trends in precipitation nor in flows, however, there is a statistically significant increasing trend in temperatures at this catchment. Parameter variability across the calibration periods is quantified in terms of standard deviations of normalised parameters, enabling detection of the most variable parameters. Correlation coefficients among optimised model parameters and total precipitation P, mean temperature T and mean flow Q are calculated to give an insight into parameter dependence on the hydrometeorological drivers. The results reveal high sensitivity of almost all model parameters towards calibration period. The highest variability is displayed by the refreezing coefficient, water holding capacity, and temperature gradient. The only statistically significant (decreasing) trend is detected in the evapotranspiration reduction threshold. Statistically significant correlation is detected between the precipitation gradient and precipitation depth, and between the time-area histogram base and flows. All other correlations are not statistically significant, implying that changes in optimised parameters cannot generally be linked to the changes in P, T or Q. As for the model performance, the model reproduces the observed runoff satisfactorily, though the runoff is slightly overestimated in wet periods. The Nash-Sutcliffe efficiency coefficient (NSE) ranges from 0.44 to 0.79. Higher NSE values are obtained over wetter periods, what is supported by statistically significant correlation between NSE and flows. Overall, no systematic variations in parameters or in model performance are detected. Parameter variability may therefore rather be attributed to errors in data or inadequacies in the model structure. Further research is required to examine the impact of the calibration strategy or model structure on the variability in optimised parameters in time.

Bayesian Techniques for Comparing Time-dependent GRMHD Simulations to Variable Event Horizon Telescope Observations

NASA Astrophysics Data System (ADS)

Kim, Junhan; Marrone, Daniel P.; Chan, Chi-Kwan; Medeiros, Lia; Özel, Feryal; Psaltis, Dimitrios

2016-12-01

The Event Horizon Telescope (EHT) is a millimeter-wavelength, very-long-baseline interferometry (VLBI) experiment that is capable of observing black holes with horizon-scale resolution. Early observations have revealed variable horizon-scale emission in the Galactic Center black hole, Sagittarius A* (Sgr A*). Comparing such observations to time-dependent general relativistic magnetohydrodynamic (GRMHD) simulations requires statistical tools that explicitly consider the variability in both the data and the models. We develop here a Bayesian method to compare time-resolved simulation images to variable VLBI data, in order to infer model parameters and perform model comparisons. We use mock EHT data based on GRMHD simulations to explore the robustness of this Bayesian method and contrast it to approaches that do not consider the effects of variability. We find that time-independent models lead to offset values of the inferred parameters with artificially reduced uncertainties. Moreover, neglecting the variability in the data and the models often leads to erroneous model selections. We finally apply our method to the early EHT data on Sgr A*.

BAYESIAN TECHNIQUES FOR COMPARING TIME-DEPENDENT GRMHD SIMULATIONS TO VARIABLE EVENT HORIZON TELESCOPE OBSERVATIONS

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

Kim, Junhan; Marrone, Daniel P.; Chan, Chi-Kwan

2016-12-01

The Event Horizon Telescope (EHT) is a millimeter-wavelength, very-long-baseline interferometry (VLBI) experiment that is capable of observing black holes with horizon-scale resolution. Early observations have revealed variable horizon-scale emission in the Galactic Center black hole, Sagittarius A* (Sgr A*). Comparing such observations to time-dependent general relativistic magnetohydrodynamic (GRMHD) simulations requires statistical tools that explicitly consider the variability in both the data and the models. We develop here a Bayesian method to compare time-resolved simulation images to variable VLBI data, in order to infer model parameters and perform model comparisons. We use mock EHT data based on GRMHD simulations to explore themore » robustness of this Bayesian method and contrast it to approaches that do not consider the effects of variability. We find that time-independent models lead to offset values of the inferred parameters with artificially reduced uncertainties. Moreover, neglecting the variability in the data and the models often leads to erroneous model selections. We finally apply our method to the early EHT data on Sgr A*.« less

Exact Scheffé-type confidence intervals for output from groundwater flow models: 2. Combined use of hydrogeologic information and calibration data

USGS Publications Warehouse

Cooley, Richard L.

1993-01-01

Calibration data (observed values corresponding to model-computed values of dependent variables) are incorporated into a general method of computing exact Scheffé-type confidence intervals analogous to the confidence intervals developed in part 1 (Cooley, this issue) for a function of parameters derived from a groundwater flow model. Parameter uncertainty is specified by a distribution of parameters conditioned on the calibration data. This distribution was obtained as a posterior distribution by applying Bayes' theorem to the hydrogeologically derived prior distribution of parameters from part 1 and a distribution of differences between the calibration data and corresponding model-computed dependent variables. Tests show that the new confidence intervals can be much smaller than the intervals of part 1 because the prior parameter variance-covariance structure is altered so that combinations of parameters that give poor model fit to the data are unlikely. The confidence intervals of part 1 and the new confidence intervals can be effectively employed in a sequential method of model construction whereby new information is used to reduce confidence interval widths at each stage.

Relationship among several measurements of slipperiness obtained in a laboratory environment.

PubMed

Chang, Wen-Ruey; Chang, Chien-Chi

2018-04-01

Multiple sensing mechanisms could be used in forming responses to avoid slips, but previous studies, correlating only two parameters, revealed a limited picture of this complex system. In this study, the participants walked as fast as possible without a slip under 15 conditions of different degrees of slipperiness. The relationships among various response parameters, including perceived slipperiness rating, utilized coefficient of friction (UCOF), slipmeter measurement and kinematic parameters, were evaluated. The results showed that the UCOF, perceived rating and heel angle had higher adjusted R 2 values as dependent variables in the multiple linear regressions with the remaining variables in the final pool as independent variables. Although each variable in the final data pool could reflect some measurement of slipperiness, these three variables are more inclusive than others in representing the other variables and were bigger predictors of other variables, so they could be better candidates for measurements of slipperiness. Copyright © 2017 Elsevier Ltd. All rights reserved.

Estimation of pharmacokinetic parameters from non-compartmental variables using Microsoft Excel.

PubMed

Dansirikul, Chantaratsamon; Choi, Malcolm; Duffull, Stephen B

2005-06-01

This study was conducted to develop a method, termed 'back analysis (BA)', for converting non-compartmental variables to compartment model dependent pharmacokinetic parameters for both one- and two-compartment models. A Microsoft Excel spreadsheet was implemented with the use of Solver and visual basic functions. The performance of the BA method in estimating pharmacokinetic parameter values was evaluated by comparing the parameter values obtained to a standard modelling software program, NONMEM, using simulated data. The results show that the BA method was reasonably precise and provided low bias in estimating fixed and random effect parameters for both one- and two-compartment models. The pharmacokinetic parameters estimated from the BA method were similar to those of NONMEM estimation.

Increased intra-individual reaction time variability in cocaine-dependent subjects: role of cocaine-related cues.

PubMed

Liu, Shijing; Lane, Scott D; Schmitz, Joy M; Green, Charles E; Cunningham, Kathryn A; Moeller, F Gerard

2012-02-01

Neuroimaging data suggest that impaired performance on response inhibition and information processing tests in cocaine-dependent subjects is related to prefrontal and frontal cortical dysfunction and that dysfunction in these brain areas may underlie some aspects of cocaine addiction. In subjects with attention-deficit hyperactivity disorder and other psychiatric disorders, the Intra-Individual Reaction Time Variability (IIRTV) has been associated with frontal cortical dysfunction. In the present study, we evaluated IIRTV parameters in cocaine-dependent subjects vs. controls using a cocaine Stroop task. Fifty control and 123 cocaine-dependent subjects compiled from three studies completed a cocaine Stroop task. Standard deviation (SD) and coefficient of variation (CV) for reaction times (RT) were calculated for both trials with neutral and trials with cocaine-related words. The parameters mu, sigma, and tau were calculated using an ex-Gaussian analysis employed to characterize variability in RTs. The ex-Gaussian analysis divides the RTs into normal (mu, sigma) and exponential (tau) components. Using robust regression analysis, cocaine-dependent subjects showed greater SD, CV and Tau on trials with cocaine-related words compared to controls (p<0.05). However, in trials with neutral words, there was no evidence of group differences in any IIRTV parameters (p>0.05). The Wilcoxon matched-pairs signed-rank test showed that for cocaine-dependent subjects, both SD and tau were larger in trials with cocaine-related words than in trials with neutral words (p<0.05). The observation that only cocaine-related words increased IIRTV in cocaine-dependent subjects suggests that cocaine-related stimuli might disrupt information processing subserved by prefrontal and frontal cortical circuits. Copyright © 2011 Elsevier Ltd. All rights reserved.

On the relationship between ecosystem-scale hyperspectral reflectance and CO2 exchange in European mountain grasslands

NASA Astrophysics Data System (ADS)

Balzarolo, M.; Vescovo, L.; Hammerle, A.; Gianelle, D.; Papale, D.; Tomelleri, E.; Wohlfahrt, G.

2015-05-01

In this paper we explore the skill of hyperspectral reflectance measurements and vegetation indices (VIs) derived from these in estimating carbon dioxide (CO2) fluxes of grasslands. Hyperspectral reflectance data, CO2 fluxes and biophysical parameters were measured at three grassland sites located in European mountain regions using standardized protocols. The relationships between CO2 fluxes, ecophysiological variables, traditional VIs and VIs derived using all two-band combinations of wavelengths available from the whole hyperspectral data space were analysed. We found that VIs derived from hyperspectral data generally explained a large fraction of the variability in the investigated dependent variables but differed in their ability to estimate midday and daily average CO2 fluxes and various derived ecophysiological parameters. Relationships between VIs and CO2 fluxes and ecophysiological parameters were site-specific, likely due to differences in soils, vegetation parameters and environmental conditions. Chlorophyll and water-content-related VIs explained the largest fraction of variability in most of the dependent variables. Band selection based on a combination of a genetic algorithm with random forests (GA-rF) confirmed that it is difficult to select a universal band region suitable across the investigated ecosystems. Our findings have major implications for upscaling terrestrial CO2 fluxes to larger regions and for remote- and proximal-sensing sampling and analysis strategies and call for more cross-site synthesis studies linking ground-based spectral reflectance with ecosystem-scale CO2 fluxes.

Can Dynamic Visualizations with Variable Control Enhance the Acquisition of Intuitive Knowledge?

ERIC Educational Resources Information Center

Wichmann, Astrid; Timpe, Sebastian

2015-01-01

An important feature of inquiry learning is to take part in science practices including exploring variables and testing hypotheses. Computer-based dynamic visualizations have the potential to open up various exploration possibilities depending on the level of learner control. It is assumed that variable control, e.g., by changing parameters of a…

SU-G-IeP4-13: PET Image Noise Variability and Its Consequences for Quantifying Tumor Hypoxia

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

Kueng, R; Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario; Manser, P

Purpose: The values in a PET image which represent activity concentrations of a radioactive tracer are influenced by a large number of parameters including patient conditions as well as image acquisition and reconstruction. This work investigates noise characteristics in PET images for various image acquisition and image reconstruction parameters. Methods: Different phantoms with homogeneous activity distributions were scanned using several acquisition parameters and reconstructed with numerous sets of reconstruction parameters. Images from six PET scanners from different vendors were analyzed and compared with respect to quantitative noise characteristics. Local noise metrics, which give rise to a threshold value defining themore » metric of hypoxic fraction, as well as global noise measures in terms of noise power spectra (NPS) were computed. In addition to variability due to different reconstruction parameters, spatial variability of activity distribution and its noise metrics were investigated. Patient data from clinical trials were mapped onto phantom scans to explore the impact of the scanner’s intrinsic noise variability on quantitative clinical analysis. Results: Local noise metrics showed substantial variability up to an order of magnitude for different reconstruction parameters. Investigations of corresponding NPS revealed reconstruction dependent structural noise characteristics. For the acquisition parameters, noise metrics were guided by Poisson statistics. Large spatial non-uniformity of the noise was observed in both axial and radial direction of a PET image. In addition, activity concentrations in PET images of homogeneous phantom scans showed intriguing spatial fluctuations for most scanners. The clinical metric of the hypoxic fraction was shown to be considerably influenced by the PET scanner’s spatial noise characteristics. Conclusion: We showed that a hypoxic fraction metric based on noise characteristics requires careful consideration of the various dependencies in order to justify its quantitative validity. This work may result in recommendations for harmonizing QA of PET imaging for multi-institutional clinical trials.« less

Density dependence in demography and dispersal generates fluctuating invasion speeds

PubMed Central

Li, Bingtuan; Miller, Tom E. X.

2017-01-01

Density dependence plays an important role in population regulation and is known to generate temporal fluctuations in population density. However, the ways in which density dependence affects spatial population processes, such as species invasions, are less understood. Although classical ecological theory suggests that invasions should advance at a constant speed, empirical work is illuminating the highly variable nature of biological invasions, which often exhibit nonconstant spreading speeds, even in simple, controlled settings. Here, we explore endogenous density dependence as a mechanism for inducing variability in biological invasions with a set of population models that incorporate density dependence in demographic and dispersal parameters. We show that density dependence in demography at low population densities—i.e., an Allee effect—combined with spatiotemporal variability in population density behind the invasion front can produce fluctuations in spreading speed. The density fluctuations behind the front can arise from either overcompensatory population growth or density-dependent dispersal, both of which are common in nature. Our results show that simple rules can generate complex spread dynamics and highlight a source of variability in biological invasions that may aid in ecological forecasting. PMID:28442569

Regression dilution in the proportional hazards model.

PubMed

Hughes, M D

1993-12-01

The problem of regression dilution arising from covariate measurement error is investigated for survival data using the proportional hazards model. The naive approach to parameter estimation is considered whereby observed covariate values are used, inappropriately, in the usual analysis instead of the underlying covariate values. A relationship between the estimated parameter in large samples and the true parameter is obtained showing that the bias does not depend on the form of the baseline hazard function when the errors are normally distributed. With high censorship, adjustment of the naive estimate by the factor 1 + lambda, where lambda is the ratio of within-person variability about an underlying mean level to the variability of these levels in the population sampled, removes the bias. As censorship increases, the adjustment required increases and when there is no censorship is markedly higher than 1 + lambda and depends also on the true risk relationship.

Controls on the variability of net infiltration to desert sandstone

USGS Publications Warehouse

Heilweil, Victor M.; McKinney, Tim S.; Zhdanov, Michael S.; Watt, Dennis E.

2007-01-01

As populations grow in arid climates and desert bedrock aquifers are increasingly targeted for future development, understanding and quantifying the spatial variability of net infiltration becomes critically important for accurately inventorying water resources and mapping contamination vulnerability. This paper presents a conceptual model of net infiltration to desert sandstone and then develops an empirical equation for its spatial quantification at the watershed scale using linear least squares inversion methods for evaluating controlling parameters (independent variables) based on estimated net infiltration rates (dependent variables). Net infiltration rates used for this regression analysis were calculated from environmental tracers in boreholes and more than 3000 linear meters of vadose zone excavations in an upland basin in southwestern Utah underlain by Navajo sandstone. Soil coarseness, distance to upgradient outcrop, and topographic slope were shown to be the primary physical parameters controlling the spatial variability of net infiltration. Although the method should be transferable to other desert sandstone settings for determining the relative spatial distribution of net infiltration, further study is needed to evaluate the effects of other potential parameters such as slope aspect, outcrop parameters, and climate on absolute net infiltration rates.

Cluster-enriched Yang-Baxter equation from SUSY gauge theories

NASA Astrophysics Data System (ADS)

Yamazaki, Masahito

2018-04-01

We propose a new generalization of the Yang-Baxter equation, where the R-matrix depends on cluster y-variables in addition to the spectral parameters. We point out that we can construct solutions to this new equation from the recently found correspondence between Yang-Baxter equations and supersymmetric gauge theories. The S^2 partition function of a certain 2d N=(2,2) quiver gauge theory gives an R-matrix, whereas its FI parameters can be identified with the cluster y-variables.

The Routine Fitting of Kinetic Data to Models

PubMed Central

Berman, Mones; Shahn, Ezra; Weiss, Marjory F.

1962-01-01

A mathematical formalism is presented for use with digital computers to permit the routine fitting of data to physical and mathematical models. Given a set of data, the mathematical equations describing a model, initial conditions for an experiment, and initial estimates for the values of model parameters, the computer program automatically proceeds to obtain a least squares fit of the data by an iterative adjustment of the values of the parameters. When the experimental measures are linear combinations of functions, the linear coefficients for a least squares fit may also be calculated. The values of both the parameters of the model and the coefficients for the sum of functions may be unknown independent variables, unknown dependent variables, or known constants. In the case of dependence, only linear dependencies are provided for in routine use. The computer program includes a number of subroutines, each one of which performs a special task. This permits flexibility in choosing various types of solutions and procedures. One subroutine, for example, handles linear differential equations, another, special non-linear functions, etc. The use of analytic or numerical solutions of equations is possible. PMID:13867975

Variability of Remote Sensing Spectral Indices in Boreal Lake Basins

NASA Astrophysics Data System (ADS)

Hakala, T.; Pölönen, I.; Honkavaara, E.; Näsi, R.; Hakala, T.; Lindfors, A.

2018-05-01

Remotely sensed hyperspectral data has widely been used to determine water quality parameters in oceanic waters. However in freshwater basins the dependence between the hyperspectral data and the parameters is more complicated. In this work some ideas are presented concerning the study of this dependence. The data used in this study were collected from the lake Hiidenvesi in southern Finland. The hyperspectral data consists of reflectances in 36 bands in the wavelength area 508…878 nm and the separately measured water quality parameters are turbidity, blue-green algae, chlorophyll, pH and dissolved oxygen. Hyperspectral data was used as bare band reflectances, but also in the form of two simple spectral indices: ratio A / B and difference A - B, where A and B go through all the bands. The correlations of the indices with the parameters were presented visually as 1- or 2-dimensional arrays. To examine the significance on the results of different variables, the data was classified in two different ways: the natural basins and the values of the water quality parameters. It was noticed that the variability of the correlation arrays was particularly strong among different basins in both the magnitude of correlation and the best performing indices. Further studies are needed to clarify which features of the basins are of most importance in predicting the shapes of the correlation arrays.

Control of end-tidal PCO2 reduces middle cerebral artery blood velocity variability: implications for physiological neuroimaging.

PubMed

Harris, Ashley D; Ide, Kojiro; Poulin, Marc J; Frayne, Richard

2006-02-15

Breath-by-breath variability of the end-tidal partial pressure of CO2 (Pet(CO2)) has been shown to be associated with cerebral blood flow (CBF) fluctuations. These fluctuations can impact neuroimaging techniques that depend on cerebrovascular blood flow. We hypothesized that controlling Pet(CO2) would reduce CBF variability. Dynamic end-tidal forcing was used to control Pet(CO2) at 1.5 mm Hg above the resting level and to hold the end-tidal partial pressure of oxygen (Pet(O2)) at the resting level. Peak blood velocity in the middle cerebral artery (MCA) was measured by transcranial Doppler ultrasound (TCD) as an index of CBF. Blood velocity parameters and timing features were determined on each waveform and the variance of these parameters was compared between Normal (air breathing) and Forcing (end-tidal gas control) sessions. The variability of all velocity parameters was significantly reduced in the Forcing session. In particular, the variability of the average velocity over the cardiac cycle was decreased by 18.2% (P < 0.001). For the most part, the variability of the timing parameters was unchanged. Thus, we conclude that controlling Pet(CO2) is effective in reducing CBF variability, which would have important implications for physiologic neuroimaging.

Maximum likelihood estimation for predicting the probability of obtaining variable shortleaf pine regeneration densities

Treesearch

Thomas B. Lynch; Jean Nkouka; Michael M. Huebschmann; James M. Guldin

2003-01-01

A logistic equation is the basis for a model that predicts the probability of obtaining regeneration at specified densities. The density of regeneration (trees/ha) for which an estimate of probability is desired can be specified by means of independent variables in the model. When estimating parameters, the dependent variable is set to 1 if the regeneration density (...

Integrating models that depend on variable data

NASA Astrophysics Data System (ADS)

Banks, A. T.; Hill, M. C.

2016-12-01

Models of human-Earth systems are often developed with the goal of predicting the behavior of one or more dependent variables from multiple independent variables, processes, and parameters. Often dependent variable values range over many orders of magnitude, which complicates evaluation of the fit of the dependent variable values to observations. Many metrics and optimization methods have been proposed to address dependent variable variability, with little consensus being achieved. In this work, we evaluate two such methods: log transformation (based on the dependent variable being log-normally distributed with a constant variance) and error-based weighting (based on a multi-normal distribution with variances that tend to increase as the dependent variable value increases). Error-based weighting has the advantage of encouraging model users to carefully consider data errors, such as measurement and epistemic errors, while log-transformations can be a black box for typical users. Placing the log-transformation into the statistical perspective of error-based weighting has not formerly been considered, to the best of our knowledge. To make the evaluation as clear and reproducible as possible, we use multiple linear regression (MLR). Simulations are conducted with MatLab. The example represents stream transport of nitrogen with up to eight independent variables. The single dependent variable in our example has values that range over 4 orders of magnitude. Results are applicable to any problem for which individual or multiple data types produce a large range of dependent variable values. For this problem, the log transformation produced good model fit, while some formulations of error-based weighting worked poorly. Results support previous suggestions fthat error-based weighting derived from a constant coefficient of variation overemphasizes low values and degrades model fit to high values. Applying larger weights to the high values is inconsistent with the log-transformation. Greater consistency is obtained by imposing smaller (by up to a factor of 1/35) weights on the smaller dependent-variable values. From an error-based perspective, the small weights are consistent with large standard deviations. This work considers the consequences of these two common ways of addressing variable data.

Approaches to highly parameterized inversion: A guide to using PEST for model-parameter and predictive-uncertainty analysis

USGS Publications Warehouse

Doherty, John E.; Hunt, Randall J.; Tonkin, Matthew J.

2010-01-01

Analysis of the uncertainty associated with parameters used by a numerical model, and with predictions that depend on those parameters, is fundamental to the use of modeling in support of decisionmaking. Unfortunately, predictive uncertainty analysis with regard to models can be very computationally demanding, due in part to complex constraints on parameters that arise from expert knowledge of system properties on the one hand (knowledge constraints) and from the necessity for the model parameters to assume values that allow the model to reproduce historical system behavior on the other hand (calibration constraints). Enforcement of knowledge and calibration constraints on parameters used by a model does not eliminate the uncertainty in those parameters. In fact, in many cases, enforcement of calibration constraints simply reduces the uncertainties associated with a number of broad-scale combinations of model parameters that collectively describe spatially averaged system properties. The uncertainties associated with other combinations of parameters, especially those that pertain to small-scale parameter heterogeneity, may not be reduced through the calibration process. To the extent that a prediction depends on system-property detail, its postcalibration variability may be reduced very little, if at all, by applying calibration constraints; knowledge constraints remain the only limits on the variability of predictions that depend on such detail. Regrettably, in many common modeling applications, these constraints are weak. Though the PEST software suite was initially developed as a tool for model calibration, recent developments have focused on the evaluation of model-parameter and predictive uncertainty. As a complement to functionality that it provides for highly parameterized inversion (calibration) by means of formal mathematical regularization techniques, the PEST suite provides utilities for linear and nonlinear error-variance and uncertainty analysis in these highly parameterized modeling contexts. Availability of these utilities is particularly important because, in many cases, a significant proportion of the uncertainty associated with model parameters-and the predictions that depend on them-arises from differences between the complex properties of the real world and the simplified representation of those properties that is expressed by the calibrated model. This report is intended to guide intermediate to advanced modelers in the use of capabilities available with the PEST suite of programs for evaluating model predictive error and uncertainty. A brief theoretical background is presented on sources of parameter and predictive uncertainty and on the means for evaluating this uncertainty. Applications of PEST tools are then discussed for overdetermined and underdetermined problems, both linear and nonlinear. PEST tools for calculating contributions to model predictive uncertainty, as well as optimization of data acquisition for reducing parameter and predictive uncertainty, are presented. The appendixes list the relevant PEST variables, files, and utilities required for the analyses described in the document.

3-D ballistic transport of ellipsoidal volcanic projectiles considering horizontal wind field and variable shape-dependent drag coefficients

NASA Astrophysics Data System (ADS)

Bertin, Daniel

2017-02-01

An innovative 3-D numerical model for the dynamics of volcanic ballistic projectiles is presented here. The model focuses on ellipsoidal particles and improves previous approaches by considering horizontal wind field, virtual mass forces, and drag forces subjected to variable shape-dependent drag coefficients. Modeling suggests that the projectile's launch velocity and ejection angle are first-order parameters influencing ballistic trajectories. The projectile's density and minor radius are second-order factors, whereas both intermediate and major radii of the projectile are of third order. Comparing output parameters, assuming different input data, highlights the importance of considering a horizontal wind field and variable shape-dependent drag coefficients in ballistic modeling, which suggests that they should be included in every ballistic model. On the other hand, virtual mass forces should be discarded since they almost do not contribute to ballistic trajectories. Simulation results were used to constrain some crucial input parameters (launch velocity, ejection angle, wind speed, and wind azimuth) of the block that formed the biggest and most distal ballistic impact crater during the 1984-1993 eruptive cycle of Lascar volcano, Northern Chile. Subsequently, up to 106 simulations were performed, whereas nine ejection parameters were defined by a Latin-hypercube sampling approach. Simulation results were summarized as a quantitative probabilistic hazard map for ballistic projectiles. Transects were also done in order to depict aerial hazard zones based on the same probabilistic procedure. Both maps combined can be used as a hazard prevention tool for ground and aerial transits nearby unresting volcanoes.

Time Delay Embedding Increases Estimation Precision of Models of Intraindividual Variability

ERIC Educational Resources Information Center

von Oertzen, Timo; Boker, Steven M.

2010-01-01

This paper investigates the precision of parameters estimated from local samples of time dependent functions. We find that "time delay embedding," i.e., structuring data prior to analysis by constructing a data matrix of overlapping samples, increases the precision of parameter estimates and in turn statistical power compared to standard…

Explicit expressions of self-diffusion coefficient, shear viscosity, and the Stokes-Einstein relation for binary mixtures of Lennard-Jones liquids

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

Ohtori, Norikazu, E-mail: ohtori@chem.sc.niigata-u.ac.jp; Ishii, Yoshiki

Explicit expressions of the self-diffusion coefficient, D{sub i}, and shear viscosity, η{sub sv}, are presented for Lennard-Jones (LJ) binary mixtures in the liquid states along the saturated vapor line. The variables necessary for the expressions were derived from dimensional analysis of the properties: atomic mass, number density, packing fraction, temperature, and the size and energy parameters used in the LJ potential. The unknown dependence of the properties on each variable was determined by molecular dynamics (MD) calculations for an equimolar mixture of Ar and Kr at the temperature of 140 K and density of 1676 kg m{sup −3}. The scalingmore » equations obtained by multiplying all the single-variable dependences can well express D{sub i} and η{sub sv} evaluated by the MD simulation for a whole range of compositions and temperatures without any significant coupling between the variables. The equation for D{sub i} can also explain the dual atomic-mass dependence, i.e., the average-mass and the individual-mass dependence; the latter accounts for the “isotope effect” on D{sub i}. The Stokes-Einstein (SE) relation obtained from these equations is fully consistent with the SE relation for pure LJ liquids and that for infinitely dilute solutions. The main differences from the original SE relation are the presence of dependence on the individual mass and on the individual energy parameter. In addition, the packing-fraction dependence turned out to bridge another gap between the present and original SE relations as well as unifying the SE relation between pure liquids and infinitely dilute solutions.« less

X-Ray Spectral Variability Signatures of Flares in BL Lac Objects

NASA Technical Reports Server (NTRS)

Boettcher, Markus; Chiang, James; White, Nicholas E. (Technical Monitor)

2002-01-01

We are presenting a detailed parameter study of the time-dependent electron injection and kinematics and the self-consistent radiation transport in jets of intermediate and low-frequency peaked BL Lac objects. Using a time-dependent, combined synchrotron-self-Compton and external-Compton jet model, we study the influence of variations of several essential model parameters, such as the electron injection compactness, the relative contribution of synchrotron to external soft photons to the soft photon compactness, the electron- injection spectral index, and the details of the time profiles of the electron injection episodes giving rise to flaring activity. In the analysis of our results, we focus on the expected X-ray spectral variability signatures in a region of parameter space particularly well suited to reproduce the broadband spectral energy distributions of intermediate and low-frequency peaked BL Lac objects. We demonstrate that SSC- and external-Compton dominated models for the gamma-ray emission from blazars are producing significantly different signatures in the X-ray variability, in particular in the soft X-ray light curves and the spectral hysteresis at soft X-ray energies, which can be used as a powerful diagnostic to unveil the nature of the high-energy emission from BL Lac objects.

Numerical investigation for entropy generation in hydromagnetic flow of fluid with variable properties and slip

NASA Astrophysics Data System (ADS)

Khan, M. Ijaz; Hayat, Tasawar; Alsaedi, Ahmed

2018-02-01

This modeling and computations present the study of viscous fluid flow with variable properties by a rotating stretchable disk. Rotating flow is generated through nonlinear rotating stretching surface. Nonlinear thermal radiation and heat generation/absorption are studied. Flow is conducting for a constant applied magnetic field. No polarization is taken. Induced magnetic field is not taken into account. Attention is focused on the entropy generation rate and Bejan number. The entropy generation rate and Bejan number clearly depend on velocity and thermal fields. The von Kármán approach is utilized to convert the partial differential expressions into ordinary ones. These expressions are non-dimensionalized, and numerical results are obtained for flow variables. The effects of the magnetic parameter, Prandtl number, radiative parameter, heat generation/absorption parameter, and slip parameter on velocity and temperature fields as well as the entropy generation rate and Bejan number are discussed. Drag forces (radial and tangential) and heat transfer rates are calculated and discussed. Furthermore the entropy generation rate is a decreasing function of magnetic variable and Reynolds number. The Bejan number effect on the entropy generation rate is reverse to that of the magnetic variable. Also opposite behavior of heat transfers is observed for varying estimations of radiative and slip variables.

A time to search: finding the meaning of variable activation energy.

PubMed

Vyazovkin, Sergey

2016-07-28

This review deals with the phenomenon of variable activation energy frequently observed when studying the kinetics in the liquid or solid phase. This phenomenon commonly manifests itself through nonlinear Arrhenius plots or dependencies of the activation energy on conversion computed by isoconversional methods. Variable activation energy signifies a multi-step process and has a meaning of a collective parameter linked to the activation energies of individual steps. It is demonstrated that by using appropriate models of the processes, the link can be established in algebraic form. This allows one to analyze experimentally observed dependencies of the activation energy in a quantitative fashion and, as a result, to obtain activation energies of individual steps, to evaluate and predict other important parameters of the process, and generally to gain deeper kinetic and mechanistic insights. This review provides multiple examples of such analysis as applied to the processes of crosslinking polymerization, crystallization and melting of polymers, gelation, and solid-solid morphological and glass transitions. The use of appropriate computational techniques is discussed as well.

Multi-band implications of external-IC flares

NASA Astrophysics Data System (ADS)

Richter, Stephan; Spanier, Felix

2015-02-01

Very fast variability on scales of minutes is regularly observed in Blazars. The assumption that these flares are emerging from the dominant emission zone of the very high energy (VHE) radiation within the jet challenges current acceleration and radiation models. In this work we use a spatially resolved and time dependent synchrotron-self-Compton (SSC) model that includes the full time dependence of Fermi-I acceleration. We use the (apparent) orphan γ -ray flare of Mrk501 during MJD 54952 and test various flare scenarios against the observed data. We find that a rapidly variable external radiation field can reproduce the high energy lightcurve best. However, the effect of the strong inverse Compton (IC) cooling on other bands and the X-ray observations are constraining the parameters to rather extreme ranges. Then again other scenarios would require parameters even more extreme or stronger physical constraints on the rise and decay of the source of the variability which might be in contradiction with constraints derived from the size of the black hole's ergosphere.

Stabilometric parameters are affected by anthropometry and foot placement.

PubMed

Chiari, Lorenzo; Rocchi, Laura; Cappello, Angelo

2002-01-01

To recognize and quantify the influence of biomechanical factors, namely anthropometry and foot placement, on the more common measures of stabilometric performance, including new-generation stochastic parameters. Fifty normal-bodied young adults were selected in order to cover a sufficiently wide range of anthropometric properties. They were allowed to choose their preferred side-by-side foot position and their quiet stance was recorded with eyes open and closed by a force platform. biomechanical factors are known to influence postural stability but their impact on stabilometric parameters has not been extensively explored yet. Principal component analysis was used for feature selection among several biomechanical factors. A collection of 55 stabilometric parameters from the literature was estimated from the center-of-pressure time series. Linear relations between stabilometric parameters and selected biomechanical factors were investigated by robust regression techniques. The feature selection process returned height, weight, maximum foot width, base-of-support area, and foot opening angle as the relevant biomechanical variables. Only eleven out of the 55 stabilometric parameters were completely immune from a linear dependence on these variables. The remaining parameters showed a moderate to high dependence that was strengthened upon eye closure. For these parameters, a normalization procedure was proposed, to remove what can well be considered, in clinical investigations, a spurious source of between-subject variability. Care should be taken when quantifying postural sway through stabilometric parameters. It is suggested as a good practice to include some anthropometric measurements in the experimental protocol, and to standardize or trace foot position. Although the role of anthropometry and foot placement has been investigated in specific studies, there are no studies in the literature that systematically explore the relationship between such BF and stabilometric parameters. This knowledge may contribute to better defining the experimental protocol and improving the functional evaluation of postural sway for clinical purposes, e.g. by removing through normalization the spurious effects of body properties and foot position on postural performance.

Scale-Dependent Solute Dispersion in Variably Saturated Porous Media

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

Rockhold, Mark L.; Zhang, Z. F.; Bott, Yi-Ju

2016-03-29

This work was performed to support performance assessment (PA) calculations for the Integrated Disposal Facility (IDF) at the Hanford Site. PA calculations require defensible estimates of physical, hydraulic, and transport parameters to simulate subsurface water flow and contaminant transport in both the near- and far-field environments. Dispersivity is one of the required transport parameters.

Parameter estimation of history-dependent leaky integrate-and-fire neurons using maximum-likelihood methods

PubMed Central

Dong, Yi; Mihalas, Stefan; Russell, Alexander; Etienne-Cummings, Ralph; Niebur, Ernst

2012-01-01

When a neuronal spike train is observed, what can we say about the properties of the neuron that generated it? A natural way to answer this question is to make an assumption about the type of neuron, select an appropriate model for this type, and then to choose the model parameters as those that are most likely to generate the observed spike train. This is the maximum likelihood method. If the neuron obeys simple integrate and fire dynamics, Paninski, Pillow, and Simoncelli (2004) showed that its negative log-likelihood function is convex and that its unique global minimum can thus be found by gradient descent techniques. The global minimum property requires independence of spike time intervals. Lack of history dependence is, however, an important constraint that is not fulfilled in many biological neurons which are known to generate a rich repertoire of spiking behaviors that are incompatible with history independence. Therefore, we expanded the integrate and fire model by including one additional variable, a variable threshold (Mihalas & Niebur, 2009) allowing for history-dependent firing patterns. This neuronal model produces a large number of spiking behaviors while still being linear. Linearity is important as it maintains the distribution of the random variables and still allows for maximum likelihood methods to be used. In this study we show that, although convexity of the negative log-likelihood is not guaranteed for this model, the minimum of the negative log-likelihood function yields a good estimate for the model parameters, in particular if the noise level is treated as a free parameter. Furthermore, we show that a nonlinear function minimization method (r-algorithm with space dilation) frequently reaches the global minimum. PMID:21851282

The Impact of Variability of Selected Geological and Mining Parameters on the Value and Risks of Projects in the Hard Coal Mining Industry

NASA Astrophysics Data System (ADS)

Kopacz, Michał

2017-09-01

The paper attempts to assess the impact of variability of selected geological (deposit) parameters on the value and risks of projects in the hard coal mining industry. The study was based on simulated discounted cash flow analysis, while the results were verified for three existing bituminous coal seams. The Monte Carlo simulation was based on nonparametric bootstrap method, while correlations between individual deposit parameters were replicated with use of an empirical copula. The calculations take into account the uncertainty towards the parameters of empirical distributions of the deposit variables. The Net Present Value (NPV) and the Internal Rate of Return (IRR) were selected as the main measures of value and risk, respectively. The impact of volatility and correlation of deposit parameters were analyzed in two aspects, by identifying the overall effect of the correlated variability of the parameters and the indywidual impact of the correlation on the NPV and IRR. For this purpose, a differential approach, allowing determining the value of the possible errors in calculation of these measures in numerical terms, has been used. Based on the study it can be concluded that the mean value of the overall effect of the variability does not exceed 11.8% of NPV and 2.4 percentage points of IRR. Neglecting the correlations results in overestimating the NPV and the IRR by up to 4.4%, and 0.4 percentage point respectively. It should be noted, however, that the differences in NPV and IRR values can vary significantly, while their interpretation depends on the likelihood of implementation. Generalizing the obtained results, based on the average values, the maximum value of the risk premium in the given calculation conditions of the "X" deposit, and the correspondingly large datasets (greater than 2500), should not be higher than 2.4 percentage points. The impact of the analyzed geological parameters on the NPV and IRR depends primarily on their co-existence, which can be measured by the strength of correlation. In the analyzed case, the correlations result in limiting the range of variation of the geological parameters and economics results (the empirical copula reduces the NPV and IRR in probabilistic approach). However, this is due to the adjustment of the calculation under conditions similar to those prevailing in the deposit.

Investigation on the effects of temperature dependency of material parameters on a thermoelastic loading problem

NASA Astrophysics Data System (ADS)

Kumar, Anil; Mukhopadhyay, Santwana

2017-08-01

The present work is concerned with the investigation of thermoelastic interactions inside a spherical shell with temperature-dependent material parameters. We employ the heat conduction model with a single delay term. The problem is studied by considering three different kinds of time-dependent temperature and stress distributions applied at the inner and outer surfaces of the shell. The problem is formulated by considering that the thermal properties vary as linear function of temperature that yield nonlinear governing equations. The problem is solved by applying Kirchhoff transformation along with integral transform technique. The numerical results of the field variables are shown in the different graphs to study the influence of temperature-dependent thermal parameters in various cases. It has been shown that the temperature-dependent effect is more prominent in case of stress distribution as compared to other fields and also the effect is significant in case of thermal shock applied at the two boundary surfaces of the spherical shell.

Polynomial chaos expansion with random and fuzzy variables

NASA Astrophysics Data System (ADS)

Jacquelin, E.; Friswell, M. I.; Adhikari, S.; Dessombz, O.; Sinou, J.-J.

2016-06-01

A dynamical uncertain system is studied in this paper. Two kinds of uncertainties are addressed, where the uncertain parameters are described through random variables and/or fuzzy variables. A general framework is proposed to deal with both kinds of uncertainty using a polynomial chaos expansion (PCE). It is shown that fuzzy variables may be expanded in terms of polynomial chaos when Legendre polynomials are used. The components of the PCE are a solution of an equation that does not depend on the nature of uncertainty. Once this equation is solved, the post-processing of the data gives the moments of the random response when the uncertainties are random or gives the response interval when the variables are fuzzy. With the PCE approach, it is also possible to deal with mixed uncertainty, when some parameters are random and others are fuzzy. The results provide a fuzzy description of the response statistical moments.

Periodic and chaotic psychological stress variations as predicted by a social support buffered response model

NASA Astrophysics Data System (ADS)

Field, Richard J.; Gallas, Jason A. C.; Schuldberg, David

2017-08-01

Recent work has introduced social dynamic models of people's stress-related processes, some including amelioration of stress symptoms by support from others. The effects of support may be ;direct;, depending only on the level of support, or ;buffering;, depending on the product of the level of support and level of stress. We focus here on the nonlinear buffering term and use a model involving three variables (and 12 control parameters), including stress as perceived by the individual, physical and psychological symptoms, and currently active social support. This model is quantified by a set of three nonlinear differential equations governing its stationary-state stability, temporal evolution (sometimes oscillatory), and how each variable affects the others. Chaos may appear with periodic forcing of an environmental stress parameter. Here we explore this model carefully as the strength and amplitude of this forcing, and an important psychological parameter relating to self-kindling in the stress response, are varied. Three significant observations are made: 1. There exist many complex but orderly regions of periodicity and chaos, 2. there are nested regions of increasing number of peaks per cycle that may cascade to chaos, and 3. there are areas where more than one state, e.g., a period-2 oscillation and chaos, coexist for the same parameters; which one is reached depends on initial conditions.

Using Indirect Turbulence Measurements for Real-Time Parameter Estimation in Turbulent Air

NASA Technical Reports Server (NTRS)

Martos, Borja; Morelli, Eugene A.

2012-01-01

The use of indirect turbulence measurements for real-time estimation of parameters in a linear longitudinal dynamics model in atmospheric turbulence was studied. It is shown that measuring the atmospheric turbulence makes it possible to treat the turbulence as a measured explanatory variable in the parameter estimation problem. Commercial off-the-shelf sensors were researched and evaluated, then compared to air data booms. Sources of colored noise in the explanatory variables resulting from typical turbulence measurement techniques were identified and studied. A major source of colored noise in the explanatory variables was identified as frequency dependent upwash and time delay. The resulting upwash and time delay corrections were analyzed and compared to previous time shift dynamic modeling research. Simulation data as well as flight test data in atmospheric turbulence were used to verify the time delay behavior. Recommendations are given for follow on flight research and instrumentation.

Influence of thermodynamic parameter in Lanosterol 14alpha-demethylase inhibitory activity as antifungal agents: a QSAR approach.

PubMed

Vasanthanathan, Poongavanam; Lakshmi, Manickavasagam; Arockia Babu, Marianesan; Kaskhedikar, Sathish Gopalrao

2006-06-01

A quantitative structure activity relationship, Hansch approach was applied on twenty compounds of chromene derivatives as Lanosterol 14alpha-demethylase inhibitory activity against eight fungal organisms. Various physicochemical descriptors and reported minimum inhibitory concentration values of different fungal organisms were used as independent variables and dependent variable respectively. The best models for eight different fungal organisms were first validated by leave-one-out cross validation procedure. It was revealed that thermodynamic parameters were found to have overall significant correlationship with anti fungal activity and these studies provide an insight to design new molecules.

Oxidative Stress Parameters in Saliva and Its Association with Periodontal Disease and Types of Bacteria.

PubMed

Almerich-Silla, Jose Manuel; Montiel-Company, Jose María; Pastor, Sara; Serrano, Felipe; Puig-Silla, Miriam; Dasí, Francisco

2015-01-01

To determine the association between oxidative stress parameters with periodontal disease, bleeding, and the presence of different periodontal bacteria. A cross-sectional study in a sample of eighty-six patients, divided into three groups depending on their periodontal status. Thirty-three with chronic periodontitis, sixteen with gingivitis, and thirty-seven with periodontal healthy as control. Oxidative stress biomarkers (8-OHdG and MDA), total antioxidant capacity (TAOC), and the activity of two antioxidant enzymes (GPx and SOD) were determined in saliva. Subgingival plaque samples were obtained from the deepest periodontal pocket and PCR was used to determine the presence of the 6 fimA genotypes of Porphyromonas gingivalis, Aggregatibacter actinomycetemcomitans, Tannerella forsythia, and Treponema denticola. Periodontal disease was found to be associated with increased oxidative stress parameter levels. These levels rose according to the number and type of different periodontal bacteria found in the periodontal pockets. The presence of different types of periodontal bacteria is predictive independent variables in linear regresion models of oxidative stress parameters as dependent variable, above all 8-OHdG. Oxidative stress parameter levels are correlated with the presence of different types of bacteria. Determination of these levels and periodontal bacteria could be a potent tool for controlling periodontal disease development.

Interpolation of Regional Groundwater Quality Parameters With Categorical and Real-Valued Secondary Information in the State of Baden-Württemberg, Germany

NASA Astrophysics Data System (ADS)

Haslauer, C. P.; Allmendinger, M.; Gnann, S.; Heisserer, T.; Bárdossy, A.

2017-12-01

The basic problem of geostatistics is to estimate the primary variable (e.g. groundwater quality, nitrate) at an un-sampled location based on point measurements at locations in the vicinity. Typically, models are being used that describe the spatial dependence based on the geometry of the observation network. This presentation demonstrates methods that take the following properties additionally into account: the statistical distribution of the measurements, a different degree of dependence in different quantiles, censored measurements, the composition of categorical additional information in the neighbourhood (exhaustive secondary information), and the spatial dependence of a dependent secondary variable, possibly measured with a different observation network (non-exhaustive secondary data). Two modelling approaches are demonstrated individually and combined: The non-stationarity in the marginal distribution is accounted for by locally mixed distribution functions that depend on the composition of the categorical variable in the neighbourhood of each interpolation location. This methodology is currently being implemented for operational use at the environmental state agency of Baden-Württemberg. An alternative to co-Kriging in copula space with an arbitrary number of secondary parameters is presented: The method performs better than traditional techniques if the primary variable is undersampled and does not produce erroneous negative estimates. Even more, the quality of the uncertainty estimates is much improved. The worth of the secondary information is thoroughly evaluated. The improved geostatistical hydrogeological models are being analyzed using measurements of a large observation network ( 2500 measurement locations) in the state of Baden-Württemberg ( 36.000 km2). Typical groundwater quality parameters such as nitrate, chloride, barium, antrazine, and desethylatrazine are being assessed, cross-validated, and compared with traditional geostatistical methods. The secondary information of land use is available on a 30m x 30m raster. We show that the presented methods are not only better estimators (e.g. in the sense of an average quadratic error), but exhibit a much more realistic structure of the uncertainty and hence are improvements compared to existing methods.

Climate-driven vital rates do not always mean climate-driven population.

PubMed

Tavecchia, Giacomo; Tenan, Simone; Pradel, Roger; Igual, José-Manuel; Genovart, Meritxell; Oro, Daniel

2016-12-01

Current climatic changes have increased the need to forecast population responses to climate variability. A common approach to address this question is through models that project current population state using the functional relationship between demographic rates and climatic variables. We argue that this approach can lead to erroneous conclusions when interpopulation dispersal is not considered. We found that immigration can release the population from climate-driven trajectories even when local vital rates are climate dependent. We illustrated this using individual-based data on a trans-equatorial migratory seabird, the Scopoli's shearwater Calonectris diomedea, in which the variation of vital rates has been associated with large-scale climatic indices. We compared the population annual growth rate λ i , estimated using local climate-driven parameters with ρ i , a population growth rate directly estimated from individual information and that accounts for immigration. While λ i varied as a function of climatic variables, reflecting the climate-dependent parameters, ρ i did not, indicating that dispersal decouples the relationship between population growth and climate variables from that between climatic variables and vital rates. Our results suggest caution when assessing demographic effects of climatic variability especially in open populations for very mobile organisms such as fish, marine mammals, bats, or birds. When a population model cannot be validated or it is not detailed enough, ignoring immigration might lead to misleading climate-driven projections. © 2016 John Wiley & Sons Ltd.

The relation of autonomic function to physical fitness in patients suffering from alcohol dependence.

PubMed

Herbsleb, Marco; Schulz, Steffen; Ostermann, Stephanie; Donath, Lars; Eisenträger, Daniela; Puta, Christian; Voss, Andreas; Gabriel, Holger W; Bär, Karl-Jürgen

2013-10-01

Reduced cardio-vascular health has been found in patients suffering from alcohol dependence. Low cardio-respiratory fitness is an independent predictor of cardio-vascular disease. We investigated physical fitness in 22 alcohol-dependent patients 10 days after acute alcohol withdrawal and compared results with matched controls. The standardized 6-min walk test (6 MWT) was used to analyze the relationship of autonomic dysfunction and physical fitness. Ventilatory indices and gas exchanges were assessed using a portable spiroergometric system while heart rate recordings were obtained separately. We calculated walking distance, indices of heart rate variability and efficiency parameters of heart rate and breathing. In addition, levels of exhaled carbon monoxide were measured in all participants to account for differences in smoking behaviour. Multivariate analyses of variance (MANOVA) were performed to investigate differences between patients and controls with regard to autonomic and efficiency parameters. Patients walked a significantly shorter distance in comparison to healthy subjects during the 6 MWT. Significantly decreased heart rate variability was observed before and after the test in patients when compared to controls, while no such difference was observed during exercise. The efficiency parameters indicated significantly reduced efficiency in physiological regulation when the obtained parameters were normalized to the distance. The 6 MWT is an easily applied instrument to measure physical fitness in alcohol dependent patients. It can also be used during exercise interventions. Reduced physical fitness, as observed in our study, might partly be caused by autonomic dysfunction, leading to less efficient regulation of physiological processes during exercise. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Advanced Flight Simulator: Utilization in A-10 Conversion and Air-to-Surface Attack Training.

DTIC Science & Technology

1981-01-01

ASPT to the A-I0. Finally. the objectivity of the criteria ( parameters of aircraft control. bomb-drop circular error. and percentage of rounds through a...low angle strafe task. Table 4 presents a listing of these tasks and their related release parameters . 12 __ __ _ __ Tab/e .1. A/S Weapons I)eliven...Scoring. Two dependent variables, specific to the phase of student training, were used. In the conversion training phase. specific parameters for

The Mathematics of Psychotherapy: A Nonlinear Model of Change Dynamics.

PubMed

Schiepek, Gunter; Aas, Benjamin; Viol, Kathrin

2016-07-01

Psychotherapy is a dynamic process produced by a complex system of interacting variables. Even though there are qualitative models of such systems the link between structure and function, between network and network dynamics is still missing. The aim of this study is to realize these links. The proposed model is composed of five state variables (P: problem severity, S: success and therapeutic progress, M: motivation to change, E: emotions, I: insight and new perspectives) interconnected by 16 functions. The shape of each function is modified by four parameters (a: capability to form a trustful working alliance, c: mentalization and emotion regulation, r: behavioral resources and skills, m: self-efficacy and reward expectation). Psychologically, the parameters play the role of competencies or traits, which translate into the concept of control parameters in synergetics. The qualitative model was transferred into five coupled, deterministic, nonlinear difference equations generating the dynamics of each variable as a function of other variables. The mathematical model is able to reproduce important features of psychotherapy processes. Examples of parameter-dependent bifurcation diagrams are given. Beyond the illustrated similarities between simulated and empirical dynamics, the model has to be further developed, systematically tested by simulated experiments, and compared to empirical data.

Sobol' sensitivity analysis for stressor impacts on honeybee ...

EPA Pesticide Factsheets

We employ Monte Carlo simulation and nonlinear sensitivity analysis techniques to describe the dynamics of a bee exposure model, VarroaPop. Daily simulations are performed of hive population trajectories, taking into account queen strength, foraging success, mite impacts, weather, colony resources, population structure, and other important variables. This allows us to test the effects of defined pesticide exposure scenarios versus controlled simulations that lack pesticide exposure. The daily resolution of the model also allows us to conditionally identify sensitivity metrics. We use the variancebased global decomposition sensitivity analysis method, Sobol’, to assess firstand secondorder parameter sensitivities within VarroaPop, allowing us to determine how variance in the output is attributed to each of the input variables across different exposure scenarios. Simulations with VarroaPop indicate queen strength, forager life span and pesticide toxicity parameters are consistent, critical inputs for colony dynamics. Further analysis also reveals that the relative importance of these parameters fluctuates throughout the simulation period according to the status of other inputs. Our preliminary results show that model variability is conditional and can be attributed to different parameters depending on different timescales. By using sensitivity analysis to assess model output and variability, calibrations of simulation models can be better informed to yield more

Using ERA-Interim reanalysis for creating datasets of energy-relevant climate variables

NASA Astrophysics Data System (ADS)

Jones, Philip D.; Harpham, Colin; Troccoli, Alberto; Gschwind, Benoit; Ranchin, Thierry; Wald, Lucien; Goodess, Clare M.; Dorling, Stephen

2017-07-01

The construction of a bias-adjusted dataset of climate variables at the near surface using ERA-Interim reanalysis is presented. A number of different, variable-dependent, bias-adjustment approaches have been proposed. Here we modify the parameters of different distributions (depending on the variable), adjusting ERA-Interim based on gridded station or direct station observations. The variables are air temperature, dewpoint temperature, precipitation (daily only), solar radiation, wind speed, and relative humidity. These are available on either 3 or 6 h timescales over the period 1979-2016. The resulting bias-adjusted dataset is available through the Climate Data Store (CDS) of the Copernicus Climate Change Data Store (C3S) and can be accessed at present from ftp://ecem.climate.copernicus.eu. The benefit of performing bias adjustment is demonstrated by comparing initial and bias-adjusted ERA-Interim data against gridded observational fields.

Selection of latent variables for multiple mixed-outcome models

PubMed Central

ZHOU, LING; LIN, HUAZHEN; SONG, XINYUAN; LI, YI

2014-01-01

Latent variable models have been widely used for modeling the dependence structure of multiple outcomes data. However, the formulation of a latent variable model is often unknown a priori, the misspecification will distort the dependence structure and lead to unreliable model inference. Moreover, multiple outcomes with varying types present enormous analytical challenges. In this paper, we present a class of general latent variable models that can accommodate mixed types of outcomes. We propose a novel selection approach that simultaneously selects latent variables and estimates parameters. We show that the proposed estimator is consistent, asymptotically normal and has the oracle property. The practical utility of the methods is confirmed via simulations as well as an application to the analysis of the World Values Survey, a global research project that explores peoples’ values and beliefs and the social and personal characteristics that might influence them. PMID:27642219

Using Bayesian regression to test hypotheses about relationships between parameters and covariates in cognitive models.

PubMed

Boehm, Udo; Steingroever, Helen; Wagenmakers, Eric-Jan

2018-06-01

An important tool in the advancement of cognitive science are quantitative models that represent different cognitive variables in terms of model parameters. To evaluate such models, their parameters are typically tested for relationships with behavioral and physiological variables that are thought to reflect specific cognitive processes. However, many models do not come equipped with the statistical framework needed to relate model parameters to covariates. Instead, researchers often revert to classifying participants into groups depending on their values on the covariates, and subsequently comparing the estimated model parameters between these groups. Here we develop a comprehensive solution to the covariate problem in the form of a Bayesian regression framework. Our framework can be easily added to existing cognitive models and allows researchers to quantify the evidential support for relationships between covariates and model parameters using Bayes factors. Moreover, we present a simulation study that demonstrates the superiority of the Bayesian regression framework to the conventional classification-based approach.

Real topological entropy versus metric entropy for birational measure-preserving transformations

NASA Astrophysics Data System (ADS)

Abarenkova, N.; Anglès d'Auriac, J.-Ch.; Boukraa, S.; Maillard, J.-M.

2000-10-01

We consider a family of birational measure-preserving transformations of two complex variables, depending on one parameter for which simple rational expressions for the dynamical zeta function have been conjectured, together with an equality between the topological entropy and the logarithm of the Arnold complexity (divided by the number of iterations). Similar results have been obtained for the adaptation of these two concepts to dynamical systems of real variables, yielding to introduce a “real topological entropy” and a “real Arnold complexity”. We try to compare, here, the Kolmogorov-Sinai metric entropy and this real Arnold complexity, or real topological entropy, on this particular example of a one-parameter dependent birational transformation of two variables. More precisely, we analyze, using an infinite precision calculation, the Lyapunov characteristic exponents for various values of the parameter of the birational transformation, in order to compare these results with the ones for the real Arnold complexity. We find a quite surprising result: for this very birational example, and, in fact, for a large set of birational measure-preserving mappings generated by involutions, the Lyapunov characteristic exponents seem to be equal to zero or, at least, extremely small, for all the orbits we have considered, and for all values of the parameter. Birational measure-preserving transformations, generated by involutions, could thus allow to better understand the difference between the topological description and the probabilistic description of discrete dynamical systems. Many birational measure-preserving transformations, generated by involutions, seem to provide examples of discrete dynamical systems which can be topologically chaotic while they are metrically almost quasi-periodic. Heuristically, this can be understood as a consequence of the fact that their orbits seem to form some kind of “transcendental foliation” of the two-dimensional space of variables.

Application of Different Statistical Techniques in Integrated Logistics Support of the International Space Station Alpha

NASA Technical Reports Server (NTRS)

Sepehry-Fard, F.; Coulthard, Maurice H.

1995-01-01

The process to predict the values of the maintenance time dependent variable parameters such as mean time between failures (MTBF) over time must be one that will not in turn introduce uncontrolled deviation in the results of the ILS analysis such as life cycle cost spares calculation, etc. A minor deviation in the values of the maintenance time dependent variable parameters such as MTBF over time will have a significant impact on the logistics resources demands, International Space Station availability, and maintenance support costs. It is the objective of this report to identify the magnitude of the expected enhancement in the accuracy of the results for the International Space Station reliability and maintainability data packages by providing examples. These examples partially portray the necessary information hy evaluating the impact of the said enhancements on the life cycle cost and the availability of the International Space Station.

Reproductive Indicators of Leguminous Plants as a Characteristic of the Ecological State of Urban Areas

NASA Astrophysics Data System (ADS)

Zamaletdinov, R. I.; Okulova, S. M.; Gavrilova, E. A.; Zakhvatova, A. A.

2018-01-01

This article examines the results of many years of research on the reproductive performance of six species of leguminous plants (FabaceaeLind., 1836) under conditions of urbanization of habitat (Kazan). The range of variability of the main reproductive indices in six species is illustrated: the potential productivity, the actual productivity of the six main types of leguminous plants. The features of variability of seed death at different stages of development are shown depending on habitat conditions. It is established that the main regularities of changes in reproductive parameters depending on habitat conditions are manifested both in native species and in the introduced species Caraganaarborescens Lam., 1785. Based on the results of the study we made conclusion about the advisability of monitoring the reproductive parameters of leguminous plants for indicating the state of the environment in a large city.

Parameter and prediction uncertainty in an optimized terrestrial carbon cycle model: Effects of constraining variables and data record length

NASA Astrophysics Data System (ADS)

Ricciuto, Daniel M.; King, Anthony W.; Dragoni, D.; Post, Wilfred M.

2011-03-01

Many parameters in terrestrial biogeochemical models are inherently uncertain, leading to uncertainty in predictions of key carbon cycle variables. At observation sites, this uncertainty can be quantified by applying model-data fusion techniques to estimate model parameters using eddy covariance observations and associated biometric data sets as constraints. Uncertainty is reduced as data records become longer and different types of observations are added. We estimate parametric and associated predictive uncertainty at the Morgan Monroe State Forest in Indiana, USA. Parameters in the Local Terrestrial Ecosystem Carbon (LoTEC) are estimated using both synthetic and actual constraints. These model parameters and uncertainties are then used to make predictions of carbon flux for up to 20 years. We find a strong dependence of both parametric and prediction uncertainty on the length of the data record used in the model-data fusion. In this model framework, this dependence is strongly reduced as the data record length increases beyond 5 years. If synthetic initial biomass pool constraints with realistic uncertainties are included in the model-data fusion, prediction uncertainty is reduced by more than 25% when constraining flux records are less than 3 years. If synthetic annual aboveground woody biomass increment constraints are also included, uncertainty is similarly reduced by an additional 25%. When actual observed eddy covariance data are used as constraints, there is still a strong dependence of parameter and prediction uncertainty on data record length, but the results are harder to interpret because of the inability of LoTEC to reproduce observed interannual variations and the confounding effects of model structural error.

Force-Time Entropy of Isometric Impulse.

PubMed

Hsieh, Tsung-Yu; Newell, Karl M

2016-01-01

The relation between force and temporal variability in discrete impulse production has been viewed as independent (R. A. Schmidt, H. Zelaznik, B. Hawkins, J. S. Frank, & J. T. Quinn, 1979 ) or dependent on the rate of force (L. G. Carlton & K. M. Newell, 1993 ). Two experiments in an isometric single finger force task investigated the joint force-time entropy with (a) fixed time to peak force and different percentages of force level and (b) fixed percentage of force level and different times to peak force. The results showed that the peak force variability increased either with the increment of force level or through a shorter time to peak force that also reduced timing error variability. The peak force entropy and entropy of time to peak force increased on the respective dimension as the parameter conditions approached either maximum force or a minimum rate of force production. The findings show that force error and timing error are dependent but complementary when considered in the same framework with the joint force-time entropy at a minimum in the middle parameter range of discrete impulse.

Production of a water quality map of Saginaw Bay by computer processing of LANDSAT-2 data

NASA Technical Reports Server (NTRS)

Mckeon, J. B.; Rogers, R. H.; Smith, V. E.

1977-01-01

Surface truth and LANDSAT measurements collected July 31, 1975, for Saginaw Bay were used to demonstrate a technique for producing a color coded water quality map. On this map, color was used as a code to quantify five discrete ranges in the following water quality parameters: (1) temperature, (2) Secchi depth, (3) chloride, (4) conductivity, (5) total Kjeldahl nitrogen, (6) total phosphorous, (7)chlorophyll a, (8) total solids and (9) suspended solids. The LANDSAT and water quality relationship was established through the use of a set of linear regression equations where the water quality parameters are the dependent variables and LANDSAT measurements are the independent variables. Although the procedure is scene and surface truth dependent, it provides both a basis for extrapolating water quality parameters from point samples to unsampled areas and a synoptic view of water mass boundaries over the 3000 sq. km bay area made from one day's ship data that is superior, in many ways, to the traditional machine contoured maps made from three day's ship data.

Spatial variability versus parameter uncertainty in freshwater fate and exposure factors of chemicals.

PubMed

Nijhof, Carl O P; Huijbregts, Mark A J; Golsteijn, Laura; van Zelm, Rosalie

2016-04-01

We compared the influence of spatial variability in environmental characteristics and the uncertainty in measured substance properties of seven chemicals on freshwater fate factors (FFs), representing the residence time in the freshwater environment, and on exposure factors (XFs), representing the dissolved fraction of a chemical. The influence of spatial variability was quantified using the SimpleBox model in which Europe was divided in 100 × 100 km regions, nested in a regional (300 × 300 km) and supra-regional (500 × 500 km) scale. Uncertainty in substance properties was quantified by means of probabilistic modelling. Spatial variability and parameter uncertainty were expressed by the ratio k of the 95%ile and 5%ile of the FF and XF. Our analysis shows that spatial variability ranges in FFs of persistent chemicals that partition predominantly into one environmental compartment was up to 2 orders of magnitude larger compared to uncertainty. For the other (less persistent) chemicals, uncertainty in the FF was up to 1 order of magnitude larger than spatial variability. Variability and uncertainty in freshwater XFs of the seven chemicals was negligible (k < 1.5). We found that, depending on the chemical and emission scenario, accounting for region-specific environmental characteristics in multimedia fate modelling, as well as accounting for parameter uncertainty, can have a significant influence on freshwater fate factor predictions. Therefore, we conclude that it is important that fate factors should not only account for parameter uncertainty, but for spatial variability as well, as this further increases the reliability of ecotoxicological impacts in LCA. Copyright © 2016 Elsevier Ltd. All rights reserved.

Total ozone trend significance from space time variability of daily Dobson data

NASA Technical Reports Server (NTRS)

Wilcox, R. W.

1981-01-01

Estimates of standard errors of total ozone time and area means, as derived from ozone's natural temporal and spatial variability and autocorrelation in middle latitudes determined from daily Dobson data are presented. Assessing the significance of apparent total ozone trends is equivalent to assessing the standard error of the means. Standard errors of time averages depend on the temporal variability and correlation of the averaged parameter. Trend detectability is discussed, both for the present network and for satellite measurements.

Quantitative measure of the variation in fault rheology due to fluid-rock interactions

USGS Publications Warehouse

Blanpied, M.L.; Marone, C.J.; Lockner, D.A.; Byerlee, J.D.; King, D.P.

1998-01-01

We analyze friction data from two published suites of laboratory tests on granite in order to explore and quantify the effects of temperature (T) and pore water pressure (Pp) on the sliding behavior of faults. Rate-stepping sliding tests were performed on laboratory faults in granite containing "gouge" (granite powder), both dry at 23?? to 845??C [Lockner et al., 1986], and wet (Pp = 100 MPa) at 23?? to 600??C [Blanpied et al., 1991, 1995]. Imposed slip velocities (V) ranged from 0.01 to 5.5 ??m/s, and effective normal stresses were near 400 MPa. For dried granite at all temperatures, and wet granite below -300??C, the coefficient of friction (??) shows low sensitivity to V, T, and Pp. For wet granite above -350??, ?? drops rapidly with increasing T and shows a strong, positive rate dependence and protracted strength transients following steps in V, presumably reflecting the activity of a water-aided deformation process. By inverting strength data from velocity stepping tests we determined values for parameters in three formulations of a rate- and state-dependent constitutive law. One or two state variables were used to represent slip history effects. Each velocity step yielded an independent set of values for the nominal friction level, five constitutive parameters (transient parameters a, b1, and b2 and characteristic displacements Dcl and Dc2), and the velocity dependence of steady state friction ?????ss/??? In V = a-b1-b2. Below 250??, data from dry and most wet tests are adequately modeled by using the "slip law" [Ruina, 1983] and one state variable (a = 0.003 to 0.018, b = 0.001 to +0.018, Dc ??? 1 to 20 ??m). Dried tests above 250?? can also be fitted with one state variable. In contrast, wet tests above 350?? require higher direct rate dependence (a = 0.03 to 0.12), plus a second state variable with large, negative amplitude (b2 = -0.03 to -0.14) and large characteristic displacement (Dc2 = 300 to >4000 ??m). Thus the parameters a, b1, and b2 for wet granite show a pronounced change in their temperature dependence in the range 270?? to 350??C, which may reflect a change in underlying deformation mechanism. We quantify the trends in parameter values from 25?? to 600??C by piecewise linear regressions, which provide a straightforward means to incorporate the full constitutive response of granite into numerical models of fault slip. The modeling results suggest that the succeptibility for unstable (stick-slip) sliding is maximized between 90?? and 360??C, in agreement with laboratory observations and consistent with the depth range of earthquakes on mature faults in the continental crust.

Rough parameter dependence in climate models and the role of Ruelle-Pollicott resonances.

PubMed

Chekroun, Mickaël David; Neelin, J David; Kondrashov, Dmitri; McWilliams, James C; Ghil, Michael

2014-02-04

Despite the importance of uncertainties encountered in climate model simulations, the fundamental mechanisms at the origin of sensitive behavior of long-term model statistics remain unclear. Variability of turbulent flows in the atmosphere and oceans exhibits recurrent large-scale patterns. These patterns, while evolving irregularly in time, manifest characteristic frequencies across a large range of time scales, from intraseasonal through interdecadal. Based on modern spectral theory of chaotic and dissipative dynamical systems, the associated low-frequency variability may be formulated in terms of Ruelle-Pollicott (RP) resonances. RP resonances encode information on the nonlinear dynamics of the system, and an approach for estimating them--as filtered through an observable of the system--is proposed. This approach relies on an appropriate Markov representation of the dynamics associated with a given observable. It is shown that, within this representation, the spectral gap--defined as the distance between the subdominant RP resonance and the unit circle--plays a major role in the roughness of parameter dependences. The model statistics are the most sensitive for the smallest spectral gaps; such small gaps turn out to correspond to regimes where the low-frequency variability is more pronounced, whereas autocorrelations decay more slowly. The present approach is applied to analyze the rough parameter dependence encountered in key statistics of an El-Niño-Southern Oscillation model of intermediate complexity. Theoretical arguments, however, strongly suggest that such links between model sensitivity and the decay of correlation properties are not limited to this particular model and could hold much more generally.

Rough parameter dependence in climate models and the role of Ruelle-Pollicott resonances

PubMed Central

Chekroun, Mickaël David; Neelin, J. David; Kondrashov, Dmitri; McWilliams, James C.; Ghil, Michael

2014-01-01

Despite the importance of uncertainties encountered in climate model simulations, the fundamental mechanisms at the origin of sensitive behavior of long-term model statistics remain unclear. Variability of turbulent flows in the atmosphere and oceans exhibits recurrent large-scale patterns. These patterns, while evolving irregularly in time, manifest characteristic frequencies across a large range of time scales, from intraseasonal through interdecadal. Based on modern spectral theory of chaotic and dissipative dynamical systems, the associated low-frequency variability may be formulated in terms of Ruelle-Pollicott (RP) resonances. RP resonances encode information on the nonlinear dynamics of the system, and an approach for estimating them—as filtered through an observable of the system—is proposed. This approach relies on an appropriate Markov representation of the dynamics associated with a given observable. It is shown that, within this representation, the spectral gap—defined as the distance between the subdominant RP resonance and the unit circle—plays a major role in the roughness of parameter dependences. The model statistics are the most sensitive for the smallest spectral gaps; such small gaps turn out to correspond to regimes where the low-frequency variability is more pronounced, whereas autocorrelations decay more slowly. The present approach is applied to analyze the rough parameter dependence encountered in key statistics of an El-Niño–Southern Oscillation model of intermediate complexity. Theoretical arguments, however, strongly suggest that such links between model sensitivity and the decay of correlation properties are not limited to this particular model and could hold much more generally. PMID:24443553

A New Method for Determining the Equation of State of Aluminized Explosive

NASA Astrophysics Data System (ADS)

Zhou, Zheng-Qing; Nie, Jian-Xin; Guo, Xue-Yong; Wang, Qiu-Shi; Ou, Zhuo-Cheng; Jiao, Qing-Jie

2015-01-01

The time-dependent Jones—Wilkins—Lee equation of state (JWL-EOS) is applied to describe detonation state products for aluminized explosives. To obtain the time-dependent JWL-EOS parameters, cylinder tests and underwater explosion experiments are performed. According to the result of the wall radial velocity in cylinder tests and the shock wave pressures in underwater explosion experiments, the time-dependent JWL-EOS parameters are determined by iterating these variables in AUTODYN hydrocode simulations until the experimental values are reproduced. In addition, to verify the reliability of the derived JWL-EOS parameters, the aluminized explosive experiment is conducted in concrete. The shock wave pressures in the affected concrete bodies are measured by using manganin pressure sensors, and the rod velocity is obtained by using a high-speed camera. Simultaneously, the shock wave pressure and the rod velocity are calculated by using the derived time-dependent JWL equation of state. The calculated results are in good agreement with the experimental data.

A similarity solution of time dependent MHD liquid film flow over stretching sheet with variable physical properties

NASA Astrophysics Data System (ADS)

Idrees, M.; Rehman, Sajid; Shah, Rehan Ali; Ullah, M.; Abbas, Tariq

2018-03-01

An analysis is performed for the fluid dynamics incorporating the variation of viscosity and thermal conductivity on an unsteady two-dimensional free surface flow of a viscous incompressible conducting fluid taking into account the effect of a magnetic field. Surface tension quadratically vary with temperature while fluid viscosity and thermal conductivity are assumed to vary as a linear function of temperature. The boundary layer partial differential equations in cartesian coordinates are transformed into a system of nonlinear ordinary differential equations (ODEs) by similarity transformation. The developed nonlinear equations are solved analytically by Homotopy Analysis Method (HAM) while numerically by using the shooting method. The Effects of natural parameters such as the variable viscosity parameter A, variable thermal conductivity parameter N, Hartmann number Ma, film Thickness, unsteadiness parameter S, Thermocapillary number M and Prandtl number Pr on the velocity and temperature profiles are investigated. The results for the surface skin friction coefficient f″ (0) , Nusselt number (heat flux) -θ‧ (0) and free surface temperature θ (1) are presented graphically and in tabular form.

Forced convective heat transfer in boundary layer flow of Sisko fluid over a nonlinear stretching sheet.

PubMed

Munir, Asif; Shahzad, Azeem; Khan, Masood

2014-01-01

The major focus of this article is to analyze the forced convective heat transfer in a steady boundary layer flow of Sisko fluid over a nonlinear stretching sheet. Two cases are studied, namely (i) the sheet with variable temperature (PST case) and (ii) the sheet with variable heat flux (PHF case). The heat transfer aspects are investigated for both integer and non-integer values of the power-law index. The governing partial differential equations are reduced to a system of nonlinear ordinary differential equations using appropriate similarity variables and solved numerically. The numerical results are obtained by the shooting method using adaptive Runge Kutta method with Broyden's method in the domain[Formula: see text]. The numerical results for the temperature field are found to be strongly dependent upon the power-law index, stretching parameter, wall temperature parameter, material parameter of the Sisko fluid and Prandtl number. In addition, the local Nusselt number versus wall temperature parameter is also graphed and tabulated for different values of pertaining parameters. Further, numerical results are validated by comparison with exact solutions as well as previously published results in the literature.

Wave propagation in embedded inhomogeneous nanoscale plates incorporating thermal effects

NASA Astrophysics Data System (ADS)

Ebrahimi, Farzad; Barati, Mohammad Reza; Dabbagh, Ali

2018-04-01

In this article, an analytical approach is developed to study the effects of thermal loading on the wave propagation characteristics of an embedded functionally graded (FG) nanoplate based on refined four-variable plate theory. The heat conduction equation is solved to derive the nonlinear temperature distribution across the thickness. Temperature-dependent material properties of nanoplate are graded using Mori-Tanaka model. The nonlocal elasticity theory of Eringen is introduced to consider small-scale effects. The governing equations are derived by the means of Hamilton's principle. Obtained frequencies are validated with those of previously published works. Effects of different parameters such as temperature distribution, foundation parameters, nonlocal parameter, and gradient index on the wave propagation response of size-dependent FG nanoplates have been investigated.

Local Infrasound Variability Related to In Situ Atmospheric Observation

NASA Astrophysics Data System (ADS)

Kim, Keehoon; Rodgers, Arthur; Seastrand, Douglas

2018-04-01

Local infrasound is widely used to constrain source parameters of near-surface events (e.g., chemical explosions and volcanic eruptions). While atmospheric conditions are critical to infrasound propagation and source parameter inversion, local atmospheric variability is often ignored by assuming homogeneous atmospheres, and their impact on the source inversion uncertainty has never been accounted for due to the lack of quantitative understanding of infrasound variability. We investigate atmospheric impacts on local infrasound propagation by repeated explosion experiments with a dense acoustic network and in situ atmospheric measurement. We perform full 3-D waveform simulations with local atmospheric data and numerical weather forecast model to quantify atmosphere-dependent infrasound variability and address the advantage and restriction of local weather data/numerical weather model for sound propagation simulation. Numerical simulations with stochastic atmosphere models also showed nonnegligible influence of atmospheric heterogeneity on infrasound amplitude, suggesting an important role of local turbulence.

An analysis of input errors in precipitation-runoff models using regression with errors in the independent variables

USGS Publications Warehouse

Troutman, Brent M.

1982-01-01

Errors in runoff prediction caused by input data errors are analyzed by treating precipitation-runoff models as regression (conditional expectation) models. Independent variables of the regression consist of precipitation and other input measurements; the dependent variable is runoff. In models using erroneous input data, prediction errors are inflated and estimates of expected storm runoff for given observed input variables are biased. This bias in expected runoff estimation results in biased parameter estimates if these parameter estimates are obtained by a least squares fit of predicted to observed runoff values. The problems of error inflation and bias are examined in detail for a simple linear regression of runoff on rainfall and for a nonlinear U.S. Geological Survey precipitation-runoff model. Some implications for flood frequency analysis are considered. A case study using a set of data from Turtle Creek near Dallas, Texas illustrates the problems of model input errors.

Visual Inspection of Surfaces

NASA Technical Reports Server (NTRS)

Hughes, David; Perez, Xavier

2007-01-01

This presentation evaluates the parameters that affect visual inspection of cleanliness. Factors tested include surface reflectance, surface roughness, size of the largest particle, exposure time, inspector and distance from sample surface. It is concluded that distance predictions were not great, particularly because the distance at which contamination is seen may depend on more variables than those tested. Most parameters estimates had confidence of 95% or better, except for exposure and reflectance. Additionally, the distance at which surface is visibly contaminated decreases with increasing reflectance, roughness, and exposure. The distance at which the surface is visually contaminated increased with the largest particle size. These variables were only slightly affected the observer.

Square Root Graphical Models: Multivariate Generalizations of Univariate Exponential Families that Permit Positive Dependencies

PubMed Central

Inouye, David I.; Ravikumar, Pradeep; Dhillon, Inderjit S.

2016-01-01

We develop Square Root Graphical Models (SQR), a novel class of parametric graphical models that provides multivariate generalizations of univariate exponential family distributions. Previous multivariate graphical models (Yang et al., 2015) did not allow positive dependencies for the exponential and Poisson generalizations. However, in many real-world datasets, variables clearly have positive dependencies. For example, the airport delay time in New York—modeled as an exponential distribution—is positively related to the delay time in Boston. With this motivation, we give an example of our model class derived from the univariate exponential distribution that allows for almost arbitrary positive and negative dependencies with only a mild condition on the parameter matrix—a condition akin to the positive definiteness of the Gaussian covariance matrix. Our Poisson generalization allows for both positive and negative dependencies without any constraints on the parameter values. We also develop parameter estimation methods using node-wise regressions with ℓ1 regularization and likelihood approximation methods using sampling. Finally, we demonstrate our exponential generalization on a synthetic dataset and a real-world dataset of airport delay times. PMID:27563373

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

Morphometric variability of Arctodiaptomus salinus (Copepoda) in the Mediterranean-Black Sea region.

PubMed

Anufriieva, Elena V; Shadrin, Nickolai V

2015-11-18

Inter-species variability in morphological traits creates a need to know the range of variability of characteristics in the species for taxonomic and ecological tasks. Copepoda Arctodiaptomus salinus, which inhabits water bodies across Eurasia and North Africa, plays a dominant role in plankton of different water bodies-from fresh to hypersaline. This work assesses the intra- and inter-population morphometric variability of A. salinus in the Mediterranean-Black Sea region and discusses some observed regularities. The variability of linear body parameters and proportions was studied. The impacts of salinity, temperature, and population density on morphological characteristics and their variability can manifest themselves in different ways at the intra- and inter-population levels. A significant effect of salinity, pH and temperature on the body proportions was not found. Their intra-population variability is dependent on temperature and salinity. Sexual dimorphism of A. salinus manifests in different linear parameters, proportions, and their variability. There were no effects of temperature, pH and salinity on the female/male parameter ratio. There were significant differences in the body proportions of males and females in different populations. The influence of temperature, salinity, and population density can be attributed to 80%-90% of intra-population variability of A. salinus. However, these factors can explain less than 40% of inter-population differences. Significant differences in the body proportions of males and females from different populations may suggest that some local populations of A. salinus in the Mediterranean-Black Sea region are in the initial stages of differentiation.

VIIP Bedrest Analog Roadmap

NASA Technical Reports Server (NTRS)

Villarreal, Jennifer D.

2014-01-01

The objective is to define successive bed rest campaigns leading to a potential VIIP (Vision Impairment and Intracranial Pressure) countermeasure. To determine if the analog is successful, changes need to occur in the following outcome measures (dependent variables): Intracranial pressure; Retinal nerve fiber layer; Choroidal engorgement; Globe flattening; Axial biometry; Optic nerve sheath diameter distention; Cycloplegic refraction; Visual acuity. Study parameters (independent variables) to include: CO2; Sodium; Exercise (resistive & aerobic); Strict tilt angle.

INM Integrated Noise Model Version 2. Programmer’s Guide

DTIC Science & Technology

1979-09-01

cost, turnaround time, and system-dependent limitations. 3.2 CONVERSION PROBLEMS Item Item Item No. Desciption Category 1 BLOCK DATA Initialization IBM ...Restricted 2 Boolean Operations Differences Call Statement Parameters Extensions 4 Data Initialization IBM Restricted 5 ENTRY Differences 6 EQUIVALENCE...Machine Dependent 7 Format: A CDC Extension 8 Hollerith Strings IBM Restricted 9 Hollerith Variables IBM Restricted 10 Identifier Names CDC Extension

Variability of multilevel switching in scaled hybrid RS/CMOS nanoelectronic circuits: theory

NASA Astrophysics Data System (ADS)

Heittmann, Arne; Noll, Tobias G.

2013-07-01

A theory is presented which describes the variability of multilevel switching in scaled hybrid resistive-switching/CMOS nanoelectronic circuits. Variability is quantified in terms of conductance variation using the first two moments derived from the probability density function (PDF) of the RS conductance. For RS, which are based on the electrochemical metallization effect (ECM), this variability is - to some extent - caused by discrete events such as electrochemical reactions, which occur on atomic scale and are at random. The theory shows that the conductance variation depends on the joint interaction between the programming circuit and the resistive switch (RS), and explicitly quantifies the impact of RS device parameters and parameters of the programming circuit on the conductance variance. Using a current mirror as an exemplary programming circuit an upper limit of 2-4 bits (dependent on the filament surface area) is estimated as the storage capacity exploiting the multilevel capabilities of an ECM cell. The theoretical results were verified by Monte Carlo circuit simulations on a standard circuit simulation environment using an ECM device model which models the filament growth by a Poisson process. Contribution to the Topical Issue “International Semiconductor Conference Dresden-Grenoble - ISCDG 2012”, Edited by Gérard Ghibaudo, Francis Balestra and Simon Deleonibus.

Parameter Estimation with Almost No Public Communication for Continuous-Variable Quantum Key Distribution

NASA Astrophysics Data System (ADS)

Lupo, Cosmo; Ottaviani, Carlo; Papanastasiou, Panagiotis; Pirandola, Stefano

2018-06-01

One crucial step in any quantum key distribution (QKD) scheme is parameter estimation. In a typical QKD protocol the users have to sacrifice part of their raw data to estimate the parameters of the communication channel as, for example, the error rate. This introduces a trade-off between the secret key rate and the accuracy of parameter estimation in the finite-size regime. Here we show that continuous-variable QKD is not subject to this constraint as the whole raw keys can be used for both parameter estimation and secret key generation, without compromising the security. First, we show that this property holds for measurement-device-independent (MDI) protocols, as a consequence of the fact that in a MDI protocol the correlations between Alice and Bob are postselected by the measurement performed by an untrusted relay. This result is then extended beyond the MDI framework by exploiting the fact that MDI protocols can simulate device-dependent one-way QKD with arbitrarily high precision.

Three ingredients for Improved global aftershock forecasts: Tectonic region, time-dependent catalog incompleteness, and inter-sequence variability

USGS Publications Warehouse

Page, Morgan T.; Van Der Elst, Nicholas; Hardebeck, Jeanne L.; Felzer, Karen; Michael, Andrew J.

2016-01-01

Following a large earthquake, seismic hazard can be orders of magnitude higher than the long‐term average as a result of aftershock triggering. Because of this heightened hazard, emergency managers and the public demand rapid, authoritative, and reliable aftershock forecasts. In the past, U.S. Geological Survey (USGS) aftershock forecasts following large global earthquakes have been released on an ad hoc basis with inconsistent methods, and in some cases aftershock parameters adapted from California. To remedy this, the USGS is currently developing an automated aftershock product based on the Reasenberg and Jones (1989) method that will generate more accurate forecasts. To better capture spatial variations in aftershock productivity and decay, we estimate regional aftershock parameters for sequences within the García et al. (2012) tectonic regions. We find that regional variations for mean aftershock productivity reach almost a factor of 10. We also develop a method to account for the time‐dependent magnitude of completeness following large events in the catalog. In addition to estimating average sequence parameters within regions, we develop an inverse method to estimate the intersequence parameter variability. This allows for a more complete quantification of the forecast uncertainties and Bayesian updating of the forecast as sequence‐specific information becomes available.

The multi-parameter remote measurement of rainfall

NASA Technical Reports Server (NTRS)

Atlas, D.; Ulbrich, C. W.; Meneghini, R.

1982-01-01

The measurement of rainfall by remote sensors is investigated. One parameter radar rainfall measurement is limited because both reflectivity and rain rate are dependent on at least two parameters of the drop size distribution (DSD), i.e., representative raindrop size and number concentration. A generalized rain parameter diagram is developed which includes a third distribution parameter, the breadth of the DSD, to better specify rain rate and all possible remote variables. Simulations show the improvement in accuracy attainable through the use of combinations of two and three remote measurables. The spectrum of remote measurables is reviewed. These include path integrated techniques of radiometry and of microwave and optical attenuation.

Effect of elevation on extreme precipitation of short durations: evidences of orographic signature on the parameters of Depth-Duration-Frequency curves

NASA Astrophysics Data System (ADS)

Avanzi, Francesco; De Michele, Carlo; Gabriele, Salvatore; Ghezzi, Antonio; Rosso, Renzo

2015-04-01

Here, we show how atmospheric circulation and topography rule the variability of depth-duration-frequency (DDF) curves parameters, and we discuss how this variability has physical implications on the formation of extreme precipitations at high elevations. A DDF is a curve ruling the value of the maximum annual precipitation H as a function of duration D and the level of probability F. We consider around 1500 stations over the Italian territory, with at least 20 years of data of maximum annual precipitation depth at different durations. We estimated the DDF parameters at each location by using the asymptotic distribution of extreme values, i.e. the so-called Generalized Extreme Value (GEV) distribution, and considering a statistical simple scale invariance hypothesis. Consequently, a DDF curve depends on five different parameters. A first set relates H with the duration (namely, the mean value of annual maximum precipitation depth for unit duration and the scaling exponent), while a second set links H to F (namely, a scale, position and shape parameter). The value of the shape parameter has consequences on the type of random variable (unbounded, upper or lower bounded). This extensive analysis shows that the variability of the mean value of annual maximum precipitation depth for unit duration obeys to the coupled effect of topography and modal direction of moisture flux during extreme events. Median values of this parameter decrease with elevation. We called this phenomenon "reverse orographic effect" on extreme precipitation of short durations, since it is in contrast with general knowledge about the orographic effect on mean precipitation. Moreover, the scaling exponent is mainly driven by topography alone (with increasing values of this parameter at increasing elevations). Therefore, the quantiles of H(D,F) at durations greater than unit turn to be more variable at high elevations than at low elevations. Additionally, the analysis of the variability of the shape parameter with elevation shows that extreme events at high elevations appear to be distributed according to an upper bounded probability distribution. These evidences could be a characteristic sign of the formation of extreme precipitation events at high elevations.

Effect of reference conditions on flow rate, modifier fraction and retention in supercritical fluid chromatography.

PubMed

De Pauw, Ruben; Shoykhet Choikhet, Konstantin; Desmet, Gert; Broeckhoven, Ken

2016-08-12

When using compressible mobile phases such as fluidic CO2, the density, the volumetric flow rates and volumetric fractions are pressure dependent. The pressure and temperature definition of these volumetric parameters (referred to as the reference conditions) may alter between systems, manufacturers and operating conditions. A supercritical fluid chromatography system was modified to operate in two modes with different definition of the eluent delivery parameters, referred to as fixed and variable mode. For the variable mode, the volumetric parameters are defined with reference to the pump operating pressure and actual pump head temperature. These conditions may vary when, e.g. changing the column length, permeability, flow rate, etc. and are thus variable reference conditions. For the fixed mode, the reference conditions were set at 150bar and 30°C, resulting in a mass flow rate and mass fraction of modifier definition which is independent of the operation conditions. For the variable mode, the mass flow rate of carbon dioxide increases with system pump operating pressure, decreasing the fraction of modifier. Comparing the void times and retention factor shows that the deviation between the two modes is almost independent of modifier percentage, but depends on the operating pressure. Recalculating the set volumetric fraction of modifier to the mass fraction results in the same retention behaviour for both modes. This shows that retention in SFC can be best modelled using the mass fraction of modifier. The fixed mode also simplifies method scaling as it only requires matching average column pressure. Copyright © 2016 Elsevier B.V. All rights reserved.

Temperature and depth dependence of positron annihilation parameters in YBa2Cu3O7-x and La1.85Sr0.15CuO4

NASA Astrophysics Data System (ADS)

Lynn, K. G.; Usmar, S. G.; Nielsen, B.; van der Kolk, G. J.; Kanazawa, I.; Sferlazzo, P.; Moodenbaugh, A. R.

1988-02-01

The temperature dependence of the positron annihilation parameters for YBa2Cu3O7-x x=0.7, 0.4 and 0.0 and La1.85Sr0.15CuO4 were measured. The depth dependence of the YBa2Cu3O7 was studied using a variable-energy positron beam showing a strong depth dependence in the Doppler line-shape extending up to an average depth of ˜5.0 μm. It was found that a transition in the Doppler line-shape parameter, ``S'', was associated with the superconducting transition temperature (Tc) in YBa2Cu3O7-x x=0.4 and 0.0 while no transition was observed in the nonsuperconducting YBa2Cu3O6.3. Positron lifetime parameters in YBa2Cu3O7 were found to be consistent with positrons localized at open volume regions (probably unoccupied crystallographic sites) in this material with a lifetime of 210 psec at 300 K. These results indicate that the electron density at these unoccupied sites increases, using a free electron model, approximately 9% between 100 and 12 K.

Developing population models with data from marked individuals

USGS Publications Warehouse

Hae Yeong Ryu,; Kevin T. Shoemaker,; Eva Kneip,; Anna Pidgeon,; Patricia Heglund,; Brooke Bateman,; Thogmartin, Wayne E.; Reşit Akçakaya,

2016-01-01

Population viability analysis (PVA) is a powerful tool for biodiversity assessments, but its use has been limited because of the requirements for fully specified population models such as demographic structure, density-dependence, environmental stochasticity, and specification of uncertainties. Developing a fully specified population model from commonly available data sources – notably, mark–recapture studies – remains complicated due to lack of practical methods for estimating fecundity, true survival (as opposed to apparent survival), natural temporal variability in both survival and fecundity, density-dependence in the demographic parameters, and uncertainty in model parameters. We present a general method that estimates all the key parameters required to specify a stochastic, matrix-based population model, constructed using a long-term mark–recapture dataset. Unlike standard mark–recapture analyses, our approach provides estimates of true survival rates and fecundities, their respective natural temporal variabilities, and density-dependence functions, making it possible to construct a population model for long-term projection of population dynamics. Furthermore, our method includes a formal quantification of parameter uncertainty for global (multivariate) sensitivity analysis. We apply this approach to 9 bird species and demonstrate the feasibility of using data from the Monitoring Avian Productivity and Survivorship (MAPS) program. Bias-correction factors for raw estimates of survival and fecundity derived from mark–recapture data (apparent survival and juvenile:adult ratio, respectively) were non-negligible, and corrected parameters were generally more biologically reasonable than their uncorrected counterparts. Our method allows the development of fully specified stochastic population models using a single, widely available data source, substantially reducing the barriers that have until now limited the widespread application of PVA. This method is expected to greatly enhance our understanding of the processes underlying population dynamics and our ability to analyze viability and project trends for species of conservation concern.

Assessing locomotor skills development in childhood using wearable inertial sensor devices: the running paradigm.

PubMed

Masci, Ilaria; Vannozzi, Giuseppe; Bergamini, Elena; Pesce, Caterina; Getchell, Nancy; Cappozzo, Aurelio

2013-04-01

Objective quantitative evaluation of motor skill development is of increasing importance to carefully drive physical exercise programs in childhood. Running is a fundamental motor skill humans adopt to accomplish locomotion, which is linked to physical activity levels, although the assessment is traditionally carried out using qualitative evaluation tests. The present study aimed at investigating the feasibility of using inertial sensors to quantify developmental differences in the running pattern of young children. Qualitative and quantitative assessment tools were adopted to identify a skill-sensitive set of biomechanical parameters for running and to further our understanding of the factors that determine progression to skilled running performance. Running performances of 54 children between the ages of 2 and 12 years were submitted to both qualitative and quantitative analysis, the former using sequences of developmental level, the latter estimating temporal and kinematic parameters from inertial sensor measurements. Discriminant analysis with running developmental level as dependent variable allowed to identify a set of temporal and kinematic parameters, within those obtained with the sensor, that best classified children into the qualitative developmental levels (accuracy higher than 67%). Multivariate analysis of variance with the quantitative parameters as dependent variables allowed to identify whether and which specific parameters or parameter subsets were differentially sensitive to specific transitions between contiguous developmental levels. The findings showed that different sets of temporal and kinematic parameters are able to tap all steps of the transitional process in running skill described through qualitative observation and can be prospectively used for applied diagnostic and sport training purposes. Copyright © 2012 Elsevier B.V. All rights reserved.

Metocean design parameter estimation for fixed platform based on copula functions

NASA Astrophysics Data System (ADS)

Zhai, Jinjin; Yin, Qilin; Dong, Sheng

2017-08-01

Considering the dependent relationship among wave height, wind speed, and current velocity, we construct novel trivariate joint probability distributions via Archimedean copula functions. Total 30-year data of wave height, wind speed, and current velocity in the Bohai Sea are hindcast and sampled for case study. Four kinds of distributions, namely, Gumbel distribution, lognormal distribution, Weibull distribution, and Pearson Type III distribution, are candidate models for marginal distributions of wave height, wind speed, and current velocity. The Pearson Type III distribution is selected as the optimal model. Bivariate and trivariate probability distributions of these environmental conditions are established based on four bivariate and trivariate Archimedean copulas, namely, Clayton, Frank, Gumbel-Hougaard, and Ali-Mikhail-Haq copulas. These joint probability models can maximize marginal information and the dependence among the three variables. The design return values of these three variables can be obtained by three methods: univariate probability, conditional probability, and joint probability. The joint return periods of different load combinations are estimated by the proposed models. Platform responses (including base shear, overturning moment, and deck displacement) are further calculated. For the same return period, the design values of wave height, wind speed, and current velocity obtained by the conditional and joint probability models are much smaller than those by univariate probability. Considering the dependence among variables, the multivariate probability distributions provide close design parameters to actual sea state for ocean platform design.

Mid-Infrared Lifetime Imaging for Viability Evaluation of Lettuce Seeds Based on Time-Dependent Thermal Decay Characterization

PubMed Central

Kim, Ghiseok; Kim, Geon Hee; Ahn, Chi-Kook; Yoo, Yoonkyu; Cho, Byoung-Kwan

2013-01-01

An infrared lifetime thermal imaging technique for the measurement of lettuce seed viability was evaluated. Thermal emission signals from mid-infrared images of healthy seeds and seeds aged for 24, 48, and 72 h were obtained and reconstructed using regression analysis. The emission signals were fitted with a two-term exponential model that had two amplitudes and two time variables as lifetime parameters. The lifetime thermal decay parameters were significantly different for seeds with different aging times. Single-seed viability was visualized using thermal lifetime images constructed from the calculated lifetime parameter values. The time-dependent thermal signal decay characteristics, along with the decay amplitude and delay time images, can be used to distinguish aged lettuce seeds from normal seeds. PMID:23529120

Study the Cyclic Plasticity Behavior of 508 LAS under Constant, Variable and Grid-Load-Following Loading Cycles for Fatigue Evaluation of PWR Components

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

Mohanty, Subhasish; Barua, Bipul; Soppet, William K.

This report provides an update of an earlier assessment of environmentally assisted fatigue for components in light water reactors. This report is a deliverable in September 2016 under the work package for environmentally assisted fatigue under DOE’s Light Water Reactor Sustainability program. In an April 2016 report, we presented a detailed thermal-mechanical stress analysis model for simulating the stress-strain state of a reactor pressure vessel and its nozzles under grid-load-following conditions. In this report, we provide stress-controlled fatigue test data for 508 LAS base metal alloy under different loading amplitudes (constant, variable, and random grid-load-following) and environmental conditions (in airmore » or pressurized water reactor coolant water at 300°C). Also presented is a cyclic plasticity-based analytical model that can simultaneously capture the amplitude and time dependency of the component behavior under fatigue loading. Results related to both amplitude-dependent and amplitude-independent parameters are presented. The validation results for the analytical/mechanistic model are discussed. This report provides guidance for estimating time-dependent, amplitude-independent parameters related to material behavior under different service conditions. The developed mechanistic models and the reported material parameters can be used to conduct more accurate fatigue and ratcheting evaluation of reactor components.« less

Characterizing scale- and location-dependent correlation of water retention parameters with soil physical properties using wavelet techniques.

PubMed

Shu, Qiaosheng; Liu, Zuoxin; Si, Bingcheng

2008-01-01

Understanding the correlation between soil hydraulic parameters and soil physical properties is a prerequisite for the prediction of soil hydraulic properties from soil physical properties. The objective of this study was to examine the scale- and location-dependent correlation between two water retention parameters (alpha and n) in the van Genuchten (1980) function and soil physical properties (sand content, bulk density [Bd], and organic carbon content) using wavelet techniques. Soil samples were collected from a transect from Fuxin, China. Soil water retention curves were measured, and the van Genuchten parameters were obtained through curve fitting. Wavelet coherency analysis was used to elucidate the location- and scale-dependent relationships between these parameters and soil physical properties. Results showed that the wavelet coherence between alpha and sand content was significantly different from red noise at small scales (8-20 m) and from a distance of 30 to 470 m. Their wavelet phase spectrum was predominantly out of phase, indicating negative correlation between these two variables. The strong negative correlation between alpha and Bd existed mainly at medium scales (30-80 m). However, parameter n had a strong positive correlation only with Bd at scales between 20 and 80 m. Neither of the two retention parameters had significant wavelet coherency with organic carbon content. These results suggested that location-dependent scale analyses are necessary to improve the performance for soil water retention characteristic predictions.

Relevance of anisotropy and spatial variability of gas diffusivity for soil-gas transport

NASA Astrophysics Data System (ADS)

Schack-Kirchner, Helmer; Kühne, Anke; Lang, Friederike

2017-04-01

Models of soil gas transport generally do not consider neither direction dependence of gas diffusivity, nor its small-scale variability. However, in a recent study, we could provide evidence for anisotropy favouring vertical gas diffusion in natural soils. We hypothesize that gas transport models based on gas diffusion data measured with soil rings are strongly influenced by both, anisotropy and spatial variability and the use of averaged diffusivities could be misleading. To test this we used a 2-dimensional model of soil gas transport to under compacted wheel tracks to model the soil-air oxygen distribution in the soil. The model was parametrized with data obtained from soil-ring measurements with its central tendency and variability. The model includes vertical parameter variability as well as variation perpendicular to the elongated wheel track. Different parametrization types have been tested: [i)]Averaged values for wheel track and undisturbed. em [ii)]Random distribution of soil cells with normally distributed variability within the strata. em [iii)]Random distributed soil cells with uniformly distributed variability within the strata. All three types of small-scale variability has been tested for [j)] isotropic gas diffusivity and em [jj)]reduced horizontal gas diffusivity (constant factor), yielding in total six models. As expected the different parametrizations had an important influence to the aeration state under wheel tracks with the strongest oxygen depletion in case of uniformly distributed variability and anisotropy towards higher vertical diffusivity. The simple simulation approach clearly showed the relevance of anisotropy and spatial variability in case of identical central tendency measures of gas diffusivity. However, until now it did not consider spatial dependency of variability, that could even aggravate effects. To consider anisotropy and spatial variability in gas transport models we recommend a) to measure soil-gas transport parameters spatially explicit including different directions and b) to use random-field stochastic models to assess the possible effects for gas-exchange models.

Measurement of event shape variables in deep inelastic e p scattering

NASA Astrophysics Data System (ADS)

Adloff, C.; Aid, S.; Anderson, M.; Andreev, V.; Andrieu, B.; Arkadov, V.; Arndt, C.; Ayyaz, I.; Babaev, A.; Bähr, J.; Bán, J.; Baranov, P.; Barrelet, E.; Barschke, R.; Bartel, W.; Bassler, U.; Beck, H. P.; Beck, M.; Behrend, H.-J.; Belousov, A.; Berger, Ch.; Bernardi, G.; Bertrand-Coremans, G.; Beyer, R.; Biddulph, P.; Bizot, J. C.; Borras, K.; Botterweck, F.; Boudry, V.; Bourov, S.; Braemer, A.; Braunschweig, W.; Brisson, V.; Brown, D. P.; Brückner, W.; Bruel, P.; Bruncko, D.; Brune, C.; Bürger, J.; Büsser, F. W.; Buniatian, A.; Burke, S.; Buschhorn, G.; Calvet, D.; Campbell, A. J.; Carli, T.; Charlet, M.; Clarke, D.; Clerbaux, B.; Cocks, S.; Contreras, J. G.; Cormack, C.; Coughlan, J. A.; Cousinou, M.-C.; Cox, B. E.; Cozzika, G.; Cussans, D. G.; Cvach, J.; Dagoret, S.; Dainton, J. B.; Dau, W. D.; Daum, K.; David, M.; de Roeck, A.; de Wolf, E. A.; Delcourt, B.; Dirkmann, M.; Dixon, P.; Dlugosz, W.; Dollfus, C.; Donovan, K. T.; Dowell, J. D.; Dreis, H. B.; Droutskoi, A.; Ebert, J.; Ebert, T. R.; Eckerlin, G.; Efremenko, V.; Egli, S.; Eichler, R.; Eisele, F.; Eisenhandler, E.; Elsen, E.; Erdmann, M.; Fahr, A. B.; Favart, L.; Fedotov, A.; Felst, R.; Feltesse, J.; Ferencei, J.; Ferrarotto, F.; Flamm, K.; Fleischer, M.; Flieser, M.; Flügge, G.; Fomenko, A.; Formánek, J.; Foster, J. M.; Franke, G.; Gabathuler, E.; Gabathuler, K.; Gaede, F.; Garvey, J.; Gayler, J.; Gebauer, M.; Gerhards, R.; Glazov, A.; Goerlich, L.; Gogitidze, N.; Goldberg, M.; Gonzalez-Pineiro, B.; Gorelov, I.; Grab, C.; Grässler, H.; Greenshaw, T.; Griffiths, R. K.; Grindhammer, G.; Gruber, A.; Gruber, C.; Hadig, T.; Haidt, D.; Hajduk, L.; Haller, T.; Hampel, M.; Haynes, W. J.; Heinemann, B.; Heinzelmann, G.; Henderson, R. C. W.; Hengstmann, S.; Henschel, H.; Herynek, I.; Hess, M. F.; Hewitt, K.; Hiller, K. H.; Hilton, C. D.; Hladký, J.; Höppner, M.; Hoffmann, D.; Holtom, T.; Horisberger, R.; Hudgson, V. L.; Hütte, M.; Ibbotson, M.; İşsever, Ç.; Itterbeck, H.; Jacquet, M.; Jaffre, M.; Janoth, J.; Jansen, D. M.; Jönsson, L.; Johnson, D. P.; Jung, H.; Kalmus, P. I. P.; Kander, M.; Kant, D.; Kathage, U.; Katzy, J.; Kaufmann, H. H.; Kaufmann, O.; Kausch, M.; Kazarian, S.; Kenyon, I. R.; Kermiche, S.; Keuker, C.; Kiesling, C.; Klein, M.; Kleinwort, C.; Knies, G.; Köhler, T.; Köhne, J. H.; Kolanoski, H.; Kolya, S. D.; Korbel, V.; Kostka, P.; Kotelnikov, S. K.; Krämerkämper, T.; Krasny, M. W.; Krehbiel, H.; Krücker, D.; Küpper, A.; Küster, H.; Kuhlen, M.; Kurča, T.; Laforge, B.; Landon, M. P. J.; Lange, W.; Langenegger, U.; Lebedev, A.; Lehner, F.; Lemaitre, V.; Levonian, S.; Lindstroem, M.; Linsel, F.; Lipinski, J.; List, B.; Lobo, G.; Lopez, G. C.; Lubimov, V.; Lüke, D.; Lytkin, L.; Magnussen, N.; Mahlke-Krüger, H.; Malinovski, E.; Maraček, R.; Marage, P.; Marks, J.; Marshall, R.; Martens, J.; Martin, G.; Martin, R.; Martyn, H.-U.; Martyniak, J.; Mavroidis, T.; Maxfield, S. J.; McMahon, S. J.; Mehta, A.; Meier, K.; Merkel, P.; Metlica, F.; Meyer, A.; Meyer, A.; Meyer, H.; Meyer, J.; Meyer, P.-O.; Migliori, A.; Mikocki, S.; Milstead, D.; Moeck, J.; Moreau, F.; Morris, J. V.; Mroczko, E.; Müller, D.; Müller, K.; Murín, P.; Nagovizin, V.; Nahnhauer, R.; Naroska, B.; Naumann, Th.; Négri, I.; Newman, P. R.; Newton, D.; Nguyen, H. K.; Nicholls, T. C.; Niebergall, F.; Niebuhr, C.; Niedzballa, Ch.; Niggli, H.; Nowak, G.; Nunnemann, T.; Oberlack, H.; Olsson, J. E.; Ozerov, D.; Palmen, P.; Panaro, E.; Panitch, A.; Pascaud, C.; Passaggio, S.; Patel, G. D.; Pawletta, H.; Peppel, E.; Perez, E.; Phillips, J. P.; Pieuchot, A.; Pitzl, D.; Pöschl, R.; Pope, G.; Povh, B.; Rabbertz, K.; Reimer, P.; Rick, H.; Reiss, S.; Rizvi, E.; Robmann, P.; Roosen, R.; Rosenbauer, K.; Rostovtsev, A.; Rouse, F.; Royon, C.; Rüter, K.; Rusakov, S.; Rybicki, K.; Sankey, D. P. C.; Schacht, P.; Schiek, S.; Schleif, S.; Schleper, P.; von Schlippe, W.; Schmidt, D.; Schmidt, G.; Schoeffel, L.; Schöning, A.; Schröder, V.; Schuhmann, E.; Schwab, B.; Sefkow, F.; Semenov, A.; Shekelyan, V.; Sheviakov, I.; Shtarkov, L. N.; Siegmon, G.; Siewert, U.; Sirois, Y.; Skillicorn, I. O.; Sloan, T.; Smirnov, P.; Smith, M.; Solochenko, V.; Soloviev, Y.; Specka, A.; Spiekermann, J.; Spielman, S.; Spitzer, H.; Squinabol, F.; Steffen, P.; Steinberg, R.; Steinhart, J.; Stella, B.; Stellberger, A.; Stiewe, J.; Stößlein, U.; Stolze, K.; Straumann, U.; Struczinski, W.; Sutton, J. P.; Tapprogge, S.; Taševský, M.; Tchernyshov, V.; Tchetchelnitski, S.; Theissen, J.; Thompson, G.; Thompson, P. D.; Tobien, N.; Todenhagen, R.; Truöl, P.; Tsipolitis, G.; Turnau, J.; Tzamariudaki, E.; Uelkes, P.; Usik, A.; Valkár, S.; Valkárová, A.; Vallée, C.; van Esch, P.; van Mechelen, P.; Vandenplas, D.; Vazdik, Y.; Verrecchia, P.; Villet, G.; Wacker, K.; Wagener, A.; Wagener, M.; Wallny, R.; Walter, T.; Waugh, B.; Weber, G.; Weber, M.; Wegener, D.; Wegner, A.; Wengler, T.; Werner, M.; West, L. R.; Wiesand, S.; Wilksen, T.; Willard, S.; Winde, M.; Winter, G.-G.; Wittek, C.; Wobisch, M.; Wollatz, H.; Wünsch, E.; ŽáČek, J.; Zarbock, D.; Zhang, Z.; Zhokin, A.; Zini, P.; Zomer, F.; Zsembery, J.; Zurnedden, M.

1997-02-01

Deep inelastic e p scattering data, taken with the H1 detector at HERA, are used to study the event shape variables thrust, jet broadening and jet mass in the current hemisphere of the Breit frame over a large range of momentum transfers Q between 7 GeV and 100 GeV. The data are compared with results from e+e- experiments. Using second order QCD calculations and an approach to relate hadronisation effects to power corrections an analysis of the Q dependences of the means of the event shape parameters is presented, from which both the power corrections and the strong coupling constant are determined without any assumption on fragmentation models. The power corrections of all event shape variables investigated follow a 1/Q behaviour and can be described by a common parameter α0.

R programming for parameters estimation of geographically weighted ordinal logistic regression (GWOLR) model based on Newton Raphson

NASA Astrophysics Data System (ADS)

Zuhdi, Shaifudin; Saputro, Dewi Retno Sari

2017-03-01

GWOLR model used for represent relationship between dependent variable has categories and scale of category is ordinal with independent variable influenced the geographical location of the observation site. Parameters estimation of GWOLR model use maximum likelihood provide system of nonlinear equations and hard to be found the result in analytic resolution. By finishing it, it means determine the maximum completion, this thing associated with optimizing problem. The completion nonlinear system of equations optimize use numerical approximation, which one is Newton Raphson method. The purpose of this research is to make iteration algorithm Newton Raphson and program using R software to estimate GWOLR model. Based on the research obtained that program in R can be used to estimate the parameters of GWOLR model by forming a syntax program with command "while".

Applications of Black Scholes Complexity Concepts to Combat Modelling

DTIC Science & Technology

2009-03-01

Lauren, G C McIntosh, N D Perry and J Moffat, Chaos 17, 2007. 4 Lanchester Models of Warfare Volumes 1 and 2, J G Taylor, Operations Research Society...transformation matrix A Lanchester Equation solution parameter bi Dependent model variables b(x,t) Variable variance rate B Lanchester Equation solution...distribution. The similarity between this equation and the Lanchester Equations (equation 1) is clear. This suggests an obvious solution to the question of

Predictive factors in patients with hepatocellular carcinoma receiving sorafenib therapy using time-dependent receiver operating characteristic analysis.

PubMed

Nishikawa, Hiroki; Nishijima, Norihiro; Enomoto, Hirayuki; Sakamoto, Azusa; Nasu, Akihiro; Komekado, Hideyuki; Nishimura, Takashi; Kita, Ryuichi; Kimura, Toru; Iijima, Hiroko; Nishiguchi, Shuhei; Osaki, Yukio

2017-01-01

To investigate variables before sorafenib therapy on the clinical outcomes in hepatocellular carcinoma (HCC) patients receiving sorafenib and to further assess and compare the predictive performance of continuous parameters using time-dependent receiver operating characteristics (ROC) analysis. A total of 225 HCC patients were analyzed. We retrospectively examined factors related to overall survival (OS) and progression free survival (PFS) using univariate and multivariate analyses. Subsequently, we performed time-dependent ROC analysis of continuous parameters which were significant in the multivariate analysis in terms of OS and PFS. Total sum of area under the ROC in all time points (defined as TAAT score) in each case was calculated. Our cohort included 175 male and 50 female patients (median age, 72 years) and included 158 Child-Pugh A and 67 Child-Pugh B patients. The median OS time was 0.68 years, while the median PFS time was 0.24 years. On multivariate analysis, gender, body mass index (BMI), Child-Pugh classification, extrahepatic metastases, tumor burden, aspartate aminotransferase (AST) and alpha-fetoprotein (AFP) were identified as significant predictors of OS and ECOG-performance status, Child-Pugh classification and extrahepatic metastases were identified as significant predictors of PFS. Among three continuous variables (i.e., BMI, AST and AFP), AFP had the highest TAAT score for the entire cohort. In subgroup analyses, AFP had the highest TAAT score except for Child-Pugh B and female among three continuous variables. In continuous variables, AFP could have higher predictive accuracy for survival in HCC patients undergoing sorafenib therapy.

A viscoelastic damage rheology and rate- and state-dependent friction

NASA Astrophysics Data System (ADS)

Lyakhovsky, Vladimir; Ben-Zion, Yehuda; Agnon, Amotz

2005-04-01

We analyse the relations between a viscoelastic damage rheology model and rate- and state-dependent (RS) friction. Both frameworks describe brittle deformation, although the former models localization zones in a deforming volume while the latter is associated with sliding on existing surfaces. The viscoelastic damage model accounts for evolving elastic properties and inelastic strain. The evolving elastic properties are related quantitatively to a damage state variable representing the local density of microcracks. Positive and negative changes of the damage variable lead, respectively, to degradation and recovery of the material in response to loading. A model configuration having an existing narrow zone with localized damage produces for appropriate loading and temperature-pressure conditions an overall cyclic stick-slip motion compatible with a frictional response. Each deformation cycle (limit cycle) can be divided into healing and weakening periods associated with decreasing and increasing damage, respectively. The direct effect of the RS friction and the magnitude of the frictional parameter a are related to material strengthening with increasing rate of loading. The strength and residence time of asperities (model elements) in the weakening stage depend on the rates of damage evolution and accumulation of irreversible strain. The evolutionary effect of the RS friction and overall change in the friction parameters (a-b) are controlled by the duration of the healing period and asperity (element) strengthening during this stage. For a model with spatially variable properties, the damage rheology reproduces the logarithmic dependency of the steady-state friction coefficient on the sliding velocity and the normal stress. The transition from a velocity strengthening regime to a velocity weakening one can be obtained by varying the rate of inelastic strain accumulation and keeping the other damage rheology parameters fixed. The developments unify previous damage rheology results on deformation localization leading to formation of new fault zones with detailed experimental results on frictional sliding. The results provide a route for extending the formulation of RS friction into a non-linear continuum mechanics framework.

Stochastic and Statistical Analysis of Utility Revenues and Weather Data Analysis for Consumer Demand Estimation in Smart Grids

PubMed Central

Ali, S. M.; Mehmood, C. A; Khan, B.; Jawad, M.; Farid, U; Jadoon, J. K.; Ali, M.; Tareen, N. K.; Usman, S.; Majid, M.; Anwar, S. M.

2016-01-01

In smart grid paradigm, the consumer demands are random and time-dependent, owning towards stochastic probabilities. The stochastically varying consumer demands have put the policy makers and supplying agencies in a demanding position for optimal generation management. The utility revenue functions are highly dependent on the consumer deterministic stochastic demand models. The sudden drifts in weather parameters effects the living standards of the consumers that in turn influence the power demands. Considering above, we analyzed stochastically and statistically the effect of random consumer demands on the fixed and variable revenues of the electrical utilities. Our work presented the Multi-Variate Gaussian Distribution Function (MVGDF) probabilistic model of the utility revenues with time-dependent consumer random demands. Moreover, the Gaussian probabilities outcome of the utility revenues is based on the varying consumer n demands data-pattern. Furthermore, Standard Monte Carlo (SMC) simulations are performed that validated the factor of accuracy in the aforesaid probabilistic demand-revenue model. We critically analyzed the effect of weather data parameters on consumer demands using correlation and multi-linear regression schemes. The statistical analysis of consumer demands provided a relationship between dependent (demand) and independent variables (weather data) for utility load management, generation control, and network expansion. PMID:27314229

Stochastic and Statistical Analysis of Utility Revenues and Weather Data Analysis for Consumer Demand Estimation in Smart Grids.

PubMed

Ali, S M; Mehmood, C A; Khan, B; Jawad, M; Farid, U; Jadoon, J K; Ali, M; Tareen, N K; Usman, S; Majid, M; Anwar, S M

2016-01-01

In smart grid paradigm, the consumer demands are random and time-dependent, owning towards stochastic probabilities. The stochastically varying consumer demands have put the policy makers and supplying agencies in a demanding position for optimal generation management. The utility revenue functions are highly dependent on the consumer deterministic stochastic demand models. The sudden drifts in weather parameters effects the living standards of the consumers that in turn influence the power demands. Considering above, we analyzed stochastically and statistically the effect of random consumer demands on the fixed and variable revenues of the electrical utilities. Our work presented the Multi-Variate Gaussian Distribution Function (MVGDF) probabilistic model of the utility revenues with time-dependent consumer random demands. Moreover, the Gaussian probabilities outcome of the utility revenues is based on the varying consumer n demands data-pattern. Furthermore, Standard Monte Carlo (SMC) simulations are performed that validated the factor of accuracy in the aforesaid probabilistic demand-revenue model. We critically analyzed the effect of weather data parameters on consumer demands using correlation and multi-linear regression schemes. The statistical analysis of consumer demands provided a relationship between dependent (demand) and independent variables (weather data) for utility load management, generation control, and network expansion.

Evolution of stochastic demography with life history tradeoffs in density-dependent age-structured populations.

PubMed

Lande, Russell; Engen, Steinar; Sæther, Bernt-Erik

2017-10-31

We analyze the stochastic demography and evolution of a density-dependent age- (or stage-) structured population in a fluctuating environment. A positive linear combination of age classes (e.g., weighted by body mass) is assumed to act as the single variable of population size, [Formula: see text], exerting density dependence on age-specific vital rates through an increasing function of population size. The environment fluctuates in a stationary distribution with no autocorrelation. We show by analysis and simulation of age structure, under assumptions often met by vertebrate populations, that the stochastic dynamics of population size can be accurately approximated by a univariate model governed by three key demographic parameters: the intrinsic rate of increase and carrying capacity in the average environment, [Formula: see text] and [Formula: see text], and the environmental variance in population growth rate, [Formula: see text] Allowing these parameters to be genetically variable and to evolve, but assuming that a fourth parameter, [Formula: see text], measuring the nonlinearity of density dependence, remains constant, the expected evolution maximizes [Formula: see text] This shows that the magnitude of environmental stochasticity governs the classical trade-off between selection for higher [Formula: see text] versus higher [Formula: see text] However, selection also acts to decrease [Formula: see text], so the simple life-history trade-off between [Formula: see text]- and [Formula: see text]-selection may be obscured by additional trade-offs between them and [Formula: see text] Under the classical logistic model of population growth with linear density dependence ([Formula: see text]), life-history evolution in a fluctuating environment tends to maximize the average population size. Published under the PNAS license.

Can statistical linkage of missing variables reduce bias in treatment effect estimates in comparative effectiveness research studies?

PubMed

Crown, William; Chang, Jessica; Olson, Melvin; Kahler, Kristijan; Swindle, Jason; Buzinec, Paul; Shah, Nilay; Borah, Bijan

2015-09-01

Missing data, particularly missing variables, can create serious analytic challenges in observational comparative effectiveness research studies. Statistical linkage of datasets is a potential method for incorporating missing variables. Prior studies have focused upon the bias introduced by imperfect linkage. This analysis uses a case study of hepatitis C patients to estimate the net effect of statistical linkage on bias, also accounting for the potential reduction in missing variable bias. The results show that statistical linkage can reduce bias while also enabling parameter estimates to be obtained for the formerly missing variables. The usefulness of statistical linkage will vary depending upon the strength of the correlations of the missing variables with the treatment variable, as well as the outcome variable of interest.

Multivariate Longitudinal Analysis with Bivariate Correlation Test

PubMed Central

Adjakossa, Eric Houngla; Sadissou, Ibrahim; Hounkonnou, Mahouton Norbert; Nuel, Gregory

2016-01-01

In the context of multivariate multilevel data analysis, this paper focuses on the multivariate linear mixed-effects model, including all the correlations between the random effects when the dimensional residual terms are assumed uncorrelated. Using the EM algorithm, we suggest more general expressions of the model’s parameters estimators. These estimators can be used in the framework of the multivariate longitudinal data analysis as well as in the more general context of the analysis of multivariate multilevel data. By using a likelihood ratio test, we test the significance of the correlations between the random effects of two dependent variables of the model, in order to investigate whether or not it is useful to model these dependent variables jointly. Simulation studies are done to assess both the parameter recovery performance of the EM estimators and the power of the test. Using two empirical data sets which are of longitudinal multivariate type and multivariate multilevel type, respectively, the usefulness of the test is illustrated. PMID:27537692

Multivariate Longitudinal Analysis with Bivariate Correlation Test.

PubMed

Adjakossa, Eric Houngla; Sadissou, Ibrahim; Hounkonnou, Mahouton Norbert; Nuel, Gregory

2016-01-01

In the context of multivariate multilevel data analysis, this paper focuses on the multivariate linear mixed-effects model, including all the correlations between the random effects when the dimensional residual terms are assumed uncorrelated. Using the EM algorithm, we suggest more general expressions of the model's parameters estimators. These estimators can be used in the framework of the multivariate longitudinal data analysis as well as in the more general context of the analysis of multivariate multilevel data. By using a likelihood ratio test, we test the significance of the correlations between the random effects of two dependent variables of the model, in order to investigate whether or not it is useful to model these dependent variables jointly. Simulation studies are done to assess both the parameter recovery performance of the EM estimators and the power of the test. Using two empirical data sets which are of longitudinal multivariate type and multivariate multilevel type, respectively, the usefulness of the test is illustrated.

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

Nagayama, K., E-mail: nagayama@aero.kyushu-u.ac.jp

The dimensionless material parameter R introduced by Wu and Jing into the Rice-Walsh equation of state (EOS) has been deduced from the LASL shock Hugoniot data for porous Al and Cu. It was found that the parameter R/p decays smoothly with shock pressure p and displays small experimental scatter in the high pressure region. This finding led to the conclusion that the parameter has only a weak temperature dependence and is well approximated by a function of pressure alone, and the Grüneisen parameter should be temperature dependent under compression. The thermodynamic formulation of the Rice-Walsh EOS for Al and Cumore » was realized using the empirically determined function R(p) for each material and their known shock Hugoniot. It was then possible to reproduce porous shock Hugoniot for these metals. For most degrees of porosity, agreement between the porous data and the calculated Hugoniots using the empirical function described was very good. However, slight discrepancies were seen for Hugoniots with very high porosity. Two new thermal variables were introduced after further analysis, which enabled the calculation of the cold compression curve for these metals. The Grüneisen parameters along full-density and porous Hugoniot curve were calculated using a thermodynamic identity connecting R and the Grüneisen parameter. It was shown that the Grüneisen parameter is strongly temperature dependent. The present analysis suggested that the Rice-Walsh type EOS is a preferable choice for the analysis with its simple form, pressure-dependent empirical Wu-Jing parameter, and its compatibility with porous shock data.« less

Quasar spectral variability from the XMM-Newton serendipitous source catalogue

NASA Astrophysics Data System (ADS)

Serafinelli, R.; Vagnetti, F.; Middei, R.

2017-04-01

Context. X-ray spectral variability analyses of active galactic nuclei (AGN) with moderate luminosities and redshifts typically show a "softer when brighter" behaviour. Such a trend has rarely been investigated for high-luminosity AGNs (Lbol ≳ 1044 erg/s), nor for a wider redshift range (e.g. 0 ≲ z ≲ 5). Aims: We present an analysis of spectral variability based on a large sample of 2700 quasars, measured at several different epochs, extracted from the fifth release of the XMM-Newton Serendipitous Source Catalogue. Methods: We quantified the spectral variability through the parameter β defined as the ratio between the change in the photon index Γ and the corresponding logarithmic flux variation, β = -ΔΓ/Δlog FX. Results: Our analysis confirms a softer when brighter behaviour for our sample, extending the previously found general trend to high luminosity and redshift. We estimate an ensemble value of the spectral variability parameter β = -0.69 ± 0.03. We do not find dependence of β on redshift, X-ray luminosity, black hole mass or Eddington ratio. A subsample of radio-loud sources shows a smaller spectral variability parameter. There is also some change with the X-ray flux, with smaller β (in absolute value) for brighter sources. We also find significant correlations for a small number of individual sources, indicating more negative values for some sources.

Morphometric variability of Arctodiaptomus salinus (Copepoda) in the Mediterranean-Black Sea region

PubMed Central

ANUFRIIEVA, Elena V.; SHADRIN, Nickolai V.

2015-01-01

Inter-species variability in morphological traits creates a need to know the range of variability of characteristics in the species for taxonomic and ecological tasks. Copepoda Arctodiaptomus salinus, which inhabits water bodies across Eurasia and North Africa, plays a dominant role in plankton of different water bodies-from fresh to hypersaline. This work assesses the intra- and inter-population morphometric variability of A. salinus in the Mediterranean-Black Sea region and discusses some observed regularities. The variability of linear body parameters and proportions was studied. The impacts of salinity, temperature, and population density on morphological characteristics and their variability can manifest themselves in different ways at the intra- and inter-population levels. A significant effect of salinity, pH and temperature on the body proportions was not found. Their intra-population variability is dependent on temperature and salinity. Sexual dimorphism of A. salinus manifests in different linear parameters, proportions, and their variability. There were no effects of temperature, pH and salinity on the female/male parameter ratio. There were significant differences in the body proportions of males and females in different populations. The influence of temperature, salinity, and population density can be attributed to 80%-90% of intra-population variability of A. salinus. However, these factors can explain less than 40% of inter-population differences. Significant differences in the body proportions of males and females from different populations may suggest that some local populations of A. salinus in the Mediterranean-Black Sea region are in the initial stages of differentiation. PMID:26646569

Identification of sensitive parameters in the modeling of SVOC reemission processes from soil to atmosphere.

PubMed

Loizeau, Vincent; Ciffroy, Philippe; Roustan, Yelva; Musson-Genon, Luc

2014-09-15

Semi-volatile organic compounds (SVOCs) are subject to Long-Range Atmospheric Transport because of transport-deposition-reemission successive processes. Several experimental data available in the literature suggest that soil is a non-negligible contributor of SVOCs to atmosphere. Then coupling soil and atmosphere in integrated coupled models and simulating reemission processes can be essential for estimating atmospheric concentration of several pollutants. However, the sources of uncertainty and variability are multiple (soil properties, meteorological conditions, chemical-specific parameters) and can significantly influence the determination of reemissions. In order to identify the key parameters in reemission modeling and their effect on global modeling uncertainty, we conducted a sensitivity analysis targeted on the 'reemission' output variable. Different parameters were tested, including soil properties, partition coefficients and meteorological conditions. We performed EFAST sensitivity analysis for four chemicals (benzo-a-pyrene, hexachlorobenzene, PCB-28 and lindane) and different spatial scenari (regional and continental scales). Partition coefficients between air, solid and water phases are influent, depending on the precision of data and global behavior of the chemical. Reemissions showed a lower variability to soil parameters (soil organic matter and water contents at field capacity and wilting point). A mapping of these parameters at a regional scale is sufficient to correctly estimate reemissions when compared to other sources of uncertainty. Copyright © 2014 Elsevier B.V. All rights reserved.

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

NASA Technical Reports Server (NTRS)

Litt, Jonathan S.

2007-01-01

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

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

NASA Technical Reports Server (NTRS)

Litt, Jonathan S.

2007-01-01

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

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

NASA Technical Reports Server (NTRS)

Litt, Jonathan S.

2005-01-01

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

Effect of aquifer storage and recovery (ASR) on recovered stormwater quality variability.

PubMed

Page, D W; Peeters, L; Vanderzalm, J; Barry, K; Gonzalez, D

2017-06-15

Aquifer Storage and Recovery (ASR) is increasingly being considered as a means of reusing urban stormwater to supplement available urban water resources. Storage of stormwater in an aquifer has been shown to affect water quality but it has also been claimed that storage will also decrease the stormwater quality variability making for improved predictability and management. This study is the first to document the changes in stormwater quality variability as a result of subsurface storage at four full scale ASR sites using advanced statistical techniques. New methods to examine water quality are required as data is often highly left censored and so traditional measures of variability such as the coefficient of variation are inappropriate. It was observed that for some water quality parameters (most notably E. coli) there was a marked improvement of water quality and a significant decrease in variability at all sites. This means that aquifer storage prior to engineered treatment systems may be advantageous in terms of system design to avoid over engineering. For other parameters such as metal(loids)s and nutrients the trend was less clear due to the numerous processes occurring during storage leading to an increase in variability, especially for geogenic metals and metalloids such as iron and arsenic. Depending upon the specific water quality parameters and end use, use of ASR may not have a dampening effect on stormwater quality variability. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

The role of updraft velocity in temporal variability of cloud hydrometeor number

NASA Astrophysics Data System (ADS)

Sullivan, Sylvia; Nenes, Athanasios; Lee, Dong Min; Oreopoulos, Lazaros

2016-04-01

Significant effort has been dedicated to incorporating direct aerosol-cloud links, through parameterization of liquid droplet activation and ice crystal nucleation, within climate models. This significant accomplishment has generated the need for understanding which parameters affecting hydrometer formation drives its variability in coupled climate simulations, as it provides the basis for optimal parameter estimation as well as robust comparison with data, and other models. Sensitivity analysis alone does not address this issue, given that the importance of each parameter for hydrometer formation depends on its variance and sensitivity. To address the above issue, we develop and use a series of attribution metrics defined with adjoint sensitivities to attribute the temporal variability in droplet and crystal number to important aerosol and dynamical parameters. This attribution analysis is done both for the NASA Global Modeling and Assimilation Office Goddard Earth Observing System Model, Version 5 and the National Center for Atmospheric Research Community Atmosphere Model Version 5.1. Within the GEOS simulation, up to 48% of temporal variability in output ice crystal number and 61% in droplet number can be attributed to input updraft velocity fluctuations, while for the CAM simulation, they explain as much as 89% of the ice crystal number variability. This above results suggest that vertical velocity in both model frameworks is seen to be a very important (or dominant) driver of hydrometer variability. Yet, observations of vertical velocity are seldomly available (or used) to evaluate the vertical velocities in simulations; this strikingly contrasts the amount and quality of data available for aerosol-related parameters. Consequentially, there is a strong need for retrievals or measurements of vertical velocity for addressing this important knowledge gap that requires a significant investment and effort by the atmospheric community. The attribution metrics as a tool of understanding for hydrometer variability can be instrumental for understanding the source of differences between models used for aerosol-cloud-climate interaction studies.

Angular position of the cleat according to torsional parameters of the cyclist's lower limb.

PubMed

Ramos-Ortega, Javier; Domínguez, Gabriel; Castillo, José Manuel; Fernández-Seguín, Lourdes; Munuera, Pedro V

2014-05-01

The aim of this work was to study the relationship of torsional and rotational parameters of the lower limb with a specific angular position of the cleat to establish whether these variables affect the adjustment of the cleat. Correlational study. Motion analysis laboratory. Thirty-seven male cyclists of high performance. The variables studied of the cyclist's lower limb were hip rotation (internal and external), tibial torsion angle, Q angle, and forefoot adductus angle. The cleat angle was measured through a photograph of the sole and with an Rx of this using the software AutoCAD 2008. The variables were photograph angle (photograph), the variable denominated cleat-tarsus minor angle, and a variable denominated cleat-second metatarsal angle (Rx). Analysis included the intraclass correlation coefficient for the reliability of the measurements, Student's t test performed on the dependent variables to compare side, and the multiple linear regression models were calculated using the software SPSS 15.0 for Windows. The Student's t test performed on the dependent variables to compare side showed no significant differences (P = 0.209 for the photograph angle, P = 0.735 for the cleat-tarsus minor angle, and P = 0.801 for the cleat-second metatarsal angle). Values of R and R2 for the photograph angle model were 0.303 and 0.092 (P = 0.08), the cleat/tarsus minor angle model were 0.683 and 0.466 (P < 0.001), and the cleat/second metatarsal angle model were 0.618 and 0.382, respectively (P < 0.001). The equation given by the model was cleat-tarsus minor angle = 75.094 - (0.521 × forefoot adductus angle) + (0.116 × outward rotation of the hips) + (0.220 × Q angle).

The reliable solution and computation time of variable parameters logistic model

NASA Astrophysics Data System (ADS)

Wang, Pengfei; Pan, Xinnong

2018-05-01

The study investigates the reliable computation time (RCT, termed as T c) by applying a double-precision computation of a variable parameters logistic map (VPLM). Firstly, by using the proposed method, we obtain the reliable solutions for the logistic map. Secondly, we construct 10,000 samples of reliable experiments from a time-dependent non-stationary parameters VPLM and then calculate the mean T c. The results indicate that, for each different initial value, the T cs of the VPLM are generally different. However, the mean T c trends to a constant value when the sample number is large enough. The maximum, minimum, and probable distribution functions of T c are also obtained, which can help us to identify the robustness of applying a nonlinear time series theory to forecasting by using the VPLM output. In addition, the T c of the fixed parameter experiments of the logistic map is obtained, and the results suggest that this T c matches the theoretical formula-predicted value.

Adaptive Elastic Net for Generalized Methods of Moments.

PubMed

Caner, Mehmet; Zhang, Hao Helen

2014-01-30

Model selection and estimation are crucial parts of econometrics. This paper introduces a new technique that can simultaneously estimate and select the model in generalized method of moments (GMM) context. The GMM is particularly powerful for analyzing complex data sets such as longitudinal and panel data, and it has wide applications in econometrics. This paper extends the least squares based adaptive elastic net estimator of Zou and Zhang (2009) to nonlinear equation systems with endogenous variables. The extension is not trivial and involves a new proof technique due to estimators lack of closed form solutions. Compared to Bridge-GMM of Caner (2009), we allow for the number of parameters to diverge to infinity as well as collinearity among a large number of variables, also the redundant parameters set to zero via a data dependent technique. This method has the oracle property, meaning that we can estimate nonzero parameters with their standard limit and the redundant parameters are dropped from the equations simultaneously. Numerical examples are used to illustrate the performance of the new method.

Shoulder pain and time dependent structure in wheelchair propulsion variability

PubMed Central

Jayaraman, Chandrasekaran; Moon, Yaejin; Sosnoff, Jacob J.

2016-01-01

Manual wheelchair propulsion places considerable repetitive mechanical strain on the upper limbs leading to shoulder injury and pain. While recent research indicates that the amount of variability in wheelchair propulsion and shoulder pain may be related. There has been minimal inquiry into the fluctuation over time (i.e. time-dependent structure) in wheelchair propulsion variability. Consequently the purpose of this investigation was to examine if the time-dependent structure in the wheelchair propulsion parameters are related to shoulder pain. 27 experienced wheelchair users manually propelled their own wheelchair fitted with a SMARTWheel on a roller at 1.1 m/s for 3 minutes. Time-dependent structure of cycle-to-cycle fluctuations in contact angle and inter push time interval was quantified using sample entropy (SampEn) and compared between the groups with/without shoulder pain using non-parametric statistics. Overall findings were, (1) variability observed in contact angle fluctuations during manual wheelchair propulsion is structured (Z=3.15;p<0.05), (2) individuals with shoulder pain exhibited higher SampEn magnitude for contact angle during wheelchair propulsion than those without pain (χ2(1)=6.12;p<0.05); and (3) SampEn of contact angle correlated significantly with self-reported shoulder pain (rs (WUSPI) =0.41;rs (VAS)=0.56;p<0.05). It was concluded that the time-dependent structure in wheelchair propulsion may provide novel information for tracking and monitoring shoulder pain. PMID:27134151

Using genetic algorithms to achieve an automatic and global optimization of analogue methods for statistical downscaling of precipitation

NASA Astrophysics Data System (ADS)

Horton, Pascal; Weingartner, Rolf; Obled, Charles; Jaboyedoff, Michel

2017-04-01

Analogue methods (AMs) rely on the hypothesis that similar situations, in terms of atmospheric circulation, are likely to result in similar local or regional weather conditions. These methods consist of sampling a certain number of past situations, based on different synoptic-scale meteorological variables (predictors), in order to construct a probabilistic prediction for a local weather variable of interest (predictand). They are often used for daily precipitation prediction, either in the context of real-time forecasting, reconstruction of past weather conditions, or future climate impact studies. The relationship between predictors and predictands is defined by several parameters (predictor variable, spatial and temporal windows used for the comparison, analogy criteria, and number of analogues), which are often calibrated by means of a semi-automatic sequential procedure that has strong limitations. AMs may include several subsampling levels (e.g. first sorting a set of analogs in terms of circulation, then restricting to those with similar moisture status). The parameter space of the AMs can be very complex, with substantial co-dependencies between the parameters. Thus, global optimization techniques are likely to be necessary for calibrating most AM variants, as they can optimize all parameters of all analogy levels simultaneously. Genetic algorithms (GAs) were found to be successful in finding optimal values of AM parameters. They allow taking into account parameters inter-dependencies, and selecting objectively some parameters that were manually selected beforehand (such as the pressure levels and the temporal windows of the predictor variables), and thus obviate the need of assessing a high number of combinations. The performance scores of the optimized methods increased compared to reference methods, and this even to a greater extent for days with high precipitation totals. The resulting parameters were found to be relevant and spatially coherent. Moreover, they were obtained automatically and objectively, which reduces efforts invested in exploration attempts when adapting the method to a new region or for a new predictand. In addition, the approach allowed for new degrees of freedom, such as a weighting between the pressure levels, and non overlapping spatial windows. Genetic algorithms were then used further in order to automatically select predictor variables and analogy criteria. This resulted in interesting outputs, providing new predictor-criterion combinations. However, some limitations of the approach were encountered, and the need of the expert input is likely to remain necessary. Nevertheless, letting GAs exploring a dataset for the best predictor for a predictand of interest is certainly a useful tool, particularly when applied for a new predictand or a new region under different climatic characteristics.

A biodynamic feedthrough model based on neuromuscular principles.

PubMed

Venrooij, Joost; Abbink, David A; Mulder, Mark; van Paassen, Marinus M; Mulder, Max; van der Helm, Frans C T; Bulthoff, Heinrich H

2014-07-01

A biodynamic feedthrough (BDFT) model is proposed that describes how vehicle accelerations feed through the human body, causing involuntary limb motions and so involuntary control inputs. BDFT dynamics strongly depend on limb dynamics, which can vary between persons (between-subject variability), but also within one person over time, e.g., due to the control task performed (within-subject variability). The proposed BDFT model is based on physical neuromuscular principles and is derived from an established admittance model-describing limb dynamics-which was extended to include control device dynamics and account for acceleration effects. The resulting BDFT model serves primarily the purpose of increasing the understanding of the relationship between neuromuscular admittance and biodynamic feedthrough. An added advantage of the proposed model is that its parameters can be estimated using a two-stage approach, making the parameter estimation more robust, as the procedure is largely based on the well documented procedure required for the admittance model. To estimate the parameter values of the BDFT model, data are used from an experiment in which both neuromuscular admittance and biodynamic feedthrough are measured. The quality of the BDFT model is evaluated in the frequency and time domain. Results provide strong evidence that the BDFT model and the proposed method of parameter estimation put forward in this paper allows for accurate BDFT modeling across different subjects (accounting for between-subject variability) and across control tasks (accounting for within-subject variability).

Robust peptidoglycan growth by dynamic and variable multi-protein complexes.

PubMed

Pazos, Manuel; Peters, Katharina; Vollmer, Waldemar

2017-04-01

In Gram-negative bacteria such as Escherichia coli the peptidoglycan sacculus resides in the periplasm, a compartment that experiences changes in pH value, osmolality, ion strength and other parameters depending on the cell's environment. Hence, the cell needs robust peptidoglycan growth mechanisms to grow and divide under different conditions. Here we propose a model according to which the cell achieves robust peptidoglycan growth by employing dynamic multi-protein complexes, which assemble with variable composition from freely diffusing sets of peptidoglycan synthases, hydrolases and their regulators, whereby the composition of the active complexes depends on the cell cycle state - cell elongation or division - and the periplasmic growth conditions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Height extrapolation of wind data

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

Mikhail, A.S.

1982-11-01

Hourly average data for a period of 1 year from three tall meteorological towers - the Erie tower in Colorado, the Goodnoe Hills tower in Washington and the WKY-TV tower in Oklahoma - were used to analyze the wind shear exponent variabiilty with various parameters such as thermal stability, anemometer level wind speed, projection height and surface roughness. Different proposed models for prediction of height variability of short-term average wind speeds were discussed. Other models that predict the height dependence of Weilbull distribution parameters were tested. The observed power law exponent for all three towers showed strong dependence on themore » anemometer level wind speed and stability (nighttime and daytime). It also exhibited a high degree of dependence on extrapolation height with respect to anemometer height. These dependences became less severe as the anemometer level wind speeds were increased due to the turbulent mixing of the atmospheric boundary layer. The three models used for Weibull distribution parameter extrapolation were he velocity-dependent power law model (Justus), the velocity, surface roughness, and height-dependent model (Mikhail) and the velocity and surface roughness-dependent model (NASA). The models projected the scale parameter C fairly accurately for the Goodnoe Hills and WKY-TV towers and were less accurate for the Erie tower. However, all models overestimated the C value. The maximum error for the Mikhail model was less than 2% for Goodnoe Hills, 6% for WKY-TV and 28% for Erie. The error associated with the prediction of the shape factor (K) was similar for the NASA, Mikhail and Justus models. It ranged from 20 to 25%. The effect of the misestimation of hub-height distribution parameters (C and K) on average power output is briefly discussed.« less

Measuring determinants of career satisfaction of anesthesiologists: validation of a survey instrument.

PubMed

Afonso, Anoushka M; Diaz, James H; Scher, Corey S; Beyl, Robbie A; Nair, Singh R; Kaye, Alan David

2013-06-01

To measure the parameter of job satisfaction among anesthesiologists. Survey instrument. Academic anesthesiology departments in the United States. 320 anesthesiologists who attended the annual meeting of the ASA in 2009 (95% response rate). The anonymous 50-item survey collected information on 26 independent demographic variables and 24 dependent ranked variables of career satisfaction among practicing anesthesiologists. Mean survey scores were calculated for each demographic variable and tested for statistically significant differences by analysis of variance. Questions within each domain that were internally consistent with each other within domains were identified by Cronbach's alpha ≥ 0.7. P-values ≤ 0.05 were considered statistically significant. Cronbach's alpha analysis showed strong internal consistency for 10 dependent outcome questions in the practice factor-related domain (α = 0.72), 6 dependent outcome questions in the peer factor-related domain (α = 0.71), and 8 dependent outcome questions in the personal factor-related domain (α = 0.81). Although age was not a variable, full-time status, early satisfaction within the first 5 years of practice, working with respected peers, and personal choice factors were all significantly associated with anesthesiologist job satisfaction. Improvements in factors related to job satisfaction among anesthesiologists may lead to higher early and current career satisfaction. Copyright © 2013 Elsevier Inc. All rights reserved.

DBH Prediction Using Allometry Described by Bivariate Copula Distribution

NASA Astrophysics Data System (ADS)

Xu, Q.; Hou, Z.; Li, B.; Greenberg, J. A.

2017-12-01

Forest biomass mapping based on single tree detection from the airborne laser scanning (ALS) usually depends on an allometric equation that relates diameter at breast height (DBH) with per-tree aboveground biomass. The incapability of the ALS technology in directly measuring DBH leads to the need to predict DBH with other ALS-measured tree-level structural parameters. A copula-based method is proposed in the study to predict DBH with the ALS-measured tree height and crown diameter using a dataset measured in the Lassen National Forest in California. Instead of exploring an explicit mathematical equation that explains the underlying relationship between DBH and other structural parameters, the copula-based prediction method utilizes the dependency between cumulative distributions of these variables, and solves the DBH based on an assumption that for a single tree, the cumulative probability of each structural parameter is identical. Results show that compared with the bench-marking least-square linear regression and the k-MSN imputation, the copula-based method obtains better accuracy in the DBH for the Lassen National Forest. To assess the generalization of the proposed method, prediction uncertainty is quantified using bootstrapping techniques that examine the variability of the RMSE of the predicted DBH. We find that the copula distribution is reliable in describing the allometric relationship between tree-level structural parameters, and it contributes to the reduction of prediction uncertainty.

Adaptive control for a class of nonlinear complex dynamical systems with uncertain complex parameters and perturbations

PubMed Central

Liu, Jian; Liu, Kexin; Liu, Shutang

2017-01-01

In this paper, adaptive control is extended from real space to complex space, resulting in a new control scheme for a class of n-dimensional time-dependent strict-feedback complex-variable chaotic (hyperchaotic) systems (CVCSs) in the presence of uncertain complex parameters and perturbations, which has not been previously reported in the literature. In detail, we have developed a unified framework for designing the adaptive complex scalar controller to ensure this type of CVCSs asymptotically stable and for selecting complex update laws to estimate unknown complex parameters. In particular, combining Lyapunov functions dependent on complex-valued vectors and back-stepping technique, sufficient criteria on stabilization of CVCSs are derived in the sense of Wirtinger calculus in complex space. Finally, numerical simulation is presented to validate our theoretical results. PMID:28467431

Adaptive control for a class of nonlinear complex dynamical systems with uncertain complex parameters and perturbations.

PubMed

Liu, Jian; Liu, Kexin; Liu, Shutang

2017-01-01

In this paper, adaptive control is extended from real space to complex space, resulting in a new control scheme for a class of n-dimensional time-dependent strict-feedback complex-variable chaotic (hyperchaotic) systems (CVCSs) in the presence of uncertain complex parameters and perturbations, which has not been previously reported in the literature. In detail, we have developed a unified framework for designing the adaptive complex scalar controller to ensure this type of CVCSs asymptotically stable and for selecting complex update laws to estimate unknown complex parameters. In particular, combining Lyapunov functions dependent on complex-valued vectors and back-stepping technique, sufficient criteria on stabilization of CVCSs are derived in the sense of Wirtinger calculus in complex space. Finally, numerical simulation is presented to validate our theoretical results.

Demographic behavior and the welfare state: econometric issues in the identification of the effects of tax and transfer programs.

PubMed

Moffitt, R

1989-01-01

It is difficult and risky to identify the effects of tax and transfer programs on demographic behavior. The primary concern of this article is to see if real exogenous variation in these programs' parameters exist to adequately evaluate the effects of the programs on behavior. A 1982 study examined the effect of the Aid to Families with Dependent Children (AFDC), a commonly used example of a US transfer program, on the probability that a female heads a household of children 18 years old with no adult male present. The dependent variable merged household, marital status, and fertility choice into 1 variable. The independent variables included leisure hours and income which also defined a woman's utility function. In this study, the parameters used to represent AFDC effects were not only identified by variation in the AFDC variables. 2 other studies attempting to examine AFDC's effects on demographic behavior (Hutchens [1979] and Ellwood and Bane [1985]) also failed to identify these effects. Ellwood and Bane appropriately concentrated on exogenous program variation (since benefits vary from state to state) and how it might be used in evaluating the effects of AFDC on behavior. They erroneously determined, however, that state variation should not be considered in their model. The studies reviewed in this article looked at AFDC, a program with significant intracountry parameter variation, yet these studies relied on potentially illegitimate sources of variation. Intracountry program variation is less likely to occur in Western Europe and therefore the problem of identifying effects of tax and transfer programs on demographic behavior is apt to be even more severe. Any further such studies should address these issues.

Estimation of gloss from rough surface parameters

NASA Astrophysics Data System (ADS)

Simonsen, Ingve; Larsen, Åge G.; Andreassen, Erik; Ommundsen, Espen; Nord-Varhaug, Katrin

2005-12-01

Gloss is a quantity used in the optical industry to quantify and categorize materials according to how well they scatter light specularly. With the aid of phase perturbation theory, we derive an approximate expression for this quantity for a one-dimensional randomly rough surface. It is demonstrated that gloss depends in an exponential way on two dimensionless quantities that are associated with the surface randomness: the root-mean-square roughness times the perpendicular momentum transfer for the specular direction, and a correlation function dependent factor times a lateral momentum variable associated with the collection angle. Rigorous Monte Carlo simulations are used to access the quality of this approximation, and good agreement is observed over large regions of parameter space.

Statistical simplex approach to primary and secondary color correction in thick lens assemblies

NASA Astrophysics Data System (ADS)

Ament, Shelby D. V.; Pfisterer, Richard

2017-11-01

A glass selection optimization algorithm is developed for primary and secondary color correction in thick lens systems. The approach is based on the downhill simplex method, and requires manipulation of the surface color equations to obtain a single glass-dependent parameter for each lens element. Linear correlation is used to relate this parameter to all other glass-dependent variables. The algorithm provides a statistical distribution of Abbe numbers for each element in the system. Examples of several lenses, from 2-element to 6-element systems, are performed to verify this approach. The optimization algorithm proposed is capable of finding glass solutions with high color correction without requiring an exhaustive search of the glass catalog.

Nonautonomous solitons for an extended forced Korteweg-de Vries equation with variable coefficients in the fluid or plasma

NASA Astrophysics Data System (ADS)

Wang, Yong-Yan; Su, Chuan-Qi; Liu, Xue-Qing; Li, Jian-Guang

2018-07-01

Under investigation in this paper is an extended forced Korteweg-de Vries equation with variable coefficients in the fluid or plasma. Lax pair, bilinear forms, and bilinear Bäcklund transformations are derived. Based on the bilinear forms, the first-, second-, and third-order nonautonomous soliton solutions are derived. Propagation and interaction of the nonautonomous solitons are investigated and influence of the variable coefficients is also discussed: Amplitude of the first-order nonautonomous soliton is determined by the spectral parameter and perturbed factor; there exist two kinds of the solitons, namely the elevation and depression solitons, depending on the sign of the spectral parameter; the background where the nonautonomous soliton exists is influenced by the perturbed factor and external force coefficient; breather solutions can be constructed under the conjugate condition, and period of the breather is related to the dispersive and nonuniform coefficients.

Radiation and polarization signatures of the 3D multizone time-dependent hadronic blazar model

DOE PAGES

Zhang, Haocheng; Diltz, Chris; Bottcher, Markus

2016-09-23

We present a newly developed time-dependent three-dimensional multizone hadronic blazar emission model. By coupling a Fokker–Planck-based lepto-hadronic particle evolution code, 3DHad, with a polarization-dependent radiation transfer code, 3DPol, we are able to study the time-dependent radiation and polarization signatures of a hadronic blazar model for the first time. Our current code is limited to parameter regimes in which the hadronic γ-ray output is dominated by proton synchrotron emission, neglecting pion production. Our results demonstrate that the time-dependent flux and polarization signatures are generally dominated by the relation between the synchrotron cooling and the light-crossing timescale, which is largely independent ofmore » the exact model parameters. We find that unlike the low-energy polarization signatures, which can vary rapidly in time, the high-energy polarization signatures appear stable. Lastly, future high-energy polarimeters may be able to distinguish such signatures from the lower and more rapidly variable polarization signatures expected in leptonic models.« less

A possible loophole in the theorem of Bell.

PubMed

Hess, K; Philipp, W

2001-12-04

The celebrated inequalities of Bell are based on the assumption that local hidden parameters exist. When combined with conflicting experimental results, these inequalities appear to prove that local hidden parameters cannot exist. This contradiction suggests to many that only instantaneous action at a distance can explain the Einstein, Podolsky, and Rosen type of experiments. We show that, in addition to the assumption that hidden parameters exist, Bell tacitly makes a variety of other assumptions that contribute to his being able to obtain the desired contradiction. For instance, Bell assumes that the hidden parameters do not depend on time and are governed by a single probability measure independent of the analyzer settings. We argue that the exclusion of time has neither a physical nor a mathematical basis but is based on Bell's translation of the concept of Einstein locality into the language of probability theory. Our additional set of local hidden variables includes time-like correlated parameters and a generalized probability density. We prove that our extended space of local hidden variables does not permit Bell-type proofs to go forward.

Thermal Management in Friction-Stir Welding of Precipitation-Hardening Aluminum Alloys

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

Upadhyay, Piyush; Reynolds, Anthony

2015-05-25

Process design and implementation in FSW is mostly dependent on empirical information gathered through experience. Basic science of friction stir welding and processing can only be complete when fundamental interrelationships between process control parameters and response variables and resulting weld microstructure and properties are established to a reasonable extent. It is known that primary process control parameters like tool rotation and translation rate and forge axis force have complicated and interactive relationships to the process response variables such as peak temperature, time at temperature etc. Of primary influence to the other process response parameters are temperature and its gradient atmore » the deformation and heat affected zones. Through review of pertinent works in the literature and some experimental results from boundary condition work performed in precipitation hardening aluminum alloys this paper will partially elucidate the nature and effects of temperature transients caused by variation of thermal boundaries in Friction Stir Welding.« less

Thermal Management in Friction-Stir Welding of Precipitation-Hardened Aluminum Alloys

NASA Astrophysics Data System (ADS)

Upadhyay, Piyush; Reynolds, Anthony P.

2015-05-01

Process design and implementation in friction-stir welding (FSW) is mostly dependent on empirical information. Basic science of FSW and processing can only be complete when fundamental interrelationships between the process control parameters and response variables and the resulting weld microstructure and properties are established to a reasonable extent. It is known that primary process control parameters such as tool rotation, translation rates, and forge axis force have complicated and interactive relationships to process-response variables such as peak temperature and time at temperature. Of primary influence on the other process-response parameters are temperature and its gradient in the deformation and heat-affected zones. Through a review of pertinent works in the literature and results from boundary condition experiments performed in precipitation-hardening aluminum alloys, this article partially elucidates the nature and effects of temperature transients caused by variation of thermal boundaries in FSW.

An opinion-driven behavioral dynamics model for addictive behaviors

NASA Astrophysics Data System (ADS)

Moore, Thomas W.; Finley, Patrick D.; Apelberg, Benjamin J.; Ambrose, Bridget K.; Brodsky, Nancy S.; Brown, Theresa J.; Husten, Corinne; Glass, Robert J.

2015-04-01

We present a model of behavioral dynamics that combines a social network-based opinion dynamics model with behavioral mapping. The behavioral component is discrete and history-dependent to represent situations in which an individual's behavior is initially driven by opinion and later constrained by physiological or psychological conditions that serve to maintain the behavior. Individuals are modeled as nodes in a social network connected by directed edges. Parameter sweeps illustrate model behavior and the effects of individual parameters and parameter interactions on model results. Mapping a continuous opinion variable into a discrete behavioral space induces clustering on directed networks. Clusters provide targets of opportunity for influencing the network state; however, the smaller the network the greater the stochasticity and potential variability in outcomes. This has implications both for behaviors that are influenced by close relationships verses those influenced by societal norms and for the effectiveness of strategies for influencing those behaviors.

High-order sliding-mode control for blood glucose regulation in the presence of uncertain dynamics.

PubMed

Hernández, Ana Gabriela Gallardo; Fridman, Leonid; Leder, Ron; Andrade, Sergio Islas; Monsalve, Cristina Revilla; Shtessel, Yuri; Levant, Arie

2011-01-01

The success of blood glucose automatic regulation depends on the robustness of the control algorithm used. It is a difficult task to perform due to the complexity of the glucose-insulin regulation system. The variety of model existing reflects the great amount of phenomena involved in the process, and the inter-patient variability of the parameters represent another challenge. In this research a High-Order Sliding-Mode Control is proposed. It is applied to two well known models, Bergman Minimal Model, and Sorensen Model, to test its robustness with respect to uncertain dynamics, and patients' parameter variability. The controller designed based on the simulations is tested with the specific Bergman Minimal Model of a diabetic patient whose parameters were identified from an in vivo assay. To minimize the insulin infusion rate, and avoid the hypoglycemia risk, the glucose target is a dynamical profile.

Contextualization: Memory Formation and Retrieval in a Nested Environment

NASA Astrophysics Data System (ADS)

Piefke, Martina; Markowitsch, Hans J.

Episodic memory functions are highly context-dependent. This is true for both experimental and autobiographical episodic memory. We here review neuropsychological and neuroimaging evidence for effects of differential encoding and retrieval contexts on episodic memory performance as well as the underlying neurofunctional mechanisms. In studies of laboratory episodic memory, the influence of context parameters can be assessed by experimental manipulations. Such experiments suggest that contextual variables mainly affect prefrontal functions supporting executive processes involved in episodic learning and retrieval. Context parameters affecting episodic autobiographical memory are far more complex and cannot easily be controlled. Data support the view that not only prefrontal, but also further medial temporal and posterior parietal regions mediating the re-experience and emotional evaluation of personal memories are highly influenced by changing contextual variables of memory encoding and retrieval. Based on our review of available data, we thus suggest that experimental and autobiographical episodic memories are influenced by both overlapping and differential context parameters.

Local Variability of Parameters for Characterization of the Corneal Subbasal Nerve Plexus.

PubMed

Winter, Karsten; Scheibe, Patrick; Köhler, Bernd; Allgeier, Stephan; Guthoff, Rudolf F; Stachs, Oliver

2016-01-01

The corneal subbasal nerve plexus (SNP) offers high potential for early diagnosis of diabetic peripheral neuropathy. Changes in subbasal nerve fibers can be assessed in vivo by confocal laser scanning microscopy (CLSM) and quantified using specific parameters. While current study results agree regarding parameter tendency, there are considerable differences in terms of absolute values. The present study set out to identify factors that might account for this high parameter variability. In three healthy subjects, we used a novel method of software-based large-scale reconstruction that provided SNP images of the central cornea, decomposed the image areas into all possible image sections corresponding to the size of a single conventional CLSM image (0.16 mm2), and calculated a set of parameters for each image section. In order to carry out a large number of virtual examinations within the reconstructed image areas, an extensive simulation procedure (10,000 runs per image) was implemented. The three analyzed images ranged in size from 3.75 mm2 to 4.27 mm2. The spatial configuration of the subbasal nerve fiber networks varied greatly across the cornea and thus caused heavily location-dependent results as well as wide value ranges for the parameters assessed. Distributions of SNP parameter values varied greatly between the three images and showed significant differences between all images for every parameter calculated (p < 0.001 in each case). The relatively small size of the conventionally evaluated SNP area is a contributory factor in high SNP parameter variability. Averaging of parameter values based on multiple CLSM frames does not necessarily result in good approximations of the respective reference values of the whole image area. This illustrates the potential for examiner bias when selecting SNP images in the central corneal area.

Proton Form Factor Puzzle and the CEBAF Large Acceptance Spectrometer (CLAS) Two-Photon Exchange Experiment

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

Rimal, Dipak

2014-05-01

The electromagnetic form factors are the most fundamental observables that encode information about the internal structure of the nucleon. This dissertation explored dependence of R on kinematic variables such as squared four-momentum transfer (Q 2) and the virtual photon polarization parameter (ε).

Verification of the effects of Schumann frequency range electromagnetic fields on the human cardiovascular system

NASA Astrophysics Data System (ADS)

Tuzhilkin, D. A.; Borodin, A. S.

2017-11-01

The results of the study of variations in the electromagnetic background parameters of the Schumann resonator frequency range and the variability indices of the human heart period during its free activity are presented on the basis of 24-hour synchronous monitoring data. It is shown that the integral evaluation of the conjugacy of the heart rate variability indices from the Schumann resonance parameters is extremely weak. In this case, the differential evaluation of this dependence with separation into characteristic time intervals of the day, characterized by different motor activity of the subjects, becomes significantly higher. The number of volunteers whose conjugacy is characterized by a strong correlation in some cases reaches 35 percent of the sample.

Maximum likelihood estimation for life distributions with competing failure modes

NASA Technical Reports Server (NTRS)

Sidik, S. M.

1979-01-01

Systems which are placed on test at time zero, function for a period and die at some random time were studied. Failure may be due to one of several causes or modes. The parameters of the life distribution may depend upon the levels of various stress variables the item is subject to. Maximum likelihood estimation methods are discussed. Specific methods are reported for the smallest extreme-value distributions of life. Monte-Carlo results indicate the methods to be promising. Under appropriate conditions, the location parameters are nearly unbiased, the scale parameter is slight biased, and the asymptotic covariances are rapidly approached.

The use of auxiliary variables in capture-recapture and removal experiments

USGS Publications Warehouse

Pollock, K.H.; Hines, J.E.; Nichols, J.D.

1984-01-01

The dependence of animal capture probabilities on auxiliary variables is an important practical problem which has not been considered in the development of estimation procedures for capture-recapture and removal experiments. In this paper the linear logistic binary regression model is used to relate the probability of capture to continuous auxiliary variables. The auxiliary variables could be environmental quantities such as air or water temperature, or characteristics of individual animals, such as body length or weight. Maximum likelihood estimators of the population parameters are considered for a variety of models which all assume a closed population. Testing between models is also considered. The models can also be used when one auxiliary variable is a measure of the effort expended in obtaining the sample.

Modeling of laser transmission contour welding process using FEA and DoE

NASA Astrophysics Data System (ADS)

Acherjee, Bappa; Kuar, Arunanshu S.; Mitra, Souren; Misra, Dipten

2012-07-01

In this research, a systematic investigation on laser transmission contour welding process is carried out using finite element analysis (FEA) and design of experiments (DoE) techniques. First of all, a three-dimensional thermal model is developed to simulate the laser transmission contour welding process with a moving heat source. The commercial finite element code ANSYS® multi-physics is used to obtain the numerical results by implementing a volumetric Gaussian heat source, and combined convection-radiation boundary conditions. Design of experiments together with regression analysis is then employed to plan the experiments and to develop mathematical models based on simulation results. Four key process parameters, namely power, welding speed, beam diameter, and carbon black content in absorbing polymer, are considered as independent variables, while maximum temperature at weld interface, weld width, and weld depths in transparent and absorbing polymers are considered as dependent variables. Sensitivity analysis is performed to determine how different values of an independent variable affect a particular dependent variable.

Uncertainty analyses of the calibrated parameter values of a water quality model

NASA Astrophysics Data System (ADS)

Rode, M.; Suhr, U.; Lindenschmidt, K.-E.

2003-04-01

For river basin management water quality models are increasingly used for the analysis and evaluation of different management measures. However substantial uncertainties exist in parameter values depending on the available calibration data. In this paper an uncertainty analysis for a water quality model is presented, which considers the impact of available model calibration data and the variance of input variables. The investigation was conducted based on four extensive flowtime related longitudinal surveys in the River Elbe in the years 1996 to 1999 with varying discharges and seasonal conditions. For the model calculations the deterministic model QSIM of the BfG (Germany) was used. QSIM is a one dimensional water quality model and uses standard algorithms for hydrodynamics and phytoplankton dynamics in running waters, e.g. Michaelis Menten/Monod kinetics, which are used in a wide range of models. The multi-objective calibration of the model was carried out with the nonlinear parameter estimator PEST. The results show that for individual flow time related measuring surveys very good agreements between model calculation and measured values can be obtained. If these parameters are applied to deviating boundary conditions, substantial errors in model calculation can occur. These uncertainties can be decreased with an increased calibration database. More reliable model parameters can be identified, which supply reasonable results for broader boundary conditions. The extension of the application of the parameter set on a wider range of water quality conditions leads to a slight reduction of the model precision for the specific water quality situation. Moreover the investigations show that highly variable water quality variables like the algal biomass always allow a smaller forecast accuracy than variables with lower coefficients of variation like e.g. nitrate.

A variant of sparse partial least squares for variable selection and data exploration.

PubMed

Olson Hunt, Megan J; Weissfeld, Lisa; Boudreau, Robert M; Aizenstein, Howard; Newman, Anne B; Simonsick, Eleanor M; Van Domelen, Dane R; Thomas, Fridtjof; Yaffe, Kristine; Rosano, Caterina

2014-01-01

When data are sparse and/or predictors multicollinear, current implementation of sparse partial least squares (SPLS) does not give estimates for non-selected predictors nor provide a measure of inference. In response, an approach termed "all-possible" SPLS is proposed, which fits a SPLS model for all tuning parameter values across a set grid. Noted is the percentage of time a given predictor is chosen, as well as the average non-zero parameter estimate. Using a "large" number of multicollinear predictors, simulation confirmed variables not associated with the outcome were least likely to be chosen as sparsity increased across the grid of tuning parameters, while the opposite was true for those strongly associated. Lastly, variables with a weak association were chosen more often than those with no association, but less often than those with a strong relationship to the outcome. Similarly, predictors most strongly related to the outcome had the largest average parameter estimate magnitude, followed by those with a weak relationship, followed by those with no relationship. Across two independent studies regarding the relationship between volumetric MRI measures and a cognitive test score, this method confirmed a priori hypotheses about which brain regions would be selected most often and have the largest average parameter estimates. In conclusion, the percentage of time a predictor is chosen is a useful measure for ordering the strength of the relationship between the independent and dependent variables, serving as a form of inference. The average parameter estimates give further insight regarding the direction and strength of association. As a result, all-possible SPLS gives more information than the dichotomous output of traditional SPLS, making it useful when undertaking data exploration and hypothesis generation for a large number of potential predictors.

Multi-frequency properties of synthetic blazar radio light curves within the shock-in-jet scenario

NASA Astrophysics Data System (ADS)

Fromm, C. M.; Fuhrmann, L.; Perucho, M.

2015-08-01

Context. Blazars are among the most powerful extragalactic objects as a sub-class of active galactic nuclei. They launch relativistic jets and their emitted radiation shows strong variability across the entire electro-magnetic spectrum. The mechanisms producing the variability are still controversial, and different models have been proposed to explain the observed variations in multi-frequency blazar light curves. Aims: We investigate the capabilities of the classical shock-in-jet model to explain and reconstruct the observed evolution of flares in the turnover frequency - turnover flux density (νm-Sm) plane and their frequency dependent light curve parameters. With a detailed parameter space study, we provide the framework for future, detailed comparisons of observed flare signatures with the shock-in-jet scenario. Methods: Based on the shock model, we compute synthetic single-dish light curves at different radio frequencies (2.6 to 345 GHz) and for different physical conditions in a conical jet (e.g. magnetic field geometry and Doppler factor). From those we extract the slopes of the different energy loss stages within the (νm-Sm) plane and deduce the frequency dependence of different light curve parameters, such as flare amplitude, time scale, and cross-band delays. Results: The evolution of the Doppler factor along the jet has the strongest influence on the evolution of the flare and on the frequency dependent light curve parameters. The synchrotron stage can be hidden in the Compton or in the adiabatic stage, depending mainly on the evolution of the Doppler factor, which makes it difficult to detect its signature in observations. In addition, we show that the time lags between different frequencies can be used as an efficient tool to better constrain the physical properties of these objects. Appendix A is available in electronic form at http://www.aanda.org

Re/Os constraint on the time variability of the fine-structure constant.

PubMed

Fujii, Yasunori; Iwamoto, Akira

2003-12-31

We argue that the accuracy by which the isochron parameters of the decay 187Re-->187Os are determined by dating iron meteorites may constrain the possible time dependence of the decay rate and hence of the fine-structure constant alpha, not directly but only in a model-dependent manner. From this point of view, some of the attempts to analyze the Oklo constraint and the results of the quasistellar-object absorption lines are reexamined.

Demographic models reveal the shape of density dependence for a specialist insect herbivore on variable host plants.

PubMed

Miller, Tom E X

2007-07-01

1. It is widely accepted that density-dependent processes play an important role in most natural populations. However, persistent challenges in our understanding of density-dependent population dynamics include evaluating the shape of the relationship between density and demographic rates (linear, concave, convex), and identifying extrinsic factors that can mediate this relationship. 2. I studied the population dynamics of the cactus bug Narnia pallidicornis on host plants (Opuntia imbricata) that varied naturally in relative reproductive effort (RRE, the proportion of meristems allocated to reproduction), an important plant quality trait. I manipulated per-plant cactus bug densities, quantified subsequent dynamics, and fit stage-structured models to the experimental data to ask if and how density influences demographic parameters. 3. In the field experiment, I found that populations with variable starting densities quickly converged upon similar growth trajectories. In the model-fitting analyses, the data strongly supported a model that defined the juvenile cactus bug retention parameter (joint probability of surviving and not dispersing) as a nonlinear decreasing function of density. The estimated shape of this relationship shifted from concave to convex with increasing host-plant RRE. 4. The results demonstrate that host-plant traits are critical sources of variation in the strength and shape of density dependence in insects, and highlight the utility of integrated experimental-theoretical approaches for identifying processes underlying patterns of change in natural populations.

Computing the structural influence matrix for biological systems.

PubMed

Giordano, Giulia; Cuba Samaniego, Christian; Franco, Elisa; Blanchini, Franco

2016-06-01

We consider the problem of identifying structural influences of external inputs on steady-state outputs in a biological network model. We speak of a structural influence if, upon a perturbation due to a constant input, the ensuing variation of the steady-state output value has the same sign as the input (positive influence), the opposite sign (negative influence), or is zero (perfect adaptation), for any feasible choice of the model parameters. All these signs and zeros can constitute a structural influence matrix, whose (i, j) entry indicates the sign of steady-state influence of the jth system variable on the ith variable (the output caused by an external persistent input applied to the jth variable). Each entry is structurally determinate if the sign does not depend on the choice of the parameters, but is indeterminate otherwise. In principle, determining the influence matrix requires exhaustive testing of the system steady-state behaviour in the widest range of parameter values. Here we show that, in a broad class of biological networks, the influence matrix can be evaluated with an algorithm that tests the system steady-state behaviour only at a finite number of points. This algorithm also allows us to assess the structural effect of any perturbation, such as variations of relevant parameters. Our method is applied to nontrivial models of biochemical reaction networks and population dynamics drawn from the literature, providing a parameter-free insight into the system dynamics.

Geochemical Characterization Using Geophysical Data and Markov Chain Monte Carlo Methods

NASA Astrophysics Data System (ADS)

Chen, J.; Hubbard, S.; Rubin, Y.; Murray, C.; Roden, E.; Majer, E.

2002-12-01

Although the spatial distribution of geochemical parameters is extremely important for many subsurface remediation approaches, traditional characterization of those parameters is invasive and laborious, and thus is rarely performed sufficiently to describe natural hydrogeological variability at the field-scale. This study is an effort to jointly use multiple sources of information, including noninvasive geophysical data, for geochemical characterization of the saturated and anaerobic portion of the DOE South Oyster Bacterial Transport Site in Virginia. Our data set includes hydrogeological and geochemical measurements from five boreholes and ground-penetrating radar (GPR) and seismic tomographic data along two profiles that traverse the boreholes. The primary geochemical parameters are the concentrations of extractable ferrous iron Fe(II) and ferric iron Fe(III). Since iron-reducing bacteria can reduce Fe(III) to Fe(II) under certain conditions, information about the spatial distributions of Fe(II) and Fe(III) may indicate both where microbial iron reduction has occurred and in which zone it is likely to occur in the future. In addition, as geochemical heterogeneity influences bacterial transport and activity, estimates of the geochemical parameters provide important input to numerical flow and contaminant transport models geared toward bioremediation. Motivated by our previous research, which demonstrated that crosshole geophysical data could be very useful for estimating hydrogeological parameters, we hypothesize in this study that geochemical and geophysical parameters may be linked through their mutual dependence on hydrogeological parameters such as lithofacies. We attempt to estimate geochemical parameters using both hydrogeological and geophysical measurements in a Bayesian framework. Within the two-dimensional study domain (12m x 6m vertical cross section divided into 0.25m x 0.25m pixels), geochemical and hydrogeological parameters were considered as data if they were available from direct measurements or as variables otherwise. To estimate the geochemical parameters, we first assigned a prior model for each variable and a likelihood model for each type of data, which together define posterior probability distributions for each variable on the domain. Since the posterior probability distribution may involve hundreds of variables, we used a Markov Chain Monte Carlo (MCMC) method to explore each variable by generating and subsequently evaluating hundreds of realizations. Results from this case study showed that although geophysical attributes are not necessarily directly related to geochemical parameters, geophysical data could be very useful for providing accurate and high-resolution information about geochemical parameter distribution through their joint and indirect connections with hydrogeological properties such as lithofacies. This case study also demonstrated that MCMC methods were particularly useful for geochemical parameter estimation using geophysical data because they allow incorporation into the procedure of spatial correlation information, measurement errors, and cross correlations among different types of parameters.

Uncertainty quantification for accident management using ACE surrogates

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

Varuttamaseni, A.; Lee, J. C.; Youngblood, R. W.

The alternating conditional expectation (ACE) regression method is used to generate RELAP5 surrogates which are then used to determine the distribution of the peak clad temperature (PCT) during the loss of feedwater accident coupled with a subsequent initiation of the feed and bleed (F and B) operation in the Zion-1 nuclear power plant. The construction of the surrogates assumes conditional independence relations among key reactor parameters. The choice of parameters to model is based on the macroscopic balance statements governing the behavior of the reactor. The peak clad temperature is calculated based on the independent variables that are known tomore » be important in determining the success of the F and B operation. The relationship between these independent variables and the plant parameters such as coolant pressure and temperature is represented by surrogates that are constructed based on 45 RELAP5 cases. The time-dependent PCT for different values of F and B parameters is calculated by sampling the independent variables from their probability distributions and propagating the information through two layers of surrogates. The results of our analysis show that the ACE surrogates are able to satisfactorily reproduce the behavior of the plant parameters even though a quasi-static assumption is primarily used in their construction. The PCT is found to be lower in cases where the F and B operation is initiated, compared to the case without F and B, regardless of the F and B parameters used. (authors)« less

Time-dependent landslide probability mapping

USGS Publications Warehouse

Campbell, Russell H.; Bernknopf, Richard L.; ,

1993-01-01

Case studies where time of failure is known for rainfall-triggered debris flows can be used to estimate the parameters of a hazard model in which the probability of failure is a function of time. As an example, a time-dependent function for the conditional probability of a soil slip is estimated from independent variables representing hillside morphology, approximations of material properties, and the duration and rate of rainfall. If probabilities are calculated in a GIS (geomorphic information system ) environment, the spatial distribution of the result for any given hour can be displayed on a map. Although the probability levels in this example are uncalibrated, the method offers a potential for evaluating different physical models and different earth-science variables by comparing the map distribution of predicted probabilities with inventory maps for different areas and different storms. If linked with spatial and temporal socio-economic variables, this method could be used for short-term risk assessment.

The significance of spatial variability of rainfall on streamflow: A synthetic analysis at the Upper Lee catchment, UK

NASA Astrophysics Data System (ADS)

Pechlivanidis, Ilias; McIntyre, Neil; Wheater, Howard

2017-04-01

Rainfall, one of the main inputs in hydrological modeling, is a highly heterogeneous process over a wide range of scales in space, and hence the ignorance of the spatial rainfall information could affect the simulated streamflow. Calibration of hydrological model parameters is rarely a straightforward task due to parameter equifinality and parameters' 'nature' to compensate for other uncertainties, i.e. structural and forcing input. In here, we analyse the significance of spatial variability of rainfall on streamflow as a function of catchment scale and type, and antecedent conditions using the continuous time, semi-distributed PDM hydrological model at the Upper Lee catchment, UK. The impact of catchment scale and type is assessed using 11 nested catchments ranging in scale from 25 to 1040 km2, and further assessed by artificially changing the catchment characteristics and translating these to model parameters with uncertainty using model regionalisation. Synthetic rainfall events are introduced to directly relate the change in simulated streamflow to the spatial variability of rainfall. Overall, we conclude that the antecedent catchment wetness and catchment type play an important role in controlling the significance of the spatial distribution of rainfall on streamflow. Results show a relationship between hydrograph characteristics (streamflow peak and volume) and the degree of spatial variability of rainfall for the impermeable catchments under dry antecedent conditions, although this decreases at larger scales; however this sensitivity is significantly undermined under wet antecedent conditions. Although there is indication that the impact of spatial rainfall on streamflow varies as a function of catchment scale, the variability of antecedent conditions between the synthetic catchments seems to mask this significance. Finally, hydrograph responses to different spatial patterns in rainfall depend on assumptions used for model parameter estimation and also the spatial variation in parameters indicating the need of an uncertainty framework in such investigation.

Thermo-Mechanical Calculations of Hybrid Rotary Friction Welding at Equal Diameter Copper Bars and Effects of Essential Parameters on Dependent Special Variables

NASA Astrophysics Data System (ADS)

Parsa, M. H.; Davari, H.; Hadian, A. M.; Ahmadabadi, M. Nili

2007-05-01

Hybrid Rotary Friction Welding is a modified type of common rotary friction welding processes. In this welding method parameters such as pressure, angular velocity and time of welding control temperature, stress, strain and their variations. These dependent factors play an important rule in defining optimum process parameters combinations in order to improve the design and manufacturing of welding machines and quality of welded parts. Thermo-mechanical simulation of friction welding has been carried out and it has been shown that, simulation is an important tool for prediction of generated heat and strain at the weld interface and can be used for prediction of microstructure and evaluation of quality of welds. For simulation of Hybrid Rotary Friction Welding, a commercial finite element program has been used and the effects of pressure and rotary velocity of rotary part on temperature and strain variations have been investigated.

On determining important aspects of mathematical models: Application to problems in physics and chemistry

NASA Technical Reports Server (NTRS)

Rabitz, Herschel

1987-01-01

The use of parametric and functional gradient sensitivity analysis techniques is considered for models described by partial differential equations. By interchanging appropriate dependent and independent variables, questions of inverse sensitivity may be addressed to gain insight into the inversion of observational data for parameter and function identification in mathematical models. It may be argued that the presence of a subset of dominantly strong coupled dependent variables will result in the overall system sensitivity behavior collapsing into a simple set of scaling and self similarity relations amongst elements of the entire matrix of sensitivity coefficients. These general tools are generic in nature, but herein their application to problems arising in selected areas of physics and chemistry is presented.

Shoulder pain and time dependent structure in wheelchair propulsion variability.

PubMed

Jayaraman, Chandrasekaran; Moon, Yaejin; Sosnoff, Jacob J

2016-07-01

Manual wheelchair propulsion places considerable repetitive mechanical strain on the upper limbs leading to shoulder injury and pain. While recent research indicates that the amount of variability in wheelchair propulsion and shoulder pain may be related. There has been minimal inquiry into the fluctuation over time (i.e. time-dependent structure) in wheelchair propulsion variability. Consequently the purpose of this investigation was to examine if the time-dependent structure in the wheelchair propulsion parameters are related to shoulder pain. 27 experienced wheelchair users manually propelled their own wheelchair fitted with a SMARTWheel on a roller at 1.1m/s for 3min. Time-dependent structure of cycle-to-cycle fluctuations in contact angle and inter push time interval was quantified using sample entropy (SampEn) and compared between the groups with/without shoulder pain using non-parametric statistics. Overall findings were, (1) variability observed in contact angle fluctuations during manual wheelchair propulsion is structured (Z=3.15;p<0.05), (2) individuals with shoulder pain exhibited higher SampEn magnitude for contact angle during wheelchair propulsion than those without pain (χ(2)(1)=6.12;p<0.05); and (3) SampEn of contact angle correlated significantly with self-reported shoulder pain (rs (WUSPI) =0.41;rs (VAS)=0.56;p<0.05). It was concluded that the time-dependent structure in wheelchair propulsion may provide novel information for tracking and monitoring shoulder pain. Copyright © 2016 IPEM. Published by Elsevier Ltd. All rights reserved.

Homogenous polynomially parameter-dependent H∞ filter designs of discrete-time fuzzy systems.

PubMed

Zhang, Huaguang; Xie, Xiangpeng; Tong, Shaocheng

2011-10-01

This paper proposes a novel H(∞) filtering technique for a class of discrete-time fuzzy systems. First, a novel kind of fuzzy H(∞) filter, which is homogenous polynomially parameter dependent on membership functions with an arbitrary degree, is developed to guarantee the asymptotic stability and a prescribed H(∞) performance of the filtering error system. Second, relaxed conditions for H(∞) performance analysis are proposed by using a new fuzzy Lyapunov function and the Finsler lemma with homogenous polynomial matrix Lagrange multipliers. Then, based on a new kind of slack variable technique, relaxed linear matrix inequality-based H(∞) filtering conditions are proposed. Finally, two numerical examples are provided to illustrate the effectiveness of the proposed approach.

Spatial Dependence and Heterogeneity in Bayesian Factor Analysis: A Cross-National Investigation of Schwartz Values

ERIC Educational Resources Information Center

Stakhovych, Stanislav; Bijmolt, Tammo H. A.; Wedel, Michel

2012-01-01

In this article, we present a Bayesian spatial factor analysis model. We extend previous work on confirmatory factor analysis by including geographically distributed latent variables and accounting for heterogeneity and spatial autocorrelation. The simulation study shows excellent recovery of the model parameters and demonstrates the consequences…

A Survival Model for Shortleaf Pine Tress Growing in Uneven-Aged Stands

Treesearch

Thomas B. Lynch; Lawrence R. Gering; Michael M. Huebschmann; Paul A. Murphy

1999-01-01

A survival model for shortleaf pine (Pinus echinata Mill.) trees growing in uneven-aged stands was developed using data from permanently established plots maintained by an industrial forestry company in western Arkansas. Parameters were fitted to a logistic regression model with a Bernoulli dependent variable in which "0" represented...

Additive Manufacturing in Production: A Study Case Applying Technical Requirements

NASA Astrophysics Data System (ADS)

Ituarte, Iñigo Flores; Coatanea, Eric; Salmi, Mika; Tuomi, Jukka; Partanen, Jouni

Additive manufacturing (AM) is expanding the manufacturing capabilities. However, quality of AM produced parts is dependent on a number of machine, geometry and process parameters. The variability of these parameters affects the manufacturing drastically and therefore standardized processes and harmonized methodologies need to be developed to characterize the technology for end use applications and enable the technology for manufacturing. This research proposes a composite methodology integrating Taguchi Design of Experiments, multi-objective optimization and statistical process control, to optimize the manufacturing process and fulfil multiple requirements imposed to an arbitrary geometry. The proposed methodology aims to characterize AM technology depending upon manufacturing process variables as well as to perform a comparative assessment of three AM technologies (Selective Laser Sintering, Laser Stereolithography and Polyjet). Results indicate that only one machine, laser-based Stereolithography, was feasible to fulfil simultaneously macro and micro level geometrical requirements but mechanical properties were not at required level. Future research will study a single AM system at the time to characterize AM machine technical capabilities and stimulate pre-normative initiatives of the technology for end use applications.

Transverse momentum dependence of spectra of cumulative particles produced from droplets of dense nuclear matter

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

Vechernin, Vladimir

2016-01-22

The transverse momentum dependence of the yields of particles produced from the clusters of dense cold nuclear matter in nuclei is calculated in the approach based on perturbative QCD calculations of the corresponding quark diagrams near the thresholds. It is shown that the transverse momentum dependence of the pion and proton spectra at different values of the Feynman variable x in the cumulative region, x > 1, can be described by the only parameter - the constituent quark mass, taken to be equal 300 MeV. It is found that the cumulative protons are formed predominantly via a coherent coalescence of threemore » fast cluster quarks, whereas the production of cumulative pions is dominated by one fast cluster quark hadronization. This enabled to explain the experimentally observed more slow increase of the mean transverse momentum of cumulative protons with the increase of the cumulative variable x, compared to pions.« less

TRUMP. Transient & S-State Temperature Distribution

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

Elrod, D.C.; Turner, W.D.

1992-03-03

TRUMP solves a general nonlinear parabolic partial differential equation describing flow in various kinds of potential fields, such as fields of temperature, pressure, or electricity and magnetism; simultaneously, it will solve two additional equations representing, in thermal problems, heat production by decomposition of two reactants having rate constants with a general Arrhenius temperature dependence. Steady-state and transient flow in one, two, or three dimensions are considered in geometrical configurations having simple or complex shapes and structures. Problem parameters may vary with spatial position, time, or primary dependent variables, temperature, pressure, or field strength. Initial conditions may vary with spatial position,more » and among the criteria that may be specified for ending a problem are upper and lower limits on the size of the primary dependent variable, upper limits on the problem time or on the number of time-steps or on the computer time, and attainment of steady state.« less

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

Elrod, D.C.; Turner, W.D.

TRUMP solves a general nonlinear parabolic partial differential equation describing flow in various kinds of potential fields, such as fields of temperature, pressure, or electricity and magnetism; simultaneously, it will solve two additional equations representing, in thermal problems, heat production by decomposition of two reactants having rate constants with a general Arrhenius temperature dependence. Steady-state and transient flow in one, two, or three dimensions are considered in geometrical configurations having simple or complex shapes and structures. Problem parameters may vary with spatial position, time, or primary dependent variables, temperature, pressure, or field strength. Initial conditions may vary with spatial position,more » and among the criteria that may be specified for ending a problem are upper and lower limits on the size of the primary dependent variable, upper limits on the problem time or on the number of time-steps or on the computer time, and attainment of steady state.« less

Random Predictor Models for Rigorous Uncertainty Quantification: Part 2

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Kenny, Sean P.; Giesy, Daniel P.

2015-01-01

This and a companion paper propose techniques for constructing parametric mathematical models describing key features of the distribution of an output variable given input-output data. By contrast to standard models, which yield a single output value at each value of the input, Random Predictors Models (RPMs) yield a random variable at each value of the input. Optimization-based strategies for calculating RPMs having a polynomial dependency on the input and a linear dependency on the parameters are proposed. These formulations yield RPMs having various levels of fidelity in which the mean, the variance, and the range of the model's parameter, thus of the output, are prescribed. As such they encompass all RPMs conforming to these prescriptions. The RPMs are optimal in the sense that they yield the tightest predictions for which all (or, depending on the formulation, most) of the observations are less than a fixed number of standard deviations from the mean prediction. When the data satisfies mild stochastic assumptions, and the optimization problem(s) used to calculate the RPM is convex (or, when its solution coincides with the solution to an auxiliary convex problem), the model's reliability, which is the probability that a future observation would be within the predicted ranges, is bounded rigorously.

Random Predictor Models for Rigorous Uncertainty Quantification: Part 1

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Kenny, Sean P.; Giesy, Daniel P.

2015-01-01

This and a companion paper propose techniques for constructing parametric mathematical models describing key features of the distribution of an output variable given input-output data. By contrast to standard models, which yield a single output value at each value of the input, Random Predictors Models (RPMs) yield a random variable at each value of the input. Optimization-based strategies for calculating RPMs having a polynomial dependency on the input and a linear dependency on the parameters are proposed. These formulations yield RPMs having various levels of fidelity in which the mean and the variance of the model's parameters, thus of the predicted output, are prescribed. As such they encompass all RPMs conforming to these prescriptions. The RPMs are optimal in the sense that they yield the tightest predictions for which all (or, depending on the formulation, most) of the observations are less than a fixed number of standard deviations from the mean prediction. When the data satisfies mild stochastic assumptions, and the optimization problem(s) used to calculate the RPM is convex (or, when its solution coincides with the solution to an auxiliary convex problem), the model's reliability, which is the probability that a future observation would be within the predicted ranges, can be bounded tightly and rigorously.

Vertical Variability of Rain Drop Size Distribution from Micro Rain Radar Measurements during IFloodS

NASA Astrophysics Data System (ADS)

Adirosi, Elisa; Tokay, Ali; Roberto, Nicoletta; Gorgucci, Eugenio; Montopoli, Mario; Baldini, Luca

2017-04-01

Ground based weather radars are highly used to generate rainfall products for meteorological and hydrological applications. However, weather radar quantitative rainfall estimation is obtained at a certain altitude that depends mainly on the radar elevation angle and on the distance from the radar. Therefore, depending on the vertical variability of rainfall, a time-height ambiguity between radar measurement and rainfall at the ground can affect the rainfall products. The vertically pointing radars (such as the Micro Rain Radar, MRR) are great tool to investigate the vertical variability of rainfall and its characteristics and ultimately, to fill the gap between the ground level and the first available radar elevation. Furthermore, the knowledge of rain Drop Size Distribution (DSD) variability is linked to the well-known problem of the non-uniform beam filling that is one of the main uncertainties of Global Precipitation Measurement (GPM) mission Dual frequency Precipitation Radar (DPR). During GPM Ground Validation Iowa Flood Studies (IFloodS) field experiment, data collected with 2D video disdrometers (2DVD), Autonomous OTT Parsivel2 Units (APU), and MRR profilers at different sites were available. In three different sites co-located APU, 2DVD and MRR are available and covered by the S-band Dual Polarimetric Doppler radar (NPOL). The first elevation height of the radar beam varies, among the three sites, between 70 m and 1100 m. The IFloodS set-up has been used to compare disdrometers, MRR and NPOL data and to evaluate the uncertainties of those measurements. First, the performance of disdrometers and MRR in determining different rainfall parameters at ground has been evaluated and then the MRR based parameters have been compared with the ones obtained from NPOL data at the lowest elevations. Furthermore, the vertical variability of DSD and integral rainfall parameters within the MRR bins (from ground to 1085 m each 35 m) has been investigated in order to provide some insight on the variability of the rainfall microphysical characteristics within about 1 km above the ground.

Possible influences of exercise-intensity-dependent increases in non-cortical hemodynamic variables on NIRS-based neuroimaging analysis during cognitive tasks: Technical note

PubMed Central

Byun, Kyeongho; Hyodo, Kazuki; Suwabe, Kazuya; Kujach, Sylwester; Kato, Morimasa; Soya, Hideaki

2014-01-01

[Purpose] Functional near-infrared spectroscopy (fNIRS) provides functional imaging of cortical activations by measuring regional oxy- and deoxy-hemoglobin (Hb) changes in the forehead during a cognitive task. There are, however, potential problems regarding NIRS signal contamination by non-cortical hemodynamic (NCH) variables such as skin blood flow, middle cerebral artery blood flow, and heart rate (HR), which are further complicated during acute exercise. It is thus necessary to determine the appropriate post-exercise timing that allows for valid NIRS assessment during a task without any increase in NCH variables. Here, we monitored post-exercise changes in NCH parameters with different intensities of exercise. [Methods] Fourteen healthy young participants cycled 30, 50 and 70% of their peak oxygen uptake (Vo2peak) for 10 min per intensity, each on different days. Changes in skin blood flow velocity (SBFv), middle cerebral artery mean blood velocity (MCA Vmean) and HR were monitored before, during, and after the exercise. [Results] Post-exercise levels of both SBFv and HR in contrast to MCA Vmean remained high compared to basal levels and the times taken to return to baseline levels for both parameters were delayed (2-8 min after exercise), depending upon exercise intensity. [Conclusion] These results indicate that the delayed clearance of NCH variables of up to 8 min into the post-exercise phase may contaminate NIRS measurements, and could be a limitation of NIRS-based neuroimaging studies. PMID:25671198

Multi-wavelength campaign on NGC 7469. II. Column densities and variability in the X-ray spectrum

NASA Astrophysics Data System (ADS)

Peretz, U.; Behar, E.; Kriss, G. A.; Kaastra, J.; Arav, N.; Bianchi, S.; Branduardi-Raymont, G.; Cappi, M.; Costantini, E.; De Marco, B.; Di Gesu, L.; Ebrero, J.; Kaspi, S.; Mehdipour, M.; Middei, R.; Paltani, S.; Petrucci, P. O.; Ponti, G.; Ursini, F.

2018-01-01

We have investigated the ionic column density variability of the ionized outflows associated with NGC 7469, to estimate their location and power. This could allow a better understanding of galactic feedback of AGNs to their host galaxies. Analysis of seven XMM-Newton grating observations from 2015 is reported. We used an individual-ion spectral fitting approach, and compared different epochs to accurately determine variability on timescales of years, months, and days. We find no significant column density variability in a ten-year period implying that the outflow is far from the ionizing source. The implied lower bound on the ionization equilibrium time, ten years, constrains the lower limit on the distance to be at least 12 pc, and up to 31 pc, much less but consistent with the 1 kpc wide starburst ring. The ionization distribution of column density is reconstructed from measured column densities, nicely matching results of two 2004 observations, with one large high ionization parameter (ξ) component at 2 < log ξ< 3.5, and one at 0.5 < log ξ< 1 in cgs units. The strong dependence of the expression for kinetic power, ∝ 1 /ξ, hampers tight constraints on the feedback mechanism of outflows with a large range in ionization parameter, which is often observed and indicates a non-conical outflow. The kinetic power of the outflow is estimated here to be within 0.4 and 60% of the Eddington luminosity, depending on the ion used to estimate ξ.

Soliton and periodic solutions for time-dependent coefficient non-linear equation

NASA Astrophysics Data System (ADS)

Guner, Ozkan

2016-01-01

In this article, we establish exact solutions for the generalized (3+1)-dimensional variable coefficient Kadomtsev-Petviashvili (GVCKP) equation. Using solitary wave ansatz in terms of ? functions and the modified sine-cosine method, we find exact analytical bright soliton solutions and exact periodic solutions for the considered model. The physical parameters in the soliton solutions are obtained as function of the dependent model coefficients. The effectiveness and reliability of the method are shown by its application to the GVCKP equation.

The true invariant of an arbitrage free portfolio

NASA Astrophysics Data System (ADS)

Schmidt, Anatoly B.

2003-03-01

It is shown that the arbitrage free portfolio paradigm being applied to a portfolio with an arbitrary number of shares N allows for the extended solution in which the option price F depends on N. However the resulting stock hedging expense Q= MF (where M is the number of options in the portfolio) does not depend on whether N is treated as an independent variable or as a parameter. Therefore the stock hedging expense is the true invariant of the arbitrage free portfolio paradigm.

Identification of a thermo-elasto-viscoplastic behavior law for the simulation of thermoforming of high impact polystyrene

NASA Astrophysics Data System (ADS)

Atmani, O.; Abbès, B.; Abbès, F.; Li, Y. M.; Batkam, S.

2018-05-01

Thermoforming of high impact polystyrene sheets (HIPS) requires technical knowledge on material behavior, mold type, mold material, and process variables. Accurate thermoforming simulations are needed in the optimization process. Determining the behavior of the material under thermoforming conditions is one of the key parameters for an accurate simulation. The aim of this work is to identify the thermomechanical behavior of HIPS in the thermoforming conditions. HIPS behavior is highly dependent on temperature and strain rate. In order to reproduce the behavior of such material, a thermo-elasto-viscoplastic constitutive law was implement in the finite element code ABAQUS. The proposed model parameters are considered as thermo-dependent. The strain-dependence effect is introduced using Prony series. Tensile tests were carried out at different temperatures and strain rates. The material parameters were then identified using a NSGA-II algorithm. To validate the rheological model, experimental blowing tests were carried out on a thermoforming pilot machine. To compare the numerical results with the experimental ones the thickness distribution and the bubble shape were investigated.

Modeling the dynamics of choice.

PubMed

Baum, William M; Davison, Michael

2009-06-01

A simple linear-operator model both describes and predicts the dynamics of choice that may underlie the matching relation. We measured inter-food choice within components of a schedule that presented seven different pairs of concurrent variable-interval schedules for 12 food deliveries each with no signals indicating which pair was in force. This measure of local choice was accurately described and predicted as obtained reinforcer sequences shifted it to favor one alternative or the other. The effect of a changeover delay was reflected in one parameter, the asymptote, whereas the effect of a difference in overall rate of food delivery was reflected in the other parameter, rate of approach to the asymptote. The model takes choice as a primary dependent variable, not derived by comparison between alternatives-an approach that agrees with the molar view of behaviour.

Resistance to uprooting of Alfalfa and Avena Sativa and related importance for flume experiments

NASA Astrophysics Data System (ADS)

Edmaier, K.; Crouzy, B.; Burlando, P.; Perona, P.

2012-04-01

Vegetation influences sediment dynamics by stabilizing the alluvial sediment with its root system. Thus, vegetation engineers the riparian ecosystem by contributing to the formation and stabilization of river bars and islands. The resistance to uprooting of young plants in non-cohesive sediment depends on the competition between flow induced drag and root growth timescales. The investigation of flow-sediment-plant interactions in situ is difficult since variables cannot be controlled and material hardly be collected. In order to investigate ecomorphological processes, laboratory experiments are essential and have gained importance in the last decade. To achieve a better understanding of the dependence of resistance to uprooting on the root system (length and structure) we conducted vertical uprooting experiments with Alfalfa and Avena Sativa which are both species that have been used in flume experiments on vegetation-flow interactions (e.g. Tal and Paola, 2010; Perona et al., in press). Seeds were seeded on quartz sand and vertically uprooted with constant velocity whereat the weight force required to uproot a seedling was measured. After uprooting, roots were scanned and analyzed and the correlation of root parameters with the uprooting work was studied. Total root length was found to be the best explanatory variable, in particular the uprooting work increases following a power law with increasing root length. The impact of other root parameters (main root length, root number, tortuosity) on the uprooting work was as well analyzed. Still, not all influencing root parameters could be captured, like the angle between roots or root hair distribution. Environmental conditions like grain size and saturation were also found to have an effect on the uprooting resistance of roots. So, lower saturated sediment results in a higher uprooting work. This work is a first step to better understand the energy regime for vegetation uprooting and its dependence on various biological and hydraulic variables. Future experiments using the same sediment and vegetation species will apply this knowledge to further investigate flow-vegetation-sediment interactions.

Replicates in high dimensions, with applications to latent variable graphical models.

PubMed

Tan, Kean Ming; Ning, Yang; Witten, Daniela M; Liu, Han

2016-12-01

In classical statistics, much thought has been put into experimental design and data collection. In the high-dimensional setting, however, experimental design has been less of a focus. In this paper, we stress the importance of collecting multiple replicates for each subject in this setting. We consider learning the structure of a graphical model with latent variables, under the assumption that these variables take a constant value across replicates within each subject. By collecting multiple replicates for each subject, we are able to estimate the conditional dependence relationships among the observed variables given the latent variables. To test the null hypothesis of conditional independence between two observed variables, we propose a pairwise decorrelated score test. Theoretical guarantees are established for parameter estimation and for this test. We show that our proposal is able to estimate latent variable graphical models more accurately than some existing proposals, and apply the proposed method to a brain imaging dataset.

Electrical transport via variable range hopping in an individual multi-wall carbon nanotube

NASA Astrophysics Data System (ADS)

Husain Khan, Zishan; Husain, M.; Perng, T. P.; Salah, Numan; Habib, Sami

2008-11-01

E-beam lithography is used to make four leads on an individual multi-wall carbon nanotube for carrying out electrical transport measurements. Temperature dependence of conductance of an individual multi-wall carbon nanotube (MWNT) is studied over a temperature range of (297 4.8 K). The results indicate that the conduction is governed by variable range hopping (VRH) for the entire temperature range (297 4.8 K). This VRH mechanism changes from three dimensions (3D) to two dimensions (2D) as we go down to 70 K. Three-dimensional variable range hopping (3D VRH) is responsible for conduction in the temperature range (297 70 K), which changes to two-dimensional VRH for much lower temperatures (70 4.8 K). For 3D VRH, various Mott parameters such as density of states, hopping distance and hopping energy have been calculated. The 2D VRH mechanism has been applied for the temperature range (70 4.8 K) and, with the help of this model, the parameters such as localization length and hopping distance are calculated. All these parameters give interesting information about this complex structure, which may be useful for many applications.

On parametric Gevrey asymptotics for some nonlinear initial value Cauchy problems

NASA Astrophysics Data System (ADS)

Lastra, A.; Malek, S.

2015-11-01

We study a nonlinear initial value Cauchy problem depending upon a complex perturbation parameter ɛ with vanishing initial data at complex time t = 0 and whose coefficients depend analytically on (ɛ, t) near the origin in C2 and are bounded holomorphic on some horizontal strip in C w.r.t. the space variable. This problem is assumed to be non-Kowalevskian in time t, therefore analytic solutions at t = 0 cannot be expected in general. Nevertheless, we are able to construct a family of actual holomorphic solutions defined on a common bounded open sector with vertex at 0 in time and on the given strip above in space, when the complex parameter ɛ belongs to a suitably chosen set of open bounded sectors whose union form a covering of some neighborhood Ω of 0 in C*. These solutions are achieved by means of Laplace and Fourier inverse transforms of some common ɛ-depending function on C × R, analytic near the origin and with exponential growth on some unbounded sectors with appropriate bisecting directions in the first variable and exponential decay in the second, when the perturbation parameter belongs to Ω. Moreover, these solutions satisfy the remarkable property that the difference between any two of them is exponentially flat for some integer order w.r.t. ɛ. With the help of the classical Ramis-Sibuya theorem, we obtain the existence of a formal series (generally divergent) in ɛ which is the common Gevrey asymptotic expansion of the built up actual solutions considered above.

Erosive Augmentation of Solid Propellant Burning Rate: Motor Size Scaling Effect

NASA Technical Reports Server (NTRS)

Strand, L. D.; Cohen, Norman S.

1990-01-01

Two different independent variable forms, a difference form and a ratio form, were investigated for correlating the normalized magnitude of the measured erosive burning rate augmentation above the threshold in terms of the amount that the driving parameter (mass flux or Reynolds number) exceeds the threshold value for erosive augmentation at the test condition. The latter was calculated from the previously determined threshold correlation. Either variable form provided a correlation for each of the two motor size data bases individually. However, the data showed a motor size effect, supporting the general observation that the magnitude of erosive burning rate augmentation is reduced for larger rocket motors. For both independent variable forms, the required motor size scaling was attained by including the motor port radius raised to a power in the independent parameter. A boundary layer theory analysis confirmed the experimental finding, but showed that the magnitude of the scale effect is itself dependent upon scale, tending to diminish with increasing motor size.

Effect of multiplicative noise on stationary stochastic process

NASA Astrophysics Data System (ADS)

Kargovsky, A. V.; Chikishev, A. Yu.; Chichigina, O. A.

2018-03-01

An open system that can be analyzed using the Langevin equation with multiplicative noise is considered. The stationary state of the system results from a balance of deterministic damping and random pumping simulated as noise with controlled periodicity. The dependence of statistical moments of the variable that characterizes the system on parameters of the problem is studied. A nontrivial decrease in the mean value of the main variable with an increase in noise stochasticity is revealed. Applications of the results in several physical, chemical, biological, and technical problems of natural and humanitarian sciences are discussed.

An opinion-driven behavioral dynamics model for addictive behaviors

DOE PAGES

Moore, Thomas W.; Finley, Patrick D.; Apelberg, Benjamin J.; ...

2015-04-08

We present a model of behavioral dynamics that combines a social network-based opinion dynamics model with behavioral mapping. The behavioral component is discrete and history-dependent to represent situations in which an individual’s behavior is initially driven by opinion and later constrained by physiological or psychological conditions that serve to maintain the behavior. Additionally, individuals are modeled as nodes in a social network connected by directed edges. Parameter sweeps illustrate model behavior and the effects of individual parameters and parameter interactions on model results. Mapping a continuous opinion variable into a discrete behavioral space induces clustering on directed networks. Clusters providemore » targets of opportunity for influencing the network state; however, the smaller the network the greater the stochasticity and potential variability in outcomes. Furthermore, this has implications both for behaviors that are influenced by close relationships verses those influenced by societal norms and for the effectiveness of strategies for influencing those behaviors.« less

Magnetohydrodynamic dissipative flow across the slendering stretching sheet with temperature dependent variable viscosity

NASA Astrophysics Data System (ADS)

Jayachandra Babu, M.; Sandeep, N.; Ali, M. E.; Nuhait, Abdullah O.

The boundary layer flow across a slendering stretching sheet has gotten awesome consideration due to its inexhaustible pragmatic applications in nuclear reactor technology, acoustical components, chemical and manufacturing procedures, for example, polymer extrusion, and machine design. By keeping this in view, we analyzed the two-dimensional MHD flow across a slendering stretching sheet within the sight of variable viscosity and viscous dissipation. The sheet is thought to be convectively warmed. Convective boundary conditions through heat and mass are employed. Similarity transformations used to change over the administering nonlinear partial differential equations as a group of nonlinear ordinary differential equations. Runge-Kutta based shooting technique is utilized to solve the converted equations. Numerical estimations of the physical parameters involved in the problem are calculated for the friction factor, local Nusselt and Sherwood numbers. Viscosity variation parameter and chemical reaction parameter shows the opposite impact to each other on the concentration profile. Heat and mass transfer Biot numbers are helpful to enhance the temperature and concentration respectively.

Design considerations of high-performance InGaAs/InP single-photon avalanche diodes for quantum key distribution.

PubMed

Ma, Jian; Bai, Bing; Wang, Liu-Jun; Tong, Cun-Zhu; Jin, Ge; Zhang, Jun; Pan, Jian-Wei

2016-09-20

InGaAs/InP single-photon avalanche diodes (SPADs) are widely used in practical applications requiring near-infrared photon counting such as quantum key distribution (QKD). Photon detection efficiency and dark count rate are the intrinsic parameters of InGaAs/InP SPADs, due to the fact that their performances cannot be improved using different quenching electronics given the same operation conditions. After modeling these parameters and developing a simulation platform for InGaAs/InP SPADs, we investigate the semiconductor structure design and optimization. The parameters of photon detection efficiency and dark count rate highly depend on the variables of absorption layer thickness, multiplication layer thickness, excess bias voltage, and temperature. By evaluating the decoy-state QKD performance, the variables for SPAD design and operation can be globally optimized. Such optimization from the perspective of specific applications can provide an effective approach to design high-performance InGaAs/InP SPADs.

Repeatability of Bolus Kinetics Ultrasound Perfusion Imaging for the Quantification of Cerebral Blood Flow.

PubMed

Vinke, Elisabeth J; Eyding, Jens; de Korte, Chris L; Slump, Cornelis H; van der Hoeven, Johannes G; Hoedemaekers, Cornelia W E

2017-12-01

Ultrasound perfusion imaging (UPI) can be used for the quantification of cerebral perfusion. In a neuro-intensive care setting, repeated measurements are required to evaluate changes in cerebral perfusion and monitor therapy. The aim of this study was to determine the repeatability of UPI in quantification of cerebral perfusion. UPI measurement of cerebral perfusion was performed three times in healthy patients. The coefficients of variation of the three bolus injections were calculated for both time- and volume-derived perfusion parameters in the macro- and microcirculation. The UPI time-dependent parameters had overall the lowest CVs in both the macro- and microcirculation. The volume-related parameters had poorer repeatability, especially in the microcirculation. Both intra-observer variability and inter-observer variability were low. Although UPI is a promising tool for the bedside measurement of cerebral perfusion, improvement of the technique is required before implementation in routine clinical practice. Copyright © 2017 World Federation for Ultrasound in Medicine and Biology. Published by Elsevier Inc. All rights reserved.

Variability in in vitro fertilization outcomes of prepubertal goat oocytes explained by basic semen analyses.

PubMed

Palomo, M J; Quintanilla, R; Izquierdo, M D; Mogas, T; Paramio, M T

2016-12-01

This work analyses the changes that caprine spermatozoa undergo during in vitro fertilization (IVF) of in vitro matured prepubertal goat oocytes and their relationship with IVF outcome, in order to obtain an effective model that allows prediction of in vitro fertility on the basis of semen assessment. The evolution of several sperm parameters (motility, viability and acrosomal integrity) during IVF and their relationship with three IVF outcome criteria (total penetration, normal penetration and cleavage rates) were studied in a total of 56 IVF replicates. Moderate correlation coefficients between some sperm parameters and IVF outcome were observed. In addition, stepwise multiple regression analyses were conducted that considered three grouping of sperm parameters as potential explanatory variables of the three IVF outcome criteria. The proportion of IVF outcome variation that can be explained by the fitted models ranged from 0.62 to 0.86, depending upon the trait analysed and the variables considered. Seven out of 32 sperm parameters were selected as partial covariates in at least one of the nine multiple regression models. Among these, progressive sperm motility assessed immediately after swim-up, the percentage of dead sperm with intact acrosome and the incidence of acrosome reaction both determined just before the gamete co-culture, and finally the proportion of viable spermatozoa at 17 h post-insemination were the most frequently selected sperm parameters. Nevertheless, the predictive ability of these models must be confirmed in a larger sample size experiment.

Error in the Sampling Area of an Optical Disdrometer: Consequences in Computing Rain Variables

PubMed Central

Fraile, R.; Castro, A.; Fernández-Raga, M.; Palencia, C.; Calvo, A. I.

2013-01-01

The aim of this study is to improve the estimation of the characteristic uncertainties of optic disdrometers in an attempt to calculate the efficient sampling area according to the size of the drop and to study how this influences the computation of other parameters, taking into account that the real sampling area is always smaller than the nominal area. For large raindrops (a little over 6 mm), the effective sampling area may be half the area indicated by the manufacturer. The error committed in the sampling area is propagated to all the variables depending on this surface, such as the rain intensity and the reflectivity factor. Both variables tend to underestimate the real value if the sampling area is not corrected. For example, the rainfall intensity errors may be up to 50% for large drops, those slightly larger than 6 mm. The same occurs with reflectivity values, which may be up to twice the reflectivity calculated using the uncorrected constant sampling area. The Z-R relationships appear to have little dependence on the sampling area, because both variables depend on it the same way. These results were obtained by studying one particular rain event that occurred on April 16, 2006. PMID:23844393

Potential for geophysical experiments in large scale tests.

USGS Publications Warehouse

Dieterich, J.H.

1981-01-01

Potential research applications for large-specimen geophysical experiments include measurements of scale dependence of physical parameters and examination of interactions with heterogeneities, especially flaws such as cracks. In addition, increased specimen size provides opportunities for improved recording resolution and greater control of experimental variables. Large-scale experiments using a special purpose low stress (100MPa).-Author

Synchronization in Biochemical Substance Exchange Between Two Cells

NASA Astrophysics Data System (ADS)

Mihailović, Dragutin T.; Balaž, Igor

In this paper, Mihailović et al. [Mod. Phys. Lett. B 25 (2011) 2407-2417] introduce a simplified model of cell communication in a form of coupled difference logistic equations. Then we investigated stability of exchange of signaling molecules under variability of internal and external parameters. However, we have not touched questions about synchronization and effect of noise on biochemical substance exchange between cells. In this paper, we consider synchronization in intercellular exchange in dependence of environmental and cell intrinsic parameters by analyzing the largest Lyapunov exponent, cross sample entropy and bifurcation maps.

Well-Tempered Metadynamics: A Smoothly Converging and Tunable Free-Energy Method

NASA Astrophysics Data System (ADS)

Barducci, Alessandro; Bussi, Giovanni; Parrinello, Michele

2008-01-01

We present a method for determining the free-energy dependence on a selected number of collective variables using an adaptive bias. The formalism provides a unified description which has metadynamics and canonical sampling as limiting cases. Convergence and errors can be rigorously and easily controlled. The parameters of the simulation can be tuned so as to focus the computational effort only on the physically relevant regions of the order parameter space. The algorithm is tested on the reconstruction of an alanine dipeptide free-energy landscape.

Well-tempered metadynamics: a smoothly converging and tunable free-energy method.

PubMed

Barducci, Alessandro; Bussi, Giovanni; Parrinello, Michele

2008-01-18

We present a method for determining the free-energy dependence on a selected number of collective variables using an adaptive bias. The formalism provides a unified description which has metadynamics and canonical sampling as limiting cases. Convergence and errors can be rigorously and easily controlled. The parameters of the simulation can be tuned so as to focus the computational effort only on the physically relevant regions of the order parameter space. The algorithm is tested on the reconstruction of an alanine dipeptide free-energy landscape.

Spectroscopic properties of a two-dimensional time-dependent Cepheid model. II. Determination of stellar parameters and abundances

NASA Astrophysics Data System (ADS)

Vasilyev, V.; Ludwig, H.-G.; Freytag, B.; Lemasle, B.; Marconi, M.

2018-03-01

Context. Standard spectroscopic analyses of variable stars are based on hydrostatic 1D model atmospheres. This quasi-static approach has not been theoretically validated. Aim. We aim at investigating the validity of the quasi-static approximation for Cepheid variables. We focus on the spectroscopic determination of the effective temperature Teff, surface gravity log g, microturbulent velocity ξt, and a generic metal abundance log A, here taken as iron. Methods: We calculated a grid of 1D hydrostatic plane-parallel models covering the ranges in effective temperature and gravity that are encountered during the evolution of a 2D time-dependent envelope model of a Cepheid computed with the radiation-hydrodynamics code CO5BOLD. We performed 1D spectral syntheses for artificial iron lines in local thermodynamic equilibrium by varying the microturbulent velocity and abundance. We fit the resulting equivalent widths to corresponding values obtained from our dynamical model for 150 instances in time, covering six pulsational cycles. In addition, we considered 99 instances during the initial non-pulsating stage of the temporal evolution of the 2D model. In the most general case, we treated Teff, log g, ξt, and log A as free parameters, and in two more limited cases, we fixed Teff and log g by independent constraints. We argue analytically that our approach of fitting equivalent widths is closely related to current standard procedures focusing on line-by-line abundances. Results: For the four-parametric case, the stellar parameters are typically underestimated and exhibit a bias in the iron abundance of ≈-0.2 dex. To avoid biases of this type, it is favorable to restrict the spectroscopic analysis to photometric phases ϕph ≈ 0.3…0.65 using additional information to fix the effective temperature and surface gravity. Conclusions: Hydrostatic 1D model atmospheres can provide unbiased estimates of stellar parameters and abundances of Cepheid variables for particular phases of their pulsations. We identified convective inhomogeneities as the main driver behind potential biases. To obtain a complete view on the effects when determining stellar parameters with 1D models, multidimensional Cepheid atmosphere models are necessary for variables of longer period than investigated here.

Ground-Motion Variability for a Strike-Slip Earthquake from Broadband Ground-Motion Simulations

NASA Astrophysics Data System (ADS)

Iwaki, A.; Maeda, T.; Morikawa, N.; Fujiwara, H.

2016-12-01

One of the important issues in seismic hazard analysis is the evaluation of ground-motion variability due to the epistemic and aleatory uncertainties in various aspects of ground-motion simulations. This study investigates the within-event ground-motion variability in broadband ground-motion simulations for strike-slip events. We conduct ground-motion simulations for a past event (2000 MW6.6 Tottori earthquake) using a set of characterized source models (e.g. Irikura and Miyake, 2011) considering aleatory variability. Broadband ground motion is computed by a hybrid approach that combines a 3D finite-difference method (> 1 s) and the stochastic Green's function method (< 1 s), using the 3D velocity model J-SHIS v2. We consider various locations of the asperities, which are defined as the regions with large slip and stress drop within the fault, and the rupture nucleation point (hypocenter). Ground motion records at 29 K-NET and KiK-net stations are used to validate our simulations. By comparing the simulated and observed ground motion, we found that the performance of the simulations is acceptable under the condition that the source parameters are poorly constrained. In addition to the observation stations, we set 318 virtual receivers with the spatial intervals of 10 km for statistical analysis of the simulated ground motion. The maximum fault-distance is 160 km. Standard deviation (SD) of the simulated acceleration response spectra (Sa, 5% damped) of RotD50 component (Boore, 2010) is investigated at each receiver. SD from 50 different patterns of asperity locations is generally smaller than 0.15 in terms of log10 (0.34 in natural log). It shows dependence on distance at periods shorter than 1 s; SD increases as the distance decreases. On the other hand, SD from 39 different hypocenter locations is again smaller than 0.15 in log10, and showed azimuthal dependence at long periods; it increases as the rupture directivity parameter Xcosθ(Somerville et al. 1997) increases at periods longer than 1 s. The characteristics of ground-motion variability inferred from simulations can provide information on variability in simulation-based seismic hazard assessment for future earthquakes. We will further investigate the variability in other source parameters; rupture velocity and short-period level.

Multi-Objective Optimization of a Turbofan for an Advanced, Single-Aisle Transport

NASA Technical Reports Server (NTRS)

Berton, Jeffrey J.; Guynn, Mark D.

2012-01-01

Considerable interest surrounds the design of the next generation of single-aisle commercial transports in the Boeing 737 and Airbus A320 class. Aircraft designers will depend on advanced, next-generation turbofan engines to power these airplanes. The focus of this study is to apply single- and multi-objective optimization algorithms to the conceptual design of ultrahigh bypass turbofan engines for this class of aircraft, using NASA s Subsonic Fixed Wing Project metrics as multidisciplinary objectives for optimization. The independent design variables investigated include three continuous variables: sea level static thrust, wing reference area, and aerodynamic design point fan pressure ratio, and four discrete variables: overall pressure ratio, fan drive system architecture (i.e., direct- or gear-driven), bypass nozzle architecture (i.e., fixed- or variable geometry), and the high- and low-pressure compressor work split. Ramp weight, fuel burn, noise, and emissions are the parameters treated as dependent objective functions. These optimized solutions provide insight to the ultrahigh bypass engine design process and provide information to NASA program management to help guide its technology development efforts.

Selection of entropy-measure parameters for knowledge discovery in heart rate variability data

PubMed Central

2014-01-01

Background Heart rate variability is the variation of the time interval between consecutive heartbeats. Entropy is a commonly used tool to describe the regularity of data sets. Entropy functions are defined using multiple parameters, the selection of which is controversial and depends on the intended purpose. This study describes the results of tests conducted to support parameter selection, towards the goal of enabling further biomarker discovery. Methods This study deals with approximate, sample, fuzzy, and fuzzy measure entropies. All data were obtained from PhysioNet, a free-access, on-line archive of physiological signals, and represent various medical conditions. Five tests were defined and conducted to examine the influence of: varying the threshold value r (as multiples of the sample standard deviation σ, or the entropy-maximizing rChon), the data length N, the weighting factors n for fuzzy and fuzzy measure entropies, and the thresholds rF and rL for fuzzy measure entropy. The results were tested for normality using Lilliefors' composite goodness-of-fit test. Consequently, the p-value was calculated with either a two sample t-test or a Wilcoxon rank sum test. Results The first test shows a cross-over of entropy values with regard to a change of r. Thus, a clear statement that a higher entropy corresponds to a high irregularity is not possible, but is rather an indicator of differences in regularity. N should be at least 200 data points for r = 0.2 σ and should even exceed a length of 1000 for r = rChon. The results for the weighting parameters n for the fuzzy membership function show different behavior when coupled with different r values, therefore the weighting parameters have been chosen independently for the different threshold values. The tests concerning rF and rL showed that there is no optimal choice, but r = rF = rL is reasonable with r = rChon or r = 0.2σ. Conclusions Some of the tests showed a dependency of the test significance on the data at hand. Nevertheless, as the medical conditions are unknown beforehand, compromises had to be made. Optimal parameter combinations are suggested for the methods considered. Yet, due to the high number of potential parameter combinations, further investigations of entropy for heart rate variability data will be necessary. PMID:25078574

Selection of entropy-measure parameters for knowledge discovery in heart rate variability data.

PubMed

Mayer, Christopher C; Bachler, Martin; Hörtenhuber, Matthias; Stocker, Christof; Holzinger, Andreas; Wassertheurer, Siegfried

2014-01-01

Heart rate variability is the variation of the time interval between consecutive heartbeats. Entropy is a commonly used tool to describe the regularity of data sets. Entropy functions are defined using multiple parameters, the selection of which is controversial and depends on the intended purpose. This study describes the results of tests conducted to support parameter selection, towards the goal of enabling further biomarker discovery. This study deals with approximate, sample, fuzzy, and fuzzy measure entropies. All data were obtained from PhysioNet, a free-access, on-line archive of physiological signals, and represent various medical conditions. Five tests were defined and conducted to examine the influence of: varying the threshold value r (as multiples of the sample standard deviation σ, or the entropy-maximizing rChon), the data length N, the weighting factors n for fuzzy and fuzzy measure entropies, and the thresholds rF and rL for fuzzy measure entropy. The results were tested for normality using Lilliefors' composite goodness-of-fit test. Consequently, the p-value was calculated with either a two sample t-test or a Wilcoxon rank sum test. The first test shows a cross-over of entropy values with regard to a change of r. Thus, a clear statement that a higher entropy corresponds to a high irregularity is not possible, but is rather an indicator of differences in regularity. N should be at least 200 data points for r = 0.2 σ and should even exceed a length of 1000 for r = rChon. The results for the weighting parameters n for the fuzzy membership function show different behavior when coupled with different r values, therefore the weighting parameters have been chosen independently for the different threshold values. The tests concerning rF and rL showed that there is no optimal choice, but r = rF = rL is reasonable with r = rChon or r = 0.2σ. Some of the tests showed a dependency of the test significance on the data at hand. Nevertheless, as the medical conditions are unknown beforehand, compromises had to be made. Optimal parameter combinations are suggested for the methods considered. Yet, due to the high number of potential parameter combinations, further investigations of entropy for heart rate variability data will be necessary.

Size, Loading Efficiency, and Cytotoxicity of Albumin-Loaded Chitosan Nanoparticles: An Artificial Neural Networks Study.

PubMed

Baharifar, Hadi; Amani, Amir

2017-01-01

When designing nanoparticles for drug delivery, many variables such as size, loading efficiency, and cytotoxicity should be considered. Usually, smaller particles are preferred in drug delivery because of longer blood circulation time and their ability to escape from immune system, whereas smaller nanoparticles often show increased toxicity. Determination of parameters which affect size of particles and factors such as loading efficiency and cytotoxicity could be very helpful in designing drug delivery systems. In this work, albumin (as a protein drug model)-loaded chitosan nanoparticles were prepared by polyelectrolyte complexation method. Simultaneously, effects of 4 independent variables including chitosan and albumin concentrations, pH, and reaction time were determined on 3 dependent variables (i.e., size, loading efficiency, and cytotoxicity) by artificial neural networks. Results showed that concentrations of initial materials are the most important factors which may affect the dependent variables. A drop in the concentrations decreases the size directly, but they simultaneously decrease loading efficiency and increase cytotoxicity. Therefore, an optimization of the independent variables is required to obtain the most useful preparation. Copyright © 2016 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

A fully Sinc-Galerkin method for Euler-Bernoulli beam models

NASA Technical Reports Server (NTRS)

Smith, R. C.; Bowers, K. L.; Lund, J.

1990-01-01

A fully Sinc-Galerkin method in both space and time is presented for fourth-order time-dependent partial differential equations with fixed and cantilever boundary conditions. The Sinc discretizations for the second-order temporal problem and the fourth-order spatial problems are presented. Alternate formulations for variable parameter fourth-order problems are given which prove to be especially useful when applying the forward techniques to parameter recovery problems. The discrete system which corresponds to the time-dependent partial differential equations of interest are then formulated. Computational issues are discussed and a robust and efficient algorithm for solving the resulting matrix system is outlined. Numerical results which highlight the method are given for problems with both analytic and singular solutions as well as fixed and cantilever boundary conditions.

Oxygen and iron production by electrolytic smelting of lunar soil

NASA Technical Reports Server (NTRS)

Haskin, Larry A.

1989-01-01

Previous work has shown that Fe(sup 0) and O2 can be derived by electrolysis from silicate smelt of a composition typical of lunar soils (Lindstrom and Haskin 1979). In the present study, the goal is to refine further the conditions necessary to optimize production and to determine efficiencies of production (how much product is derived for a given current) and purity of products. These depend on several factors, including potential imposed between electrodes, configuration and surface area of the electrodes, composition of the electrolyzed silicate melt, and oxygen fugacity. Experiments were designed to measure the dependence on these variables of three parameters that must be known before production by electrolysis can be optimized. These parameters are: Limiting Current; Actual Current; and Efficiencies of Production.

Variability in aerosol optical properties over an urban site, Kanpur, in the Indo-Gangetic Plain: A case study of haze and dust events

NASA Astrophysics Data System (ADS)

Ram, Kirpa; Singh, Sunita; Sarin, M. M.; Srivastava, A. K.; Tripathi, S. N.

2016-06-01

In this study, we report on three important optical parameters, viz. absorption and scattering coefficients (babs, bscat) and single scattering abledo (SSA) based on one-year chemical-composition data collected from an urban site (Kanpur) in the Indo-Gangetic-Plain (IGP) of northern India. In addition, absorption Ängstrom exponent (AAE) was also estimated in order to understand the wavelength dependence of absorption and to decipher emission sources of carbonaceous aerosols, in particular of black carbon. The absorption and scattering coefficients ranged between 8.3 to 95.2 Mm- 1 (1 Mm- 1 = 10- 6 m- 1) and 58 to 564 Mm- 1, respectively during the study period (for n = 66; from January 2007 to March 2008) and exhibit large seasonal variability with higher values occurring in winter and lower in the summer. Single scattering albedo varied from 0.65 to 0.92 whereas AAE ranged from 0.79 to 1.40 during pre-monsoon and winter seasons, respectively. The strong seasonal variability in aerosol optical properties is attributed to varying contribution from different emission sources of carbonaceous aerosols in the IGP. A case study of haze and dust events further provide information on extreme variability in aerosol optical parameters, particularly SSA, a crucial parameter in atmospheric radiative forcing estimates.

An investigation of the influence of process and formulation variables on mechanical properties of high shear granules using design of experiment.

PubMed

Mangwandi, Chirangano; Adams, Michael J; Hounslow, Michael J; Salman, Agba D

2012-05-10

Being able to predict the properties of granules from the knowledge of the process and formulation variables is what most industries are striving for. This research uses experimental design to investigate the effect of process variables and formulation variables on mechanical properties of pharmaceutical granules manufactured from a classical blend of lactose and starch using hydroxypropyl cellulose (HPC) as the binder. The process parameters investigated were granulation time and impeller speed whilst the formulation variables were starch-to-lactose ratio and HPC concentration. The granule properties investigated include granule packing coefficient and granule strength. The effect of some components of the formulation on mechanical properties would also depend on the process variables used in granulation process. This implies that by subjecting the same formulation to different process conditions results in products with different properties. Copyright © 2012 Elsevier B.V. All rights reserved.

3D ground‐motion simulations of Mw 7 earthquakes on the Salt Lake City segment of the Wasatch fault zone: Variability of long‐period (T≥1  s) ground motions and sensitivity to kinematic rupture parameters

USGS Publications Warehouse

Moschetti, Morgan P.; Hartzell, Stephen; Ramirez-Guzman, Leonardo; Frankel, Arthur; Angster, Stephen J.; Stephenson, William J.

2017-01-01

We examine the variability of long‐period (T≥1  s) earthquake ground motions from 3D simulations of Mw 7 earthquakes on the Salt Lake City segment of the Wasatch fault zone, Utah, from a set of 96 rupture models with varying slip distributions, rupture speeds, slip velocities, and hypocenter locations. Earthquake ruptures were prescribed on a 3D fault representation that satisfies geologic constraints and maintained distinct strands for the Warm Springs and for the East Bench and Cottonwood faults. Response spectral accelerations (SA; 1.5–10 s; 5% damping) were measured, and average distance scaling was well fit by a simple functional form that depends on the near‐source intensity level SA0(T) and a corner distance Rc:SA(R,T)=SA0(T)(1+(R/Rc))−1. Period‐dependent hanging‐wall effects manifested and increased the ground motions by factors of about 2–3, though the effects appeared partially attributable to differences in shallow site response for sites on the hanging wall and footwall of the fault. Comparisons with modern ground‐motion prediction equations (GMPEs) found that the simulated ground motions were generally consistent, except within deep sedimentary basins, where simulated ground motions were greatly underpredicted. Ground‐motion variability exhibited strong lateral variations and, at some sites, exceeded the ground‐motion variability indicated by GMPEs. The effects on the ground motions of changing the values of the five kinematic rupture parameters can largely be explained by three predominant factors: distance to high‐slip subevents, dynamic stress drop, and changes in the contributions from directivity. These results emphasize the need for further characterization of the underlying distributions and covariances of the kinematic rupture parameters used in 3D ground‐motion simulations employed in probabilistic seismic‐hazard analyses.

Seabirds as indicators of marine food supplies: Cairns revisited

USGS Publications Warehouse

Piatt, John F.; Harding, Ann M.A.; Shultz, Michael T.; Speckman, Suzann G.; van Pelt, Thomas I.; Drew, Gary S.; Kettle, Arthur B.

2007-01-01

In his seminal paper about using seabirds as indicators of marine food supplies, Cairns (1987, Biol Oceanogr 5:261–271) predicted that (1) parameters of seabird biology and behavior would vary in curvilinear fashion with changes in food supply, (2) the threshold of prey density over which birds responded would be different for each parameter, and (3) different seabird species would respond differently to variation in food availability depending on foraging behavior and ability to adjust time budgets. We tested these predictions using data collected at colonies of common murre Uria aalge and black-legged kittiwake Rissa tridactyla in Cook Inlet, Alaska. (1) Of 22 seabird responses fitted with linear and non-linear functions, 16 responses exhibited significant curvilinear shapes, and Akaike’s information criterion (AIC) analysis indicated that curvilinear functions provided the best-fitting model for 12 of those. (2) However, there were few differences among parameters in their threshold to prey density, presumably because most responses ultimately depend upon a single threshold for prey acquisition at sea. (3) There were similarities and some differences in how species responded to variability in prey density. Both murres and kittiwakes minimized variability (CV < 15%) in their own body condition and growth of chicks in the face of high annual variability (CV = 69%) in local prey density. Whereas kittiwake breeding success (CV = 63%, r2 = 0.89) reflected prey variability, murre breeding success did not (CV = 29%, r2< 0.00). It appears that murres were able to buffer breeding success by reallocating discretionary ‘loafing’ time to foraging effort in response (r2 = 0.64) to declining prey density. Kittiwakes had little or no discretionary time, so fledging success was a more direct function of local prey density. Implications of these results for using ‘seabirds as indicators’ are discussed.

Iontophoretic delivery of lisinopril: Optimization of process variables by Box-Behnken statistical design.

PubMed

Gannu, Ramesh; Yamsani, Vamshi Vishnu; Palem, Chinna Reddy; Yamsani, Shravan Kumar; Yamsani, Madhusudan Rao

2010-01-01

The objective of the investigation was to optimize the iontophoresis process parameters of lisinopril (LSP) by 3 x 3 factorial design, Box-Behnken statistical design. LSP is an ideal candidate for iontophoretic delivery to avoid the incomplete absorption problem associated after its oral administration. Independent variables selected were current (X(1)), salt (sodium chloride) concentration (X(2)) and medium/pH (X(3)). The dependent variables studied were amount of LSP permeated in 4 h (Y(1): Q(4)), 24 h (Y(2): Q(24)) and lag time (Y(3)). Mathematical equations and response surface plots were used to relate the dependent and independent variables. The regression equation generated for the iontophoretic permeation was Y(1) = 1.98 + 1.23X(1) - 0.49X(2) + 0.025X(3) - 0.49X(1)X(2) + 0.040X(1)X(3) - 0.010X(2)X(3) + 0.58X(1)(2) - 0.17X(2)(2) - 0.18X(3)(2); Y(2) = 7.28 + 3.32X(1) - 1.52X(2) + 0.22X(3) - 1.30X(1)X(2) + 0.49X(1)X(3) - 0.090X(2)X(3) + 0.79X(1)(2) - 0.62X(2)(2) - 0.33X(3)(2) and Y(3) = 0.60 + 0.0038X(1) + 0.12X(2) - 0.011X(3) + 0.005X(1)X(2) - 0.018X(1)X(3) - 0.015X(2)X(3) - 0.00075X(1)(2) + 0.017X(2)(2) - 0.11X(3)(2). The statistical validity of the polynomials was established and optimized process parameters were selected by feasibility and grid search. Validation of the optimization study with 8 confirmatory runs indicated high degree of prognostic ability of response surface methodology. The use of Box-Behnken design approach helped in identifying the critical process parameters in the iontophoretic delivery of lisinopril.

Understanding the relationships among phytoplankton, benthic macroinvertebrates, and water quality variables in peri-urban river systems.

PubMed

Pinto, Uthpala; Maheshwari, Basant L; Morris, E Charles

2014-12-01

In this article, using the Hawkesbury-Nepean River as a case study, the spatial and temporal trends of water quality variables over three sampling surveys in a peri-urban situation are examined for their effect on benthic macroinvertebrate communities and phytoplankton communities and whether phytoplankton and benthic macroinvertebrate species can be used as indicators for river health assessment. For this, the authors monitored the spatial and temporal difference of 10 water quality parameters: temperature, turbidity, pH, dissolved oxygen, electrical conductivity, oxidation reduction potential, total nitrogen, total phosphorus, manganese, and suspended solids. The variability in water quality parameters clearly indicated a complex pattern, depending on the season (interaction p = 0.001), which highlighted how the river condition is stressed at multiple points as a result of anthropogenic effects. In particular, the downstream locations indicated an accumulation of nutrients, the presence of increased sediments, and phytoplankton related variables such as total counts, bio-volumes, chlorophyll-a, and total phosphorus. The patterns of phytoplankton communities varied in a complex way depending on the season (interaction p = 0.001). Abundances of phytoplankton were also found in low concentrations where the water column is not severely disturbed by flow and tide. However, when the water clarity drops resulting from tidal cycles, inflows from tributaries, and intense boating activities, the phytoplankton abundances also increased considerably. On the other hand, benthic macroinvertebrates compositions were significantly different between locations (p = 0.001) with increased abundances associated with upstream sites. Aphanocapsa holsatica and chironomid larvae appeared as the important indicators for upstream and downstream site differences in water quality. Water temperature influenced the phytoplankton community pattern (ρ(w) = 0.408), whereas pH influenced the benthic macroinvertebrate community pattern (ρ(w) = 0.437). The findings of this study provide valuable insights into the interactions of water quality parameters on biotic assemblages and to the extent that benthic macroinvertebrates and phytoplankton assemblages are suitable as indicators for monitoring and assessing peri-urban river health.

A vertical hydroclimatology of the Upper Indus Basin and initial insights to potential hydrological change in the region

NASA Astrophysics Data System (ADS)

Forsythe, Nathan; Kilsby, Chris G.; Fowler, Hayley J.; Archer, David R.

2010-05-01

The water resources of the Upper Indus Basin (UIB) are of the utmost importance to the economic wellbeing of Pakistan. The irrigated agriculture made possible by Indus river runoff underpins the food security for Pakistan's nearly 200 million people. Contributions from hydropower account for more than one fifth of peak installed electrical generating capacity in a country where widespread, prolonged load-shedding handicaps business activity and industrial development. Pakistan's further socio-economic development thus depends largely on optimisation of its precious water resources. Confident, accurate projections of future water resource availability and variability are urgent insights needed by development planners and infrastructure managers at all levels. Correctly projecting future hydrological conditions depends first and foremost on a thorough understanding of the underlying mechanisms and processes of present hydroclimatology. The vertical and horizontal spatial variations in key climate parameters (temperature, precipitation) govern the contributions of the various elevation zones and subcatchments comprising the UIB. Trends in this complex mountainous region are highly varied by season and parameter. Observed changes here often do not match general global trends or even necessarily those found in neighbouring regions. This study considers data from a variety sources in order to compose the most complete picture possible of the vertical hydroclimatology of the UIB. The study presents the observed climatology and trends for precipitation and temperature from local observations at long-record meteorological stations (Pakistan Meteorological Department). These data are compared to characterisations of additional water cycle parameters (humidity, cloud, snow cover and snow-water-equivalent) derived from local short-record automatic weather stations, the ECMWF ‘ERA' reanalysis projects and satellite based observations (AVHRR, MODIS, etc). The potential implications of the vertical (hypsometric) distribution of these parameters are considered. Interlinkages between observed changes in these parameters and the evolution of large-scale circulation indices (ENSO, NAO, local vorticity) are also investigated. In parallel to these climatological considerations, the study presents the typology of the observed UIB hydrological regimes -- glacial, nival and pluvial -- including interannual variability as quantified from the available river gauging record. In order to begin to assess potential implications of future climate change on UIB hydrology, key modes of variability in the climate parameters are identified. The study then analyses in detail the corresponding observed anomalies in UIB discharge for years exemplifying these modes. In conclusion, this work postulates potential impacts of changes in the hydrological variability stemming from continuation of estimated present local climatic trends.

Sensitivity of turbine-height wind speeds to parameters in planetary boundary-layer and surface-layer schemes in the weather research and forecasting model

DOE PAGES

Yang, Ben; Qian, Yun; Berg, Larry K.; ...

2016-07-21

We evaluate the sensitivity of simulated turbine-height wind speeds to 26 parameters within the Mellor–Yamada–Nakanishi–Niino (MYNN) planetary boundary-layer scheme and MM5 surface-layer scheme of the Weather Research and Forecasting model over an area of complex terrain. An efficient sampling algorithm and generalized linear model are used to explore the multiple-dimensional parameter space and quantify the parametric sensitivity of simulated turbine-height wind speeds. The results indicate that most of the variability in the ensemble simulations is due to parameters related to the dissipation of turbulent kinetic energy (TKE), Prandtl number, turbulent length scales, surface roughness, and the von Kármán constant. Themore » parameter associated with the TKE dissipation rate is found to be most important, and a larger dissipation rate produces larger hub-height wind speeds. A larger Prandtl number results in smaller nighttime wind speeds. Increasing surface roughness reduces the frequencies of both extremely weak and strong airflows, implying a reduction in the variability of wind speed. All of the above parameters significantly affect the vertical profiles of wind speed and the magnitude of wind shear. Lastly, the relative contributions of individual parameters are found to be dependent on both the terrain slope and atmospheric stability.« less

Sensitivity of turbine-height wind speeds to parameters in planetary boundary-layer and surface-layer schemes in the weather research and forecasting model

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

Yang, Ben; Qian, Yun; Berg, Larry K.

We evaluate the sensitivity of simulated turbine-height wind speeds to 26 parameters within the Mellor–Yamada–Nakanishi–Niino (MYNN) planetary boundary-layer scheme and MM5 surface-layer scheme of the Weather Research and Forecasting model over an area of complex terrain. An efficient sampling algorithm and generalized linear model are used to explore the multiple-dimensional parameter space and quantify the parametric sensitivity of simulated turbine-height wind speeds. The results indicate that most of the variability in the ensemble simulations is due to parameters related to the dissipation of turbulent kinetic energy (TKE), Prandtl number, turbulent length scales, surface roughness, and the von Kármán constant. Themore » parameter associated with the TKE dissipation rate is found to be most important, and a larger dissipation rate produces larger hub-height wind speeds. A larger Prandtl number results in smaller nighttime wind speeds. Increasing surface roughness reduces the frequencies of both extremely weak and strong airflows, implying a reduction in the variability of wind speed. All of the above parameters significantly affect the vertical profiles of wind speed and the magnitude of wind shear. Lastly, the relative contributions of individual parameters are found to be dependent on both the terrain slope and atmospheric stability.« less

Hierarchical Bayesian Modeling of Fluid-Induced Seismicity

NASA Astrophysics Data System (ADS)

Broccardo, M.; Mignan, A.; Wiemer, S.; Stojadinovic, B.; Giardini, D.

2017-11-01

In this study, we present a Bayesian hierarchical framework to model fluid-induced seismicity. The framework is based on a nonhomogeneous Poisson process with a fluid-induced seismicity rate proportional to the rate of injected fluid. The fluid-induced seismicity rate model depends upon a set of physically meaningful parameters and has been validated for six fluid-induced case studies. In line with the vision of hierarchical Bayesian modeling, the rate parameters are considered as random variables. We develop both the Bayesian inference and updating rules, which are used to develop a probabilistic forecasting model. We tested the Basel 2006 fluid-induced seismic case study to prove that the hierarchical Bayesian model offers a suitable framework to coherently encode both epistemic uncertainty and aleatory variability. Moreover, it provides a robust and consistent short-term seismic forecasting model suitable for online risk quantification and mitigation.

Analysis of isothermal and cooling rate dependent immersion freezing by a unifying stochastic ice nucleation model

NASA Astrophysics Data System (ADS)

Alpert, P. A.; Knopf, D. A.

2015-05-01

Immersion freezing is an important ice nucleation pathway involved in the formation of cirrus and mixed-phase clouds. Laboratory immersion freezing experiments are necessary to determine the range in temperature (T) and relative humidity (RH) at which ice nucleation occurs and to quantify the associated nucleation kinetics. Typically, isothermal (applying a constant temperature) and cooling rate dependent immersion freezing experiments are conducted. In these experiments it is usually assumed that the droplets containing ice nuclei (IN) all have the same IN surface area (ISA), however the validity of this assumption or the impact it may have on analysis and interpretation of the experimental data is rarely questioned. A stochastic immersion freezing model based on first principles of statistics is presented, which accounts for variable ISA per droplet and uses physically observable parameters including the total number of droplets (Ntot) and the heterogeneous ice nucleation rate coefficient, Jhet(T). This model is applied to address if (i) a time and ISA dependent stochastic immersion freezing process can explain laboratory immersion freezing data for different experimental methods and (ii) the assumption that all droplets contain identical ISA is a valid conjecture with subsequent consequences for analysis and interpretation of immersion freezing. The simple stochastic model can reproduce the observed time and surface area dependence in immersion freezing experiments for a variety of methods such as: droplets on a cold-stage exposed to air or surrounded by an oil matrix, wind and acoustically levitated droplets, droplets in a continuous flow diffusion chamber (CFDC), the Leipzig aerosol cloud interaction simulator (LACIS), and the aerosol interaction and dynamics in the atmosphere (AIDA) cloud chamber. Observed time dependent isothermal frozen fractions exhibiting non-exponential behavior with time can be readily explained by this model considering varying ISA. An apparent cooling rate dependence ofJhet is explained by assuming identical ISA in each droplet. When accounting for ISA variability, the cooling rate dependence of ice nucleation kinetics vanishes as expected from classical nucleation theory. The model simulations allow for a quantitative experimental uncertainty analysis for parameters Ntot, T, RH, and the ISA variability. In an idealized cloud parcel model applying variability in ISAs for each droplet, the model predicts enhanced immersion freezing temperatures and greater ice crystal production compared to a case when ISAs are uniform in each droplet. The implications of our results for experimental analysis and interpretation of the immersion freezing process are discussed.

Analysis of isothermal and cooling-rate-dependent immersion freezing by a unifying stochastic ice nucleation model

NASA Astrophysics Data System (ADS)

Alpert, Peter A.; Knopf, Daniel A.

2016-02-01

Immersion freezing is an important ice nucleation pathway involved in the formation of cirrus and mixed-phase clouds. Laboratory immersion freezing experiments are necessary to determine the range in temperature, T, and relative humidity, RH, at which ice nucleation occurs and to quantify the associated nucleation kinetics. Typically, isothermal (applying a constant temperature) and cooling-rate-dependent immersion freezing experiments are conducted. In these experiments it is usually assumed that the droplets containing ice nucleating particles (INPs) all have the same INP surface area (ISA); however, the validity of this assumption or the impact it may have on analysis and interpretation of the experimental data is rarely questioned. Descriptions of ice active sites and variability of contact angles have been successfully formulated to describe ice nucleation experimental data in previous research; however, we consider the ability of a stochastic freezing model founded on classical nucleation theory to reproduce previous results and to explain experimental uncertainties and data scatter. A stochastic immersion freezing model based on first principles of statistics is presented, which accounts for variable ISA per droplet and uses parameters including the total number of droplets, Ntot, and the heterogeneous ice nucleation rate coefficient, Jhet(T). This model is applied to address if (i) a time and ISA-dependent stochastic immersion freezing process can explain laboratory immersion freezing data for different experimental methods and (ii) the assumption that all droplets contain identical ISA is a valid conjecture with subsequent consequences for analysis and interpretation of immersion freezing. The simple stochastic model can reproduce the observed time and surface area dependence in immersion freezing experiments for a variety of methods such as: droplets on a cold-stage exposed to air or surrounded by an oil matrix, wind and acoustically levitated droplets, droplets in a continuous-flow diffusion chamber (CFDC), the Leipzig aerosol cloud interaction simulator (LACIS), and the aerosol interaction and dynamics in the atmosphere (AIDA) cloud chamber. Observed time-dependent isothermal frozen fractions exhibiting non-exponential behavior can be readily explained by this model considering varying ISA. An apparent cooling-rate dependence of Jhet is explained by assuming identical ISA in each droplet. When accounting for ISA variability, the cooling-rate dependence of ice nucleation kinetics vanishes as expected from classical nucleation theory. The model simulations allow for a quantitative experimental uncertainty analysis for parameters Ntot, T, RH, and the ISA variability. The implications of our results for experimental analysis and interpretation of the immersion freezing process are discussed.

Collocation mismatch uncertainties in satellite aerosol retrieval validation

NASA Astrophysics Data System (ADS)

Virtanen, Timo H.; Kolmonen, Pekka; Sogacheva, Larisa; Rodríguez, Edith; Saponaro, Giulia; de Leeuw, Gerrit

2018-02-01

Satellite-based aerosol products are routinely validated against ground-based reference data, usually obtained from sun photometer networks such as AERONET (AEROsol RObotic NETwork). In a typical validation exercise a spatial sample of the instantaneous satellite data is compared against a temporal sample of the point-like ground-based data. The observations do not correspond to exactly the same column of the atmosphere at the same time, and the representativeness of the reference data depends on the spatiotemporal variability of the aerosol properties in the samples. The associated uncertainty is known as the collocation mismatch uncertainty (CMU). The validation results depend on the sampling parameters. While small samples involve less variability, they are more sensitive to the inevitable noise in the measurement data. In this paper we study systematically the effect of the sampling parameters in the validation of AATSR (Advanced Along-Track Scanning Radiometer) aerosol optical depth (AOD) product against AERONET data and the associated collocation mismatch uncertainty. To this end, we study the spatial AOD variability in the satellite data, compare it against the corresponding values obtained from densely located AERONET sites, and assess the possible reasons for observed differences. We find that the spatial AOD variability in the satellite data is approximately 2 times larger than in the ground-based data, and the spatial variability correlates only weakly with that of AERONET for short distances. We interpreted that only half of the variability in the satellite data is due to the natural variability in the AOD, and the rest is noise due to retrieval errors. However, for larger distances (˜ 0.5°) the correlation is improved as the noise is averaged out, and the day-to-day changes in regional AOD variability are well captured. Furthermore, we assess the usefulness of the spatial variability of the satellite AOD data as an estimate of CMU by comparing the retrieval errors to the total uncertainty estimates including the CMU in the validation. We find that accounting for CMU increases the fraction of consistent observations.

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.

Novel models on fluid's variable thermo-physical properties for extensive study on convection heat and mass transfer

NASA Astrophysics Data System (ADS)

Shang, De-Yi; Zhong, Liang-Cai

2017-01-01

Our novel models for fluid's variable physical properties are improved and reported systematically in this work for enhancement of theoretical and practical value on study of convection heat and mass transfer. It consists of three models, namely (1) temperature parameter model, (2) polynomial model, and (3) weighted-sum model, respectively for treatment of temperature-dependent physical properties of gases, temperature-dependent physical properties of liquids, and concentration- and temperature-dependent physical properties of vapour-gas mixture. Two related components are proposed, and involved in each model for fluid's variable physical properties. They are basic physic property equations and theoretical similarity equations on physical property factors. The former, as the foundation of the latter, is based on the typical experimental data and physical analysis. The latter is built up by similarity analysis and mathematical derivation based on the former basic physical properties equations. These models are available for smooth simulation and treatment of fluid's variable physical properties for assurance of theoretical and practical value of study on convection of heat and mass transfer. Especially, so far, there has been lack of available study on heat and mass transfer of film condensation convection of vapour-gas mixture, and the wrong heat transfer results existed in widespread studies on the related research topics, due to ignorance of proper consideration of the concentration- and temperature-dependent physical properties of vapour-gas mixture. For resolving such difficult issues, the present novel physical property models have their special advantages.

Bayesian prediction of future ice sheet volume using local approximation Markov chain Monte Carlo methods

NASA Astrophysics Data System (ADS)

Davis, A. D.; Heimbach, P.; Marzouk, Y.

2017-12-01

We develop a Bayesian inverse modeling framework for predicting future ice sheet volume with associated formal uncertainty estimates. Marine ice sheets are drained by fast-flowing ice streams, which we simulate using a flowline model. Flowline models depend on geometric parameters (e.g., basal topography), parameterized physical processes (e.g., calving laws and basal sliding), and climate parameters (e.g., surface mass balance), most of which are unknown or uncertain. Given observations of ice surface velocity and thickness, we define a Bayesian posterior distribution over static parameters, such as basal topography. We also define a parameterized distribution over variable parameters, such as future surface mass balance, which we assume are not informed by the data. Hyperparameters are used to represent climate change scenarios, and sampling their distributions mimics internal variation. For example, a warming climate corresponds to increasing mean surface mass balance but an individual sample may have periods of increasing or decreasing surface mass balance. We characterize the predictive distribution of ice volume by evaluating the flowline model given samples from the posterior distribution and the distribution over variable parameters. Finally, we determine the effect of climate change on future ice sheet volume by investigating how changing the hyperparameters affects the predictive distribution. We use state-of-the-art Bayesian computation to address computational feasibility. Characterizing the posterior distribution (using Markov chain Monte Carlo), sampling the full range of variable parameters and evaluating the predictive model is prohibitively expensive. Furthermore, the required resolution of the inferred basal topography may be very high, which is often challenging for sampling methods. Instead, we leverage regularity in the predictive distribution to build a computationally cheaper surrogate over the low dimensional quantity of interest (future ice sheet volume). Continual surrogate refinement guarantees asymptotic sampling from the predictive distribution. Directly characterizing the predictive distribution in this way allows us to assess the ice sheet's sensitivity to climate variability and change.

Human Dose-Response Data for Francisella tularensis and a Dose- and Time-Dependent Mathematical Model of Early-Phase Fever Associated with Tularemia After Inhalation Exposure.

PubMed

McClellan, Gene; Coleman, Margaret; Crary, David; Thurman, Alec; Thran, Brandolyn

2018-04-25

Military health risk assessors, medical planners, operational planners, and defense system developers require knowledge of human responses to doses of biothreat agents to support force health protection and chemical, biological, radiological, nuclear (CBRN) defense missions. This article reviews extensive data from 118 human volunteers administered aerosols of the bacterial agent Francisella tularensis, strain Schu S4, which causes tularemia. The data set includes incidence of early-phase febrile illness following administration of well-characterized inhaled doses of F. tularensis. Supplemental data on human body temperature profiles over time available from de-identified case reports is also presented. A unified, logically consistent model of early-phase febrile illness is described as a lognormal dose-response function for febrile illness linked with a stochastic time profile of fever. Three parameters are estimated from the human data to describe the time profile: incubation period or onset time for fever; rise time of fever; and near-maximum body temperature. Inhaled dose-dependence and variability are characterized for each of the three parameters. These parameters enable a stochastic model for the response of an exposed population through incorporation of individual-by-individual variability by drawing random samples from the statistical distributions of these three parameters for each individual. This model provides risk assessors and medical decisionmakers reliable representations of the predicted health impacts of early-phase febrile illness for as long as one week after aerosol exposures of human populations to F. tularensis. © 2018 Society for Risk Analysis.

Uniform modeling of bacterial colony patterns with varying nutrient and substrate

NASA Astrophysics Data System (ADS)

Schwarcz, Deborah; Levine, Herbert; Ben-Jacob, Eshel; Ariel, Gil

2016-04-01

Bacteria develop complex patterns depending on growth condition. For example, Bacillus subtilis exhibit five different patterns depending on substrate hardness and nutrient concentration. We present a unified integro-differential model that reproduces the entire experimentally observed morphology diagram at varying nutrient concentrations and substrate hardness. The model allows a comprehensive and quantitative comparison between experimental and numerical variables and parameters, such as colony growth rate, nutrient concentration and diffusion constants. As a result, the role of the different physical mechanisms underlying and regulating the growth of the colony can be evaluated.

[Impact of acquired brain injury towards the community integration: employment outcome, disability and dependence two years after injury].

PubMed

Luna-Lario, P; Ojeda, N; Tirapu-Ustarroz, J; Pena, J

2016-06-16

To analyze the impact of acquired brain injury towards the community integration (professional career, disability, and dependence) in a sample of people affected by vascular, traumatic and tumor etiology acquired brain damage, over a two year time period after the original injury, and also to examine what sociodemographic variables, premorbid and injury related clinical data can predict the level of the person's integration into the community. 106 adults sample suffering from acquired brain injury who were attended by the Neuropsychology and Neuropsychiatry Department at Hospital of Navarra (Spain) affected by memory deficit as their main sequel. Differences among groups have been analyzed by using t by Student, chi squared and U by Mann-Whitney tests. 19% and 29% of the participants who were actively working before the injury got back their previous status within one and two years time respectively. 45% of the total sample were recognized disabled and 17% dependant. No relationship between sociodemographic and clinical variables and functional parameters observed were found. Acquired brain damage presents a high intensity impact on affected person's life trajectory. Nevertheless, in Spain, its consequences at sociolaboral adjustment over the the two years following the damage through functional parameters analyzed with official governmental means over a vascular, traumatic and tumor etiology sample had never been studied before.

Solution of magnetohydrodynamic flow and heat transfer of radiative viscoelastic fluid with temperature dependent viscosity in wire coating analysis

PubMed Central

Khan, Muhammad Altaf; Siddiqui, Nasir; Ullah, Murad; Shah, Qayyum

2018-01-01

Wire coating process is a continuous extrusion process for primary insulation of conducting wires with molten polymers for mechanical strength and protection in aggressive environments. In the present study, radiative melt polymer satisfying third grade fluid model is used for wire coating process. The effect of magnetic parameter, thermal radiation parameter and temperature dependent viscosity on wire coating analysis has been investigated. Reynolds model and Vogel’s models have been incorporated for variable viscosity. The governing equations characterizing the flow and heat transfer phenomena are solved analytically by utilizing homotopy analysis method (HAM). The computed results are also verified by ND-Solve method (Numerical technique) and Adomian Decomposition Method (ADM). The effect of pertinent parameters is shown graphically. In addition, the instability of the flow in the flows of the wall of the extrusion die is well marked in the case of the Vogel model as pointed by Nhan-Phan-Thien. PMID:29596448

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

Dana L. Kelly

Typical engineering systems in applications with high failure consequences such as nuclear reactor plants often employ redundancy and diversity of equipment in an effort to lower the probability of failure and therefore risk. However, it has long been recognized that dependencies exist in these redundant and diverse systems. Some dependencies, such as common sources of electrical power, are typically captured in the logic structure of the risk model. Others, usually referred to as intercomponent dependencies, are treated implicitly by introducing one or more statistical parameters into the model. Such common-cause failure models have limitations in a simulation environment. In addition,more » substantial subjectivity is associated with parameter estimation for these models. This paper describes an approach in which system performance is simulated by drawing samples from the joint distributions of dependent variables. The approach relies on the notion of a copula distribution, a notion which has been employed by the actuarial community for ten years or more, but which has seen only limited application in technological risk assessment. The paper also illustrates how equipment failure data can be used in a Bayesian framework to estimate the parameter values in the copula model. This approach avoids much of the subjectivity required to estimate parameters in traditional common-cause failure models. Simulation examples are presented for failures in time. The open-source software package R is used to perform the simulations. The open-source software package WinBUGS is used to perform the Bayesian inference via Markov chain Monte Carlo sampling.« less

The Ostrogradsky Prescription for BFV Formalism

NASA Astrophysics Data System (ADS)

Nirov, Khazret S.

Gauge-invariant systems of a general form with higher order time derivatives of gauge parameters are investigated within the framework of the BFV formalism. Higher order terms of the BRST charge and BRST-invariant Hamiltonian are obtained. It is shown that the identification rules for Lagrangian and Hamiltonian BRST ghost variables depend on the choice of the extension of constraints from the primary constraint surface.

Un-reduction in field theory.

PubMed

Arnaudon, Alexis; López, Marco Castrillón; Holm, Darryl D

2018-01-01

The un-reduction procedure introduced previously in the context of classical mechanics is extended to covariant field theory. The new covariant un-reduction procedure is applied to the problem of shape matching of images which depend on more than one independent variable (for instance, time and an additional labelling parameter). Other possibilities are also explored: nonlinear [Formula: see text]-models and the hyperbolic flows of curves.

Interpersonal distance modeling during fighting activities.

PubMed

Dietrich, Gilles; Bredin, Jonathan; Kerlirzin, Yves

2010-10-01

The aim of this article is to elaborate a general framework for modeling dual opposition activities, or more generally, dual interaction. The main hypothesis is that opposition behavior can be measured directly from a global variable and that the relative distance between the two subjects can be this parameter. Moreover, this parameter should be considered as multidimensional parameter depending not only on the dynamics of the subjects but also on the "internal" parameters of the subjects, such as sociological and/or emotional states. Standard and simple mechanical formalization will be used to model this multifactorial distance. To illustrate such a general modeling methodology, this model was compared with actual data from an opposition activity like Japanese fencing (kendo). This model captures not only coupled coordination, but more generally interaction in two-subject activities.

Empirical meaning of DTM multifractal parameters in the precipitation context

NASA Astrophysics Data System (ADS)

Portilla Farfan, Freddy; Valencia, Jose Luis; Villeta, Maria; Tarquis, Ana M.; Saa-Requejo, Antonio

2015-04-01

The main objective of this research is to interpret the multifractal parameters in the case of precipitation series from an empirical approach. In order to do so nineteen precipitation series were generated with a daily precipitation simulator derived from year and month estimations and considering the classical statistics, used commonly in hydrology studies, from actual data of four Spanish rain gauges located in a gradient from NW to SE. For all generated series the multifractal parameters were estimated following the technique DTM (Double Trace Moments) developed by Lavalle et al. (1993) and the variations produced considered. The results show the following conclusions: 1. The intermittency, C1, increases when precipitation is concentrating for fewer days, making it more variable, or when increasing its concentration on maximum monthly precipitation days, while it is not affected due to the modification in the variability in the number of days rained. 2. Multifractility, α, increases with the number of rainy days and the variability of the precipitation, yearly as well as monthly, as well as with the concentration of precipitation on the maximum monthly precipitation day. 3. The maximum probable singularity, γs, increases with the concentration of rain on the day of the maximum monthly precipitation and the variability in yearly and monthly level. 4. The non-conservative degree, H, depends on the number of rainy days that appear on the series and secondly on the general variability of the rain. References Lavallée D., S. Lovejoy, D. Schertzer and P. Ladoy, 1993. Nonlinear variability and landscape topography: analysis and simulation. In: Fractals in Geography (N. Lam and L. De Cola, Eds.) Prentice Hall, Englewood Cliffs, 158-192.

Smooth time-dependent receiver operating characteristic curve estimators.

PubMed

Martínez-Camblor, Pablo; Pardo-Fernández, Juan Carlos

2018-03-01

The receiver operating characteristic curve is a popular graphical method often used to study the diagnostic capacity of continuous (bio)markers. When the considered outcome is a time-dependent variable, two main extensions have been proposed: the cumulative/dynamic receiver operating characteristic curve and the incident/dynamic receiver operating characteristic curve. In both cases, the main problem for developing appropriate estimators is the estimation of the joint distribution of the variables time-to-event and marker. As usual, different approximations lead to different estimators. In this article, the authors explore the use of a bivariate kernel density estimator which accounts for censored observations in the sample and produces smooth estimators of the time-dependent receiver operating characteristic curves. The performance of the resulting cumulative/dynamic and incident/dynamic receiver operating characteristic curves is studied by means of Monte Carlo simulations. Additionally, the influence of the choice of the required smoothing parameters is explored. Finally, two real-applications are considered. An R package is also provided as a complement to this article.

Spatial Variability of Streambed Hydraulic Conductivity of a Lowland River

NASA Astrophysics Data System (ADS)

Schneidewind, Uwe; Thornton, Steven; Van De Vijver, Ellen; Joris, Ingeborg; Seuntjens, Piet

2015-04-01

Streambed hydraulic conductivity K is a key physical parameter, which describes flow processes in the hyporheic zone (HZ), i.e. the dynamic interface between aquifers and streams or rivers. Knowledge of the spatial variability of K is also important for the interpretation of contaminant transport processes in the HZ. Streambed K can vary over several magnitudes at small spatial scales. It depends mostly on streambed sediment characteristics (e.g. effective porosity, grain size, packing), streambed processes (e.g. sedimentation, colmation and erosion) and the development of stream channel geometry and streambed morphology (e.g. dunes, anti-dunes, pool-riffle sequences, etc.). Although heterogeneous in natural streambeds, streambed K is often considered to be a constant parameter due to a lack of information on its spatial distribution. Here we show the spatial variability of streambed K for a small section of the River Tern, a lowland river in the UK. Streambed K was determined for more than 120 vertically and horizontally distributed locations from grain size analyses using four empirical approaches (Hazen, Beyer, Kozeny and the USBR model). Additionally, streambed K was estimated from falling head tests in 36 piezometers installed into the streambed on a 4 m by 16 m grid, by applying the Springer-Gelhar Model. For both methods streambed K followed a log-normal distribution. Variogram analysis was used to deduce the spatial variability of the streambed K values within several streambed profiles parallel and perpendicular to the main flow direction in the stream. Hydraulic conductivity Kg estimated from grain size analyses varied between 1 m/d and 155 m/d with standard deviations of 79% to 99% depending on the empirical approach used. Kh estimated from falling head tests varied between 1 m/d and 22 m/d with a standard deviation of about 50%, depending on the degree of anisotropy assumed. After rescaling the data to obtain a common sample support, Pearson correlation coefficients r were calculated between Kg and Kh. Overall, a relatively weak correlation (r < 0.3) was found between both parameters. This is most probably a result from soil coring that destroys the original sediment structure and any anisotropy within it. Analysis of streambed K improved our understanding of the flow behavior in the HZ on a local scale. This will be of importance for the subsequent assessment of nitrate transport and attenuation in the river section.

The influence of redox status on inter-individual variability in the response of human peripheral blood lymphocytes to ionizing radiation.

PubMed

Pajic, Jelena; Rovcanin, Branislav; Kekic, Dusan; Jovicic, Dubravka; Milovanovic, Aleksandar P S

2018-04-30

Ionizing radiation (IR) can act on atomic structures, producing damage to biomolecules. Earlier investigations evaluating individual radiosensitivity in vitro were focused on cytogenetic biomarkers (chromosomal aberrations - CA and micronuclei - MN). Since IR can also cause oxidative damage by producing reactive oxygen species, the main goal of this investigation was to establish the influence of redox status on CA and MN frequency in human peripheral blood lymphocytes. Blood samples from 56 healthy donors were irradiated at doses of 0, 0.75, 1.5 and 3 Gy and then analyzed cytogenetically and biochemically. The results showed inter-individual variability in all analyzed parameters, as well as dose-dependent increases in almost all of them. Correlation analysis indicated no association between CA, MN and oxidative stress parameters. However, findings for overall response (HRR) parameters showed that donors with lower values for parameters of antioxidant status had increased levels of cytogenetic damage and higher responses to irradiation and vice versa. Besides well-established cytogenetic biomarkers of radiation exposure, our results indicated promising future use for biochemical oxidative status parameters in routine radiation protection practice, since together they can provide a complete radiation response profile in cases of continuous low-dose exposure, as well as in a radiation emergency.

On Budyko curve as a consequence of climate-soil-vegetation equilibrium hypothesis

NASA Astrophysics Data System (ADS)

Pande, S.

2012-04-01

A hypothesis that Budyko curve is a consequence of stable equilibriums of climate-soil-vegetation co-evolution is tested at biome scale. We assume that i) distribution of vegetation, soil and climate within a biome is a distribution of equilibriums of similar soil-vegetation dynamics and that this dynamics is different across different biomes and ii) soil and vegetation are in dynamic equilibrium with climate while in static equilibrium with each other. In order to test the hypothesis, a two stage regression is considered using MOPEX/Hydrologic Synthesis Project dataset for basins in eastern United States. In the first stage, multivariate regression (Seemingly Unrelated Regression) is performed for each biome with soil (estimated porosity and slope of soil water retention curve) and vegetation characteristics (5-week NDVI gradient) as dependent variables and aridity index, vegetation and soil characteristics as independent variables for respective dependent variables. The regression residuals of the first stage along with aridity index then serve as second stage independent variables while actual vaporization to precipitation ratio (vapor index) serving as dependent variable. Insignificance, if revealed, of a first stage parameter allows us to reject the role of corresponding soil or vegetation characteristics in the co-evolution hypothesis. Meanwhile the significance of second stage regression parameter corresponding to a first stage residual allow us to reject the hypothesis that Budyko curve is a locus "solely" of climate-soil-vegetation co-evolution equilibrium points. Results suggest lack of evidence for soil-vegetation co-evolution in Prairies and Mixed/SouthEast Forests (unlike in Deciduous Forests) though climate plays a dominant role in explaining within biome soil and vegetation characteristics across all the biomes. Preliminary results indicate absence of effects beyond climate-soil-vegetation co-evolution in explaining the ratio of annual total minimum monthly flows to precipitation in Deciduous Forests though other three biome types show presence of effects beyond co-evolutionary. Such an analysis can yield insights into the nature of hydrologic change when assessed along the Budyko curve as well as non co-evolutionary effects such as anthropogenic effects on basin scale annual water balances.

[Age-related changes of somatotype and body mass components in girls].

PubMed

Tambovtseva, R V; Zhukova, S G

2005-01-01

The longitudinal and transverse studies of girls aged 7 to 17 years living in Moscow and the town of Yelabuga were performed to monitor the dynamics of their growth processes, parameters of ectomorphism, mesomorphism and endomorphism depending on the type of body build. Anthropometric, anthroposcopic metods and cluster analysis were used to evaluate the type of body build according to V.G. Shtefko and A.G. Ostrovskiy (1928). Quantitative assessment of parameters of endo-, meso- and ectomorphism was performed using Heath-Carter method (1980). It was shown that the age-related variability of the types of body build appeared in association with the developmental heterochronism, which resulted from the uneven growth rate of different body components. The least variable parameters were found in the girls of digestive and asthenoid types of body build, while in girls of muscular and thoracic types these parameters changed more frequently. The critical periods during which the significant changes of somatotype were increased in number, were defined as 9 to 10 years and puberty period--11 to 14 years. Most sensitive time points in the time-course of somatotype establishment in girls are the ages of 12 and 14 years.

Optimal dynamic pricing and replenishment policy for perishable items with inventory-level-dependent demand

NASA Astrophysics Data System (ADS)

Lu, Lihao; Zhang, Jianxiong; Tang, Wansheng

2016-04-01

An inventory system for perishable items with limited replenishment capacity is introduced in this paper. The demand rate depends on the stock quantity displayed in the store as well as the sales price. With the goal to realise profit maximisation, an optimisation problem is addressed to seek for the optimal joint dynamic pricing and replenishment policy which is obtained by solving the optimisation problem with Pontryagin's maximum principle. A joint mixed policy, in which the sales price is a static decision variable and the replenishment rate remains to be a dynamic decision variable, is presented to compare with the joint dynamic policy. Numerical results demonstrate the advantages of the joint dynamic one, and further show the effects of different system parameters on the optimal joint dynamic policy and the maximal total profit.

Modeling the microstructurally dependent mechanical properties of poly(ester-urethane-urea)s.

PubMed

Warren, P Daniel; Sycks, Dalton G; McGrath, Dominic V; Vande Geest, Jonathan P

2013-12-01

Poly(ester-urethane-urea) (PEUU) is one of many synthetic biodegradable elastomers under scrutiny for biomedical and soft tissue applications. The goal of this study was to investigate the effect of the experimental parameters on mechanical properties of PEUUs following exposure to different degrading environments, similar to that of the human body, using linear regression, producing one predictive model. The model utilizes two independent variables of poly(caprolactone) (PCL) type and copolymer crystallinity to predict the dependent variable of maximum tangential modulus (MTM). Results indicate that comparisons between PCLs at different degradation states are statistically different (p < 0.0003), while the difference between experimental and predicted average MTM is statistically negligible (p < 0.02). The linear correlation between experimental and predicted MTM values is R(2) = 0.75. Copyright © 2013 Wiley Periodicals, Inc., a Wiley Company.

Composite system in rotationally invariant noncommutative phase space

NASA Astrophysics Data System (ADS)

Gnatenko, Kh. P.; Tkachuk, V. M.

2018-03-01

Composite system is studied in noncommutative phase space with preserved rotational symmetry. We find conditions on the parameters of noncommutativity on which commutation relations for coordinates and momenta of the center-of-mass of composite system reproduce noncommutative algebra for coordinates and momenta of individual particles. Also, on these conditions, the coordinates and the momenta of the center-of-mass satisfy noncommutative algebra with effective parameters of noncommutativity which depend on the total mass of the system and do not depend on its composition. Besides, it is shown that on these conditions the coordinates in noncommutative space do not depend on mass and can be considered as kinematic variables, the momenta are proportional to mass as it has to be. A two-particle system with Coulomb interaction is studied and the corrections to the energy levels of the system are found in rotationally invariant noncommutative phase space. On the basis of this result the effect of noncommutativity on the spectrum of exotic atoms is analyzed.

Modeling of Internet Influence on Group Emotion

NASA Astrophysics Data System (ADS)

Czaplicka, Agnieszka; Hołyst, Janusz A.

Long-range interactions are introduced to a two-dimensional model of agents with time-dependent internal variables ei = 0, ±1 corresponding to valencies of agent emotions. Effects of spontaneous emotion emergence and emotional relaxation processes are taken into account. The valence of agent i depends on valencies of its four nearest neighbors but it is also influenced by long-range interactions corresponding to social relations developed for example by Internet contacts to a randomly chosen community. Two types of such interactions are considered. In the first model the community emotional influence depends only on the sign of its temporary emotion. When the coupling parameter approaches a critical value a phase transition takes place and as result for larger coupling constants the mean group emotion of all agents is nonzero over long time periods. In the second model the community influence is proportional to magnitude of community average emotion. The ordered emotional phase was here observed for a narrow set of system parameters.

Evaluation of SimpleTreat 4.0: Simulations of pharmaceutical removal in wastewater treatment plant facilities.

PubMed

Lautz, L S; Struijs, J; Nolte, T M; Breure, A M; van der Grinten, E; van de Meent, D; van Zelm, R

2017-02-01

In this study, the removal of pharmaceuticals from wastewater as predicted by SimpleTreat 4.0 was evaluated. Field data obtained from literature of 43 pharmaceuticals, measured in 51 different activated sludge WWTPs were used. Based on reported influent concentrations, the effluent concentrations were calculated with SimpleTreat 4.0 and compared to measured effluent concentrations. The model predicts effluent concentrations mostly within a factor of 10, using the specific WWTP parameters as well as SimpleTreat default parameters, while it systematically underestimates concentrations in secondary sludge. This may be caused by unexpected sorption, resulting from variability in WWTP operating conditions, and/or QSAR applicability domain mismatch and background concentrations prior to measurements. Moreover, variability in detection techniques and sampling methods can cause uncertainty in measured concentration levels. To find possible structural improvements, we also evaluated SimpleTreat 4.0 using several specific datasets with different degrees of uncertainty and variability. This evaluation verified that the most influencing parameters for water effluent predictions were biodegradation and the hydraulic retention time. Results showed that model performance is highly dependent on the nature and quality, i.e. degree of uncertainty, of the data. The default values for reactor settings in SimpleTreat result in realistic predictions. Copyright © 2016 Elsevier Ltd. All rights reserved.

Multiplicative Forests for Continuous-Time Processes

PubMed Central

Weiss, Jeremy C.; Natarajan, Sriraam; Page, David

2013-01-01

Learning temporal dependencies between variables over continuous time is an important and challenging task. Continuous-time Bayesian networks effectively model such processes but are limited by the number of conditional intensity matrices, which grows exponentially in the number of parents per variable. We develop a partition-based representation using regression trees and forests whose parameter spaces grow linearly in the number of node splits. Using a multiplicative assumption we show how to update the forest likelihood in closed form, producing efficient model updates. Our results show multiplicative forests can be learned from few temporal trajectories with large gains in performance and scalability. PMID:25284967

Multiplicative Forests for Continuous-Time Processes.

PubMed

Weiss, Jeremy C; Natarajan, Sriraam; Page, David

2012-01-01

Learning temporal dependencies between variables over continuous time is an important and challenging task. Continuous-time Bayesian networks effectively model such processes but are limited by the number of conditional intensity matrices, which grows exponentially in the number of parents per variable. We develop a partition-based representation using regression trees and forests whose parameter spaces grow linearly in the number of node splits. Using a multiplicative assumption we show how to update the forest likelihood in closed form, producing efficient model updates. Our results show multiplicative forests can be learned from few temporal trajectories with large gains in performance and scalability.

Parameter identification of process simulation models as a means for knowledge acquisition and technology transfer

NASA Astrophysics Data System (ADS)

Batzias, Dimitris F.; Ifanti, Konstantina

2012-12-01

Process simulation models are usually empirical, therefore there is an inherent difficulty in serving as carriers for knowledge acquisition and technology transfer, since their parameters have no physical meaning to facilitate verification of the dependence on the production conditions; in such a case, a 'black box' regression model or a neural network might be used to simply connect input-output characteristics. In several cases, scientific/mechanismic models may be proved valid, in which case parameter identification is required to find out the independent/explanatory variables and parameters, which each parameter depends on. This is a difficult task, since the phenomenological level at which each parameter is defined is different. In this paper, we have developed a methodological framework under the form of an algorithmic procedure to solve this problem. The main parts of this procedure are: (i) stratification of relevant knowledge in discrete layers immediately adjacent to the layer that the initial model under investigation belongs to, (ii) design of the ontology corresponding to these layers, (iii) elimination of the less relevant parts of the ontology by thinning, (iv) retrieval of the stronger interrelations between the remaining nodes within the revised ontological network, and (v) parameter identification taking into account the most influential interrelations revealed in (iv). The functionality of this methodology is demonstrated by quoting two representative case examples on wastewater treatment.

Global sensitivity analysis of a local water balance model predicting evaporation, water yield and drought

NASA Astrophysics Data System (ADS)

Speich, Matthias; Zappa, Massimiliano; Lischke, Heike

2017-04-01

Evaporation and transpiration affect both catchment water yield and the growing conditions for vegetation. They are driven by climate, but also depend on vegetation, soil and land surface properties. In hydrological and land surface models, these properties may be included as constant parameters, or as state variables. Often, little is known about the effect of these variables on model outputs. In the present study, the effect of surface properties on evaporation was assessed in a global sensitivity analysis. To this effect, we developed a simple local water balance model combining state-of-the-art process formulations for evaporation, transpiration and soil water balance. The model is vertically one-dimensional, and the relative simplicity of its process formulations makes it suitable for integration in a spatially distributed model at regional scale. The main model outputs are annual total evaporation (TE, i.e. the sum of transpiration, soil evaporation and interception), and a drought index (DI), which is based on the ratio of actual and potential transpiration. This index represents the growing conditions for forest trees. The sensitivity analysis was conducted in two steps. First, a screening analysis was applied to identify unimportant parameters out of an initial set of 19 parameters. In a second step, a statistical meta-model was applied to a sample of 800 model runs, in which the values of the important parameters were varied. Parameter effect and interactions were analyzed with effects plots. The model was driven with forcing data from ten meteorological stations in Switzerland, representing a wide range of precipitation regimes across a strong temperature gradient. Of the 19 original parameters, eight were identified as important in the screening analysis. Both steps highlighted the importance of Plant Available Water Capacity (AWC) and Leaf Area Index (LAI). However, their effect varies greatly across stations. For example, while a transition from a sparse to a closed forest canopy has almost no effect on annual TE at warm and dry sites, it increases TE by up to 100 mm/year at cold-humid and warm-humid sites. Further parameters of importance describe infiltration, as well as canopy resistance and its response to environmental variables. This study offers insights for future development of hydrological and ecohydrological models. First, it shows that although local water balance is primarily controlled by climate, the vegetation and soil parameters may have a large impact on the outputs. Second, it indicates that modeling studies should prioritize a realistic parameterization of LAI and AWC, while other parameters may be set to fixed values. Third, it illustrates to which extent parameter effect and interactions depend on local climate.

Behavior of sensitivities in the one-dimensional advection-dispersion equation: Implications for parameter estimation and sampling design

USGS Publications Warehouse

Knopman, Debra S.; Voss, Clifford I.

1987-01-01

The spatial and temporal variability of sensitivities has a significant impact on parameter estimation and sampling design for studies of solute transport in porous media. Physical insight into the behavior of sensitivities is offered through an analysis of analytically derived sensitivities for the one-dimensional form of the advection-dispersion equation. When parameters are estimated in regression models of one-dimensional transport, the spatial and temporal variability in sensitivities influences variance and covariance of parameter estimates. Several principles account for the observed influence of sensitivities on parameter uncertainty. (1) Information about a physical parameter may be most accurately gained at points in space and time with a high sensitivity to the parameter. (2) As the distance of observation points from the upstream boundary increases, maximum sensitivity to velocity during passage of the solute front increases and the consequent estimate of velocity tends to have lower variance. (3) The frequency of sampling must be “in phase” with the S shape of the dispersion sensitivity curve to yield the most information on dispersion. (4) The sensitivity to the dispersion coefficient is usually at least an order of magnitude less than the sensitivity to velocity. (5) The assumed probability distribution of random error in observations of solute concentration determines the form of the sensitivities. (6) If variance in random error in observations is large, trends in sensitivities of observation points may be obscured by noise and thus have limited value in predicting variance in parameter estimates among designs. (7) Designs that minimize the variance of one parameter may not necessarily minimize the variance of other parameters. (8) The time and space interval over which an observation point is sensitive to a given parameter depends on the actual values of the parameters in the underlying physical system.

Seismic variability of subduction thrust faults: Insights from laboratory models

NASA Astrophysics Data System (ADS)

Corbi, F.; Funiciello, F.; Faccenna, C.; Ranalli, G.; Heuret, A.

2011-06-01

Laboratory models are realized to investigate the role of interface roughness, driving rate, and pressure on friction dynamics. The setup consists of a gelatin block driven at constant velocity over sand paper. The interface roughness is quantified in terms of amplitude and wavelength of protrusions, jointly expressed by a reference roughness parameter obtained by their product. Frictional behavior shows a systematic dependence on system parameters. Both stick slip and stable sliding occur, depending on driving rate and interface roughness. Stress drop and frequency of slip episodes vary directly and inversely, respectively, with the reference roughness parameter, reflecting the fundamental role for the amplitude of protrusions. An increase in pressure tends to favor stick slip. Static friction is a steeply decreasing function of the reference roughness parameter. The velocity strengthening/weakening parameter in the state- and rate-dependent dynamic friction law becomes negative for specific values of the reference roughness parameter which are intermediate with respect to the explored range. Despite the simplifications of the adopted setup, which does not address the problem of off-fault fracturing, a comparison of the experimental results with the depth distribution of seismic energy release along subduction thrust faults leads to the hypothesis that their behavior is primarily controlled by the depth- and time-dependent distribution of protrusions. A rough subduction fault at shallow depths, unable to produce significant seismicity because of low lithostatic pressure, evolves into a moderately rough, velocity-weakening fault at intermediate depths. The magnitude of events in this range is calibrated by the interplay between surface roughness and subduction rate. At larger depths, the roughness further decreases and stable sliding becomes gradually more predominant. Thus, although interplate seismicity is ultimately controlled by tectonic parameters (velocity of the plates/trench and the thermal regime), the direct control is exercised by the resulting frictional properties of the plate interface.

On X-Ray Variability in Seyfert Galaxies

NASA Technical Reports Server (NTRS)

Turner, T. J.; George, I. M.; Nandra, K.; Turcan, D.

1999-01-01

This paper presents a quantification of the X-ray variability amplitude for 79 ASCA observations of 36 Seyfert 1 galaxies. We find that consideration of sources with the narrowest permitted lines in the optical band introduces scatter into the established correlation between X-ray variability and nuclear luminosity. Consideration of the X-ray spectral index and variability properties together shows distinct groupings in parameter space for broad and narrow-line Seyfert 1 galaxies, confirming previous studies. A strong correlation is found between hard X-ray variability and FWHM Hbeta. A range of nuclear mass and accretion rate across the Seyfert population can explain the differences observed in X-ray and optical properties. An attractive alternative model, which does not depend on any systematic difference in central mass, is that the circumnuclear gas of NLSy1s is different to BLSy1s in temperature, optical depth, density or geometry.

Can Dynamic Visualizations with Variable Control Enhance the Acquisition of Intuitive Knowledge?

NASA Astrophysics Data System (ADS)

Wichmann, Astrid; Timpe, Sebastian

2015-10-01

An important feature of inquiry learning is to take part in science practices including exploring variables and testing hypotheses. Computer-based dynamic visualizations have the potential to open up various exploration possibilities depending on the level of learner control. It is assumed that variable control, e.g., by changing parameters of a variable, leads to deeper processing (Chang and Linn 2013; de Jong and Njoo 1992; Nerdel 2003; Trey and Khan 2008). Variable control may be helpful, in particular, for acquiring intuitive knowledge (Swaak and de Jong 2001). However, it bares the risk of mental exhaustion and thus may have detrimental effects on knowledge acquisition (Sweller 1998). Students ( N = 118) from four chemistry classes followed inquiry cycles using the software Molecular Workbench (Xie and Tinker 2006). Variable control was varied across the conditions (1) No-Manipulation group and (2) Manipulation group. By adding a third condition, (3) Manipulation-Plus group, we tested whether adding an active hypothesis phase prepares students before changing parameters of a variable. As expected, students in the Manipulation group and Manipulation-Plus group performed better concerning intuitive knowledge ( d = 1.14) than students in the No-Manipulation group. On a descriptive level, results indicated higher cognitive effort in the Manipulation group and the Manipulation-Plus group than in the No-Manipulation group. Unexpectedly, students in the Manipulation-Plus group did not benefit from the active hypothesis phase (intuitive knowledge: d = .36). Findings show that students benefit from variable control. Furthermore, findings point toward the direction that variable control evokes desirable difficulties (Bjork and Linn 2006).

Solar coronal and photospheric abundances from solar energetic particle measurements

NASA Technical Reports Server (NTRS)

Breneman, H.; Stone, E. C.

1985-01-01

Solar energetic particle (SEP) elemental abundance data from the Cosmic Ray Subsystem (CRS) aboard the Voyager 1 and 2 spacecraft are used to derive unfractionated coronal and photospheric abundances for elements with 3 = or Z or = 30. The ionic charge-to-mass ratio (Q/M) is the principal organizing parameter for the fractionation of SEPs by acceleration and propagation processes and for flare-to-flare variability, making possible a single-parameter Q/M-dependent correction to the average SEP abundances to obtain unfractionated coronal abundances. A further correction based on first ionization potential allows the determination of unfractionated photospheric abundances.

Optimal positions and parameters of translational and rotational mass dampers in beams subjected to random excitation

NASA Astrophysics Data System (ADS)

Łatas, Waldemar

2018-01-01

The problem of vibrations of the beam with the attached system of translational and rotational dynamic mass dampers subjected to random excitations with peaked power spectral densities, is presented in the hereby paper. The Euler-Bernoulli beam model is applied, while for solving the equation of motion the Galerkin method and the Laplace time transform are used. The obtained transfer functions allow to determine power spectral densities of the beam deflection and other dependent variables. Numerical examples present simple optimization problems of mass dampers parameters for local and global objective functions.

Relative desirability of leisure activities and work parameters in a simulation of isolated work stations. [long term space flight simulation

NASA Technical Reports Server (NTRS)

Sullins, W. R., Jr.; Rogers, J. G.

1974-01-01

The kinds of activities that are attractive to man in long duration isolation are delineated considering meaningful work as major activity and a choice of leisure/living provisions. The dependent variables are the relative distribution between various work, leisure, and living activities where external constraints on the subject's freedom of choice are minimized. Results indicate that an average of at least five hours per day of significant meaningful work is required for satisfactory enjoyment of the situation; most other parameters of the situation have less effects on overall performance and satisfaction

HEATING 7. 1 user's manual

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

Childs, K.W.

1991-07-01

HEATING is a FORTRAN program designed to solve steady-state and/or transient heat conduction problems in one-, two-, or three- dimensional Cartesian, cylindrical, or spherical coordinates. A model may include multiple materials, and the thermal conductivity, density, and specific heat of each material may be both time- and temperature-dependent. The thermal conductivity may be anisotropic. Materials may undergo change of phase. Thermal properties of materials may be input or may be extracted from a material properties library. Heating generation rates may be dependent on time, temperature, and position, and boundary temperatures may be time- and position-dependent. The boundary conditions, which maymore » be surface-to-boundary or surface-to-surface, may be specified temperatures or any combination of prescribed heat flux, forced convection, natural convection, and radiation. The boundary condition parameters may be time- and/or temperature-dependent. General graybody radiation problems may be modeled with user-defined factors for radiant exchange. The mesh spacing may be variable along each axis. HEATING is variably dimensioned and utilizes free-form input. Three steady-state solution techniques are available: point-successive-overrelaxation iterative method with extrapolation, direct-solution (for one-dimensional or two-dimensional problems), and conjugate gradient. Transient problems may be solved using one of several finite-difference schemes: Crank-Nicolson implicit, Classical Implicit Procedure (CIP), Classical Explicit Procedure (CEP), or Levy explicit method (which for some circumstances allows a time step greater than the CEP stability criterion). The solution of the system of equations arising from the implicit techniques is accomplished by point-successive-overrelaxation iteration and includes procedures to estimate the optimum acceleration parameter.« less

An inexpensive frequency-modulated (FM) audio monitor of time-dependent analog parameters.

PubMed

Langdon, R B; Jacobs, R S

1980-02-01

The standard method for quantification and presentation of an experimental variable in real time is the use of visual display on the ordinate of an oscilloscope screen or chart recorder. This paper describes a relatively simple electronic circuit, using commercially available and inexpensive integrated circuits (IC), which generates an audible tone, the pitch of which varies in proportion to a running variable of interest. This device, which we call an "Audioscope," can accept as input the monitor output from any instrument that expresses an experimental parameter as a dc voltage. The Audioscope is particularly useful in implanting microelectrodes intracellularly. It may also function to mediate the first step in data recording on magnetic tape, and/or data analysis and reduction by electronic circuitary. We estimate that this device can be built, with two-channel capability, for less than $50, and in less than 10 hr by an experienced electronics technician.

A new numerical benchmark of a freshwater lens

NASA Astrophysics Data System (ADS)

Stoeckl, L.; Walther, M.; Graf, T.

2016-04-01

A numerical benchmark for 2-D variable-density flow and solute transport in a freshwater lens is presented. The benchmark is based on results of laboratory experiments conducted by Stoeckl and Houben (2012) using a sand tank on the meter scale. This benchmark describes the formation and degradation of a freshwater lens over time as it can be found under real-world islands. An error analysis gave the appropriate spatial and temporal discretization of 1 mm and 8.64 s, respectively. The calibrated parameter set was obtained using the parameter estimation tool PEST. Comparing density-coupled and density-uncoupled results showed that the freshwater-saltwater interface position is strongly dependent on density differences. A benchmark that adequately represents saltwater intrusion and that includes realistic features of coastal aquifers or freshwater lenses was lacking. This new benchmark was thus developed and is demonstrated to be suitable to test variable-density groundwater models applied to saltwater intrusion investigations.

Time variability of viscosity parameter in differentially rotating discs

NASA Astrophysics Data System (ADS)

Rajesh, S. R.; Singh, Nishant K.

2014-07-01

We propose a mechanism to produce fluctuations in the viscosity parameter (α) in differentially rotating discs. We carried out a nonlinear analysis of a general accretion flow, where any perturbation on the background α was treated as a passive/slave variable in the sense of dynamical system theory. We demonstrate a complete physical picture of growth, saturation and final degradation of the perturbation as a result of the nonlinear nature of coupled system of equations. The strong dependence of this fluctuation on the radial location in the accretion disc and the base angular momentum distribution is demonstrated. The growth of fluctuations is shown to have a time scale comparable to the radial drift time and hence the physical significance is discussed. The fluctuation is found to be a power law in time in the growing phase and we briefly discuss its statistical significance.

On two diffusion neuronal models with multiplicative noise: The mean first-passage time properties

NASA Astrophysics Data System (ADS)

D'Onofrio, G.; Lansky, P.; Pirozzi, E.

2018-04-01

Two diffusion processes with multiplicative noise, able to model the changes in the neuronal membrane depolarization between two consecutive spikes of a single neuron, are considered and compared. The processes have the same deterministic part but different stochastic components. The differences in the state-dependent variabilities, their asymptotic distributions, and the properties of the first-passage time across a constant threshold are investigated. Closed form expressions for the mean of the first-passage time of both processes are derived and applied to determine the role played by the parameters involved in the model. It is shown that for some values of the input parameters, the higher variability, given by the second moment, does not imply shorter mean first-passage time. The reason for that can be found in the complete shape of the stationary distribution of the two processes. Applications outside neuroscience are also mentioned.

Simulation of drive of mechanisms, working in specific conditions

NASA Astrophysics Data System (ADS)

Ivanovskaya, A. V.; Rybak, A. T.

2018-05-01

This paper presents a method for determining the dynamic loads on the lifting actuator device other than the conventional methods, for example, ship windlass. For such devices, the operation of their drives is typical under special conditions: different environments, the influence of hydrometeorological factors, a high level of vibration, variability of loading, etc. Hoisting devices working in such conditions are not considered in the standard; however, relevant studies concern permissible parameters of the drive devices of this kind. As an example, the article studied the work deck lifting devices - windlass. To construct a model, the windlass is represented by a rod of the variable cross-section. As a result, a mathematical model of the longitudinal oscillations of such rod is obtained. Analytic dependencies have also been obtained to determine the natural frequencies of the lowest forms of oscillations, which are necessary and are the basis for evaluating the parameters of operation of this type of the device.

Optimal traits of plant hydraulic capacitance as an adaptation to hydroclimatic variability

NASA Astrophysics Data System (ADS)

Hartzell, S. R.; Bartlett, M. S., Jr.; Porporato, A. M.

2016-12-01

Hydraulic capacitance allows plants to uptake and store water when it is abundant. This stored water is utilized during periods of water stress, decreasing tissue damage and increasing carbon assimilation. By providing a more consistent and readily accessible water supply, it buffers water stress variability across daily and seasonal timescales. The rate of plant water storage and withdrawal varies widely between plant species and is principally governed by several plant hydraulic parameters, principally the hydraulic capacitance, the total water storage capacity, and the conductance between xylem and water storage tissue. The timescale of the plant response to changes in environmental conditions may be related to the timescale of relevant environmental variability. For example, the Baobab tree (Adansonia), which grows in an environment with very strong seasonal rainfall variability, has a relatively long timescale of hydraulic response, while an evergreen tree such as Pinus taeda, which mainly contends with daily and inter-rainfall moisture variability, has a much shorter timescale of hydraulic response. Here a model of hydraulic capacitance is coupled to a resistance model of soil-plant-atmosphere continuum. We force this model with stochastic rainfall and examine plant responses to moisture variability at various timescales. Optimal plant hydraulic properties are examined as a function of mean soil moisture (daily variability), mean period between rainfall events (inter-rainfall variability), and seasonal rainfall variability, and the relative importance of each type of variability in shaping plant water use strategies is assessed. Results are compared to typical hydraulic parameters of plants growing under specific environmental conditions. Values of hydraulic traits which optimize carbon assimilation and water use efficiency are found; these values are dependent on mean environmental conditions as well as the timescale of environmental variability.

Quantile regression models of animal habitat relationships

USGS Publications Warehouse

Cade, Brian S.

2003-01-01

Typically, all factors that limit an organism are not measured and included in statistical models used to investigate relationships with their environment. If important unmeasured variables interact multiplicatively with the measured variables, the statistical models often will have heterogeneous response distributions with unequal variances. Quantile regression is an approach for estimating the conditional quantiles of a response variable distribution in the linear model, providing a more complete view of possible causal relationships between variables in ecological processes. Chapter 1 introduces quantile regression and discusses the ordering characteristics, interval nature, sampling variation, weighting, and interpretation of estimates for homogeneous and heterogeneous regression models. Chapter 2 evaluates performance of quantile rankscore tests used for hypothesis testing and constructing confidence intervals for linear quantile regression estimates (0 ≤ τ ≤ 1). A permutation F test maintained better Type I errors than the Chi-square T test for models with smaller n, greater number of parameters p, and more extreme quantiles τ. Both versions of the test required weighting to maintain correct Type I errors when there was heterogeneity under the alternative model. An example application related trout densities to stream channel width:depth. Chapter 3 evaluates a drop in dispersion, F-ratio like permutation test for hypothesis testing and constructing confidence intervals for linear quantile regression estimates (0 ≤ τ ≤ 1). Chapter 4 simulates from a large (N = 10,000) finite population representing grid areas on a landscape to demonstrate various forms of hidden bias that might occur when the effect of a measured habitat variable on some animal was confounded with the effect of another unmeasured variable (spatially and not spatially structured). Depending on whether interactions of the measured habitat and unmeasured variable were negative (interference interactions) or positive (facilitation interactions), either upper (τ > 0.5) or lower (τ < 0.5) quantile regression parameters were less biased than mean rate parameters. Sampling (n = 20 - 300) simulations demonstrated that confidence intervals constructed by inverting rankscore tests provided valid coverage of these biased parameters. Quantile regression was used to estimate effects of physical habitat resources on a bivalve mussel (Macomona liliana) in a New Zealand harbor by modeling the spatial trend surface as a cubic polynomial of location coordinates.

The spatial and temporal variability of groundwater recharge in a forested basin in northern Wisconsin

USGS Publications Warehouse

Dripps, W.R.; Bradbury, K.R.

2010-01-01

Recharge varies spatially and temporally as it depends on a wide variety of factors (e.g. vegetation, precipitation, climate, topography, geology, and soil type), making it one of the most difficult, complex, and uncertain hydrologic parameters to quantify. Despite its inherent variability, groundwater modellers, planners, and policy makers often ignore recharge variability and assume a single average recharge value for an entire watershed. Relatively few attempts have been made to quantify or incorporate spatial and temporal recharge variability into water resource planning or groundwater modelling efforts. In this study, a simple, daily soil-water balance model was developed and used to estimate the spatial and temporal distribution of groundwater recharge of the Trout Lake basin of northern Wisconsin for 1996-2000 as a means to quantify recharge variability. For the 5 years of study, annual recharge varied spatially by as much as 18 cm across the basin; vegetation was the predominant control on this variability. Recharge also varied temporally with a threefold annual difference over the 5-year period. Intra-annually, recharge was limited to a few isolated events each year and exhibited a distinct seasonal pattern. The results suggest that ignoring recharge variability may not only be inappropriate, but also, depending on the application, may invalidate model results and predictions for regional and local water budget calculations, water resource management, nutrient cycling, and contaminant transport studies. Recharge is spatially and temporally variable, and should be modelled as such. Copyright ?? 2009 John Wiley & Sons, Ltd.

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.

Properties of behavior under different random ratio and random interval schedules: A parametric study.

PubMed

Dembo, M; De Penfold, J B; Ruiz, R; Casalta, H

1985-03-01

Four pigeons were trained to peck a key under different values of a temporally defined independent variable (T) and different probabilities of reinforcement (p). Parameter T is a fixed repeating time cycle and p the probability of reinforcement for the first response of each cycle T. Two dependent variables were used: mean response rate and mean postreinforcement pause. For all values of p a critical value for the independent variable T was found (T=1 sec) in which marked changes took place in response rate and postreinforcement pauses. Behavior typical of random ratio schedules was obtained at T 1 sec and behavior typical of random interval schedules at T 1 sec. Copyright © 1985. Published by Elsevier B.V.

Sensitivity analysis of a sound absorption model with correlated inputs

NASA Astrophysics Data System (ADS)

Chai, W.; Christen, J.-L.; Zine, A.-M.; Ichchou, M.

2017-04-01

Sound absorption in porous media is a complex phenomenon, which is usually addressed with homogenized models, depending on macroscopic parameters. Since these parameters emerge from the structure at microscopic scale, they may be correlated. This paper deals with sensitivity analysis methods of a sound absorption model with correlated inputs. Specifically, the Johnson-Champoux-Allard model (JCA) is chosen as the objective model with correlation effects generated by a secondary micro-macro semi-empirical model. To deal with this case, a relatively new sensitivity analysis method Fourier Amplitude Sensitivity Test with Correlation design (FASTC), based on Iman's transform, is taken into application. This method requires a priori information such as variables' marginal distribution functions and their correlation matrix. The results are compared to the Correlation Ratio Method (CRM) for reference and validation. The distribution of the macroscopic variables arising from the microstructure, as well as their correlation matrix are studied. Finally the results of tests shows that the correlation has a very important impact on the results of sensitivity analysis. Assessment of correlation strength among input variables on the sensitivity analysis is also achieved.

Sensitivity of numerical simulation models of debris flow to the rheological parameters and application in the engineering environment

NASA Astrophysics Data System (ADS)

Rosso, M.; Sesenna, R.; Magni, L.; Demurtas, L.; Uras, G.

2009-04-01

Debris flows represents serious hazards in mountainous regions. For engineers it is important to know the quantitative analysis of the flow in terms of volumes, velocities and front height, and it is significant to predict possible triggering and deposition areas. In order to predict flow and deposition behaviour, debris flows traditionally have been regarded as homogenous fluids and bulk flow behaviour that was considered to be controlled by the rheological properties of the matrix. Flow mixtures with a considerable fraction of fines particles typically show a viscoplastic flow behaviour but due to the high variability of the material composition, complex physical interactions on the particle scale and time dependent effects, no generally applicable models are at time capable to cover the full range of all possible flow types. A first category of models, mostly of academic origin, uses a rigorous methodological approach, directed to describe to the phenomenon characterizing all the main parameters that regulate the origin and the propagation of the debris flow, with detail attention to rheology. A second category, which are referred mainly to the commercial environment, has as first objective the versatility and the simplicity of use, introducing theoretical simplifications in the definition of the rheology and in the propagation of the debris flow. The physical variables connected to the rheology are often difficult to determine and involve complex procedures of calibration of the model or long and expensive campaigns of measure, whose application can turn out not suitable to the engineering environment. The rheological parameters of the debris are however to the base of the codes of calculation mainly used in commerce. The necessary data to the implementation of the model refer mainly to the dynamic viscosity, to the shear stress, to the volumetric mass and to the volumetric concentration, that are linked variables. Through the application of various bidimensional and monodimensional commercial models for the simulation of debris flow, in particular because of the reconstruction of famous and expected events in the river basin of the Comboè torrent (Aosta Valley, Italy), it has been possible to reach careful consideration about the calibration of the rheological parameters and the sensitivity of simulation models, specifically about the variability of them. The geomechanical and volumetric characteristics of the sediment at the bottom of the debris could produce uncertainties in model implementation, above all in not exclusively cinematic models, mostly influenced by the rheological parameters. The parameter that mainly influences the final result of the applied numerical models is the volumetric solid concentration that is variable in space and time during the debris flow propagation. In fact rheological parameters are described by a power equation of volumetric concentration. The potentiality and the suitability of a numerical code in the engineering environmental application have to be consider not referring only to the quality and amount of results, but also to the sensibility regarding the parameters variability that are bases of the inner ruotines of the program. Therefore, a suitable model will have to be sensitive to the variability of parameters that the customer can calculate with greater precision. On the other side, it will have to be sufficiently stable to the variation of those parameters that the customer cannot define univocally, but only by range of variation. One of the models utilized for the simulation of debris flow on the Comboè Torrent has been demonstrated as an heavy influenced example by small variation of rheological parameters. Consequently, in spite of the possibility to lead accurate procedures of back-analysis about a recent intense event, it has been found a difficulty in the calibration of the concentration for new expected events. That involved an extreme variability of the final results. In order to achieve more accuracy in the numerical simulation, the rheological parameters were estimated by an implicit way, proceeding to their determination through the application of simple numerical iteration. In fact they can link the obtained values of velocity and hydraulic levels. Literature formulations were used in order to determine rheological parameters. The parameters and ? wowere correlated to velocity and to empirical parameters that have small range of variability. This approach allows to produce a control of input parameters in the calculation models, comparing the obtained base result (velocity and water surface elevation). The implementation of numerical models for engineering profession must be carried out in order that aleatory variables, that are difficult to determine, do not involve an extreme variability of the final result. However, it's a good manner to proceed to the determination of interested variables by means of empirical formulations and through the comparison between different simplified models, including in the analysis pure cinematic models.

g-Jitter Mixed Convective Slip Flow of Nanofluid past a Permeable Stretching Sheet Embedded in a Darcian Porous Media with Variable Viscosity

PubMed Central

Uddin, Mohammed J.; Khan, Waqar A.; Amin, Norsarahaida S.

2014-01-01

The unsteady two-dimensional laminar g-Jitter mixed convective boundary layer flow of Cu-water and Al2O3-water nanofluids past a permeable stretching sheet in a Darcian porous is studied by using an implicit finite difference numerical method with quasi-linearization technique. It is assumed that the plate is subjected to velocity and thermal slip boundary conditions. We have considered temperature dependent viscosity. The governing boundary layer equations are converted into non-similar equations using suitable transformations, before being solved numerically. The transport equations have been shown to be controlled by a number of parameters including viscosity parameter, Darcy number, nanoparticle volume fraction, Prandtl number, velocity slip, thermal slip, suction/injection and mixed convection parameters. The dimensionless velocity and temperature profiles as well as friction factor and heat transfer rates are presented graphically and discussed. It is found that the velocity reduces with velocity slip parameter for both nanofluids for fluid with both constant and variable properties. It is further found that the skin friction decreases with both Darcy number and momentum slip parameter while it increases with viscosity variation parameter. The surface temperature increases as the dimensionless time increases for both nanofluids. Nusselt numbers increase with mixed convection parameter and Darcy numbers and decreases with the momentum slip. Excellent agreement is found between the numerical results of the present paper with published results. PMID:24927277

State-variable theories for nonelastic deformation

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

Li, C.Y.

The various concepts of mechanical equation of state for nonelastic deformation in crystalline solids, originally proposed for plastic deformation, have been recently extended to describe additional phenomena such as anelastic and microplastic deformation including the Bauschinger effect. It has been demonstrated that it is possible to predict, based on current state variables in a unified way, the mechanical response of a material under an arbitrary loading. Thus, if the evolution laws of the state variables are known, one can describe the behavior of a material for a thermal-mechanical path of interest, for example, during constant load (or stress) creep withoutmore » relying on specialized theories. Some of the existing theories of mechanical equation of state for nonelastic deformation are reviewed. The establishment of useful forms of mechanical equation of state has to depend on extensive experimentation in the same way as that involved in the development, for example, the ideal gas law. Recent experimental efforts are also reviewed. It has been possible to develop state-variable deformation models based on experimental findings and apply them to creep, cyclic deformation, and other time-dependent deformation. Attempts are being made to correlate the material parameters of the state-variable models with the microstructure of a material. 24 figures.« less

Reliability Based Geometric Design of Horizontal Circular Curves

NASA Astrophysics Data System (ADS)

Rajbongshi, Pabitra; Kalita, Kuldeep

2018-06-01

Geometric design of horizontal circular curve primarily involves with radius of the curve and stopping sight distance at the curve section. Minimum radius is decided based on lateral thrust exerted on the vehicles and the minimum stopping sight distance is provided to maintain the safety in longitudinal direction of vehicles. Available sight distance at site can be regulated by changing the radius and middle ordinate at the curve section. Both radius and sight distance depend on design speed. Speed of vehicles at any road section is a variable parameter and therefore, normally the 98th percentile speed is taken as the design speed. This work presents a probabilistic approach for evaluating stopping sight distance, considering the variability of all input parameters of sight distance. It is observed that the 98th percentile sight distance value is much lower than the sight distance corresponding to 98th percentile speed. The distribution of sight distance parameter is also studied and found to follow a lognormal distribution. Finally, the reliability based design charts are presented for both plain and hill regions, and considering the effect of lateral thrust.

Modelling tourists arrival using time varying parameter

NASA Astrophysics Data System (ADS)

Suciptawati, P.; Sukarsa, K. G.; Kencana, Eka N.

2017-06-01

The importance of tourism and its related sectors to support economic development and poverty reduction in many countries increase researchers’ attentions to study and model tourists’ arrival. This work is aimed to demonstrate time varying parameter (TVP) technique to model the arrival of Korean’s tourists to Bali. The number of Korean tourists whom visiting Bali for period January 2010 to December 2015 were used to model the number of Korean’s tourists to Bali (KOR) as dependent variable. The predictors are the exchange rate of Won to IDR (WON), the inflation rate in Korea (INFKR), and the inflation rate in Indonesia (INFID). Observing tourists visit to Bali tend to fluctuate by their nationality, then the model was built by applying TVP and its parameters were approximated using Kalman Filter algorithm. The results showed all of predictor variables (WON, INFKR, INFID) significantly affect KOR. For in-sample and out-of-sample forecast with ARIMA’s forecasted values for the predictors, TVP model gave mean absolute percentage error (MAPE) as much as 11.24 percent and 12.86 percent, respectively.

A study on the dependence of nuclear viscosity on temperature

NASA Astrophysics Data System (ADS)

Vardaci, E.; Di Nitto, A.; Nadtochy, P. N.; La Rana, G.; Cinausero, M.; Prete, G.; Gelli, N.; Ashaduzzaman, M.; Davide, F.; Pulcini, A.; Quero, D.; Kozulin, E. M.; Knyazheva, G. N.; Itkis, I. M.

2018-05-01

Nuclear viscosity is an irreplaceable ingredient of nuclear fission collective dynamical models. It drives the exchange of energy between the collective variables and the thermal bath of single particle degrees of freedom. Its dependence on the shape and temperature is a matter of controversy. By using systems of intermediate fissility we have demonstrated in a recent study that the viscosity parameters is larger for compact shapes, and decreases for larger deformations of the fissioning system, at variance with the conclusions of the statistical model modified to include empirically viscosity and time scales. In this contribution we propose an experimental scenario to highlight the possible dependence of the viscosity from the temperature.

Gender differences in pharmacokinetics and pharmacodynamics of methadone substitution therapy.

PubMed

Graziani, Manuela; Nisticò, Robert

2015-01-01

Gender-related differences in the pharmacological effects of drug are an emerging topic. This review examines gender differences in both pharmacokinetic and pharmacodynamic aspects of methadone, a long-acting opioid agonist that is prescribed as a treatment for opioid dependence and the management of chronic pain. We performed a search in the Medline database from 1990 to 2014 in order to find published literature related to gender differences in pharmacokinetics (PK) and pharmacodynamics (PD) of methadone. None of the studies were carried out with the primary or secondary aim to identify any gender differences in the pharmacokinetic profile of methadone. Importantly; high inter-subjects variability in PK parameters was found also intra female population. The reported differences in volume of distribution could be ascribed to the physiological differences between men and women in body weight and composition, taking into account that the dose of methadone was established irrespective of body weight of patients (Peles and Adelson, 2006). On the other hand, the few studies present in literature found no gender difference in some direct pharmacodynamic parameters. Some reports have suggested that female gender is associated with an increased risk for long-QT-related cardiac arrhythmias in methadone maintenance subjects. Even though it may be too simplistic to expect variability only in one parameter to explain inter-individual variation in methadone response, we believe that a better knowledge of gender-related differences might have significant implications for better outcomes in opioid dependence substitution therapy in women.

Long term measurements of optical properties and their hygroscopic enhancement

NASA Astrophysics Data System (ADS)

Hervo, M.; Sellegri, K.; Pichon, J. M.; Roger, J. C.; Laj, P.

2014-11-01

Optical properties of aerosols were measured from the GAW Puy de Dôme station (1465 m) over a seven year period (2006-2012). The impact of hygroscopicity on aerosol optical properties was calculated over a two year period (2010-2011). The analysis of the spatial and temporal variability of the optical properties showed that while no long term trend was found, a clear seasonal and diurnal variation was observed on the extensive parameters (scattering, absorption). Scattering and absorption coefficients were highest during the warm season and daytime, in concordance with the seasonality and diurnal variation of the PBL height reaching the site. Intensive parameters (single scattering albedo, asymmetry factor, refractive index) did not show such a strong diurnal variability, but still indicated different values depending on the season. Both extensive and intensive optical parameters were sensitive to the air mass origin. A strong impact of hygroscopicity on aerosol optical properties was calculated, mainly on aerosol scattering, with a dependence on the aerosol type. At 90% humidity, the scattering factor enhancement (fσsca) was more than 4.4 for oceanic aerosol that have mixed with a pollution plume. Consequently, the aerosol radiative forcing was estimated to be 2.8 times higher at RH = 90% and 1.75 times higher at ambient RH when hygroscopic growth of the aerosol was considered. The hygroscopicity enhancement factor of the scattering coefficient was parameterized as a function of humidity and air mass type.

Consolidation of fatigue and fatigue-crack-propagation data for design use

NASA Technical Reports Server (NTRS)

Rice, R. C.; Davies, K. B.; Jaske, C. E.; Feddersen, C. E.

1975-01-01

Analytical methods developed for consolidation of fatigue and fatigue-crack-propagation data for use in design of metallic aerospace structural components are evaluated. A comprehensive file of data on 2024 and 7075 aluminums, Ti-6Al-4V alloy, and 300M steel was established by obtaining information from both published literature and reports furnished by aerospace companies. Analyses are restricted to information obtained from constant-amplitude load or strain cycling of specimens in air at room temperature. Both fatigue and fatigue-crack-propagation data are analyzed on a statistical basis using a least-squares regression approach. For fatigue, an equivalent strain parameter is used to account for mean stress or stress ratio effects and is treated as the independent variable; cyclic fatigue life is considered to be the dependent variable. An effective stress-intensity factor is used to account for the effect of load ratio on fatigue-crack-propagation and treated as the independent variable. In this latter case, crack-growth rate is considered to be the dependent variable. A two term power function is used to relate equivalent strain to fatigue life, and an arc-hyperbolic-tangent function is used to relate effective stress intensity to crack-growth rate.

Effect of Small Numbers of Test Results on Accuracy of Hoek-Brown Strength Parameter Estimations: A Statistical Simulation Study

NASA Astrophysics Data System (ADS)

Bozorgzadeh, Nezam; Yanagimura, Yoko; Harrison, John P.

2017-12-01

The Hoek-Brown empirical strength criterion for intact rock is widely used as the basis for estimating the strength of rock masses. Estimations of the intact rock H-B parameters, namely the empirical constant m and the uniaxial compressive strength σc, are commonly obtained by fitting the criterion to triaxial strength data sets of small sample size. This paper investigates how such small sample sizes affect the uncertainty associated with the H-B parameter estimations. We use Monte Carlo (MC) simulation to generate data sets of different sizes and different combinations of H-B parameters, and then investigate the uncertainty in H-B parameters estimated from these limited data sets. We show that the uncertainties depend not only on the level of variability but also on the particular combination of parameters being investigated. As particular combinations of H-B parameters can informally be considered to represent specific rock types, we discuss that as the minimum number of required samples depends on rock type it should correspond to some acceptable level of uncertainty in the estimations. Also, a comparison of the results from our analysis with actual rock strength data shows that the probability of obtaining reliable strength parameter estimations using small samples may be very low. We further discuss the impact of this on ongoing implementation of reliability-based design protocols and conclude with suggestions for improvements in this respect.

Spectral Behavior of a Linearized Land-Atmosphere Model: Applications to Hydrometeorology

NASA Astrophysics Data System (ADS)

Gentine, P.; Entekhabi, D.; Polcher, J.

2008-12-01

The present study develops an improved version of the linearized land-atmosphere model first introduced by Lettau (1951). This model is used to investigate the spectral response of land-surface variables to a daily forcing of incoming radiation at the land-surface. An analytical solution of the problem is found in the form of temporal Fourier series and gives the atmospheric boundary-layer and soil profiles of state variables (potential temperature, specific humidity, sensible and latent heat fluxes). Moreover the spectral dependency of surface variables is expressed as function of land-surface parameters (friction velocity, vegetation height, aerodynamic resistance, stomatal conductance). This original approach has several advantages: First, the model only requires little data to work and perform well: only time series of incoming radiation at the land-surface, mean specific humidity and temperature at any given height are required. These inputs being widely available over the globe, the model can easily be run and tested under various conditions. The model will also help analysing the diurnal shape and frequency dependency of surface variables and soil-ABL profiles. In particular, a strong emphasis is being placed on the explanation and prediction of Evaporative Fraction (EF) and Bowen Ratio diurnal shapes. EF is shown to remain a diurnal constant under restricting conditions: fair and dry weather, with strong solar radiation and no clouds. Moreover, the EF pseudo-constancy value is found and given as function of surface parameters, such as aerodynamic resistance and stomatal conductance. Then, application of the model for the conception of remote-sensing tools, according to the temporal resolution of the sensor, will also be discussed. Finally, possible extensions and improvement of the model will be discussed.

Quantum Parameter Estimation: From Experimental Design to Constructive Algorithm

NASA Astrophysics Data System (ADS)

Yang, Le; Chen, Xi; Zhang, Ming; Dai, Hong-Yi

2017-11-01

In this paper we design the following two-step scheme to estimate the model parameter ω 0 of the quantum system: first we utilize the Fisher information with respect to an intermediate variable v=\\cos ({ω }0t) to determine an optimal initial state and to seek optimal parameters of the POVM measurement operators; second we explore how to estimate ω 0 from v by choosing t when a priori information knowledge of ω 0 is available. Our optimal initial state can achieve the maximum quantum Fisher information. The formulation of the optimal time t is obtained and the complete algorithm for parameter estimation is presented. We further explore how the lower bound of the estimation deviation depends on the a priori information of the model. Supported by the National Natural Science Foundation of China under Grant Nos. 61273202, 61673389, and 61134008

A variable temperature EPR study of Mn(2+)-doped NH(4)Cl(0.9)I(0.1) single crystal at 170 GHz: zero-field splitting parameter and its absolute sign.

PubMed

Misra, Sushil K; Andronenko, Serguei I; Chand, Prem; Earle, Keith A; Paschenko, Sergei V; Freed, Jack H

2005-06-01

EPR measurements have been carried out on a single crystal of Mn(2+)-doped NH(4)Cl(0.9)I(0.1) at 170-GHz in the temperature range of 312-4.2K. The spectra have been analyzed (i) to estimate the spin-Hamiltonian parameters; (ii) to study the temperature variation of the zero-field splitting (ZFS) parameter; (iii) to confirm the negative absolute sign of the ZFS parameter unequivocally from the temperature-dependent relative intensities of hyperfine sextets at temperatures below 10K; and (iv) to detect the occurrence of a structural phase transition at 4.35K from the change in the structure of the EPR lines with temperature below 10K.

Analog design optimization methodology for ultralow-power circuits using intuitive inversion-level and saturation-level parameters

NASA Astrophysics Data System (ADS)

Eimori, Takahisa; Anami, Kenji; Yoshimatsu, Norifumi; Hasebe, Tetsuya; Murakami, Kazuaki

2014-01-01

A comprehensive design optimization methodology using intuitive nondimensional parameters of inversion-level and saturation-level is proposed, especially for ultralow-power, low-voltage, and high-performance analog circuits with mixed strong, moderate, and weak inversion metal-oxide-semiconductor transistor (MOST) operations. This methodology is based on the synthesized charge-based MOST model composed of Enz-Krummenacher-Vittoz (EKV) basic concepts and advanced-compact-model (ACM) physics-based equations. The key concept of this methodology is that all circuit and system characteristics are described as some multivariate functions of inversion-level parameters, where the inversion level is used as an independent variable representative of each MOST. The analog circuit design starts from the first step of inversion-level design using universal characteristics expressed by circuit currents and inversion-level parameters without process-dependent parameters, followed by the second step of foundry-process-dependent design and the last step of verification using saturation-level criteria. This methodology also paves the way to an intuitive and comprehensive design approach for many kinds of analog circuit specifications by optimization using inversion-level log-scale diagrams and saturation-level criteria. In this paper, we introduce an example of our design methodology for a two-stage Miller amplifier.

Microprocessor-based long term cardiorespirography. II. Status evaluation in term and premature newborns.

PubMed

Hörnchen, H; Betz, R; Kotlarek, F; Roebruck, P

1983-01-01

In 1965 URBACH et al. and RUDOLPH et al. [35, 39] described a loss of heart rate variability in severely ill neonates. In this study we investigated the correlation between instantaneous heart rate patterns and status diagnosis. We used a microprocessor-based cardiorespirography system. Seventy five newborn infants (51 prematures and 24 term neonates) were studied for about 12 hours each. Twenty nine patients had a second record after the first investigation. Parameters were: Type of frequency and oscillation, long time variability (LTV), short time variability (STV) and the newly introduced P-value (maximal difference between two successive R-peaks in five minutes). We found clear differences between the study groups. With increasing severity of illness mean values ("group mean values") of long time variability, short time variability and P-value decreased. Fixed heart rate became predominant. The most pronounced loss of heart rate variability was seen in infants with severe intracranial bleeding, thus offering a tentative diagnosis. For statistical analysis long time variability and the silent oscillation type have been proved as best parameters for this diagnosis. Severely decreased heart rate variations also have been seen in infants with acute renal failure--possibly because of brain edema--, after application of muscle relaxants, repeated doses of sedatives, and after prolonged anesthesia. Otherwise, the heart rate variability was probably dependent on age and gestational age in prematures and newborn infants without intracranial bleeding. It is possible to use microprocessor-based long time cardiorespirography as a simple screening method for the diagnosis of neonatal intracerebral bleeding. In future experiences transcutaneous measurements of oxygen tension should be included.

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.

U(1)-invariant membranes: The geometric formulation, Abel, and pendulum differential equations

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

Zheltukhin, A. A.; Fysikum, AlbaNova, Stockholm University, 106 91 Stockholm; NORDITA, Roslagstullsbacken 23, 106 91 Stockholm

The geometric approach to study the dynamics of U(1)-invariant membranes is developed. The approach reveals an important role of the Abel nonlinear differential equation of the first type with variable coefficients depending on time and one of the membrane extendedness parameters. The general solution of the Abel equation is constructed. Exact solutions of the whole system of membrane equations in the D=5 Minkowski space-time are found and classified. It is shown that if the radial component of the membrane world vector is only time dependent, then the dynamics is described by the pendulum equation.

Thermally stratified flow of second grade fluid with non-Fourier heat flux and temperature dependent thermal conductivity

NASA Astrophysics Data System (ADS)

Khan, M. Ijaz; Zia, Q. M. Zaigham; Alsaedi, A.; Hayat, T.

2018-03-01

This attempt explores stagnation point flow of second grade material towards an impermeable stretched cylinder. Non-Fourier heat flux and thermal stratification are considered. Thermal conductivity dependents upon temperature. Governing non-linear differential system is solved using homotopic procedure. Interval of convergence for the obtained series solutions is explicitly determined. Physical quantities of interest have been examined for the influential variables entering into the problems. It is examined that curvature parameter leads to an enhancement in velocity and temperature. Further temperature for non-Fourier heat flux model is less than Fourier's heat conduction law.

Event-scale power law recession analysis: quantifying methodological uncertainty

NASA Astrophysics Data System (ADS)

Dralle, David N.; Karst, Nathaniel J.; Charalampous, Kyriakos; Veenstra, Andrew; Thompson, Sally E.

2017-01-01

The study of single streamflow recession events is receiving increasing attention following the presentation of novel theoretical explanations for the emergence of power law forms of the recession relationship, and drivers of its variability. Individually characterizing streamflow recessions often involves describing the similarities and differences between model parameters fitted to each recession time series. Significant methodological sensitivity has been identified in the fitting and parameterization of models that describe populations of many recessions, but the dependence of estimated model parameters on methodological choices has not been evaluated for event-by-event forms of analysis. Here, we use daily streamflow data from 16 catchments in northern California and southern Oregon to investigate how combinations of commonly used streamflow recession definitions and fitting techniques impact parameter estimates of a widely used power law recession model. Results are relevant to watersheds that are relatively steep, forested, and rain-dominated. The highly seasonal mediterranean climate of northern California and southern Oregon ensures study catchments explore a wide range of recession behaviors and wetness states, ideal for a sensitivity analysis. In such catchments, we show the following: (i) methodological decisions, including ones that have received little attention in the literature, can impact parameter value estimates and model goodness of fit; (ii) the central tendencies of event-scale recession parameter probability distributions are largely robust to methodological choices, in the sense that differing methods rank catchments similarly according to the medians of these distributions; (iii) recession parameter distributions are method-dependent, but roughly catchment-independent, such that changing the choices made about a particular method affects a given parameter in similar ways across most catchments; and (iv) the observed correlative relationship between the power-law recession scale parameter and catchment antecedent wetness varies depending on recession definition and fitting choices. Considering study results, we recommend a combination of four key methodological decisions to maximize the quality of fitted recession curves, and to minimize bias in the related populations of fitted recession parameters.

Sensitivity of Turbine-Height Wind Speeds to Parameters in Planetary Boundary-Layer and Surface-Layer Schemes in the Weather Research and Forecasting Model

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

Yang, Ben; Qian, Yun; Berg, Larry K.

We evaluate the sensitivity of simulated turbine-height winds to 26 parameters applied in a planetary boundary layer (PBL) scheme and a surface layer scheme of the Weather Research and Forecasting (WRF) model over an area of complex terrain during the Columbia Basin Wind Energy Study. An efficient sampling algorithm and a generalized linear model are used to explore the multiple-dimensional parameter space and quantify the parametric sensitivity of modeled turbine-height winds. The results indicate that most of the variability in the ensemble simulations is contributed by parameters related to the dissipation of the turbulence kinetic energy (TKE), Prandtl number, turbulencemore » length scales, surface roughness, and the von Kármán constant. The relative contributions of individual parameters are found to be dependent on both the terrain slope and atmospheric stability. The parameter associated with the TKE dissipation rate is found to be the most important one, and a larger dissipation rate can produce larger hub-height winds. A larger Prandtl number results in weaker nighttime winds. Increasing surface roughness reduces the frequencies of both extremely weak and strong winds, implying a reduction in the variability of the wind speed. All of the above parameters can significantly affect the vertical profiles of wind speed, the altitude of the low-level jet and the magnitude of the wind shear strength. The wind direction is found to be modulated by the same subset of influential parameters. Remainder of abstract is in attachment.« less

Analysis of isothermal and cooling-rate-dependent immersion freezing by a unifying stochastic ice nucleation model

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

Alpert, Peter A.; Knopf, Daniel A.

Immersion freezing is an important ice nucleation pathway involved in the formation of cirrus and mixed-phase clouds. Laboratory immersion freezing experiments are necessary to determine the range in temperature, T, and relative humidity, RH, at which ice nucleation occurs and to quantify the associated nucleation kinetics. Typically, isothermal (applying a constant temperature) and cooling-rate-dependent immersion freezing experiments are conducted. In these experiments it is usually assumed that the droplets containing ice nucleating particles (INPs) all have the same INP surface area (ISA); however, the validity of this assumption or the impact it may have on analysis and interpretation of the experimentalmore » data is rarely questioned. Descriptions of ice active sites and variability of contact angles have been successfully formulated to describe ice nucleation experimental data in previous research; however, we consider the ability of a stochastic freezing model founded on classical nucleation theory to reproduce previous results and to explain experimental uncertainties and data scatter. A stochastic immersion freezing model based on first principles of statistics is presented, which accounts for variable ISA per droplet and uses parameters including the total number of droplets, N tot, and the heterogeneous ice nucleation rate coefficient, J het( T). This model is applied to address if (i) a time and ISA-dependent stochastic immersion freezing process can explain laboratory immersion freezing data for different experimental methods and (ii) the assumption that all droplets contain identical ISA is a valid conjecture with subsequent consequences for analysis and interpretation of immersion freezing. The simple stochastic model can reproduce the observed time and surface area dependence in immersion freezing experiments for a variety of methods such as: droplets on a cold-stage exposed to air or surrounded by an oil matrix, wind and acoustically levitated droplets, droplets in a continuous-flow diffusion chamber (CFDC), the Leipzig aerosol cloud interaction simulator (LACIS), and the aerosol interaction and dynamics in the atmosphere (AIDA) cloud chamber. Observed time-dependent isothermal frozen fractions exhibiting non-exponential behavior can be readily explained by this model considering varying ISA. An apparent cooling-rate dependence of J het is explained by assuming identical ISA in each droplet. When accounting for ISA variability, the cooling-rate dependence of ice nucleation kinetics vanishes as expected from classical nucleation theory. Finally, the model simulations allow for a quantitative experimental uncertainty analysis for parameters N tot, T, RH, and the ISA variability. We discuss the implications of our results for experimental analysis and interpretation of the immersion freezing process.« less

Analysis of isothermal and cooling-rate-dependent immersion freezing by a unifying stochastic ice nucleation model

DOE PAGES

Alpert, Peter A.; Knopf, Daniel A.

2016-02-24

Immersion freezing is an important ice nucleation pathway involved in the formation of cirrus and mixed-phase clouds. Laboratory immersion freezing experiments are necessary to determine the range in temperature, T, and relative humidity, RH, at which ice nucleation occurs and to quantify the associated nucleation kinetics. Typically, isothermal (applying a constant temperature) and cooling-rate-dependent immersion freezing experiments are conducted. In these experiments it is usually assumed that the droplets containing ice nucleating particles (INPs) all have the same INP surface area (ISA); however, the validity of this assumption or the impact it may have on analysis and interpretation of the experimentalmore » data is rarely questioned. Descriptions of ice active sites and variability of contact angles have been successfully formulated to describe ice nucleation experimental data in previous research; however, we consider the ability of a stochastic freezing model founded on classical nucleation theory to reproduce previous results and to explain experimental uncertainties and data scatter. A stochastic immersion freezing model based on first principles of statistics is presented, which accounts for variable ISA per droplet and uses parameters including the total number of droplets, N tot, and the heterogeneous ice nucleation rate coefficient, J het( T). This model is applied to address if (i) a time and ISA-dependent stochastic immersion freezing process can explain laboratory immersion freezing data for different experimental methods and (ii) the assumption that all droplets contain identical ISA is a valid conjecture with subsequent consequences for analysis and interpretation of immersion freezing. The simple stochastic model can reproduce the observed time and surface area dependence in immersion freezing experiments for a variety of methods such as: droplets on a cold-stage exposed to air or surrounded by an oil matrix, wind and acoustically levitated droplets, droplets in a continuous-flow diffusion chamber (CFDC), the Leipzig aerosol cloud interaction simulator (LACIS), and the aerosol interaction and dynamics in the atmosphere (AIDA) cloud chamber. Observed time-dependent isothermal frozen fractions exhibiting non-exponential behavior can be readily explained by this model considering varying ISA. An apparent cooling-rate dependence of J het is explained by assuming identical ISA in each droplet. When accounting for ISA variability, the cooling-rate dependence of ice nucleation kinetics vanishes as expected from classical nucleation theory. Finally, the model simulations allow for a quantitative experimental uncertainty analysis for parameters N tot, T, RH, and the ISA variability. We discuss the implications of our results for experimental analysis and interpretation of the immersion freezing process.« less

MIMICKING COUNTERFACTUAL OUTCOMES TO ESTIMATE CAUSAL EFFECTS.

PubMed

Lok, Judith J

2017-04-01

In observational studies, treatment may be adapted to covariates at several times without a fixed protocol, in continuous time. Treatment influences covariates, which influence treatment, which influences covariates, and so on. Then even time-dependent Cox-models cannot be used to estimate the net treatment effect. Structural nested models have been applied in this setting. Structural nested models are based on counterfactuals: the outcome a person would have had had treatment been withheld after a certain time. Previous work on continuous-time structural nested models assumes that counterfactuals depend deterministically on observed data, while conjecturing that this assumption can be relaxed. This article proves that one can mimic counterfactuals by constructing random variables, solutions to a differential equation, that have the same distribution as the counterfactuals, even given past observed data. These "mimicking" variables can be used to estimate the parameters of structural nested models without assuming the treatment effect to be deterministic.

Adaptive distributed source coding.

PubMed

Varodayan, David; Lin, Yao-Chung; Girod, Bernd

2012-05-01

We consider distributed source coding in the presence of hidden variables that parameterize the statistical dependence among sources. We derive the Slepian-Wolf bound and devise coding algorithms for a block-candidate model of this problem. The encoder sends, in addition to syndrome bits, a portion of the source to the decoder uncoded as doping bits. The decoder uses the sum-product algorithm to simultaneously recover the source symbols and the hidden statistical dependence variables. We also develop novel techniques based on density evolution (DE) to analyze the coding algorithms. We experimentally confirm that our DE analysis closely approximates practical performance. This result allows us to efficiently optimize parameters of the algorithms. In particular, we show that the system performs close to the Slepian-Wolf bound when an appropriate doping rate is selected. We then apply our coding and analysis techniques to a reduced-reference video quality monitoring system and show a bit rate saving of about 75% compared with fixed-length coding.

LSENS, a general chemical kinetics and sensitivity analysis code for gas-phase reactions: User's guide

NASA Technical Reports Server (NTRS)

Radhakrishnan, Krishnan; Bittker, David A.

1993-01-01

A general chemical kinetics and sensitivity analysis code for complex, homogeneous, gas-phase reactions is described. The main features of the code, LSENS, are its flexibility, efficiency and convenience in treating many different chemical reaction models. The models include static system, steady, one-dimensional, inviscid flow, shock initiated reaction, and a perfectly stirred reactor. In addition, equilibrium computations can be performed for several assigned states. An implicit numerical integration method, which works efficiently for the extremes of very fast and very slow reaction, is used for solving the 'stiff' differential equation systems that arise in chemical kinetics. For static reactions, sensitivity coefficients of all dependent variables and their temporal derivatives with respect to the initial values of dependent variables and/or the rate coefficient parameters can be computed. This paper presents descriptions of the code and its usage, and includes several illustrative example problems.

Can Functional Cardiac Age be Predicted from ECG in a Normal Healthy Population

NASA Technical Reports Server (NTRS)

Schlegel, Todd; Starc, Vito; Leban, Manja; Sinigoj, Petra; Vrhovec, Milos

2011-01-01

In a normal healthy population, we desired to determine the most age-dependent conventional and advanced ECG parameters. We hypothesized that changes in several ECG parameters might correlate with age and together reliably characterize the functional age of the heart. Methods: An initial study population of 313 apparently healthy subjects was ultimately reduced to 148 subjects (74 men, 84 women, in the range from 10 to 75 years of age) after exclusion criteria. In all subjects, ECG recordings (resting 5-minute 12-lead high frequency ECG) were evaluated via custom software programs to calculate up to 85 different conventional and advanced ECG parameters including beat-to-beat QT and RR variability, waveform complexity, and signal-averaged, high-frequency and spatial/spatiotemporal ECG parameters. The prediction of functional age was evaluated by multiple linear regression analysis using the best 5 univariate predictors. Results: Ignoring what were ultimately small differences between males and females, the functional age was found to be predicted (R2= 0.69, P < 0.001) from a linear combination of 5 independent variables: QRS elevation in the frontal plane (p<0.001), a new repolarization parameter QTcorr (p<0.001), mean high frequency QRS amplitude (p=0.009), the variability parameter % VLF of RRV (p=0.021) and the P-wave width (p=0.10). Here, QTcorr represents the correlation between the calculated QT and the measured QT signal. Conclusions: In apparently healthy subjects with normal conventional ECGs, functional cardiac age can be estimated by multiple linear regression analysis of mostly advanced ECG results. Because some parameters in the regression formula, such as QTcorr, high frequency QRS amplitude and P-wave width also change with disease in the same direction as with increased age, increased functional age of the heart may reflect subtle age-related pathologies in cardiac electrical function that are usually hidden on conventional ECG.

Local linear estimation of concordance probability with application to covariate effects models on association for bivariate failure-time data.

PubMed

Ding, Aidong Adam; Hsieh, Jin-Jian; Wang, Weijing

2015-01-01

Bivariate survival analysis has wide applications. In the presence of covariates, most literature focuses on studying their effects on the marginal distributions. However covariates can also affect the association between the two variables. In this article we consider the latter issue by proposing a nonstandard local linear estimator for the concordance probability as a function of covariates. Under the Clayton copula, the conditional concordance probability has a simple one-to-one correspondence with the copula parameter for different data structures including those subject to independent or dependent censoring and dependent truncation. The proposed method can be used to study how covariates affect the Clayton association parameter without specifying marginal regression models. Asymptotic properties of the proposed estimators are derived and their finite-sample performances are examined via simulations. Finally, for illustration, we apply the proposed method to analyze a bone marrow transplant data set.

Correlating the internal length in strain gradient plasticity theory with the microstructure of material

NASA Astrophysics Data System (ADS)

Zhao, Jianfeng; Zhang, Xu; Konstantinidis, Avraam A.; Kang, Guozheng

2015-06-01

The internal length is the governing parameter in strain gradient theories which among other things have been used successfully to interpret size effects at the microscale. Physically, the internal length is supposed to be related with the microstructure of the material and evolves during the deformation. Based on Taylor hardening law, we propose a power-law relationship to describe the evolution of the variable internal length with strain. Then, the classical Fleck-Hutchinson strain gradient theory is extended with a strain-dependent internal length, and the generalized Fleck-Hutchinson theory is confirmed here, by comparing our model predictions to recent experimental data on tension and torsion of thin wires with varying diameter and grain size. Our work suggests that the internal length is a configuration-dependent parameter, closely related to dislocation characteristics and grain size, as well as sample geometry when this affects either the underlying microstructure or the ductility of the material.

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.

Airborne fungal spores of Alternaria, meteorological parameters and predicting variables

NASA Astrophysics Data System (ADS)

Filali Ben Sidel, Farah; Bouziane, Hassan; del Mar Trigo, Maria; El Haskouri, Fatima; Bardei, Fadoua; Redouane, Abdelbari; Kadiri, Mohamed; Riadi, Hassane; Kazzaz, Mohamed

2015-03-01

Alternaria is frequently found as airborne fungal spores and is recognized as an important cause of respiratory allergies. The aerobiological monitoring of fungal spores was performed using a Burkard volumetric spore traps. To establish predicting variables for daily and weakly spore counts, a stepwise multiple regression between spore concentrations and independent variables (meteorological parameters and lagged values from the series of spore concentrations: previous day or week concentration (Alt t - 1) and mean concentration of the same day or week in other years ( C mean)) was made with data obtained during 2009-2011. Alternaria conidia are present throughout the year in the atmosphere of Tetouan, although they show important seasonal fluctuations. The highest levels of Alternaria spores were recorded during the spring and summer or autumn. Alternaria showed maximum daily values in April, May or October depending on year. When the spore variables of Alternaria, namely C mean and Alt t - 1, and meteorological parameters were included in the equation, the resulting R 2 satisfactorily predict future concentrations for 55.5 to 81.6 % during the main spore season and the pre-peak 2. In the predictive model using weekly values, the adjusted R 2 varied from 0.655 to 0.676. The Wilcoxon test was used to compare the results from the expected values and the pre-peak spore data or weekly values for 2012, indicating that there were no significant differences between series compared. This test showed the C mean, Alt t - 1, frequency of the wind third quadrant, maximum wind speed and minimum relative humidity as the most efficient independent variables to forecast the overall trend of this spore in the air.

Using state variables to model the response of tumour cells to radiation and heat: a novel multi-hit-repair approach.

PubMed

Scheidegger, Stephan; Fuchs, Hans U; Zaugg, Kathrin; Bodis, Stephan; Füchslin, Rudolf M

2013-01-01

In order to overcome the limitations of the linear-quadratic model and include synergistic effects of heat and radiation, a novel radiobiological model is proposed. The model is based on a chain of cell populations which are characterized by the number of radiation induced damages (hits). Cells can shift downward along the chain by collecting hits and upward by a repair process. The repair process is governed by a repair probability which depends upon state variables used for a simplistic description of the impact of heat and radiation upon repair proteins. Based on the parameters used, populations up to 4-5 hits are relevant for the calculation of the survival. The model describes intuitively the mathematical behaviour of apoptotic and nonapoptotic cell death. Linear-quadratic-linear behaviour of the logarithmic cell survival, fractionation, and (with one exception) the dose rate dependencies are described correctly. The model covers the time gap dependence of the synergistic cell killing due to combined application of heat and radiation, but further validation of the proposed approach based on experimental data is needed. However, the model offers a work bench for testing different biological concepts of damage induction, repair, and statistical approaches for calculating the variables of state.

Variability in colonization of arbuscular mycorrhizal fungi and its effect on mycorrhizal dependency of improved and unimproved soybean cultivars.

PubMed

Salloum, M S; Guzzo, M C; Velazquez, M S; Sagadin, M B; Luna, C M

2016-12-01

Breeding selection of germplasm under fertilized conditions may reduce the frequency of genes that promote mycorrhizal associations. This study was developed to compare variability in mycorrhizal colonization and its effect on mycorrhizal dependency (MD) in improved soybean genotypes (I-1 and I-2) with differential tolerance to drought stress, and in unimproved soybean genotypes (UI-3 and UI-4). As inoculum, a mixed native arbuscular mycorrhizal fungi (AMF) was isolated from soybean roots, showing spores mostly of the species Funneliformis mosseae. At 20 days, unimproved genotypes followed by I-2, showed an increase in arbuscule formation, but not in I-1. At 40 days, mycorrhizal plants showed an increase in nodulation, this effect being more evident in unimproved genotypes. Mycorrhizal dependency, evaluated as growth and biochemical parameters from oxidative stress was increased in unimproved and I-2 since 20 days, whereas in I-1, MD increased at 40 days. We cannot distinguish significant differences in AMF colonization and MD between unimproved and I-2. However, variability among improved genotypes was observed. Our results suggest that selection for improved soybean genotypes with good and rapid AMF colonization, particularly high arbuscule/hyphae ratio could be a useful strategy for the development of genotypes that optimize AMF contribution to cropping systems.

A method for predicting optimized processing parameters for surfacing

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

Dupont, J.N.; Marder, A.R.

1994-12-31

Welding is used extensively for surfacing applications. To operate a surfacing process efficiently, the variables must be optimized to produce low levels of dilution with the substrate while maintaining high deposition rates. An equation for dilution in terms of the welding variables, thermal efficiency factors, and thermophysical properties of the overlay and substrate was developed by balancing energy and mass terms across the welding arc. To test the validity of the resultant dilution equation, the PAW, GTAW, GMAW, and SAW processes were used to deposit austenitic stainless steel onto carbon steel over a wide range of parameters. Arc efficiency measurementsmore » were conducted using a Seebeck arc welding calorimeter. Melting efficiency was determined based on knowledge of the arc efficiency. Dilution was determined for each set of processing parameters using a quantitative image analysis system. The pertinent equations indicate dilution is a function of arc power (corrected for arc efficiency), filler metal feed rate, melting efficiency, and thermophysical properties of the overlay and substrate. With the aid of the dilution equation, the effect of processing parameters on dilution is presented by a new processing diagram. A new method is proposed for determining dilution from welding variables. Dilution is shown to depend on the arc power, filler metal feed rate, arc and melting efficiency, and the thermophysical properties of the overlay and substrate. Calculated dilution levels were compared with measured values over a large range of processing parameters and good agreement was obtained. The results have been applied to generate a processing diagram which can be used to: (1) predict the maximum deposition rate for a given arc power while maintaining adequate fusion with the substrate, and (2) predict the resultant level of dilution with the substrate.« less

Spectral Kernel Approach to Study Radiative Response of Climate Variables and Interannual Variability of Reflected Solar Spectrum

NASA Technical Reports Server (NTRS)

Jin, Zhonghai; Wielicki, Bruce A.; Loukachine, Constantin; Charlock, Thomas P.; Young, David; Noeel, Stefan

2011-01-01

The radiative kernel approach provides a simple way to separate the radiative response to different climate parameters and to decompose the feedback into radiative and climate response components. Using CERES/MODIS/Geostationary data, we calculated and analyzed the solar spectral reflectance kernels for various climate parameters on zonal, regional, and global spatial scales. The kernel linearity is tested. Errors in the kernel due to nonlinearity can vary strongly depending on climate parameter, wavelength, surface, and solar elevation; they are large in some absorption bands for some parameters but are negligible in most conditions. The spectral kernels are used to calculate the radiative responses to different climate parameter changes in different latitudes. The results show that the radiative response in high latitudes is sensitive to the coverage of snow and sea ice. The radiative response in low latitudes is contributed mainly by cloud property changes, especially cloud fraction and optical depth. The large cloud height effect is confined to absorption bands, while the cloud particle size effect is found mainly in the near infrared. The kernel approach, which is based on calculations using CERES retrievals, is then tested by direct comparison with spectral measurements from Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) (a different instrument on a different spacecraft). The monthly mean interannual variability of spectral reflectance based on the kernel technique is consistent with satellite observations over the ocean, but not over land, where both model and data have large uncertainty. RMS errors in kernel ]derived monthly global mean reflectance over the ocean compared to observations are about 0.001, and the sampling error is likely a major component.

Compensation for Lithography Induced Process Variations during Physical Design

NASA Astrophysics Data System (ADS)

Chin, Eric Yiow-Bing

This dissertation addresses the challenge of designing robust integrated circuits in the deep sub micron regime in the presence of lithography process variability. By extending and combining existing process and circuit analysis techniques, flexible software frameworks are developed to provide detailed studies of circuit performance in the presence of lithography variations such as focus and exposure. Applications of these software frameworks to select circuits demonstrate the electrical impact of these variations and provide insight into variability aware compact models that capture the process dependent circuit behavior. These variability aware timing models abstract lithography variability from the process level to the circuit level and are used to estimate path level circuit performance with high accuracy with very little overhead in runtime. The Interconnect Variability Characterization (IVC) framework maps lithography induced geometrical variations at the interconnect level to electrical delay variations. This framework is applied to one dimensional repeater circuits patterned with both 90nm single patterning and 32nm double patterning technologies, under the presence of focus, exposure, and overlay variability. Studies indicate that single and double patterning layouts generally exhibit small variations in delay (between 1--3%) due to self compensating RC effects associated with dense layouts and overlay errors for layouts without self-compensating RC effects. The delay response of each double patterned interconnect structure is fit with a second order polynomial model with focus, exposure, and misalignment parameters with 12 coefficients and residuals of less than 0.1ps. The IVC framework is also applied to a repeater circuit with cascaded interconnect structures to emulate more complex layout scenarios, and it is observed that the variations on each segment average out to reduce the overall delay variation. The Standard Cell Variability Characterization (SCVC) framework advances existing layout-level lithography aware circuit analysis by extending it to cell-level applications utilizing a physically accurate approach that integrates process simulation, compact transistor models, and circuit simulation to characterize electrical cell behavior. This framework is applied to combinational and sequential cells in the Nangate 45nm Open Cell Library, and the timing response of these cells to lithography focus and exposure variations demonstrate Bossung like behavior. This behavior permits the process parameter dependent response to be captured in a nine term variability aware compact model based on Bossung fitting equations. For a two input NAND gate, the variability aware compact model captures the simulated response to an accuracy of 0.3%. The SCVC framework is also applied to investigate advanced process effects including misalignment and layout proximity. The abstraction of process variability from the layout level to the cell level opens up an entire new realm of circuit analysis and optimization and provides a foundation for path level variability analysis without the computationally expensive costs associated with joint process and circuit simulation. The SCVC framework is used with slight modification to illustrate the speedup and accuracy tradeoffs of using compact models. With variability aware compact models, the process dependent performance of a three stage logic circuit can be estimated to an accuracy of 0.7% with a speedup of over 50,000. Path level variability analysis also provides an accurate estimate (within 1%) of ring oscillator period in well under a second. Another significant advantage of variability aware compact models is that they can be easily incorporated into existing design methodologies for design optimization. This is demonstrated by applying cell swapping on a logic circuit to reduce the overall delay variability along a circuit path. By including these variability aware compact models in cell characterization libraries, design metrics such as circuit timing, power, area, and delay variability can be quickly assessed to optimize for the correct balance of all design metrics, including delay variability. Deterministic lithography variations can be easily captured using the variability aware compact models described in this dissertation. However, another prominent source of variability is random dopant fluctuations, which affect transistor threshold voltage and in turn circuit performance. The SCVC framework is utilized to investigate the interactions between deterministic lithography variations and random dopant fluctuations. Monte Carlo studies show that the output delay distribution in the presence of random dopant fluctuations is dependent on lithography focus and exposure conditions, with a 3.6 ps change in standard deviation across the focus exposure process window. This indicates that the electrical impact of random variations is dependent on systematic lithography variations, and this dependency should be included for precise analysis.

Soil and vegetation parameter uncertainty on future terrestrial carbon sinks

NASA Astrophysics Data System (ADS)

Kothavala, Z.; Felzer, B. S.

2013-12-01

We examine the role of the terrestrial carbon cycle in a changing climate at the centennial scale using an intermediate complexity Earth system climate model that includes the effects of dynamic vegetation and the global carbon cycle. We present a series of ensemble simulations to evaluate the sensitivity of simulated terrestrial carbon sinks to three key model parameters: (a) The temperature dependence of soil carbon decomposition, (b) the upper temperature limits on the rate of photosynthesis, and (c) the nitrogen limitation of the maximum rate of carboxylation of Rubisco. We integrated the model in fully coupled mode for a 1200-year spin-up period, followed by a 300-year transient simulation starting at year 1800. Ensemble simulations were conducted varying each parameter individually and in combination with other variables. The results of the transient simulations show that terrestrial carbon uptake is very sensitive to the choice of model parameters. Changes in net primary productivity were most sensitive to the upper temperature limit on the rate of photosynthesis, which also had a dominant effect on overall land carbon trends; this is consistent with previous research that has shown the importance of climatic suppression of photosynthesis as a driver of carbon-climate feedbacks. Soil carbon generally decreased with increasing temperature, though the magnitude of this trend depends on both the net primary productivity changes and the temperature dependence of soil carbon decomposition. Vegetation carbon increased in some simulations, but this was not consistent across all configurations of model parameters. Comparing to global carbon budget observations, we identify the subset of model parameters which are consistent with observed carbon sinks; this serves to narrow considerably the future model projections of terrestrial carbon sink changes in comparison with the full model ensemble.

Internal state variable approach for predicting stiffness reductions in fibrous laminated composites with matrix cracks

NASA Technical Reports Server (NTRS)

Lee, Jong-Won; Allen, D. H.; Harris, C. E.

1989-01-01

A mathematical model utilizing the internal state variable concept is proposed for predicting the upper bound of the reduced axial stiffnesses in cross-ply laminates with matrix cracks. The axial crack opening displacement is explicitly expressed in terms of the observable axial strain and the undamaged material properties. A crack parameter representing the effect of matrix cracks on the observable axial Young's modulus is calculated for glass/epoxy and graphite/epoxy material systems. The results show that the matrix crack opening displacement and the effective Young's modulus depend not on the crack length, but on its ratio to the crack spacing.

Reduction of Energy Consumption for Air Conditioning While Maintaining Acceptable Human Comfort.

DTIC Science & Technology

1988-04-01

Fanger, 1972). It is not always possible, or, practical, to obtain optimi thermal comfort conditions. Therefore Frofessor Fanger devised an index to...understand the complex interaction of the six key variables that affect human comfort. Thermal comfort is not exclusively a function of air temperature... Thermal comfort also depends on five other, less obvious, parameters: mean radiant temperature, relative air velocity, humidity, activity level, and

Proposed Test of Relative Phase as Hidden Variable in Quantum Mechanics

DTIC Science & Technology

2012-01-01

implicitly due to its ubiquity in quantum theory , but searches for dependence of measurement outcome on other parameters have been lacking. For a two -state...implemen- tation for the specific case of an atomic two -state system with laser-induced fluores- cence for measurement. Keywords Quantum measurement...Measurement postulate · Born rule 1 Introduction 1.1 Problems with Quantum Measurement Quantum theory prescribes probabilities for outcomes of measurements

Predicting seasonal influenza transmission using functional regression models with temporal dependence.

PubMed

Oviedo de la Fuente, Manuel; Febrero-Bande, Manuel; Muñoz, María Pilar; Domínguez, Àngela

2018-01-01

This paper proposes a novel approach that uses meteorological information to predict the incidence of influenza in Galicia (Spain). It extends the Generalized Least Squares (GLS) methods in the multivariate framework to functional regression models with dependent errors. These kinds of models are useful when the recent history of the incidence of influenza are readily unavailable (for instance, by delays on the communication with health informants) and the prediction must be constructed by correcting the temporal dependence of the residuals and using more accessible variables. A simulation study shows that the GLS estimators render better estimations of the parameters associated with the regression model than they do with the classical models. They obtain extremely good results from the predictive point of view and are competitive with the classical time series approach for the incidence of influenza. An iterative version of the GLS estimator (called iGLS) was also proposed that can help to model complicated dependence structures. For constructing the model, the distance correlation measure [Formula: see text] was employed to select relevant information to predict influenza rate mixing multivariate and functional variables. These kinds of models are extremely useful to health managers in allocating resources in advance to manage influenza epidemics.

Manipulations of the features of standard video lottery terminal (VLT) games: effects in pathological and non-pathological gamblers.

PubMed

Loba, P; Stewart, S H; Klein, R M; Blackburn, J R

2001-01-01

The present study was conducted to identify game parameters that would reduce the risk of abuse of video lottery terminals (VLTs) by pathological gamblers, while exerting minimal effects on the behavior of non-pathological gamblers. Three manipulations of standard VLT game features were explored. Participants were exposed to: a counter which displayed a running total of money spent; a VLT spinning reels game where participants could no longer "stop" the reels by touching the screen; and sensory feature manipulations. In control conditions, participants were exposed to standard settings for either a spinning reels or a video poker game. Dependent variables were self-ratings of reactions to each set of parameters. A set of 2(3) x 2 x 2 (game manipulation [experimental condition(s) vs. control condition] x game [spinning reels vs. video poker] x gambler status [pathological vs. non-pathological]) repeated measures ANOVAs were conducted on all dependent variables. The findings suggest that the sensory manipulations (i.e., fast speed/sound or slow speed/no sound manipulations) produced the most robust reaction differences. Before advocating harm reduction policies such as lowering sensory features of VLT games to reduce potential harm to pathological gamblers, it is important to replicate findings in a more naturalistic setting, such as a real bar.

General Multimechanism Reversible-Irreversible Time-Dependent Constitutive Deformation Model Being Developed

NASA Technical Reports Server (NTRS)

Saleeb, A. F.; Arnold, Steven M.

2001-01-01

Since most advanced material systems (for example metallic-, polymer-, and ceramic-based systems) being currently researched and evaluated are for high-temperature airframe and propulsion system applications, the required constitutive models must account for both reversible and irreversible time-dependent deformations. Furthermore, since an integral part of continuum-based computational methodologies (be they microscale- or macroscale-based) is an accurate and computationally efficient constitutive model to describe the deformation behavior of the materials of interest, extensive research efforts have been made over the years on the phenomenological representations of constitutive material behavior in the inelastic analysis of structures. From a more recent and comprehensive perspective, the NASA Glenn Research Center in conjunction with the University of Akron has emphasized concurrently addressing three important and related areas: that is, 1) Mathematical formulation; 2) Algorithmic developments for updating (integrating) the external (e.g., stress) and internal state variables; 3) Parameter estimation for characterizing the model. This concurrent perspective to constitutive modeling has enabled the overcoming of the two major obstacles to fully utilizing these sophisticated time-dependent (hereditary) constitutive models in practical engineering analysis. These obstacles are: 1) Lack of efficient and robust integration algorithms; 2) Difficulties associated with characterizing the large number of required material parameters, particularly when many of these parameters lack obvious or direct physical interpretations.

Recognition of speech in noise after application of time-frequency masks: Dependence on frequency and threshold parameters

PubMed Central

Sinex, Donal G.

2013-01-01

Binary time-frequency (TF) masks can be applied to separate speech from noise. Previous studies have shown that with appropriate parameters, ideal TF masks can extract highly intelligible speech even at very low speech-to-noise ratios (SNRs). Two psychophysical experiments provided additional information about the dependence of intelligibility on the frequency resolution and threshold criteria that define the ideal TF mask. Listeners identified AzBio Sentences in noise, before and after application of TF masks. Masks generated with 8 or 16 frequency bands per octave supported nearly-perfect identification. Word recognition accuracy was slightly lower and more variable with 4 bands per octave. When TF masks were generated with a local threshold criterion of 0 dB SNR, the mean speech reception threshold was −9.5 dB SNR, compared to −5.7 dB for unprocessed sentences in noise. Speech reception thresholds decreased by about 1 dB per dB of additional decrease in the local threshold criterion. Information reported here about the dependence of speech intelligibility on frequency and level parameters has relevance for the development of non-ideal TF masks for clinical applications such as speech processing for hearing aids. PMID:23556604

Probabilistic durability assessment of concrete structures in marine environments: Reliability and sensitivity analysis

NASA Astrophysics Data System (ADS)

Yu, Bo; Ning, Chao-lie; Li, Bing

2017-03-01

A probabilistic framework for durability assessment of concrete structures in marine environments was proposed in terms of reliability and sensitivity analysis, which takes into account the uncertainties under the environmental, material, structural and executional conditions. A time-dependent probabilistic model of chloride ingress was established first to consider the variations in various governing parameters, such as the chloride concentration, chloride diffusion coefficient, and age factor. Then the Nataf transformation was adopted to transform the non-normal random variables from the original physical space into the independent standard Normal space. After that the durability limit state function and its gradient vector with respect to the original physical parameters were derived analytically, based on which the first-order reliability method was adopted to analyze the time-dependent reliability and parametric sensitivity of concrete structures in marine environments. The accuracy of the proposed method was verified by comparing with the second-order reliability method and the Monte Carlo simulation. Finally, the influences of environmental conditions, material properties, structural parameters and execution conditions on the time-dependent reliability of concrete structures in marine environments were also investigated. The proposed probabilistic framework can be implemented in the decision-making algorithm for the maintenance and repair of deteriorating concrete structures in marine environments.

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

Post, Wilfred M; King, Anthony Wayne; Dragoni, Danilo

Many parameters in terrestrial biogeochemical models are inherently uncertain, leading to uncertainty in predictions of key carbon cycle variables. At observation sites, this uncertainty can be quantified by applying model-data fusion techniques to estimate model parameters using eddy covariance observations and associated biometric data sets as constraints. Uncertainty is reduced as data records become longer and different types of observations are added. We estimate parametric and associated predictive uncertainty at the Morgan Monroe State Forest in Indiana, USA. Parameters in the Local Terrestrial Ecosystem Carbon (LoTEC) are estimated using both synthetic and actual constraints. These model parameters and uncertainties aremore » then used to make predictions of carbon flux for up to 20 years. We find a strong dependence of both parametric and prediction uncertainty on the length of the data record used in the model-data fusion. In this model framework, this dependence is strongly reduced as the data record length increases beyond 5 years. If synthetic initial biomass pool constraints with realistic uncertainties are included in the model-data fusion, prediction uncertainty is reduced by more than 25% when constraining flux records are less than 3 years. If synthetic annual aboveground woody biomass increment constraints are also included, uncertainty is similarly reduced by an additional 25%. When actual observed eddy covariance data are used as constraints, there is still a strong dependence of parameter and prediction uncertainty on data record length, but the results are harder to interpret because of the inability of LoTEC to reproduce observed interannual variations and the confounding effects of model structural error.« less

Validation of the alternating conditional estimation algorithm for estimation of flexible extensions of Cox's proportional hazards model with nonlinear constraints on the parameters.

PubMed

Wynant, Willy; Abrahamowicz, Michal

2016-11-01

Standard optimization algorithms for maximizing likelihood may not be applicable to the estimation of those flexible multivariable models that are nonlinear in their parameters. For applications where the model's structure permits separating estimation of mutually exclusive subsets of parameters into distinct steps, we propose the alternating conditional estimation (ACE) algorithm. We validate the algorithm, in simulations, for estimation of two flexible extensions of Cox's proportional hazards model where the standard maximum partial likelihood estimation does not apply, with simultaneous modeling of (1) nonlinear and time-dependent effects of continuous covariates on the hazard, and (2) nonlinear interaction and main effects of the same variable. We also apply the algorithm in real-life analyses to estimate nonlinear and time-dependent effects of prognostic factors for mortality in colon cancer. Analyses of both simulated and real-life data illustrate good statistical properties of the ACE algorithm and its ability to yield new potentially useful insights about the data structure. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Optimization of design and operating parameters of a space-based optical-electronic system with a distributed aperture.

PubMed

Tcherniavski, Iouri; Kahrizi, Mojtaba

2008-11-20

Using a gradient optimization method with objective functions formulated in terms of a signal-to-noise ratio (SNR) calculated at given values of the prescribed spatial ground resolution, optimization problems of geometrical parameters of a distributed optical system and a charge-coupled device of a space-based optical-electronic system are solved for samples of the optical systems consisting of two and three annular subapertures. The modulation transfer function (MTF) of the distributed aperture is expressed in terms of an average MTF taking residual image alignment (IA) and optical path difference (OPD) errors into account. The results show optimal solutions of the optimization problems depending on diverse variable parameters. The information on the magnitudes of the SNR can be used to determine the number of the subapertures and their sizes, while the information on the SNR decrease depending on the IA and OPD errors can be useful in design of a beam combination control system to produce the necessary requirements to its accuracy on the basis of the permissible deterioration in the image quality.

Global Weirding? - Using Very Large Ensembles and Extreme Value Theory to assess Changes in Extreme Weather Events Today

NASA Astrophysics Data System (ADS)

Otto, F. E. L.; Mitchell, D.; Sippel, S.; Black, M. T.; Dittus, A. J.; Harrington, L. J.; Mohd Saleh, N. H.

2014-12-01

A shift in the distribution of socially-relevant climate variables such as daily minimum winter temperatures and daily precipitation extremes, has been attributed to anthropogenic climate change for various mid-latitude regions. However, while there are many process-based arguments suggesting also a change in the shape of these distributions, attribution studies demonstrating this have not currently been undertaken. Here we use a very large initial condition ensemble of ~40,000 members simulating the European winter 2013/2014 using the distributed computing infrastructure under the weather@home project. Two separate scenarios are used:1. current climate conditions, and 2. a counterfactual scenario of "world that might have been" without anthropogenic forcing. Specifically focusing on extreme events, we assess how the estimated parameters of the Generalized Extreme Value (GEV) distribution vary depending on variable-type, sampling frequency (daily, monthly, …) and geographical region. We find that the location parameter changes for most variables but, depending on the region and variables, we also find significant changes in scale and shape parameters. The very large ensemble allows, furthermore, to assess whether such findings in the fitted GEV distributions are consistent with an empirical analysis of the model data, and whether the most extreme data still follow a known underlying distribution that in a small sample size might otherwise be thought of as an out-lier. The ~40,000 member ensemble is simulated using 12 different SST patterns (1 'observed', and 11 best guesses of SSTs with no anthropogenic warming). The range in SSTs, along with the corresponding changings in the NAO and high-latitude blocking inform on the dynamics governing some of these extreme events. While strong tele-connection patterns are not found in this particular experiment, the high number of simulated extreme events allows for a more thorough analysis of the dynamics than has been performed before. Therefore, combining extreme value theory with very large ensemble simulations allows us to understand the dynamics of changes in extreme events which is not possible just using the former but also shows in which cases statistics combined with smaller ensembles give as valid results as very large initial conditions.

Solar Coronal and photospheric abundances from solar energetic particle measurements

NASA Technical Reports Server (NTRS)

Breneman, H.; Stone, E. C.

1985-01-01

Solar energetic particle (SEP) elemental abundance data from the cosmic ray subsystem (CRS) aboard the Voyager 1 and 2 spacecraft are used to derive unfractionated coronal and photospheric abundances for elements with 3 Z or = 30. It is found that the ionic charge-to-mass ratio (Q/M) is the principal organizing parameter for the fractionation of SEPs by acceleration and propagation processes and for flare-to-flare variability, making possible a single-parameter Q/M-dependent correction to the average SEP abundances to obtain unfractionated coronal abundances. A further correction based on first ionization potential allows the determination of unfractionated photospheric abundances.

The Simpsons program 6-D phase space tracking with acceleration

NASA Astrophysics Data System (ADS)

Machida, S.

1993-12-01

A particle tracking code, Simpsons, in 6-D phase space including energy ramping has been developed to model proton synchrotrons and storage rings. We take time as the independent variable to change machine parameters and diagnose beam quality in a quite similar way as real machines, unlike existing tracking codes for synchrotrons which advance a particle element by element. Arbitrary energy ramping and rf voltage curves as a function of time are read as an input file for defining a machine cycle. The code is used to study beam dynamics with time dependent parameters. Some of the examples from simulations of the Superconducting Super Collider (SSC) boosters are shown.

Solar coronal and photospheric abundances from solar energetic particle measurements

NASA Technical Reports Server (NTRS)

Breneman, H. H.; Stone, E. C.

1985-01-01

Solar energetic particle (SEP) elemental abundance data from the cosmic ray subsystem (CRS) aboard the Voyager 1 and 2 spacecraft are used to derive unfractionated coronal and photospheric abundances for elements with Z = 6-30. It is found that the ionic charge-to-mass ratio (Q/M) is the principal organizing parameter for the fractionation of SEPs by acceleration and propagation processes and for flare-to-flare variability, making possible a single-parameter Q/M-dependent correction to the average SEP abundances to obtain unfractionated coronal abundances. A further correction based on first ionization potential allows the determination of unfractionated photospheric abundances.

Variability Analysis of MOS Differential Amplifier

NASA Astrophysics Data System (ADS)

Aoki, Masakazu; Seto, Kenji; Yamawaki, Taizo; Tanaka, Satoshi

Variation characteristics in MOS differential amplifier are evaluated by using the concise statistical model parameters for SPICE simulation. We find that the variation in the differential-mode gain, Adm, induced by the current factor variation, Δβ0, in the Id-variation of the differential MOS transistors is more than one order of magnitude larger than that induced by the threshold voltage variation, ΔVth, which has been regarded as a major factor for circuit variations in SoC's (2). The results obtained by the Monte Carlo simulations are verified by the theoretical analysis combined with the sensitivity analysis which clarifies the specific device parameter dependences of the variation in Adm.

Oxidative stress biomarker monitoring in elite women volleyball athletes during a 6-week training period.

PubMed

Martinović, Jelena; Dopsaj, Violeta; Kotur-Stevuljević, Jelena; Dopsaj, Milivoj; Vujović, Ana; Stefanović, Aleksandra; Nešić, Goran

2011-05-01

The objectives of this study were to determine (a) if reactive oxygen metabolites (ROMs) are a reliable parameter for monitoring oxidative stress in athletes alone or in association with other parameters of oxidative stress and depending on whether antioxidant supplements are taken or not; (b) the level of oxidative stress in athletes before the competition season; and (c) if oxidative status could be improved in volleyball athletes. Sixteen women athletes (supplemented group) received an antioxidant cocktail containing vitamin E, vitamin C, zinc gluconate, and selenium as a dietary supplement during a 6-week training period, whereas 12 of them (control group) received no dietary supplement. Blood samples were taken before and after the training period. The following parameters were measured: ROMs, superoxide anion (O2⁻₂), malondialdehyde (MDA), advanced oxidation protein products (AOPP), lipid hydroperoxide (LOOH), biological antioxidative potential (BAP), paraoxonase activity toward paraoxon (POase) and diazoxon (DZOase), superoxide dismutase(SOD), total sulfydryl group concentration (SH groups), and lipid status. Reactive oxygen metabolites were taken as the dependent variable and MDA, O2⁻₂, AOPP, and LOOH as independent variables. In the group of athletes who have received supplementation, linear regression analysis revealed that the implemented model had a lower influence on dROMs (70.4 vs. 27.9%) after the training period. The general linear model showed significant differences between parameters before and after training/supplementation (Wilks' lambda = 0.074, F = 11.76, p < 0.01). At the partial level, significant increases in ROM levels (p <0.05, 95% confidence interval [CI]: 286-337), SOD activity (CI: 113-144), and BAP (CI: 2,388-2,580) (p < 0.01) were observed. The association between ROMs and other parameters of oxidative stress was reduced in athletes who received supplements. During the precompetition training period, treatment with dietary supplements prevented the depletion of antioxidative defense in volleyball athletes.

Using genetic algorithms to optimize the analogue method for precipitation prediction in the Swiss Alps

NASA Astrophysics Data System (ADS)

Horton, Pascal; Jaboyedoff, Michel; Obled, Charles

2018-01-01

Analogue methods provide a statistical precipitation prediction based on synoptic predictors supplied by general circulation models or numerical weather prediction models. The method samples a selection of days in the archives that are similar to the target day to be predicted, and consider their set of corresponding observed precipitation (the predictand) as the conditional distribution for the target day. The relationship between the predictors and predictands relies on some parameters that characterize how and where the similarity between two atmospheric situations is defined. This relationship is usually established by a semi-automatic sequential procedure that has strong limitations: (i) it cannot automatically choose the pressure levels and temporal windows (hour of the day) for a given meteorological variable, (ii) it cannot handle dependencies between parameters, and (iii) it cannot easily handle new degrees of freedom. In this work, a global optimization approach relying on genetic algorithms could optimize all parameters jointly and automatically. The global optimization was applied to some variants of the analogue method for the Rhône catchment in the Swiss Alps. The performance scores increased compared to reference methods, especially for days with high precipitation totals. The resulting parameters were found to be relevant and coherent between the different subregions of the catchment. Moreover, they were obtained automatically and objectively, which reduces the effort that needs to be invested in exploration attempts when adapting the method to a new region or for a new predictand. For example, it obviates the need to assess a large number of combinations of pressure levels and temporal windows of predictor variables that were manually selected beforehand. The optimization could also take into account parameter inter-dependencies. In addition, the approach allowed for new degrees of freedom, such as a possible weighting between pressure levels, and non-overlapping spatial windows.

Seasonal dependence of the "forecast parameter" based on the EIA characteristics for the prediction of Equatorial Spread F (ESF)

NASA Astrophysics Data System (ADS)

Thampi, S. V.; Ravindran, S.; Pant, T. K.; Devasia, C. V.; Sridharan, R.

2008-06-01

In an earlier study, Thampi et al. (2006) have shown that the strength and asymmetry of Equatorial Ionization Anomaly (EIA), obtained well ahead of the onset time of Equatorial Spread F (ESF) have a definite role on the subsequent ESF activity, and a new "forecast parameter" has been identified for the prediction of ESF. This paper presents the observations of EIA strength and asymmetry from the Indian longitudes during the period from August 2005 March 2007. These observations are made using the line of sight Total Electron Content (TEC) measured by a ground-based beacon receiver located at Trivandrum (8.5° N, 77° E, 0.5° N dip lat) in India. It is seen that the seasonal variability of EIA strength and asymmetry are manifested in the latitudinal gradients obtained using the relative TEC measurements. As a consequence, the "forecast parameter" also displays a definite seasonal pattern. The seasonal variability of the EIA strength and asymmetry, and the "forecast parameter" are discussed in the present paper and a critical value for has been identified for each month/season. The likely "skill factor" of the new parameter is assessed using the data for a total of 122 days, and it is seen that when the estimated value of the "forecast parameter" exceeds the critical value, the ESF is seen to occur on more than 95% of cases.

Demonstration and evaluation of a method for assessing mediated moderation.

PubMed

Morgan-Lopez, Antonio A; MacKinnon, David P

2006-02-01

Mediated moderation occurs when the interaction between two variables affects a mediator, which then affects a dependent variable. In this article, we describe the mediated moderation model and evaluate it with a statistical simulation using an adaptation of product-of-coefficients methods to assess mediation. We also demonstrate the use of this method with a substantive example from the adolescent tobacco literature. In the simulation, relative bias (RB) in point estimates and standard errors did not exceed problematic levels of +/- 10% although systematic variability in RB was accounted for by parameter size, sample size, and nonzero direct effects. Power to detect mediated moderation effects appears to be severely compromised under one particular combination of conditions: when the component variables that make up the interaction terms are correlated and partial mediated moderation exists. Implications for the estimation of mediated moderation effects in experimental and nonexperimental research are discussed.

Micro-Macro Duality and Space-Time Emergence

NASA Astrophysics Data System (ADS)

Ojima, Izumi

2011-03-01

The microscopic origin of space-time geometry is explained on the basis of an emergence process associated with the condensation of infinite number of microscopic quanta responsible for symmetry breakdown, which implements the basic essence of "Quantum-Classical Correspondence" and of the forcing method in physical and mathematical contexts, respectively. From this viewpoint, the space-time dependence of physical quantities arises from the "logical extension" [8] to change "constant objects" into "variable objects" by tagging the order parameters associated with the condensation onto "constant objects"; the logical direction here from a value y to a domain variable x (to materialize the basic mechanism behind the Gel'fand isomorphism) is just opposite to that common in the usual definition of a function ƒ : x⟼ƒ(x) from its domain variable x to a value y = ƒ(x).

Visualization of Global Sensitivity Analysis Results Based on a Combination of Linearly Dependent and Independent Directions

NASA Technical Reports Server (NTRS)

Davies, Misty D.; Gundy-Burlet, Karen

2010-01-01

A useful technique for the validation and verification of complex flight systems is Monte Carlo Filtering -- a global sensitivity analysis that tries to find the inputs and ranges that are most likely to lead to a subset of the outputs. A thorough exploration of the parameter space for complex integrated systems may require thousands of experiments and hundreds of controlled and measured variables. Tools for analyzing this space often have limitations caused by the numerical problems associated with high dimensionality and caused by the assumption of independence of all of the dimensions. To combat both of these limitations, we propose a technique that uses a combination of the original variables with the derived variables obtained during a principal component analysis.

Spray-drying nanocapsules in presence of colloidal silica as drying auxiliary agent: formulation and process variables optimization using experimental designs.

PubMed

Tewa-Tagne, Patrice; Degobert, Ghania; Briançon, Stéphanie; Bordes, Claire; Gauvrit, Jean-Yves; Lanteri, Pierre; Fessi, Hatem

2007-04-01

Spray-drying process was used for the development of dried polymeric nanocapsules. The purpose of this research was to investigate the effects of formulation and process variables on the resulting powder characteristics in order to optimize them. Experimental designs were used in order to estimate the influence of formulation parameters (nanocapsules and silica concentrations) and process variables (inlet temperature, spray-flow air, feed flow rate and drying air flow rate) on spray-dried nanocapsules when using silica as drying auxiliary agent. The interactions among the formulation parameters and process variables were also studied. Responses analyzed for computing these effects and interactions were outlet temperature, moisture content, operation yield, particles size, and particulate density. Additional qualitative responses (particles morphology, powder behavior) were also considered. Nanocapsules and silica concentrations were the main factors influencing the yield, particulate density and particle size. In addition, they were concerned for the only significant interactions occurring among two different variables. None of the studied variables had major effect on the moisture content while the interaction between nanocapsules and silica in the feed was of first interest and determinant for both the qualitative and quantitative responses. The particles morphology depended on the feed formulation but was unaffected by the process conditions. This study demonstrated that drying nanocapsules using silica as auxiliary agent by spray drying process enables the obtaining of dried micronic particle size. The optimization of the process and the formulation variables resulted in a considerable improvement of product yield while minimizing the moisture content.

Inter-Annual Variability of Fledgling Sex Ratio in King Penguins.

PubMed

Bordier, Célia; Saraux, Claire; Viblanc, Vincent A; Gachot-Neveu, Hélène; Beaugey, Magali; Le Maho, Yvon; Le Bohec, Céline

2014-01-01

As the number of breeding pairs depends on the adult sex ratio in a monogamous species with biparental care, investigating sex-ratio variability in natural populations is essential to understand population dynamics. Using 10 years of data (2000-2009) in a seasonally monogamous seabird, the king penguin (Aptenodytes patagonicus), we investigated the annual sex ratio at fledging, and the potential environmental causes for its variation. Over more than 4000 birds, the annual sex ratio at fledging was highly variable (ranging from 44.4% to 58.3% of males), and on average slightly biased towards males (51.6%). Yearly variation in sex-ratio bias was neither related to density within the colony, nor to global or local oceanographic conditions known to affect both the productivity and accessibility of penguin foraging areas. However, rising sea surface temperature coincided with an increase in fledging sex-ratio variability. Fledging sex ratio was also correlated with difference in body condition between male and female fledglings. When more males were produced in a given year, their body condition was higher (and reciprocally), suggesting that parents might adopt a sex-biased allocation strategy depending on yearly environmental conditions and/or that the effect of environmental parameters on chick condition and survival may be sex-dependent. The initial bias in sex ratio observed at the juvenile stage tended to return to 1∶1 equilibrium upon first breeding attempts, as would be expected from Fisher's classic theory of offspring sex-ratio variation.

Combined model of intrinsic and extrinsic variability for computational network design with application to synthetic biology.

PubMed

Toni, Tina; Tidor, Bruce

2013-01-01

Biological systems are inherently variable, with their dynamics influenced by intrinsic and extrinsic sources. These systems are often only partially characterized, with large uncertainties about specific sources of extrinsic variability and biochemical properties. Moreover, it is not yet well understood how different sources of variability combine and affect biological systems in concert. To successfully design biomedical therapies or synthetic circuits with robust performance, it is crucial to account for uncertainty and effects of variability. Here we introduce an efficient modeling and simulation framework to study systems that are simultaneously subject to multiple sources of variability, and apply it to make design decisions on small genetic networks that play a role of basic design elements of synthetic circuits. Specifically, the framework was used to explore the effect of transcriptional and post-transcriptional autoregulation on fluctuations in protein expression in simple genetic networks. We found that autoregulation could either suppress or increase the output variability, depending on specific noise sources and network parameters. We showed that transcriptional autoregulation was more successful than post-transcriptional in suppressing variability across a wide range of intrinsic and extrinsic magnitudes and sources. We derived the following design principles to guide the design of circuits that best suppress variability: (i) high protein cooperativity and low miRNA cooperativity, (ii) imperfect complementarity between miRNA and mRNA was preferred to perfect complementarity, and (iii) correlated expression of mRNA and miRNA--for example, on the same transcript--was best for suppression of protein variability. Results further showed that correlations in kinetic parameters between cells affected the ability to suppress variability, and that variability in transient states did not necessarily follow the same principles as variability in the steady state. Our model and findings provide a general framework to guide design principles in synthetic biology.

Combined Model of Intrinsic and Extrinsic Variability for Computational Network Design with Application to Synthetic Biology

PubMed Central

Toni, Tina; Tidor, Bruce

2013-01-01

Biological systems are inherently variable, with their dynamics influenced by intrinsic and extrinsic sources. These systems are often only partially characterized, with large uncertainties about specific sources of extrinsic variability and biochemical properties. Moreover, it is not yet well understood how different sources of variability combine and affect biological systems in concert. To successfully design biomedical therapies or synthetic circuits with robust performance, it is crucial to account for uncertainty and effects of variability. Here we introduce an efficient modeling and simulation framework to study systems that are simultaneously subject to multiple sources of variability, and apply it to make design decisions on small genetic networks that play a role of basic design elements of synthetic circuits. Specifically, the framework was used to explore the effect of transcriptional and post-transcriptional autoregulation on fluctuations in protein expression in simple genetic networks. We found that autoregulation could either suppress or increase the output variability, depending on specific noise sources and network parameters. We showed that transcriptional autoregulation was more successful than post-transcriptional in suppressing variability across a wide range of intrinsic and extrinsic magnitudes and sources. We derived the following design principles to guide the design of circuits that best suppress variability: (i) high protein cooperativity and low miRNA cooperativity, (ii) imperfect complementarity between miRNA and mRNA was preferred to perfect complementarity, and (iii) correlated expression of mRNA and miRNA – for example, on the same transcript – was best for suppression of protein variability. Results further showed that correlations in kinetic parameters between cells affected the ability to suppress variability, and that variability in transient states did not necessarily follow the same principles as variability in the steady state. Our model and findings provide a general framework to guide design principles in synthetic biology. PMID:23555205

Uncertainty of inhalation dose coefficients for representative physical and chemical forms of iodine-131

NASA Astrophysics Data System (ADS)

Harvey, Richard Paul, III

Releases of radioactive material have occurred at various Department of Energy (DOE) weapons facilities and facilities associated with the nuclear fuel cycle in the generation of electricity. Many different radionuclides have been released to the environment with resulting exposure of the population to these various sources of radioactivity. Radioiodine has been released from a number of these facilities and is a potential public health concern due to its physical and biological characteristics. Iodine exists as various isotopes, but our focus is on 131I due to its relatively long half-life, its prevalence in atmospheric releases and its contribution to offsite dose. The assumption of physical and chemical form is speculated to have a profound impact on the deposition of radioactive material within the respiratory tract. In the case of iodine, it has been shown that more than one type of physical and chemical form may be released to, or exist in, the environment; iodine can exist as a particle or as a gas. The gaseous species can be further segregated based on chemical form: elemental, inorganic, and organic iodides. Chemical compounds in each class are assumed to behave similarly with respect to biochemistry. Studies at Oak Ridge National Laboratories have demonstrated that 131I is released as a particulate, as well as in elemental, inorganic and organic chemical form. The internal dose estimate from 131I may be very different depending on the effect that chemical form has on fractional deposition, gas uptake, and clearance in the respiratory tract. There are many sources of uncertainty in the estimation of environmental dose including source term, airborne transport of radionuclides, and internal dosimetry. Knowledge of uncertainty in internal dosimetry is essential for estimating dose to members of the public and for determining total uncertainty in dose estimation. Important calculational steps in any lung model is regional estimation of deposition fractions and gas uptake of radionuclides in various regions of the lung. Variability in regional radionuclide deposition within lung compartments may significantly contribute to the overall uncertainty of the lung model. The uncertainty of lung deposition and biological clearance is dependent upon physiological and anatomical parameters of individuals as well as characteristic parameters of the particulate material. These parameters introduce uncertainty into internal dose estimates due to their inherent variability. Anatomical and physiological input parameters are age and gender dependent. This work has determined the uncertainty in internal dose estimates and the sensitive parameters involved in modeling particulate deposition and gas uptake of different physical and chemical forms of 131I with age and gender dependencies.

Tack Measurements of Prepreg Tape at Variable Temperature and Humidity

NASA Technical Reports Server (NTRS)

Wohl, Christopher; Palmieri, Frank L.; Forghani, Alireza; Hickmott, Curtis; Bedayat, Houman; Coxon, Brian; Poursartip, Anoush; Grimsley, Brian

2017-01-01

NASA’s Advanced Composites Project has established the goal of achieving a 30 percent reduction in the timeline for certification of primary composite structures for application on commercial aircraft. Prepreg tack is one of several critical parameters affecting composite manufacturing by automated fiber placement (AFP). Tack plays a central role in the prevention of wrinkles and puckers that can occur during AFP, thus knowledge of tack variation arising from a myriad of manufacturing and environmental conditions is imperative for the prediction of defects during AFP. A full design of experiments was performed to experimentally characterize tack on 0.25-inch slit-tape tow IM7/8552-1 prepreg using probe tack testing. Several process parameters (contact force, contact time, retraction speed, and probe diameter) as well as environmental parameters (temperature and humidity) were varied such that the entire parameter space could be efficiently evaluated. Mid-point experimental conditions (i.e., parameters not at either extrema) were included to enable prediction of curvature in relationships and repeat measurements were performed to characterize experimental error. Collectively, these experiments enable determination of primary dependencies as well as multi-parameter relationships. Slit-tape tow samples were mounted to the bottom plate of a rheometer parallel plate fixture using a jig to prevent modification of the active area to be interrogated with the top plate, a polished stainless steel probe, during tack testing. The probe surface was slowly brought into contact with the pre-preg surface until a pre-determined normal force was achieved (2-30 newtons). After a specified dwell time (0.02-10 seconds), during which the probe substrate interaction was maintained under displacement control, the probe was retracted from the surface (0.1-50 millimeters per second). Initial results indicated a clear dependence of tack strength on several parameters, with a particularly strong dependence on temperature and humidity. Although an increase in either of these parameters reduces tack strength, a maximum in tack was predicted to occur under conditions of low temperature and moderate humidity.

Evaluation of the effects of climate and man intervention on ground waters and their dependent ecosystems using time series analysis

NASA Astrophysics Data System (ADS)

Gemitzi, Alexandra; Stefanopoulos, Kyriakos

2011-06-01

SummaryGroundwaters and their dependent ecosystems are affected both by the meteorological conditions as well as from human interventions, mainly in the form of groundwater abstractions for irrigation needs. This work aims at investigating the quantitative effects of meteorological conditions and man intervention on groundwater resources and their dependent ecosystems. Various seasonal Auto-Regressive Integrated Moving Average (ARIMA) models with external predictor variables were used in order to model the influence of meteorological conditions and man intervention on the groundwater level time series. Initially, a seasonal ARIMA model that simulates the abstraction time series using as external predictor variable temperature ( T) was prepared. Thereafter, seasonal ARIMA models were developed in order to simulate groundwater level time series in 8 monitoring locations, using the appropriate predictor variables determined for each individual case. The spatial component was introduced through the use of Geographical Information Systems (GIS). Application of the proposed methodology took place in the Neon Sidirochorion alluvial aquifer (Northern Greece), for which a 7-year long time series (i.e., 2003-2010) of piezometric and groundwater abstraction data exists. According to the developed ARIMA models, three distinct groups of groundwater level time series exist; the first one proves to be dependent only on the meteorological parameters, the second group demonstrates a mixed dependence both on meteorological conditions and on human intervention, whereas the third group shows a clear influence from man intervention. Moreover, there is evidence that groundwater abstraction has affected an important protected ecosystem.

Uncertainty Quantification in Scale-Dependent Models of Flow in Porous Media: SCALE-DEPENDENT UQ

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

Tartakovsky, A. M.; Panzeri, M.; Tartakovsky, G. D.

Equations governing flow and transport in heterogeneous porous media are scale-dependent. We demonstrate that it is possible to identify a support scalemore » $$\\eta^*$$, such that the typically employed approximate formulations of Moment Equations (ME) yield accurate (statistical) moments of a target environmental state variable. Under these circumstances, the ME approach can be used as an alternative to the Monte Carlo (MC) method for Uncertainty Quantification in diverse fields of Earth and environmental sciences. MEs are directly satisfied by the leading moments of the quantities of interest and are defined on the same support scale as the governing stochastic partial differential equations (PDEs). Computable approximations of the otherwise exact MEs can be obtained through perturbation expansion of moments of the state variables in orders of the standard deviation of the random model parameters. As such, their convergence is guaranteed only for the standard deviation smaller than one. We demonstrate our approach in the context of steady-state groundwater flow in a porous medium with a spatially random hydraulic conductivity.« less

Free oscillations in a climate model with ice-sheet dynamics

NASA Technical Reports Server (NTRS)

Kallen, E.; Crafoord, C.; Ghil, M.

1979-01-01

A study of stable periodic solutions to a simple nonlinear model of the ocean-atmosphere-ice system is presented. The model has two dependent variables: ocean-atmosphere temperature and latitudinal extent of the ice cover. No explicit dependence on latitude is considered in the model. Hence all variables depend only on time and the model consists of a coupled set of nonlinear ordinary differential equations. The globally averaged ocean-atmosphere temperature in the model is governed by the radiation balance. The reflectivity to incoming solar radiation, i.e., the planetary albedo, includes separate contributions from sea ice and from continental ice sheets. The major physical mechanisms active in the model are (1) albedo-temperature feedback, (2) continental ice-sheet dynamics and (3) precipitation-rate variations. The model has three-equilibrium solutions, two of which are linearly unstable, while one is linearly stable. For some choices of parameters, the stability picture changes and sustained, finite-amplitude oscillations obtain around the previously stable equilibrium solution. The physical interpretation of these oscillations points to the possibility of internal mechanisms playing a role in glaciation cycles.

Geometry of the q-exponential distribution with dependent competing risks and accelerated life testing

NASA Astrophysics Data System (ADS)

Zhang, Fode; Shi, Yimin; Wang, Ruibing

2017-02-01

In the information geometry suggested by Amari (1985) and Amari et al. (1987), a parametric statistical model can be regarded as a differentiable manifold with the parameter space as a coordinate system. Note that the q-exponential distribution plays an important role in Tsallis statistics (see Tsallis, 2009), this paper investigates the geometry of the q-exponential distribution with dependent competing risks and accelerated life testing (ALT). A copula function based on the q-exponential function, which can be considered as the generalized Gumbel copula, is discussed to illustrate the structure of the dependent random variable. Employing two iterative algorithms, simulation results are given to compare the performance of estimations and levels of association under different hybrid progressively censoring schemes (HPCSs).

Uncertainty quantification in LES of channel flow

DOE PAGES

Safta, Cosmin; Blaylock, Myra; Templeton, Jeremy; ...

2016-07-12

Here, in this paper, we present a Bayesian framework for estimating joint densities for large eddy simulation (LES) sub-grid scale model parameters based on canonical forced isotropic turbulence direct numerical simulation (DNS) data. The framework accounts for noise in the independent variables, and we present alternative formulations for accounting for discrepancies between model and data. To generate probability densities for flow characteristics, posterior densities for sub-grid scale model parameters are propagated forward through LES of channel flow and compared with DNS data. Synthesis of the calibration and prediction results demonstrates that model parameters have an explicit filter width dependence andmore » are highly correlated. Discrepancies between DNS and calibrated LES results point to additional model form inadequacies that need to be accounted for.« less

Skin friction and heat transfer correlations for high-speed low-density flow past a flat plate

NASA Technical Reports Server (NTRS)

Woronowicz, Michael S.; Baganoff, Donald

1991-01-01

The independent and dependent variables associated with drag and heat transfer to a flat plate at zero incidence in high-speed, rarefied flow are analyzed anew to reflect the importance of kinetic effects occurring near the plate surface on energy and momentum transfer, rather than following arguments normally used to describe continuum, higher density flowfields. A new parameter, the wall Knudsen number Knx,w, based on an estimate of the mean free path length of molecules having just interacted with the surface of the plate, is introduced and used to correlate published drag and heat transfer data. The new parameter is shown to provide better correlation than either the viscous interaction parameter X or the widely-used slip parameter Voo for drag and heat transfer data over a wide range of Mach numbers, Reynolds numbers, and plate-to-freestream stagnation temperature ratios.

Effects of developmental variability on the dynamics and self-organization of cell populations

NASA Astrophysics Data System (ADS)

Prabhakara, Kaumudi H.; Gholami, Azam; Zykov, Vladimir S.; Bodenschatz, Eberhard

2017-11-01

We report experimental and theoretical results for spatiotemporal pattern formation in cell populations, where the parameters vary in space and time due to mechanisms intrinsic to the system, namely Dictyostelium discoideum (D.d.) in the starvation phase. We find that different patterns are formed when the populations are initialized at different developmental stages, or when populations at different initial developmental stages are mixed. The experimentally observed patterns can be understood with a modified Kessler-Levine model that takes into account the initial spatial heterogeneity of the cell populations and a developmental path introduced by us, i.e. the time dependence of the various biochemical parameters. The dynamics of the parameters agree with known biochemical studies. Most importantly, the modified model reproduces not only our results, but also the observations of an independent experiment published earlier. This shows that pattern formation can be used to understand and quantify the temporal evolution of the system parameters.

The A and m coefficients in the Bruun/Dean equilibrium profile equation seen from the Arctic

USGS Publications Warehouse

Are, F.; Reimnitz, E.

2008-01-01

The Bruun/Dean relation between water depth and distance from the shore with a constant profile shape factor is widely used to describe shoreface profiles in temperate environments. However, it has been shown that the sediment scale parameter (A) and the profile shape factor (m) are interrelated variables. An analysis of 63 Arctic erosional shoreface profiles shows that both coefficients are highly variable. Relative frequency of the average m value is only 16% by the class width 0.1. No other m value frequency exceeds 21%. Therefore, there is insufficient reason to use average m to characterize Arctic shoreface profile shape. The shape of each profile has a definite combination of A and m values. Coefficients A and m show a distinct inverse relationship, as in temperate climate. A dependence of m values on coastal sediment grain size is seen, and m decreases with increasing grain size. With constant m = 0.67, parameter A obtains a dimension unit m1/3. But A equals the water depth in meters 1 m from the water edge. This fact and the variability of parameter m testify that the Bruun/Dean equation is essentially an empirical formula. There is no need to give any measurement unit to parameter A. But the International System of Units (SI) has to be used in applying the Bruun/Dean equation for shoreface profiles. A comparison of the shape of Arctic shoreface profiles with those of temperate environments shows surprising similarity. Therefore, the conclusions reached in this Arctic paper seem to apply also to temperate environments.

Anthropometric parameters and sexual maturation in 12- to 15-year-old Estonian boys.

PubMed

Veldre, Gudrun; Jürimäe, Toivo

2004-06-01

The aims of this study were 1. to fix main sexual maturation signs and anthropometric measurements, and 2. to investigate relations between maturational status and main anthropometric parameters (i.e. skinfolds, girths, lengths, breadths/lengths) in 12-15-year old boys. In total, 361 boys from Tartu, Estonia, were studied. Body height and weight, 9 skinfolds, 13 girths, 8 lengths and 8 breadths/lengths were measured. Pubertal stages were determined according to the criteria described by Tanner (1962). Self-assessment of pubic hair (PH1-PH5) was used. Genital development (G1-G5) was estimated by palpating the left testis and matching the size of wood ovoid of the Prader orchidometer. Finally, boys were asked about oigarche (= age at the first ejaculation of sperm). Most of the measured anthropometric variables were significantly different in boys of different chronological age and sexual maturity groups. By linear discriminant analysis, the safety of separation of the chronological age groups was higher than by sexual maturation variables. Nonlinear discriminant analysis allowed to separate sexual maturity groups by anthropometric variables up to 99% security. It was concluded that though the growth and development of a child is highly individual, on an average the anthropometric characteristics alter very constantly with the increase of age and biological maturation. Our results indicated that there were some significant differences in the anthropometrical parameters depending on the chronological age and biological maturation. Mostly length and breadth/length parameters change during the studied age period in respect to sexual development subgroups of boys. The skinfold thicknesses were not changed or even decreased.

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.

Empirical source noise prediction method with application to subsonic coaxial jet mixing noise

NASA Technical Reports Server (NTRS)

Zorumski, W. E.; Weir, D. S.

1982-01-01

A general empirical method, developed for source noise predictions, uses tensor splines to represent the dependence of the acoustic field on frequency and direction and Taylor's series to represent the dependence on source state parameters. The method is applied to prediction of mixing noise from subsonic circular and coaxial jets. A noise data base of 1/3-octave-band sound pressure levels (SPL's) from 540 tests was gathered from three countries: United States, United Kingdom, and France. The SPL's depend on seven variables: frequency, polar direction angle, and five source state parameters: inner and outer nozzle pressure ratios, inner and outer stream total temperatures, and nozzle area ratio. A least-squares seven-dimensional curve fit defines a table of constants which is used for the prediction method. The resulting prediction has a mean error of 0 dB and a standard deviation of 1.2 dB. The prediction method is used to search for a coaxial jet which has the greatest coaxial noise benefit as compared with an equivalent single jet. It is found that benefits of about 6 dB are possible.

Concurrently adjusting interrelated control parameters to achieve optimal engine performance

DOEpatents

Jiang, Li; Lee, Donghoon; Yilmaz, Hakan; Stefanopoulou, Anna

2015-12-01

Methods and systems for real-time engine control optimization are provided. A value of an engine performance variable is determined, a value of a first operating condition and a value of a second operating condition of a vehicle engine are detected, and initial values for a first engine control parameter and a second engine control parameter are determined based on the detected first operating condition and the detected second operating condition. The initial values for the first engine control parameter and the second engine control parameter are adjusted based on the determined value of the engine performance variable to cause the engine performance variable to approach a target engine performance variable. In order to cause the engine performance variable to approach the target engine performance variable, adjusting the initial value for the first engine control parameter necessitates a corresponding adjustment of the initial value for the second engine control parameter.

Reference tissue modeling with parameter coupling: application to a study of SERT binding in HIV

NASA Astrophysics Data System (ADS)

Endres, Christopher J.; Hammoud, Dima A.; Pomper, Martin G.

2011-04-01

When applicable, it is generally preferred to evaluate positron emission tomography (PET) studies using a reference tissue-based approach as that avoids the need for invasive arterial blood sampling. However, most reference tissue methods have been shown to have a bias that is dependent on the level of tracer binding, and the variability of parameter estimates may be substantially affected by noise level. In a study of serotonin transporter (SERT) binding in HIV dementia, it was determined that applying parameter coupling to the simplified reference tissue model (SRTM) reduced the variability of parameter estimates and yielded the strongest between-group significant differences in SERT binding. The use of parameter coupling makes the application of SRTM more consistent with conventional blood input models and reduces the total number of fitted parameters, thus should yield more robust parameter estimates. Here, we provide a detailed evaluation of the application of parameter constraint and parameter coupling to [11C]DASB PET studies. Five quantitative methods, including three methods that constrain the reference tissue clearance (kr2) to a common value across regions were applied to the clinical and simulated data to compare measurement of the tracer binding potential (BPND). Compared with standard SRTM, either coupling of kr2 across regions or constraining kr2 to a first-pass estimate improved the sensitivity of SRTM to measuring a significant difference in BPND between patients and controls. Parameter coupling was particularly effective in reducing the variance of parameter estimates, which was less than 50% of the variance obtained with standard SRTM. A linear approach was also improved when constraining kr2 to a first-pass estimate, although the SRTM-based methods yielded stronger significant differences when applied to the clinical study. This work shows that parameter coupling reduces the variance of parameter estimates and may better discriminate between-group differences in specific binding.

Dynamic multipopulation and density dependent evolutionary games related to replicator dynamics. A metasimplex concept.

PubMed

Argasinski, Krzysztof

2006-07-01

This paper contains the basic extensions of classical evolutionary games (multipopulation and density dependent models). It is shown that classical bimatrix approach is inconsistent with other approaches because it does not depend on proportion between populations. The main conclusion is that interspecific proportion parameter is important and must be considered in multipopulation models. The paper provides a synthesis of both extensions (a metasimplex concept) which solves the problem intrinsic in the bimatrix model. It allows us to model interactions among any number of subpopulations including density dependence effects. We prove that all modern approaches to evolutionary games are closely related. All evolutionary models (except classical bimatrix approaches) can be reduced to a single population general model by a simple change of variables. Differences between classic bimatrix evolutionary games and a new model which is dependent on interspecific proportion are shown by examples.

Geometry and Kinematics of Fault-Propagation Folds with Variable Interlimb Angles

NASA Astrophysics Data System (ADS)

Dhont, D.; Jabbour, M.; Hervouet, Y.; Deroin, J.

2009-12-01

Fault-propagation folds are common features in foreland basins and fold-and-thrust belts. Several conceptual models have been proposed to account for their geometry and kinematics. It is generally accepted that the shape of fault-propagation folds depends directly from both the amount of displacement along the basal decollement level and the dip angle of the ramp. Among these, the variable interlimb angle model proposed by Mitra (1990) is based on a folding kinematics that is able to explain open and close natural folds. However, the application of this model is limited because the geometric evolution and thickness variation of the fold directly depend on imposed parameters such as the maximal value of the ramp height. Here, we use the ramp and the interlimb angles as input data to develop a forward fold modelling accounting for thickness variations in the forelimb. The relationship between the fold amplitude and fold wavelength are subsequently applied to build balanced geologic cross-sections from surface parameters only, and to propose a kinematic restoration of the folding through time. We considered three natural examples to validate the variable interlimb angle model. Observed thickness variations in the forelimb of the Turner Valley anticline in the Alberta foothills of Canada precisely correspond to the theoretical values proposed by our model. Deep reconstruction of the Alima anticline in the southern Tunisian Atlas implies that the decollement level is localized in the Triassic-Liassic series, as highlighted by seismic imaging. Our kinematic reconstruction of the Ucero anticline in the Spanish Castilian mountains is also in agreement with the anticline geometry derived from two cross-sections. The variable interlimb angle model implies that the fault-propagation fold can be symmetric, normal asymmetric (with a greater dip value in the forelimb than in the backlimb), or reversely asymmetric (with greater dip in the backlimb) depending on the shortening amount. This model allows also: (i) to easily explain folds with wide variety of geometries; (ii) to understand the deep architecture of anticlines; and (iii) to deduce the kinematic evolution of folding with time. Mitra, S., 1990, Fault-propagation folds: geometry, kinematic evolution, and hydrocarbon traps. AAPG Bulletin, v. 74, no. 6, p. 921-945.

Review of Methods for Buildings Energy Performance Modelling

NASA Astrophysics Data System (ADS)

Krstić, Hrvoje; Teni, Mihaela

2017-10-01

Research presented in this paper gives a brief review of methods used for buildings energy performance modelling. This paper gives also a comprehensive review of the advantages and disadvantages of available methods as well as the input parameters used for modelling buildings energy performance. European Directive EPBD obliges the implementation of energy certification procedure which gives an insight on buildings energy performance via exiting energy certificate databases. Some of the methods for buildings energy performance modelling mentioned in this paper are developed by employing data sets of buildings which have already undergone an energy certification procedure. Such database is used in this paper where the majority of buildings in the database have already gone under some form of partial retrofitting - replacement of windows or installation of thermal insulation but still have poor energy performance. The case study presented in this paper utilizes energy certificates database obtained from residential units in Croatia (over 400 buildings) in order to determine the dependence between buildings energy performance and variables from database by using statistical dependencies tests. Building energy performance in database is presented with building energy efficiency rate (from A+ to G) which is based on specific annual energy needs for heating for referential climatic data [kWh/(m2a)]. Independent variables in database are surfaces and volume of the conditioned part of the building, building shape factor, energy used for heating, CO2 emission, building age and year of reconstruction. Research results presented in this paper give an insight in possibilities of methods used for buildings energy performance modelling. Further on it gives an analysis of dependencies between buildings energy performance as a dependent variable and independent variables from the database. Presented results could be used for development of new building energy performance predictive model.

The Nustar Spectrum of Mrk 335: Extreme Relativistic Effects Within Two Gravitational Radii of the Event Horizon?

NASA Technical Reports Server (NTRS)

Parker, M. L.; Wilkins, D. R.; Fabian, A. C.; Grupe, D.; Dauser, T.; Matt, G.; Harrison, F. A.; Brenneman, L.; Boggs, S. E.; Christensen, F. E.;

Use of the Wii Gaming System for Balance Rehabilitation: Establishing Parameters for Healthy Individuals.

PubMed

Burns, Melissa K; Andeway, Kathleen; Eppenstein, Paula; Ruroede, Kathleen

2014-06-01

This study was designed to establish balance parameters for the Nintendo(®) (Redmond, WA) "Wii Fit™" Balance Board system with three common games, in a sample of healthy adults, and to evaluate the balance measurement reproducibility with separation by age. This was a prospective, multivariate analysis of variance, cohort study design. Seventy-five participants who satisfied all inclusion criteria and completed an informed consent were enrolled. Participants were grouped into age ranges: 21-35 years (n=24), 36-50 years (n=24), and 51-65 years (n=27). Each participant completed the following games three consecutive times, in a randomized order, during one session: "Balance Bubble" (BB) for distance and duration, "Tight Rope" (TR) for distance and duration, and "Center of Balance" (COB) on the left and right sides. COB distributed weight was fairly symmetrical across all subjects and trials; therefore, no influence was assumed on or interaction with other "Wii Fit" measurements. Homogeneity of variance statistics indicated the assumption of distribution normality of the dependent variables (rates) were tenable. The multivariate analysis of variance included dependent variables BB and TR rates (distance divided by duration to complete) with age group and trials as the independent variables. The BB rate was statistically significant (F=4.725, P<0.005), but not the TR rate. The youngest group's BB rate was significantly larger than those of the other two groups. "Wii Fit" can discriminate among age groups across trials. The results show promise as a viable tool to measure balance and distance across time (speed) and center of balance distribution.

Clustering coefficients of protein-protein interaction networks

NASA Astrophysics Data System (ADS)

Miller, Gerald A.; Shi, Yi Y.; Qian, Hong; Bomsztyk, Karol

2007-05-01

The properties of certain networks are determined by hidden variables that are not explicitly measured. The conditional probability (propagator) that a vertex with a given value of the hidden variable is connected to k other vertices determines all measurable properties. We study hidden variable models and find an averaging approximation that enables us to obtain a general analytical result for the propagator. Analytic results showing the validity of the approximation are obtained. We apply hidden variable models to protein-protein interaction networks (PINs) in which the hidden variable is the association free energy, determined by distributions that depend on biochemistry and evolution. We compute degree distributions as well as clustering coefficients of several PINs of different species; good agreement with measured data is obtained. For the human interactome two different parameter sets give the same degree distributions, but the computed clustering coefficients differ by a factor of about 2. This shows that degree distributions are not sufficient to determine the properties of PINs.

A fully relativistic twisted disc around a slowly rotating Kerr black hole: derivation of dynamical equations and the shape of stationary configurations

NASA Astrophysics Data System (ADS)

Zhuravlev, V. V.; Ivanov, P. B.

2011-08-01

In this paper we derive equations describing the dynamics and stationary configurations of a twisted fully relativistic thin accretion disc around a slowly rotating black hole. We assume that the inclination angle of the disc is small and that the standard relativistic generalization of the α model of accretion discs is valid when the disc is flat. We find that similar to the case of non-relativistic twisted discs the disc dynamics and stationary shapes can be determined by a pair of equations formulated for two complex variables describing the orientation of the disc rings and velocity perturbations induced by the twist. We analyse analytically and numerically the shapes of stationary twisted configurations of accretion discs having non-zero inclinations with respect to the black hole equatorial plane at large distances r from the black hole. It is shown that the stationary configurations depend on two parameters - the viscosity parameter α and the parameter ?, where δ* is the opening angle (δ*˜h/r, where h is the disc half-thickness and r is large) of a flat disc and a is the black hole rotational parameter. When a > 0 and ? the shapes depend drastically on the value of α. When α is small the disc inclination angle oscillates with radius with amplitude and radial frequency of the oscillations dramatically increasing towards the last stable orbit, Rms. When α has a moderately small value the oscillations do not take place but the disc does not align with the equatorial plane at small radii. The disc inclination angle either is increasing towards Rms or exhibits a non-monotonic dependence on the radial coordinate. Finally, when α is sufficiently large the disc aligns with the equatorial plane at small radii. When a < 0 the disc aligns with the equatorial plane for all values of α. The results reported here may have implications for determining the structure and variability of accretion discs close to Rms as well as for modelling of emission spectra coming from different sources, which are supposed to contain black holes.

Urea-temperature phase diagrams capture the thermodynamics of denatured state expansion that accompany protein unfolding

PubMed Central

Tischer, Alexander; Auton, Matthew

2013-01-01

We have analyzed the thermodynamic properties of the von Willebrand factor (VWF) A3 domain using urea-induced unfolding at variable temperature and thermal unfolding at variable urea concentrations to generate a phase diagram that quantitatively describes the equilibrium between native and denatured states. From this analysis, we were able to determine consistent thermodynamic parameters with various spectroscopic and calorimetric methods that define the urea–temperature parameter plane from cold denaturation to heat denaturation. Urea and thermal denaturation are experimentally reversible and independent of the thermal scan rate indicating that all transitions are at equilibrium and the van't Hoff and calorimetric enthalpies obtained from analysis of individual thermal transitions are equivalent demonstrating two-state character. Global analysis of the urea–temperature phase diagram results in a significantly higher enthalpy of unfolding than obtained from analysis of individual thermal transitions and significant cross correlations describing the urea dependence of and that define a complex temperature dependence of the m-value. Circular dichroism (CD) spectroscopy illustrates a large increase in secondary structure content of the urea-denatured state as temperature increases and a loss of secondary structure in the thermally denatured state upon addition of urea. These structural changes in the denatured ensemble make up ∼40% of the total ellipticity change indicating a highly compact thermally denatured state. The difference between the thermodynamic parameters obtained from phase diagram analysis and those obtained from analysis of individual thermal transitions illustrates that phase diagrams capture both contributions to unfolding and denatured state expansion and by comparison are able to decipher these contributions. PMID:23813497

Analysis of colour stability of selected provisional prosthetic materials: an in vitro study.

PubMed

Koczorowski, Ryszard; Linkowska-Swidzińska, Kamila; Gedrange, Tomasz; Swidziński, Teodor

2009-08-01

Prosthetic restorative materials (that are) used for temporary fixed dentures tend to exhibit variable discolouration over several weeks of use. The aim of this study was to perform a spectrophotometric analysis of the influence of selected discolouring factors on the colour stability of provisional prosthetic materials in vitro. In the study, the following prosthetic materials for short-term use in the oral cavity were evaluated: Luxatemp, Structur 2S.C., Protemp II, Zhermacryl STC and Dentalon Plus. Samples of these materials were immersed in coffee, tea and dark fruit juice for 60 h at different pH values. Colour was evaluated by determining the monochromatic coefficients of light reflected by the samples, using a spectrophotometric method. Results received in artificial light (illuminant A) were compared with those obtained in daylight (illuminant D65). Changes in colour and its parameters according to the CIE L*a*b* system were analysed. The analysis (of the colour and colour parameters) of the tested materials in two types of light showed that Structur displayed the greatest tendency to discolouration and that the least tendency to discolouration was exhibited by Dentalon Plus. The fact that colour parameters obtained in two types of light were not identical suggests that changes in the colour of the same material may be perceived differently, depending on the illuminant. Provisional prosthetic materials show variable colour stability under different conditions in the oral cavity. The colour of prosthetic materials may be perceived differently, depending on the illuminant and the effect of the environment in which they are used.

An Extended Eddy-Diffusivity Mass-Flux Scheme for Unified Representation of Subgrid-Scale Turbulence and Convection

NASA Astrophysics Data System (ADS)

Tan, Zhihong; Kaul, Colleen M.; Pressel, Kyle G.; Cohen, Yair; Schneider, Tapio; Teixeira, João.

2018-03-01

Large-scale weather forecasting and climate models are beginning to reach horizontal resolutions of kilometers, at which common assumptions made in existing parameterization schemes of subgrid-scale turbulence and convection—such as that they adjust instantaneously to changes in resolved-scale dynamics—cease to be justifiable. Additionally, the common practice of representing boundary-layer turbulence, shallow convection, and deep convection by discontinuously different parameterizations schemes, each with its own set of parameters, has contributed to the proliferation of adjustable parameters in large-scale models. Here we lay the theoretical foundations for an extended eddy-diffusivity mass-flux (EDMF) scheme that has explicit time-dependence and memory of subgrid-scale variables and is designed to represent all subgrid-scale turbulence and convection, from boundary layer dynamics to deep convection, in a unified manner. Coherent up and downdrafts in the scheme are represented as prognostic plumes that interact with their environment and potentially with each other through entrainment and detrainment. The more isotropic turbulence in their environment is represented through diffusive fluxes, with diffusivities obtained from a turbulence kinetic energy budget that consistently partitions turbulence kinetic energy between plumes and environment. The cross-sectional area of up and downdrafts satisfies a prognostic continuity equation, which allows the plumes to cover variable and arbitrarily large fractions of a large-scale grid box and to have life cycles governed by their own internal dynamics. Relatively simple preliminary proposals for closure parameters are presented and are shown to lead to a successful simulation of shallow convection, including a time-dependent life cycle.

PCAN: Probabilistic Correlation Analysis of Two Non-normal Data Sets

PubMed Central

Zoh, Roger S.; Mallick, Bani; Ivanov, Ivan; Baladandayuthapani, Veera; Manyam, Ganiraju; Chapkin, Robert S.; Lampe, Johanna W.; Carroll, Raymond J.

2016-01-01

Summary Most cancer research now involves one or more assays profiling various biological molecules, e.g., messenger RNA and micro RNA, in samples collected on the same individuals. The main interest with these genomic data sets lies in the identification of a subset of features that are active in explaining the dependence between platforms. To quantify the strength of the dependency between two variables, correlation is often preferred. However, expression data obtained from next-generation sequencing platforms are integer with very low counts for some important features. In this case, the sample Pearson correlation is not a valid estimate of the true correlation matrix, because the sample correlation estimate between two features/variables with low counts will often be close to zero, even when the natural parameters of the Poisson distribution are, in actuality, highly correlated. We propose a model-based approach to correlation estimation between two non-normal data sets, via a method we call Probabilistic Correlations ANalysis, or PCAN. PCAN takes into consideration the distributional assumption about both data sets and suggests that correlations estimated at the model natural parameter level are more appropriate than correlations estimated directly on the observed data. We demonstrate through a simulation study that PCAN outperforms other standard approaches in estimating the true correlation between the natural parameters. We then apply PCAN to the joint analysis of a microRNA (miRNA) and a messenger RNA (mRNA) expression data set from a squamous cell lung cancer study, finding a large number of negative correlation pairs when compared to the standard approaches. PMID:27037601

PCAN: Probabilistic correlation analysis of two non-normal data sets.

PubMed

Zoh, Roger S; Mallick, Bani; Ivanov, Ivan; Baladandayuthapani, Veera; Manyam, Ganiraju; Chapkin, Robert S; Lampe, Johanna W; Carroll, Raymond J

2016-12-01

Most cancer research now involves one or more assays profiling various biological molecules, e.g., messenger RNA and micro RNA, in samples collected on the same individuals. The main interest with these genomic data sets lies in the identification of a subset of features that are active in explaining the dependence between platforms. To quantify the strength of the dependency between two variables, correlation is often preferred. However, expression data obtained from next-generation sequencing platforms are integer with very low counts for some important features. In this case, the sample Pearson correlation is not a valid estimate of the true correlation matrix, because the sample correlation estimate between two features/variables with low counts will often be close to zero, even when the natural parameters of the Poisson distribution are, in actuality, highly correlated. We propose a model-based approach to correlation estimation between two non-normal data sets, via a method we call Probabilistic Correlations ANalysis, or PCAN. PCAN takes into consideration the distributional assumption about both data sets and suggests that correlations estimated at the model natural parameter level are more appropriate than correlations estimated directly on the observed data. We demonstrate through a simulation study that PCAN outperforms other standard approaches in estimating the true correlation between the natural parameters. We then apply PCAN to the joint analysis of a microRNA (miRNA) and a messenger RNA (mRNA) expression data set from a squamous cell lung cancer study, finding a large number of negative correlation pairs when compared to the standard approaches. © 2016, The International Biometric Society.

Applying petrophysical models to radar travel time and electrical resistivity tomograms: Resolution-dependent limitations

USGS Publications Warehouse

Day-Lewis, F. D.; Singha, K.; Binley, A.M.

2005-01-01

Geophysical imaging has traditionally provided qualitative information about geologic structure; however, there is increasing interest in using petrophysical models to convert tomograms to quantitative estimates of hydrogeologic, mechanical, or geochemical parameters of interest (e.g., permeability, porosity, water content, and salinity). Unfortunately, petrophysical estimation based on tomograms is complicated by limited and variable image resolution, which depends on (1) measurement physics (e.g., electrical conduction or electromagnetic wave propagation), (2) parameterization and regularization, (3) measurement error, and (4) spatial variability. We present a framework to predict how core-scale relations between geophysical properties and hydrologic parameters are altered by the inversion, which produces smoothly varying pixel-scale estimates. We refer to this loss of information as "correlation loss." Our approach upscales the core-scale relation to the pixel scale using the model resolution matrix from the inversion, random field averaging, and spatial statistics of the geophysical property. Synthetic examples evaluate the utility of radar travel time tomography (RTT) and electrical-resistivity tomography (ERT) for estimating water content. This work provides (1) a framework to assess tomograms for geologic parameter estimation and (2) insights into the different patterns of correlation loss for ERT and RTT. Whereas ERT generally performs better near boreholes, RTT performs better in the interwell region. Application of petrophysical models to the tomograms in our examples would yield misleading estimates of water content. Although the examples presented illustrate the problem of correlation loss in the context of near-surface geophysical imaging, our results have clear implications for quantitative analysis of tomograms for diverse geoscience applications. Copyright 2005 by the American Geophysical Union.

Experimental studies on the physico-mechanical properties of jet-grout columns in sandy and silty soils

NASA Astrophysics Data System (ADS)

Akin, Muge K.

2016-04-01

The term of ground improvement states to the modification of the engineering properties of soils. Jet-grouting is one of the grouting methods among various ground improvement techniques. During jet-grouting, different textures of columns can be obtained depending on the characteristics of surrounding subsoil as well as the adopted jet-grouting system for each site is variable. In addition to textural properties, strength and index parameters of jet-grout columns are highly affected by the adjacent soil. In this study, the physical and mechanical properties of jet-grout columns constructed at two different sites in silty and sandy soil conditions were determined by laboratory tests. A number of statistical relationships between physical and mechanical properties of soilcrete were established in this study in order to investigate the dependency of numerous variables. The relationship between qu and γd is more reliable for sandy soilcrete than that of silty columns considering the determination coefficients. Positive linear relationships between Vp and γd with significantly high determination coefficients were obtained for the jet-grout columns in silt and sand. The regression analyses indicate that the P-wave velocity is a very dominant parameter for the estimation of physical and mechanical properties of jet-grout columns and should be involved during the quality control of soilcrete material despite the intensive use of uniaxial compressive strength test. Besides, it is concluded that the dry unit weight of jet-grout column is a good indicator of the efficiency of employed operational parameters during jet-grouting.

An Extended Eddy‐Diffusivity Mass‐Flux Scheme for Unified Representation of Subgrid‐Scale Turbulence and Convection

PubMed Central

Tan, Zhihong; Kaul, Colleen M.; Pressel, Kyle G.; Cohen, Yair; Teixeira, João

2018-01-01

Abstract Large‐scale weather forecasting and climate models are beginning to reach horizontal resolutions of kilometers, at which common assumptions made in existing parameterization schemes of subgrid‐scale turbulence and convection—such as that they adjust instantaneously to changes in resolved‐scale dynamics—cease to be justifiable. Additionally, the common practice of representing boundary‐layer turbulence, shallow convection, and deep convection by discontinuously different parameterizations schemes, each with its own set of parameters, has contributed to the proliferation of adjustable parameters in large‐scale models. Here we lay the theoretical foundations for an extended eddy‐diffusivity mass‐flux (EDMF) scheme that has explicit time‐dependence and memory of subgrid‐scale variables and is designed to represent all subgrid‐scale turbulence and convection, from boundary layer dynamics to deep convection, in a unified manner. Coherent up and downdrafts in the scheme are represented as prognostic plumes that interact with their environment and potentially with each other through entrainment and detrainment. The more isotropic turbulence in their environment is represented through diffusive fluxes, with diffusivities obtained from a turbulence kinetic energy budget that consistently partitions turbulence kinetic energy between plumes and environment. The cross‐sectional area of up and downdrafts satisfies a prognostic continuity equation, which allows the plumes to cover variable and arbitrarily large fractions of a large‐scale grid box and to have life cycles governed by their own internal dynamics. Relatively simple preliminary proposals for closure parameters are presented and are shown to lead to a successful simulation of shallow convection, including a time‐dependent life cycle. PMID:29780442

Magneto-Structural Correlations in Pseudotetrahedral Forms of the [Co(SPh)4]2- Complex Probed by Magnetometry, MCD Spectroscopy, Advanced EPR Techniques, and ab Initio Electronic Structure Calculations.

PubMed

Suturina, Elizaveta A; Nehrkorn, Joscha; Zadrozny, Joseph M; Liu, Junjie; Atanasov, Mihail; Weyhermüller, Thomas; Maganas, Dimitrios; Hill, Stephen; Schnegg, Alexander; Bill, Eckhard; Long, Jeffrey R; Neese, Frank

2017-03-06

The magnetic properties of pseudotetrahedral Co(II) complexes spawned intense interest after (PPh 4 ) 2 [Co(SPh) 4 ] was shown to be the first mononuclear transition-metal complex displaying slow relaxation of the magnetization in the absence of a direct current magnetic field. However, there are differing reports on its fundamental magnetic spin Hamiltonian (SH) parameters, which arise from inherent experimental challenges in detecting large zero-field splittings. There are also remarkable changes in the SH parameters of [Co(SPh) 4 ] 2- upon structural variations, depending on the counterion and crystallization conditions. In this work, four complementary experimental techniques are utilized to unambiguously determine the SH parameters for two different salts of [Co(SPh) 4 ] 2- : (PPh 4 ) 2 [Co(SPh) 4 ] (1) and (NEt 4 ) 2 [Co(SPh) 4 ] (2). The characterization methods employed include multifield SQUID magnetometry, high-field/high-frequency electron paramagnetic resonance (HF-EPR), variable-field variable-temperature magnetic circular dichroism (VTVH-MCD), and frequency domain Fourier transform THz-EPR (FD-FT THz-EPR). Notably, the paramagnetic Co(II) complex [Co(SPh) 4 ] 2- shows strong axial magnetic anisotropy in 1, with D = -55(1) cm -1 and E/D = 0.00(3), but rhombic anisotropy is seen for 2, with D = +11(1) cm -1 and E/D = 0.18(3). Multireference ab initio CASSCF/NEVPT2 calculations enable interpretation of the remarkable variation of D and its dependence on the electronic structure and geometry.

How spatial and temporal rainfall variability affect runoff across basin scales: insights from field observations in the (semi-)urbanised Charlotte watershed

NASA Astrophysics Data System (ADS)

Ten Veldhuis, M. C.; Smith, J. A.; Zhou, Z.

2017-12-01

Impacts of rainfall variability on runoff response are highly scale-dependent. Sensitivity analyses based on hydrological model simulations have shown that impacts are likely to depend on combinations of storm type, basin versus storm scale, temporal versus spatial rainfall variability. So far, few of these conclusions have been confirmed on observational grounds, since high quality datasets of spatially variable rainfall and runoff over prolonged periods are rare. Here we investigate relationships between rainfall variability and runoff response based on 30 years of radar-rainfall datasets and flow measurements for 16 hydrological basins ranging from 7 to 111 km2. Basins vary not only in scale, but also in their degree of urbanisation. We investigated temporal and spatial variability characteristics of rainfall fields across a range of spatial and temporal scales to identify main drivers for variability in runoff response. We identified 3 ranges of basin size with different temporal versus spatial rainfall variability characteristics. Total rainfall volume proved to be the dominant agent determining runoff response at all basin scales, independent of their degree of urbanisation. Peak rainfall intensity and storm core volume are of secondary importance. This applies to all runoff parameters, including runoff volume, runoff peak, volume-to-peak and lag time. Position and movement of the storm with respect to the basin have a negligible influence on runoff response, with the exception of lag times in some of the larger basins. This highlights the importance of accuracy in rainfall estimation: getting the position right but the volume wrong will inevitably lead to large errors in runoff prediction. Our study helps to identify conditions where rainfall variability matters for correct estimation of the rainfall volume as well as the associated runoff response.

Weighted partial least squares based on the error and variance of the recovery rate in calibration set.

PubMed

Yu, Shaohui; Xiao, Xue; Ding, Hong; Xu, Ge; Li, Haixia; Liu, Jing

2017-08-05

The quantitative analysis is very difficult for the emission-excitation fluorescence spectroscopy of multi-component mixtures whose fluorescence peaks are serious overlapping. As an effective method for the quantitative analysis, partial least squares can extract the latent variables from both the independent variables and the dependent variables, so it can model for multiple correlations between variables. However, there are some factors that usually affect the prediction results of partial least squares, such as the noise, the distribution and amount of the samples in calibration set etc. This work focuses on the problems in the calibration set that are mentioned above. Firstly, the outliers in the calibration set are removed by leave-one-out cross-validation. Then, according to two different prediction requirements, the EWPLS method and the VWPLS method are proposed. The independent variables and dependent variables are weighted in the EWPLS method by the maximum error of the recovery rate and weighted in the VWPLS method by the maximum variance of the recovery rate. Three organic matters with serious overlapping excitation-emission fluorescence spectroscopy are selected for the experiments. The step adjustment parameter, the iteration number and the sample amount in the calibration set are discussed. The results show the EWPLS method and the VWPLS method are superior to the PLS method especially for the case of small samples in the calibration set. Copyright © 2017 Elsevier B.V. All rights reserved.

Variable Viscosity Effects on Time Dependent Magnetic Nanofluid Flow past a Stretchable Rotating Plate

NASA Astrophysics Data System (ADS)

Ram, Paras; Joshi, Vimal Kumar; Sharma, Kushal; Walia, Mittu; Yadav, Nisha

2016-01-01

An attempt has been made to describe the effects of geothermal viscosity with viscous dissipation on the three dimensional time dependent boundary layer flow of magnetic nanofluids due to a stretchable rotating plate in the presence of a porous medium. The modelled governing time dependent equations are transformed a from boundary value problem to an initial value problem, and thereafter solved by a fourth order Runge-Kutta method in MATLAB with a shooting technique for the initial guess. The influences of mixed temperature, depth dependent viscosity, and the rotation strength parameter on the flow field and temperature field generated on the plate surface are investigated. The derived results show direct impact in the problems of heat transfer in high speed computer disks (Herrero et al. [1]) and turbine rotor systems (Owen and Rogers [2]).

[Generalization of the Lotka-Volterra equation].

PubMed

Nazarenko, V G

1976-01-01

A complete qualitative study of Lotka--Volterra model with cooperative interactions in the system predator-prey is carried out. The model is as follows: (see abstract). The character of all possible stationary states is investigated in the first quadrant of the phase plane of the model variables depending on the system parameters. It is shown that for the generalized model considered unstable and stable limit cycles only of the infinite amplitude are possible in the first quadrant.

An experimental study of the influence of elevated buoyancy levels on flame spread rate over thermally thin cellulosic materials

NASA Technical Reports Server (NTRS)

Shang, P. C.; Altenkirch, R. A.; Eichhorn, R.

1978-01-01

The role of buoyancy on the flame spread rate over paper and its effect on extinction was studied by changing the gravity level and pressure. It was found that the flame spread rate decreases as the buoyancy induced flow increases. A method for correlating flame spread data using dimensionless parameters is presented. The Damkohler number is shown to be the dependent variable.

Impacts of variable thermal conductivity on stagnation point boundary layer flow past a Riga plate with variable thickness using generalized Fourier's law

NASA Astrophysics Data System (ADS)

Shah, S.; Hussain, S.; Sagheer, M.

2018-06-01

This article explores the problem of two-dimensional, laminar, steady and boundary layer stagnation point slip flow over a Riga plate. The incompressible upper-convected Maxwell fluid has been considered as a rheological fluid model. The heat transfer characteristics are investigated with generalized Fourier's law. The fluid thermal conductivity is assumed to be temperature dependent in this study. A system of partial differential equations governing the flow of an upper-convected Maxwell fluid, heat and mass transfer using generalized Fourier's law is developed. The main objective of the article is to inspect the impacts of pertinent physical parameters such as the stretching ratio parameter (0 ⩽ A ⩽ 0.3) , Deborah number (0 ⩽ β ⩽ 0.6) , thermal relaxation parameter (0 ⩽ γ ⩽ 0.5) , wall thickness parameter (0.1 ⩽ α ⩽ 3.5) , slip parameter (0 ⩽ R ⩽ 1.5) , thermal conductivity parameter (0.1 ⩽ δ ⩽ 1.0) and modified Hartmann number (0 ⩽ Q ⩽ 3) on the velocity and temperature profiles. Suitable local similarity transformations have been used to get a system of non-linear ODEs from the governing PDEs. The numerical solutions for the dimensionless velocity and temperature distributions have been achieved by employing an effective numerical method called the shooting method. It is seen that the velocity profile shows the reduction in the velocity for the higher values of viscoelastic parameter and the thermal relaxation parameter. In addition, to enhance the reliability at the maximum level of the obtained numerical results by shooting method, a MATLAB built-in solver bvp4c has also been utilized.

Experiences in multiyear combined state-parameter estimation with an ecosystem model of the North Atlantic and Arctic Oceans using the Ensemble Kalman Filter

NASA Astrophysics Data System (ADS)

Simon, Ehouarn; Samuelsen, Annette; Bertino, Laurent; Mouysset, Sandrine

2015-12-01

A sequence of one-year combined state-parameter estimation experiments has been conducted in a North Atlantic and Arctic Ocean configuration of the coupled physical-biogeochemical model HYCOM-NORWECOM over the period 2007-2010. The aim is to evaluate the ability of an ensemble-based data assimilation method to calibrate ecosystem model parameters in a pre-operational setting, namely the production of the MyOcean pilot reanalysis of the Arctic biology. For that purpose, four biological parameters (two phyto- and two zooplankton mortality rates) are estimated by assimilating weekly data such as, satellite-derived Sea Surface Temperature, along-track Sea Level Anomalies, ice concentrations and chlorophyll-a concentrations with an Ensemble Kalman Filter. The set of optimized parameters locally exhibits seasonal variations suggesting that time-dependent parameters should be used in ocean ecosystem models. A clustering analysis of the optimized parameters is performed in order to identify consistent ecosystem regions. In the north part of the domain, where the ecosystem model is the most reliable, most of them can be associated with Longhurst provinces and new provinces emerge in the Arctic Ocean. However, the clusters do not coincide anymore with the Longhurst provinces in the Tropics due to large model errors. Regarding the ecosystem state variables, the assimilation of satellite-derived chlorophyll concentration leads to significant reduction of the RMS errors in the observed variables during the first year, i.e. 2008, compared to a free run simulation. However, local filter divergences of the parameter component occur in 2009 and result in an increase in the RMS error at the time of the spring bloom.

Effect of ENSO on the variability of SST and Chlorophyll-a in Java Sea

NASA Astrophysics Data System (ADS)

Wirasatriya, Anindya; Prasetyawan, Indra B.; Triyono, Chandra D.; Muslim; Maslukah, Lilik

2018-02-01

Sea surface temperature (SST) and chlorophyll-a (Chl-a) are two parameters often used for identifying the marine productivity. Located at the maritime continent, the variability of SST and Chl-a in the Indonesian seas is influenced by El Niño Southern Oscillation (ENSO). The previous studies showed that the effect of El Niño tend to decrease SST and increase Chl-a in the areas within the Indonesian seas. Using long time observation of satellite data (2003-2016), it was found different result in Java Sea. Since Java Sea has strong seasonal variability influenced by monsoon wind, the effect of ENSO depend on the season. During southeast monsoon season, El Niño (La Niña) tend to increase (decrease) the speed of southeasterly wind cause the decrease or increase of SST. On the contrary, during northwest monsoon season, El Niño (La Niña) tend to decrease (increase) the speed of northwesterly wind cause the increase (decrease) of SST. The dependence of Chl-a on wind speed is only observed in the off shore which exhibit the strong seasonal variation. However, the effect of ENSO on the variability of Chl-a is not robust since the effected amplitude is less than the RMSE of Chl-a data.

Predictors of competitive achievement among pubescent synchronized swimmers: an analysis of the solo-figure competition.

PubMed

Peric, M; Cavar, M; Zenic, N; Sekulic, D; Sajber, D

2014-02-01

This study examined the applicability of sport-specific fitness tests (SSTs), anthropometrics, and respiratory parameters in predicting competitive results among pubescent synchronized swimmers. A total of 25 synchronized swimmers (16-17 years; 166.2 ± 5.4 cm; and 58.4 ± 4.3 kg) volunteered for this study. The independent variables were body mass, body height, Body Mass Index (BMI), body fat percentage (BF%), lean body mass percentage, respiratory variables, and four SSTs (two specific power tests plus one aerobic- and one anaerobic-endurance test). The dependent variable was competitive achievement in the solo figure competition. The reliability analyses, Pearson's correlation coefficient and forward stepwise regression were calculated. The SSTs were reliable for testing fitness status among pubescent synchronized swimmers. The forward stepwise regression retained two SSTs, BF% and forced vital capacity (FVC, relative for age and stature) in a set of predictors of competitive achievement. Significant Beta coefficients are found for aerobic-endurance, SST and FVC. The sport-specific measure of aerobic endurance and FVC appropriately predicted competitive achievement with regard to the figures used in the competition when competitive results (the dependent variable) were obtained. Athletes and coaches should be aware of the probable negative influence of very low body fat levels on competitive achievement.

[Therapeutic algorithm of idiopathic scoliosis in children].

PubMed

Ciortan, Ionica; Goţia, D G

2008-01-01

Acquired deformations of spinal cord (scoliosis, kyphosis, lordosis) represent a frequent pathology in child; their treatment is complex, with variable results which depend on various parameters. Mild scoliosis, with an angle less than 30 degrees, is treated with physiotherapy and regular follow-up. If the angle is higher than 30 degrees, the orthopedic corset is required; the angle over 45 degrees impose surgically correction. The indications of every therapeutic method depend on many factors, the main target of the treatment is to prevent the aggravation of the curvature; concerning the surgery, the goal is to obtain a correction as normal as possible of the spinal axis.

A computational framework for testing arrhythmia marker sensitivities to model parameters in functionally calibrated populations of atrial cells

NASA Astrophysics Data System (ADS)

Vagos, Márcia R.; Arevalo, Hermenegild; de Oliveira, Bernardo Lino; Sundnes, Joakim; Maleckar, Mary M.

2017-09-01

Models of cardiac cell electrophysiology are complex non-linear systems which can be used to gain insight into mechanisms of cardiac dynamics in both healthy and pathological conditions. However, the complexity of cardiac models can make mechanistic insight difficult. Moreover, these are typically fitted to averaged experimental data which do not incorporate the variability in observations. Recently, building populations of models to incorporate inter- and intra-subject variability in simulations has been combined with sensitivity analysis (SA) to uncover novel ionic mechanisms and potentially clarify arrhythmogenic behaviors. We used the Koivumäki human atrial cell model to create two populations, representing normal Sinus Rhythm (nSR) and chronic Atrial Fibrillation (cAF), by varying 22 key model parameters. In each population, 14 biomarkers related to the action potential and dynamic restitution were extracted. Populations were calibrated based on distributions of biomarkers to obtain reasonable physiological behavior, and subjected to SA to quantify correlations between model parameters and pro-arrhythmia markers. The two populations showed distinct behaviors under steady state and dynamic pacing. The nSR population revealed greater variability, and more unstable dynamic restitution, as compared to the cAF population, suggesting that simulated cAF remodeling rendered cells more stable to parameter variation and rate adaptation. SA revealed that the biomarkers depended mainly on five ionic currents, with noted differences in sensitivities to these between nSR and cAF. Also, parameters could be selected to produce a model variant with no alternans and unaltered action potential morphology, highlighting that unstable dynamical behavior may be driven by specific cell parameter settings. These results ultimately suggest that arrhythmia maintenance in cAF may not be due to instability in cell membrane excitability, but rather due to tissue-level effects which promote initiation and maintenance of reentrant arrhythmia.

Computational modeling of unsteady third-grade fluid flow over a vertical cylinder: A study of heat transfer visualization

NASA Astrophysics Data System (ADS)

Reddy, G. Janardhana; Hiremath, Ashwini; Kumar, Mahesh

2018-03-01

The present paper aims to investigate the effect of Prandtl number for unsteady third-grade fluid flow over a uniformly heated vertical cylinder using Bejan's heat function concept. The mathematical model of this problem is given by highly time-dependent non-linear coupled equations and are resolved by an efficient unconditionally stable implicit scheme. The time histories of average values of momentum and heat transport coefficients as well as the steady-state flow variables are displayed graphically for distinct values of non-dimensional control parameters arising in the system. As the non-dimensional parameter value gets amplified, the time taken for the fluid flow variables to attain the time-independent state is decreasing. The dimensionless heat function values are closely associated with an overall rate of heat transfer. Thermal energy transfer visualization implies that the heat function contours are compact in the neighborhood of the leading edge of the hot cylindrical wall. It is noticed that the deviations of flow-field variables from the hot wall for a non-Newtonian third-grade fluid flow are significant compared to the usual Newtonian fluid flow.

Assessing landslide susceptibility by statistical data analysis and GIS: the case of Daunia (Apulian Apennines, Italy)

NASA Astrophysics Data System (ADS)

Ceppi, C.; Mancini, F.; Ritrovato, G.

2009-04-01

This study aim at the landslide susceptibility mapping within an area of the Daunia (Apulian Apennines, Italy) by a multivariate statistical method and data manipulation in a Geographical Information System (GIS) environment. Among the variety of existing statistical data analysis techniques, the logistic regression was chosen to produce a susceptibility map all over an area where small settlements are historically threatened by landslide phenomena. By logistic regression a best fitting between the presence or absence of landslide (dependent variable) and the set of independent variables is performed on the basis of a maximum likelihood criterion, bringing to the estimation of regression coefficients. The reliability of such analysis is therefore due to the ability to quantify the proneness to landslide occurrences by the probability level produced by the analysis. The inventory of dependent and independent variables were managed in a GIS, where geometric properties and attributes have been translated into raster cells in order to proceed with the logistic regression by means of SPSS (Statistical Package for the Social Sciences) package. A landslide inventory was used to produce the bivariate dependent variable whereas the independent set of variable concerned with slope, aspect, elevation, curvature, drained area, lithology and land use after their reductions to dummy variables. The effect of independent parameters on landslide occurrence was assessed by the corresponding coefficient in the logistic regression function, highlighting a major role played by the land use variable in determining occurrence and distribution of phenomena. Once the outcomes of the logistic regression are determined, data are re-introduced in the GIS to produce a map reporting the proneness to landslide as predicted level of probability. As validation of results and regression model a cell-by-cell comparison between the susceptibility map and the initial inventory of landslide events was performed and an agreement at 75% level achieved.

A Study on the Influence of Process Parameters on the Viscoelastic Properties of ABS Components Manufactured by FDM Process

NASA Astrophysics Data System (ADS)

Dakshinamurthy, Devika; Gupta, Srinivasa

2018-04-01

Fused Deposition Modelling (FDM) is a fast growing Rapid Prototyping (RP) technology due to its ability to build parts having complex geometrical shape in reasonable time period. The quality of built parts depends on many process variables. In this study, the influence of three FDM process parameters namely, slice height, raster angle and raster width on viscoelastic properties of Acrylonitrile Butadiene Styrene (ABS) RP-specimen is studied. Statistically designed experiments have been conducted for finding the optimum process parameter setting for enhancing the storage modulus. Dynamic Mechanical Analysis has been used to understand the viscoelastic properties at various parameter settings. At the optimal parameter setting the storage modulus and loss modulus of the ABS-RP specimen was 1008 and 259.9 MPa respectively. The relative percentage contribution of slice height and raster width on the viscoelastic properties of the FDM-RP components was found to be 55 and 31 % respectively.

An investigation of wash-off controlling parameters at urban and commercial monitoring sites.

PubMed

Berretta, C; Gnecco, I; Lanza, L G; La Barbera, P

2007-01-01

The relationship between the parameters of the wash-off function and the controlling hydrologic variables are investigated in this paper, assuming that the pollutant generation process basically depends on the watershed rainfall-runoff response characteristics. Data collected during an intense monitoring program carried out by the Department of Environmental Engineering of the University of Genova (Italy) within a residential area, an auto dismantler facility, a tourism terminal and a urban waste truck depot are used to this aim. The observed runoff events are classified into different TSS mass delivery processes and the occurrence of the first flush phenomenon is also investigated. The correlation between the mathematical parameters describing the exponential process and the hydrological parameters of the corresponding rainfall-runoff event is analysed: runoff parameters and in particular the maximum flow discharge over the time of concentration of the drainage network are proposed as the controlling factor for the total mass of pollutant that is made available for wash-off during each runoff event.

Catchment Tomography - Joint Estimation of Surface Roughness and Hydraulic Conductivity with the EnKF

NASA Astrophysics Data System (ADS)

Baatz, D.; Kurtz, W.; Hendricks Franssen, H. J.; Vereecken, H.; Kollet, S. J.

2017-12-01

Parameter estimation for physically based, distributed hydrological models becomes increasingly challenging with increasing model complexity. The number of parameters is usually large and the number of observations relatively small, which results in large uncertainties. A moving transmitter - receiver concept to estimate spatially distributed hydrological parameters is presented by catchment tomography. In this concept, precipitation, highly variable in time and space, serves as a moving transmitter. As response to precipitation, runoff and stream discharge are generated along different paths and time scales, depending on surface and subsurface flow properties. Stream water levels are thus an integrated signal of upstream parameters, measured by stream gauges which serve as the receivers. These stream water level observations are assimilated into a distributed hydrological model, which is forced with high resolution, radar based precipitation estimates. Applying a joint state-parameter update with the Ensemble Kalman Filter, the spatially distributed Manning's roughness coefficient and saturated hydraulic conductivity are estimated jointly. The sequential data assimilation continuously integrates new information into the parameter estimation problem, especially during precipitation events. Every precipitation event constrains the possible parameter space. In the approach, forward simulations are performed with ParFlow, a variable saturated subsurface and overland flow model. ParFlow is coupled to the Parallel Data Assimilation Framework for the data assimilation and the joint state-parameter update. In synthetic, 3-dimensional experiments including surface and subsurface flow, hydraulic conductivity and the Manning's coefficient are efficiently estimated with the catchment tomography approach. A joint update of the Manning's coefficient and hydraulic conductivity tends to improve the parameter estimation compared to a single parameter update, especially in cases of biased initial parameter ensembles. The computational experiments additionally show to which degree of spatial heterogeneity and to which degree of uncertainty of subsurface flow parameters the Manning's coefficient and hydraulic conductivity can be estimated efficiently.

Hydrodynamics of pedestrians' instability in floodwaters

NASA Astrophysics Data System (ADS)

Arrighi, Chiara; Oumeraci, Hocine; Castelli, Fabio

2017-01-01

People's safety is the first objective to be fulfilled by flood risk mitigation measures, and according to existing reports on the causes of casualties, most of the fatalities are due to inappropriate behaviour such as walking or driving in floodwaters. Currently available experimental data on people instability in floodwaters suffer from a large dispersion primarily depending on the large variability of the physical characteristics of the subjects. This paper introduces a dimensionless mobility parameter θP for people partly immersed in flood flows, which accounts for both flood and subject characteristics. The parameter θP is capable of identifying a unique threshold of instability depending on a Froude number, thus reducing the scatter of existing experimental data. Moreover, a three-dimensional (3-D) numerical model describing the detailed geometry of a human body and reproducing a selection of critical pairs of water depth and velocity is presented. The numerical results in terms of hydrodynamic forces and force coefficients are analysed and discussed. Both the mobility parameter θP and the numerical results hint at the crucial role of the Froude number and relative submergence as the most relevant dimensionless numbers to interpret the loss of stability. Finally, the mobility parameter θP is compared with an analogous dimensionless parameter for vehicles' instability in floodwaters, providing a new contribution to support flood risk management and educating people.

Generalized correlation integral vectors: A distance concept for chaotic dynamical systems

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

Haario, Heikki, E-mail: heikki.haario@lut.fi; Kalachev, Leonid, E-mail: KalachevL@mso.umt.edu; Hakkarainen, Janne

2015-06-15

Several concepts of fractal dimension have been developed to characterise properties of attractors of chaotic dynamical systems. Numerical approximations of them must be calculated by finite samples of simulated trajectories. In principle, the quantities should not depend on the choice of the trajectory, as long as it provides properly distributed samples of the underlying attractor. In practice, however, the trajectories are sensitive with respect to varying initial values, small changes of the model parameters, to the choice of a solver, numeric tolerances, etc. The purpose of this paper is to present a statistically sound approach to quantify this variability. Wemore » modify the concept of correlation integral to produce a vector that summarises the variability at all selected scales. The distribution of this stochastic vector can be estimated, and it provides a statistical distance concept between trajectories. Here, we demonstrate the use of the distance for the purpose of estimating model parameters of a chaotic dynamic model. The methodology is illustrated using computational examples for the Lorenz 63 and Lorenz 95 systems, together with a framework for Markov chain Monte Carlo sampling to produce posterior distributions of model parameters.« less

Kinematic analysis of head, trunk, and pelvic motion during mirror therapy for stroke patients

PubMed Central

Kim, Jinmin; Yi, Jaehoon; Song, Chang-Ho

2017-01-01

[Purpose] The purpose of this study was to investigate mirror therapy (MT) condition by analyzing kinematic parameters according to mirror size and angle. [Subjects and Methods] Three hemiparesis stroke patients and five healthy adults participated in this cross-sectional study. Kinematic parameters during the MT were collected over a total of 5 trials for each subject (3 mirror angles × 3 mirror sizes). Center of pressure (COP) excursion data was collected by force plate, and other kinematic parameters by infra-red cameras. [Results] The larger the size and smaller the angle, the overall dependent variables decreased in all participants. Particularly, when virtual reality reflection equipment (VRRE) was used, the value of the flexion and the lateral tilt was the closest to the midline compared to all other independent variables. Moreover, it showed tendency of moving towards the affected side. Based on the results, MT for stroke patients has a disadvantage of shifting weight and leaning towards the unaffected side during therapy. [Conclusion] Therefore, it seems to be more effective in terms of clinics to apply VRRE to make up for the weak parts and provide more elaborate visual feedback. PMID:29184290

Kinematic analysis of head, trunk, and pelvic motion during mirror therapy for stroke patients.

PubMed

Kim, Jinmin; Yi, Jaehoon; Song, Chang-Ho

2017-10-01

[Purpose] The purpose of this study was to investigate mirror therapy (MT) condition by analyzing kinematic parameters according to mirror size and angle. [Subjects and Methods] Three hemiparesis stroke patients and five healthy adults participated in this cross-sectional study. Kinematic parameters during the MT were collected over a total of 5 trials for each subject (3 mirror angles × 3 mirror sizes). Center of pressure (COP) excursion data was collected by force plate, and other kinematic parameters by infra-red cameras. [Results] The larger the size and smaller the angle, the overall dependent variables decreased in all participants. Particularly, when virtual reality reflection equipment (VRRE) was used, the value of the flexion and the lateral tilt was the closest to the midline compared to all other independent variables. Moreover, it showed tendency of moving towards the affected side. Based on the results, MT for stroke patients has a disadvantage of shifting weight and leaning towards the unaffected side during therapy. [Conclusion] Therefore, it seems to be more effective in terms of clinics to apply VRRE to make up for the weak parts and provide more elaborate visual feedback.

Real data assimilation for optimization of frictional parameters and prediction of afterslip in the 2003 Tokachi-oki earthquake inferred from slip velocity by an adjoint method

NASA Astrophysics Data System (ADS)

Kano, Masayuki; Miyazaki, Shin'ichi; Ishikawa, Yoichi; Hiyoshi, Yoshihisa; Ito, Kosuke; Hirahara, Kazuro

2015-10-01

Data assimilation is a technique that optimizes the parameters used in a numerical model with a constraint of model dynamics achieving the better fit to observations. Optimized parameters can be utilized for the subsequent prediction with a numerical model and predicted physical variables are presumably closer to observations that will be available in the future, at least, comparing to those obtained without the optimization through data assimilation. In this work, an adjoint data assimilation system is developed for optimizing a relatively large number of spatially inhomogeneous frictional parameters during the afterslip period in which the physical constraints are a quasi-dynamic equation of motion and a laboratory derived rate and state dependent friction law that describe the temporal evolution of slip velocity at subduction zones. The observed variable is estimated slip velocity on the plate interface. Before applying this method to the real data assimilation for the afterslip of the 2003 Tokachi-oki earthquake, a synthetic data assimilation experiment is conducted to examine the feasibility of optimizing the frictional parameters in the afterslip area. It is confirmed that the current system is capable of optimizing the frictional parameters A-B, A and L by adopting the physical constraint based on a numerical model if observations capture the acceleration and decaying phases of slip on the plate interface. On the other hand, it is unlikely to constrain the frictional parameters in the region where the amplitude of afterslip is less than 1.0 cm d-1. Next, real data assimilation for the 2003 Tokachi-oki earthquake is conducted to incorporate slip velocity data inferred from time dependent inversion of Global Navigation Satellite System time-series. The optimized values of A-B, A and L are O(10 kPa), O(102 kPa) and O(10 mm), respectively. The optimized frictional parameters yield the better fit to the observations and the better prediction skill of slip velocity afterwards. Also, further experiment shows the importance of employing a fine-mesh model. It will contribute to the further understanding of the frictional properties on plate interfaces and lead to the forecasting system that provides useful information on the possibility of consequent earthquakes.

Determination of riverbank erosion probability using Locally Weighted Logistic Regression

NASA Astrophysics Data System (ADS)

Ioannidou, Elena; Flori, Aikaterini; Varouchakis, Emmanouil A.; Giannakis, Georgios; Vozinaki, Anthi Eirini K.; Karatzas, George P.; Nikolaidis, Nikolaos

2015-04-01

Riverbank erosion is a natural geomorphologic process that affects the fluvial environment. The most important issue concerning riverbank erosion is the identification of the vulnerable locations. An alternative to the usual hydrodynamic models to predict vulnerable locations is to quantify the probability of erosion occurrence. This can be achieved by identifying the underlying relations between riverbank erosion and the geomorphological or hydrological variables that prevent or stimulate erosion. Thus, riverbank erosion can be determined by a regression model using independent variables that are considered to affect the erosion process. The impact of such variables may vary spatially, therefore, a non-stationary regression model is preferred instead of a stationary equivalent. Locally Weighted Regression (LWR) is proposed as a suitable choice. This method can be extended to predict the binary presence or absence of erosion based on a series of independent local variables by using the logistic regression model. It is referred to as Locally Weighted Logistic Regression (LWLR). Logistic regression is a type of regression analysis used for predicting the outcome of a categorical dependent variable (e.g. binary response) based on one or more predictor variables. The method can be combined with LWR to assign weights to local independent variables of the dependent one. LWR allows model parameters to vary over space in order to reflect spatial heterogeneity. The probabilities of the possible outcomes are modelled as a function of the independent variables using a logistic function. Logistic regression measures the relationship between a categorical dependent variable and, usually, one or several continuous independent variables by converting the dependent variable to probability scores. Then, a logistic regression is formed, which predicts success or failure of a given binary variable (e.g. erosion presence or absence) for any value of the independent variables. The erosion occurrence probability can be calculated in conjunction with the model deviance regarding the independent variables tested. The most straightforward measure for goodness of fit is the G statistic. It is a simple and effective way to study and evaluate the Logistic Regression model efficiency and the reliability of each independent variable. The developed statistical model is applied to the Koiliaris River Basin on the island of Crete, Greece. Two datasets of river bank slope, river cross-section width and indications of erosion were available for the analysis (12 and 8 locations). Two different types of spatial dependence functions, exponential and tricubic, were examined to determine the local spatial dependence of the independent variables at the measurement locations. The results show a significant improvement when the tricubic function is applied as the erosion probability is accurately predicted at all eight validation locations. Results for the model deviance show that cross-section width is more important than bank slope in the estimation of erosion probability along the Koiliaris riverbanks. The proposed statistical model is a useful tool that quantifies the erosion probability along the riverbanks and can be used to assist managing erosion and flooding events. Acknowledgements This work is part of an on-going THALES project (CYBERSENSORS - High Frequency Monitoring System for Integrated Water Resources Management of Rivers). The project has been co-financed by the European Union (European Social Fund - ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: THALES. Investing in knowledge society through the European Social Fund.

Modelisation numerique de l'hydrologie pour l'aide a la gestion des bassins versants, par l'utilisation conjointe des systemes d'information geographique et de la methode des elements finis un nouvel outil pour le developpement durable SAGESS

NASA Astrophysics Data System (ADS)

Bel Hadj Kacem, Mohamed Salah

All hydrological processes are affected by the spatial variability of the physical parameters of the watershed, and also by human intervention on the landscape. The water outflow from a watershed strictly depends on the spatial and temporal variabilities of the physical parameters of the watershed. It is now apparent that the integration of mathematical models into GIS's can benefit both GIS and three-dimension environmental models: a true modeling capability can help the modeling community bridge the gap between planners, scientists, decision-makers and end-users. The main goal of this research is to design a practical tool to simulate run-off water surface using Geographic design a practical tool to simulate run-off water surface using Geographic Information Systems and the simulation of the hydrological behavior by the Finite Element Method.

The Lambert Way to Gaussianize Heavy-Tailed Data with the Inverse of Tukey's h Transformation as a Special Case

PubMed Central

Goerg, Georg M.

2015-01-01

I present a parametric, bijective transformation to generate heavy tail versions of arbitrary random variables. The tail behavior of this heavy tail Lambert  W × F X random variable depends on a tail parameter δ ≥ 0: for δ = 0, Y ≡ X, for δ > 0 Y has heavier tails than X. For X being Gaussian it reduces to Tukey's h distribution. The Lambert W function provides an explicit inverse transformation, which can thus remove heavy tails from observed data. It also provides closed-form expressions for the cumulative distribution (cdf) and probability density function (pdf). As a special case, these yield analytic expression for Tukey's h pdf and cdf. Parameters can be estimated by maximum likelihood and applications to S&P 500 log-returns demonstrate the usefulness of the presented methodology. The R package LambertW implements most of the introduced methodology and is publicly available on CRAN. PMID:26380372

Influence of seasonal cycles in Martian atmosphere on entry, descent and landing sequence

NASA Astrophysics Data System (ADS)

Marčeta, Dušan; Šegan, Stevo; Rašuo, Boško

2014-05-01

The phenomena like high eccentricity of Martian orbit, obliquity of the orbital plane and close alignment of the winter solstice and the orbital perihelion, separately or together can significantly alter not only the level of some Martian atmospheric parameters but also the characteristics of its diurnal and seasonal cycle. Considering that entry, descent and landing (EDL) sequence is mainly driven by the density profile of the atmosphere and aerodynamic characteristic of the entry vehicle. We have performed the analysis of the influence of the seasonal cycles of the atmospheric parameters on EDL profiles by using Mars Global Reference Atmospheric Model (Mars-GRAM). Since the height of the deployment of the parachute and the time passed from the deployment to propulsion firing (descent time) are of crucial importance for safe landing and the achievable landing site elevation we paid special attention to the influence of the areocentric longitude of the Sun (Ls) on these variables. We have found that these variables have periodic variability with respect to Ls and can be very well approximated with a sine wave function whose mean value depends only on the landing site elevation while the amplitudes and phases depend only on the landing site latitude. The amplitudes exhibit behavior which is symmetric with respect to the latitude but the symmetry is shifted from the equator to the northern mid-tropics. We have also noticed that the strong temperature inversions which are usual for middle and higher northern latitudes while Mars is around its orbital perihelion significantly alter the descent time without influencing the height of the parachute deployment. At last, we applied our model to determine the dependence of the accessible landing region on Ls and found that this region reaches maximum when Mars is around the orbital perihelion and can vary 50° in latitude throughout the Martian year.

Optimization of the transmission of observable expectation values and observable statistics in continuous-variable teleportation

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

Albano Farias, L.; Stephany, J.

2010-12-15

We analyze the statistics of observables in continuous-variable (CV) quantum teleportation in the formalism of the characteristic function. We derive expressions for average values of output-state observables, in particular, cumulants which are additive in terms of the input state and the resource of teleportation. Working with a general class of teleportation resources, the squeezed-bell-like states, which may be optimized in a free parameter for better teleportation performance, we discuss the relation between resources optimal for fidelity and those optimal for different observable averages. We obtain the values of the free parameter of the squeezed-bell-like states which optimize the central momentamore » and cumulants up to fourth order. For the cumulants the distortion between in and out states due to teleportation depends only on the resource. We obtain optimal parameters {Delta}{sub (2)}{sup opt} and {Delta}{sub (4)}{sup opt} for the second- and fourth-order cumulants, which do not depend on the squeezing of the resource. The second-order central momenta, which are equal to the second-order cumulants, and the photon number average are also optimized by the resource with {Delta}{sub (2)}{sup opt}. We show that the optimal fidelity resource, which has been found previously to depend on the characteristics of input, approaches for high squeezing to the resource that optimizes the second-order momenta. A similar behavior is obtained for the resource that optimizes the photon statistics, which is treated here using the sum of the squared differences in photon probabilities of input versus output states as the distortion measure. This is interpreted naturally to mean that the distortions associated with second-order momenta dominate the behavior of the output state for large squeezing of the resource. Optimal fidelity resources and optimal photon statistics resources are compared, and it is shown that for mixtures of Fock states both resources are equivalent.« less

Effect of soil property uncertainties on permafrost thaw projections: a calibration-constrained analysis

NASA Astrophysics Data System (ADS)

Harp, D. R.; Atchley, A. L.; Painter, S. L.; Coon, E. T.; Wilson, C. J.; Romanovsky, V. E.; Rowland, J. C.

2016-02-01

The effects of soil property uncertainties on permafrost thaw projections are studied using a three-phase subsurface thermal hydrology model and calibration-constrained uncertainty analysis. The null-space Monte Carlo method is used to identify soil hydrothermal parameter combinations that are consistent with borehole temperature measurements at the study site, the Barrow Environmental Observatory. Each parameter combination is then used in a forward projection of permafrost conditions for the 21st century (from calendar year 2006 to 2100) using atmospheric forcings from the Community Earth System Model (CESM) in the Representative Concentration Pathway (RCP) 8.5 greenhouse gas concentration trajectory. A 100-year projection allows for the evaluation of predictive uncertainty (due to soil property (parametric) uncertainty) and the inter-annual climate variability due to year to year differences in CESM climate forcings. After calibrating to measured borehole temperature data at this well-characterized site, soil property uncertainties are still significant and result in significant predictive uncertainties in projected active layer thickness and annual thaw depth-duration even with a specified future climate. Inter-annual climate variability in projected soil moisture content and Stefan number are small. A volume- and time-integrated Stefan number decreases significantly, indicating a shift in subsurface energy utilization in the future climate (latent heat of phase change becomes more important than heat conduction). Out of 10 soil parameters, ALT, annual thaw depth-duration, and Stefan number are highly dependent on mineral soil porosity, while annual mean liquid saturation of the active layer is highly dependent on the mineral soil residual saturation and moderately dependent on peat residual saturation. By comparing the ensemble statistics to the spread of projected permafrost metrics using different climate models, we quantify the relative magnitude of soil property uncertainty to another source of permafrost uncertainty, structural climate model uncertainty. We show that the effect of calibration-constrained uncertainty in soil properties, although significant, is less than that produced by structural climate model uncertainty for this location.

Decision tree analysis in subarachnoid hemorrhage: prediction of outcome parameters during the course of aneurysmal subarachnoid hemorrhage using decision tree analysis.

PubMed

Hostettler, Isabel Charlotte; Muroi, Carl; Richter, Johannes Konstantin; Schmid, Josef; Neidert, Marian Christoph; Seule, Martin; Boss, Oliver; Pangalu, Athina; Germans, Menno Robbert; Keller, Emanuela

2018-01-19

OBJECTIVE The aim of this study was to create prediction models for outcome parameters by decision tree analysis based on clinical and laboratory data in patients with aneurysmal subarachnoid hemorrhage (aSAH). METHODS The database consisted of clinical and laboratory parameters of 548 patients with aSAH who were admitted to the Neurocritical Care Unit, University Hospital Zurich. To examine the model performance, the cohort was randomly divided into a derivation cohort (60% [n = 329]; training data set) and a validation cohort (40% [n = 219]; test data set). The classification and regression tree prediction algorithm was applied to predict death, functional outcome, and ventriculoperitoneal (VP) shunt dependency. Chi-square automatic interaction detection was applied to predict delayed cerebral infarction on days 1, 3, and 7. RESULTS The overall mortality was 18.4%. The accuracy of the decision tree models was good for survival on day 1 and favorable functional outcome at all time points, with a difference between the training and test data sets of < 5%. Prediction accuracy for survival on day 1 was 75.2%. The most important differentiating factor was the interleukin-6 (IL-6) level on day 1. Favorable functional outcome, defined as Glasgow Outcome Scale scores of 4 and 5, was observed in 68.6% of patients. Favorable functional outcome at all time points had a prediction accuracy of 71.1% in the training data set, with procalcitonin on day 1 being the most important differentiating factor at all time points. A total of 148 patients (27%) developed VP shunt dependency. The most important differentiating factor was hyperglycemia on admission. CONCLUSIONS The multiple variable analysis capability of decision trees enables exploration of dependent variables in the context of multiple changing influences over the course of an illness. The decision tree currently generated increases awareness of the early systemic stress response, which is seemingly pertinent for prognostication.

[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.

Propagating uncertainty from hydrology into human health risk assessment

NASA Astrophysics Data System (ADS)

Siirila, E. R.; Maxwell, R. M.

2013-12-01

Hydro-geologic modeling and uncertainty assessment of flow and transport parameters can be incorporated into human health risk (both cancer and non-cancer) assessment to better understand the associated uncertainties. This interdisciplinary approach is needed now more than ever as societal problems concerning water quality are increasingly interdisciplinary as well. For example, uncertainty can originate from environmental conditions such as a lack of information or measurement error, or can manifest as variability, such as differences in physiological and exposure parameters between individuals. To complicate the matter, traditional risk assessment methodologies are independent of time, virtually neglecting any temporal dependence. Here we present not only how uncertainty and variability can be incorporated into a risk assessment, but also how time dependent risk assessment (TDRA) allows for the calculation of risk as a function of time. The development of TDRA and the inclusion of quantitative risk analysis in this research provide a means to inform decision makers faced with water quality issues and challenges. The stochastic nature of this work also provides a means to address the question of uncertainty in management decisions, a component that is frequently difficult to quantify. To illustrate this new formulation and to investigate hydraulic mechanisms for sensitivity, an example of varying environmental concentration signals resulting from rate dependencies in geochemical reactions is used. Cancer risk is computed and compared using environmental concentration ensembles modeled with sorption as 1) a linear equilibrium assumption and 2) first order kinetics. Results show that the up scaling of these small-scale processes controls the distribution, magnitude, and associated uncertainty of cancer risk.

Pulsed Accretion in the T Tauri Binary TWA 3A

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

Tofflemire, Benjamin M.; Mathieu, Robert D.; Herczeg, Gregory J.

TWA 3A is the most recent addition to a small group of young binary systems that both actively accrete from a circumbinary disk and have spectroscopic orbital solutions. As such, it provides a unique opportunity to test binary accretion theory in a well-constrained setting. To examine TWA 3A’s time-variable accretion behavior, we have conducted a two-year, optical photometric monitoring campaign, obtaining dense orbital phase coverage (∼20 observations per orbit) for ∼15 orbital periods. From U -band measurements we derive the time-dependent binary mass accretion rate, finding bursts of accretion near each periastron passage. On average, these enhanced accretion events evolvemore » over orbital phases 0.85 to 1.05, reaching their peak at periastron. The specific accretion rate increases above the quiescent value by a factor of ∼4 on average but the peak can be as high as an order of magnitude in a given orbit. The phase dependence and amplitude of TWA 3A accretion is in good agreement with numerical simulations of binary accretion with similar orbital parameters. In these simulations, periastron accretion bursts are fueled by periodic streams of material from the circumbinary disk that are driven by the binary orbit. We find that TWA 3A’s average accretion behavior is remarkably similar to DQ Tau, another T Tauri binary with similar orbital parameters, but with significantly less variability from orbit to orbit. This is only the second clear case of orbital-phase-dependent accretion in a T Tauri binary.« less

Informing soil models using pedotransfer functions: challenges and perspectives

NASA Astrophysics Data System (ADS)

Pachepsky, Yakov; Romano, Nunzio

2015-04-01

Pedotransfer functions (PTFs) are empirical relationships between parameters of soil models and more easily obtainable data on soil properties. PTFs have become an indispensable tool in modeling soil processes. As alternative methods to direct measurements, they bridge the data we have and data we need by using soil survey and monitoring data to enable modeling for real-world applications. Pedotransfer is extensively used in soil models addressing the most pressing environmental issues. The following is an attempt to provoke a discussion by listing current issues that are faced by PTF development. 1. As more intricate biogeochemical processes are being modeled, development of PTFs for parameters of those processes becomes essential. 2. Since the equations to express PTF relationships are essentially unknown, there has been a trend to employ highly nonlinear equations, e.g. neural networks, which in theory are flexible enough to simulate any dependence. This, however, comes with the penalty of large number of coefficients that are difficult to estimate reliably. A preliminary classification applied to PTF inputs and PTF development for each of the resulting groups may provide simple, transparent, and more reliable pedotransfer equations. 3. The multiplicity of models, i.e. presence of several models producing the same output variables, is commonly found in soil modeling, and is a typical feature in the PTF research field. However, PTF intercomparisons are lagging behind PTF development. This is aggravated by the fact that coefficients of PTF based on machine-learning methods are usually not reported. 4. The existence of PTFs is the result of some soil processes. Using models of those processes to generate PTFs, and more general, developing physics-based PTFs remains to be explored. 5. Estimating the variability of soil model parameters becomes increasingly important, as the newer modeling technologies such as data assimilation, ensemble modeling, and model abstraction, become progressively more popular. The variability PTFs rely on the spatio-temporal dynamics of soil variables, and that opens new sources of PTF inputs stemming from technology advances such as monitoring networks, remote and proximal sensing, and omics. 6. Burgeoning PTF development has not so far affected several persisting regional knowledge gaps. Remarkably little effort was put so far into PTF development for saline soils, calcareous and gypsiferous soils, peat soils, paddy soils, soils with well expressed shrink-swell behavior, and soils affected by freeze-thaw cycles. 7. Soils from tropical regions are quite often considered as a pseudo-entity for which a single PTF can be applied. This assumption will not be needed as more regional data will be accumulated and analyzed. 8. Other advances in regional PTFs will be possible due to presence of large databases on region-specific useful PTF inputs such as moisture equivalent, laser diffractometry data, or soil specific surface. 9. Most of flux models in soils, be it water, solutes, gas, or heat, involve parameters that are scale-dependent. Including scale dependencies in PTFs will be critical to improve PTF usability. 10. Another scale-related matter is pedotransfer for coarse-scale soil modeling, for example, in weather or climate models. Soil hydraulic parameters in these models cannot be measured and the efficiency of the pedotransfer can be evaluated only in terms of its utility. There is a pressing need to determine combinations of pedotransfer and upscaling procedures that can lead to the derivation of suitable coarse-scale soil model parameters. 11. The spatial coarse scale often assumes a coarse temporal support, and that may lead to including in PTFs other environmental variables such as topographic, weather, and management attributes. 12. Some PTF inputs are time- or space-dependent, and yet little is known whether the spatial or temporal structure of PTF outputs is properly predicted from such inputs 13. Further exploration is needed to use PTF as a source of hypotheses on and insights into relationships between soil processes and soil composition as well as between soil structure and soil functioning. PTFs are empirical relationships and their accuracy outside the database used for the PTF development is essentially unknown. Therefore they should never be considered as an ultimate source of parameters in soil modeling. Rather they strive to provide a balance between accuracy and availability. The primary role of PTF is to assist in modeling for screening and comparative purposes, establishing ranges and/or probability distributions of model parameters, and creating realistic synthetic soil datasets and scenarios. Developing and improving PTFs will remain the mainstream way of packaging data and knowledge for applications of soil modeling.

Detrended fluctuation analysis as a regression framework: Estimating dependence at different scales

NASA Astrophysics Data System (ADS)

Kristoufek, Ladislav

2015-02-01

We propose a framework combining detrended fluctuation analysis with standard regression methodology. The method is built on detrended variances and covariances and it is designed to estimate regression parameters at different scales and under potential nonstationarity and power-law correlations. The former feature allows for distinguishing between effects for a pair of variables from different temporal perspectives. The latter ones make the method a significant improvement over the standard least squares estimation. Theoretical claims are supported by Monte Carlo simulations. The method is then applied on selected examples from physics, finance, environmental science, and epidemiology. For most of the studied cases, the relationship between variables of interest varies strongly across scales.

Statistical analysis for understanding and predicting battery degradations in real-life electric vehicle use

NASA Astrophysics Data System (ADS)

Barré, Anthony; Suard, Frédéric; Gérard, Mathias; Montaru, Maxime; Riu, Delphine

2014-01-01

This paper describes the statistical analysis of recorded data parameters of electrical battery ageing during electric vehicle use. These data permit traditional battery ageing investigation based on the evolution of the capacity fade and resistance raise. The measured variables are examined in order to explain the correlation between battery ageing and operating conditions during experiments. Such study enables us to identify the main ageing factors. Then, detailed statistical dependency explorations present the responsible factors on battery ageing phenomena. Predictive battery ageing models are built from this approach. Thereby results demonstrate and quantify a relationship between variables and battery ageing global observations, and also allow accurate battery ageing diagnosis through predictive models.

Adaptable structural synthesis using advanced analysis and optimization coupled by a computer operating system

NASA Technical Reports Server (NTRS)

Sobieszczanski-Sobieski, J.; Bhat, R. B.

1979-01-01

A finite element program is linked with a general purpose optimization program in a 'programing system' which includes user supplied codes that contain problem dependent formulations of the design variables, objective function and constraints. The result is a system adaptable to a wide spectrum of structural optimization problems. In a sample of numerical examples, the design variables are the cross-sectional dimensions and the parameters of overall shape geometry, constraints are applied to stresses, displacements, buckling and vibration characteristics, and structural mass is the objective function. Thin-walled, built-up structures and frameworks are included in the sample. Details of the system organization and characteristics of the component programs are given.

Some rules for polydimensional squeezing

NASA Technical Reports Server (NTRS)

Manko, Vladimir I.

1994-01-01

The review of the following results is presented: For mixed state light of N-mode electromagnetic field described by Wigner function which has generic Gaussian form, the photon distribution function is obtained and expressed explicitly in terms of Hermite polynomials of 2N-variables. The momenta of this distribution are calculated and expressed as functions of matrix invariants of the dispersion matrix. The role of new uncertainty relation depending on photon state mixing parameter is elucidated. New sum rules for Hermite polynomials of several variables are found. The photon statistics of polymode even and odd coherent light and squeezed polymode Schroedinger cat light is given explicitly. Photon distribution for polymode squeezed number states expressed in terms of multivariable Hermite polynomials is discussed.

Seismicity in a model governed by competing frictional weakening and healing mechanisms

NASA Astrophysics Data System (ADS)

Hillers, G.; Carlson, J. M.; Archuleta, R. J.

2009-09-01

Observations from laboratory, field and numerical work spanning a wide range of space and time scales suggest a strain dependent progressive evolution of material properties that control the stability of earthquake faults. The associated weakening mechanisms are counterbalanced by a variety of restrengthening mechanisms. The efficiency of the healing processes depends on local material properties and on rheologic, temperature, and hydraulic conditions. We investigate the relative effects of these competing non-linear feedbacks on seismogenesis in the context of evolving frictional properties, using a mechanical earthquake model that is governed by slip weakening friction. Weakening and strengthening mechanisms are parametrized by the evolution of the frictional control variable-the slip weakening rate R-using empirical relationships obtained from laboratory experiments. In our model, weakening depends on the slip of an earthquake and tends to increase R, following the behaviour of real and simulated frictional interfaces. Healing causes R to decrease and depends on the time passed since the last slip. Results from models with these competing feedbacks are compared with simulations using non-evolving friction. Compared to fixed R conditions, evolving properties result in a significantly increased variability in the system dynamics. We find that for a given set of weakening parameters the resulting seismicity patterns are sensitive to details of the restrengthening process, such as the healing rate b and a lower cutoff time, tc, up to which no significant change in the friction parameter is observed. For relatively large and small cutoff times, the statistics are typical of fixed large and small R values, respectively. However, a wide range of intermediate values leads to significant fluctuations in the internal energy levels. The frequency-size statistics of earthquake occurrence show corresponding non-stationary characteristics on time scales over which negligible fluctuations are observed in the fixed-R case. The progressive evolution implies that-except for extreme weakening and healing rates-faults and fault networks possibly are not well characterized by steady states on typical catalogue time scales, thus highlighting the essential role of memory and history dependence in seismogenesis. The results suggest that an extrapolation to future seismicity occurrence based on temporally limited data may be misleading due to variability in seismicity patterns associated with competing mechanisms that affect fault stability.

Space Weather Activities of IONOLAB Group: TEC Mapping

NASA Astrophysics Data System (ADS)

Arikan, F.; Yilmaz, A.; Arikan, O.; Sayin, I.; Gurun, M.; Akdogan, K. E.; Yildirim, S. A.

2009-04-01

Being a key player in Space Weather, ionospheric variability affects the performance of both communication and navigation systems. To improve the performance of these systems, ionosphere has to be monitored. Total Electron Content (TEC), line integral of the electron density along a ray path, is an important parameter to investigate the ionospheric variability. A cost-effective way of obtaining TEC is by using dual-frequency GPS receivers. Since these measurements are sparse in space, accurate and robust interpolation techniques are needed to interpolate (or map) the TEC distribution for a given region in space. However, the TEC data derived from GPS measurements contain measurement noise, model and computational errors. Thus, it is necessary to analyze the interpolation performance of the techniques on synthetic data sets that can represent various ionospheric states. By this way, interpolation performance of the techniques can be compared over many parameters that can be controlled to represent the desired ionospheric states. In this study, Multiquadrics, Inverse Distance Weighting (IDW), Cubic Splines, Ordinary and Universal Kriging, Random Field Priors (RFP), Multi-Layer Perceptron Neural Network (MLP-NN), and Radial Basis Function Neural Network (RBF-NN) are employed as the spatial interpolation algorithms. These mapping techniques are initially tried on synthetic TEC surfaces for parameter and coefficient optimization and determination of error bounds. Interpolation performance of these methods are compared on synthetic TEC surfaces over the parameters of sampling pattern, number of samples, the variability of the surface and the trend type in the TEC surfaces. By examining the performance of the interpolation methods, it is observed that both Kriging, RFP and NN have important advantages and possible disadvantages depending on the given constraints. It is also observed that the determining parameter in the error performance is the trend in the Ionosphere. Optimization of the algorithms in terms of their performance parameters (like the choice of the semivariogram function for Kriging algorithms and the hidden layer and neuron numbers for MLP-NN) mostly depend on the behavior of the ionosphere at that given time instant for the desired region. The sampling pattern and number of samples are the other important parameters that may contribute to the higher errors in reconstruction. For example, for all of the above listed algorithms, hexagonal regular sampling of the ionosphere provides the lowest reconstruction error and the performance significantly degrades as the samples in the region become sparse and clustered. The optimized models and coefficients are applied to regional GPS-TEC mapping using the IONOLAB-TEC data (www.ionolab.org). Both Kriging combined with Kalman Filter and dynamic modeling of NN are also implemented as first trials of TEC and space weather predictions.

Numerical simulation for heat transfer performance in unsteady flow of Williamson fluid driven by a wedge-geometry

NASA Astrophysics Data System (ADS)

Hamid, Aamir; Hashim; Khan, Masood

2018-06-01

The main concern of this communication is to investigate the two-layer flow of a non-Newtonian rheological fluid past a wedge-shaped geometry. One remarkable aspect of this article is the mathematical formulation for two-dimensional flow of Williamson fluid by incorporating the effect of infinite shear rate viscosity. The impacts of heat transfer mechanism on time-dependent flow field are further studied. At first, we employ the suitable non-dimensional variables to transmute the time-dependent governing flow equations into a system of non-linear ordinary differential equations. The converted conservation equations are numerically integrated subject to physically suitable boundary conditions with the aid of Runge-Kutta Fehlberg integration procedure. The effects of involved pertinent parameters, such as, moving wedge parameter, wedge angle parameter, local Weissenberg number, unsteadiness parameter and Prandtl number on the non-dimensional velocity and temperature distributions have been evaluated. In addition, the numerical values of the local skin friction coefficient and the local Nusselt number are compared and presented through tables. The outcomes of this study indicate that the rate of heat transfer increases with the growth of both wedge angle parameter and unsteadiness parameter. Moreover, a substantial rise in the fluid velocity is observed with enhancement in the viscosity ratio parameter while an opposite trend is true for the non-dimensional temperature field. A comparison is presented between the current study and already published works and results found to be in outstanding agreement. Finally, the main findings of this article are highlighted in the last section.

Reconstruction of normal forms by learning informed observation geometries from data.

PubMed

Yair, Or; Talmon, Ronen; Coifman, Ronald R; Kevrekidis, Ioannis G

2017-09-19

The discovery of physical laws consistent with empirical observations is at the heart of (applied) science and engineering. These laws typically take the form of nonlinear differential equations depending on parameters; dynamical systems theory provides, through the appropriate normal forms, an "intrinsic" prototypical characterization of the types of dynamical regimes accessible to a given model. Using an implementation of data-informed geometry learning, we directly reconstruct the relevant "normal forms": a quantitative mapping from empirical observations to prototypical realizations of the underlying dynamics. Interestingly, the state variables and the parameters of these realizations are inferred from the empirical observations; without prior knowledge or understanding, they parametrize the dynamics intrinsically without explicit reference to fundamental physical quantities.

Global dynamics of oscillator populations under common noise

NASA Astrophysics Data System (ADS)

Braun, W.; Pikovsky, A.; Matias, M. A.; Colet, P.

2012-07-01

Common noise acting on a population of identical oscillators can synchronize them. We develop a description of this process which is not limited to the states close to synchrony, but provides a global picture of the evolution of the ensembles. The theory is based on the Watanabe-Strogatz transformation, allowing us to obtain closed stochastic equations for the global variables. We show that at the initial stage, the order parameter grows linearly in time, while at the later stages the convergence to synchrony is exponentially fast. Furthermore, we extend the theory to nonidentical ensembles with the Lorentzian distribution of natural frequencies and determine the stationary values of the order parameter in dependence on driving noise and mismatch.

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

Ahmad, Zeeshan; Viswanathan, Venkatasubramanian

Here, we investigate the stability of electrodeposition at solid-solid interfaces for materials exhibiting an anisotropic mechanical response. The stability of electrodeposition or resistance to the formation of dendrites is studied within a linear stability analysis. The deformation and stress equations are solved using the Stroh formalism and faithfully recover the boundary conditions at the interface. The stability parameter is used to quantify the stability of different solid-solid interfaces incorporating the full anisotropy of the elastic tensor of the two materials. Our results show a high degree of variability in the stability parameter depending on the crystallographic orientation of the solidsmore » in contact, and point to opportunities for exploiting this effect in developing Li metal anodes.« less

Dynamics of a minimal consumer network with bi-directional influence

NASA Astrophysics Data System (ADS)

Ekaterinchuk, Ekaterina; Jungeilges, Jochen; Ryazanova, Tatyana; Sushko, Iryna

2018-05-01

We study the dynamics of a model of interdependent consumer behavior defined by a family of two-dimensional noninvertible maps. This family belongs to a class of coupled logistic maps with different nonlinearity parameters and coupling terms that depend on one variable only. In our companion paper we considered the case of independent consumers as well as the case of uni-directionally connected consumers. The present paper aims at describing the dynamics in the case of a bi-directional connection. In particular, we investigate the bifurcation structure of the parameter plane associated with the strength of coupling between the consumers, focusing on the mechanisms of qualitative transformations of coexisting attractors and their basins of attraction.

Structure and magnetic properties of ScFe 10Si 2

NASA Astrophysics Data System (ADS)

Bodak, O. I.; Stȩpień-Damm, J.; Drulis, H.; Kotur, B.; Suski, W.; Vagizov, F. G.; Wochowski, K.; Mydlarz, T.

1995-02-01

ScFe 10Si 2 crystallizes in the ThMn 12-type tetragonal structure with the space group I4/mmm and the lattice parameters: a = 0.8280 (1) nm, c = 0.4706 (1) nm and c/ a = 0.57. In the refinement performed for 317 independent reflections and 10 variable parameters, a final discrepancy factor R = 4.69% has been reached. The compound is ferromagnetic below 506 K ( 57Fe ME) and 560 K (magnetic). The distribution of the Fe atoms in the 8( i), 8( j) and 8( f) positions corresponds to 40, 31 and 29%, respectively. The Debye temperature determined from the temperature dependence of the isomer shift is 340 K.

Role of anisotropy in determining stability of electrodeposition at solid-solid interfaces

NASA Astrophysics Data System (ADS)

Ahmad, Zeeshan; Viswanathan, Venkatasubramanian

2017-10-01

We investigate the stability of electrodeposition at solid-solid interfaces for materials exhibiting an anisotropic mechanical response. The stability of electrodeposition or resistance to the formation of dendrites is studied within a linear stability analysis. The deformation and stress equations are solved using the Stroh formalism and faithfully recover the boundary conditions at the interface. The stability parameter is used to quantify the stability of different solid-solid interfaces incorporating the full anisotropy of the elastic tensor of the two materials. Results show a high degree of variability in the stability parameter depending on the crystallographic orientation of the solids in contact, and point to opportunities for exploiting this effect in developing Li metal anodes.

Assessing the Uncertainties on Seismic Source Parameters: Towards Realistic Estimates of Moment Tensor Determinations

NASA Astrophysics Data System (ADS)

Magnoni, F.; Scognamiglio, L.; Tinti, E.; Casarotti, E.

2014-12-01

Seismic moment tensor is one of the most important source parameters defining the earthquake dimension and style of the activated fault. Moment tensor catalogues are ordinarily used by geoscientists, however, few attempts have been done to assess possible impacts of moment magnitude uncertainties upon their own analysis. The 2012 May 20 Emilia mainshock is a representative event since it is defined in literature with a moment magnitude value (Mw) spanning between 5.63 and 6.12. An uncertainty of ~0.5 units in magnitude leads to a controversial knowledge of the real size of the event. The possible uncertainty associated to this estimate could be critical for the inference of other seismological parameters, suggesting caution for seismic hazard assessment, coulomb stress transfer determination and other analyses where self-consistency is important. In this work, we focus on the variability of the moment tensor solution, highlighting the effect of four different velocity models, different types and ranges of filtering, and two different methodologies. Using a larger dataset, to better quantify the source parameter uncertainty, we also analyze the variability of the moment tensor solutions depending on the number, the epicentral distance and the azimuth of used stations. We endorse that the estimate of seismic moment from moment tensor solutions, as well as the estimate of the other kinematic source parameters, cannot be considered an absolute value and requires to come out with the related uncertainties and in a reproducible framework characterized by disclosed assumptions and explicit processing workflows.

Agreement in cardiovascular risk rating based on anthropometric parameters

PubMed Central

Dantas, Endilly Maria da Silva; Pinto, Cristiane Jordânia; Freitas, Rodrigo Pegado de Abreu; de Medeiros, Anna Cecília Queiroz

2015-01-01

Objective To investigate the agreement in evaluation of risk of developing cardiovascular diseases based on anthropometric parameters in young adults. Methods The study included 406 students, measuring weight, height, and waist and neck circumferences. Waist-to-height ratio and the conicity index. The kappa coefficient was used to assess agreement in risk classification for cardiovascular diseases. The positive and negative specific agreement values were calculated as well. The Pearson chi-square (χ2) test was used to assess associations between categorical variables (p<0.05). Results The majority of the parameters assessed (44%) showed slight (k=0.21 to 0.40) and/or poor agreement (k<0.20), with low values of negative specific agreement. The best agreement was observed between waist circumference and waist-to-height ratio both for the general population (k=0.88) and between sexes (k=0.93 to 0.86). There was a significant association (p<0.001) between the risk of cardiovascular diseases and females when using waist circumference and conicity index, and with males when using neck circumference. This resulted in a wide variation in the prevalence of cardiovascular disease risk (5.5%-36.5%), depending on the parameter and the sex that was assessed. Conclusion The results indicate variability in agreement in assessing risk for cardiovascular diseases, based on anthropometric parameters, and which also seems to be influenced by sex. Further studies in the Brazilian population are required to better understand this issue. PMID:26466060

Effects of climate change on evapotranspiration over the Okavango Delta water resources

NASA Astrophysics Data System (ADS)

Moses, Oliver; Hambira, Wame L.

2018-06-01

In semi-arid developing countries, most poor people depend on contaminated surface or groundwater resources since they do not have access to safe and centrally supplied water. These water resources are threatened by several factors that include high evapotranspiration rates. In the Okavango Delta region in the north-western Botswana, communities facing insufficient centrally supplied water rely mainly on the surface water resources of the Delta. The Delta loses about 98% of its water through evapotranspiration. However, the 2% remaining water rescues the communities facing insufficient water from the main stream water supply. To understand the effects of climate change on evapotranspiration over the Okavango Delta water resources, this study analysed trends in the main climatic parameters needed as input variables in evapotranspiration models. The Mann Kendall test was used in the analysis. Trend analysis is crucial since it reveals the direction of trends in the climatic parameters, which is helpful in determining the effects of climate change on evapotranspiration. The main climatic parameters required as input variables in evapotranspiration models that were of interest in this study were wind speeds, solar radiation and relative humidity. Very little research has been conducted on these climatic parameters in the Okavango Delta region. The conducted trend analysis was more on wind speeds, which had relatively longer data records than the other two climatic parameters of interest. Generally, statistically significant increasing trends have been found, which suggests that climate change is likely to further increase evapotranspiration over the Okavango Delta water resources.

Evaluation of GIS Technology in Assessing and Modeling Land Management Practices

NASA Technical Reports Server (NTRS)

Archer, F.; Coleman, T. L.; Manu, A.; Tadesse, W.; Liu, G.

1997-01-01

There is an increasing concern of land owners to protect and maintain healthy and sustainable agroecosystems through the implementation of best management practices (BMP). The objectives of this study were: (1) To develop and evaluate the use of a Geographic Information System (GIS) technology for enhancing field-scale management practices; (2) evaluate the use of 2-dimensional displays of the landscape and (3) define spatial classes of variables from interpretation of geostatistical parameters. Soil samples were collected to a depth of 2 m at 15 cm increments. Existing data from topographic, land use, and soil survey maps of the Winfred Thomas Agricultural Research Station were converted to digital format. Additional soils data which included texture, pH, and organic matter were also generated. The digitized parameters were used to create a multilayered field-scale GIS. Two dimensional (2-D) displays of the parameters were generated using the ARC/INFO software. The spatial distribution of the parameters evaluated in both fields were similar which could be attributed to the similarity in vegetation and surface elevation. The ratio of the nugget to total semivariance, expressed as a percentage, was used to assess the degree of spatial variability. The results indicated that most of the parameters were moderate spatially dependent Biophysical constraint maps were generated from the database layers, and used in multiple combination to visualize results of the BMP. Understanding the spatial relationships of physical and chemical parameters that exists within a field should enable land managers to more effectively implement BMP to ensure a safe and sustainable environment.

Fragmentation uncertainties in hadronic observables for top-quark mass measurements

NASA Astrophysics Data System (ADS)

Corcella, Gennaro; Franceschini, Roberto; Kim, Doojin

2018-04-01

We study the Monte Carlo uncertainties due to modeling of hadronization and showering in the extraction of the top-quark mass from observables that use exclusive hadronic final states in top decays, such as t →anything + J / ψ or t →anything + (B →charged tracks), where B is a B-hadron. To this end, we investigate the sensitivity of the top-quark mass, determined by means of a few observables already proposed in the literature as well as some new proposals, to the relevant parameters of event generators, such as HERWIG 6 and PYTHIA 8. We find that constraining those parameters at O (1%- 10%) is required to avoid a Monte Carlo uncertainty on mt greater than 500 MeV. For the sake of achieving the needed accuracy on such parameters, we examine the sensitivity of the top-quark mass measured from spectral features, such as peaks, endpoints and distributions of EB, mBℓ, and some mT2-like variables. We find that restricting oneself to regions sufficiently close to the endpoints enables one to substantially decrease the dependence on the Monte Carlo parameters, but at the price of inflating significantly the statistical uncertainties. To ameliorate this situation we study how well the data on top-quark production and decay at the LHC can be utilized to constrain the showering and hadronization variables. We find that a global exploration of several calibration observables, sensitive to the Monte Carlo parameters but very mildly to mt, can offer useful constraints on the parameters, as long as such quantities are measured with a 1% precision.

Vineyard zonal management for grape quality assessment by combining airborne remote sensed imagery and soil sensors

NASA Astrophysics Data System (ADS)

Bonilla, I.; Martínez De Toda, F.; Martínez-Casasnovas, J. A.

2014-10-01

Vineyard variability within the fields is well known by grape growers, producing different plant responses and fruit characteristics. Many technologies have been developed in last recent decades in order to assess this spatial variability, including remote sensing and soil sensors. In this paper we study the possibility of creating a stable classification system that better provides useful information for the grower, especially in terms of grape batch quality sorting. The work was carried out during 4 years in a rain-fed Tempranillo vineyard located in Rioja (Spain). NDVI was extracted from airborne imagery, and soil conductivity (EC) data was acquired by an EM38 sensor. Fifty-four vines were sampled at véraison for vegetative parameters and before harvest for yield and grape analysis. An Isocluster unsupervised classification in two classes was performed in 5 different ways, combining NDVI maps individually, collectively and combined with EC. The target vines were assigned in different zones depending on the clustering combination. Analysis of variance was performed in order to verify the ability of the combinations to provide the most accurate information. All combinations showed a similar behaviour concerning vegetative parameters. Yield parameters classify better by the EC-based clustering, whilst maturity grape parameters seemed to give more accuracy by combining all NDVIs and EC. Quality grape parameters (anthocyanins and phenolics), presented similar results for all combinations except for the NDVI map of the individual year, where the results were poorer. This results reveal that stable parameters (EC or/and NDVI all-together) clustering outcomes in better information for a vineyard zonal management strategy.

A fuzzy adaptive network approach to parameter estimation in cases where independent variables come from an exponential distribution

NASA Astrophysics Data System (ADS)

Dalkilic, Turkan Erbay; Apaydin, Aysen

2009-11-01

In a regression analysis, it is assumed that the observations come from a single class in a data cluster and the simple functional relationship between the dependent and independent variables can be expressed using the general model; Y=f(X)+[epsilon]. However; a data cluster may consist of a combination of observations that have different distributions that are derived from different clusters. When faced with issues of estimating a regression model for fuzzy inputs that have been derived from different distributions, this regression model has been termed the [`]switching regression model' and it is expressed with . Here li indicates the class number of each independent variable and p is indicative of the number of independent variables [J.R. Jang, ANFIS: Adaptive-network-based fuzzy inference system, IEEE Transaction on Systems, Man and Cybernetics 23 (3) (1993) 665-685; M. Michel, Fuzzy clustering and switching regression models using ambiguity and distance rejects, Fuzzy Sets and Systems 122 (2001) 363-399; E.Q. Richard, A new approach to estimating switching regressions, Journal of the American Statistical Association 67 (338) (1972) 306-310]. In this study, adaptive networks have been used to construct a model that has been formed by gathering obtained models. There are methods that suggest the class numbers of independent variables heuristically. Alternatively, in defining the optimal class number of independent variables, the use of suggested validity criterion for fuzzy clustering has been aimed. In the case that independent variables have an exponential distribution, an algorithm has been suggested for defining the unknown parameter of the switching regression model and for obtaining the estimated values after obtaining an optimal membership function, which is suitable for exponential distribution.

Objective assessment of gait in xylazine-induced ataxic horses.

PubMed

Nout-Lomas, Y S; Page, K M; Kang, H G; Aanstoos, M E; Greene, H M

2017-05-01

There is poor agreement between observers of equine neurological gait abnormalities using the modified Mayhew grading scale. To stimulate a dose-dependent ataxia in horses through xylazine administration and identify quantifiable relevant gait parameters. Balanced, randomised, 2-way crossover design. Eight horses were assessed before and after administration of xylazine (low dose and high dose). Gait analyses performed before and after xylazine administration included: 1) kinematic data collected on an equine high-speed treadmill (flat and 10% decline) and from accelerometers placed on head and sacrum; and 2) kinetic data collected on a force plate. All horses developed dose-dependent ataxia. Horses developed a dose-dependent increased stride time, stride length, and time of contact (P<0.0001), and a decreased stride frequency (P<0.0002) after administration of xylazine. Although pelvic acceleration increased in the mediolateral direction (P<0.05) in horses walked on the treadmill, this movement decreased when walking over ground after administration of xylazine (P<0.05). Furthermore, centre of pressure and path length indices changed significantly in horses following administration of xylazine (P<0.05). This study examined one breed of horse (Arabian), all of similar height and weight. Accelerometers were attached to skin, not bone; no correction was made for artefacts from skin displacement. The sedative drug effect is of certain duration, limiting the data collection period. Administration of xylazine induced a dose-dependent ataxia in horses and resulted in significant changes of gait parameters, pelvic accelerations, and stabilographic variables, some of which changed in a dose-dependent fashion. Some of the altered gait parameters in this model were probably a result of overall slowing down of the stride cycle secondary to the sedative effect. Continued efforts to discover and evaluate quantifiable gait parameters that are susceptible to change following development of clinical neurological disease in horses is warranted. © 2016 EVJ Ltd.

HRV Analysis to Identify Stages of Home-based Telerehabilitation Exercise.

PubMed

Jeong, In Cheol; Finkelstein, Joseph

2014-01-01

Spectral analysis of heart rate variability (HRV) has been widely used to investigate activity of autonomous nervous system. Previous studies demonstrated potential of analysis of short-term sequences of heart rate data in a time domain for continuous monitoring of levels of physiological stress however the value of HRV parameters in frequency domain for monitoring cycling exercise has not been established. The goal of this study was to assess whether HRV parameters in frequency domain differ depending on a stage of cycling exercise. We compared major HRV parameters in high, low and very low frequency ranges during rest, height of exercise, and recovery during cycling exercise. Our results indicated responsiveness of frequency-domain indices to different phases of cycling exercise program and their potential in monitoring autonomic balance and stress levels as a part of a tailored home-based telerehabilitation program.

Optimal configuration of partial Mueller matrix polarimeter for measuring the ellipsometric parameters in the presence of Poisson shot noise and Gaussian noise

NASA Astrophysics Data System (ADS)

Quan, Naicheng; Zhang, Chunmin; Mu, Tingkui

2018-05-01

We address the optimal configuration of a partial Mueller matrix polarimeter used to determine the ellipsometric parameters in the presence of additive Gaussian noise and signal-dependent shot noise. The numerical results show that, for the PSG/PSA consisting of a variable retarder and a fixed polarizer, the detection process immune to these two types of noise can be optimally composed by 121.2° retardation with a pair of azimuths ±71.34° and a 144.48° retardation with a pair of azimuths ±31.56° for four Mueller matrix elements measurement. Compared with the existing configurations, the configuration presented in this paper can effectively decrease the measurement variance and thus statistically improve the measurement precision of the ellipsometric parameters.

Parameter identification using a creeping-random-search algorithm

NASA Technical Reports Server (NTRS)

Parrish, R. V.

1971-01-01

A creeping-random-search algorithm is applied to different types of problems in the field of parameter identification. The studies are intended to demonstrate that a random-search algorithm can be applied successfully to these various problems, which often cannot be handled by conventional deterministic methods, and, also, to introduce methods that speed convergence to an extremal of the problem under investigation. Six two-parameter identification problems with analytic solutions are solved, and two application problems are discussed in some detail. Results of the study show that a modified version of the basic creeping-random-search algorithm chosen does speed convergence in comparison with the unmodified version. The results also show that the algorithm can successfully solve problems that contain limits on state or control variables, inequality constraints (both independent and dependent, and linear and nonlinear), or stochastic models.

Evidence for history-dependence of influenza pandemic emergence

NASA Astrophysics Data System (ADS)

Hill, Edward M.; Tildesley, Michael J.; House, Thomas

2017-03-01

Influenza A viruses have caused a number of global pandemics, with considerable mortality in humans. Here, we analyse the time periods between influenza pandemics since 1700 under different assumptions to determine whether the emergence of new pandemic strains is a memoryless or history-dependent process. Bayesian model selection between exponential and gamma distributions for these time periods gives support to the hypothesis of history-dependence under eight out of nine sets of modelling assumptions. Using the fitted parameters to make predictions shows a high level of variability in the modelled number of pandemics from 2010-2110. The approach we take here relies on limited data, so is uncertain, but it provides cheap, safe and direct evidence relating to pandemic emergence, a field where indirect measurements are often made at great risk and cost.

Sensor fault diagnosis of singular delayed LPV systems with inexact parameters: an uncertain system approach

NASA Astrophysics Data System (ADS)

Hassanabadi, Amir Hossein; Shafiee, Masoud; Puig, Vicenc

2018-01-01

In this paper, sensor fault diagnosis of a singular delayed linear parameter varying (LPV) system is considered. In the considered system, the model matrices are dependent on some parameters which are real-time measurable. The case of inexact parameter measurements is considered which is close to real situations. Fault diagnosis in this system is achieved via fault estimation. For this purpose, an augmented system is created by including sensor faults as additional system states. Then, an unknown input observer (UIO) is designed which estimates both the system states and the faults in the presence of measurement noise, disturbances and uncertainty induced by inexact measured parameters. Error dynamics and the original system constitute an uncertain system due to inconsistencies between real and measured values of the parameters. Then, the robust estimation of the system states and the faults are achieved with H∞ performance and formulated with a set of linear matrix inequalities (LMIs). The designed UIO is also applicable for fault diagnosis of singular delayed LPV systems with unmeasurable scheduling variables. The efficiency of the proposed approach is illustrated with an example.

Multi-objective optimization of combustion, performance and emission parameters in a jatropha biodiesel engine using Non-dominated sorting genetic algorithm-II

NASA Astrophysics Data System (ADS)

Dhingra, Sunil; Bhushan, Gian; Dubey, Kashyap Kumar

2014-03-01

The present work studies and identifies the different variables that affect the output parameters involved in a single cylinder direct injection compression ignition (CI) engine using jatropha biodiesel. Response surface methodology based on Central composite design (CCD) is used to design the experiments. Mathematical models are developed for combustion parameters (Brake specific fuel consumption (BSFC) and peak cylinder pressure (Pmax)), performance parameter brake thermal efficiency (BTE) and emission parameters (CO, NO x , unburnt HC and smoke) using regression techniques. These regression equations are further utilized for simultaneous optimization of combustion (BSFC, Pmax), performance (BTE) and emission (CO, NO x , HC, smoke) parameters. As the objective is to maximize BTE and minimize BSFC, Pmax, CO, NO x , HC, smoke, a multiobjective optimization problem is formulated. Nondominated sorting genetic algorithm-II is used in predicting the Pareto optimal sets of solution. Experiments are performed at suitable optimal solutions for predicting the combustion, performance and emission parameters to check the adequacy of the proposed model. The Pareto optimal sets of solution can be used as guidelines for the end users to select optimal combination of engine output and emission parameters depending upon their own requirements.

X-Ray and UV Orbital Phase Dependence in LMC X-3

NASA Technical Reports Server (NTRS)

Dolan, Joseph F.; Boyd, P. T.; Smale, A. P.

2001-01-01

The black-hole binary LMC X-3 is known to be variable on time scales of days to years. We investigated X-ray and ultraviolet variability in the system as a function of the 1.7 d binary orbit using a 6.4 day observation with the Rossi X-ray Timing Explorer (RXTE) in 1998 December. An abrupt 14 % flux decrease lasting nearly an entire orbit was followed by a return to previous flux levels. This behavior occurred twice at nearly the same binary phase, but is not present in consecutive orbits. When the X-ray flux is at lower intensity, a periodic amplitude modulation of 7 % is evident in data folded modulo the orbital period. The higher intensity data show weaker correlation with phase. This is the first report of X-ray variability at the orbital period of LMC X-3. Archival RXTE observations of LMC X-3 during a high flux state in 1996 December show similar phase dependence. An ultraviolet light curve obtained with the High Speed Photometer (HSP) on the Hubble Space Telescope (HST) shows a phase dependent variability consistent with that observed in the visible, ascribed to the ellipsoidal variation of the visible star. The X-ray spectrum of LMC X-3 is acceptably represented by a phenomenological disk black-body plus a power law. Changes in the spectrum of LMX X-3 during our observations are compatible with earlier observations during which variations in the 2-10 keV flux are closely correlated with the disk geometry spectral model parameter.

The interrelationship between disease severity, dynamic stability, and falls in cerebellar ataxia.

PubMed

Schniepp, Roman; Schlick, Cornelia; Pradhan, Cauchy; Dieterich, Marianne; Brandt, Thomas; Jahn, Klaus; Wuehr, Max

2016-07-01

Cerebellar ataxia (CA) results in discoordination of body movements (ataxia), a gait disorder, and falls. All three aspects appear to be obviously interrelated; however, experimental evidence is sparse. This study systematically correlated the clinical rating of the severity of ataxia with dynamic stability measures and the fall frequency in patients with CA. Clinical severity of CA in patients with sporadic (n = 34) and hereditary (n = 24) forms was assessed with the Scale for the Assessment and Rating of Ataxia (SARA). Gait performance was examined during slow, preferred, and maximally fast walking speeds. Spatiotemporal variability parameters in the fore-aft and medio-lateral directions were analyzed. The fall frequency was assessed using a standardized interview about fall events within the last 6 months. Fore-aft gait variability showed significant speed-dependent characteristics with highest magnitudes during slow and fast walking. The SARA score correlated positively with fore-aft gait variability, most prominently during fast walking. The fall frequency was significantly associated to fore-aft gait variability during slow walking. Severity of ataxia, dynamic stability, and the occurrence of falls were interrelated in a speed-dependent manner: (a) Severity of ataxia symptoms was closely related to instability during fast walking. (b) Fall frequency was associated with instability during slow walking. These findings suggest the presence of a speed-dependent, twofold cerebellar locomotor control. Assessment of gait performance during non-preferred, slow and fast walking speeds provides novel insights into the pathophysiology of cerebellar locomotor control and may become a useful approach in the clinical evaluation of patients with CA.

A delay differential model of ENSO variability: parametric instability and the distribution of extremes

NASA Astrophysics Data System (ADS)

Zaliapin, I.; Ghil, M.; Thompson, S.

2007-12-01

We consider a Delay Differential Equation (DDE) model for El-Nino Southern Oscillation (ENSO) variability. The model combines two key mechanisms that participate in the ENSO dynamics: delayed negative feedback and seasonal forcing. Descriptive and metric stability analyses of the model are performed in a complete 3D space of its physically relevant parameters. Existence of two regimes --- stable and unstable --- is reported. The domains of the regimes are separated by a sharp neutral curve in the parameter space. The detailed structure of the neutral curve become very complicated (possibly fractal), and individual trajectories within the unstable region become highly complex (possibly chaotic) as the atmosphere-ocean coupling increases. In the unstable regime, spontaneous transitions in the mean "temperature" (i.e., thermocline depth), period, and extreme annual values occur, for purely periodic, seasonal forcing. This indicates (via the continuous dependence theorem) the existence of numerous unstable solutions responsible for the complex dynamics of the system. In the stable regime, only periodic solutions are found. Our results illustrate the role of the distinct parameters of ENSO variability, such as strength of seasonal forcing vs. atmosphere ocean coupling and propagation period of oceanic waves across the Tropical Pacific. The model reproduces, among other phenomena, the Devil's bleachers (caused by period locking) documented in other ENSO models, such as nonlinear PDEs and GCMs, as well as in certain observations. We expect such behavior in much more detailed and realistic models, where it is harder to describe its causes as completely.

Characterizating Multi-layered Coastal Aquifer using Pneumatic Slug Tests

NASA Astrophysics Data System (ADS)

Malama, B.; Abere, M.; Mikenna, M.

2016-12-01

Results of pneumatic slug tests conducted in a monitoring wells of a shallow aquifer on the California Central Coast are presented. The aquifer is in the Los Osos groundwater basin on the California Central Coast, a semi-closed near-triangular groundwater basin bounded to the north and south by impermeable igneousbed rock and to the west by the Pacific Ocean. The groundwater basin is a multi-layered system comprising a perched, near-surface semi-confined, and a deep confined aquifer. The unincorporated community of Los Osos is wholly dependent on the groundwater basin that is threatened with seawater intrusion and nitratecontamination. The slug tests reported here were performed in the perched and semi-confined aquifers as part of a seawater intrusion characterization study. The semi-confined and confined aquifers show evidence of seawater intrusion with upconing in some deep aquifer municipal wells. The upconing has beeninterpreted by previous studies as evidence of preferential flow through a high permeability channel. The objective of the work was to test this hypothesis by mapping the horizontal and vertical spatial variability of hydraulic parameters across the basin and establish the extent of the high permeability unit.Here only preliminary results of slug tests conducted across the basin for vertically averaged hydraulic parameters are reported. The results provide an indication of the horizontal variability of hydraulic parameters. An additional study will be performed to characterize the vertical variability to investigate the probableexistsence of a high permeability channel.

Performance of nonlinear mixed effects models in the presence of informative dropout.

PubMed

Björnsson, Marcus A; Friberg, Lena E; Simonsson, Ulrika S H

2015-01-01

Informative dropout can lead to bias in statistical analyses if not handled appropriately. The objective of this simulation study was to investigate the performance of nonlinear mixed effects models with regard to bias and precision, with and without handling informative dropout. An efficacy variable and dropout depending on that efficacy variable were simulated and model parameters were reestimated, with or without including a dropout model. The Laplace and FOCE-I estimation methods in NONMEM 7, and the stochastic simulations and estimations (SSE) functionality in PsN, were used in the analysis. For the base scenario, bias was low, less than 5% for all fixed effects parameters, when a dropout model was used in the estimations. When a dropout model was not included, bias increased up to 8% for the Laplace method and up to 21% if the FOCE-I estimation method was applied. The bias increased with decreasing number of observations per subject, increasing placebo effect and increasing dropout rate, but was relatively unaffected by the number of subjects in the study. This study illustrates that ignoring informative dropout can lead to biased parameters in nonlinear mixed effects modeling, but even in cases with few observations or high dropout rate, the bias is relatively low and only translates into small effects on predictions of the underlying effect variable. A dropout model is, however, crucial in the presence of informative dropout in order to make realistic simulations of trial outcomes.

Individual movement behavior, matrix heterogeneity, and the dynamics of spatially structured populations.

PubMed

Revilla, Eloy; Wiegand, Thorsten

2008-12-09

The dynamics of spatially structured populations is characterized by within- and between-patch processes. The available theory describes the latter with simple distance-dependent functions that depend on landscape properties such as interpatch distance or patch size. Despite its potential role, we lack a good mechanistic understanding of how the movement of individuals between patches affects the dynamics of these populations. We used the theoretical framework provided by movement ecology to make a direct representation of the processes determining how individuals connect local populations in a spatially structured population of Iberian lynx. Interpatch processes depended on the heterogeneity of the matrix where patches are embedded and the parameters defining individual movement behavior. They were also very sensitive to the dynamic demographic variables limiting the time moving, the within-patch dynamics of available settlement sites (both spatiotemporally heterogeneous) and the response of individuals to the perceived risk while moving. These context-dependent dynamic factors are an inherent part of the movement process, producing connectivities and dispersal kernels whose variability is affected by other demographic processes. Mechanistic representations of interpatch movements, such as the one provided by the movement-ecology framework, permit the dynamic interaction of birth-death processes and individual movement behavior, thus improving our understanding of stochastic spatially structured populations.

Bounds for the price of discrete arithmetic Asian options

NASA Astrophysics Data System (ADS)

Vanmaele, M.; Deelstra, G.; Liinev, J.; Dhaene, J.; Goovaerts, M. J.

2006-01-01

In this paper the pricing of European-style discrete arithmetic Asian options with fixed and floating strike is studied by deriving analytical lower and upper bounds. In our approach we use a general technique for deriving upper (and lower) bounds for stop-loss premiums of sums of dependent random variables, as explained in Kaas et al. (Ins. Math. Econom. 27 (2000) 151-168), and additionally, the ideas of Rogers and Shi (J. Appl. Probab. 32 (1995) 1077-1088) and of Nielsen and Sandmann (J. Financial Quant. Anal. 38(2) (2003) 449-473). We are able to create a unifying framework for European-style discrete arithmetic Asian options through these bounds, that generalizes several approaches in the literature as well as improves the existing results. We obtain analytical and easily computable bounds. The aim of the paper is to formulate an advice of the appropriate choice of the bounds given the parameters, investigate the effect of different conditioning variables and compare their efficiency numerically. Several sets of numerical results are included. We also discuss hedging using these bounds. Moreover, our methods are applicable to a wide range of (pricing) problems involving a sum of dependent random variables.

A model of a fishery with fish stock involving delay equations.

PubMed

Auger, P; Ducrot, Arnaud

2009-12-13

The aim of this paper is to provide a new mathematical model for a fishery by including a stock variable for the resource. This model takes the form of an infinite delay differential equation. It is mathematically studied and a bifurcation analysis of the steady states is fulfilled. Depending on the different parameters of the problem, we show that Hopf bifurcation may occur leading to oscillating behaviours of the system. The mathematical results are finally discussed.

Unsupervised Domain Adaptation with Multiple Acoustic Models

DTIC Science & Technology

2010-12-01

Discriminative MAP Adaptation Standard ML-MAP has been extended to incorporate discrim- inative training criteria such as MMI and MPE [10]. Dis- criminative MAP...smoothing variable I . For example, the MMI - MAP mean is given by ( mmi -map) jm = fnumjm (O) den jm(O)g+Djm̂jm + I (ml-map) jm f numjm den... MMI training, and Djm is the Gaussian-dependent parameter for the extended Baum-Welch (EBW) algorithm. MMI -MAP has been successfully applied in

Safety parameters for avoiding acute ocular damage from the reflected CO2 (10.6 microns) laser beam.

PubMed

Friedman, N R; Saleeby, E R; Rubin, M G; Sandu, T; Krull, E A

1987-11-01

Reflections from instruments in the surgical field involving the CO2 laser beam present a serious ocular hazard. In addition to the use of plastic or glass protective eyewear, this hazard can be minimized by utilizing anodized instruments and recognizing the specific distances at which various reflections are no longer hazardous depending upon certain variables, including laser output wattage, emergent beam lengths, and surface characteristics of the reflecting instruments.

Wheelchair Propulsion Biomechanics in Junior Basketball Players: A Method for the Evaluation of the Efficacy of a Specific Training Program

PubMed Central

Bergamini, Elena; Morelli, Francesca; Marchetti, Flavia; Vannozzi, Giuseppe; Polidori, Lorenzo; Paradisi, Francesco; Traballesi, Marco; Cappozzo, Aurelio

2015-01-01

As participation in wheelchair sports increases, the need of quantitative assessment of biomechanical performance indicators and of sports- and population-specific training protocols has become central. The present study focuses on junior wheelchair basketball and aims at (i) proposing a method to identify biomechanical performance indicators of wheelchair propulsion using an instrumented in-field test and (ii) developing a training program specific for the considered population and assessing its efficacy using the proposed method. Twelve athletes (10 M, 2 F, age = 17.1 ± 2.7 years, years of practice = 4.5 ± 1.8) equipped with wheelchair- and wrist-mounted inertial sensors performed a 20-metre sprint test. Biomechanical parameters related to propulsion timing, progression force, and coordination were estimated from the measured accelerations and used in a regression model where the time to complete the test was set as dependent variable. Force- and coordination-related parameters accounted for 80% of the dependent variable variance. Based on these results, a training program was designed and administered for three months to six of the athletes (the others acting as control group). The biomechanical indicators proved to be effective in providing additional information about the wheelchair propulsion technique with respect to the final test outcome and demonstrated the efficacy of the developed program. PMID:26543852

Outcome-Dependent Sampling with Interval-Censored Failure Time Data

PubMed Central

Zhou, Qingning; Cai, Jianwen; Zhou, Haibo

2017-01-01

Summary Epidemiologic studies and disease prevention trials often seek to relate an exposure variable to a failure time that suffers from interval-censoring. When the failure rate is low and the time intervals are wide, a large cohort is often required so as to yield reliable precision on the exposure-failure-time relationship. However, large cohort studies with simple random sampling could be prohibitive for investigators with a limited budget, especially when the exposure variables are expensive to obtain. Alternative cost-effective sampling designs and inference procedures are therefore desirable. We propose an outcome-dependent sampling (ODS) design with interval-censored failure time data, where we enrich the observed sample by selectively including certain more informative failure subjects. We develop a novel sieve semiparametric maximum empirical likelihood approach for fitting the proportional hazards model to data from the proposed interval-censoring ODS design. This approach employs the empirical likelihood and sieve methods to deal with the infinite-dimensional nuisance parameters, which greatly reduces the dimensionality of the estimation problem and eases the computation difficulty. The consistency and asymptotic normality of the resulting regression parameter estimator are established. The results from our extensive simulation study show that the proposed design and method works well for practical situations and is more efficient than the alternative designs and competing approaches. An example from the Atherosclerosis Risk in Communities (ARIC) study is provided for illustration. PMID:28771664

A simple measure of cognitive reserve is relevant for cognitive performance in MS patients.

PubMed

Della Corte, Marida; Santangelo, Gabriella; Bisecco, Alvino; Sacco, Rosaria; Siciliano, Mattia; d'Ambrosio, Alessandro; Docimo, Renato; Cuomo, Teresa; Lavorgna, Luigi; Bonavita, Simona; Tedeschi, Gioacchino; Gallo, Antonio

2018-05-04

Cognitive reserve (CR) contributes to preserve cognition despite brain damage. This theory has been applied to multiple sclerosis (MS) to explain the partial relationship between cognition and MRI markers of brain pathology. Our aim was to determine the relationship between two measures of CR and cognition in MS. One hundred and forty-seven MS patients were enrolled. Cognition was assessed using the Rao's Brief Repeatable Battery and the Stroop Test. CR was measured as the vocabulary subtest of the WAIS-R score (VOC) and the number of years of formal education (EDU). Regression analysis included raw score data on each neuropsychological (NP) test as dependent variables and demographic/clinical parameters, VOC, and EDU as independent predictors. A binary logistic regression analysis including clinical/CR parameters as covariates and absence/presence of cognitive deficits as dependent variables was performed too. VOC, but not EDU, was strongly correlated with performances at all ten NP tests. EDU was correlated with executive performances. The binary logistic regression showed that only the Expanded Disability Status Scale (EDSS) and VOC were independently correlated with the presence/absence of CD. The lower the VOC and/or the higher the EDSS, the higher the frequency of CD. In conclusion, our study supports the relevance of CR in subtending cognitive performances and the presence of CD in MS patients.

Factorial experimental design for the culture of human embryonic stem cells as aggregates in stirred suspension bioreactors reveals the potential for interaction effects between bioprocess parameters.

PubMed

Hunt, Megan M; Meng, Guoliang; Rancourt, Derrick E; Gates, Ian D; Kallos, Michael S

2014-01-01

Traditional optimization of culture parameters for the large-scale culture of human embryonic stem cells (ESCs) as aggregates is carried out in a stepwise manner whereby the effect of varying each culture parameter is investigated individually. However, as evidenced by the wide range of published protocols and culture performance indicators (growth rates, pluripotency marker expression, etc.), there is a lack of systematic investigation into the true effect of varying culture parameters especially with respect to potential interactions between culture variables. Here we describe the design and execution of a two-parameter, three-level (3(2)) factorial experiment resulting in nine conditions that were run in duplicate 125-mL stirred suspension bioreactors. The two parameters investigated here were inoculation density and agitation rate, which are easily controlled, but currently, poorly characterized. Cell readouts analyzed included fold expansion, maximum density, and exponential growth rate. Our results reveal that the choice of best case culture parameters was dependent on which cell property was chosen as the primary output variable. Subsequent statistical analyses via two-way analysis of variance indicated significant interaction effects between inoculation density and agitation rate specifically in the case of exponential growth rates. Results indicate that stepwise optimization has the potential to miss out on the true optimal case. In addition, choosing an optimum condition for a culture output of interest from the factorial design yielded similar results when repeated with the same cell line indicating reproducibility. We finally validated that human ESCs remain pluripotent in suspension culture as aggregates under our optimal conditions and maintain their differentiation capabilities as well as a stable karyotype and strong expression levels of specific human ESC markers over several passages in suspension bioreactors.

Implementation of smart phone video plethysmography and dependence on lighting parameters.

PubMed

Fletcher, Richard Ribón; Chamberlain, Daniel; Paggi, Nicholas; Deng, Xinyue

2015-08-01

The remote measurement of heart rate (HR) and heart rate variability (HRV) via a digital camera (video plethysmography) has emerged as an area of great interest for biomedical and health applications. While a few implementations of video plethysmography have been demonstrated on smart phones under controlled lighting conditions, it has been challenging to create a general scalable solution due to the large variability in smart phone hardware performance, software architecture, and the variable response to lighting parameters. In this context, we present a selfcontained smart phone implementation of video plethysmography for Android OS, which employs both stochastic and deterministic algorithms, and we use this to study the effect of lighting parameters (illuminance, color spectrum) on the accuracy of the remote HR measurement. Using two different phone models, we present the median HR error for five different video plethysmography algorithms under three different types of lighting (natural sunlight, compact fluorescent, and halogen incandescent) and variations in brightness. For most algorithms, we found the optimum light brightness to be in the range 1000-4000 lux and the optimum lighting types to be compact fluorescent and natural light. Moderate errors were found for most algorithms with some devices under conditions of low-brightness (<;500 lux) and highbrightness (>4000 lux). Our analysis also identified camera frame rate jitter as a major source of variability and error across different phone models, but this can be largely corrected through non-linear resampling. Based on testing with six human subjects, our real-time Android implementation successfully predicted the measured HR with a median error of -0.31 bpm, and an inter-quartile range of 2.1bpm.

Stochastic, goal-oriented rapid impact modeling of uncertainty and environmental impacts in poorly-sampled sites using ex-situ priors

NASA Astrophysics Data System (ADS)

Li, Xiaojun; Li, Yandong; Chang, Ching-Fu; Tan, Benjamin; Chen, Ziyang; Sege, Jon; Wang, Changhong; Rubin, Yoram

2018-01-01

Modeling of uncertainty associated with subsurface dynamics has long been a major research topic. Its significance is widely recognized for real-life applications. Despite the huge effort invested in the area, major obstacles still remain on the way from theory and applications. Particularly problematic here is the confusion between modeling uncertainty and modeling spatial variability, which translates into a (mis)conception, in fact an inconsistency, in that it suggests that modeling of uncertainty and modeling of spatial variability are equivalent, and as such, requiring a lot of data. This paper investigates this challenge against the backdrop of a 7 km, deep underground tunnel in China, where environmental impacts are of major concern. We approach the data challenge by pursuing a new concept for Rapid Impact Modeling (RIM), which bypasses altogether the need to estimate posterior distributions of model parameters, focusing instead on detailed stochastic modeling of impacts, conditional to all information available, including prior, ex-situ information and in-situ measurements as well. A foundational element of RIM is the construction of informative priors for target parameters using ex-situ data, relying on ensembles of well-documented sites, pre-screened for geological and hydrological similarity to the target site. The ensembles are built around two sets of similarity criteria: a physically-based set of criteria and an additional set covering epistemic criteria. In another variation to common Bayesian practice, we update the priors to obtain conditional distributions of the target (environmental impact) dependent variables and not the hydrological variables. This recognizes that goal-oriented site characterization is in many cases more useful in applications compared to parameter-oriented characterization.

T1 mapping with the variable flip angle technique: A simple correction for insufficient spoiling of transverse magnetization.

PubMed

Baudrexel, Simon; Nöth, Ulrike; Schüre, Jan-Rüdiger; Deichmann, Ralf

2018-06-01

The variable flip angle method derives T 1 maps from radiofrequency-spoiled gradient-echo data sets, acquired with different flip angles α. Because the method assumes validity of the Ernst equation, insufficient spoiling of transverse magnetization yields errors in T 1 estimation, depending on the chosen radiofrequency-spoiling phase increment (Δϕ). This paper presents a versatile correction method that uses modified flip angles α' to restore the validity of the Ernst equation. Spoiled gradient-echo signals were simulated for three commonly used phase increments Δϕ (50°/117°/150°), different values of α, repetition time (TR), T 1 , and a T 2 of 85 ms. For each parameter combination, α' (for which the Ernst equation yielded the same signal) and a correction factor C Δϕ (α, TR, T 1 ) = α'/α were determined. C Δϕ was found to be independent of T 1 and fitted as polynomial C Δϕ (α, TR), allowing to calculate α' for any protocol using this Δϕ. The accuracy of the correction method for T 2 values deviating from 85 ms was also determined. The method was tested in vitro and in vivo for variable flip angle scans with different acquisition parameters. The technique considerably improved the accuracy of variable flip angle-based T 1 maps in vitro and in vivo. The proposed method allows for a simple correction of insufficient spoiling in gradient-echo data. The required polynomial parameters are supplied for three common Δϕ. Magn Reson Med 79:3082-3092, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

[Optimization of application parameters of soil seed bank in vegetation recovery via response surface methodology].

PubMed

He, Meng-Xuan; Li, Hong-Yuan; Mo, Xun-Qiang; Meng, Wei-Qing; Yang, Jia-Nan

2014-08-01

The thickness of surface soil, the covering thickness and the number of adding arbor seeds are all important factors to be considered in the application of soil seed bank (SSB) for vegetation recovery. To determine the optimal conditions, the Box-Behnken central composite design with three parameters and three levels was conducted and Design-Expert was used for response surface optimization. Finally, the optimal model and optimal level of each parameter were selected. The quadratic model was more suitable for response surface optimization (P < 0.0001), indicating the model had good statistical significance which could express ideal relations between all the independent variable and dependent variable. For the optimum condition, the thickness of surface soil was 4.3 cm, the covering thickness was 2 cm, and the number of adding arbor seeds was 224 ind x m(-2), under which the number of germinated seedlings could be reached up to 6222 plants x m(-2). During the process of seed germination, significant interactions between the thickness of surface soil and the covering thickness, as well as the thickness of surface soil and the number of adding arbor seeds were found, but the relationship between the covering thickness and the number of adding arbor seeds was relatively unremarkable. Among all the parameters, the thickness of surface soil was the most important one, which had the steepest curve and the largest standardized coefficient.

Hydraulic resistance of submerged flexible vegetation

NASA Astrophysics Data System (ADS)

Stephan, Ursula; Gutknecht, Dieter

2002-12-01

The main research objective consisted in analysing the influence of roughness caused by aquatic vegetation (av), in particular submerged macrophytes, on the overall flow field. These plants are highly flexible and behave differently depending on the flow situation. They also react substantially to the flow field and thus, the roughness becomes variable and dynamic. Conventional flow formulas, such as the Manning or the Strickler formula, are one-dimensional and based on integral flow parameters. They are not suitable for quantifying the roughness of av, because the flow is complex and more dimensional due to the variable behaviour of the plants. Therefore, the present investigation concentrates on the definition of a characteristic hydraulic roughness parameter to quantify the resistance of av. Within this investigation laboratory experiments were carried out with three different types of av, chosen with respect to varying plant structures as well as stem lengths. Velocity measurements above these plants were conducted to determine the relationship between the hydraulic roughness and the deflected plant height. The deflected plant height is used as the geometric roughness parameter, whereas the equivalent sand roughness based on the universal logarithmic law modified by Nikuradse was used as hydraulic roughness parameter. The influence of relative submergence on the hydraulic roughness was also analysed. The analysis of the velocity measurements illustrates that equivalent sand roughness and zero plane displacement of the logarithmic law are correlated to the deflected plant height and are equally to this height.

Application of Fourier transform near-infrared spectroscopy to optimization of green tea steaming process conditions.

PubMed

Ono, Daiki; Bamba, Takeshi; Oku, Yuichi; Yonetani, Tsutomu; Fukusaki, Eiichiro

2011-09-01

In this study, we constructed prediction models by metabolic fingerprinting of fresh green tea leaves using Fourier transform near-infrared (FT-NIR) spectroscopy and partial least squares (PLS) regression analysis to objectively optimize of the steaming process conditions in green tea manufacture. The steaming process is the most important step for manufacturing high quality green tea products. However, the parameter setting of the steamer is currently determined subjectively by the manufacturer. Therefore, a simple and robust system that can be used to objectively set the steaming process parameters is necessary. We focused on FT-NIR spectroscopy because of its simple operation, quick measurement, and low running costs. After removal of noise in the spectral data by principal component analysis (PCA), PLS regression analysis was performed using spectral information as independent variables, and the steaming parameters set by experienced manufacturers as dependent variables. The prediction models were successfully constructed with satisfactory accuracy. Moreover, the results of the demonstrated experiment suggested that the green tea steaming process parameters could be predicted on a larger manufacturing scale. This technique will contribute to improvement of the quality and productivity of green tea because it can objectively optimize the complicated green tea steaming process and will be suitable for practical use in green tea manufacture. Copyright © 2011 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Stability analysis of BWR nuclear-coupled thermal-hyraulics using a simple model

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

Karve, A.A.; Rizwan-uddin; Dorning, J.J.

1995-09-01

A simple mathematical model is developed to describe the dynamics of the nuclear-coupled thermal-hydraulics in a boiling water reactor (BWR) core. The model, which incorporates the essential features of neutron kinetics, and single-phase and two-phase thermal-hydraulics, leads to simple dynamical system comprised of a set of nonlinear ordinary differential equations (ODEs). The stability boundary is determined and plotted in the inlet-subcooling-number (enthalpy)/external-reactivity operating parameter plane. The eigenvalues of the Jacobian matrix of the dynamical system also are calculated at various steady-states (fixed points); the results are consistent with those of the direct stability analysis and indicate that a Hopf bifurcationmore » occurs as the stability boundary in the operating parameter plane is crossed. Numerical simulations of the time-dependent, nonlinear ODEs are carried out for selected points in the operating parameter plane to obtain the actual damped and growing oscillations in the neutron number density, the channel inlet flow velocity, and the other phase variables. These indicate that the Hopf bifurcation is subcritical, hence, density wave oscillations with growing amplitude could result from a finite perturbation of the system even where the steady-state is stable. The power-flow map, frequently used by reactor operators during start-up and shut-down operation of a BWR, is mapped to the inlet-subcooling-number/neutron-density (operating-parameter/phase-variable) plane, and then related to the stability boundaries for different fixed inlet velocities corresponding to selected points on the flow-control line. The stability boundaries for different fixed inlet subcooling numbers corresponding to those selected points, are plotted in the neutron-density/inlet-velocity phase variable plane and then the points on the flow-control line are related to their respective stability boundaries in this plane.« less

Effects of metal- and fiber-reinforced composite root canal posts on flexural properties.

PubMed

Kim, Su-Hyeon; Oh, Tack-Oon; Kim, Ju-Young; Park, Chun-Woong; Baek, Seung-Ho; Park, Eun-Seok

2016-01-01

The aim of this study was to observe the effects of different test conditions on the flexural properties of root canal post. Metal- and fiber-reinforced composite root canal posts of various diameters were measured to determine flexural properties using a threepoint bending test at different conditions. In this study, the span length/post diameter ratio of root canal posts varied from 3.0 to 10.0. Multiple regression models for maximum load as a dependent variable were statistically significant. The models for flexural properties as dependent variables were statistically significant, but linear regression models could not be fitted to data sets. At a low span length/post diameter ratio, the flexural properties were distorted by occurrence of shear stress in short samples. It was impossible to obtain high span length/post diameter ratio with root canal posts. The addition of parameters or coefficients is necessary to appropriately represent the flexural properties of root canal posts.

Green-Naghdi dynamics of surface wind waves in finite depth

NASA Astrophysics Data System (ADS)

Manna, M. A.; Latifi, A.; Kraenkel, R. A.

2018-04-01

The Miles’ quasi laminar theory of waves generation by wind in finite depth h is presented. In this context, the fully nonlinear Green-Naghdi model equation is derived for the first time. This model equation is obtained by the non perturbative Green-Naghdi approach, coupling a nonlinear evolution of water waves with the atmospheric dynamics which works as in the classic Miles’ theory. A depth-dependent and wind-dependent wave growth γ is drawn from the dispersion relation of the coupled Green-Naghdi model with the atmospheric dynamics. Different values of the dimensionless water depth parameter δ = gh/U 1, with g the gravity and U 1 a characteristic wind velocity, produce two families of growth rate γ in function of the dimensionless theoretical wave-age c 0: a family of γ with h constant and U 1 variable and another family of γ with U 1 constant and h variable. The allowed minimum and maximum values of γ in this model are exhibited.

Generalized scaling relationships on transition metals: Influence of adsorbate-coadsorbate interactions

NASA Astrophysics Data System (ADS)

Majumdar, Paulami; Greeley, Jeffrey

2018-04-01

Linear scaling relations of adsorbate energies across a range of catalytic surfaces have emerged as a central interpretive paradigm in heterogeneous catalysis. They are, however, typically developed for low adsorbate coverages which are not always representative of realistic heterogeneous catalytic environments. Herein, we present generalized linear scaling relations on transition metals that explicitly consider adsorbate-coadsorbate interactions at variable coverages. The slopes of these scaling relations do not follow the simple bond counting principles that govern scaling on transition metals at lower coverages. The deviations from bond counting are explained using a pairwise interaction model wherein the interaction parameter determines the slope of the scaling relationship on a given metal at variable coadsorbate coverages, and the slope across different metals at fixed coadsorbate coverage is approximated by adding a coverage-dependent correction to the standard bond counting contribution. The analysis provides a compact explanation for coverage-dependent deviations from bond counting in scaling relationships and suggests a useful strategy for incorporation of coverage effects into catalytic trends studies.

Automated combinatorial method for fast and robust prediction of lattice thermal conductivity

NASA Astrophysics Data System (ADS)

Plata, Jose J.; Nath, Pinku; Usanmaz, Demet; Toher, Cormac; Fornari, Marco; Buongiorno Nardelli, Marco; Curtarolo, Stefano

The lack of computationally inexpensive and accurate ab-initio based methodologies to predict lattice thermal conductivity, κl, without computing the anharmonic force constants or performing time-consuming ab-initio molecular dynamics, is one of the obstacles preventing the accelerated discovery of new high or low thermal conductivity materials. The Slack equation is the best alternative to other more expensive methodologies but is highly dependent on two variables: the acoustic Debye temperature, θa, and the Grüneisen parameter, γ. Furthermore, different definitions can be used for these two quantities depending on the model or approximation. Here, we present a combinatorial approach based on the quasi-harmonic approximation to elucidate which definitions of both variables produce the best predictions of κl. A set of 42 compounds was used to test accuracy and robustness of all possible combinations. This approach is ideal for obtaining more accurate values than fast screening models based on the Debye model, while being significantly less expensive than methodologies that solve the Boltzmann transport equation.

Gestation-Specific Changes in the Anatomy and Physiology of Healthy Pregnant Women: An Extended Repository of Model Parameters for Physiologically Based Pharmacokinetic Modeling in Pregnancy.

PubMed

Dallmann, André; Ince, Ibrahim; Meyer, Michaela; Willmann, Stefan; Eissing, Thomas; Hempel, Georg

2017-11-01

In the past years, several repositories for anatomical and physiological parameters required for physiologically based pharmacokinetic modeling in pregnant women have been published. While providing a good basis, some important aspects can be further detailed. For example, they did not account for the variability associated with parameters or were lacking key parameters necessary for developing more detailed mechanistic pregnancy physiologically based pharmacokinetic models, such as the composition of pregnancy-specific tissues. The aim of this meta-analysis was to provide an updated and extended database of anatomical and physiological parameters in healthy pregnant women that also accounts for changes in the variability of a parameter throughout gestation and for the composition of pregnancy-specific tissues. A systematic literature search was carried out to collect study data on pregnancy-related changes of anatomical and physiological parameters. For each parameter, a set of mathematical functions was fitted to the data and to the standard deviation observed among the data. The best performing functions were selected based on numerical and visual diagnostics as well as based on physiological plausibility. The literature search yielded 473 studies, 302 of which met the criteria to be further analyzed and compiled in a database. In total, the database encompassed 7729 data. Although the availability of quantitative data for some parameters remained limited, mathematical functions could be generated for many important parameters. Gaps were filled based on qualitative knowledge and based on physiologically plausible assumptions. The presented results facilitate the integration of pregnancy-dependent changes in anatomy and physiology into mechanistic population physiologically based pharmacokinetic models. Such models can ultimately provide a valuable tool to investigate the pharmacokinetics during pregnancy in silico and support informed decision making regarding optimal dosing regimens in this vulnerable special population.

Unsteady Convection Flow and Heat Transfer over a Vertical Stretching Surface

PubMed Central

Cai, Wenli; Su, Ning; Liu, Xiangdong

2014-01-01

This paper investigates the effect of thermal radiation on unsteady convection flow and heat transfer over a vertical permeable stretching surface in porous medium, where the effects of temperature dependent viscosity and thermal conductivity are also considered. By using a similarity transformation, the governing time-dependent boundary layer equations for momentum and thermal energy are first transformed into coupled, non-linear ordinary differential equations with variable coefficients. Numerical solutions to these equations subject to appropriate boundary conditions are obtained by the numerical shooting technique with fourth-fifth order Runge-Kutta scheme. Numerical results show that as viscosity variation parameter increases both the absolute value of the surface friction coefficient and the absolute value of the surface temperature gradient increase whereas the temperature decreases slightly. With the increase of viscosity variation parameter, the velocity decreases near the sheet surface but increases far away from the surface of the sheet in the boundary layer. The increase in permeability parameter leads to the decrease in both the temperature and the absolute value of the surface friction coefficient, and the increase in both the velocity and the absolute value of the surface temperature gradient. PMID:25264737

Unsteady convection flow and heat transfer over a vertical stretching surface.

PubMed

Cai, Wenli; Su, Ning; Liu, Xiangdong

2014-01-01

This paper investigates the effect of thermal radiation on unsteady convection flow and heat transfer over a vertical permeable stretching surface in porous medium, where the effects of temperature dependent viscosity and thermal conductivity are also considered. By using a similarity transformation, the governing time-dependent boundary layer equations for momentum and thermal energy are first transformed into coupled, non-linear ordinary differential equations with variable coefficients. Numerical solutions to these equations subject to appropriate boundary conditions are obtained by the numerical shooting technique with fourth-fifth order Runge-Kutta scheme. Numerical results show that as viscosity variation parameter increases both the absolute value of the surface friction coefficient and the absolute value of the surface temperature gradient increase whereas the temperature decreases slightly. With the increase of viscosity variation parameter, the velocity decreases near the sheet surface but increases far away from the surface of the sheet in the boundary layer. The increase in permeability parameter leads to the decrease in both the temperature and the absolute value of the surface friction coefficient, and the increase in both the velocity and the absolute value of the surface temperature gradient.

Revisiting the positive DC corona discharge theory: Beyond Peek's and Townsend's law

NASA Astrophysics Data System (ADS)

Monrolin, Nicolas; Praud, Olivier; Plouraboué, Franck

2018-06-01

The classical positive Corona Discharge theory in a cylindrical axisymmetric configuration is revisited in order to find analytically the influence of gas properties and thermodynamic conditions on the corona current. The matched asymptotic expansion of Durbin and Turyn [J. Phys. D: Appl. Phys. 20, 1490-1495 (1987)] of a simplified but self-consistent problem is performed and explicit analytical solutions are derived. The mathematical derivation enables us to express a new positive DC corona current-voltage characteristic, choosing either a dimensionless or dimensional formulation. In dimensional variables, the current voltage law and the corona inception voltage explicitly depend on the electrode size and physical gas properties such as ionization and photoionization parameters. The analytical predictions are successfully confronted with experiments and Peek's and Townsend's laws. An analytical expression of the corona inception voltage φ o n is proposed, which depends on the known values of physical parameters without adjustable parameters. As a proof of consistency, the classical Townsend current-voltage law I = C φ ( φ - φ o n ) is retrieved by linearizing the non-dimensional analytical solution. A brief parametric study showcases the interest in this analytical current model, especially for exploring small corona wires or considering various thermodynamic conditions.

Spatio-temporal modelling of wind speed variations and extremes in the Caribbean and the Gulf of Mexico

NASA Astrophysics Data System (ADS)

Rychlik, Igor; Mao, Wengang

2018-02-01

The wind speed variability in the North Atlantic has been successfully modelled using a spatio-temporal transformed Gaussian field. However, this type of model does not correctly describe the extreme wind speeds attributed to tropical storms and hurricanes. In this study, the transformed Gaussian model is further developed to include the occurrence of severe storms. In this new model, random components are added to the transformed Gaussian field to model rare events with extreme wind speeds. The resulting random field is locally stationary and homogeneous. The localized dependence structure is described by time- and space-dependent parameters. The parameters have a natural physical interpretation. To exemplify its application, the model is fitted to the ECMWF ERA-Interim reanalysis data set. The model is applied to compute long-term wind speed distributions and return values, e.g., 100- or 1000-year extreme wind speeds, and to simulate random wind speed time series at a fixed location or spatio-temporal wind fields around that location.

Lead iodide perovskite light-emitting field-effect transistor

PubMed Central

Chin, Xin Yu; Cortecchia, Daniele; Yin, Jun; Bruno, Annalisa; Soci, Cesare

2015-01-01

Despite the widespread use of solution-processable hybrid organic–inorganic perovskites in photovoltaic and light-emitting applications, determination of their intrinsic charge transport parameters has been elusive due to the variability of film preparation and history-dependent device performance. Here we show that screening effects associated to ionic transport can be effectively eliminated by lowering the operating temperature of methylammonium lead iodide perovskite (CH3NH3PbI3) field-effect transistors. Field-effect carrier mobility is found to increase by almost two orders of magnitude below 200 K, consistent with phonon scattering-limited transport. Under balanced ambipolar carrier injection, gate-dependent electroluminescence is also observed from the transistor channel, with spectra revealing the tetragonal to orthorhombic phase transition. This demonstration of CH3NH3PbI3 light-emitting field-effect transistors provides intrinsic transport parameters to guide materials and solar cell optimization, and will drive the development of new electro-optic device concepts, such as gated light-emitting diodes and lasers operating at room temperature. PMID:26108967

Temporal variability in stage-discharge relationships

NASA Astrophysics Data System (ADS)

Guerrero, José-Luis; Westerberg, Ida K.; Halldin, Sven; Xu, Chong-Yu; Lundin, Lars-Christer

2012-06-01

SummaryAlthough discharge estimations are central for water management and hydropower, there are few studies on the variability and uncertainty of their basis; deriving discharge from stage heights through the use of a rating curve that depends on riverbed geometry. A large fraction of the world's river-discharge stations are presumably located in alluvial channels where riverbed characteristics may change over time because of erosion and sedimentation. This study was conducted to analyse and quantify the dynamic relationship between stage and discharge and to determine to what degree currently used methods are able to account for such variability. The study was carried out for six hydrometric stations in the upper Choluteca River basin, Honduras, where a set of unusually frequent stage-discharge data are available. The temporal variability and the uncertainty of the rating curve and its parameters were analysed through a Monte Carlo (MC) analysis on a moving window of data using the Generalised Likelihood Uncertainty Estimation (GLUE) methodology. Acceptable ranges for the values of the rating-curve parameters were determined from riverbed surveys at the six stations, and the sampling space was constrained according to those ranges, using three-dimensional alpha shapes. Temporal variability was analysed in three ways: (i) with annually updated rating curves (simulating Honduran practices), (ii) a rating curve for each time window, and (iii) a smoothed, continuous dynamic rating curve derived from the MC analysis. The temporal variability of the rating parameters translated into a high rating-curve variability. The variability could turn out as increasing or decreasing trends and/or cyclic behaviour. There was a tendency at all stations to a seasonal variability. The discharge at a given stage could vary by a factor of two or more. The quotient in discharge volumes estimated from dynamic and static rating curves varied between 0.5 and 1.5. The difference between discharge volumes derived from static and dynamic curves was largest for sub-daily ratings but stayed large also for monthly and yearly totals. The relative uncertainty was largest for low flows but it was considerable also for intermediate and large flows. The standard procedure of adjusting rating curves when calculated and observed discharge differ by more than 5% would have required continuously updated rating curves at the studied locations. We believe that these findings can be applicable to many other discharge stations around the globe.

Effect of land use on the spatial variability of organic matter and nutrient status in an Oxisol

NASA Astrophysics Data System (ADS)

Paz-Ferreiro, Jorge; Alves, Marlene Cristina; Vidal Vázquez, Eva

2013-04-01

Heterogeneity is now considered as an inherent soil property. Spatial variability of soil attributes in natural landscapes results mainly from soil formation factors. In cultivated soils much heterogeneity can additionally occur as a result of land use, agricultural systems and management practices. Organic matter content (OMC) and nutrients associated to soil exchange complex are key attribute in the maintenance of a high quality soil. Neglecting spatial heterogeneity in soil OMC and nutrient status at the field scale might result in reduced yield and in environmental damage. We analyzed the impact of land use on the pattern of spatial variability of OMC and soil macronutrients at the stand scale. The study was conducted in São Paulo state, Brazil. Land uses were pasture, mango orchard and corn field. Soil samples were taken at 0-10 cm and 10-20 cm depth in 84 points, within 100 m x 100 m plots. Texture, pH, OMC, cation exchange capacity (CEC), exchangeable cations (Ca, Mg, K, H, Al) and resin extractable phosphorus were analyzed.. Statistical variability was found to be higher in parameters defining the soil nutrient status (resin extractable P, K, Ca and Mg) than in general soil properties (OMC, CEC, base saturation and pH). Geostatistical analysis showed contrasting patterns of spatial dependence for the different soil uses, sampling depths and studied properties. Most of the studied data sets collected at two different depths exhibited spatial dependence at the sampled scale and their semivariograms were modeled by a nugget effect plus a structure. The pattern of soil spatial variability was found to be different between the three study soil uses and at the two sampling depths, as far as model type, nugget effect or ranges of spatial dependence were concerned. Both statistical and geostatistical results pointed out the importance of OMC as a driver responsible for the spatial variability of soil nutrient status.

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.

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.

Sensitivity Analysis of Methane Hydrate Reservoirs: Effects of Reservoir Parameters on Gas Productivity and Economics

NASA Astrophysics Data System (ADS)

Anderson, B. J.; Gaddipati, M.; Nyayapathi, L.

2008-12-01

This paper presents a parametric study on production rates of natural gas from gas hydrates by the method of depressurization, using CMG STARS. Seven factors/parameters were considered as perturbations from a base-case hydrate reservoir description based on Problem 7 of the International Methane Hydrate Reservoir Simulator Code Comparison Study led by the Department of Energy and the USGS. This reservoir is modeled after the inferred properties of the hydrate deposit at the Prudhoe Bay L-106 site. The included sensitivity variables were hydrate saturation, pressure (depth), temperature, bottom-hole pressure of the production well, free water saturation, intrinsic rock permeability, and porosity. A two-level (L=2) Plackett-Burman experimental design was used to study the relative effects of these factors. The measured variable was the discounted cumulative gas production. The discount rate chosen was 15%, resulting in the gas contribution to the net present value of a reservoir. Eight different designs were developed for conducting sensitivity analysis and the effects of the parameters on the real and discounted production rates will be discussed. The breakeven price in various cases and the dependence of the breakeven price on the production parameters is given in the paper. As expected, initial reservoir temperature has the strongest positive effect on the productivity of a hydrate deposit and the bottom-hole pressure in the production well has the strongest negative dependence. Also resulting in a positive correlation is the intrinsic permeability and the initial free water of the formation. Negative effects were found for initial hydrate saturation (at saturations greater than 50% of the pore space) and the reservoir porosity. These negative effects are related to the available sensible heat of the reservoir, with decreasing productivity due to decreasing available sensible heat. Finally, we conclude that for the base case reservoir, the break-even price (BEP) for natural gas is approximately 7/mcf and for warmer and deeper reservoirs the BEP can approach 5.33/mcf.

The Role of Model Complexity in Determining Patterns of Chlorophyll Variability in the Coastal Northwest North Atlantic

NASA Astrophysics Data System (ADS)

Kuhn, A. M.; Fennel, K.; Bianucci, L.

2016-02-01

A key feature of the North Atlantic Ocean's biological dynamics is the annual phytoplankton spring bloom. In the region comprising the continental shelf and adjacent deep ocean of the northwest North Atlantic, we identified two patterns of bloom development: 1) locations with cold temperatures and deep winter mixed layers, where the spring bloom peaks around April and the annual chlorophyll cycle has a large amplitude, and 2) locations with warmer temperatures and shallow winter mixed layers, where the spring bloom peaks earlier in the year, sometimes indiscernible from the fall bloom. These patterns result from a combination of limiting environmental factors and interactions among planktonic groups with different optimal requirements. Simple models that represent the ecosystem with a single phytoplankton (P) and a single zooplankton (Z) group are challenged to reproduce these ecological interactions. Here we investigate the effect that added complexity has on determining spatio-temporal chlorophyll. We compare two ecosystem models, one that contains one P and one Z group, and one with two P and three Z groups. We consider three types of changes in complexity: 1) added dependencies among variables (e.g., temperature dependent rates), 2) modified structural pathways, and 3) added pathways. Subsets of the most sensitive parameters are optimized in each model to replicate observations in the region. For computational efficiency, the parameter optimization is performed using 1D surrogates of a 3D model. We evaluate how model complexity affects model skill, and whether the optimized parameter sets found for each model modify the interpretation of ecosystem functioning. Spatial differences in the parameter sets that best represent different areas hint at the existence of different ecological communities or at physical-biological interactions that are not represented in the simplest model. Our methodology emphasizes the combined use of observations, 1D models to help identifying patterns, and 3D models able to simulate the environment modre realistically, as a means to acquire predictive understanding of the ocean's ecology.

Using Copulas in the Estimation of the Economic Project Value in the Mining Industry, Including Geological Variability

NASA Astrophysics Data System (ADS)

Krysa, Zbigniew; Pactwa, Katarzyna; Wozniak, Justyna; Dudek, Michal

2017-12-01

Geological variability is one of the main factors that has an influence on the viability of mining investment projects and on the technical risk of geology projects. In the current scenario, analyses of economic viability of new extraction fields have been performed for the KGHM Polska Miedź S.A. underground copper mine at Fore Sudetic Monocline with the assumption of constant averaged content of useful elements. Research presented in this article is aimed at verifying the value of production from copper and silver ore for the same economic background with the use of variable cash flows resulting from the local variability of useful elements. Furthermore, the ore economic model is investigated for a significant difference in model value estimated with the use of linear correlation between useful elements content and the height of mine face, and the approach in which model parameters correlation is based upon the copula best matched information capacity criterion. The use of copula allows the simulation to take into account the multi variable dependencies at the same time, thereby giving a better reflection of the dependency structure, which linear correlation does not take into account. Calculation results of the economic model used for deposit value estimation indicate that the correlation between copper and silver estimated with the use of copula generates higher variation of possible project value, as compared to modelling correlation based upon linear correlation. Average deposit value remains unchanged.

Urea-temperature phase diagrams capture the thermodynamics of denatured state expansion that accompany protein unfolding.

PubMed

Tischer, Alexander; Auton, Matthew

2013-09-01

We have analyzed the thermodynamic properties of the von Willebrand factor (VWF) A3 domain using urea-induced unfolding at variable temperature and thermal unfolding at variable urea concentrations to generate a phase diagram that quantitatively describes the equilibrium between native and denatured states. From this analysis, we were able to determine consistent thermodynamic parameters with various spectroscopic and calorimetric methods that define the urea-temperature parameter plane from cold denaturation to heat denaturation. Urea and thermal denaturation are experimentally reversible and independent of the thermal scan rate indicating that all transitions are at equilibrium and the van't Hoff and calorimetric enthalpies obtained from analysis of individual thermal transitions are equivalent demonstrating two-state character. Global analysis of the urea-temperature phase diagram results in a significantly higher enthalpy of unfolding than obtained from analysis of individual thermal transitions and significant cross correlations describing the urea dependence of ΔH0 and ΔCP0 that define a complex temperature dependence of the m-value. Circular dichroism (CD) spectroscopy illustrates a large increase in secondary structure content of the urea-denatured state as temperature increases and a loss of secondary structure in the thermally denatured state upon addition of urea. These structural changes in the denatured ensemble make up ∼40% of the total ellipticity change indicating a highly compact thermally denatured state. The difference between the thermodynamic parameters obtained from phase diagram analysis and those obtained from analysis of individual thermal transitions illustrates that phase diagrams capture both contributions to unfolding and denatured state expansion and by comparison are able to decipher these contributions. © 2013 The Protein Society.

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.

A consistent framework for Horton regression statistics that leads to a modified Hack's law

USGS Publications Warehouse

Furey, P.R.; Troutman, B.M.

2008-01-01

A statistical framework is introduced that resolves important problems with the interpretation and use of traditional Horton regression statistics. The framework is based on a univariate regression model that leads to an alternative expression for Horton ratio, connects Horton regression statistics to distributional simple scaling, and improves the accuracy in estimating Horton plot parameters. The model is used to examine data for drainage area A and mainstream length L from two groups of basins located in different physiographic settings. Results show that confidence intervals for the Horton plot regression statistics are quite wide. Nonetheless, an analysis of covariance shows that regression intercepts, but not regression slopes, can be used to distinguish between basin groups. The univariate model is generalized to include n > 1 dependent variables. For the case where the dependent variables represent ln A and ln L, the generalized model performs somewhat better at distinguishing between basin groups than two separate univariate models. The generalized model leads to a modification of Hack's law where L depends on both A and Strahler order ??. Data show that ?? plays a statistically significant role in the modified Hack's law expression. ?? 2008 Elsevier B.V.

Effect of medium electrophysical parameters and their temperature dependences on wideband electromagnetic pulse propagation

NASA Astrophysics Data System (ADS)

Volkomirskaya, L. B.; Gulevich, O. A.; Reznikov, A. E.

2017-03-01

The dielectric permittivity of fiery spoil tips (Shakhty town, Rostov Region) is studied with the use of a GROT 12E remote-controlled ground-penetrating radar (GPR). An anomalous zone in a combustion source is shown to be clearly pronounced in GPR data due to the temperature dependence of the dielectric permittivity of these spoil tips. To substantiate this statement, the GPR data are compared with direct measurements of soil temperatures at depths from 1.5 to 2.5 m. The experimental results are compared with the variable spectral range of a GPR sounding pulse. GPR is shown to be a promising tool for the mapping of temperature-contrast underground objects.

Synchronization behaviors of coupled systems composed of hidden attractors

NASA Astrophysics Data System (ADS)

Zhang, Ge; Wu, Fuqiang; Wang, Chunni; Ma, Jun

2017-10-01

Based on a class of chaotic system composed of hidden attractors, in which the equilibrium points are described by a circular function, complete synchronization between two identical systems, pattern formation and synchronization of network is investigated, respectively. A statistical factor of synchronization is defined and calculated by using the mean field theory, the dependence of synchronization on bifurcation parameters discussed in numerical way. By setting a chain network, which local kinetic is described by hidden attractors, synchronization approach is investigated. It is found that the synchronization and pattern formation are dependent on the coupling intensity and also the selection of coupling variables. In the end, open problems are proposed for readers’ extensive guidance and investigation.

Dimensional Reduction for the General Markov Model on Phylogenetic Trees.

PubMed

Sumner, Jeremy G

2017-03-01

We present a method of dimensional reduction for the general Markov model of sequence evolution on a phylogenetic tree. We show that taking certain linear combinations of the associated random variables (site pattern counts) reduces the dimensionality of the model from exponential in the number of extant taxa, to quadratic in the number of taxa, while retaining the ability to statistically identify phylogenetic divergence events. A key feature is the identification of an invariant subspace which depends only bilinearly on the model parameters, in contrast to the usual multi-linear dependence in the full space. We discuss potential applications including the computation of split (edge) weights on phylogenetic trees from observed sequence data.

A numerical study of variable density flow and mixing in porous media

NASA Astrophysics Data System (ADS)

Fan, Yin; Kahawita, René

1994-10-01

A numerical study of a negatively buoyant plume intruding into a neutrally stratified porous medium has been undertaken using finite different methods. Of particular interest has been to ascertain whether the experimentally observed gravitational instabilities that form along the lower edge of the plume are reproduced in the numerical model. The model has been found to faithfully reproduce the mean flow as well as the gravitational instabilities in the intruding plume. A linear stability analysis has confirmed the fact that the negatively buoyant plume is in fact gravitationally unstable and that the stability depends on two parameters: a concentration Rayleigh number and a characteristic length scale which is dependent on the transverse dispersivity.

Estimating outflow facility through pressure dependent pathways of the human eye

PubMed Central

Gardiner, Bruce S.

2017-01-01

We develop and test a new theory for pressure dependent outflow from the eye. The theory comprises three main parameters: (i) a constant hydraulic conductivity, (ii) an exponential decay constant and (iii) a no-flow intraocular pressure, from which the total pressure dependent outflow, average outflow facilities and local outflow facilities for the whole eye may be evaluated. We use a new notation to specify precisely the meaning of model parameters and so model outputs. Drawing on a range of published data, we apply the theory to animal eyes, enucleated eyes and in vivo human eyes, and demonstrate how to evaluate model parameters. It is shown that the theory can fit high quality experimental data remarkably well. The new theory predicts that outflow facilities and total pressure dependent outflow for the whole eye are more than twice as large as estimates based on the Goldman equation and fluorometric analysis of anterior aqueous outflow. It appears likely that this discrepancy can be largely explained by pseudofacility and aqueous flow through the retinal pigmented epithelium, while any residual discrepancy may be due to pathological processes in aged eyes. The model predicts that if the hydraulic conductivity is too small, or the exponential decay constant is too large, then intraocular eye pressure may become unstable when subjected to normal circadian changes in aqueous production. The model also predicts relationships between variables that may be helpful when planning future experiments, and the model generates many novel testable hypotheses. With additional research, the analysis described here may find application in the differential diagnosis, prognosis and monitoring of glaucoma. PMID:29261696

Three-dimensional benchmark for variable-density flow and transport simulation: matching semi-analytic stability modes for steady unstable convection in an inclined porous box

USGS Publications Warehouse

Voss, Clifford I.; Simmons, Craig T.; Robinson, Neville I.

2010-01-01

This benchmark for three-dimensional (3D) numerical simulators of variable-density groundwater flow and solute or energy transport consists of matching simulation results with the semi-analytical solution for the transition from one steady-state convective mode to another in a porous box. Previous experimental and analytical studies of natural convective flow in an inclined porous layer have shown that there are a variety of convective modes possible depending on system parameters, geometry and inclination. In particular, there is a well-defined transition from the helicoidal mode consisting of downslope longitudinal rolls superimposed upon an upslope unicellular roll to a mode consisting of purely an upslope unicellular roll. Three-dimensional benchmarks for variable-density simulators are currently (2009) lacking and comparison of simulation results with this transition locus provides an unambiguous means to test the ability of such simulators to represent steady-state unstable 3D variable-density physics.

Probabilistic structural analysis methods for improving Space Shuttle engine reliability

NASA Technical Reports Server (NTRS)

Boyce, L.

1989-01-01

Probabilistic structural analysis methods are particularly useful in the design and analysis of critical structural components and systems that operate in very severe and uncertain environments. These methods have recently found application in space propulsion systems to improve the structural reliability of Space Shuttle Main Engine (SSME) components. A computer program, NESSUS, based on a deterministic finite-element program and a method of probabilistic analysis (fast probability integration) provides probabilistic structural analysis for selected SSME components. While computationally efficient, it considers both correlated and nonnormal random variables as well as an implicit functional relationship between independent and dependent variables. The program is used to determine the response of a nickel-based superalloy SSME turbopump blade. Results include blade tip displacement statistics due to the variability in blade thickness, modulus of elasticity, Poisson's ratio or density. Modulus of elasticity significantly contributed to blade tip variability while Poisson's ratio did not. Thus, a rational method for choosing parameters to be modeled as random is provided.

Effect of water table fluctuations on phreatophytic root distribution.

PubMed

Tron, Stefania; Laio, Francesco; Ridolfi, Luca

2014-11-07

The vertical root distribution of riparian vegetation plays a relevant role in soil water balance, in the partition of water fluxes into evaporation and transpiration, in the biogeochemistry of hyporheic corridors, in river morphodynamics evolution, and in bioengineering applications. The aim of this work is to assess the effect of the stochastic variability of the river level on the root distribution of phreatophytic plants. A function describing the vertical root profile has been analytically obtained by coupling a white shot noise representation of the river level variability to a description of the dynamics of root growth and decay. The root profile depends on easily determined parameters, linked to stream dynamics, vegetation and soil characteristics. The riparian vegetation of a river characterized by a high variability turns out to have a rooting system spread over larger depths, but with shallower mean root depths. In contrast, a lower river variability determines root profiles with higher mean root depths. Copyright © 2014 Elsevier Ltd. All rights reserved.

A fast chaos-based image encryption scheme with a dynamic state variables selection mechanism

NASA Astrophysics Data System (ADS)

Chen, Jun-xin; Zhu, Zhi-liang; Fu, Chong; Yu, Hai; Zhang, Li-bo

2015-03-01

In recent years, a variety of chaos-based image cryptosystems have been investigated to meet the increasing demand for real-time secure image transmission. Most of them are based on permutation-diffusion architecture, in which permutation and diffusion are two independent procedures with fixed control parameters. This property results in two flaws. (1) At least two chaotic state variables are required for encrypting one plain pixel, in permutation and diffusion stages respectively. Chaotic state variables produced with high computation complexity are not sufficiently used. (2) The key stream solely depends on the secret key, and hence the cryptosystem is vulnerable against known/chosen-plaintext attacks. In this paper, a fast chaos-based image encryption scheme with a dynamic state variables selection mechanism is proposed to enhance the security and promote the efficiency of chaos-based image cryptosystems. Experimental simulations and extensive cryptanalysis have been carried out and the results prove the superior security and high efficiency of the scheme.

The role of impulse parameters in force variability

NASA Technical Reports Server (NTRS)

Carlton, L. G.; Newell, K. M.

1986-01-01

One of the principle limitations of the human motor system is the ability to produce consistent motor responses. When asked to repeatedly make the same movement, performance outcomes are characterized by a considerable amount of variability. This occurs whether variability is expressed in terms of kinetics or kinematics. Variability in performance is of considerable importance because for tasks requiring accuracy it is a critical variable in determining the skill of the performer. What has long been sought is a description of the parameter or parameters that determine the degree of variability. Two general experimental protocals were used. One protocal is to use dynamic actions and record variability in kinematic parameters such as spatial or temporal error. A second strategy was to use isometric actions and record kinetic variables such as peak force produced. What might be the important force related factors affecting variability is examined and an experimental approach to examine the influence of each of these variables is provided.

Intermediary Variables and Algorithm Parameters for an Electronic Algorithm for Intravenous Insulin Infusion

PubMed Central

Braithwaite, Susan S.; Godara, Hemant; Song, Julie; Cairns, Bruce A.; Jones, Samuel W.; Umpierrez, Guillermo E.

2009-01-01

Background Algorithms for intravenous insulin infusion may assign the infusion rate (IR) by a two-step process. First, the previous insulin infusion rate (IRprevious) and the rate of change of blood glucose (BG) from the previous iteration of the algorithm are used to estimate the maintenance rate (MR) of insulin infusion. Second, the insulin IR for the next iteration (IRnext) is assigned to be commensurate with the MR and the distance of the current blood glucose (BGcurrent) from target. With use of a specific set of algorithm parameter values, a family of iso-MR curves is created, each giving IR as a function of MR and BG. Method To test the feasibility of estimating MR from the IRprevious and the previous rate of change of BG, historical hyperglycemic data points were used to compute the “maintenance rate cross step next estimate” (MRcsne). Historical cases had been treated with intravenous insulin infusion using a tabular protocol that estimated MR according to column-change rules. The mean IR on historical stable intervals (MRtrue), an estimate of the biologic value of MR, was compared to MRcsne during the hyperglycemic iteration immediately preceding the stable interval. Hypothetically calculated MRcsne-dependent IRnext was compared to IRnext assigned historically. An expanded theory of an algorithm is developed mathematically. Practical recommendations for computerization are proposed. Results The MRtrue determined on each of 30 stable intervals and the MRcsne during the immediately preceding hyperglycemic iteration differed, having medians with interquartile ranges 2.7 (1.2–3.7) and 3.2 (1.5–4.6) units/h, respectively. However, these estimates of MR were strongly correlated (R2 = 0.88). During hyperglycemia at 941 time points the IRnext assigned historically and the hypothetically calculated MRcsne-dependent IRnext differed, having medians with interquartile ranges 4.0 (3.0–6.0) and 4.6 (3.0–6.8) units/h, respectively, but these paired values again were correlated (R2 = 0.87). This article describes a programmable algorithm for intravenous insulin infusion. The fundamental equation of the algorithm gives the relationship among IR; the biologic parameter MR; and two variables expressing an instantaneous rate of change of BG, one of which must be zero at any given point in time and the other positive, negative, or zero, namely the rate of change of BG from below target (rate of ascent) and the rate of change of BG from above target (rate of descent). In addition to user-definable parameters, three special algorithm parameters discoverable in nature are described: the maximum rate of the spontaneous ascent of blood glucose during nonhypoglycemia, the glucose per daily dose of insulin exogenously mediated, and the MR at given patient time points. User-assignable parameters will facilitate adaptation to different patient populations. Conclusions An algorithm is described that estimates MR prior to the attainment of euglycemia and computes MR-dependent values for IRnext. Design features address glycemic variability, promote safety with respect to hypoglycemia, and define a method for specifying glycemic targets that are allowed to differ according to patient condition. PMID:20144334

Generalization of symmetric α-stable Lévy distributions for q >1

NASA Astrophysics Data System (ADS)

Umarov, Sabir; Tsallis, Constantino; Gell-Mann, Murray; Steinberg, Stanly

2010-03-01

The α-stable distributions introduced by Lévy play an important role in probabilistic theoretical studies and their various applications, e.g., in statistical physics, life sciences, and economics. In the present paper we study sequences of long-range dependent random variables whose distributions have asymptotic power-law decay, and which are called (q,α)-stable distributions. These sequences are generalizations of independent and identically distributed α-stable distributions and have not been previously studied. Long-range dependent (q,α)-stable distributions might arise in the description of anomalous processes in nonextensive statistical mechanics, cell biology, finance. The parameter q controls dependence. If q =1 then they are classical independent and identically distributed with α-stable Lévy distributions. In the present paper we establish basic properties of (q,α)-stable distributions and generalize the result of Umarov et al. [Milan J. Math. 76, 307 (2008)], where the particular case α =2,qɛ[1,3) was considered, to the whole range of stability and nonextensivity parameters α ɛ(0,2] and q ɛ[1,3), respectively. We also discuss possible further extensions of the results that we obtain and formulate some conjectures.

Functional Covariance Networks: Obtaining Resting-State Networks from Intersubject Variability

PubMed Central

Gohel, Suril; Di, Xin; Walter, Martin; Biswal, Bharat B.

2012-01-01

Abstract In this study, we investigate a new approach for examining the separation of the brain into resting-state networks (RSNs) on a group level using resting-state parameters (amplitude of low-frequency fluctuation [ALFF], fractional ALFF [fALFF], the Hurst exponent, and signal standard deviation). Spatial independent component analysis is used to reveal covariance patterns of the relevant resting-state parameters (not the time series) across subjects that are shown to be related to known, standard RSNs. As part of the analysis, nonresting state parameters are also investigated, such as mean of the blood oxygen level-dependent time series and gray matter volume from anatomical scans. We hypothesize that meaningful RSNs will primarily be elucidated by analysis of the resting-state functional connectivity (RSFC) parameters and not by non-RSFC parameters. First, this shows the presence of a common influence underlying individual RSFC networks revealed through low-frequency fluctation (LFF) parameter properties. Second, this suggests that the LFFs and RSFC networks have neurophysiological origins. Several of the components determined from resting-state parameters in this manner correlate strongly with known resting-state functional maps, and we term these “functional covariance networks”. PMID:22765879

Density regulation in Northeast Atlantic fish populations: Density dependence is stronger in recruitment than in somatic growth.

PubMed

Zimmermann, Fabian; Ricard, Daniel; Heino, Mikko

2018-05-01

Population regulation is a central concept in ecology, yet in many cases its presence and the underlying mechanisms are difficult to demonstrate. The current paradigm maintains that marine fish populations are predominantly regulated by density-dependent recruitment. While it is known that density-dependent somatic growth can be present too, its general importance remains unknown and most practical applications neglect it. This study aimed to close this gap by for the first time quantifying and comparing density dependence in growth and recruitment over a large set of fish populations. We fitted density-dependent models to time-series data on population size, recruitment and age-specific weight from commercially exploited fish populations in the Northeast Atlantic Ocean and the Baltic Sea. Data were standardized to enable a direct comparison within and among populations, and estimated parameters were used to quantify the impact of density regulation on population biomass. Statistically significant density dependence in recruitment was detected in a large proportion of populations (70%), whereas for density dependence in somatic growth the prevalence of density dependence depended heavily on the method (26% and 69%). Despite age-dependent variability, the density dependence in recruitment was consistently stronger among age groups and between alternative approaches that use weight-at-age or weight increments to assess growth. Estimates of density-dependent reduction in biomass underlined these results: 97% of populations with statistically significant parameters for growth and recruitment showed a larger impact of density-dependent recruitment on population biomass. The results reaffirm the importance of density-dependent recruitment in marine fishes, yet they also show that density dependence in somatic growth is not uncommon. Furthermore, the results are important from an applied perspective because density dependence in somatic growth affects productivity and catch composition, and therefore the benefits of maintaining fish populations at specific densities. © 2018 The Authors. Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.

Spatial variability of theaflavins and thearubigins fractions and their impact on black tea quality.

PubMed

Bhuyan, Lakshi Prasad; Borah, Paban; Sabhapondit, Santanu; Gogoi, Ramen; Bhattacharyya, Pradip

2015-12-01

The spatial distribution of theaflavin and thearubigin fractions and their impact on black tea quality were investigated using multivariate and geostatistics techniques. Black tea samples were collected from tea gardens of six geographical regions of Assam and West Bengal, India. Total theaflavin (TF) and its four fractions of upper Assam, south bank and North Bank teas were higher than the other regions. Simple theaflavin showed highest significant correlation with tasters' quality. Low molecular weight thearubigins of south bank and North Bank were significantly higher than other regions. Total thearubigin (TR) and its fractions revealed significant positive correlation with tasters' organoleptic valuations. Tea tasters' parameters were significantly and positively correlated with each other. The semivariogram for quality parameters were best represented by gaussian models. The nugget/sill ratio indicated a strong/moderate spatial dependence of the studied parameters. Spatial variation of tea quality parameters may be used for quality assessment in the tea growing areas of India.

A methodology for global-sensitivity analysis of time-dependent outputs in systems biology modelling.

PubMed

Sumner, T; Shephard, E; Bogle, I D L

2012-09-07

One of the main challenges in the development of mathematical and computational models of biological systems is the precise estimation of parameter values. Understanding the effects of uncertainties in parameter values on model behaviour is crucial to the successful use of these models. Global sensitivity analysis (SA) can be used to quantify the variability in model predictions resulting from the uncertainty in multiple parameters and to shed light on the biological mechanisms driving system behaviour. We present a new methodology for global SA in systems biology which is computationally efficient and can be used to identify the key parameters and their interactions which drive the dynamic behaviour of a complex biological model. The approach combines functional principal component analysis with established global SA techniques. The methodology is applied to a model of the insulin signalling pathway, defects of which are a major cause of type 2 diabetes and a number of key features of the system are identified.

Self consistent solution of the tJ model in the overdoped regime

NASA Astrophysics Data System (ADS)

Shastry, B. Sriram; Hansen, Daniel

2013-03-01

Detailed results from a recent microscopic theory of extremely correlated Fermi liquids, applied to the t-J model in two dimensions, are presented. The theory is to second order in a parameter λ, and is valid in the overdoped regime of the tJ model. The solution reported here is from Ref, where relevant equations given in Ref are self consistently solved for the square lattice. Thermodynamic variables and the resistivity are displayed at various densities and T for two sets of band parameters. The momentum distribution function and the renormalized electronic dispersion, its width and asymmetry are reported along principal directions of the zone. The optical conductivity is calculated. The electronic spectral function A (k , ω) probed in ARPES, is detailed with different elastic scattering parameters to account for the distinction between LASER and synchrotron ARPES. A high (binding) energy waterfall feature, sensitively dependent on the band hopping parameter t' is noted. This work was supported by DOE under Grant No. FG02-06ER46319.

Uncertainty in temperature-based determination of time of death

NASA Astrophysics Data System (ADS)

Weiser, Martin; Erdmann, Bodo; Schenkl, Sebastian; Muggenthaler, Holger; Hubig, Michael; Mall, Gita; Zachow, Stefan

2018-03-01

Temperature-based estimation of time of death (ToD) can be performed either with the help of simple phenomenological models of corpse cooling or with detailed mechanistic (thermodynamic) heat transfer models. The latter are much more complex, but allow a higher accuracy of ToD estimation as in principle all relevant cooling mechanisms can be taken into account. The potentially higher accuracy depends on the accuracy of tissue and environmental parameters as well as on the geometric resolution. We investigate the impact of parameter variations and geometry representation on the estimated ToD. For this, numerical simulation of analytic heat transport models is performed on a highly detailed 3D corpse model, that has been segmented and geometrically reconstructed from a computed tomography (CT) data set, differentiating various organs and tissue types. From that and prior information available on thermal parameters and their variability, we identify the most crucial parameters to measure or estimate, and obtain an a priori uncertainty quantification for the ToD.

Population density and climate shape early-life survival and recruitment in a long-lived pelagic seabird.

PubMed

Fay, Rémi; Weimerskirch, Henri; Delord, Karine; Barbraud, Christophe

2015-09-01

1. Our understanding of demographic processes is mainly based on analyses of traits from the adult component of populations. Early-life demographic traits are poorly known mainly for methodological reasons. Yet, survival of juvenile and immature individuals is critical for the recruitment into the population and thus for the whole population dynamic, especially for long-lived species. This bias currently restrains our ability to fully understand population dynamics of long-lived species and life-history theory. 2. The goal of this study was to estimate the early-life demographic parameters of a long-lived species with a long immature period (9-10 years), to test for sex and age effects on these parameters and to identify the environmental factors encountered during the period of immaturity that may influence survival and recruitment. 3. Using capture-mark-recapture multievent models allowing us to deal with uncertain and unobservable individual states, we analysed a long-term data set of wandering albatrosses to estimate both age- and sex-specific early-life survival and recruitment. We investigated environmental factors potentially driving these demographic traits using climatic and fisheries covariates and tested for density dependence. 4. Our study provides for the first time an estimate of annual survival during the first 2 years at sea for an albatross species (0·801 ± 0·014). Both age and sex affected early-life survival and recruitment processes of this long-lived seabird species. Early-life survival and recruitment were highly variable across years although the sensitivity of young birds to environmental variability decreased with age. Early-life survival was negatively associated with sea surface temperature, and recruitment rate was positively related to both Southern Annular Mode and sea surface temperature. We found strong evidence for density-dependent mortality of juveniles. Population size explained 41% of the variation of this parameter over the study period. 5. These results indicate that early-life survival and recruitment were strongly age and sex dependent in a dimorphic long-lived species. In addition, early-life demographic parameters were affected by natal environmental conditions and by environmental conditions faced during the period of immaturity. Finally, our results constitute one of the first demonstrations of density dependence on juvenile survival in seabirds, with major consequences for our understanding of population dynamics in seabirds. © 2015 The Authors. Journal of Animal Ecology © 2015 British Ecological Society.

Continuous-variable quantum teleportation with non-Gaussian resources

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

Dell'Anno, F.; Dipartimento di Fisica, Universita degli Studi di Salerno, Via S. Allende, I-84081 Baronissi; CNR-INFM Coherentia, Napoli, Italy and CNISM Unita di Salerno and INFN Sezione di Napoli, Gruppo Collegato di Salerno, Baronissi

2007-08-15

We investigate continuous variable quantum teleportation using non-Gaussian states of the radiation field as entangled resources. We compare the performance of different classes of degaussified resources, including two-mode photon-added and two-mode photon-subtracted squeezed states. We then introduce a class of two-mode squeezed Bell-like states with one-parameter dependence for optimization. These states interpolate between and include as subcases different classes of degaussified resources. We show that optimized squeezed Bell-like resources yield a remarkable improvement in the fidelity of teleportation both for coherent and nonclassical input states. The investigation reveals that the optimal non-Gaussian resources for continuous variable teleportation are those thatmore » most closely realize the simultaneous maximization of the content of entanglement, the degree of affinity with the two-mode squeezed vacuum, and the, suitably measured, amount of non-Gaussianity.« less

A default Bayesian hypothesis test for mediation.

PubMed

Nuijten, Michèle B; Wetzels, Ruud; Matzke, Dora; Dolan, Conor V; Wagenmakers, Eric-Jan

2015-03-01

In order to quantify the relationship between multiple variables, researchers often carry out a mediation analysis. In such an analysis, a mediator (e.g., knowledge of a healthy diet) transmits the effect from an independent variable (e.g., classroom instruction on a healthy diet) to a dependent variable (e.g., consumption of fruits and vegetables). Almost all mediation analyses in psychology use frequentist estimation and hypothesis-testing techniques. A recent exception is Yuan and MacKinnon (Psychological Methods, 14, 301-322, 2009), who outlined a Bayesian parameter estimation procedure for mediation analysis. Here we complete the Bayesian alternative to frequentist mediation analysis by specifying a default Bayesian hypothesis test based on the Jeffreys-Zellner-Siow approach. We further extend this default Bayesian test by allowing a comparison to directional or one-sided alternatives, using Markov chain Monte Carlo techniques implemented in JAGS. All Bayesian tests are implemented in the R package BayesMed (Nuijten, Wetzels, Matzke, Dolan, & Wagenmakers, 2014).

Optimized MPPT algorithm for boost converters taking into account the environmental variables

NASA Astrophysics Data System (ADS)

Petit, Pierre; Sawicki, Jean-Paul; Saint-Eve, Frédéric; Maufay, Fabrice; Aillerie, Michel

2016-07-01

This paper presents a study on the specific behavior of the Boost DC-DC converters generally used for powering conversion of PV panels connected to a HVDC (High Voltage Direct Current) Bus. It follows some works pointing out that converter MPPT (Maximum Power Point Tracker) is severely perturbed by output voltage variations due to physical dependency of parameters as the input voltage, the output voltage and the duty cycle of the PWM switching control of the MPPT. As a direct consequence many converters connected together on a same load perturb each other because of the output voltage variations induced by fluctuations on the HVDC bus essentially due to a not insignificant bus impedance. In this paper we show that it is possible to include an internal computed variable in charge to compensate local and external variations to take into account the environment variables.

Spatial generalised linear mixed models based on distances.

PubMed

Melo, Oscar O; Mateu, Jorge; Melo, Carlos E

2016-10-01

Risk models derived from environmental data have been widely shown to be effective in delineating geographical areas of risk because they are intuitively easy to understand. We present a new method based on distances, which allows the modelling of continuous and non-continuous random variables through distance-based spatial generalised linear mixed models. The parameters are estimated using Markov chain Monte Carlo maximum likelihood, which is a feasible and a useful technique. The proposed method depends on a detrending step built from continuous or categorical explanatory variables, or a mixture among them, by using an appropriate Euclidean distance. The method is illustrated through the analysis of the variation in the prevalence of Loa loa among a sample of village residents in Cameroon, where the explanatory variables included elevation, together with maximum normalised-difference vegetation index and the standard deviation of normalised-difference vegetation index calculated from repeated satellite scans over time. © The Author(s) 2013.

Realization of wide circadian variability by quantum dots-luminescent mesoporous silica-based white light-emitting diodes

NASA Astrophysics Data System (ADS)

Xie, Bin; Zhang, Jingjing; Chen, Wei; Hao, Junjie; Cheng, Yanhua; Hu, Run; Wu, Dan; Wang, Kai; Luo, Xiaobing

2017-10-01

Human comfort has become one of the most important criteria in modern lighting architecture. Here, we proposed a tuning strategy to enhance the non-image forming photobiological effect on the human circadian rhythm based on quantum-dots-converted white light-emitting diodes (QDs-WLEDs). We introduced the limiting variability of the circadian action factor (CAF), defined as the ratio of circadian efficiency and luminous efficiency of radiation. The CAF was deeply discussed and was found to be a function of constraining the color rendering index (CRI) and correlated color temperatures. The maximum CAF variability of QDs-WLEDs was found to be dependent on the QDs’ peak wavelength and full width at half maximum. With the optimized parameters, the packaging materials were synthesized and WLEDs were packaged. Experimental results show that at CRI > 90, the maximum CAF variability can be tuned by 3.83 times (from 0.251 at 2700 K to 0.961 at 6500 K), which implies that our approach could reduce the number of tunable channels, and could achieve wider CAF variability.

Relative efficiency and sample size for cluster randomized trials with variable cluster sizes.

PubMed

You, Zhiying; Williams, O Dale; Aban, Inmaculada; Kabagambe, Edmond Kato; Tiwari, Hemant K; Cutter, Gary

2011-02-01

The statistical power of cluster randomized trials depends on two sample size components, the number of clusters per group and the numbers of individuals within clusters (cluster size). Variable cluster sizes are common and this variation alone may have significant impact on study power. Previous approaches have taken this into account by either adjusting total sample size using a designated design effect or adjusting the number of clusters according to an assessment of the relative efficiency of unequal versus equal cluster sizes. This article defines a relative efficiency of unequal versus equal cluster sizes using noncentrality parameters, investigates properties of this measure, and proposes an approach for adjusting the required sample size accordingly. We focus on comparing two groups with normally distributed outcomes using t-test, and use the noncentrality parameter to define the relative efficiency of unequal versus equal cluster sizes and show that statistical power depends only on this parameter for a given number of clusters. We calculate the sample size required for an unequal cluster sizes trial to have the same power as one with equal cluster sizes. Relative efficiency based on the noncentrality parameter is straightforward to calculate and easy to interpret. It connects the required mean cluster size directly to the required sample size with equal cluster sizes. Consequently, our approach first determines the sample size requirements with equal cluster sizes for a pre-specified study power and then calculates the required mean cluster size while keeping the number of clusters unchanged. Our approach allows adjustment in mean cluster size alone or simultaneous adjustment in mean cluster size and number of clusters, and is a flexible alternative to and a useful complement to existing methods. Comparison indicated that we have defined a relative efficiency that is greater than the relative efficiency in the literature under some conditions. Our measure of relative efficiency might be less than the measure in the literature under some conditions, underestimating the relative efficiency. The relative efficiency of unequal versus equal cluster sizes defined using the noncentrality parameter suggests a sample size approach that is a flexible alternative and a useful complement to existing methods.

A Hardware Model Validation Tool for Use in Complex Space Systems

NASA Technical Reports Server (NTRS)

Davies, Misty Dawn; Gundy-Burlet, Karen L.; Limes, Gregory L.

2010-01-01

One of the many technological hurdles that must be overcome in future missions is the challenge of validating as-built systems against the models used for design. We propose a technique composed of intelligent parameter exploration in concert with automated failure analysis as a scalable method for the validation of complex space systems. The technique is impervious to discontinuities and linear dependencies in the data, and can handle dimensionalities consisting of hundreds of variables over tens of thousands of experiments.

Quantum corrections to quasi-periodic solution of Sine-Gordon model and periodic solution of phi4 model

NASA Astrophysics Data System (ADS)

Kwiatkowski, G.; Leble, S.

2014-03-01

Analytical form of quantum corrections to quasi-periodic solution of Sine-Gordon model and periodic solution of phi4 model is obtained through zeta function regularisation with account of all rest variables of a d-dimensional theory. Qualitative dependence of quantum corrections on parameters of the classical systems is also evaluated for a much broader class of potentials u(x) = b2f(bx) + C with b and C as arbitrary real constants.

Efficient Estimation of Mutual Information for Strongly Dependent Variables

DTIC Science & Technology

2015-05-11

the two possibilities: for a fixed dimension d and near- est neighbor parameter k, we find a constant ↵ k,d , such that if V̄ (i)/V (i) < ↵ k,d , then...also compare the results to several baseline estima- tors: KSG (Kraskov et al., 2004), generalized near- est neighbor graph (GNN) (Pál et al., 2010...Amaury Lendasse, and Francesco Corona. A boundary corrected expansion of the moments of near- est neighbor distributions. Random Struct. Algorithms

An improved rainfall disaggregation technique for GCMs

NASA Astrophysics Data System (ADS)

Onof, C.; Mackay, N. G.; Oh, L.; Wheater, H. S.

1998-08-01

Meteorological models represent rainfall as a mean value for a grid square so that when the latter is large, a disaggregation scheme is required to represent the spatial variability of rainfall. In general circulation models (GCMs) this is based on an assumption of exponentiality of rainfall intensities and a fixed value of areal rainfall coverage, dependent on rainfall type. This paper examines these two assumptions on the basis of U.K. and U.S. radar data. Firstly, the coverage of an area is strongly dependent on its size, and this dependence exhibits a scaling law over a range of sizes. Secondly, the coverage is, of course, dependent on the resolution at which it is measured, although this dependence is weak at high resolutions. Thirdly, the time series of rainfall coverages has a long-tailed autocorrelation function which is comparable to that of the mean areal rainfalls. It is therefore possible to reproduce much of the temporal dependence of coverages by using a regression of the log of the mean rainfall on the log of the coverage. The exponential assumption is satisfactory in many cases but not able to reproduce some of the long-tailed dependence of some intensity distributions. Gamma and lognormal distributions provide a better fit in these cases, but they have their shortcomings and require a second parameter. An improved disaggregation scheme for GCMs is proposed which incorporates the previous findings to allow the coverage to be obtained for any area and any mean rainfall intensity. The parameters required are given and some of their seasonal behavior is analyzed.

Van’t Hoff global analyses of variable temperature isothermal titration calorimetry data

PubMed Central

Freiburger, Lee A.; Auclair, Karine; Mittermaier, Anthony K.

2016-01-01

Isothermal titration calorimetry (ITC) can provide detailed information on the thermodynamics of biomolecular interactions in the form of equilibrium constants, KA, and enthalpy changes, ΔHA. A powerful application of this technique involves analyzing the temperature dependences of ITC-derived KA and ΔHA values to gain insight into thermodynamic linkage between binding and additional equilibria, such as protein folding. We recently developed a general method for global analysis of variable temperature ITC data that significantly improves the accuracy of extracted thermodynamic parameters and requires no prior knowledge of the coupled equilibria. Here we report detailed validation of this method using Monte Carlo simulations and an application to study coupled folding and binding in an aminoglycoside acetyltransferase enzyme. PMID:28018008

Ultrastructure of Dendritic Spines: Correlation Between Synaptic and Spine Morphologies

PubMed Central

Arellano, Jon I.; Benavides-Piccione, Ruth; DeFelipe, Javier; Yuste, Rafael

2007-01-01

Dendritic spines are critical elements of cortical circuits, since they establish most excitatory synapses. Recent studies have reported correlations between morphological and functional parameters of spines. Specifically, the spine head volume is correlated with the area of the postsynaptic density (PSD), the number of postsynaptic receptors and the ready-releasable pool of transmitter, whereas the length of the spine neck is proportional to the degree of biochemical and electrical isolation of the spine from its parent dendrite. Therefore, the morphology of a spine could determine its synaptic strength and learning rules. To better understand the natural variability of neocortical spine morphologies, we used a combination of gold-toned Golgi impregnations and serial thin-section electron microscopy and performed three-dimensional reconstructions of spines from layer 2/3 pyramidal cells from mouse visual cortex. We characterized the structure and synaptic features of 144 completed reconstructed spines, and analyzed their morphologies according to their positions. For all morphological parameters analyzed, spines exhibited a continuum of variability, without clearly distinguishable subtypes of spines or clear dependence of their morphologies on their distance to the soma. On average, the spine head volume was correlated strongly with PSD area and weakly with neck diameter, but not with neck length. The large morphological diversity suggests an equally large variability of synaptic strength and learning rules. PMID:18982124

Analysis of pelvic rotation on the standard hip ventrodorsal extended radiographic view.

PubMed

Martins, João; Colaço, Bruno J; Ferreira, António J; Ginja, Mário M

2016-01-01

To study the symmetry of the iliac horizontal diameter (IHD) maximum obturator foramen width (OFW), ischiatic femoral overlap (IFO), pelvic horizontal radius (PHR), femoral head diameter (FHD), and obturator foramen area (OFA) parameters in the normal hip extended radiographic view and to evaluate the correlation of pelvic rotation with the magnitude of asymmetry of these parameters. Nine canine cadavers from adult, large and giant breeds were radiographed in standard hip extended views and with 2°, 4° and 6° degrees of rotation. The variables IHD, OFW, IFO, PHR, FHD, and OFA were analysed in radiographs. The IHD measurements exhibited repeatability, bilateral symmetry and 95% of confidence interval of asymmetry in different pelvic rotations without superposition (p <0.05); OFW and IFO exhibited repeatability, bilateral symmetry and a small superposition in 95% of confidence interval of asymmetry according different pelvic rotations; PHR, FHD and OFA exhibited repeatability, bilateral symmetry and unacceptable superposition in 95% of confidence interval of asymmetry depending on pelvic rotation. The IHD is the recommended variable and OFW is an acceptable variable in order to evaluate slight pelvic rotation. The data may be used in qualitative analyses of hip extended radiographic views. In the future, complementary studies should be performed to evaluate the impact of degree of pelvic rotation on the hip dysplasia score.

Breath biomarkers for lung cancer detection and assessment of smoking related effects--confounding variables, influence of normalization and statistical algorithms.

PubMed

Kischkel, Sabine; Miekisch, Wolfram; Sawacki, Annika; Straker, Eva M; Trefz, Phillip; Amann, Anton; Schubert, Jochen K

2010-11-11

Up to now, none of the breath biomarkers or marker sets proposed for cancer recognition has reached clinical relevance. Possible reasons are the lack of standardized methods of sampling, analysis and data processing and effects of environmental contaminants. Concentration profiles of endogenous and exogenous breath markers were determined in exhaled breath of 31 lung cancer patients, 31 smokers and 31 healthy controls by means of SPME-GC-MS. Different correcting and normalization algorithms and a principal component analysis were applied to the data. Differences of exhalation profiles in cancer and non-cancer patients did not persist if physiology and confounding variables were taken into account. Smoking history, inspired substance concentrations, age and gender were recognized as the most important confounding variables. Normalization onto PCO2 or BSA or correction for inspired concentrations only partially solved the problem. In contrast, previous smoking behaviour could be recognized unequivocally. Exhaled substance concentrations may depend on a variety of parameters other than the disease under investigation. Normalization and correcting parameters have to be chosen with care as compensating effects may be different from one substance to the other. Only well-founded biomarker identification, normalization and data processing will provide clinically relevant information from breath analysis. 2010 Elsevier B.V. All rights reserved.

Local expansion flows of galaxies: quantifying acceleration effect of dark energy

NASA Astrophysics Data System (ADS)

Chernin, A. D.; Teerikorpi, P.

2013-08-01

The nearest expansion flow of galaxies observed around the Local group is studied as an archetypical example of the newly discovered local expansion flows around groups and clusters of galaxies in the nearby Universe. The flow is accelerating due to the antigravity produced by the universal dark energy background. We introduce a new acceleration measure of the flow which is the dimensionless ``acceleration parameter" Q (x) = x - x-2 depending on the normalized distance x only. The parameter is zero at the zero-gravity distance x = 1, and Q(x) ∝ x, when x ≫ 1. At the distance x = 3, the parameter Q = 2.9. Since the expansion flows have a self-similar structure in normalized variables, we expect that the result is valid as well for all the other expansion flows around groups and clusters of galaxies on the spatial scales from ˜ 1 to ˜ 10 Mpc everywhere in the Universe.

An open circuit voltage decay system for performing injection dependent lifetime spectroscopy

NASA Astrophysics Data System (ADS)

Lacouture, Shelby; Schrock, James; Hirsch, Emily; Bayne, Stephen; O'Brien, Heather; Ogunniyi, Aderinto A.

2017-09-01

Of all of the material parameters associated with a semiconductor, the carrier lifetime is by far the most complex and dynamic, being a function of the dominant recombination mechanism, the equilibrium number of carriers, the perturbations in carriers (e.g., carrier injection), and the temperature, to name the most prominent variables. The carrier lifetime is one of the most important parameters in bipolar devices, greatly affecting conductivity modulation, on-state voltage, and reverse recovery. Carrier lifetime is also a useful metric for device fabrication process control and material quality. As it is such a dynamic quantity, carrier lifetime cannot be quoted in a general range such as mobility; it must be measured. The following describes a stand-alone, wide-injection range open circuit voltage decay system with unique lifetime extraction algorithms. The system is initially used along with various lifetime spectroscopy techniques to extract fundamental recombination parameters from a commercial high-voltage PIN diode.

Numerical Simulation and Quantitative Uncertainty Assessment of Microchannel Flow

NASA Astrophysics Data System (ADS)

Debusschere, Bert; Najm, Habib; Knio, Omar; Matta, Alain; Ghanem, Roger; Le Maitre, Olivier

2002-11-01

This study investigates the effect of uncertainty in physical model parameters on computed electrokinetic flow of proteins in a microchannel with a potassium phosphate buffer. The coupled momentum, species transport, and electrostatic field equations give a detailed representation of electroosmotic and pressure-driven flow, including sample dispersion mechanisms. The chemistry model accounts for pH-dependent protein labeling reactions as well as detailed buffer electrochemistry in a mixed finite-rate/equilibrium formulation. To quantify uncertainty, the governing equations are reformulated using a pseudo-spectral stochastic methodology, which uses polynomial chaos expansions to describe uncertain/stochastic model parameters, boundary conditions, and flow quantities. Integration of the resulting equations for the spectral mode strengths gives the evolution of all stochastic modes for all variables. Results show the spatiotemporal evolution of uncertainties in predicted quantities and highlight the dominant parameters contributing to these uncertainties during various flow phases. This work is supported by DARPA.

Mixed convection boundary layer flow over a moving vertical flat plate in an external fluid flow with viscous dissipation effect.

PubMed

Bachok, Norfifah; Ishak, Anuar; Pop, Ioan

2013-01-01

The steady boundary layer flow of a viscous and incompressible fluid over a moving vertical flat plate in an external moving fluid with viscous dissipation is theoretically investigated. Using appropriate similarity variables, the governing system of partial differential equations is transformed into a system of ordinary (similarity) differential equations, which is then solved numerically using a Maple software. Results for the skin friction or shear stress coefficient, local Nusselt number, velocity and temperature profiles are presented for different values of the governing parameters. It is found that the set of the similarity equations has unique solutions, dual solutions or no solutions, depending on the values of the mixed convection parameter, the velocity ratio parameter and the Eckert number. The Eckert number significantly affects the surface shear stress as well as the heat transfer rate at the surface.

Magnon modes and magnon-vortex scattering in two-dimensional easy-plane ferromagnets

NASA Astrophysics Data System (ADS)

Ivanov, B. A.; Schnitzer, H. J.; Mertens, F. G.; Wysin, G. M.

1998-10-01

We calculate the magnon modes in the presence of a vortex on a circular system, combining analytical calculations in the continuum limit with a numerical diagonalization of the discrete system. The magnon modes are expressed by the S matrix for magnon-vortex scattering, as a function of the parameters and the size of the system and for different boundary conditions. Certain quasilocal translational modes are identified with the frequencies which appear in the trajectory X-->(t) of the vortex center in recent molecular dynamics simulations of the full many-spin model. Using these quasilocal modes we calculate the two parameters of a third-order equation of motion for X-->(t). This equation was recently derived by a collective variable theory and describes very well the trajectories observed in the simulations. Both parameters, the vortex mass and the factor in front of X-->⃛, depend strongly on the boundary conditions.

Applying a particle filtering technique for canola crop growth stage estimation in Canada

NASA Astrophysics Data System (ADS)

Sinha, Abhijit; Tan, Weikai; Li, Yifeng; McNairn, Heather; Jiao, Xianfeng; Hosseini, Mehdi

2017-10-01

Accurate crop growth stage estimation is important in precision agriculture as it facilitates improved crop management, pest and disease mitigation and resource planning. Earth observation imagery, specifically Synthetic Aperture Radar (SAR) data, can provide field level growth estimates while covering regional scales. In this paper, RADARSAT-2 quad polarization and TerraSAR-X dual polarization SAR data and ground truth growth stage data are used to model the influence of canola growth stages on SAR imagery extracted parameters. The details of the growth stage modeling work are provided, including a) the development of a new crop growth stage indicator that is continuous and suitable as the state variable in the dynamic estimation procedure; b) a selection procedure for SAR polarimetric parameters that is sensitive to both linear and nonlinear dependency between variables; and c) procedures for compensation of SAR polarimetric parameters for different beam modes. The data was collected over three crop growth seasons in Manitoba, Canada, and the growth model provides the foundation of a novel dynamic filtering framework for real-time estimation of canola growth stages using the multi-sensor and multi-mode SAR data. A description of the dynamic filtering framework that uses particle filter as the estimator is also provided in this paper.

Analytical Modelling and Optimization of the Temperature-Dependent Dynamic Mechanical Properties of Fused Deposition Fabricated Parts Made of PC-ABS.

PubMed

Mohamed, Omar Ahmed; Masood, Syed Hasan; Bhowmik, Jahar Lal

2016-11-04

Fused deposition modeling (FDM) additive manufacturing has been intensively used for many industrial applications due to its attractive advantages over traditional manufacturing processes. The process parameters used in FDM have significant influence on the part quality and its properties. This process produces the plastic part through complex mechanisms and it involves complex relationships between the manufacturing conditions and the quality of the processed part. In the present study, the influence of multi-level manufacturing parameters on the temperature-dependent dynamic mechanical properties of FDM processed parts was investigated using IV-optimality response surface methodology (RSM) and multilayer feed-forward neural networks (MFNNs). The process parameters considered for optimization and investigation are slice thickness, raster to raster air gap, deposition angle, part print direction, bead width, and number of perimeters. Storage compliance and loss compliance were considered as response variables. The effect of each process parameter was investigated using developed regression models and multiple regression analysis. The surface characteristics are studied using scanning electron microscope (SEM). Furthermore, performance of optimum conditions was determined and validated by conducting confirmation experiment. The comparison between the experimental values and the predicted values by IV-Optimal RSM and MFNN was conducted for each experimental run and results indicate that the MFNN provides better predictions than IV-Optimal RSM.

Analytical Modelling and Optimization of the Temperature-Dependent Dynamic Mechanical Properties of Fused Deposition Fabricated Parts Made of PC-ABS

PubMed Central

Mohamed, Omar Ahmed; Masood, Syed Hasan; Bhowmik, Jahar Lal

2016-01-01

Fused deposition modeling (FDM) additive manufacturing has been intensively used for many industrial applications due to its attractive advantages over traditional manufacturing processes. The process parameters used in FDM have significant influence on the part quality and its properties. This process produces the plastic part through complex mechanisms and it involves complex relationships between the manufacturing conditions and the quality of the processed part. In the present study, the influence of multi-level manufacturing parameters on the temperature-dependent dynamic mechanical properties of FDM processed parts was investigated using IV-optimality response surface methodology (RSM) and multilayer feed-forward neural networks (MFNNs). The process parameters considered for optimization and investigation are slice thickness, raster to raster air gap, deposition angle, part print direction, bead width, and number of perimeters. Storage compliance and loss compliance were considered as response variables. The effect of each process parameter was investigated using developed regression models and multiple regression analysis. The surface characteristics are studied using scanning electron microscope (SEM). Furthermore, performance of optimum conditions was determined and validated by conducting confirmation experiment. The comparison between the experimental values and the predicted values by IV-Optimal RSM and MFNN was conducted for each experimental run and results indicate that the MFNN provides better predictions than IV-Optimal RSM. PMID:28774019